Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
presents approximate methods and discusses their applicability. We then discuss the problem of obtaining traffic characteristic values for a connection that has crossed a series of switching nodes. This problem is particularly relevant for the traffic contract components corresponding to ICIs...... (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...... 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...
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.
Effects of model schematisation, geometry and parameter values on urban flood modelling.
Vojinovic, Z; Seyoum, S D; Mwalwaka, J M; Price, R K
2011-01-01
One-dimensional (1D) hydrodynamic models have been used as a standard industry practice for urban flood modelling work for many years. More recently, however, model formulations have included a 1D representation of the main channels and a 2D representation of the floodplains. Since the physical process of describing exchanges of flows with the floodplains can be represented in different ways, the predictive capability of different modelling approaches can also vary. The present paper explores effects of some of the issues that concern urban flood modelling work. Impacts from applying different model schematisation, geometry and parameter values were investigated. The study has mainly focussed on exploring how different Digital Terrain Model (DTM) resolution, presence of different features on DTM such as roads and building structures and different friction coefficients affect the simulation results. Practical implications of these issues are analysed and illustrated in a case study from St Maarten, N.A. The results from this study aim to provide users of numerical models with information that can be used in the analyses of flooding processes in urban areas.
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.
Recommended Parameter Values for INEEL Subsurface Disposal Area Source Release Modeling
Energy Technology Data Exchange (ETDEWEB)
Riley, Robert G.; Lopresti, Charles A.
2004-06-23
The purpose of this report is to summarize 1) associated information and values for key release model parameters (i.e., best estimate, minimum and maximum) obtained where possible from published experimental data, 2) a structure for selection of sensitivity tests cases that can be used to identify test cases, and 3) recommended test cases for selected contaminants of potential concern to assess remedy effectiveness against a no-treatment base case.
Theoretical values of various parameters in the Gummel-Poon model of a bipolar junction transistor
Benumof, R.; Zoutendyk, J.
1986-01-01
Various parameters in the Gummel-Poon model of a bipolar junction transistor are expressed in terms of the basic structure of a transistor. A consistent theoretical approach is used which facilitates an understanding of the foundations and limitations of the derived formulas. The results enable one to predict how changes in the geometry and composition of a transistor would affect performance.
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.
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.
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
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
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Huth, N.; Marin, F.; Martiné, J.-F.
2014-01-01
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, a 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 sugar cane 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
Bertram, C D; Macaskill, C; Davis, M J; Moore, J E
2014-04-01
Our published model of a lymphatic vessel consisting of multiple actively contracting segments between non-return valves has been further developed by the incorporation of properties derived from observations and measurements of rat mesenteric vessels. These included (1) a refractory period between contractions, (2) a highly nonlinear form for the passive part of the pressure-diameter relationship, (3) hysteretic and transmural-pressure-dependent valve opening and closing pressure thresholds and (4) dependence of active tension on muscle length as reflected in local diameter. Experimentally, lymphatic valves are known to be biased to stay open. In consequence, in the improved model, vessel pumping of fluid suffers losses by regurgitation, and valve closure is dependent on backflow first causing an adverse valve pressure drop sufficient to reach the closure threshold. The assumed resistance of an open valve therefore becomes a critical parameter, and experiments to measure this quantity are reported here. However, incorporating this parameter value, along with other parameter values based on existing measurements, led to ineffective pumping. It is argued that the published measurements of valve-closing pressure threshold overestimate this quantity owing to neglect of micro-pipette resistance. An estimate is made of the extent of the possible resulting error. Correcting by this amount, the pumping performance is improved, but still very inefficient unless the open-valve resistance is also increased beyond the measured level. Arguments are given as to why this is justified, and other areas where experimental data are lacking are identified. The model is capable of future adaptation as new experimental data appear.
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.
Matteucci, M.; S. Mignani, Prof.; Veldkamp, Bernard P.
2012-01-01
In testing, item response theory models are widely used in order to estimate item parameters and individual abilities. However, even unidimensional models require a considerable sample size so that all parameters can be estimated precisely. The introduction of empirical prior information about
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...
Mass dependence of optical potential parameter values
International Nuclear Information System (INIS)
Zarubin, P.P.
1987-01-01
The optical potential (OP) parameter values extracted from analysis of elastic and inelastic proton scattering cross sections with E p ∼ 6 MeV on even-even nuclei of average atomic weight in two regions A:46-70 and 100-110 are presented. All experimental data on proton scattering cross sections analysed are obtained at the U-120 cyclotron and have been published before. Analysis of proton scattering cross sections obtained by calculating scattering cross sections through the compound nucleus from the experimental scattering cross sections has been carried out in the framework of the optical model, the distorted wave and coupled channel methods. New values of some OP parameters leading to the better in comparison with standard values description of experimental elastic and inelastic proton scattering cross sections with E p ∼ 6 MeV on nuclei with the average atomic weight are obtained. Account of channel coupling during proton scattering changes considerably the W and P w values. Increase of these values in region A=50-58 and ∼100 especially presise in calculations according to the coupled channel theory gives evidence about reality of anomalies in values W discussed earlier
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)
Choubert, Jean-Marc; Stricker, Anne-Emmanuelle; Marquot, Aurélien; Racault, Yvan; Gillot, Sylvie; Héduit, Alain
2009-01-01
The Activated Sludge Model number 1 (ASM1) is the main model used in simulation projects focusing on nitrogen removal. Recent laboratory-scale studies have found that the default values given 20 years ago for the decay rate of nitrifiers and for the heterotrophic biomass yield in anoxic conditions were inadequate. To verify the relevance of the revised parameter values at full scale, a series of simulations were carried out with ASM1 using the original and updated set of parameters at 20 degrees C and 10 degrees C. The simulation results were compared with data collected at 13 full-scale nitrifying-denitrifying municipal treatment plants. This work shows that simulations using the original ASM1 default parameters tend to overpredict the nitrification rate and underpredict the denitrification rate. The updated set of parameters allows more realistic predictions over a wide range of operating conditions.
International Nuclear Information System (INIS)
Tofts, Paul S.; Cutajar, Marica; Mendichovszky, Iosif A.; Peters, A.M.; Gordon, Isky
2012-01-01
To model the uptake phase of T 1 -weighted DCE-MRI data in normal kidneys and to demonstrate that the fitted physiological parameters correlate with published normal values. The model incorporates delay and broadening of the arterial vascular peak as it appears in the capillary bed, two distinct compartments for renal intravascular and extravascular Gd tracer, and uses a small-vessel haematocrit value of 24%. Four physiological parameters can be estimated: regional filtration K trans (ml min -1 [ml tissue ] -1 ), perfusion F (ml min -1 [100 ml tissue ] -1 ), blood volume v b (%) and mean residence time MRT (s). From these are found the filtration fraction (FF; %) and total GFR (ml min -1 ). Fifteen healthy volunteers were imaged twice using oblique coronal slices every 2.5 s to determine the reproducibility. Using parenchymal ROIs, group mean values for renal biomarkers all agreed with published values: K trans : 0.25; F: 219; v b : 34; MRT: 5.5; FF: 15; GFR: 115. Nominally cortical ROIs consistently underestimated total filtration (by ∝ 50%). Reproducibility was 7-18%. Sensitivity analysis showed that these fitted parameters are most vulnerable to errors in the fixed parameters kidney T 1 , flip angle, haematocrit and relaxivity. These renal biomarkers can potentially measure renal physiology in diagnosis and treatment. circle Dynamic contrast-enhanced magnetic resonance imaging can measure renal function. circle Filtration and perfusion values in healthy volunteers agree with published normal values. circle Precision measured in healthy volunteers is between 7 and 15%. (orig.)
Belykh, Evgenii; Krutko, Alexander V; Baykov, Evgenii S; Giers, Morgan B; Preul, Mark C; Byvaltsev, Vadim A
2017-03-01
Recurrence of lumbar disc herniation (rLDH) is one of the unfavorable outcomes after microdiscectomy. Prediction of the patient population with increased risk of rLDH is important because patients may benefit from preventive measures or other surgical options. The study assessed preoperative factors associated with rLDH after microdiscectomy and created a mathematical model for estimation of chances for rLDH. This is a retrospective case-control study. The study includes patients who underwent microdiscectomy for LDH. Lumbar disc herniation recurrence was determined using magnetic resonance imaging. The study included 350 patients with LDH and a minimum of 3 years of follow-up. Patients underwent microdiscectomy for LDH at the L4-L5 and L5-S1 levels from 2008 to 2012. Patients were divided into two groups to identify predictors of recurrence: those who developed rLDH (n=50) within 3 years and those who did not develop rLDH (n=300) within the same follow-up period. Multivariate analysis was performed using patient baseline clinical and radiography data. Non-linear, multivariate, logistic regression analysis was used to build a predictive model. Recurrence of LDH occurred within 1 to 48 months after microdiscectomy. Preoperatively, patients who developed rLDH were smokers (70% vs. 27%, pnon-linear modeling allowed for more accurate prediction of rLDH (90% correct prediction of rLDH; 99% correct prediction of no rLDH) than other univariate logit models. Preoperative radiographic parameters in patients with LDH can be used to assess the risk of recurrence after microdiscectomy. The multifactorial non-linear model provided more accurate rLDH probability estimation than the univariate analyses. The software developed from this model may be implemented during patient counseling or decision making when choosing the type of primary surgery for LDH. Copyright © 2016 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Tofts, Paul S. [Brighton and Sussex Medical School, Falmer, Sussex (United Kingdom); UCL Institute of Neurology, London (United Kingdom); Cutajar, Marica [Brighton and Sussex Medical School, Falmer, Sussex (United Kingdom); UCL Institute of Child Health, London (United Kingdom); Mendichovszky, Iosif A. [University of Manchester, Imaging Science and Biomedical Engineering, Manchester (United Kingdom); Peters, A.M. [Brighton and Sussex Medical School, Falmer, Sussex (United Kingdom); Gordon, Isky [UCL Institute of Child Health, London (United Kingdom)
2012-06-15
To model the uptake phase of T{sub 1}-weighted DCE-MRI data in normal kidneys and to demonstrate that the fitted physiological parameters correlate with published normal values. The model incorporates delay and broadening of the arterial vascular peak as it appears in the capillary bed, two distinct compartments for renal intravascular and extravascular Gd tracer, and uses a small-vessel haematocrit value of 24%. Four physiological parameters can be estimated: regional filtration K{sup trans} (ml min {sup -1} [ml tissue ]{sup -1}), perfusion F (ml min {sup -1} [100 ml tissue ]{sup -1}), blood volume v{sub b} (%) and mean residence time MRT (s). From these are found the filtration fraction (FF; %) and total GFR (ml min {sup -1}). Fifteen healthy volunteers were imaged twice using oblique coronal slices every 2.5 s to determine the reproducibility. Using parenchymal ROIs, group mean values for renal biomarkers all agreed with published values: K{sup trans}: 0.25; F: 219; v{sub b}: 34; MRT: 5.5; FF: 15; GFR: 115. Nominally cortical ROIs consistently underestimated total filtration (by {proportional_to} 50%). Reproducibility was 7-18%. Sensitivity analysis showed that these fitted parameters are most vulnerable to errors in the fixed parameters kidney T{sub 1}, flip angle, haematocrit and relaxivity. These renal biomarkers can potentially measure renal physiology in diagnosis and treatment. circle Dynamic contrast-enhanced magnetic resonance imaging can measure renal function. circle Filtration and perfusion values in healthy volunteers agree with published normal values. circle Precision measured in healthy volunteers is between 7 and 15%. (orig.)
Linking Item Response Model Parameters.
van der Linden, Wim J; Barrett, Michelle D
2016-09-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of test equating scores on different test forms. This paper argues, however, that the use of item response models does not require any test score equating. Instead, it involves the necessity of parameter linking due to a fundamental problem inherent in the formal nature of these models-their general lack of identifiability. More specifically, item response model parameters need to be linked to adjust for the different effects of the identifiability restrictions used in separate item calibrations. Our main theorems characterize the formal nature of these linking functions for monotone, continuous response models, derive their specific shapes for different parameterizations of the 3PL model, and show how to identify them from the parameter values of the common items or persons in different linking designs.
You, Benoit; Colomban, Olivier; Heywood, Mark; Lee, Chee; Davy, Margaret; Reed, Nicholas; Pignata, Sandro; Varsellona, Nenzi; Emons, Günter; Rehman, Khalid; Steffensen, Karina Dahl; Reinthaller, Alexander; Pujade-Lauraine, Eric; Oza, Amit
2013-08-01
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. Data from CALYPSO phase III trial comparing 2 carboplatin-based regimens in ROC patients were analyzed. Based on population kinetic approach, serum [CA-125] concentration-time profiles during first 50 treatment days were fit to a semi-mechanistic model with following parameters: "d[CA-125]/dt=(KPROD∗exp (BETA∗t))∗Effect-KELIM∗[CA-125]" with time, t; tumor growth rate, BETA; CA-125 tumor production rate, KPROD; CA-125 elimination rate, KELIM and K-dependent treatment indirect Effect. The predictive values of kinetic parameters were tested regarding progression-free survival (PFS) against other reported prognostic factors. Individual CA-125 kinetic profiles from 895 patients were modeled. Three kinetic parameters categorized by medians had predictive values using univariate analyses: K; KPROD and KELIM (all PCA-125 response (favoring carboplatin-paclitaxel arm), treatment arm, platinum free-interval, measurable lesions and KELIM (HR=0.53; 95% CI 0.45-0.61; PCA-125 kinetics in ROC patients enables understanding of the time-change components during chemotherapy. The contradictory surrogacy of GCIG-defined CA-125 response was confirmed. The modeled CA-125 elimination rate KELIM, potentially assessable in routine, may have promising predictive value regarding PFS. Further validation of this predictive marker is warranted. Copyright © 2013 Elsevier Inc. All rights reserved.
Response model parameter linking
Barrett, M.L.D.
2015-01-01
With a few exceptions, the problem of linking item response model parameters from different item calibrations has been conceptualized as an instance of the problem of equating observed scores on different test forms. This thesis argues, however, that the use of item response models does not require
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
Unraveling the parameters of the value created by design: Toward a 'value added by design' framework
Vijfeyken, Elena; Cools, Martine; Nauwelaerts, Ysabel
2011-01-01
This paper studies the parameters that capture the value added by design. Starting from an extensive review of the existing literature, we carried out multi-case research, in order to develop an overall model for unraveling the added value of design in an organizational context. Current literature mainly focuses on financial value and is thereby unclear about other quantitative as well as qualitative aspects of value to which design contributes. We find that added value of design is mainly vi...
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.
DEFF Research Database (Denmark)
Dahl Steffensen, Karina
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...... constant (BETA); CA 125 tumor production (KIN); tumor decay rate constant (KOUT) and treatment indirect effect (Emax relationships with A and A50) “d[CA125]/dt=(KIN* exp [BETA*t]) * (1 - [A/{A+A50}]) – KOUT * (CA125)” where t is time. The predictive values of KIN; KOUT; BETA and A50 estimated during...
Application of lumped-parameter models
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
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. Subsequently, the assembly of the dynamic stiffness matrix for the foundation is considered, and the solution for obtaining the steady state response, when using lumped-parameter models is given. (au)
PhyloPars: estimation of missing parameter values using phylogeny.
Bruggeman, Jorn; Heringa, Jaap; Brandt, Bernd W
2009-07-01
A wealth of information on metabolic parameters of a species can be inferred from observations on species that are phylogenetically related. Phylogeny-based information can complement direct empirical evidence, and is particularly valuable if experiments on the species of interest are not feasible. The PhyloPars web server provides a statistically consistent method that combines an incomplete set of empirical observations with the species phylogeny to produce a complete set of parameter estimates for all species. It builds upon a state-of-the-art evolutionary model, extended with the ability to handle missing data. The resulting approach makes optimal use of all available information to produce estimates that can be an order of magnitude more accurate than ad-hoc alternatives. Uploading a phylogeny and incomplete feature matrix suffices to obtain estimates of all missing values, along with a measure of certainty. Real-time cross-validation provides further insight in the accuracy and bias expected for estimated values. The server allows for easy, efficient estimation of metabolic parameters, which can benefit a wide range of fields including systems biology and ecology. PhyloPars is available at: http://www.ibi.vu.nl/programs/phylopars/.
Estimation of Parameters of the Beta-Extreme Value Distribution
Directory of Open Access Journals (Sweden)
Zafar Iqbal
2008-09-01
Full Text Available In this research paper The Beta Extreme Value Type (III distribution which is developed by Zafar and Aleem (2007 is considered and parameters are estimated by using moments of the Beta-Extreme Value (Type III Distribution when the parameters ‘m’ & ‘n’ are real and moments of the Beta-Extreme Value (Type III Distribution when the parameters ‘m��� & ‘n’ are integers and then a Comparison between rth moments about origin when parameters are ‘m’ & ‘n’ are real and when parameters are ‘m’ & ‘n’ are integers. At the end second method, method of Maximum Likelihood is used to estimate the unknown parameters of the Beta Extreme Value Type (III distribution.
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......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...
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
Energy Technology Data Exchange (ETDEWEB)
Treml, C. A. (Christine 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.
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)
Modelling and parameter estimation of dynamic systems
Raol, JR; Singh, J
2004-01-01
Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and mor
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)
Reference values of haematological parameters of healthy adults in ...
African Journals Online (AJOL)
Reference values of haematological parameters of healthy adults in the north central zone of Nigeria. HO Olawumi, IA Durotoye, JK Afolabi, A Fadeyi, OO Desalu, SA Aderibigbe, AS Babatunde, SK Ernest, AE Fawibe, AK Salami, R Saadu, MAN Adeboye, AP Aboyeji ...
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
Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model
Custer, Michael
2015-01-01
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
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. .
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.
Nienałtowski, Karol; Włodarczyk, Michał; Lipniacki, Tomasz; Komorowski, Michał
2015-09-29
Compared to engineering or physics problems, dynamical models in quantitative biology typically depend on a relatively large number of parameters. Progress in developing mathematics to manipulate such multi-parameter models and so enable their efficient interplay with experiments has been slow. Existing solutions are significantly limited by model size. In order to simplify analysis of multi-parameter models a method for clustering of model parameters is proposed. It is based on a derived statistically meaningful measure of similarity between groups of parameters. The measure quantifies to what extend changes in values of some parameters can be compensated by changes in values of other parameters. The proposed methodology provides a natural mathematical language to precisely communicate and visualise effects resulting from compensatory changes in values of parameters. As a results, a relevant insight into identifiability analysis and experimental planning can be obtained. Analysis of NF-κB and MAPK pathway models shows that highly compensative parameters constitute clusters consistent with the network topology. The method applied to examine an exceptionally rich set of published experiments on the NF-κB dynamics reveals that the experiments jointly ensure identifiability of only 60% of model parameters. The method indicates which further experiments should be performed in order to increase the number of identifiable parameters. We currently lack methods that simplify broadly understood analysis of multi-parameter models. The introduced tools depict mutually compensative effects between parameters to provide insight regarding role of individual parameters, identifiability and experimental design. The method can also find applications in related methodological areas of model simplification and parameters estimation.
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.
De Leeuw, Astrid A C; Van de Kamer, Jeroen B; Moerland, Marinus A; Philippens, Marielle E P; Jürgenliemk-Schulz, Ina-M
2011-11-01
To evaluate the effect of different α/β and half-time of repair T(½) on the assessment of clinical treatment plans for patients with cervical cancer. We used EBRT and BT treatment plans of five patients, planned with MRI guided BT. We computed 3D EQD2 dose distributions of combined EBRT and BT treatments and calculated D90 of high-risk clinical target volume (HR-CTV) and D(2cc) for bladder and rectum, and the ratio D(2cc)(bladder)/D90(HR-CTV). BT was modelled as PDR (two applications of 32×60cGy) and HDR (two applications of 2×7Gy). We assumed a low, standard and high value for the biological parameters: HR-CTV α/β=5/10/15Gy and T(½)=0.5/1.5/2.5h; OAR α/β=2/3/4Gy; T(½)=0.5/1.5/4.5h. The chosen variation in modelling parameters had a much larger effect on PDR treatments than on HDR treatments, especially for OAR, thus creating larger uncertainties. The relative mean range of the ratio D(2cc)(bladder)/D90(HR-CTV) is 72% for PDR and 25% for HDR. Out of the 125 modelled combinations 48 PDR plans and 23 HDR plans comply with clinical objectives. For HDR brachytherapy, only α/β has a significant impact on reported EQD2 values, whereas for PDR both α/β and T(½) are important. Generally, the ratio D(2cc)(bladder)/D90(HR-CTV) is more favourable for PDR, even considering the larger uncertainties in EQD2. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
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 pharmacokinetic parameters and the prediction probability of relative quantitative pharmacokinetic parameters( Z =0.867, P =0.195). Conclusion: There was no significant difference between the
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.
Multifractal Value at Risk model
Lee, Hojin; Song, Jae Wook; Chang, Woojin
2016-06-01
In this paper new Value at Risk (VaR) model is proposed and investigated. We consider the multifractal property of financial time series and develop a multifractal Value at Risk (MFVaR). MFVaR introduced in this paper is analytically tractable and not based on simulation. Empirical study showed that MFVaR can provide the more stable and accurate forecasting performance in volatile financial markets where large loss can be incurred. This implies that our multifractal VaR works well for the risk measurement of extreme credit events.
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.
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
In ground water flow system models with hydraulic-head observations but without significant imposed or observed flows, extreme parameter correlation generally exists. As a result, hydraulic conductivity and recharge parameters cannot be uniquely estimated. In complicated problems, such correlation...... 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...
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.
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
Development of new model for high explosives detonation parameters calculation
Directory of Open Access Journals (Sweden)
Jeremić Radun
2012-01-01
Full Text Available The simple semi-empirical model for calculation of detonation pressure and velocity for CHNO explosives has been developed, which is based on experimental values of detonation parameters. Model uses Avakyan’s method for determination of detonation products' chemical composition, and is applicable in wide range of densities. Compared with the well-known Kamlet's method and numerical model of detonation based on BKW EOS, the calculated values from proposed model have significantly better accuracy.
An approach to adjustment of relativistic mean field model parameters
Directory of Open Access Journals (Sweden)
Bayram Tuncay
2017-01-01
Full Text Available The Relativistic Mean Field (RMF model with a small number of adjusted parameters is powerful tool for correct predictions of various ground-state nuclear properties of nuclei. Its success for describing nuclear properties of nuclei is directly related with adjustment of its parameters by using experimental data. In the present study, the Artificial Neural Network (ANN method which mimics brain functionality has been employed for improvement of the RMF model parameters. In particular, the understanding capability of the ANN method for relations between the RMF model parameters and their predictions for binding energies (BEs of 58Ni and 208Pb have been found in agreement with the literature values.
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.
Physiological parameter values in greyhounds before and after high ...
