A Multiagent Cooperation Model Based on Trust Rating in Dynamic Infinite Interaction Environment

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Sixia Fan

2018-01-01

Full Text Available To improve the liveness of agents and enhance trust and collaboration in multiagent system, a new cooperation model based on trust rating in dynamic infinite interaction environment (TR-DII is proposed. TR-DII model is used to control agent’s autonomy and selfishness and to make agent do the rational decision. TR-DII model is based on two important components. One is dynamic repeated interaction structure, and the other is trust rating. The dynamic repeated interaction structure is formed with multistage inviting and evaluating actions. It transforms agents’ interactions into an infinity task allocation environment, where controlled and renewable cycle is a component most agent models ignored. Additionally, it influences the expectations and behaviors of agents which may not appear in one-shot time but may appear in long-time cooperation. Moreover, with rewards and punishments mechanism (RPM, the trust rating (TR is proposed to control agent blindness in selection phase. However, RPM is the factor that directly influences decisions, not the reputation as other models have suggested. Meanwhile, TR could monitor agent’s statuses in which they could be trustworthy or untrustworthy. Also, it refines agent’s disrepute in a new way which is ignored by the others. Finally, grids puzzle experiment has been used to test TR-DII model and other five models are used as comparisons. The results show that TR-DII model can effectively adjust the trust level between agents and makes the solvers be more trustworthy and do choices that are more rational. Moreover, through interaction result feedback, TR-DII model could adjust the income function, to control cooperation reputation, and could achieve a closed-loop control.

A Numerical Study of Water Loss Rate Distributions in MDCT-based Human Airway Models

Science.gov (United States)

Wu, Dan; Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Lin, Ching-Long

2015-01-01

Both three-dimensional (3D) and one-dimensional (1D) computational fluid dynamics (CFD) methods are applied to study regional water loss in three multi-detector row computed-tomography (MDCT)-based human airway models at the minute ventilations of 6, 15 and 30 L/min. The overall water losses predicted by both 3D and 1D models in the entire respiratory tract agree with available experimental measurements. However, 3D and 1D models reveal different regional water loss rate distributions due to the 3D secondary flows formed at bifurcations. The secondary flows cause local skewed temperature and humidity distributions on inspiration acting to elevate the local water loss rate; and the secondary flow at the carina tends to distribute more cold air to the lower lobes. As a result, the 3D model predicts that the water loss rate first increases with increasing airway generation, and then decreases as the air approaches saturation, while the 1D model predicts a monotonic decrease of water loss rate with increasing airway generation. Moreover, the 3D (or 1D) model predicts relatively higher water loss rates in lower (or upper) lobes. The regional water loss rate can be related to the non-dimensional wall shear stress (τ*) by the non-dimensional mass transfer coefficient (h0*) as h0* = 1.15 τ*0.272, R = 0.842. PMID:25869455

Probabilistic estimation of residential air exchange rates for population-based human exposure modeling

Science.gov (United States)

Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER meas...

Dataset for Probabilistic estimation of residential air exchange rates for population-based exposure modeling

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset provides the city-specific air exchange rate measurements, modeled, literature-based as well as housing characteristics. This dataset is associated with...

A quantitative prediction model of SCC rate for nuclear structure materials in high temperature water based on crack tip creep strain rate

International Nuclear Information System (INIS)

Yang, F.Q.; Xue, H.; Zhao, L.Y.; Fang, X.R.

2014-01-01

Highlights: • Creep is considered to be the primary mechanical factor of crack tip film degradation. • The prediction model of SCC rate is based on crack tip creep strain rate. • The SCC rate calculated at the secondary stage of creep is recommended. • The effect of stress intensity factor on SCC growth rate is discussed. - Abstract: The quantitative prediction of stress corrosion cracking (SCC) of structure materials is essential in safety assessment of nuclear power plants. A new quantitative prediction model is proposed by combining the Ford–Andresen model, a crack tip creep model and an elastic–plastic finite element method. The creep at the crack tip is considered to be the primary mechanical factor of protective film degradation, and the creep strain rate at the crack tip is suggested as primary mechanical factor in predicting the SCC rate. The SCC rates at secondary stage of creep are recommended when using the approach introduced in this study to predict the SCC rates of materials in high temperature water. The proposed approach can be used to understand the SCC crack growth in structural materials of light water reactors