African Journals Online (AJOL)
Heart rate (HR), blood lactate (BL) and rectal temperature (RT) are relevant physiological parameters to determine the dogs response to effort. ... in greyhounds have reported the effect of high-intensity exercise on many physiological parameters immediately after completing different racing distances and recovery times.
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
Djuric-Stefanovic, A; Saranovic, Dj; Sobic-Saranovic, D; Masulovic, D; Artiko, V
2015-03-01
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. 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 (rS). 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, pCT perfusion measurements and statistically significant correlation was proved. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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.
Parameters and variables appearing in repository design models
International Nuclear Information System (INIS)
Curtis, R.H.; Wart, R.J.
1983-12-01
This report defines the parameters and variables appearing in repository design models and presents typical values and ranges of values of each. Areas covered by this report include thermal, geomechanical, and coupled stress and flow analyses in rock. Particular emphasis is given to conductivity, radiation, and convection parameters for thermal analysis and elastic constants, failure criteria, creep laws, and joint properties for geomechanical analysis. The data in this report were compiled to help guide the selection of values of parameters and variables to be used in code benchmarking. 102 references, 33 figures, 51 tables
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.
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...
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.
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)
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.
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......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...
PhyloPars: estimation of missing parameter values using phylogeny.
Bruggeman, J.; Heringa, J.; Brandt, B.W.
2009-01-01
A wealth of information on metabolic parameters of a species can be inferred from observations on species that are phylogenetically related. Phylogeny-based information can complement direct empirical evidence, and is particularly valuable if experiments on the species of interest are not feasible.
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
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.
Partial sum approaches to mathematical parameters of some growth models
Korkmaz, Mehmet
2016-04-01
Growth model is fitted by evaluating the mathematical parameters, a, b and c. In this study, the method of partial sums were used. For finding the mathematical parameters, firstly three partial sums were used, secondly four partial sums were used, thirdly five partial sums were used and finally N partial sums were used. The purpose of increasing the partial decomposition is to produce a better phase model which gives a better expected value by minimizing error sum of squares in the interval used.
CHAMP: Changepoint Detection Using Approximate Model Parameters
2014-06-01
form (with independent emissions or otherwise), in which parameter estimates are available via means such as maximum likelihood fit, MCMC , or sample ...counterparts, including the ability to generate a full posterior distribution over changepoint locations and offering a natural way to incorporate prior... sample consensus method. Our modifications also remove a significant restriction on model definition when detecting parameter changes within a single
Baseline values of immunologic parameters in the lizard Salvator ...
African Journals Online (AJOL)
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 ...
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.
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
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...
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.
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.
Order parameter fluctuations in natural time and b-value variation before large earthquakes
Directory of Open Access Journals (Sweden)
E. S. Skordas
2012-11-01
Full Text Available Self-similarity may stem from two origins: the process increments infinite variance and/or process memory. The b-value of the Gutenberg-Richter law comes from the first origin. In the frame of natural time analysis of earthquake data, a fall of the b-value observed before large earthquakes reflects an increase of the order parameter fluctuations upon approaching the critical point (mainshock. The increase of these fluctuations, however, is also influenced from the second origin of self-similarity, i.e., temporal correlations between earthquake magnitudes. This is supported by observations and simulations of an earthquake model.
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
Setting Parameters for Biological Models With ANIMO
Directory of Open Access Journals (Sweden)
Stefano Schivo
2014-03-01
Full Text Available 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 between biological entities in form of a graph, while the parameters determine the speed of occurrence of such interactions. When a mismatch is observed between the behavior of an ANIMO model and experimental data, we want to update the model so that it explains the new data. In general, the topology of a model can be expanded with new (known or hypothetical nodes, and enables it to match experimental data. However, the unrestrained addition of new parts to a model causes two problems: models can become too complex too fast, to the point of being intractable, and too many parts marked as "hypothetical" or "not known" make a model unrealistic. Even if changing the topology is normally the easier task, these problems push us to try a better parameter fit as a first step, and resort to modifying the model topology only as a last resource. In this paper we show the support added in ANIMO to ease the task of expanding the knowledge on biological networks, concentrating in particular on the parameter settings.
Moisture buffer value: A comprehensive analysis of essential parameters
DEFF Research Database (Denmark)
Peuhkuri, Ruut Hannele; Rode, Carsten; Hansen, Kurt Kielsgaard
2006-01-01
for determination of the moisture buffer value of building materials. Special focus is given to the significance of e.g. the equilibrium state, the step size in the RH and whether one is studying absorption or desorption steps. In addition, the paper summarizes shortly the experience until now of studying...... the moisture buffer phenomenon. In the experiments the material samples were exposed to a sudden change in the RH of the ambient air which were either consecutive absorption and desorption steps or periodically varying cyclic steps....
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
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.
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.
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
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
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
Moolenaar, H.E.; Selten, F.M.
2004-01-01
Climate models contain numerous parameters for which the numeric values are uncertain. In the context of climate simulation and prediction, a relevant question is what range of climate outcomes is possible given the range of parameter uncertainties. Which parameter perturbation changes the climate
Modeling extreme events: Sample fraction adaptive choice in parameter estimation
Neves, Manuela; Gomes, Ivette; Figueiredo, Fernanda; Gomes, Dora Prata
2012-09-01
When modeling extreme events there are a few primordial parameters, among which we refer the extreme value index and the extremal index. The extreme value index measures the right tail-weight of the underlying distribution and the extremal index characterizes the degree of local dependence in the extremes of a stationary sequence. Most of the semi-parametric estimators of these parameters show the same type of behaviour: nice asymptotic properties, but a high variance for small values of k, the number of upper order statistics to be used in the estimation, and a high bias for large values of k. This shows a real need for the choice of k. Choosing some well-known estimators of those parameters we revisit the application of a heuristic algorithm for the adaptive choice of k. The procedure is applied to some simulated samples as well as to some real data sets.
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.
Simultaneous boundary value and material parameter estimation using imperfect compression data
CSIR Research Space (South Africa)
Jansen van Rensburg, GJ
2014-09-01
Full Text Available in experimental data. The known boundary condition and material parameter values used to perform the finite element analysis in the virtual experiment allows investigation on the accuracy of the parameter identification strategies employed. The unknown material...
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.
Integer Valued Autoregressive Models for Tipping Bucket Rainfall Measurements
DEFF Research Database (Denmark)
Thyregod, Peter; Carstensen, Niels Jacob; Madsen, Henrik
1999-01-01
A new method for modelling the dynamics of rain sampled by a tipping bucket rain gauge is proposed. The considered models belong to the class of integer valued autoregressive processes. The models take the autocorelation and discrete nature of the data into account. A first order, a second order...... and a threshold model are presented together with methods to estimate the parameters of each model. The models are demonstrated to provide a good description of dt from actual rain events requiring only two to four parameters....
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....... For a comparison the parameters are also estimated by an output error method, where the sum of squared simulation error is minimized. The former methodology is optimal for short-term prediction whereas the latter is optimal for simulations. Hence, depending on the purpose it is possible to select whether...... 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...
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
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)
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
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
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
Influence of geometrical parameters of convergent sleeve on the value of limit stress
Directory of Open Access Journals (Sweden)
Górecki Jan
2018-01-01
Full Text Available This paper presents the results of research on improving the effectiveness of the agglomeration process. Improving effectiveness was obtained as a result of the application of the convergent sleeve. The sleeve is mounted before the multi-holes die in the dry ice agglomeration machine. The empirical part of the paper presents the results of research on which FEM model was based. The numerical part of research presents the FEM model of the agglomeration process. The FEM model with a known uncertainty level was used to determine the influence of geometrical parameters of the sleeve on the limit value of the agglomeration forces. The model will be one of the starting points for the design and construction of the machine for the compaction and granulation of dry ice.
Advances in Modelling, System Identification and Parameter ...
Indian Academy of Sciences (India)
models determined from flight test data by using parameter estimation methods find extensive use in design/modification of flight control systems, high fidelity flight simulators and evaluation of handling qualitites of aircraft and rotorcraft. R K Mehra et al present new algorithms and results for flutter tests and adaptive notching ...
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)
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.
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.
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
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.
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.
Fadly, Romi; Dewi, Citra
2014-01-01
This research aims to compare the 14 transformation parameters between ITRF from computation result using the Helmert 14-parameter models with IERS standard parameters. The transforma- tion parameters are calculated from the coordinates and velocities of ITRF05 to ITRF00 epoch 2000.00, and from ITRF08 to ITRF05 epoch 2005.00 for respectively transformation models. The transformation parameters are compared to the IERS standard parameters, then tested the signifi- cance of the d...
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.
Modelling of intermittent microwave convective drying: parameter sensitivity
Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei
2017-06-01
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.
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.
Investigation of land use effects on Nash model parameters
Niazi, Faegheh; Fakheri Fard, Ahmad; Nourani, Vahid; Goodrich, David; Gupta, Hoshin
2015-04-01
Flood forecasting is of great importance in hydrologic planning, hydraulic structure design, water resources management and sustainable designs like flood control and management. Nash's instantaneous unit hydrograph is frequently used for simulating hydrological response in natural watersheds. Urban hydrology is gaining more attention due to population increases and associated construction escalation. Rapid development of urban areas affects the hydrologic processes of watersheds by decreasing soil permeability, flood base flow, lag time and increase in flood volume, peak runoff rates and flood frequency. In this study the influence of urbanization on the significant parameters of the Nash model have been investigated. These parameters were calculated using three popular methods (i.e. moment, root mean square error and random sampling data generation), in a small watershed consisting of one natural sub-watershed which drains into a residentially developed sub-watershed in the city of Sierra Vista, Arizona. The results indicated that for all three methods, the lag time, which is product of Nash parameters "K" and "n", in the natural sub-watershed is greater than the developed one. This logically implies more storage and/or attenuation in the natural sub-watershed. The median K and n parameters derived from the three methods using calibration events were tested via a set of verification events. The results indicated that all the three method have acceptable accuracy in hydrograph simulation. The CDF curves and histograms of the parameters clearly show the difference of the Nash parameter values between the natural and developed sub-watersheds. Some specific upper and lower percentile values of the median of the generated parameters (i.e. 10, 20 and 30 %) were analyzed to future investigates the derived parameters. The model was sensitive to variations in the value of the uncertain K and n parameter. Changes in n are smaller than K in both sub-watersheds indicating
Parameter estimation and model selection in computational biology.
Directory of Open Access Journals (Sweden)
Gabriele Lillacci
2010-03-01
Full Text Available A central challenge in computational modeling of biological systems is the determination of the model parameters. Typically, only a fraction of the parameters (such as kinetic rate constants are experimentally measured, while the rest are often fitted. The fitting process is usually based on experimental time course measurements of observables, which are used to assign parameter values that minimize some measure of the error between these measurements and the corresponding model prediction. The measurements, which can come from immunoblotting assays, fluorescent markers, etc., tend to be very noisy and taken at a limited number of time points. In this work we present a new approach to the problem of parameter selection of biological models. We show how one can use a dynamic recursive estimator, known as extended Kalman filter, to arrive at estimates of the model parameters. The proposed method follows. First, we use a variation of the Kalman filter that is particularly well suited to biological applications to obtain a first guess for the unknown parameters. Secondly, we employ an a posteriori identifiability test to check the reliability of the estimates. Finally, we solve an optimization problem to refine the first guess in case it should not be accurate enough. The final estimates are guaranteed to be statistically consistent with the measurements. Furthermore, we show how the same tools can be used to discriminate among alternate models of the same biological process. We demonstrate these ideas by applying our methods to two examples, namely a model of the heat shock response in E. coli, and a model of a synthetic gene regulation system. The methods presented are quite general and may be applied to a wide class of biological systems where noisy measurements are used for parameter estimation or model selection.
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.
Directory of Open Access Journals (Sweden)
Brdar Mirjana M.
2011-01-01
Full Text Available The adsorption of Cu(II onto poplar sawdust as an adsorbent is analyzed. The experimental data were fitted by the Langmuir isotherm using four linearized forms at the isotherm along with the original one. The least squares regression method was applied. Using the obtained Langmuir constants by each at methods, the enthalpy, entropy and Gibbs free energy at adsoption were calculated. A comparison of the used linear and non-linear regression methods in view at the goodness of the fit is presented. The coefficient of correlation was adopted as a criterionn to select the best method. The impact of the choice at regression model on the resulting estimates of the thermodynamic parameters is discussed. The best fit of the experimental data is obtained by the nonlinear regression. Thus, it is recommended to use the Langmuir parameters calculated by the nonlinear regression for estimating the thermodynamic parameters of adsorptin. The differences in the values obtained by different models are not so large to change the basic conclusion that the adsorption of copper ions on poplar sawdust is a spontaneous endothermic process i.e. that tested adsorbent has an affinity for copper ions.
Aqueous Electrolytes: Model Parameters and Process Simulation
DEFF Research Database (Denmark)
Thomsen, Kaj
This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer ...... program including a steady state process simulator for the design, simulation, and optimization of fractional crystallization processes is presented.......This thesis deals with aqueous electrolyte mixtures. The Extended UNIQUAC model is being used to describe the excess Gibbs energy of such solutions. Extended UNIQUAC parameters for the twelve ions Na+, K+, NH4+, H+, Cl-, NO3-, SO42-, HSO4-, OH-, CO32-, HCO3-, and S2O82- are estimated. A computer...
Predictability of extreme values in geophysical models
Directory of Open Access Journals (Sweden)
A. E. Sterk
2012-09-01
Full Text Available Extreme value theory in deterministic systems is concerned with unlikely large (or small values of an observable evaluated along evolutions of the system. In this paper we study the finite-time predictability of extreme values, such as convection, energy, and wind speeds, in three geophysical models. We study whether finite-time Lyapunov exponents are larger or smaller for initial conditions leading to extremes. General statements on whether extreme values are better or less predictable are not possible: the predictability of extreme values depends on the observable, the attractor of the system, and the prediction lead time.
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…
Sensor placement for calibration of spatially varying model parameters
Nath, Paromita; Hu, Zhen; Mahadevan, Sankaran
2017-08-01
This paper presents a sensor placement optimization framework for the calibration of spatially varying model parameters. To account for the randomness of the calibration parameters over space and across specimens, the spatially varying parameter is represented as a random field. Based on this representation, Bayesian calibration of spatially varying parameter is investigated. To reduce the required computational effort during Bayesian calibration, the original computer simulation model is substituted with Kriging surrogate models based on the singular value decomposition (SVD) of the model response and the Karhunen-Loeve expansion (KLE) of the spatially varying parameters. A sensor placement optimization problem is then formulated based on the Bayesian calibration to maximize the expected information gain measured by the expected Kullback-Leibler (K-L) divergence. The optimization problem needs to evaluate the expected K-L divergence repeatedly which requires repeated calibration of the spatially varying parameter, and this significantly increases the computational effort of solving the optimization problem. To overcome this challenge, an approximation for the posterior distribution is employed within the optimization problem to facilitate the identification of the optimal sensor locations using the simulated annealing algorithm. A heat transfer problem with spatially varying thermal conductivity is used to demonstrate the effectiveness of the proposed method.
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
Value-Oriented Coordination Process Modeling
Fatemi, Hassan; van Sinderen, Marten J.; Wieringa, Roelf J.; Hull, Richard; Mendling, Jan; Tai, Stefan
Business webs are collections of enterprises designed to jointly satisfy a consumer need. Designing business webs calls for modeling the collaboration of enterprises from different perspectives, in particular the business value and coordination process perspectives, and for mutually aligning these
Parameter uncertainty analysis of a biokinetic model of caesium
International Nuclear Information System (INIS)
Li, W.B.; Oeh, U.; Klein, W.; Blanchardon, E.; Puncher, M.; Leggett, R.W.; Breustedt, B.; Nosske, D.; Lopez, M.A.
2015-01-01
Parameter uncertainties for the biokinetic model of caesium (Cs) developed by Leggett et al. were inventoried and evaluated. The methods of parameter uncertainty analysis were used to assess the uncertainties of model predictions with the assumptions of model parameter uncertainties and distributions. Furthermore, the importance of individual model parameters was assessed by means of sensitivity analysis. The calculated uncertainties of model predictions were compared with human data of Cs measured in blood and in the whole body. It was found that propagating the derived uncertainties in model parameter values reproduced the range of bioassay data observed in human subjects at different times after intake. The maximum ranges, expressed as uncertainty factors (UFs) (defined as a square root of ratio between 97.5. and 2.5. percentiles) of blood clearance, whole-body retention and urinary excretion of Cs predicted at earlier time after intake were, respectively: 1.5, 1.0 and 2.5 at the first day; 1.8, 1.1 and 2.4 at Day 10 and 1.8, 2.0 and 1.8 at Day 100; for the late times (1000 d) after intake, the UFs were increased to 43, 24 and 31, respectively. The model parameters of transfer rates between kidneys and blood, muscle and blood and the rate of transfer from kidneys to urinary bladder content are most influential to the blood clearance and to the whole-body retention of Cs. For the urinary excretion, the parameters of transfer rates from urinary bladder content to urine and from kidneys to urinary bladder content impact mostly. The implication and effect on the estimated equivalent and effective doses of the larger uncertainty of 43 in whole-body retention in the later time, say, after Day 500 will be explored in a successive work in the framework of EURADOS. (authors)
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.
Proliferation in Non-Hodgkin’S Lymphomas and Its Prognostic Value Related to Staging Parameters
Directory of Open Access Journals (Sweden)
Irene Lorand‐Metze
2004-01-01
Full Text Available In malignant lymphomas, cell kinetics has shown to be related with histologic type as well as with the clinical behaviour. The aim of our study was to investigate the relevance of cell proliferation parameters on overall survival in non‐Hodgkin's lymphomas as well as their relationship with prognostic factors such as International Prognostic Index (IPI. We performed DNA‐flow‐cytometry (S‐phase fraction and detection of DNA‐aneuploidy as well as cytologic examination and the AgNOR technique in material obtained by fine needle aspiration of lymph nodes at diagnosis. The majority of the patients were stage IV by Ann Arbor and intermediate risk by IPI (42/55. When analyzing all patients together, histologic type by the WHO classification, IPI and the presence of a DNA‐aneuploid clone could not separate well patients with a different survival. For all patients, univariate Cox analysis revealed S‐phase (SPF and AgNOR parameters to be of prognostic value. In the multivariate analysis, however, only SPF remained in the final model. Yet, when stratifying for DNA‐ploidy, only the total number of AgNORs/nucleus was an independent parameter. Looking only at the DNA‐diploid cases, the AgNOR pattern remained the most important parameter, whereas for the DNA‐aneuploid cases this was true for SPF. When studying patients with B large cell lymphoma separately, only DNA‐ploidy was a prognostic factor. In summary, cell kinetic parameters reveal important prognostic information in NHL patients. Furthermore, DNA‐aneuploidy seems to interfere with the analysis of the AgNOR pattern.
Lumped Parameters Model of a Crescent Pump
Directory of Open Access Journals (Sweden)
Massimo Rundo
2016-10-01
Full Text Available This paper presents the lumped parameters model of an internal gear crescent pump with relief valve, able to estimate the steady-state flow-pressure characteristic and the pressure ripple. The approach is based on the identification of three variable control volumes regardless of the number of gear teeth. The model has been implemented in the commercial environment LMS Amesim with the development of customized components. Specific attention has been paid to the leakage passageways, some of them affected by the deformation of the cover plate under the action of the delivery pressure. The paper reports the finite element method analysis of the cover for the evaluation of the deflection and the validation through a contactless displacement transducer. Another aspect described in this study is represented by the computational fluid dynamics analysis of the relief valve, whose results have been used for tuning the lumped parameters model. Finally, the validation of the entire model of the pump is presented in terms of steady-state flow rate and of pressure oscillations.
Parameter Estimation for Single Diode Models of Photovoltaic Modules
Energy Technology Data Exchange (ETDEWEB)
Hansen, Clifford [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Distributed Systems Integration Dept.
2015-03-01
Many popular models for photovoltaic system performance employ a single diode model to compute the I - V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I - V curves. Many available parameter estimation methods use only short circuit, o pen circuit and maximum power points for a single I - V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I - V curves over a wide range of irradi ance and temperature conditions which, when available , should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a fu ll range of available I - V curves. We verify the accuracy of the method by recov ering known parameter values from simulated I - V curves . We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
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)
Modeling Chinese ionospheric layer parameters based on EOF analysis
Yu, You; Wan, Weixing
2016-04-01
Using 24-ionosonde observations in and around China during the 20th solar cycle, an assimilative model is constructed to map the ionospheric layer parameters (foF2, hmF2, M(3000)F2, and foE) over China based on empirical orthogonal function (EOF) analysis. First, we decompose the background maps from the International Reference Ionosphere model 2007 (IRI-07) into different EOF modes. The obtained EOF modes consist of two factors: the EOF patterns and the corresponding EOF amplitudes. These two factors individually reflect the spatial distributions (e.g., the latitudinal dependence such as the equatorial ionization anomaly structure and the longitude structure with east-west difference) and temporal variations on different time scales (e.g., solar cycle, annual, semiannual, and diurnal variations) of the layer parameters. Then, the EOF patterns and long-term observations of ionosondes are assimilated to get the observed EOF amplitudes, which are further used to construct the Chinese Ionospheric Maps (CIMs) of the layer parameters. In contrast with the IRI-07 model, the mapped CIMs successfully capture the inherent temporal and spatial variations of the ionospheric layer parameters. Finally, comparison of the modeled (EOF and IRI-07 model) and observed values reveals that the EOF model reproduces the observation with smaller root-mean-square errors and higher linear correlation co- efficients. In addition, IRI discrepancy at the low latitude especially for foF2 is effectively removed by EOF model.
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 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
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.
Improving the realism of hydrologic model through multivariate parameter estimation
Rakovec, Oldrich; Kumar, Rohini; Attinger, Sabine; Samaniego, Luis
2017-04-01
Increased availability and quality of near real-time observations should improve understanding of predictive skills of hydrological models. Recent studies have shown the limited capability of river discharge data alone to adequately constrain different components of distributed model parameterizations. In this study, the GRACE satellite-based total water storage (TWS) anomaly is used to complement the discharge data with an aim to improve the fidelity of mesoscale hydrologic model (mHM) through multivariate parameter estimation. The study is conducted in 83 European basins covering a wide range of hydro-climatic regimes. The model parameterization complemented with the TWS anomalies leads to statistically significant improvements in (1) discharge simulations during low-flow period, and (2) evapotranspiration estimates which are evaluated against independent (FLUXNET) data. Overall, there is no significant deterioration in model performance for the discharge simulations when complemented by information from the TWS anomalies. However, considerable changes in the partitioning of precipitation into runoff components are noticed by in-/exclusion of TWS during the parameter estimation. A cross-validation test carried out to assess the transferability and robustness of the calibrated parameters to other locations further confirms the benefit of complementary TWS data. In particular, the evapotranspiration estimates show more robust performance when TWS data are incorporated during the parameter estimation, in comparison with the benchmark model constrained against discharge only. This study highlights the value for incorporating multiple data sources during parameter estimation to improve the overall realism of hydrologic model and its applications over large domains. Rakovec, O., Kumar, R., Attinger, S. and Samaniego, L. (2016): Improving the realism of hydrologic model functioning through multivariate parameter estimation. Water Resour. Res., 52, http://dx.doi.org/10
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
Energy Technology Data Exchange (ETDEWEB)
Beaujean, Frederik; Caldwell, Allen [Max-Planck-Institut fuer Physik, Muenchen (Germany); Kollar, Daniel [CERN, Genf (Switzerland); Kroeninger, Kevin [Georg-August-Universitaet, Goettingen (Germany)
2011-07-01
In the analysis of experimental results it is often necessary to pass a judgment on the validity of a model as a representation of the data. A quantitative procedure to decide whether a model provides a good description of data is often based on a specific test statistic and a p-value summarizing both the data and the statistic's sampling distribution. 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 the application of p-values using a Bayesian argumentation. We then describe commonly and less commonly known test statistics and how they are used to define p-values. The distribution of these are then extracted for examples modeled on typical new physics searches in high energy physics. We comment on their usefulness for determining goodness-of-fit and highlight some common pitfalls.
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
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...
Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values that is value of the physical and chemical constants that govern reactivity. Although empirical structure activity relationships have been developed th...
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.
Montopoli, Mario; Cimini, Domenico; Marzano, Frank
2016-04-01
Volcanic eruptions inject both gas and solid particles into the Atmosphere. Solid particles are made by mineral fragments of different sizes (from few microns to meters), generally referred as tephra. Tephra from volcanic eruptions has enormous impacts on social and economical activities through the effects on the environment, climate, public health, and air traffic. The size, density and shape of a particle determine its fall velocity and thus residence time in the Atmosphere. Larger particles tend to fall quickly in the proximity of the volcano, while smaller particles may remain suspended for several days and thus may be transported by winds for thousands of km. Thus, the impact of such hazards involves local as well as large scales effects. Local effects involve mostly the large sized particles, while large scale effects are caused by the transport of the finest ejected tephra (ash) through the atmosphere. Forecasts of ash paths in the atmosphere are routinely run after eruptions using dispersion models. These models make use of meteorological and volcanic source parameters. The former are usually available as output of numerical weather prediction models or large scale reanalysis. Source parameters characterize the volcanic eruption near the vent; these are mainly the ash mass concentration along the vertical column and the top altitude of the volcanic plume, which is strictly related to the flux of the mass ejected at the emission source. These parameters should be known accurately and continuously; otherwise, strong hypothesis are usually needed, leading to large uncertainty in the dispersion forecasts. However, direct observations during an eruption are typically dangerous and impractical. Thus, satellite remote sensing is often exploited to monitor volcanic emissions, using visible (VIS) and infrared (IR) channels available on both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellites. VIS and IR satellite imagery are very useful to monitor
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.
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......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 specification of the conditional variance, conditional correlation, innovation distribution, and estimation approach. All of the models belong to the dynamic conditional correlation class, which is particularly suitable because it allows consistent estimations of the risk neutral dynamics with a manageable....... 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....
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
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
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
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.
From business value model to coordination process model
Fatemi, Hassan; Wieringa, Roelf J.; Poler, R.; van Sinderen, Marten J.; Sanchis, R.
2009-01-01
The increased complexity of business webs calls for modeling the collaboration of enterprises from different perspectives, in particular the business and process perspectives, and for mutually aligning these perspectives. Business value modeling and coordination process modeling both are necessary
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 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.
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)
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.)
Space geodetic techniques for global modeling of ionospheric peak parameters
Alizadeh, M. Mahdi; Schuh, Harald; Schmidt, Michael
The rapid development of new technological systems for navigation, telecommunication, and space missions which transmit signals through the Earth’s upper atmosphere - the ionosphere - makes the necessity of precise, reliable and near real-time models of the ionospheric parameters more crucial. In the last decades space geodetic techniques have turned into a capable tool for measuring ionospheric parameters in terms of Total Electron Content (TEC) or the electron density. Among these systems, the current space geodetic techniques, such as Global Navigation Satellite Systems (GNSS), Low Earth Orbiting (LEO) satellites, satellite altimetry missions, and others have found several applications in a broad range of commercial and scientific fields. This paper aims at the development of a three-dimensional integrated model of the ionosphere, by using various space geodetic techniques and applying a combination procedure for computation of the global model of electron density. In order to model ionosphere in 3D, electron density is represented as a function of maximum electron density (NmF2), and its corresponding height (hmF2). NmF2 and hmF2 are then modeled in longitude, latitude, and height using two sets of spherical harmonic expansions with degree and order 15. To perform the estimation, GNSS input data are simulated in such a way that the true position of the satellites are detected and used, but the STEC values are obtained through a simulation procedure, using the IGS VTEC maps. After simulating the input data, the a priori values required for the estimation procedure are calculated using the IRI-2012 model and also by applying the ray-tracing technique. The estimated results are compared with F2-peak parameters derived from the IRI model to assess the least-square estimation procedure and moreover, to validate the developed maps, the results are compared with the raw F2-peak parameters derived from the Formosat-3/Cosmic data.
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.
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)
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
Variants of Modeling Dwelling Market Value
Directory of Open Access Journals (Sweden)
Barańska Anna
2014-10-01
Full Text Available The object of this paper is to determine real estate market value on the basis of a multidimensional function model in different variants: A - directly from the model estimated on the basis of a big database, B - from the same model form, but estimated on the basis of a reduced database consisting of dwellings most similar to the estimated one, and C - based on modeled prices corrected by random correction, calculated from random deviations for dwellings most similar to the assessed one. In the framework of statistical inference procedures, the resulting comparison was carried out by parametric significance tests. They were applied to draw conclusions on the analyzed variants
Revised Parameters for the AMOEBA Polarizable Atomic Multipole Water Model.
Laury, Marie L; Wang, Lee-Ping; Pande, Vijay S; Head-Gordon, Teresa; Ponder, Jay W
2015-07-23
A set of improved parameters for the AMOEBA polarizable atomic multipole water model is developed. An automated procedure, ForceBalance, is used to adjust model parameters to enforce agreement with ab initio-derived results for water clusters and experimental 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 AMOEBA14 model accurately predicts the temperature of maximum density and qualitatively matches the experimental density curve across temperatures from 249 to 373 K. Excellent agreement is observed for the AMOEBA14 model in comparison to experimental properties as a function of temperature, including the second 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 2-20 water molecules, the AMOEBA14 model yields results similar to 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.
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.
Robust linear parameter varying induction motor control with polytopic models
Directory of Open Access Journals (Sweden)
Dalila Khamari
2013-01-01
Full Text Available This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.
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…
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
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
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.
DEFF Research Database (Denmark)
Ditlevsen, Susanne; Yip, Kay-Pong; Holstein-Rathlou, N.-H.
2005-01-01
A key parameter in the understanding of renal hemodynamics is the gain of the feedback function in the tubuloglomerular feedback mechanism. A dynamic model of autoregulation of renal blood flow and glomerular filtration rate has been extended to include a stochastic differential equations model...... analyzed, and the parameters characterizing the gain and the delay have been estimated. There was good agreement between the estimated values, and the values obtained for the same parameters in independent, previously published experiments....
Dengue human infection model performance parameters.
Endy, Timothy P
2014-06-15
Dengue is a global health problem and of concern to travelers and deploying military personnel with development and licensure of an effective tetravalent dengue vaccine a public health priority. The dengue viruses (DENVs) are mosquito-borne flaviviruses transmitted by infected Aedes mosquitoes. Illness manifests across a clinical spectrum with severe disease characterized by intravascular volume depletion and hemorrhage. DENV illness results from a complex interaction of viral properties and host immune responses. Dengue vaccine development efforts are challenged by immunologic complexity, lack of an adequate animal model of disease, absence of an immune correlate of protection, and only partially informative immunogenicity assays. A dengue human infection model (DHIM) will be an essential tool in developing potential dengue vaccines or antivirals. The potential performance parameters needed for a DHIM to support vaccine or antiviral candidates are discussed. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Dimensionality reduction of RKHS model parameters.
Taouali, Okba; Elaissi, Ilyes; Messaoud, Hassani
2015-07-01
This paper proposes a new method to reduce the parameter number of models developed in the Reproducing Kernel Hilbert Space (RKHS). In fact, this number is equal to the number of observations used in the learning phase which is assumed to be high. The proposed method entitled Reduced Kernel Partial Least Square (RKPLS) consists on approximating the retained latent components determined using the Kernel Partial Least Square (KPLS) method by their closest observation vectors. The paper proposes the design and the comparative study of the proposed RKPLS method and the Support Vector Machines on Regression (SVR) technique. The proposed method is applied to identify a nonlinear Process Trainer PT326 which is a physical process available in our laboratory. Moreover as a thermal process with large time response may help record easily effective observations which contribute to model identification. Compared to the SVR technique, the results from the proposed RKPLS method are satisfactory. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
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
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.
HOM study and parameter calculation of the TESLA cavity model
Zeng, Ri-Hua; Gerigk Frank; Wang Guang-Wei; Wegner Rolf; Liu Rong; Schuh Marcel
2010-01-01
The Superconducting Proton Linac (SPL) is the project for a superconducting, high current H-accelerator at CERN. To find dangerous higher order modes (HOMs) in the SPL superconducting cavities, simulation and analysis for the cavity model using simulation tools are necessary. The. existing TESLA 9-cell cavity geometry data have been used for the initial construction of the models in HFSS. Monopole, dipole and quadrupole modes have been obtained by applying different symmetry boundaries on various cavity models. In calculation, scripting language in HFSS was used to create scripts to automatically calculate the parameters of modes in these cavity models (these scripts are also available in other cavities with different cell numbers and geometric structures). The results calculated automatically are then compared with the values given in the TESLA paper. The optimized cavity model with the minimum error will be taken as the base for further simulation of the SPL cavities.
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)
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).
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.
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.
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
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
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.
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.
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)
DEFF Research Database (Denmark)
Pauwels, Valentijn; Balenzano, Anna; Satalino, Giuseppe
2009-01-01
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...... model is, thus, used to determine the relationship between the soil physical parameters and the remote-sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential...
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.
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.
From Business Value Model to Coordination Process Model
Fatemi, Hassan; van Sinderen, Marten; Wieringa, Roel
The increased complexity of business webs calls for modeling the collaboration of enterprises from different perspectives, in particular the business and process perspectives, and for mutually aligning these perspectives. Business value modeling and coordination process modeling both are necessary for a good e-business design, but these activities have different goals and use different concepts. Nevertheless, the resulting models should be consistent with each other because they refer to the same system from different perspectives. Hence, checking the consistency between these models or producing one based on the other would be of high value. In this paper we discuss the issue of achieving consistency in multi-level e-business design and give guidelines to produce consistent coordination process models from business value models in a stepwise manner.
Shin, Eun-Seok; Lam, Yat-Yin; Her, Ae-Young; Brachmann, Johannes; Jung, Friedrich; Park, Jai-Wun
2017-02-01
Magnetocardiography (MCG) has been proposed as a non-invasive and functional technique with high accuracy for diagnosis of myocardial ischemia. This study sought to investigate the incremental diagnostic value of combined quantitative and qualitative parameters of MCG to detect coronary artery disease (CAD). Ninety six patients with suspected CAD who underwent coronary angiography were enrolled in the analysis to test the diagnostic accuracy of 2 MCG parameters (a quantitative parameter of the percent change of ST-segment fluctuation score and a qualitative parameter of non-dipole phenomenon). The best cut-off value for the percent change of ST-segment fluctuation score was -51.0%. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 78.1, 73.9, 82.0, 79.1, and 77.4, in the percent change of ST-segment fluctuation score and 86.5, 84.8, 88.0, 86.7, and 86.3 in non-dipole phenomenon. The area under the curve of receiver-operating characteristics was 0.79 for the percent change of ST-segment fluctuation score and 0.86 for non-dipole phenomenon (pQualitative assessment of non-dipole phenomenon has a better diagnostic value than the quantitative parameter of percent change of ST-segment fluctuation score in the detection of significant CAD. Furthermore, this study found that the incorporation of non-dipole phenomenon into the percent change of ST-segment fluctuation score significantly improved the diagnostic performance of CAD detection. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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...
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.
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)
Proving the ecosystem value through hydrological modelling
Dorner, W.; Spachinger, K.; Porter, M.; Metzka, R.
2008-11-01
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
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
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.
Mattia, F.; Pauwels, V. R.; Balenzano, A.; Satalino, G.; Skriver, H.; Verhoest, N. E.
2008-12-01
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 been focused on the retrieval of land and bio-geophysical parameters (e.g. soil moisture contents). One relatively unexplored issue consists of the optimization of soil hydraulic model parameters, such as for example hydraulic conductivity values, through remote sensing. This is due to the fact 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 study is to retrieve a number of soil physical model parameters through a combination of remote sensing and land surface modeling. Spatially distributed and multitemporal SAR-based soil moisture maps are the basis of the study. The surface soil moisture values are used in a parameter estimation procedure based on the Extended Kalman Filter equations. In fact, the land surface model is thus used to determine the relationship between the soil physical parameters and the remote sensing data. An analysis is then performed, relating the retrieved soil parameters to the soil texture data available over the study area. The results of the study show that there is a potential to retrieve soil physical model parameters through a combination of land surface modeling and remote sensing.
Parameter optimization method for the water quality dynamic model based on data-driven theory.
Liang, Shuxiu; Han, Songlin; Sun, Zhaochen
2015-09-15
Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). Copyright © 2015 Elsevier Ltd. All rights reserved.
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.
Modeling Water Quality Parameters Using Data-driven Methods
Directory of Open Access Journals (Sweden)
Shima Soleimani
2017-02-01
model water quality parameters such as Na+, K+, Mg2+, So42-, Cl-, pH, Electric conductivity (EC and total dissolved solids (TDS in the Sefidrood River. For comparison the selected input variable methods coefficient of determination (R2, root mean square error (RMSE, and Nash-Sutcliff (NS are applied. Results and Discussion: According to Table 5, the results of the GA-LSSVR algorithm by using correlation coefficient and PCA methods approximately show similar results. About pH, EC, and TDS quality parameters, the results of PCA method have, the more accuracy, but the difference of RMSE between the PCA method and correlation coefficient method is not significant. The PCA method cause improvement in NS values to 22 and 0.1 percentages in pH and TDS water quality parameters to the correlation coefficient method, respectively,and NS criteria value for EC water quality parameter did not change in both methods. As a result, according to positive values of NS criteria in both PCA and correlation methods, it is clear that GA-LSSVR has a high ability for modeling of water quality parameters. Because of summation of NS criteria for PCA method is 5.53 and for correlation coefficient is 5.62, we can say that the correlation coefficient method has more applicable as a data processing method, but both methods have a high ability. Orouji et all. (18 used assumed models to model Na+, K+, Mg2+, So42- , Cl- , pH, EC, and TDS by Genetic programming (GP method. The RMSE criteria of the better models for testing data are 2.1, 0.02, 0.85, 0.93, 2.18, 0.33, 404.15, and 246.15, respectively. For comparison the orouji et al. (18 and table (5, the Results show using the correlation coefficient method as a data processing method can improve the results to 5.5 times. The results indicate the superiority of developingalgorithm increases the modeling accuracy. It is worth mentioning that according to NS criteria both selected inputs variable methods (correlation coefficient and PCA are capable to
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...... corresponding to significant Eigen values (resulting from the decomposition) is used to transform the model from having many pilot point parameters to having a few super parameters. A synthetic case model is used to analyze and demonstrate the application of the presented method of model parameterization...
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.
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 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
Chen, Xiaofeng; Li, Zhongshan; Song, Qiankun; Hu, Jin; Tan, Yuanshun
2017-07-01
This paper addresses the problem of robust stability for quaternion-valued neural networks (QVNNs) with leakage delay, discrete delay and parameter uncertainties. Based on Homeomorphic mapping theorem and Lyapunov theorem, via modulus inequality technique of quaternions, some sufficient conditions on the existence, uniqueness, and global robust stability of the equilibrium point are derived for the delayed QVNNs with parameter uncertainties. Furthermore, as direct applications of these results, several sufficient conditions are obtained for checking the global robust stability of QVNNs without leakage delay as well as complex-valued neural networks (CVNNs) with both leakage and discrete delays. Finally, two numerical examples are provided to substantiate the effectiveness of the proposed results. Published by Elsevier Ltd.
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.
Rezaei, Meisam; Seuntjens, Piet; Shahidi, Reihaneh; Joris, Ingeborg; Boënne, Wesley; Cornelis, Wim
2016-04-01
Soil hydraulic parameters, which can be derived from in situ and/or laboratory experiments, are key input parameters for modeling water flow in the vadose zone. In this study, we measured soil hydraulic properties with typical laboratory measurements and field tension infiltration experiments using Wooding's analytical solution and inverse optimization along the vertical direction within two typical podzol profiles with sand texture in a potato field. The objective was to identify proper sets of hydraulic parameters and to evaluate their relevance on hydrological model performance for irrigation management purposes. Tension disc infiltration experiments were carried out at five different depths for both profiles at consecutive negative pressure heads of 12, 6, 3 and 0.1 cm. At the same locations and depths undisturbed samples were taken to determine the water retention curve with hanging water column and pressure extractors and lab saturated hydraulic conductivity with the constant head method. Both approaches allowed to determine the Mualem-van Genuchten (MVG) hydraulic parameters (residual water content θr, saturated water content θs,, shape parameters α and n, and field or lab saturated hydraulic conductivity Kfs and Kls). Results demonstrated horizontal differences and vertical variability of hydraulic properties. Inverse optimization resulted in excellent matches between observed and fitted infiltration rates in combination with final water content at the end of the experiment, θf, using Hydrus 2D/3D. It also resulted in close correspondence of and Kfs with those from Logsdon and Jaynes' (1993) solution of Wooding's equation. The MVG parameters Kfs and α estimated from the inverse solution (θr set to zero), were relatively similar to values from Wooding's solution which were used as initial value and the estimated θs corresponded to (effective) field saturated water content θf. We found the Gardner parameter αG to be related to the optimized van
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.
Parameter and Uncertainty Estimation in Groundwater Modelling
DEFF Research Database (Denmark)
Jensen, Jacob Birk
The data basis on which groundwater models are constructed is in general very incomplete, and this leads to uncertainty in model outcome. Groundwater models form the basis for many, often costly decisions and if these are to be made on solid grounds, the uncertainty attached to model results must...... be quantified. This study was motivated by the need to estimate the uncertainty involved in groundwater models.Chapter 2 presents an integrated surface/subsurface unstructured finite difference model that was developed and applied to a synthetic case study.The following two chapters concern calibration...... was applied.Capture zone modelling was conducted on a synthetic stationary 3-dimensional flow problem involving river, surface and groundwater flow. Simulated capture zones were illustrated as likelihood maps and compared with a deterministic capture zones derived from a reference model. The results showed...
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.
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
Preferred Customer
SUBGRADE MODELING. Asrat Worku. Department of ... The models give consistently larger stiffness for the Winkler springs as compared to previously proposed similar continuum-based models that ignore the lateral stresses. ...... (ν = 0.25 and E = 40MPa); (b) a medium stiff clay (ν = 0.45 and E = 50MPa). In contrast to this, ...
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.
Hydrological Modelling and Parameter Identification for Green Roof
Lo, W.; Tung, C.
2012-12-01
Green roofs, a multilayered system covered by plants, can be used to replace traditional concrete roofs as one of various measures to mitigate the increasing stormwater runoff in the urban environment. Moreover, facing the high uncertainty of the climate change, the present engineering method as adaptation may be regarded as improper measurements; reversely, green roofs are unregretful and flexible, and thus are rather important and suitable. The related technology has been developed for several years and the researches evaluating the stormwater reduction performance of green roofs are ongoing prosperously. Many European counties, cities in the U.S., and other local governments incorporate green roof into the stormwater control policy. Therefore, in terms of stormwater management, it is necessary to develop a robust hydrologic model to quantify the efficacy of green roofs over different types of designs and environmental conditions. In this research, a physical based hydrologic model is proposed to simulate water flowing process in the green roof system. In particular, the model adopts the concept of water balance, bringing a relatively simple and intuitive idea. Also, the research compares the two methods in the surface water balance calculation. One is based on Green-Ampt equation, and the other is under the SCS curve number calculation. A green roof experiment is designed to collect weather data and water discharge. Then, the proposed model is verified with these observed data; furthermore, the parameters using in the model are calibrated to find appropriate values in the green roof hydrologic simulation. This research proposes a simple physical based hydrologic model and the measures to determine parameters for the model.
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.
Applying Atmospheric Measurements to Constrain Parameters of Terrestrial Source Models
Hyer, E. J.; Kasischke, E. S.; Allen, D. J.
2004-12-01
Quantitative inversions of atmospheric measurements have been widely applied to constrain atmospheric budgets of a range of trace gases. Experiments of this type have revealed persistent discrepancies between 'bottom-up' and 'top-down' estimates of source magnitudes. The most common atmospheric inversion uses the absolute magnitude as the sole parameter for each source, and returns the optimal value of that parameter. In order for atmospheric measurements to be useful for improving 'bottom-up' models of terrestrial sources, information about other properties of the sources must be extracted. As the density and quality of atmospheric trace gas measurements improve, examination of higher-order properties of trace gas sources should become possible. Our model of boreal forest fire emissions is parameterized to permit flexible examination of the key uncertainties in this source. Using output from this model together with the UM CTM, we examined the sensitivity of CO concentration measurements made by the MOPITT instrument to various uncertainties in the boreal source: geographic distribution of burned area, fire type (crown fires vs. surface fires), and fuel consumption in above-ground and ground-layer fuels. Our results indicate that carefully designed inversion experiments have the potential to help constrain not only the absolute magnitudes of terrestrial sources, but also the key uncertainties associated with 'bottom-up' estimates of those sources.
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
arc
age at measurement were found to be significant (P < 0.05) in all cases. Age of dam was also ... between log likelihoods was greater than the critical value the inclusion of the effect was considered significant. .... and Kleiber ratio of Boer goat and for ADG in the first 30 days of two breeds of sheep, respectively. However, the ...
DEFF Research Database (Denmark)
Christensen, Steen; Doherty, John
2008-01-01
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...... nonlinear functions. Recommendations concerning the use of pilot points and singular value decomposition in real-world groundwater model calibration are finally given. (c) 2008 Elsevier Ltd. All rights reserved....
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.
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.