An Empirical Rate Constant Based Model to Study Capacity Fading in Lithium Ion Batteries

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Srivatsan Ramesh

2015-01-01

Full Text Available A one-dimensional model based on solvent diffusion and kinetics to study the formation of the SEI (solid electrolyte interphase layer and its impact on the capacity of a lithium ion battery is developed. The model uses the earlier work on silicon oxidation but studies the kinetic limitations of the SEI growth process. The rate constant of the SEI formation reaction at the anode is seen to play a major role in film formation. The kinetics of the reactions for capacity fading for various battery systems are studied and the rate constants are evaluated. The model is used to fit the capacity fade in different battery systems.

The contagious nature of imprisonment: an agent-based model to explain racial disparities in incarceration rates.

Science.gov (United States)

Lum, Kristian; Swarup, Samarth; Eubank, Stephen; Hawdon, James

2014-09-06

We build an agent-based model of incarceration based on the susceptible-infected-suspectible (SIS) model of infectious disease propagation. Our central hypothesis is that the observed racial disparities in incarceration rates between Black and White Americans can be explained as the result of differential sentencing between the two demographic groups. We demonstrate that if incarceration can be spread through a social influence network, then even relatively small differences in sentencing can result in large disparities in incarceration rates. Controlling for effects of transmissibility, susceptibility and influence network structure, our model reproduces the observed large disparities in incarceration rates given the differences in sentence lengths for White and Black drug offenders in the USA without extensive parameter tuning. We further establish the suitability of the SIS model as applied to incarceration by demonstrating that the observed structural patterns of recidivism are an emergent property of the model. In fact, our model shows a remarkably close correspondence with California incarceration data. This work advances efforts to combine the theories and methods of epidemiology and criminology.

Probabilistic short-term forecasting of eruption rate at Kīlauea Volcano using a physics-based model

Science.gov (United States)

Anderson, K. R.

2016-12-01

Deterministic models of volcanic eruptions yield predictions of future activity conditioned on uncertainty in the current state of the system. Physics-based eruption models are well-suited for deterministic forecasting as they can relate magma physics with a wide range of observations. Yet, physics-based eruption forecasting is strongly limited by an inadequate understanding of volcanic systems, and the need for eruption models to be computationally tractable. At Kīlauea Volcano, Hawaii, episodic depressurization-pressurization cycles of the magma system generate correlated, quasi-exponential variations in ground deformation and surface height of the active summit lava lake. Deflations are associated with reductions in eruption rate, or even brief eruptive pauses, and thus partly control lava flow advance rates and associated hazard. Because of the relatively well-understood nature of Kīlauea's shallow magma plumbing system, and because more than 600 of these events have been recorded to date, they offer a unique opportunity to refine a physics-based effusive eruption forecasting approach and apply it to lava eruption rates over short (hours to days) time periods. A simple physical model of the volcano ascribes observed data to temporary reductions in magma supply to an elastic reservoir filled with compressible magma. This model can be used to predict the evolution of an ongoing event, but because the mechanism that triggers events is unknown, event durations are modeled stochastically from previous observations. A Bayesian approach incorporates diverse data sets and prior information to simultaneously estimate uncertain model parameters and future states of the system. Forecasts take the form of probability distributions for eruption rate or cumulative erupted volume at some future time. Results demonstrate the significant uncertainties that still remain even for short-term eruption forecasting at a well-monitored volcano - but also the value of a physics-based

Inflation Rate Modelling in Indonesia

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Rezzy Eko Caraka

2016-10-01

Full Text Available The purposes of this research were to analyse: (i Modelling the inflation rate in Indonesia with parametric regression. (ii Modelling the inflation rate in Indonesia using non-parametric regression spline multivariable (iii Determining the best model the inflation rate in Indonesia (iv Explaining the relationship inflation model parametric and non-parametric regression spline multivariable. Based on the analysis using the two methods mentioned the coefficient of determination (R2 in parametric regression of 65.1% while non-parametric amounted to 99.39%. To begin with, the factor of money supply or money stock, crude oil prices and the rupiah exchange rate against the dollar is significant on the rate of inflation. The stability of inflation is essential to support sustainable economic development and improve people's welfare. In conclusion, unstable inflation will complicate business planning business activities, both in production and investment activities as well as in the pricing of goods and services produced.DOI: 10.15408/etk.v15i2.3260