MATHEMATICAL MODELING OF FLOW PARAMETERS FOR SINGLE WIND TURBINE
Directory of Open Access Journals (Sweden)
2016-01-01
Full Text Available It is known that on the territory of the Russian Federation the construction of several large wind farms is planned. The tasks connected with design and efficiency evaluation of wind farm work are in demand today. One of the possible directions in design is connected with mathematical modeling. The method of large eddy simulation developed within the direction of computational hydrodynamics allows to reproduce unsteady structure of the flow in details and to determine various integrated values. The calculation of work for single wind turbine installation by means of large eddy simulation and Actuator Line Method along the turbine blade is given in this work. For problem definition the numerical method in the form of a box was considered and the adapted unstructured grid was used.The mathematical model included the main equations of continuity and momentum equations for incompressible fluid. The large-scale vortex structures were calculated by means of integration of the filtered equations. The calculation was carried out with Smagorinsky model for determination of subgrid scale turbulent viscosity. The geometrical parametersof wind turbine were set proceeding from open sources in the Internet.All physical values were defined at center of computational cell. The approximation of items in equations was ex- ecuted with the second order of accuracy for time and space. The equations for coupling velocity and pressure were solved by means of iterative algorithm PIMPLE. The total quantity of the calculated physical values on each time step was equal to 18. So, the resources of a high performance cluster were required.As a result of flow calculation in wake for the three-bladed turbine average and instantaneous values of velocity, pressure, subgrid kinetic energy and turbulent viscosity, components of subgrid stress tensor were worked out. The re- ceived results matched the known results of experiments and numerical simulation, testify the opportunity
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)
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.
Evaluation of the 235U resonance parameters to fit the standard recommended values
Directory of Open Access Journals (Sweden)
Leal Luiz
2017-01-01
Full Text Available A great deal of effort has been dedicated to the revision of the standard values in connection with the neutron interaction for some actinides. While standard data compilation are available for decades nuclear data evaluations included in existing nuclear data libraries (ENDF, JEFF, JENDL, etc. do not follow the standard recommended values. Indeed, the majority of evaluations for major actinides do not conform to the standards whatsoever. In particular, for the n + 235U interaction the only value in agreement with the standard is the thermal fission cross section. A resonance re-evaluation of the n + 235U interaction has been performed to address the issues regarding standard values in the energy range from 10−5 eV to 2250 eV. Recently, 235U fission cross-section measurements have been performed at the CERN Neutron Time-of-Flight facility (TOF, known as n_TOF, in the energy range from 0.7 eV to 10 keV. The data were normalized according to the recommended standard of the fission integral in the energy range 7.8 eV to 11 eV. As a result, the n_TOF averaged fission cross sections above 100 eV are in good agreement with the standard recommended values. The n_TOF data were included in the 235U resonance analysis that was performed with the code SAMMY. In addition to the average standard values related to the fission cross section, standard thermal values for fission, capture, and elastic cross sections were also included in the evaluation. This paper presents the procedure used for re-evaluating the 235U resonance parameters including the recommended standard values as well as new cross section measurements.
Evaluation of the 235U resonance parameters to fit the standard recommended values
Leal, Luiz; Noguere, Gilles; Paradela, Carlos; Durán, Ignacio; Tassan-Got, Laurent; Danon, Yaron; Jandel, Marian
2017-09-01
A great deal of effort has been dedicated to the revision of the standard values in connection with the neutron interaction for some actinides. While standard data compilation are available for decades nuclear data evaluations included in existing nuclear data libraries (ENDF, JEFF, JENDL, etc.) do not follow the standard recommended values. Indeed, the majority of evaluations for major actinides do not conform to the standards whatsoever. In particular, for the n + 235U interaction the only value in agreement with the standard is the thermal fission cross section. A resonance re-evaluation of the n + 235U interaction has been performed to address the issues regarding standard values in the energy range from 10-5 eV to 2250 eV. Recently, 235U fission cross-section measurements have been performed at the CERN Neutron Time-of-Flight facility (TOF), known as n_TOF, in the energy range from 0.7 eV to 10 keV. The data were normalized according to the recommended standard of the fission integral in the energy range 7.8 eV to 11 eV. As a result, the n_TOF averaged fission cross sections above 100 eV are in good agreement with the standard recommended values. The n_TOF data were included in the 235U resonance analysis that was performed with the code SAMMY. In addition to the average standard values related to the fission cross section, standard thermal values for fission, capture, and elastic cross sections were also included in the evaluation. This paper presents the procedure used for re-evaluating the 235U resonance parameters including the recommended standard values as well as new cross section measurements.
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.
Estimation of Kinetic Parameters in an Automotive SCR Catalyst Model
DEFF Research Database (Denmark)
Åberg, Andreas; Widd, Anders; Abildskov, Jens
2016-01-01
A challenge during the development of models for simulation of the automotive Selective Catalytic Reduction catalyst is the parameter estimation of the kinetic parameters, which can be time consuming and problematic. The parameter estimation is often carried out on small-scale reactor tests...
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.
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.
Estimation of Parameters in Latent Class Models with Constraints on the Parameters.
Paulson, James A.
This paper reviews the application of the EM Algorithm to marginal maximum likelihood estimation of parameters in the latent class model and extends the algorithm to the case where there are monotone homogeneity constraints on the item parameters. It is shown that the EM algorithm can be used to obtain marginal maximum likelihood estimates of the…
Behavioural Pattern of Invertibility Parameter of Arima Model ...
African Journals Online (AJOL)
It was deduced that behaviour of invertibility parameter πidepends on the order of autoregressive part (p), the order of integrated part (d), positive and negative values of moving average parameter (ϑ). Journal of the Nigerian Association of Mathematical Physics, Volume 19 (November, 2011), pp 591 – 606 ...
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…
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
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.
Incremental parameter estimation of kinetic metabolic network models
Directory of Open Access Journals (Sweden)
Jia Gengjie
2012-11-01
Full Text Available Abstract Background An efficient and reliable parameter estimation method is essential for the creation of biological models using ordinary differential equation (ODE. Most of the existing estimation methods involve finding the global minimum of data fitting residuals over the entire parameter space simultaneously. Unfortunately, the associated computational requirement often becomes prohibitively high due to the large number of parameters and the lack of complete parameter identifiability (i.e. not all parameters can be uniquely identified. Results In this work, an incremental approach was applied to the parameter estimation of ODE models from concentration time profiles. Particularly, the method was developed to address a commonly encountered circumstance in the modeling of metabolic networks, where the number of metabolic fluxes (reaction rates exceeds that of metabolites (chemical species. Here, the minimization of model residuals was performed over a subset of the parameter space that is associated with the degrees of freedom in the dynamic flux estimation from the concentration time-slopes. The efficacy of this method was demonstrated using two generalized mass action (GMA models, where the method significantly outperformed single-step estimations. In addition, an extension of the estimation method to handle missing data is also presented. Conclusions The proposed incremental estimation method is able to tackle the issue on the lack of complete parameter identifiability and to significantly reduce the computational efforts in estimating model parameters, which will facilitate kinetic modeling of genome-scale cellular metabolism in the future.
Sound propagation and absorption in foam - A distributed parameter model.
Manson, L.; Lieberman, S.
1971-01-01
Liquid-base foams are highly effective sound absorbers. A better understanding of the mechanisms of sound absorption in foams was sought by exploration of a mathematical model of bubble pulsation and coupling and the development of a distributed-parameter mechanical analog. A solution by electric-circuit analogy was thus obtained and transmission-line theory was used to relate the physical properties of the foams to the characteristic impedance and propagation constants of the analog transmission line. Comparison of measured physical properties of the foam with values obtained from measured acoustic impedance and propagation constants and the transmission-line theory showed good agreement. We may therefore conclude that the sound propagation and absorption mechanisms in foam are accurately described by the resonant response of individual bubbles coupled to neighboring bubbles.
Modeling Source Water Threshold Exceedances with Extreme Value Theory
Rajagopalan, B.; Samson, C.; Summers, R. S.
2016-12-01
Variability in surface water quality, influenced by seasonal and long-term climate changes, can impact drinking water quality and treatment. In particular, temperature and precipitation can impact surface water quality directly or through their influence on streamflow and dilution capacity. Furthermore, they also impact land surface factors, such as soil moisture and vegetation, which can in turn affect surface water quality, in particular, levels of organic matter in surface waters which are of concern. All of these will be exacerbated by anthropogenic climate change. While some source water quality parameters, particularly Total Organic Carbon (TOC) and bromide concentrations, are not directly regulated for drinking water, these parameters are precursors to the formation of disinfection byproducts (DBPs), which are regulated in drinking water distribution systems. These DBPs form when a disinfectant, added to the water to protect public health against microbial pathogens, most commonly chlorine, reacts with dissolved organic matter (DOM), measured as TOC or dissolved organic carbon (DOC), and inorganic precursor materials, such as bromide. Therefore, understanding and modeling the extremes of TOC and Bromide concentrations is of critical interest for drinking water utilities. In this study we develop nonstationary extreme value analysis models for threshold exceedances of source water quality parameters, specifically TOC and bromide concentrations. In this, the threshold exceedances are modeled as Generalized Pareto Distribution (GPD) whose parameters vary as a function of climate and land surface variables - thus, enabling to capture the temporal nonstationarity. We apply these to model threshold exceedance of source water TOC and bromide concentrations at two locations with different climate and find very good performance.
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
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 ...
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...
Exploring the interdependencies between parameters in a material model.
Energy Technology Data Exchange (ETDEWEB)
Silling, Stewart Andrew; Fermen-Coker, Muge
2014-01-01
A method is investigated to reduce the number of numerical parameters in a material model for a solid. The basis of the method is to detect interdependencies between parameters within a class of materials of interest. The method is demonstrated for a set of material property data for iron and steel using the Johnson-Cook plasticity model.
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
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...
Estimation of shape model parameters for 3D surfaces
DEFF Research Database (Denmark)
Erbou, Søren Gylling Hemmingsen; Darkner, Sune; Fripp, Jurgen
2008-01-01
is applied to a database of 3D surfaces from a section of the porcine pelvic bone extracted from 33 CT scans. A leave-one-out validation shows that the parameters of the first 3 modes of the shape model can be predicted with a mean difference within [-0.01,0.02] from the true mean, with a standard deviation......Statistical shape models are widely used as a compact way of representing shape variation. Fitting a shape model to unseen data enables characterizing the data in terms of the model parameters. In this paper a Gauss-Newton optimization scheme is proposed to estimate shape model parameters of 3D...... surfaces using distance maps, which enables the estimation of model parameters without the requirement of point correspondence. For applications with acquisition limitations such as speed and cost, this formulation enables the fitting of a statistical shape model to arbitrarily sampled data. The method...
One-Step Dynamic Classifier Ensemble Model for Customer Value Segmentation with Missing Values
Jin Xiao; Bing Zhu; Geer Teng; Changzheng He; Dunhu Liu
2014-01-01
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 classif...
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)
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 and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
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.
DEFF Research Database (Denmark)
Ottosen, T. B.; Ketzel, Matthias; Skov, H.
2016-01-01
Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street...... of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to successfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach...
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
Directory of Open Access Journals (Sweden)
TMA. Pantoja
Full Text Available The Amazonian manatee, Trichechus inunguis (Natterer 1883 is endemic to the Amazon Basin and is currently considered a vulnerable species. In order to establish normality ranges of urinary parameters to help monitor the health of this species in captivity, chemical urinalyses were performed on twelve males and nine females of various age groups. Urine was collected once a month for twelve months in the tanks just after being drained, by placing stainless steel containers under the genital slit of females and applying abdominal massages to males in order to stimulate urination. Quantitative data of glucose, urea, creatinine, uric acid and amylase levels were obtained using colorimetric spectrophotometry. Dip strips were also useful for routine analyses, despite only providing qualitative results. Normal range to glucose levels, regardless of sex or age class, was 3.0 to 3.6 mg.dL-1, coinciding with qualitative values of glucose measured by dip strips. Statistical differences observed in some parameter levels suggest that some urine parameters analysed must take into consideration the sex and the age class of the animal studied, being these differences less remarkable in creatinine and amylase levels. To this last one, statistical difference was detected only in the calve's urine (7.0 to 11.5 mg.dL-1 compared to other age classes samples (4.1 to 5.3 mg.dL-1. The results presented here may be used as comparative data in future research on urinalysis in related species.
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.)
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
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. ...
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.
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
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.
Environment modeling using runtime values for JPF-Android
CSIR Research Space (South Africa)
Van der Merwe, H
2015-11-01
Full Text Available 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...
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…
The S-parameter in Holographic Technicolor Models
Agashe, Kaustubh; Grojean, Christophe; Reece, Matthew
2007-01-01
We study the S parameter, considering especially its sign, in models of electroweak symmetry breaking (EWSB) in extra dimensions, with fermions localized near the UV brane. Such models are conjectured to be dual to 4D strong dynamics triggering EWSB. The motivation for such a study is that a negative value of S can significantly ameliorate the constraints from electroweak precision data on these models, allowing lower mass scales (TeV or below) for the new particles and leading to easier discovery at the LHC. We first extend an earlier proof of S>0 for EWSB by boundary conditions in arbitrary metric to the case of general kinetic functions for the gauge fields or arbitrary kinetic mixing. We then consider EWSB in the bulk by a Higgs VEV showing that S is positive for arbitrary metric and Higgs profile, assuming that the effects from higher-dimensional operators in the 5D theory are sub-leading and can therefore be neglected. For the specific case of AdS_5 with a power law Higgs profile, we also show that S ~ ...
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
2007-01-01
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil with focus on the horizontal sliding and rocking. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines......-parameter models with respect to the prediction of the maximum response during excitation and the geometrical damping related to free vibrations of a footing....
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
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
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....
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.
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.
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.
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.
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.)
Do Lumped-Parameter Models Provide the Correct Geometrical Damping?
DEFF Research Database (Denmark)
Andersen, Lars
This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation of struct......This paper concerns the formulation of lumped-parameter models for rigid footings on homogenous or stratified soil. Such models only contain a few degrees of freedom, which makes them ideal for inclusion in aero-elastic codes for wind turbines and other models applied to fast evaluation...... 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...
Lino, Jéssica B R; Rocha, Eduardo P; Ramalho, Teodorico C
2017-06-15
Quantum computing is the field of science that uses quantum-mechanical phenomena, such as superposition and entanglement, to perform operations on data. The fundamental information unit used in quantum computing is the quantum bit or qubit. It is well-known that quantum computers could theoretically be able to solve problems much more quickly than any classical computers. Currently, the first and still the most successful implementations of quantum information processing (QIP) have been based on nuclear spins in liquids. However, molecules that enable many qubits NMR QIP implementations should meet some conditions: have large chemical shifts and be appropriately dispersed for qubit addressability, appreciable spin-spin coupling between any pair of spins, and a long relaxation time. In this line, benzyldene-2,3-dihydro-1H-[1,3]diphosphole (BDF) derivatives have been theoretically tested for maximizing large chemical shifts, spin-spin coupling, and minimizing the hyperfine coupling constant. Thus, the structures were optimized at the B3LYP/6-311G(d,p) level and showed a significant similarity with the experimental geometrical parameters. The NMR spectroscopic parameters (δ and J) were calculated with six different DFT functionals. The τ-HCTH/6-31G(2d) level is in better agreement with the experimental data of 31 P and 13 C chemical shifts, while PCM-B3LYP/cc-pVDZ level shows a decrease on deviation between calculated and experimental values for P-P and P-C SSCC. The surface response technique was employed to rationalize how the hyperfine constant varies with the chemical shifts and coupling constants values. From our findings, BDF-NO 2 was the best candidate for NMR quantum computations (NMR-QC) among the studied series.
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.
Parameter estimation for groundwater models under uncertain irrigation data
Demissie, Yonas; Valocchi, Albert J.; Cai, Ximing; Brozovic, Nicholas; Senay, Gabriel; Gebremichael, Mekonnen
2015-01-01
The success of modeling groundwater is strongly influenced by the accuracy of the model parameters that are used to characterize the subsurface system. However, the presence of uncertainty and possibly bias in groundwater model source/sink terms may lead to biased estimates of model parameters and model predictions when the standard regression-based inverse modeling techniques are used. This study first quantifies the levels of bias in groundwater model parameters and predictions due to the presence of errors in irrigation data. Then, a new inverse modeling technique called input uncertainty weighted least-squares (IUWLS) is presented for unbiased estimation of the parameters when pumping and other source/sink data are uncertain. The approach uses the concept of generalized least-squares method with the weight of the objective function depending on the level of pumping uncertainty and iteratively adjusted during the parameter optimization process. We have conducted both analytical and numerical experiments, using irrigation pumping data from the Republican River Basin in Nebraska, to evaluate the performance of ordinary least-squares (OLS) and IUWLS calibration methods under different levels of uncertainty of irrigation data and calibration conditions. The result from the OLS method shows the presence of statistically significant (p model predictions that persist despite calibrating the models to different calibration data and sample sizes. However, by directly accounting for the irrigation pumping uncertainties during the calibration procedures, the proposed IUWLS is able to minimize the bias effectively without adding significant computational burden to the calibration processes.
Cognitive and value parameters of students’ perceptions of the effects of psychoactive substances
Directory of Open Access Journals (Sweden)
Dontsov, Aleksander I.
2016-09-01
Full Text Available This article sets forth the main results of a study analyzing attitudes toward psychoactivesubstance (PAS effects. These findings demonstrate the conditionality of social, historic, and cultural views of PAS effects. Despite the threat posed by increasing high school and university students’ drug involvement, exploration of this phenomenon in the format of scientific discourse has been limited so far. In 2014–2015, in Yekaterinburg, Moscow, and Krasnoyarsk a survey to evaluate perceptions of high school and university students about PAS effects was conducted (289 respondents, aged 16–22.The methods used included the semantic differential (Peabody Picture Vocabulary Test modified by A.G. Shmelyov, a modified version of the Rokeach Value Survey, word associations, and content analysis. The use of psychoactive substances is a specific social practice emerging in a certain social context that includes both drug-addicted and PAS-free young people. Examination of the factors affecting the formation of views about PAS effects and the dynamics of youth values is possible by using a bio-psycho-socio paradigm for performing a complex analysis of cognitive, behavioral, and value parameters. As documented in the respondents’ perceptions, distinctive features that are characteristic of drug addicts and that are seen in their behavior area loss of control over behavior, emotions, and volition; changes in value systems; and a tendency to develop a manipulative communication style. Within the system of their social perceptions the respondents endowed drug-addicted persons with pronounced negative characteristics (“aggressiveness,” “addiction,” “stupidity,” “light-mindedness”. Still, they stated that drug abusers are capable of being active, decisive, cheerful, generous, and flexible. The value analysis demonstrated that terminal values appreciated by the school and university students included health, true friends, love, happy family
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.
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.
Multiple small-angle neutron scattering for an arbitrary value of the Born parameter
International Nuclear Information System (INIS)
Bogdanov, S.G.; Men'shikov, A. Z.
2000-01-01
Computer calculations are made of the intensity of multiple small-angle neutron scattering using the general Moliere formula over a wide range of variation of the Born parameter, embracing the diffraction and refraction regimes, and a transition region between diffraction and reflection. A comparison is made with approximate formulas obtained earlier by Maleev et al. in the limiting cases of the Born parameter α > 1 for the diffraction and refraction regimes, respectively. It is shown that over a wide range of values of α the results of the calculations using the approximate and general formulas are the same. The theoretical conclusions were checked experimentally using data from measurements of small-angle neutron scattering for the domain structure of ferromagnets. Measurements were made of the neutron beam broadening for samples of different thickness and these were used to determine the effective domain sizes in pure iron and nickel exposed to thermal treatment and plastic deformation, and also in the Invar alloys Fe 65 Ni 35 and Fe 3 Pt. An analysis is made of the angular dependence of magnetic small-angle neutron scattering at the asymptote
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
Unknown
parameters which exclusively represent interactions of the higher order systems. Such a procedure is presen- ted in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
... of parameters which exclusively represent interactions of the higher order systems. Such a procedure is presented in detail in this communication. Furthermore, the details of transformations required to express the model parameters in one basis from those defined in another basis for the same system are also presented.
Prior distributions for item parameters in IRT models
Matteucci, M.; S. Mignani, Prof.; Veldkamp, Bernard P.
2012-01-01
The focus of this article is on the choice of suitable prior distributions for item parameters within item response theory (IRT) models. In particular, the use of empirical prior distributions for item parameters is proposed. Firstly, regression trees are implemented in order to build informative
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
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
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.
Input parameters for LEAP and analysis of the Model 22C data base
Energy Technology Data Exchange (ETDEWEB)
Stewart, L.; Goldstein, M.
1981-05-01
The input data for the Long-Term Energy Analysis Program (LEAP) employed by EIA for projections of long-term energy supply and demand in the US were studied and additional documentation provided. Particular emphasis has been placed on the LEAP Model 22C input data base, which was used in obtaining the output projections which appear in the 1978 Annual Report to Congress. Definitions, units, associated model parameters, and translation equations are given in detail. Many parameters were set to null values in Model 22C so as to turn off certain complexities in LEAP; these parameters are listed in Appendix B along with parameters having constant values across all activities. The values of the parameters for each activity are tabulated along with the source upon which each parameter is based - and appropriate comments provided, where available. The structure of the data base is briefly outlined and an attempt made to categorize the parameters according to the methods employed for estimating the numerical values. Due to incomplete documentation and/or lack of specific parameter definitions, few of the input values could be traced and uniquely interpreted using the information provided in the primary and secondary sources. Input parameter choices were noted which led to output projections which are somewhat suspect. Other data problems encountered are summarized. Some of the input data were corrected and a revised base case was constructed. The output projections for this revised case are compared with the Model 22C output for the year 2020, for the Transportation Sector. LEAP could be a very useful tool, especially so in the study of emerging technologies over long-time frames.
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...
Stochastic hyperelastic modeling considering dependency of material parameters
Caylak, Ismail; Penner, Eduard; Dridger, Alex; Mahnken, Rolf
2018-03-01
This paper investigates the uncertainty of a hyperelastic model by treating random material parameters as stochastic variables. For its stochastic discretization a polynomial chaos expansion (PCE) is used. An important aspect in our work is the consideration of stochastic dependencies in the stochastic modeling of Ogden's material model. To this end, artificial experiments are generated using the auto-regressive moving average process based on real experiments. The parameter identification for all data provides statistics of Ogden's material parameters, which are subsequently used for stochastic modeling. Stochastic dependencies are incorporated into the PCE using a Nataf transformation from dependent distributed random variables to independent standard normal distributed ones. The representative numerical example shows that our proposed method adequately takes into account the stochastic dependencies of Ogden's material parameters.
A compact cyclic plasticity model with parameter evolution
DEFF Research Database (Denmark)
Krenk, Steen; Tidemann, L.
2017-01-01
by the Armstrong–Frederick model, contained as a special case of the present model for a particular choice of the shape parameter. In contrast to previous work, where shaping the stress-strain loops is derived from multiple internal stress states, this effect is here represented by a single parameter......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...
Parameter Estimation for the Thurstone Case III Model.