Modeling the Volatility of Exchange Rates: GARCH Models

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Fahima Charef

2017-03-01

Full Text Available The modeling of the dynamics of the exchange rate at a long time remains a financial and economic research center. In our research we tried to study the relationship between the evolution of exchange rates and macroeconomic fundamentals. Our empirical study is based on a series of exchange rates for the Tunisian dinar against three currencies of major trading partners (dollar, euro, yen and fundamentals (the terms of trade, the inflation rate, the interest rate differential, of monthly data, from jan 2000 to dec-2014, for the case of the Tunisia. We have adopted models of conditional heteroscedasticity (ARCH, GARCH, EGARCH, TGARCH. The results indicate that there is a partial relationship between the evolution of the Tunisian dinar exchange rates and macroeconomic variables.

Comparison of two lung clearance models based on the dissolution rates of oxidized depleted uranium

Energy Technology Data Exchange (ETDEWEB)

Crist, K.C.

1984-10-01

An in-vitro dissolution study was conducted on two respirable oxidized depleted uranium samples. The dissolution rates generated from this study were then utilized in the International Commission on Radiological Protection Task Group lung clearance model and a lung clearance model proposed by Cuddihy. Predictions from both models based on the dissolution rates of the amount of oxidized depleted uranium that would be cleared to blood from the pulmonary region following an inhalation exposure were compared. It was found that the predictions made by both models differed considerably. The difference between the predictions was attributed to the differences in the way each model perceives the clearance from the pulmonary region. 33 references, 11 figures, 9 tables.

Comparison of two lung clearance models based on the dissolution rates of oxidized depleted uranium

International Nuclear Information System (INIS)

Crist, K.C.

1984-10-01

An in-vitro dissolution study was conducted on two respirable oxidized depleted uranium samples. The dissolution rates generated from this study were then utilized in the International Commission on Radiological Protection Task Group lung clearance model and a lung clearance model proposed by Cuddihy. Predictions from both models based on the dissolution rates of the amount of oxidized depleted uranium that would be cleared to blood from the pulmonary region following an inhalation exposure were compared. It was found that the predictions made by both models differed considerably. The difference between the predictions was attributed to the differences in the way each model perceives the clearance from the pulmonary region. 33 references, 11 figures, 9 tables

A Model-Based Bayesian Estimation of the Rate of Evolution of VNTR Loci in Mycobacterium tuberculosis

Science.gov (United States)

Aandahl, R. Zachariah; Reyes, Josephine F.; Sisson, Scott A.; Tanaka, Mark M.

2012-01-01

Variable numbers of tandem repeats (VNTR) typing is widely used for studying the bacterial cause of tuberculosis. Knowledge of the rate of mutation of VNTR loci facilitates the study of the evolution and epidemiology of Mycobacterium tuberculosis. Previous studies have applied population genetic models to estimate the mutation rate, leading to estimates varying widely from around to per locus per year. Resolving this issue using more detailed models and statistical methods would lead to improved inference in the molecular epidemiology of tuberculosis. Here, we use a model-based approach that incorporates two alternative forms of a stepwise mutation process for VNTR evolution within an epidemiological model of disease transmission. Using this model in a Bayesian framework we estimate the mutation rate of VNTR in M. tuberculosis from four published data sets of VNTR profiles from Albania, Iran, Morocco and Venezuela. In the first variant, the mutation rate increases linearly with respect to repeat numbers (linear model); in the second, the mutation rate is constant across repeat numbers (constant model). We find that under the constant model, the mean mutation rate per locus is (95% CI: ,)and under the linear model, the mean mutation rate per locus per repeat unit is (95% CI: ,). These new estimates represent a high rate of mutation at VNTR loci compared to previous estimates. To compare the two models we use posterior predictive checks to ascertain which of the two models is better able to reproduce the observed data. From this procedure we find that the linear model performs better than the constant model. The general framework we use allows the possibility of extending the analysis to more complex models in the future. PMID:22761563

Comparison of rate theory based modeling calculations with the surveillance test results of Korean light water reactors

International Nuclear Information System (INIS)

Lee, Gyeong Geun; Lee, Yong Bok; Kim, Min Chul; Kwon, Junh Yun

2012-01-01

Neutron irradiation to reactor pressure vessel (RPV) steels causes a decrease in fracture toughness and an increase in yield strength while in service. It is generally accepted that the growth of point defect cluster (PDC) and copper rich precipitate (CRP) affects radiation hardening of RPV steels. A number of models have been proposed to account for the embrittlement of RPV steels. The rate theory based modeling mathematically described the evolution of radiation induced microstructures of ferritic steels under neutron irradiation. In this work, we compared the rate theory based modeling calculation with the surveillance test results of Korean Light Water Reactors (LWRs)

Multi-Frame Rate Based Multiple-Model Training for Robust Speaker Identification of Disguised Voice

DEFF Research Database (Denmark)

Prasad, Swati; Tan, Zheng-Hua; Prasad, Ramjee

2013-01-01

Speaker identification systems are prone to attack when voice disguise is adopted by the user. To address this issue,our paper studies the effect of using different frame rates on the accuracy of the speaker identification system for disguised voice.In addition, a multi-frame rate based multiple......-model training method is proposed. The experimental results show the superior performance of the proposed method compared to the commonly used single frame rate method for three types of disguised voice taken from the CHAINS corpus....

Research and realization of ultrasonic gas flow rate measurement based on ultrasonic exponential model.

Science.gov (United States)

Zheng, Dandan; Hou, Huirang; Zhang, Tao

2016-04-01

For ultrasonic gas flow rate measurement based on ultrasonic exponential model, when the noise frequency is close to that of the desired signals (called similar-frequency noise) or the received signal amplitude is small and unstable at big flow rate, local convergence of the algorithm genetic-ant colony optimization-3cycles may appear, and measurement accuracy may be affected. Therefore, an improved method energy genetic-ant colony optimization-3cycles (EGACO-3cycles) is proposed to solve this problem. By judging the maximum energy position of signal, the initial parameter range of exponential model can be narrowed and then the local convergence can be avoided. Moreover, a DN100 flow rate measurement system with EGACO-3cycles method is established based on NI PCI-6110 and personal computer. A series of experiments are carried out for testing the new method and the measurement system. It is shown that local convergence doesn't appear with EGACO-3cycles method when similar-frequency noises exist and flow rate is big. Then correct time of flight can be obtained. Furthermore, through flow calibration on this system, the measurement range ratio is achieved 500:1, and the measurement accuracy is 0.5% with a low transition velocity 0.3 m/s. Copyright © 2016 Elsevier B.V. All rights reserved.

Modeling low-dose-rate effects in irradiated bipolar-base oxides

International Nuclear Information System (INIS)

Graves, R.J.; Cirba, C.R.; Schrimpf, R.D.; Milanowski, R.J.; Saigne, F.; Michez, A.; Fleetwood, D.M.; Witczak, S.C.

1997-02-01

A physical model is developed to quantify the contribution of oxide-trapped charge to enhanced low-dose-rate gain degradation in BJTs. Simulations show that space charge limited transport is partially responsible for the low-dose-rate enhancement

Mixed effects modeling of proliferation rates in cell-based models: consequence for pharmacogenomics and cancer.

Directory of Open Access Journals (Sweden)

Hae Kyung Im

2012-02-01

Full Text Available The International HapMap project has made publicly available extensive genotypic data on a number of lymphoblastoid cell lines (LCLs. Building on this resource, many research groups have generated a large amount of phenotypic data on these cell lines to facilitate genetic studies of disease risk or drug response. However, one problem that may reduce the usefulness of these resources is the biological noise inherent to cellular phenotypes. We developed a novel method, termed Mixed Effects Model Averaging (MEM, which pools data from multiple sources and generates an intrinsic cellular growth rate phenotype. This intrinsic growth rate was estimated for each of over 500 HapMap cell lines. We then examined the association of this intrinsic growth rate with gene expression levels and found that almost 30% (2,967 out of 10,748 of the genes tested were significant with FDR less than 10%. We probed further to demonstrate evidence of a genetic effect on intrinsic growth rate by determining a significant enrichment in growth-associated genes among genes targeted by top growth-associated SNPs (as eQTLs. The estimated intrinsic growth rate as well as the strength of the association with genetic variants and gene expression traits are made publicly available through a cell-based pharmacogenomics database, PACdb. This resource should enable researchers to explore the mediating effects of proliferation rate on other phenotypes.