Mackay, David B.; Chaiy, Seoil
1982-01-01
The ability of three estimation criteria to recover parameters of the Thurstone Case V and Case III models from comparative judgment data was investigated via Monte Carlo techniques. Significant differences in recovery are shown to exist. (Author/JKS)
Improved parameter estimation for hydrological models using weighted object functions
Stein, A.; Zaadnoordijk, W.J.
1999-01-01
This paper discusses the sensitivity of calibration of hydrological model parameters to different objective functions. Several functions are defined with weights depending upon the hydrological background. These are compared with an objective function based upon kriging. Calibration is applied to
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.
Regular boundary value problems for the heat equation with scalar parameters
Kalmenov, Tynysbek Sh.; Besbaev, Gani; Medetbekova, Ryskul
2017-09-01
This paper belongs to the general theory of well-posed initial-boundary value problems for parabolic equations. The classical construction of a boundary value problem is as follows: an equation and a boundary condition are given. It is necessary to investigate the solvability of this problem and properties of the solution if it exists (in the sense of belonging to some space). Beginning with the papers of J. von Neumann and M.I. Vishik (1951), there exists another more general approach: an equation and a space are given, right-hand parts of the equation and boundary conditions, and a solution must belong to this space. It is necessary to describe all the boundary conditions, for which the problem is correctly solvable in this space. Further development of this theory was given by M. Otelbaev, who constructed a complete theory for ordinary differential operators and for symmetric semibounded operators in a Banach space. In this paper we find regular solution of the regular boundary problem for the heat equation with scalar parameter.
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.
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.
Spatial scale effects on model parameter estimation and predictive uncertainty in ungauged basins
CSIR Research Space (South Africa)
Hughes, DA
2013-06-01
Full Text Available The most appropriate scale to use for hydrological modelling depends on the structure of the chosen model, the purpose of the results and the resolution of the available data used to quantify parameter values and provide the climatic forcing data...
Generic NICA-Donnan model parameters for metal-ion binding by humic substances
Milne, C.J.; Kinniburgh, D.G.; Riemsdijk, van W.H.; Tipping, E.
2003-01-01
A total of 171 datasets of literature and experimental data for metal-ion binding by fulvic and humic acids have been digitized and re-analyzed using the NICA-Donnan model. Generic parameter values have been derived that can be used for modeling in the absence of specific metal-ion binding
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.
Gatimel, N; Léandri, R D; Marino, L; Esquerre-Lamare, C; Parinaud, J
2014-11-01
Can the assessment of sperm vacuoles at high magnification contribute to the explanation of idiopathic infertility? The characteristics of sperm head vacuoles (number, area, position) are no different between fertile controls and patients with unexplained infertility. Until now, the assessment of sperm head vacuoles has been focused on a therapeutic goal in the intracytoplasmic morphologically selected sperm injection (IMSI) procedure, but it could be pertinent as a new diagnostic tool for the evaluation of male fertility. This diagnostic test study with blind assessment included a population of 50 fertile men and 51 men with idiopathic infertility. They were selected from September 2011 to May 2013. Fertile men were within couples who had a spontaneous pregnancy in the last 2 years. Infertile men were within couples who had unexplained infertility and were consulting in our centre. After analysis of conventional sperm parameters, we investigated the number, position and area of sperm head vacuoles at high magnification (×6000) with interference contrast using an image analysis software. We also carried out a nuclear status analysis by terminal deoxynucleotidyl transferase-mediated dUTP nick end labelling assay (TUNEL), sperm chromatin structure assay (SCSA) and aniline blue staining. Concerning the vacuoles data, we did not find any significant difference between the two populations. We found no significant correlation between the vacuolar parameters (mean number of vacuoles, relative vacuole area and percentage of spermatozoa with large vacuoles) and either conventional semen parameters, male age or the data from the aniline blue staining, SCSA assay and TUNEL assay. Despite the fact all of the vacuole parameters values were identical in fertile and infertile men, we cannot totally exclude that a very small cause of unexplained infertilities could be related to an excess of sperm vacuoles. In line with its widely debated use as a therapeutic tool, sperm vacuole
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
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.
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Energy Technology Data Exchange (ETDEWEB)
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four
Luo, Chuan; Li, Zhaofu; Wu, Min; Jiang, Kaixia; Chen, Xiaomin; Li, Hengpeng
2017-09-01
Numerous parameters are used to construct the HSPF (Hydrological Simulation Program Fortran) model, which results in significant difficulty in calibrating the model. Parameter sensitivity analysis is an efficient method to identify important model parameters. Through this method, a model's calibration process can be simplified on the basis of understanding the model's structure. This study investigated the sensitivity of the flow and nutrient parameters of HSPF using the DSA (differential sensitivity analysis) method in the Xitiaoxi watershed, China. The results showed that flow was mostly affected by parameters related to groundwater and evapotranspiration, including DEEPFR (fraction of groundwater inflow to deep recharge), LZETP (lower-zone evapotranspiration parameter), and AGWRC (base groundwater recession), and most of the sensitive parameters had negative and nonlinear effects on flow. Additionally, nutrient components were commonly affected by parameters from land processes, including MON-SQOLIM (monthly values limiting storage of water quality in overland flow), MON-ACCUM (monthly values of accumulation), MON-IFLW-CONC (monthly concentration of water quality in interflow), and MON-GRND-CONC (monthly concentration of water quality in active groundwater). Besides, parameters from river systems, KATM20 (unit oxidation rate of total ammonia at 20 °C) had a negative and almost linear effect on ammonia concentration and MALGR (maximal unit algal growth rate for phytoplankton) had a negative and nonlinear effect on ammonia and orthophosphate concentrations. After calibrating these sensitive parameters, our model performed well for simulating flow and nutrient outputs, with R 2 and E NS (Nash-Sutcliffe efficiency) both greater than 0.75 for flow and greater than 0.5 for nutrient components. This study is expected to serve as a valuable complement to the documentation of the HSPF model to help users identify key parameters and provide a reference for performing
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.
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 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...
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.
Volckaert, Veerle; Vandermeulen, Eva; Duchateau, Luc; Daminet, Sylvie; Saunders, Jimmy H; Peremans, Kathelijne
2017-07-01
Objectives The outcome of radioiodine therapy in hyperthyroid cats is suspected to be influenced by multiple factors. The degree of activity of the thyroid gland, represented by uptake of sodium pertechnetate or tracer activities of radioiodine by the thyroid gland on thyroid scintigraphy, has been suggested in the literature as one of those. Thyroid gland pertechnetate uptake can be represented by (semi-)quantitative factors such as the thyroid to salivary gland (T/S) ratio, the thyroid to background (T/B) ratio and the percentage technetium uptake by the thyroid glands (%TcU). The aim of this study was to investigate a possible relationship between these thyroid scan parameters and radioiodine therapy outcome. Methods Sodium pertechnetate thyroid scans of 75 hyperthyroid cats were retrospectively evaluated and statistical analysis was performed with and without correction for injected radioiodine activity. Three different background regions of interest (ROIs) were used to calculate the T/B ratio and %TcU: 'neck', 'circle' and 'copy ROI'. Results Higher T/S ratios were found to be significantly related to a persistent hyperthyroid outcome in both analyses. For the T/S ratio, a threshold value of 5.4 was determined, with a sensitivity of 73% and a specificity of 59%. An increased risk for persistent hyperthyroidism compared with a final euthyroid outcome with an increased T/B circle ratio was only found to be significant without correction for the activity of radioiodine administered. For the %TcU no statistical significance was reached. Regarding a low total thyroxine outcome, no significant relationships with any of the investigated parameters were found. Conclusions and relevance The findings of this study suggest that semi-quantification of thyroid gland uptake is best performed using the T/S ratio. A T/S ratio ⩾5.4 is a possible indicator for an increased risk of persistent hyperthyroidism.
Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width
Directory of Open Access Journals (Sweden)
S. E. Tolwinski-Ward
2013-07-01
Full Text Available We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization.
Gorgoso-Varela, J. Javier; Rojo-Alboreca, Alberto
2014-01-01
International audience; & Context Families of the Gumbel (type I), Fréchet (type II) and Weibull (type III) distributions can be combined in the generalized extreme value (GEV) family of distributions. Maximum and minimum values of diameters in forest stands can be used in forest modelling, mainly to define parameters of the functions used in diameter class models as well as in some practical cases, such as modelling maximum diameters for sawing and processing purposes. & Aims The purpose of ...
Analyses of precooling parameters for a bottom flooding ECCS rewetting velocity model
International Nuclear Information System (INIS)
Chun, M.H.
1981-01-01
An extension work of the previous paper on the rewetting velocity model is presented. Application of the rewetting velocity model presented elsewhere requires a priori values of phi. In the absence of phi values, film boiling heat transfer coefficient (hsub(df)) and fog-film length (1) data are needed. To provide these informations, a modified Bromley's correlation is first derived and used to obtain hsub(df) values at higher pressure conditions. In addition, the analysis of the precooling parameters, such as phi and 1 is further extended using much more expensive PWR FLECHT data. Thus, the applicable range of the rewetting velocity model is further expanded in this work. (author)
Engineering the Complex-Valued Constitutive Parameters of Metamaterials for Perfect Absorption.
Wang, Pengwei; Chen, Naibo; Tang, Chaojun; Chen, Jing; Liu, Fanxin; Sheng, Saiqian; Yan, Bo; Sui, Chenghua
2017-12-01
We theoretically studied how to directly engineer the constitutive parameters of metamaterials for perfect absorbers of electromagnetic waves. As an example, we numerically investigated the necessary refractive index n and extinction coefficient k and the relative permittivity ε and permeability μ of a metamaterial anti-reflection layer, which could cancel the reflection from a hydrogenated amorphous silicon (α-Si:H) thin film on a metal substrate, within the visible wavelength range from 300 to 800 nm. We found that the metamaterial anti-reflection layer should have a negative refractive index (n 0) for long-wavelength visible light. The relative permittivity ε and permeability μ could be fitted by the Lorentz model, which exhibited electric and magnetic resonances, respectively.
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.
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
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.
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.
An evolutionary computing approach for parameter estimation investigation of a model for cholera.
Akman, Olcay; Schaefer, Elsa
2015-01-01
We consider the problem of using time-series data to inform a corresponding deterministic model and introduce the concept of genetic algorithms (GA) as a tool for parameter estimation, providing instructions for an implementation of the method that does not require access to special toolboxes or software. We give as an example a model for cholera, a disease for which there is much mechanistic uncertainty in the literature. We use GA to find parameter sets using available time-series data from the introduction of cholera in Haiti and we discuss the value of comparing multiple parameter sets with similar performances in describing the data.
Mackay, D. Scott; Ewers, Brent E.; Loranty, Michael M.; Kruger, Eric L.; Samanta, Sudeep
2012-04-01
SummaryBig-leaf models of transpiration are based on the hypothesis that structural heterogeneity within forest canopies can be ignored at stand or larger scales. However, the adoption of big-leaf models is de facto rather than de jure, as forests are never structurally or functionally homogeneous. We tested big-leaf models both with and without modification to include canopy gaps, in a heterogeneous quaking aspen stand having a range of canopy densities. Leaf area index (L) and canopy closure were obtained from biometric data, stomatal conductance parameters were obtained from sap flux measurements, while leaf gas exchange data provided photosynthetic parameters. We then rigorously tested model-data consistency by incrementally starving the models of these measured parameters and using Bayesian Markov Chain Monte Carlo simulation to retrieve the withheld parameters. Model acceptability was quantified with Deviance Information Criterion (DIC), which penalized model accuracy by the number of retrieved parameters. Big-leaf models overestimated canopy transpiration with increasing error as canopy density declined, but models that included gaps had minimal error regardless of canopy density. When models used measured L the other parameters were retrieved with minimal bias. This showed that simple canopy models could predict transpiration in data scarce regions where only L was measured. Models that had L withheld had the lowest DIC values suggesting that they were the most acceptable models. However, these models failed to retrieve unbiased parameter estimates indicating a mismatch between model structure and data. By quantifying model structure and data requirements this new approach to evaluating model-data fusion has advanced the understanding of canopy transpiration.
Modeling churn using customer lifetime value
Glady, Nicolas; Baesens, Bart; Croux, Christophe
2009-01-01
The definition and modeling of customer loyalty have been central issues in customer relationship management since many years. Recent papers propose solutions to detect customers that are becoming less loyal, also called churners. The churner status is then defined as a function of the volume of commercial transactions. In the context of a Belgian retail financial service company, our first contribution is to redefine the notion of customer loyalty by considering it from a customer-centric vi...
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.
Procedures for parameter estimates of computational models for localized failure
Iacono, C.
2007-01-01
In the last years, many computational models have been developed for tensile fracture in concrete. However, their reliability is related to the correct estimate of the model parameters, not all directly measurable during laboratory tests. Hence, the development of inverse procedures is needed, that
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
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
Bandorski, Dirk; Bogossian, Harilaos; Ecke, Anja; Wiedenroth, Christoph; Gruenig, Ekkehard; Benjamin, Nicola; Arlt, Matthias; Seeger, Werner; Mayer, Eckhard; Ghofrani, Ardeschir; Hoeltgen, Reinhard; Gall, Henning
2016-01-01
Several studies have analyzed arrhythmias in patients with pulmonary hypertension (PH) and increased P-wave duration was identified as a risk factor for development of atrial fibrillation (AF). We retrospectively analyzed the incidence of arrhythmias in patients with an initial diagnosis of PH during long-term follow-up and assessed the prognostic value of electrocardiography (ECG) data. Data from 167 patients were analyzed (Dana Point Classification: Group 1: 59 patients, Group 2: 28 patients, Group 3: 39 patients, Group 4: 41 patients). Clinical, 6-min-ute walk distance test, echocardiography and right heart catheterization data were collected, and baseline/follow-up ECGs were analyzed. Baseline ECGs revealed sinus rhythm in 137 patients. Thirteen patients had newly onset AF during follow-up. In 30 patients, baseline ECG showed AF. Patients with baseline AF showed higher atrial diameters and higher right atrial pressure. Patients with P-wave du-ration > 0.11 s had shorter survival. Other ECG parameters (PQ-interval, QRS-width, QT-/ /QTc-interval) were not associated with survival. Mean survival times were 79.4 ± 5.4 months (sinus rhythm), 64.4 ± 12.9 months (baseline AF) and 58.8 ± 8.9 months (newly onset AF during follow-up) (p = 0.565). Atrial fibrillation predict adverse prognosis in patients with PH and a longer P-wave (> 0.11 s) is associated with shorter survival time.
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.
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.
THREE-PARAMETER CREEP DAMAGE CONSTITUTIVE MODEL AND ITS APPLICATION IN HYDRAULIC TUNNELLING
Directory of Open Access Journals (Sweden)
Luo Gang
2016-10-01
Full Text Available Rock deformation is a time-dependent process, generally referred to as rheology. Especially for soft rock strata, design and construction of tunnel shall take full account of rheological properties of adjoining rocks. Based on classic three-parameter HK model (generalized Kelvin model, this paper proposes a three-parameter H-K damage model of which parameters attenuate with increase of equivalent strain, provides attenuation equation of model parameters in the first, second and third stage of creep deformation and introduces equivalent strain threshold value. When the equivalent strain is greater than the threshold value, the third stage of accelerating creep will be conducted. The three-parameter H-K damage model is used for numerical calculation of finite difference method FLAC3D and deformation features of soft rock with time under high ground stress are described based on diversion tunnel project of Jinping Hydropower Station, of which model parameters can be obtained by back analysis according to measured site data and BP neural network.
Out, Lia; Vrijkotte, Tanja G M; Van Soest, Arthur J.; Bobbert, Maarten F.
This study investigates the influence of parameter values of the human triceps surae muscle on the torque-angle relationship. The model used consisted of three units, each containing a contractile, a series elastic and a parallel elastic element. Parameter values were based on morphological
Out, L.; Vrijkotte, T. G.; van Soest, A. J.; Bobbert, M. F.
1996-01-01
This study investigates the influence of parameter values of the human triceps surae muscle on the torque-angle relationship. The model used consisted of three units, each containing a contractile, a series elastic and a parallel elastic element. Parameter values were based on morphological
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...
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.
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.
Extreme value modelling of storm damage in Swedish forests
Directory of Open Access Journals (Sweden)
A. Bengtsson
2007-09-01
Full Text Available Forests cover about 56% of the land area in Sweden and forest damage due to strong winds has been a recurring problem. In this paper we analyse recorded storm damage in Swedish forests for the years 1965–2007. During the period 48 individual storm events with a total damage of 164 Mm³ have been reported with the severe storm on 8 to 9 January 2005, as the worst with 70 Mm³ damaged forest. For the analysis, storm damage data has been normalised to account for the increase in total forest volume over the period.
We show that, within the framework of statistical extreme value theory, a Poisson point process model can be used to describe these storm damage events. Damage data supports a heavy-tailed distribution with great variability in damage for the worst storm events. According to the model, and in view of available data, the return period for a storm with damage in size of the severe storm of January 2005 is approximately 80 years, i.e. a storm with damage of this magnitude will happen, on average, once every eighty years.
To investigate a possible temporal trend, models with time-dependent parameters have been analysed but give no conclusive evidence of an increasing trend in the normalised storm damage data for the period. Using a non-parametric approach with a kernel based local-likelihood method gives the same result.
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.
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.)
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)
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.
Control of the SCOLE configuration using distributed parameter models
Hsiao, Min-Hung; Huang, Jen-Kuang
1994-01-01
A continuum model for the SCOLE configuration has been derived using transfer matrices. Controller designs for distributed parameter systems have been analyzed. Pole-assignment controller design is considered easy to implement but stability is not guaranteed. An explicit transfer function of dynamic controllers has been obtained and no model reduction is required before the controller is realized. One specific LQG controller for continuum models had been derived, but other optimal controllers for more general performances need to be studied.
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.
2013-01-01
Background Parameter estimation from experimental data is critical for mathematical modeling of protein regulatory networks. For realistic networks with dozens of species and reactions, parameter estimation is an especially challenging task. In this study, we present an approach for parameter estimation that is effective in fitting a model of the budding yeast cell cycle (comprising 26 nonlinear ordinary differential equations containing 126 rate constants) to the experimentally observed phenotypes (viable or inviable) of 119 genetic strains carrying mutations of cell cycle genes. Results Starting from an initial guess of the parameter values, which correctly captures the phenotypes of only 72 genetic strains, our parameter estimation algorithm quickly improves the success rate of the model to 105–111 of the 119 strains. This success rate is comparable to the best values achieved by a skilled modeler manually choosing parameters over many weeks. The algorithm combines two search and optimization strategies. First, we use Latin hypercube sampling to explore a region surrounding the initial guess. From these samples, we choose ∼20 different sets of parameter values that correctly capture wild type viability. These sets form the starting generation of differential evolution that selects new parameter values that perform better in terms of their success rate in capturing phenotypes. In addition to producing highly successful combinations of parameter values, we analyze the results to determine the parameters that are most critical for matching experimental outcomes and the most competitive strains whose correct outcome with a given parameter vector forces numerous other strains to have incorrect outcomes. These “most critical parameters” and “most competitive strains” provide biological insights into the model. Conversely, the “least critical parameters” and “least competitive strains” suggest ways to reduce the computational complexity of the
Ackleh, Azmy S; Chellamuthu, Vinodh K; Ito, Kazufumi
2015-04-01
We study a quasilinear hierarchically size-structured population model presented in [4]. In this model the growth, mortality and reproduction rates are assumed to depend on a function of the population density. In [4] we showed that solutions to this model can become singular (measure-valued) in finite time even if all the individual parameters are smooth. Therefore, in this paper we develop a first order finite difference scheme to compute these measure-valued solutions. Convergence analysis for this method is provided. We also develop a high resolution second order scheme to compute the measure-valued solution of the model and perform a comparative study between the two schemes.
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.
[The diagnostic value and limits of diagnostic parameters for Wilson's disease].
Yang, X
2017-12-20
Wilson disease (WD) is a rare and treatable genetic disorder. This paper describes the new advances and author's long-term experiences in the diagnosis of WD. The characteristics in clinical and routine tests are: the age of presentation can be quite broad, the WD could not be excluded based on age only; the patients usually have mild digestive symptoms but obvious chronic liver disease signs; liver function tests may reveal normal or a mild elevation in bilirubin, ALT and AST, but quite abnormal in serum albumin and prothrombin time in most patients; Coombs-negative hemolytic anemia, normal or markedly subnormal serum alkaline phosphatase (typically present in 72.2% of patients at the time of diagnosis, the positive rate is significantly higher in patients with a neurological presentation (93.4%) than patients presenting with liver disease (63.3%), however, they are usually absent in children under 6 years old, occasionly present in patients with chronic cholestatic liver disease. The mean serum ceruloplamin level in WD patients is 71.1 ± 48.7 mg/L, the level is presentation in 86.7% of patients with WD, but also in 22% of Patients with certain chronic liver diseases, the sensitivity of penicillamine challenge test is lower than basal urinary copper excretion, however, the specificity is significantly higher than former (97% versus 78%). Hepatic copper determination remains the gold standard for the diagnosis of WD. We have designed a standard method for hepatic copper determination. The most useful cut-off value is 209 g/g dry wt using our method, with the sensitivity of 99.4%, and specificity of 96.1%. However, long-standing hepatic failure and or obstruction can cause heptic copper elevations into the WD area. In recent years, direct complete DNA sequencing has become easy, rapid, less expensive and commercially available. Currently reported mutation detection rate is 90%, the specificity is almost 100%. The limitation to the method has been the ability to
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
Directory of Open Access Journals (Sweden)
Wintoft Peter
2017-01-01
Full Text Available 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
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
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.
Prediction of genotypic values and estimation of genetic parameters in common bean
Directory of Open Access Journals (Sweden)
Alisson Fernando Chiorato
2008-06-01
Full Text Available Eighteen common bean (Phaseolus vulgaris L. genotypes were evaluated in 25 environments of the state of São Paulo in 2001 and 2002. The estimation of genetic parameters by the Restricted Maximum Likelihood (REML and the prediction of genotypic values via Best Linear Unbiased Prediction (BLUP were obtained by software Selegen-REML/BLUP. The estimate of the broad-sense heritability was low for the grain yield (0.03, since it took individual plots into consideration and was free of the effects of interaction with years, cultivation periods and site. Nevertheless, the heritability at the level of line means across the various environments was high (0.75, allowing a high accuracy (0.87 in the selection of lines for planting in the environment mean. Among the 18 genotypes, the predicted genotypic values of nine were higher than the general mean. The genetic gain predicted with the selection of the best line, in this case line Gen 96A31 of the IAC, was 16.25%.Dezoito genótipos de feijoeiro (Phaseolus vulgaris L. foram avaliados em 25 ambientes do estado de São Paulo durante os anos de 2001 e 2002. As estimativas de parâmetros genéticos por REML e a predição de valores genotípicos via BLUP foram obtidas por meio do aplicativo computacional Selegen REML/BLUP, seguindo o modelo misto para linhagens. A estimativa da herdabilidade no sentido amplo para produção de grãos foi baixa (0,03, por ser em nível de parcelas individuais e livre dos efeitos da interação com anos, épocas e locais. No entanto, a herdabilidade ao nível de médias de linhagens ao longo dos vários ambientes foi alta (0,75, permitindo alta acurácia (0,87 na seleção de linhagens para plantio no ambiente médio. Dentre os 18 genótipos, nove apresentaram valores genotípicos preditos superiores à média geral. O ganho genético predito com a seleção da melhor linhagem, no caso, a linhagem Gen 96A31 do IAC, foi de 16,25%.
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.
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.
Assessment of Lumped-Parameter Models for Rigid Footings
DEFF Research Database (Denmark)
Andersen, Lars
2010-01-01
The quality of consistent lumped-parameter models of rigid footings is examined. Emphasis is put on the maximum response during excitation and the geometrical damping related to free vibrations. The optimal order of a lumped-parameter model is determined for each degree of freedom, i.e. horizontal...... and vertical translations as well as torsion and rocking, and the necessity of coupling between horizontal sliding and rocking is discussed. Most of the analyses are carried out for hexagonal footings; but in order to generalise the conclusions to a broader variety of footings, comparisons are made...... with the response of circular and square foundations....
A robust methodology for kinetic model parameter estimation for biocatalytic reactions
DEFF Research Database (Denmark)
Al-Haque, Naweed; Andrade Santacoloma, Paloma de Gracia; Lima Afonso Neto, Watson
2012-01-01
Effective estimation of parameters in biocatalytic reaction kinetic expressions are very important when building process models to enable evaluation of process technology options and alternative biocatalysts. The kinetic models used to describe enzyme-catalyzed reactions generally include several...... parameters, which are strongly correlated with each other. State-of-the-art methodologies such as nonlinear regression (using progress curves) or graphical analysis (using initial rate data, for example, the Lineweaver-Burke plot, Hanes plot or Dixon plot) often incorporate errors in the estimates and rarely...... lead to globally optimized parameter values. In this article, a robust methodology to estimate parameters for biocatalytic reaction kinetic expressions is proposed. The methodology determines the parameters in a systematic manner by exploiting the best features of several of the current approaches...
Han, Xiao; Gao, Xiguang; Song, Yingdong
2017-10-01
An approach to identify parameters of interface friction model for Ceramic Matrix composites based on stress-strain response was developed. The stress distribution of fibers in the interface slip region and intact region of the damaged composite was determined by adopting the interface friction model. The relation between maximum strain, secant moduli of hysteresis loop and interface shear stress, interface de-bonding stress was established respectively with the method of symbolic-graphic combination. By comparing the experimental strain, secant moduli of hysteresis loop with computation values, the interface shear stress and interface de-bonding stress corresponding to first cycle were identified. Substituting the identification of parameters into interface friction model, the stress-strain curves were predicted and the predicted results fit experiments well. Besides, the influence of number of data points on identifying the value of interface parameters was discussed. And the approach was compared with the method based on the area of hysteresis loop.
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.
Connecting Global to Local Parameters in Barred Galaxy Models
Indian Academy of Sciences (India)
R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22
The velocity and the angular velocity units are 10 km/s and 10 km/s/kpc, respectively while G is equal to unity. Our test particle is a star of mass = 1. Therefore, the energy unit (per unit mass) is 100(km/s)2. In these units the values of the parameters are α = 12 kpc,b = 2,cb = 1.5 kpc,Md = 9500 and Mb = 3000. It is evident that ...
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.
Fuzzy Stochastic Petri Nets for Modeling Biological Systems with Uncertain Kinetic Parameters.
Liu, Fei; Heiner, Monika; Yang, Ming
2016-01-01
Stochastic Petri nets (SPNs) have been widely used to model randomness which is an inherent feature of biological systems. However, for many biological systems, some kinetic parameters may be uncertain due to incomplete, vague or missing kinetic data (often called fuzzy uncertainty), or naturally vary, e.g., between different individuals, experimental conditions, etc. (often called variability), which has prevented a wider application of SPNs that require accurate parameters. Considering the strength of fuzzy sets to deal with uncertain information, we apply a specific type of stochastic Petri nets, fuzzy stochastic Petri nets (FSPNs), to model and analyze biological systems with uncertain kinetic parameters. FSPNs combine SPNs and fuzzy sets, thereby taking into account both randomness and fuzziness of biological systems. For a biological system, SPNs model the randomness, while fuzzy sets model kinetic parameters with fuzzy uncertainty or variability by associating each parameter with a fuzzy number instead of a crisp real value. We introduce a simulation-based analysis method for FSPNs to explore the uncertainties of outputs resulting from the uncertainties associated with input parameters, which works equally well for bounded and unbounded models. We illustrate our approach using a yeast polarization model having an infinite state space, which shows the appropriateness of FSPNs in combination with simulation-based analysis for modeling and analyzing biological systems with uncertain information.
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
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....
Joint Dynamics Modeling and Parameter Identification for Space Robot Applications
Directory of Open Access Journals (Sweden)
Adenilson R. da Silva
2007-01-01
Full Text Available Long-term mission identification and model validation for in-flight manipulator control system in almost zero gravity with hostile space environment are extremely important for robotic applications. In this paper, a robot joint mathematical model is developed where several nonlinearities have been taken into account. In order to identify all the required system parameters, an integrated identification strategy is derived. This strategy makes use of a robust version of least-squares procedure (LS for getting the initial conditions and a general nonlinear optimization method (MCS—multilevel coordinate search—algorithm to estimate the nonlinear parameters. The approach is applied to the intelligent robot joint (IRJ experiment that was developed at DLR for utilization opportunity on the International Space Station (ISS. The results using real and simulated measurements have shown that the developed algorithm and strategy have remarkable features in identifying all the parameters with good accuracy.
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)
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
Measuring Teacher Quality with Value-Added Modeling
Marder, Michael
2012-01-01
Using computers to evaluate teachers based on student test scores is more difficult than it seems. Value-added modeling is a genuinely serious attempt to grapple with the difficulties. Value-added modeling carries the promise of measuring teacher quality automatically and objectively, and improving school systems at minimal cost. The essence of…
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
Finite size scaling study of a two parameter percolation model: Constant and correlated growth
Roy, Bappaditya; Santra, S. B.
2018-02-01
A new percolation model of enhanced parameter space with nucleation and growth is developed taking the initial seed concentration ρ and a growth parameter g as two tunable parameters. Percolation transition is determined by the final static configurations of spanning clusters once taking uniform growth probability for all the clusters and then taking a cluster size dependent dynamic growth probability. The uniform growth probability remains constant over time and leads to a constant growth model whereas the dynamically varying growth probability leads to a correlated growth model. In the first case, the growth of a cluster will encounter partial hindrance due to the presence of other clusters whereas in the second case the growth of a larger cluster will be further suppressed in comparison to the growth of smaller clusters. A finite size scaling theory for percolation transition is developed and numerically verified for both the models. The scaling functions are found to depend on both g and ρ. At the critical growth parameter gc, the values of the critical exponents are found to be same as that of the original percolation at all values of ρ for the constant growth model whereas in the case of correlated growth model the scaling behavior deviates from ordinary percolation in the dilute limit of ρ. The constant growth model then belongs to the same universality class of percolation for a wide range of ρ whereas the correlated growth model displays a continuously varying universality class as ρ decreases towards zero.
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 ...
Transformations among CE–CVM model parameters for ...
Indian Academy of Sciences (India)
In the development of thermodynamic databases for multicomponent systems using the cluster expansion–cluster variation methods, we need to have a consistent procedure for expressing the model parameters (CECs) of a higher order system in terms of those of the lower order subsystems and to an independent set of ...
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...
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss...
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...
Constraint on Parameters of Inverse Compton Scattering Model for ...
Indian Academy of Sciences (India)
J. Astrophys. Astr. (2011) 32, 299–300 c Indian Academy of Sciences. Constraint on Parameters of Inverse Compton Scattering Model for PSR B2319+60. H. G. Wang. ∗. & M. Lv. Center for Astrophysics,Guangzhou University, Guangzhou, China. ∗ e-mail: cosmic008@yahoo.com.cn. Abstract. Using the multifrequency radio ...
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
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
On the added value of WUDAPT for Urban Climate Modelling
Brousse, Oscar; Martilli, Alberto; Mills, Gerald; Bechtel, Benjamin; Hammerberg, Kris; Demuzere, Matthias; Wouters, Hendrik; Van Lipzig, Nicole; Ren, Chao; Feddema, Johannes J.; Masson, Valéry; Ching, Jason
2017-04-01
Over half of the planet's population now live in cities and is expected to grow up to 65% by 2050 (United Nations, 2014), most of whom will actually occupy new emerging cities of the global South. Cities' impact on climate is known to be a key driver of environmental change (IPCC, 2014) and has been studied for decades now (Howard, 1875). Still very little is known about our cities' structure around the world, preventing urban climate simulations to be done and hence guidance to be provided for mitigation. Assessing the need to bridge the urban knowledge gap for urban climate modelling perspectives, the World Urban Database and Access Portal Tool - WUDAPT - project (Ching et al., 2015; Mills et al., 2015) developed an innovative technique to map cities globally rapidly and freely. The framework established by Bechtel and Daneke (2012) derives Local Climate Zones (Stewart and Oke, 2012) city maps out of LANDSAT 8 OLI-TIRS imagery (Bechtel et al., 2015) through a supervised classification by a Random Forest Classification algorithm (Breiman, 2001). The first attempt to implement Local Climate Zones (LCZ) out of the WUDAPT product within a major climate model was carried out by Brousse et al. (2016) over Madrid, Spain. This study proved the applicability of LCZs as an enhanced urban parameterization within the WRF model (Chen et al. 2011) employing the urban canopy model BEP-BEM (Martilli, 2002; Salamanca et al., 2010), using the averaged values of the morphological and physical parameters' ranges proposed by Stewart and Oke (2012). Other studies have now used the Local Climate Zones for urban climate modelling purposes (Alexander et al., 2016; Wouters et al. 2016; Hammerberg et al., 2017; Brousse et al., 2017) and demonstrated the added value of the WUDAPT dataset. As urban data accessibility is one of the major challenge for simulations in emerging countries, this presentation will show results of simulations using LCZs and the capacity of the WUDAPT framework to be
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.
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
Mean Value Engine Modelling of an SI Engine with EGR
DEFF Research Database (Denmark)
Føns, Michael; Müller, Martin; Chevalier, Alain
1999-01-01
Mean Value Engine Models (MVEMs) are simplified, dynamic engine models what are physically based. Such models are useful for control studies, for engine control system analysis and for model based engine control systems. Very few published MVEMs have included the effects of Exhaust Gas Recirculat...
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.
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.
Directory of Open Access Journals (Sweden)
Vandana Jha
2017-01-01
Full Text Available This paper proposes an improved generalized method for evaluation of parameters, modeling, and simulation of photovoltaic modules. A new concept “Level of Improvement” has been proposed for evaluating unknown parameters of the nonlinear I-V equation of the single-diode model of PV module at any environmental condition, taking the manufacturer-specified data at Standard Test Conditions as inputs. The main contribution of the new concept is the improvement in the accuracy of values of evaluated parameters up to various levels and is based on mathematical equations of PV modules. The proposed evaluating method is implemented by MATLAB programming and, for demonstration, by using the values of parameters of the I-V equation obtained from programming results, a PV module model is build with MATLAB. The parameters evaluated by the proposed technique are validated with the datasheet values of six different commercially available PV modules (thin film, monocrystalline, and polycrystalline at Standard Test Conditions and Nominal Operating Cell Temperature Conditions. The module output characteristics generated by the proposed method are validated with experimental data of FS-270 PV module. The effects of variation of ideality factor and resistances on output characteristics are also studied. The superiority of the proposed technique is proved.
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.
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
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.
Energy Technology Data Exchange (ETDEWEB)
Choi, Hyun Seok; Kim, Ah Hyun; Ahn, Sung Soo; Shin, Na Young; Kim, Jin Na; Lee, Seung Koo [Dept. of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul , (Korea, Republic of)
2013-06-15
Permeability parameters from dynamic contrast-enhanced MRI (DCE-MRI) and apparent diffusion coefficient (ADC) value on diffusion-weighted imaging (DWI) can be quantitative physiologic metrics for gliomas. The transfer constant (K{sup trans}) has shown efficacy in grading gliomas. Volume fraction of extravascular extracellular space (v{sub e}) has been underutilized to grade gliomas. The purpose of this study was to evaluate v{sub e} in its ability to grade gliomas and to assess the correlation with other permeability parameters and ADC values. A total of 33 patients diagnosed with pathologically-confirmed gliomas were examined by 3 T MRI including DCE-MRI and ADC map. A region of interest analyses for permeability parameters from DCE-MRI and ADC were performed on the enhancing solid portion of the tumors. Permeability parameters form DCE-MRI and ADC between low- and high-grade gliomas; the diagnostic performances of presumptive metrics and correlation among those metrics were statistically analyzed. High-grade gliomas showed higher K{sup trans} (0.050 vs. 0.010 in median value, p = 0.002) and higher v{sub e} (0.170 vs. 0.015 in median value, p = 0.001) than low-grade gliomas. Receiver operating characteristic curve analysis showed significance in both K{sup trans} and v{sub e} for glioma grading. However, there was no significant difference in diagnostic performance between K{sup trans} and v{sub e}. ADC value did not correlate with any of the permeability parameters from DCE-MRI. Extravascular extracellular space (v{sub e}) appears to be comparable with transfer constant (K{sup trans}) in differentiating high-grade gliomas from low-grade gliomas. ADC value does not show correlation with any permeability parameters from DCE-MRI.
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.
Improving the transferability of hydrological model parameters under changing conditions
Huang, Yingchun; Bárdossy, András
2014-05-01
Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.
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)
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.
Directory of Open Access Journals (Sweden)
Claudia Kratzenstein
2013-07-01
Full Text Available We investigate the Oneshot Optimization strategy introduced by Hamdi and Griewank for the applicability and efficiency to identify parameters in models of the earth's climate system. Parameters of a box model of the North Atlantic Thermohaline Circulation are optimized with respect to the fit of model output to data given by another model of intermediate complexity. Since the model is run into a steady state by a pseudo time-stepping, efficient techniques are necessary to avoid extensive recomputations or storing when using gradient-based local optimization algorithms. The Oneshot approach simultaneously updates state, adjoint and parameter values. For the required partial derivatives, the algorithmic/automatic differentiation tool TAF was used. Numerical results are compared to results obtained by the BFGS-quasi-Newton method.
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.
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)
Thermal Model Parameter Identification of a Lithium Battery
Directory of Open Access Journals (Sweden)
Dirk Nissing
2017-01-01
Full Text Available The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.
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)
Zagatto, A M; Gobatto, C A
2012-08-01
The aim of this study was to verify the validity of the curvature constant parameter (W'), calculated from 2-parameter mathematical equations of critical power model, in estimating the anaerobic capacity and anaerobic work capacity from a table tennis-specific test. Specifically, we aimed to i) compare constants estimated from three critical intensity models in a table tennis-specific test (Cf); ii) correlate each estimated W' with the maximal accumulated oxygen deficit (MAOD); iii) correlate each W' with the total amount of anaerobic work (W ANAER) performed in each exercise bout performed during the Cf test. Nine national-standard male table tennis players participated in the study. MAOD was 63.0(10.8) mL · kg - 1 and W' values were 32.8(6.6) balls for the linear-frequency model, 38.3(6.9) balls for linear-total balls model, 48.7(8.9) balls for Nonlinear-2 parameter model. Estimated W' from the Nonlinear 2-parameter model was significantly different from W' from the other 2 models (P0.13). Thus, W' estimated from the 2-parameter mathematical equations did not correlate with MAOD or W ANAER in table tennis-specific tests, indicating that W' may not provide a strong and valid estimation of anaerobic capacity and anaerobic capacity work. © Georg Thieme Verlag KG Stuttgart · New York.
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)
Azam, Mohammad; Rahman, Zillur; Talib, Faisal; Singh, K J
2012-01-01
The purpose of this article is to identify and critically analyze healthcare establishment (HCE) quality parameters described in the literature. It aims to propose an integrated quality model that includes technical quality and associated supportive quality parameters to achieve optimum patient satisfaction. The authors use an extensive in-depth healthcare quality literature review, discerning gaps via a critical analysis in relation to their overall impact on patient management, while identifying an integrated quality model acceptable to hospital staff. The article provides insights into contemporary HCE quality parameters by critically analyzing relevant literature. It also evolves and proposes an integrated HCE-quality model. Owing to HCE confidentiality, especially regarding patient data, information cannot be accessed. The integrated quality model parameters have practical utility for healthcare service managers. However, further studies may be required to refine and integrate newer parameters to ensure continuous quality improvement. This article adds a new perspective to understanding quality parameters and suggests an integrated quality model that has practical value for maintaining HCE service quality to benefit many stakeholders.
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.
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
Yoon, Ra Gyoung; Kim, Ho Sung; Paik, Wooyul; Shim, Woo Hyun; Kim, Sang Joon; Kim, Jeong Hoon
2017-01-01
The aim of this study was to determine whether diffusion and perfusion imaging parameters demonstrate different diagnostic values for predicting pseudoprogression between glioblastoma subgroups stratified by O 6 -mythylguanine-DNA methyltransferase (MGMT) promoter methylation status. We enrolled seventy-five glioblastoma patients that had presented with enlarged contrast-enhanced lesions on magnetic resonance imaging (MRI) one month after completing concurrent chemoradiotherapy and undergoing MGMT promoter methylation testing. The imaging parameters included 10 or 90 % histogram cutoffs of apparent diffusion coefficient (ADC10), normalized cerebral blood volume (nCBV90), and initial area under the time signal-intensity curve (IAUC90). The results of the areas under the receiver operating characteristic curve (AUCs) with cross-validation were compared between MGMT methylation and unmethylation groups. MR imaging parameters demonstrated a trend toward higher accuracy in the MGMT promoter methylation group than in the unmethylation group (cross-validated AUCs = 0.70-0.95 and 0.56-0.87, respectively). The combination of MGMT methylation status with imaging parameters improved the AUCs from 0.70 to 0.75-0.90 for both readers in comparison with MGMT methylation status alone. The probability of pseudoprogression was highest (95.7 %) when nCBV90 was below 4.02 in the MGMT promoter methylation group. MR imaging parameters could be stronger predictors of pseudoprogression in glioblastoma patients with the methylated MGMT promoter than in patients with the unmethylated MGMT promoter. • The glioblastoma subgroup was stratified according to MGMT promoter methylation status. • Diagnostic values of diffusion and perfusion parameters for predicting pseudoprogression were compared. • Imaging parameters showed higher diagnostic accuracy in the MGMT promoter methylation group. • Imaging parameters were independent to MGMT promoter methylation status for predicting
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.
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.
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.
The definition of input parameters for modelling of energetic subsystems
Directory of Open Access Journals (Sweden)
Ptacek M.
2013-06-01
Full Text Available This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
The definition of input parameters for modelling of energetic subsystems
Ptacek, M.
2013-06-01
This paper is a short review and a basic description of mathematical models of renewable energy sources which present individual investigated subsystems of a system created in Matlab/Simulink. It solves the physical and mathematical relationships of photovoltaic and wind energy sources that are often connected to the distribution networks. The fuel cell technology is much less connected to the distribution networks but it could be promising in the near future. Therefore, the paper informs about a new dynamic model of the low-temperature fuel cell subsystem, and the main input parameters are defined as well. Finally, the main evaluated and achieved graphic results for the suggested parameters and for all the individual subsystems mentioned above are shown.
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 ...
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.
The Residual Value Models: A Framework for Business Administration
Konstantinos J. Liapis
2010-01-01
This article investigates the relationship between a firm’s performance and Residual Value Models (RVM) which serve as decision making tools in corporate management. The main measures are the Economic Value Added (EVA®) and Cash Value Added (CVA®), with key components the Residual Income (RI), Free Cash Flow (FCF) and Weighted Average Cost of Capital (WACC). These measures have attracted considerable interest among scientists, practitioners and organizations in recent years. This work focuses...
Lumped-parameter Model of a Bucket Foundation
DEFF Research Database (Denmark)
Andersen, Lars; Ibsen, Lars Bo; Liingaard, Morten
2009-01-01
As an alternative to gravity footings or pile foundations, offshore wind turbines at shallow water can be placed on a bucket foundation. The present analysis concerns the development of consistent lumped-parameter models for this type of foundation. The aim is to formulate a computationally effic...... be disregarded without significant loss of accuracy. Finally, special attention is drawn to the influence of the skirt stiffness, i.e. whether the embedded part of the caisson is rigid or flexible....
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)
A procedure for determining parameters of a simplified ligament model.
Barrett, Jeff M; Callaghan, Jack P
2018-01-03
A previous mathematical model of ligament force-generation treated their behavior as a population of collagen fibres arranged in parallel. When damage was ignored in this model, an expression for ligament force in terms of the deflection, x, effective stiffness, k, mean collagen slack length, μ, and the standard deviation of slack lengths, σ, was obtained. We present a simple three-step method for determining the three model parameters (k, μ, and σ) from force-deflection data: (1) determine the equation of the line in the linear region of this curve, its slope is k and its x -intercept is -μ; (2) interpolate the force-deflection data when x is -μ to obtain F 0 ; (3) calculate σ with the equation σ=2πF 0 /k. Results from this method were in good agreement to those obtained from a least-squares procedure on experimental data - all falling within 6%. Therefore, parameters obtained using the proposed method provide a systematic way of reporting ligament parameters, or for obtaining an initial guess for nonlinear least-squares. Copyright © 2017 Elsevier Ltd. All rights reserved.
Modelling spatial-temporal and coordinative parameters in swimming.
Seifert, L; Chollet, D
2009-07-01
This study modelled the changes in spatial-temporal and coordinative parameters through race paces in the four swimming strokes. The arm and leg phases in simultaneous strokes (butterfly and breaststroke) and the inter-arm phases in alternating strokes (crawl and backstroke) were identified by video analysis to calculate the time gaps between propulsive phases. The relationships among velocity, stroke rate, stroke length and coordination were modelled by polynomial regression. Twelve elite male swimmers swam at four race paces. Quadratic regression modelled the changes in spatial-temporal and coordinative parameters with velocity increases for all four strokes. First, the quadratic regression between coordination and velocity showed changes common to all four strokes. Notably, the time gaps between the key points defining the beginning and end of the stroke phases decreased with increases in velocity, which led to decreases in glide times and increases in the continuity between propulsive phases. Conjointly, the quadratic regression among stroke rate, stroke length and velocity was similar to the changes in coordination, suggesting that these parameters may influence coordination. The main practical application for coaches and scientists is that ineffective time gaps can be distinguished from those that simply reflect an individual swimmer's profile by monitoring the glide times within a stroke cycle. In the case of ineffective time gaps, targeted training could improve the swimmer's management of glide time.