Relationship among reaction rate, release rate and efficiency of nanomachine-based targeted drug delivery.

Science.gov (United States)

Zhao, Qingying; Li, Min; Luo, Jun

2017-12-04

In nanomachine applications towards targeted drug delivery, drug molecules released by nanomachines propagate and chemically react with tumor cells in aqueous environment. If the nanomachines release drug molecules faster than the tumor cells react, it will result in loss and waste of drug molecules. It is a potential issue associated with the relationship among reaction rate, release rate and efficiency. This paper aims to investigate the relationship among reaction rate, release rate and efficiency based on two drug reception models. We expect to pave a way for designing a control method of drug release. We adopted two analytical methods that one is drug reception process based on collision with tumors and another is based on Michaelis Menten enzymatic kinetics. To evaluate the analytical formulations, we used the well-known simulation framework N3Sim to establish simulations. The analytical results of the relationship among reaction rate, release rate and efficiency is obtained, which match well with the numerical simulation results in a 3-D environment. Based upon two drug reception models, the results of this paper would be beneficial for designing a control method of nanomahine-based drug release.

Rate-based modelling and validation of a pilot absorber using MDEA enhanced with carbonic anhydrase (CA)

DEFF Research Database (Denmark)

Gaspar, Jozsef; Gladis, Arne; Woodley, John

2017-01-01

solvent-regeneration energy demand.The focus of this work is to develop a rate-based model for CO2 absorption using MDEA enhanced with CA and to validate it against pilot-scale absorption experiments. In this work, we compare model predictions to measured temperature and CO2 concentration profiles...

Modeling inflation rates and exchange rates in Ghana: application of multivariate GARCH models.

Science.gov (United States)

Nortey, Ezekiel Nn; Ngoh, Delali D; Doku-Amponsah, Kwabena; Ofori-Boateng, Kenneth

2015-01-01

This paper was aimed at investigating the volatility and conditional relationship among inflation rates, exchange rates and interest rates as well as to construct a model using multivariate GARCH DCC and BEKK models using Ghana data from January 1990 to December 2013. The study revealed that the cumulative depreciation of the cedi to the US dollar from 1990 to 2013 is 7,010.2% and the yearly weighted depreciation of the cedi to the US dollar for the period is 20.4%. There was evidence that, the fact that inflation rate was stable, does not mean that exchange rates and interest rates are expected to be stable. Rather, when the cedi performs well on the forex, inflation rates and interest rates react positively and become stable in the long run. The BEKK model is robust to modelling and forecasting volatility of inflation rates, exchange rates and interest rates. The DCC model is robust to model the conditional and unconditional correlation among inflation rates, exchange rates and interest rates. The BEKK model, which forecasted high exchange rate volatility for the year 2014, is very robust for modelling the exchange rates in Ghana. The mean equation of the DCC model is also robust to forecast inflation rates in Ghana.

Characterizing and modeling the pressure- and rate-dependent elastic-plastic-damage behaviors of polypropylene-based polymers

KAUST Repository

Pulungan, Ditho Ardiansyah

2018-02-24

Polymers in general exhibit pressure- and rate-dependent behavior. Modeling such behavior requires extensive, costly and time-consuming experimental work. Common simplifications may lead to severe inaccuracy when using the model for predicting the failure of structures. Here, we propose a viscoelastic viscoplastic damage model for polypropylene-based polymers. Such a set of constitutive equations can be used to describe the response of polypropylene under various strain-rates and stress-triaxiality conditions. Our model can also be applied to a broad range of thermoplastic polymers. We detail the experimental campaign that is needed to identify every parameter of the model at best. We validated the proposed model by performing 3-point bending tests at different loading speeds, where the load-displacement response of polypropylene beam up to failure was accurately predicted.