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
On the value of water quality data and informative flow states in karst modelling
Hartmann, Andreas; Barberá, Juan Antonio; Andreo, Bartolomé
2017-11-01
If properly applied, karst hydrological models are a valuable tool for karst water resource management. If they are able to reproduce the relevant flow and storage processes of a karst system, they can be used for prediction of water resource availability when climate or land use are expected to change. A common challenge to apply karst simulation models is the limited availability of observations to identify their model parameters. In this study, we quantify the value of information when water quality data (NO3- and SO42-) is used in addition to discharge observations to estimate the parameters of a process-based karst simulation model at a test site in southern Spain. We use a three-step procedure to (1) confine an initial sample of 500 000 model parameter sets by discharge and water quality observations, (2) identify alterations of model parameter distributions through the confinement, and (3) quantify the strength of the confinement for the model parameters. We repeat this procedure for flow states, for which the system discharge is controlled by the unsaturated zone, the saturated zone, and the entire time period including times when the spring is influenced by a nearby river. Our results indicate that NO3- provides the most information to identify the model parameters controlling soil and epikarst dynamics during the unsaturated flow state. During the saturated flow state, SO42- and discharge observations provide the best information to identify the model parameters related to groundwater processes. We found reduced parameter identifiability when the entire time period is used as the river influence disturbs parameter estimation. We finally show that most reliable simulations are obtained when a combination of discharge and water quality date is used for the combined unsaturated and saturated flow states.
Stakeholder Theory and Value Creation Models in Brazilian Firms
Directory of Open Access Journals (Sweden)
Natalia Giugni Vidal
2015-09-01
Full Text Available Objective – The purpose of this study is to understand how top Brazilian firms think about and communicate value creation to their stakeholders. Design/methodology/approach – We use qualitative content analysis methodology to analyze the sustainability or annual integrated reports of the top 25 Brazilian firms by sales revenue. Findings – Based on our analysis, these firms were classified into three main types of stakeholder value creation models: narrow, broad, or transitioning from narrow to broad. We find that many of the firms in our sample are in a transition state between narrow and broad stakeholder value creation models. We also identify seven areas of concentration discussed by firms in creating value for stakeholders: better stakeholder relationships, better work environment, environmental preservation, increased customer base, local development, reputation, and stakeholder dialogue. Practical implications – This study shows a trend towards broader stakeholder value creation models in Brazilian firms. The findings of this study may inform practitioners interested in broadening their value creation models. Originality/value – This study adds to the discussion of stakeholder theory in the Brazilian context by understanding variations in value creation orientation in Brazil.
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.
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.
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…
Local sensitivity analysis of a distributed parameters water quality model
International Nuclear Information System (INIS)
Pastres, R.; Franco, D.; Pecenik, G.; Solidoro, C.; Dejak, C.
1997-01-01
A local sensitivity analysis is presented of a 1D water-quality reaction-diffusion model. The model describes the seasonal evolution of one of the deepest channels of the lagoon of Venice, that is affected by nutrient loads from the industrial area and heat emission from a power plant. Its state variables are: water temperature, concentrations of reduced and oxidized nitrogen, Reactive Phosphorous (RP), phytoplankton, and zooplankton densities, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). Attention has been focused on the identifiability and the ranking of the parameters related to primary production in different mixing conditions
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.
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.
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
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.
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...
Comparison of parameter estimation algorithms in hydrological modelling
DEFF Research Database (Denmark)
Blasone, Roberta-Serena; Madsen, Henrik; Rosbjerg, Dan
2006-01-01
Local search methods have been applied successfully in calibration of simple groundwater models, but might fail in locating the optimum for models of increased complexity, due to the more complex shape of the response surface. Global search algorithms have been demonstrated to perform well...... for these types of models, although at a more expensive computational cost. The main purpose of this study is to investigate the performance of a global and a local parameter optimization algorithm, respectively, the Shuffled Complex Evolution (SCE) algorithm and the gradient-based Gauss......-Marquardt-Levenberg algorithm (implemented in the PEST software), when applied to a steady-state and a transient groundwater model. The results show that PEST can have severe problems in locating the global optimum and in being trapped in local regions of attractions. The global SCE procedure is, in general, more effective...
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
Flare parameters inferred from a 3D loop model database
Cuambe, Valente A.; Costa, J. E. R.; Simões, P. J. A.
2018-04-01
We developed a database of pre-calculated flare images and spectra exploring a set of parameters which describe the physical characteristics of coronal loops and accelerated electron distribution. Due to the large number of parameters involved in describing the geometry and the flaring atmosphere in the model used (Costa et al. 2013), we built a large database of models (˜250 000) to facilitate the flare analysis. The geometry and characteristics of non-thermal electrons are defined on a discrete grid with spatial resolution greater than 4 arcsec. The database was constructed based on general properties of known solar flares and convolved with instrumental resolution to replicate the observations from the Nobeyama radio polarimeter (NoRP) spectra and Nobeyama radio-heliograph (NoRH) brightness maps. Observed spectra and brightness distribution maps are easily compared with the modelled spectra and images in the database, indicating a possible range of solutions. The parameter search efficiency in this finite database is discussed. Eight out of ten parameters analysed for one thousand simulated flare searches were recovered with a relative error of less than 20 per cent on average. In addition, from the analysis of the observed correlation between NoRH flare sizes and intensities at 17 GHz, some statistical properties were derived. From these statistics the energy spectral index was found to be δ ˜ 3, with non-thermal electron densities showing a peak distribution ⪅107 cm-3, and Bphotosphere ⪆2000 G. Some bias for larger loops with heights as great as ˜2.6 × 109 cm, and looptop events were noted. An excellent match of the spectrum and the brightness distribution at 17 and 34 GHz of the 2002 May 31 flare, is presented as well.
Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models
Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea
2014-05-01
Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.
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.
Models of consumer value cocreation in health care.
Nambisan, Priya; Nambisan, Satish
2009-01-01
In recent years, consumer participation in health care has gained critical importance as health care organizations (HCOs) seek varied avenues to enhance the quality and the value of their offerings. Many large HCOs have established online health communities where health care consumers (patients) can interact with one another to share knowledge and offer emotional support in disease management and care. Importantly, the focus of consumer participation in health care has moved beyond such personal health care management as the potential for consumers to participate in innovation and value creation in varied areas of the health care industry becomes increasingly evident. Realizing such potential, however, will require HCOs to develop a better understanding of the varied types of consumer value cocreation that are enabled by new information and communication technologies such as online health communities and Web 2.0 (social media) technologies. This article seeks to contribute toward such an understanding by offering a concise and coherent theoretical framework to analyze consumer value cocreation in health care. We identify four alternate models of consumer value cocreation-the partnership model, the open-source model, the support-group model, and the diffusion model-and discuss their implications for HCOs. We develop our theoretical framework by drawing on theories and concepts in knowledge creation, innovation management, and online communities. A set of propositions are developed by combining theoretical insights from these areas with real-world examples of consumer value cocreation in health care. The theoretical framework offered here informs on the potential impact of the different models of consumer value cocreation on important organizational variables such as innovation cost and time, service quality, and consumer perceptions of HCO. An understanding of the four models of consumer value cocreation can help HCOs adopt appropriate strategies and practices to
Directory of Open Access Journals (Sweden)
Yang Hyun M
2000-01-01
Full Text Available OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.
A review of distributed parameter groundwater management modeling methods
Gorelick, Steven M.
1983-01-01
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.
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes
Directory of Open Access Journals (Sweden)
J.-L. Guerrero
2017-12-01
Full Text Available 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.
HLB value, an important parameter for the development of essential oil phytopharmaceuticals
Directory of Open Access Journals (Sweden)
Caio P. Fernandes
2013-02-01
Full Text Available Essential oils are used primarily as natural preservatives, flavourants and fragrances in cosmetic products. Several pharmacopeias possess monographs of plants which are good sources of essential oils, such as Brazilian Pharmacopeia, including Illicium verum Hook. f., Schisandraceae and Rosmarinus offi cinalis. Since determination of Hydrophile-Lipophile Balance (HLB value of essential oils appears as a critical step for development of emulsions and other semi-solid formulations, evaluation of required HLB values for I. verum and R. offi cinalis essential oils is the aim of this study. They were obtained by hydrodistillation and several emulsions were prepared by changing emulsifiers. The couple sorbitan oleate/polysorbate 20 provided best emulsions and was used at different ratios, at a total blend concentration of 5% w/w. The lowest mean droplet diameters for R. offi cinalis and I. verum emulsions were obtained at HLB 16.5 (97.12 nm and 16.7 (246.6 nm, respectively. Moreover, emulsions with R. offi cinalis were finer and presented some bluish reflection, characteristic of nanoemulsions. The lowest turbidity value for R. offi cinalis emulsion was also obtained at HLB 16.5 (0.33. Thus, the present study describes for the first time HLB values for R. offi cinalis (16.5 and I. verum (16.7 essential oils, contributing to their physicochemical characterization and technology development of phytopharmaceuticals.
HLB value, an important parameter for the development of essential oil phytopharmaceuticals
Directory of Open Access Journals (Sweden)
Caio P. Fernandes
2012-11-01
Full Text Available Essential oils are used primarily as natural preservatives, flavourants and fragrances in cosmetic products. Several pharmacopeias possess monographs of plants which are good sources of essential oils, such as Brazilian Pharmacopeia, including Illicium verum Hook. f., Schisandraceae and Rosmarinus offi cinalis. Since determination of Hydrophile-Lipophile Balance (HLB value of essential oils appears as a critical step for development of emulsions and other semi-solid formulations, evaluation of required HLB values for I. verum and R. offi cinalis essential oils is the aim of this study. They were obtained by hydrodistillation and several emulsions were prepared by changing emulsifiers. The couple sorbitan oleate/polysorbate 20 provided best emulsions and was used at different ratios, at a total blend concentration of 5% w/w. The lowest mean droplet diameters for R. offi cinalis and I. verum emulsions were obtained at HLB 16.5 (97.12 nm and 16.7 (246.6 nm, respectively. Moreover, emulsions with R. offi cinalis were finer and presented some bluish reflection, characteristic of nanoemulsions. The lowest turbidity value for R. offi cinalis emulsion was also obtained at HLB 16.5 (0.33. Thus, the present study describes for the first time HLB values for R. offi cinalis (16.5 and I. verum (16.7 essential oils, contributing to their physicochemical characterization and technology development of phytopharmaceuticals.
Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter
Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.
2014-07-01
The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.
Some notes on unobserved parameters (frailties) in reliability modeling
International Nuclear Information System (INIS)
Cha, Ji Hwan; Finkelstein, Maxim
2014-01-01
Unobserved random quantities (frailties) often appear in various reliability problems especially when dealing with the failure rates of items from heterogeneous populations. As the failure rate is a conditional characteristic, the distributions of these random quantities, similar to Bayesian approaches, are updated in accordance with the corresponding survival information. At some instances, apart from a statistical meaning, frailties can have also useful interpretations describing the underlying lifetime model. We discuss and clarify these issues in reliability context and present and analyze several meaningful examples. We consider the proportional hazards model with a random factor; the stress–strength model, where the unobserved strength of a system can be viewed as frailty; a parallel system with a random number of components and, finally, the first passage time problem for the Wiener process with random parameters. - Highlights: • We discuss and clarify the notion of frailty in reliability context and present and analyze several meaningful examples. • The paper provides a new insight and general perspective on reliability models with unobserved parameters. • The main message of the paper is well illustrated by several meaningful examples and emphasized by detailed discussion
Directory of Open Access Journals (Sweden)
H. C. Winsemius
2008-12-01
Full Text Available In this study, land surface related parameter distributions of a conceptual semi-distributed hydrological model are constrained by employing time series of satellite-based evaporation estimates during the dry season as explanatory information. The approach has been applied to the ungauged Luangwa river basin (150 000 (km^{2} in Zambia. The information contained in these evaporation estimates imposes compliance of the model with the largest outgoing water balance term, evaporation, and a spatially and temporally realistic depletion of soil moisture within the dry season. The model results in turn provide a better understanding of the information density of remotely sensed evaporation. Model parameters to which evaporation is sensitive, have been spatially distributed on the basis of dominant land cover characteristics. Consequently, their values were conditioned by means of Monte-Carlo sampling and evaluation on satellite evaporation estimates. The results show that behavioural parameter sets for model units with similar land cover are indeed clustered. The clustering reveals hydrologically meaningful signatures in the parameter response surface: wetland-dominated areas (also called dambos show optimal parameter ranges that reflect vegetation with a relatively small unsaturated zone (due to the shallow rooting depth of the vegetation which is easily moisture stressed. The forested areas and highlands show parameter ranges that indicate a much deeper root zone which is more drought resistent. Clustering was consequently used to formulate fuzzy membership functions that can be used to constrain parameter realizations in further calibration. Unrealistic parameter ranges, found for instance in the high unsaturated soil zone values in the highlands may indicate either overestimation of satellite-based evaporation or model structural deficiencies. We believe that in these areas, groundwater uptake into the root zone and lateral movement of
[Healthcare value chain: a model for the Brazilian healthcare system].
Pedroso, Marcelo Caldeira; Malik, Ana Maria
2012-10-01
This article presents a model of the healthcare value chain which consists of a schematic representation of the Brazilian healthcare system. The proposed model is adapted for the Brazilian reality and has the scope and flexibility for use in academic activities and analysis of the healthcare sector in Brazil. It places emphasis on three components: the main activities of the value chain, grouped in vertical and horizontal links; the mission of each link and the main value chain flows. The proposed model consists of six vertical and three horizontal links, amounting to nine. These are: knowledge development; supply of products and technologies; healthcare services; financial intermediation; healthcare financing; healthcare consumption; regulation; distribution of healthcare products; and complementary and support services. Four flows can be used to analyze the value chain: knowledge and innovation; products and services; financial; and information.
Modelling Technical and Economic Parameters in Selection of Manufacturing Devices
Directory of Open Access Journals (Sweden)
Naqib Daneshjo
2017-11-01
Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.
Estimator of a non-Gaussian parameter in multiplicative log-normal models
Kiyono, Ken; Struzik, Zbigniew R.; Yamamoto, Yoshiharu
2007-10-01
We study non-Gaussian probability density functions (PDF’s) of multiplicative log-normal models in which the multiplication of Gaussian and log-normally distributed random variables is considered. To describe the PDF of the velocity difference between two points in fully developed turbulent flows, the non-Gaussian PDF model was originally introduced by Castaing [Physica D 46, 177 (1990)]. In practical applications, an experimental PDF is approximated with Castaing’s model by tuning a single non-Gaussian parameter, which corresponds to the logarithmic variance of the log-normally distributed variable in the model. In this paper, we propose an estimator of the non-Gaussian parameter based on the q th order absolute moments. To test the estimator, we introduce two types of stochastic processes within the framework of the multiplicative log-normal model. One is a sequence of independent and identically distributed random variables. The other is a log-normal cascade-type multiplicative process. By analyzing the numerically generated time series, we demonstrate that the estimator can reliably determine the theoretical value of the non-Gaussian parameter. Scale dependence of the non-Gaussian parameter in multiplicative log-normal models is also studied, both analytically and numerically. As an application of the estimator, we demonstrate that non-Gaussian PDF’s observed in the S&P500 index fluctuations are well described by the multiplicative log-normal model.
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 parameterthat can be used for detecting the severity of patients withMPM.Key words: Modified Glasgow Prognostic Score, MalignantPleural Mesothelioma, Prognosis
Directory of Open Access Journals (Sweden)
ANDRA SULER
2008-10-01
Full Text Available An important faze for food quality control is verification of microbiological parameters of food products. In this way is assuring the prevention of alimentation toxicological infections to consumer, avoiding the technological and economical losses as well as increasing the products conservation period. In this paper are presents the microbiological exam results from raw milk used in Telemea cheese technological process, for 5 stations studied. The determinations were made on 2 series with 57 samples each of them, prelevated in reception fase, in summer and winter season.
Creating Value Through the Freemium Business Model: A Consumer Perspective
G.J. Rietveld (Joost)
2016-01-01
textabstractThis paper develops a consumer-centric framework for creating value through the freemium business model. Goods that are commercialized through the freemium business model offer basic functionality for free and monetize users for extended use or complementary features. Compared to premium
Distribution-centric 3-parameter thermodynamic models of partition gas chromatography.
Blumberg, Leonid M
2017-03-31
If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van't Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T-centric construction of these functions is based on relating them to the reference values (ΔS ref and ΔH ref ) corresponding to a predetermined reference temperature (T ref ). Choosing a single T ref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔS ref and ΔH ref for those analytes that have too small or too large retention factors at T ref . Breaking all analytes in several subsets each with its own T ref leads to discontinuities in the analyte parameters. These problems are avoided in the K-centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (K Ref ) - the same for all analytes. In this report, the mathematics of the K-centric modeling are described and the properties of several types of K-centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, T char , and the characteristic thermal constant, θ char ) are a special chromatographically convenient case of the K-centric parameters. Transformations of T-centric parameters into K-centric ones and vice-versa as well as the transformations of one set of K-centric parameters into another set and vice-versa are described. Copyright © 2017 Elsevier B.V. All rights reserved.
Dynamic systems models new methods of parameter and state estimation
2016-01-01
This monograph is an exposition of a novel method for solving inverse problems, a method of parameter estimation for time series data collected from simulations of real experiments. These time series might be generated by measuring the dynamics of aircraft in flight, by the function of a hidden Markov model used in bioinformatics or speech recognition or when analyzing the dynamics of asset pricing provided by the nonlinear models of financial mathematics. Dynamic Systems Models demonstrates the use of algorithms based on polynomial approximation which have weaker requirements than already-popular iterative methods. Specifically, they do not require a first approximation of a root vector and they allow non-differentiable elements in the vector functions being approximated. The text covers all the points necessary for the understanding and use of polynomial approximation from the mathematical fundamentals, through algorithm development to the application of the method in, for instance, aeroplane flight dynamic...
Parameter Estimation for a Class of Lifetime Models
Directory of Open Access Journals (Sweden)
Xinyang Ji
2014-01-01
Full Text Available Our purpose in this paper is to present a better method of parametric estimation for a bivariate nonlinear regression model, which takes the performance indicator of rubber aging as the dependent variable and time and temperature as the independent variables. We point out that the commonly used two-step method (TSM, which splits the model and estimate parameters separately, has limitation. Instead, we apply the Marquardt’s method (MM to implement parametric estimation directly for the model and compare these two methods of parametric estimation by random simulation. Our results show that MM has better effect of data fitting, more reasonable parametric estimates, and smaller prediction error compared with TSM.
The parameter space of Cubic Galileon models for cosmic acceleration
Bellini, Emilio
2013-01-01
We use recent measurements of the expansion history of the universe to place constraints on the parameter space of cubic Galileon models. This gives strong constraints on the Lagrangian of these models. Most dynamical terms in the Galileon Lagrangian are constraint to be small and the acceleration is effectively provided by a constant term in the scalar potential, thus reducing, effectively, to a LCDM model for current acceleration. The effective equation of state is indistinguishable from that of a cosmological constant w = -1 and the data constraint it to have no temporal variations of more than at the few % level. The energy density of the Galileon can contribute only to about 10% of the acceleration energy density, being the other 90% a cosmological constant term. This demonstrates how useful direct measurements of the expansion history of the universe are at constraining the dynamical nature of dark energy.
Tillman, Fred D.; Weaver, James W.
Migration of volatile chemicals from the subsurface into overlying buildings is known as vapor intrusion (VI). Under certain circumstances, people living in homes above contaminated soil or ground water may be exposed to harmful levels of these vapors. VI is a particularly difficult pathway to assess, as challenges exist in delineating subsurface contributions to measured indoor-air concentrations as well as in adequate characterization of subsurface parameters necessary to calibrate a predictive flow and transport model. Often, a screening-level model is employed to determine if a potential indoor inhalation exposure pathway exists and, if such a pathway is complete, whether long-term exposure increases the occupants' risk for cancer or other toxic effects to an unacceptable level. A popular screening-level algorithm currently in wide use in the United States, Canada and the UK for making such determinations is the "Johnson and Ettinger" (J&E) model. Concern exists over using the J&E model for deciding whether or not further action is necessary at sites as many parameters are not routinely measured (or are un-measurable). Many screening decisions are then made based on simulations using "best estimate" look-up parameter values. While research exists on the sensitivity of the J&E model to individual parameter uncertainty, little published information is available on the combined effects of multiple uncertain parameters and their effect on screening decisions. This paper presents results of multiple-parameter uncertainty analyses using the J&E model to evaluate risk to humans from VI. Software was developed to produce automated uncertainty analyses of the model. Results indicate an increase in predicted cancer risk from multiple-parameter uncertainty by nearly a factor of 10 compared with single-parameter uncertainty. Additionally, a positive skew in model response to variation of some parameters was noted for both single and multiple parameter uncertainty analyses
Kim, Bum Soo; Kim, Seong-Jang; Pak, Kyoungjune
2016-06-01
Exact classifying between malignant and benign tumors in the parotid gland is important because the cancer has relatively poor prognosis. There have been several studies that F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) can differentiate between malignant and benign parotid gland tumors. However, the role of FDG PET is still controversial because many benign parotid gland tumors, such as Warthin's tumor and pleomorphic adenoma, show high FDG uptake. We hypothesized that metabolic heterogeneity would differentiate malignant parotid tumors because tumoral heterogeneity is an important characteristic in the malignancies. From January 2010 to April 2015, we retrospectively reviewed the 46 patients who showed FDG uptake at the parotid gland. To differentiate malignant parotid gland tumors, we obtained maximum SUV and mean SUV. Metabolic tumor volume and total lesion glycolysis were measured as metabolic volumetric parameters. We also included heterogeneity parameters of FDG PET such as heterogeneity factor (HF) and the coefficient of variation for all patients. There was significant difference of HF between malignant (-0.30 ± 0.25; range -0.937 to -0.084) and benign parotid gland tumors (-0.06 ± 0.05; range -0.291 to -0.012; p parotid gland tumors (p = 0.002). Our results suggest that HF can be utilized as a reliable and non-invasive method for differentiation of malignant and benign parotid gland tumors.