An Econometric Diffusion Model of Exchange Rate Movements within a Band - Implications for Interest Rate Differential and Credibility of Exchange Rate Policy

OpenAIRE

Rantala, Olavi

1992-01-01

The paper presents a model ofexchange rate movements within a specified exchange rate band enforced by central bank interventions. The model is based on the empirical observation that the exchange rate has usually been strictly inside the band, at least in Finland. In this model the distribution of the exchange rate is truncated lognormal from the edges towards the center of the band and hence quite different from the bimodal distribution of the standard target zone model. The model is estima...

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

Science.gov (United States)

Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

2016-10-01

In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

Solid formation in piperazine rate-based simulation

DEFF Research Database (Denmark)

Gaspar, Jozsef; Thomsen, Kaj; von Solms, Nicolas

2014-01-01

of view but also from a modeling perspective. The present work develops a rate-based model for CO2 absorption and desorption modeling for gas-liquid-solid systems and it is demonstrated for the piperazine CO2 capture process. This model is an extension of the DTU CAPCO2 model to precipitating systems....... It uses the extended UNIQUAC thermodynamic model for phase equilibria and thermal properties estimation. The mass and heat transfer phenomena is implemented in a film model approach, based on second order reactions kinetics. The transfer fluxes are calculated using the concentration of the dissolved...

Modeling Real Exchange Rate Persistence in Chile

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Leonardo Salazar

2017-07-01

Full Text Available The long and persistent swings in the real exchange rate have for a long time puzzled economists. Recent models built on imperfect knowledge economics seem to provide a theoretical explanation for this persistence. Empirical results, based on a cointegrated vector autoregressive (CVAR model, provide evidence of error-increasing behavior in prices and interest rates, which is consistent with the persistence observed in the data. The movements in the real exchange rate are compensated by movements in the interest rate spread, which restores the equilibrium in the product market when the real exchange rate moves away from its long-run benchmark value. Fluctuations in the copper price also explain the deviations of the real exchange rate from its long-run equilibrium value.

Validated analytical modeling of diesel engine regulated exhaust CO emission rate

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Waleed F Faris

2016-06-01

Full Text Available Albeit vehicle analytical models are often favorable for explainable mathematical trends, no analytical model has been developed of the regulated diesel exhaust CO emission rate for trucks yet. This research unprecedentedly develops and validates for trucks a model of the steady speed regulated diesel exhaust CO emission rate analytically. It has been found that the steady speed–based CO exhaust emission rate is based on (1 CO2 dissociation, (2 the water–gas shift reaction, and (3 the incomplete combustion of hydrocarbon. It has been found as well that the steady speed–based CO exhaust emission rate based on CO2 dissociation is considerably less than the rate that is based on the water–gas shift reaction. It has also been found that the steady speed–based CO exhaust emission rate based on the water–gas shift reaction is the dominant source of CO exhaust emission. The study shows that the average percentage of deviation of the steady speed–based simulated results from the corresponding field data is 1.7% for all freeway cycles with 99% coefficient of determination at the confidence level of 95%. This deviation of the simulated results from field data outperforms its counterpart of widely recognized models such as the comprehensive modal emissions model and VT-Micro for all freeway cycles.

Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.

Directory of Open Access Journals (Sweden)

Wei He

Full Text Available A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF for space instruments. A model for the system functional error rate (SFER is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA is presented. Based on experimental results of different ions (O, Si, Cl, Ti under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10-3(error/particle/cm2, while the MTTF is approximately 110.7 h.

DETERMINANTS OF SOVEREIGN RATING: FACTOR BASED ORDERED PROBIT MODELS FOR PANEL DATA ANALYSIS MODELING FRAMEWORK

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Dilek Teker

2013-01-01

Full Text Available The aim of this research is to compose a new rating methodology and provide credit notches to 23 countries which of 13 are developed and 10 are emerging. There are various literature that explains the determinants of credit ratings. Following the literature, we select 11 variables for our model which of 5 are eliminated by the factor analysis. We use specific dummies to investigate the structural breaks in time and cross section such as pre crises, post crises, BRIC membership, EU membership, OPEC membership, shipbuilder country and platinum reserved country. Then we run an ordered probit model and give credit notches to the countries. We use FITCH ratings as benchmark. Thus, at the end we compare the notches of FITCH with the ones we derive out of our estimated model.