Directory of Open Access Journals (Sweden)
S. I. Bartsev
2015-06-01
Full Text Available A possible method for experimental determination of parameters of the previously proposed continual mathematical model of soil organic matter transformation is theoretically considered in this paper. The previously proposed by the authors continual model of soil organic matter transformation, based on using the rate of matter transformation as a continual scale of its recalcitrance, describes the transformation process phenomenologically without going into detail of microbiological mechanisms of transformation. Thereby simplicity of the model is achieved. The model is represented in form of one differential equation in firstorder partial derivatives, which has an analytical solution in elementary functions. The model equation contains a small number of empirical parameters which generally characterize environmental conditions where the matter transformation process occurs and initial properties of the plant litter. Given the values of these parameters, it is possible to calculate dynamics of soil organic matter stocks and its distribution over transformation rate. In the present study, possible approaches for determination of the model parameters are considered and a simple method of their experimental measurement is proposed. An experiment of an incubation of chemically homogeneous samples in soil and multiple sequential measurement of the sample mass loss with time is proposed. An equation of time dynamics of mass loss of incubated homogeneous sample is derived from the basic assumption of the presented soil organic matter transformation model. Thus, fitting by the least squares method the parameters of sample mass loss curve calculated according the proposed mass loss dynamics equation allows to determine the parameters of the general equation of soil organic transformation model.
A matrix model for valuing anesthesia service with the resource-based relative value system.
Sinclair, David R; Lubarsky, David A; Vigoda, Michael M; Birnbach, David J; Harris, Eric A; Behrens, Vicente; Bazan, Richard E; Williams, Steve M; Arheart, Kristopher; Candiotti, Keith A
2014-01-01
The purpose of this study was to propose a new crosswalk using the resource-based relative value system (RBRVS) that preserves the time unit component of the anesthesia service and disaggregates anesthesia billing into component parts (preoperative evaluation, intraoperative management, and postoperative evaluation). The study was designed as an observational chart and billing data review of current and proposed payments, in the setting of a preoperative holing area, intraoperative suite, and post anesthesia care unit. In total, 1,195 charts of American Society of Anesthesiology (ASA) physical status 1 through 5 patients were reviewed. No direct patient interventions were undertaken. Spearman correlations between the proposed RBRVS billing matrix payments and the current ASA relative value guide methodology payments were strong (r=0.94-0.96, Pbilling matrix yielded payments that were 3.0%±1.34% less than would have been expected from commercial insurers, using standard rates for commercial ASA relative value units and RBRVS relative value units. Compared with current Medicare reimbursement under the ASA relative value guide, reimbursement would almost double when converting to an RBRVS billing model. The greatest increases in Medicare reimbursement between the current system and proposed billing model occurred as anesthetic management complexity increased. The new crosswalk correlates with existing evaluation and management and intensive care medicine codes in an essentially revenue neutral manner when applied to the market-based rates of commercial insurers. The new system more highly values delivery of care to more complex patients undergoing more complex surgery and better represents the true value of anesthetic case management.
A matrix model for valuing anesthesia service with the resource-based relative value system
Sinclair, David R; Lubarsky, David A; Vigoda, Michael M; Birnbach, David J; Harris, Eric A; Behrens, Vicente; Bazan, Richard E; Williams, Steve M; Arheart, Kristopher; Candiotti, Keith A
2014-01-01
Background The purpose of this study was to propose a new crosswalk using the resource-based relative value system (RBRVS) that preserves the time unit component of the anesthesia service and disaggregates anesthesia billing into component parts (preoperative evaluation, intraoperative management, and postoperative evaluation). The study was designed as an observational chart and billing data review of current and proposed payments, in the setting of a preoperative holing area, intraoperative suite, and post anesthesia care unit. In total, 1,195 charts of American Society of Anesthesiology (ASA) physical status 1 through 5 patients were reviewed. No direct patient interventions were undertaken. Results Spearman correlations between the proposed RBRVS billing matrix payments and the current ASA relative value guide methodology payments were strong (r=0.94–0.96, P<0.001 for training, test, and overall). The proposed RBRVS-based billing matrix yielded payments that were 3.0%±1.34% less than would have been expected from commercial insurers, using standard rates for commercial ASA relative value units and RBRVS relative value units. Compared with current Medicare reimbursement under the ASA relative value guide, reimbursement would almost double when converting to an RBRVS billing model. The greatest increases in Medicare reimbursement between the current system and proposed billing model occurred as anesthetic management complexity increased. Conclusion The new crosswalk correlates with existing evaluation and management and intensive care medicine codes in an essentially revenue neutral manner when applied to the market-based rates of commercial insurers. The new system more highly values delivery of care to more complex patients undergoing more complex surgery and better represents the true value of anesthetic case management. PMID:25336964
Analysis of Model Parameters for a Polymer Filtration Simulator
Directory of Open Access Journals (Sweden)
N. Brackett-Rozinsky
2011-01-01
Full Text Available We examine a simulation model for polymer extrusion filters and determine its sensitivity to filter parameters. The simulator is a three-dimensional, time-dependent discretization of a coupled system of nonlinear partial differential equations used to model fluid flow and debris transport, along with statistical relationships that define debris distributions and retention probabilities. The flow of polymer fluid, and suspended debris particles, is tracked to determine how well a filter performs and how long it operates before clogging. A filter may have multiple layers, characterized by thickness, porosity, and average pore diameter. In this work, the thickness of each layer is fixed, while the porosities and pore diameters vary for a two-layer and three-layer study. The effects of porosity and average pore diameter on the measures of filter quality are calculated. For the three layer model, these effects are tested for statistical significance using analysis of variance. Furthermore, the effects of each pair of interacting parameters are considered. This allows the detection of complexity, where in changing two aspects of a filter together may generate results substantially different from what occurs when those same aspects change separately. The principal findings indicate that the first layer of a filter is the most important.
Bayesian parameter estimation for stochastic models of biological cell migration
Dieterich, Peter; Preuss, Roland
2013-08-01
Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.
Kahl, Gunnar M; Sidorenko, Yury; Gottesbüren, Bernhard
2015-04-01
As an option for higher-tier leaching assessment of pesticides in Europe according to FOCUS, pesticide properties can be estimated from lysimeter studies by inversely fitting parameter values (substance half-life DT50 and sorption coefficient to organic matter kom ). The aim of the study was to identify adequate methods for inverse modelling. Model parameters for the PEARL (Pesticide Emission Assessment at Regional and Local scales) model were estimated with different inverse optimisation algorithms - the Levenberg-Marquardt (LM), PD_MS2 (PEST Driver Multiple Starting Points 2) and SCEM (Shuffled Complex Evolution Metropolis) algorithms. Optimisation of crop factors and hydraulic properties was found to be an ill-posed problem, and all algorithms failed to identify reliable global minima for the hydrological parameters. All algorithms performed equally well in estimating pesticide sorption and degradation parameters. SCEM was in most cases the only algorithm that reliably calculated uncertainties. The most reliable approach for finding the best parameter set in the stepwise approach of optimising evapotranspiration, soil hydrology and pesticide parameters was to run only SCEM or a combined approach with more than one algorithm using the best fit of each step for further processing. PD_MS2 was well suited to a quick parameter search. The linear parameter uncertainty intervals estimated by LM and PD_MS2 were usually larger than by the non-linear method used by SCEM. With the suggested methods, parameter optimisation, together with reliable estimation of uncertainties, is possible also for relatively complex systems. © 2014 Society of Chemical Industry.
The model relationship of wastes for parameter design with green lean production of fresh water
Directory of Open Access Journals (Sweden)
Mastiadi Tamjidillah
2017-12-01
Full Text Available Lean manufacturing is about eliminating waste including the seven traditional, this writing suggested an observation on no value added of seven wastes influencing the process of fresh water production. The relationship value among waste was statistically verified to create an approach for continuous improvement action. Thus, the main goal of this research is to develop a methodology of relationship among wastes and eliminate them. In relationship among wastes, it could be known that the high value indicating how often it happened in the production process gave direct cause in the system of fresh water treatment. A recommendation to reduce the highest value of waste is by doing improvement on parameter setting to obtain an optimum mixing model between water supply, alum and stroke pump with Taguchi method. The interaction of relationship among these seven types of waste can be portrayed using fishbone diagram and a relationship model among wastes using PLS smart (partial least squares. The final relationship model with the highest value of waste was analyzed using off-line quality control to upgrade the quality of fresh water used as the basis to eliminate waste and find out the optimal parameter of mixing process in accordance with the health standard.
Microbial Communities Model Parameter Calculation for TSPA/SR
Energy Technology Data Exchange (ETDEWEB)
D. Jolley
2001-07-16
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M&O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M&O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow {Delta}G (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M&O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M&O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed.
Microbial Communities Model Parameter Calculation for TSPA/SR
International Nuclear Information System (INIS)
D. Jolley
2001-01-01
This calculation has several purposes. First the calculation reduces the information contained in ''Committed Materials in Repository Drifts'' (BSC 2001a) to useable parameters required as input to MING V1.O (CRWMS M and O 1998, CSCI 30018 V1.O) for calculation of the effects of potential in-drift microbial communities as part of the microbial communities model. The calculation is intended to replace the parameters found in Attachment II of the current In-Drift Microbial Communities Model revision (CRWMS M and O 2000c) with the exception of Section 11-5.3. Second, this calculation provides the information necessary to supercede the following DTN: M09909SPAMING1.003 and replace it with a new qualified dataset (see Table 6.2-1). The purpose of this calculation is to create the revised qualified parameter input for MING that will allow ΔG (Gibbs Free Energy) to be corrected for long-term changes to the temperature of the near-field environment. Calculated herein are the quadratic or second order regression relationships that are used in the energy limiting calculations to potential growth of microbial communities in the in-drift geochemical environment. Third, the calculation performs an impact review of a new DTN: M00012MAJIONIS.000 that is intended to replace the currently cited DTN: GS9809083 12322.008 for water chemistry data used in the current ''In-Drift Microbial Communities Model'' revision (CRWMS M and O 2000c). Finally, the calculation updates the material lifetimes reported on Table 32 in section 6.5.2.3 of the ''In-Drift Microbial Communities'' AMR (CRWMS M and O 2000c) based on the inputs reported in BSC (2001a). Changes include adding new specified materials and updating old materials information that has changed
Parameter Optimization of Single-Diode Model of Photovoltaic Cell Using Memetic Algorithm
Directory of Open Access Journals (Sweden)
Yourim Yoon
2015-01-01
Full Text Available This study proposes a memetic approach for optimally determining the parameter values of single-diode-equivalent solar cell model. The memetic algorithm, which combines metaheuristic and gradient-based techniques, has the merit of good performance in both global and local searches. First, 10 single algorithms were considered including genetic algorithm, simulated annealing, particle swarm optimization, harmony search, differential evolution, cuckoo search, least squares method, and pattern search; then their final solutions were used as initial vectors for generalized reduced gradient technique. From this memetic approach, we could further improve the accuracy of the estimated solar cell parameters when compared with single algorithm approaches.
Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models
Directory of Open Access Journals (Sweden)
Plinio Andrade
2015-09-01
Full Text Available In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well as decreasing variability as time increases. Different values of the memory parameter influence the speed of this decrease, making this heteroscedastic model very flexible. Its properties are used to implement an approximate Bayesian computation and MCMC scheme to obtain posterior estimates. We test and validate our method through simulations and real data from the big earthquake that occurred in 2010 in Chile.
mr. A C++ library for the matching and running of the Standard Model parameters
International Nuclear Information System (INIS)
Kniehl, Bernd A.; Veretin, Oleg L.; Pikelner, Andrey F.; Joint Institute for Nuclear Research, Dubna
2016-01-01
We present the C++ program library mr that allows us to reliably calculate the values of the running parameters in the Standard Model at high energy scales. The initial conditions are obtained by relating the running parameters in the MS renormalization scheme to observables at lower energies with full two-loop precision. The evolution is then performed in accordance with the renormalization group equations with full three-loop precision. Pure QCD corrections to the matching and running are included through four loops. We also provide a Mathematica interface for this program library.
The Unfolding of Value Sources During Online Business Model Transformation
Directory of Open Access Journals (Sweden)
Nadja Hoßbach
2016-12-01
Full Text Available Purpose: In the magazine publishing industry, viable online business models are still rare to absent. To prepare for the ‘digital future’ and safeguard their long-term survival, many publishers are currently in the process of transforming their online business model. Against this backdrop, this study aims to develop a deeper understanding of (1 how the different building blocks of an online business model are transformed over time and (2 how sources of value creation unfold during this transformation process. Methodology: To answer our research question, we conducted a longitudinal case study with a leading German business magazine publisher (called BIZ. Data was triangulated from multiple sources including interviews, internal documents, and direct observations. Findings: Based on our case study, we nd that BIZ used the transformation process to differentiate its online business model from its traditional print business model along several dimensions, and that BIZ’s online business model changed from an efficiency- to a complementarity- to a novelty-based model during this process. Research implications: Our findings suggest that different business model transformation phases relate to different value sources, questioning the appropriateness of value source-based approaches for classifying business models. Practical implications: The results of our case study highlight the need for online-offline business model differentiation and point to the important distinction between service and product differentiation. Originality: Our study contributes to the business model literature by applying a dynamic and holistic perspective on the link between online business model changes and unfolding value sources.
Parameter-free methods distinguish Wnt pathway models and guide design of experiments
MacLean, Adam L.
2015-02-17
The canonical Wnt signaling pathway, mediated by β-catenin, is crucially involved in development, adult stem cell tissue maintenance, and a host of diseases including cancer. We analyze existing mathematical models of Wnt and compare them to a new Wnt signaling model that targets spatial localization; our aim is to distinguish between the models and distill biological insight from them. Using Bayesian methods we infer parameters for each model from mammalian Wnt signaling data and find that all 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 regulation: the new model, via control of shuttling and degradation parameters, permits multiple stable steady states corresponding to stem-like vs. committed cell states in the differentiation hierarchy. Our analysis also identifies groups of variables that should be measured to fully characterize and discriminate between competing models, and thus serves as a guide for performing minimal experiments for model comparison.
Optimization of Allelic Combinations Controlling Parameters of a Peach Quality Model.
Quilot-Turion, Bénédicte; Génard, Michel; Valsesia, Pierre; Memmah, Mohamed-Mahmoud
2016-01-01
Process-based models are effective tools to predict the phenotype of an individual in different growing conditions. Combined with a quantitative trait locus (QTL) mapping approach, it is then possible to predict the behavior of individuals with any combinations of alleles. However the number of simulations to explore the realm of possibilities may become infinite. Therefore, the use of an efficient optimization algorithm to intelligently explore the search space becomes imperative. The optimization algorithm has to solve a multi-objective problem, since the phenotypes of interest are usually a complex of traits, to identify the individuals with best tradeoffs between those traits. In this study we proposed to unroll such a combined approach in the case of peach fruit quality described through three targeted traits, using a process-based model with seven parameters controlled by QTL. We compared a current approach based on the optimization of the values of the parameters with a more evolved way to proceed which consists in the direct optimization of the alleles controlling the parameters. The optimization algorithm has been adapted to deal with both continuous and combinatorial problems. We compared the spaces of parameters obtained with different tactics and the phenotype of the individuals resulting from random simulations and optimization in these spaces. The use of a genetic model enabled the restriction of the dimension of the parameter space toward more feasible combinations of parameter values, reproducing relationships between parameters as observed in a real progeny. The results of this study demonstrated the potential of such an approach to refine the solutions toward more realistic ideotypes. Perspectives of improvement are discussed.
Modelled basic parameters for semi-industrial irradiation plant design
International Nuclear Information System (INIS)
Mangussi, J.
2009-01-01
The basic parameters of an irradiation plant design are the total activity, the product uniformity ratio and the efficiency process. The target density, the minimum dose required and the throughput depends on the use to which the irradiator will be put at. In this work, a model for calculating the specific dose rate at several depths in an infinite homogeneous medium produced by a slab source irradiator is presented. The product minimum dose rate for a set of target thickness is obtained. The design method steps are detailed and an illustrative example is presented. (author)
Lumped-parameter fuel rod model for rapid thermal transients
International Nuclear Information System (INIS)
Perkins, K.R.; Ramshaw, J.D.
1975-07-01
The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company
Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?
Valente, Giordano; Pitto, Lorenzo; Testi, Debora; Seth, Ajay; Delp, Scott L; Stagni, Rita; Viceconti, Marco; Taddei, Fulvia
2014-01-01
Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312) across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force predictions could be
Are subject-specific musculoskeletal models robust to the uncertainties in parameter identification?
Directory of Open Access Journals (Sweden)
Giordano Valente
Full Text Available Subject-specific musculoskeletal modeling can be applied to study musculoskeletal disorders, allowing inclusion of personalized anatomy and properties. Independent of the tools used for model creation, there are unavoidable uncertainties associated with parameter identification, whose effect on model predictions is still not fully understood. The aim of the present study was to analyze the sensitivity of subject-specific model predictions (i.e., joint angles, joint moments, muscle and joint contact forces during walking to the uncertainties in the identification of body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. The uncertainties in input variables had a moderate effect on model predictions, as muscle and joint contact forces showed maximum standard deviation of 0.3 times body-weight and maximum range of 2.1 times body-weight. In addition, the output variables significantly correlated with few input variables (up to 7 out of 312 across the gait cycle, including the geometry definition of larger muscles and the maximum muscle tension in limited gait portions. Although we found subject-specific models not markedly sensitive to parameter identification, researchers should be aware of the model precision in relation to the intended application. In fact, force
Taming Many-Parameter BSM Models with Bayesian Neural Networks
Kuchera, M. P.; Karbo, A.; Prosper, H. B.; Sanchez, A.; Taylor, J. Z.
2017-09-01
The search for physics Beyond the Standard Model (BSM) is a major focus of large-scale high energy physics experiments. One method is to look for specific deviations from the Standard Model that are predicted by BSM models. In cases where the model has a large number of free parameters, standard search methods become intractable due to computation time. This talk presents results using Bayesian Neural Networks, a supervised machine learning method, to enable the study of higher-dimensional models. The popular phenomenological Minimal Supersymmetric Standard Model was studied as an example of the feasibility and usefulness of this method. Graphics Processing Units (GPUs) are used to expedite the calculations. Cross-section predictions for 13 TeV proton collisions will be presented. My participation in the Conference Experience for Undergraduates (CEU) in 2004-2006 exposed me to the national and global significance of cutting-edge research. At the 2005 CEU, I presented work from the previous summer's SULI internship at Lawrence Berkeley Laboratory, where I learned to program while working on the Majorana Project. That work inspired me to follow a similar research path, which led me to my current work on computational methods applied to BSM physics.
Bayesian analysis of inflation: Parameter estimation for single field models
International Nuclear Information System (INIS)
Mortonson, Michael J.; Peiris, Hiranya V.; Easther, Richard
2011-01-01
Future astrophysical data sets promise to strengthen constraints on models of inflation, and extracting these constraints requires methods and tools commensurate with the quality of the data. In this paper we describe ModeCode, a new, publicly available code that computes the primordial scalar and tensor power spectra for single-field inflationary models. ModeCode solves the inflationary mode equations numerically, avoiding the slow roll approximation. It is interfaced with CAMB and CosmoMC to compute cosmic microwave background angular power spectra and perform likelihood analysis and parameter estimation. ModeCode is easily extendable to additional models of inflation, and future updates will include Bayesian model comparison. Errors from ModeCode contribute negligibly to the error budget for analyses of data from Planck or other next generation experiments. We constrain representative single-field models (φ n with n=2/3, 1, 2, and 4, natural inflation, and 'hilltop' inflation) using current data, and provide forecasts for Planck. From current data, we obtain weak but nontrivial limits on the post-inflationary physics, which is a significant source of uncertainty in the predictions of inflationary models, while we find that Planck will dramatically improve these constraints. In particular, Planck will link the inflationary dynamics with the post-inflationary growth of the horizon, and thus begin to probe the ''primordial dark ages'' between TeV and grand unified theory scale energies.
Finite element modeling to analyze TEER values across silicon nanomembranes.
Khire, Tejas S; Nehilla, Barrett J; Getpreecharsawas, Jirachai; Gracheva, Maria E; Waugh, Richard E; McGrath, James L
2018-01-05
Silicon nanomembranes are ultrathin, highly permeable, optically transparent and biocompatible substrates for the construction of barrier tissue models. Trans-epithelial/endothelial electrical resistance (TEER) is often used as a non-invasive, sensitive and quantitative technique to assess barrier function. The current study characterizes the electrical behavior of devices featuring silicon nanomembranes to facilitate their application in TEER studies. In conventional practice with commercial systems, raw resistance values are multiplied by the area of the membrane supporting cell growth to normalize TEER measurements. We demonstrate that under most circumstances, this multiplication does not 'normalize' TEER values as is assumed, and that the assumption is worse if applied to nanomembrane chips with a limited active area. To compare the TEER values from nanomembrane devices to those obtained from conventional polymer track-etched (TE) membranes, we develop finite element models (FEM) of the electrical behavior of the two membrane systems. Using FEM and parallel cell-culture experiments on both types of membranes, we successfully model the evolution of resistance values during the growth of endothelial monolayers. Further, by exploring the relationship between the models we develop a 'correction' function, which when applied to nanomembrane TEER, maps to experiments on conventional TE membranes. In summary, our work advances the the utility of silicon nanomembranes as substrates for barrier tissue models by developing an interpretation of TEER values compatible with conventional systems.
Classification of customer lifetime value models using Markov chain
Permana, Dony; Pasaribu, Udjianna S.; Indratno, Sapto W.; Suprayogi
2017-10-01
A firm’s potential reward in future time from a customer can be determined by customer lifetime value (CLV). There are some mathematic methods to calculate it. One method is using Markov chain stochastic model. Here, a customer is assumed through some states. Transition inter the states follow Markovian properties. If we are given some states for a customer and the relationships inter states, then we can make some Markov models to describe the properties of the customer. As Markov models, CLV is defined as a vector contains CLV for a customer in the first state. In this paper we make a classification of Markov Models to calculate CLV. Start from two states of customer model, we make develop in many states models. The development a model is based on weaknesses in previous model. Some last models can be expected to describe how real characters of customers in a firm.
A new method for determination of parameters in sewer pollutant transformation process model.
Jiang, F; Leung, H W D; Li, S Y; Lin, G S; Chen, G H
2007-11-01
Understanding pollutant transformation in sewers is important in controlling odor emission from pressure mains as well as in assessing organic pollutant removal capacity of gravity sewers. Sewer process models have thus been developed to quantify the pollutant transformation processes under various sewer conditions. The quantification largely depends on model parameter values, in particular the kinetic and stoichiometric parameters related to microbial activities. The current approaches not only involve a large amount of experimental work but also may induce significant errors when microbial reactions cannot be differentiated effectively during the experiments. Therefore, this study is aimed at developing a new method that can reduce experimental work significantly. The proposed method utilizes a genetic algorithm (GA) to enable the determination with a single set of batch experiments. To study the feasibility of the proposed method, a set of 72-hr batch experiments was first conducted for determining the parameters of a sewer model developed in this study, which adopted a full version of the International Water Association (IWA) Activated Sludge Model No. 3 (ASM3) to describe the microbial activities in sewers. The results were then verified with two different sets of the batch experiments. Furthermore, dynamic variation data of dissolved oxygen level were collected at the outlet of a 1.5-km gravity sewer to validate the determined parameters. All the results showed that the proposed parameter determination method is effective.
Building X-ray pulsar timing model without the use of radio parameters
Sun,