Exploring the relationships among performance-based functional ability, self-rated disability, perceived instrumental support, and depression: a structural equation model analysis.

Science.gov (United States)

Weil, Joyce; Hutchinson, Susan R; Traxler, Karen

2014-11-01

Data from the Women's Health and Aging Study were used to test a model of factors explaining depressive symptomology. The primary purpose of the study was to explore the association between performance-based measures of functional ability and depression and to examine the role of self-rated physical difficulties and perceived instrumental support in mediating the relationship between performance-based functioning and depression. The inclusion of performance-based measures allows for the testing of functional ability as a clinical precursor to disability and depression: a critical, but rarely examined, association in the disablement process. Structural equation modeling supported the overall fit of the model and found an indirect relationship between performance-based functioning and depression, with perceived physical difficulties serving as a significant mediator. Our results highlight the complementary nature of performance-based and self-rated measures and the importance of including perception of self-rated physical difficulties when examining depression in older persons. © The Author(s) 2014.

A MODEL OF RATING FOR BANKS IN ROMANIA

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POPA ANAMARIA

2012-07-01

Full Text Available Abstract.In the paper the authors present a model of rating for the banking system. Thus we took into account the records of 11 banks in Romania, based on annual financial reports. The model classified the banks in seven categories according with notes used by Standard Poor’s and Moody’s rating Agencies.

Constitutive law for seismicity rate based on rate and state friction: Dieterich 1994 revisited.

Science.gov (United States)

Heimisson, E. R.; Segall, P.

2017-12-01

Dieterich [1994] derived a constitutive law for seismicity rate based on rate and state friction, which has been applied widely to aftershocks, earthquake triggering, and induced seismicity in various geological settings. Here, this influential work is revisited, and re-derived in a more straightforward manner. By virtue of this new derivation the model is generalized to include changes in effective normal stress associated with background seismicity. Furthermore, the general case when seismicity rate is not constant under constant stressing rate is formulated. The new derivation provides directly practical integral expressions for the cumulative number of events and rate of seismicity for arbitrary stressing history. Arguably, the most prominent limitation of Dieterich's 1994 theory is the assumption that seismic sources do not interact. Here we derive a constitutive relationship that considers source interactions between sub-volumes of the crust, where the stress in each sub-volume is assumed constant. Interactions are considered both under constant stressing rate conditions and for arbitrary stressing history. This theory can be used to model seismicity rate due to stress changes or to estimate stress changes using observed seismicity from triggered earthquake swarms where earthquake interactions and magnitudes are take into account. We identify special conditions under which influence of interactions cancel and the predictions reduces to those of Dieterich 1994. This remarkable result may explain the apparent success of the model when applied to observations of triggered seismicity. This approach has application to understanding and modeling induced and triggered seismicity, and the quantitative interpretation of geodetic and seismic data. It enables simultaneous modeling of geodetic and seismic data in a self-consistent framework. To date physics-based modeling of seismicity with or without geodetic data has been found to give insight into various processes

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

Science.gov (United States)

van den Ende, M. P. A.; Chen, J.; Ampuero, J.-P.; Niemeijer, A. R.

2018-05-01

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions.

Micromechanical modeling of rate-dependent behavior of Connective tissues.

Science.gov (United States)

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2017-03-07

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multistate cohort models with proportional transfer rates

DEFF Research Database (Denmark)

Schoen, Robert; Canudas-Romo, Vladimir

2006-01-01

of transfer rates. The two living state case and hierarchical multistate models with any number of living states are analyzed in detail. Applying our approach to 1997 U.S. fertility data, we find that observed rates of parity progression are roughly proportional over age. Our proportional transfer rate...... approach provides trajectories by parity state and facilitates analyses of the implications of changes in parity rate levels and patterns. More women complete childbearing at parity 2 than at any other parity, and parity 2 would be the modal parity in models with total fertility rates (TFRs) of 1.40 to 2......We present a new, broadly applicable approach to summarizing the behavior of a cohort as it moves through a variety of statuses (or states). The approach is based on the assumption that all rates of transfer maintain a constant ratio to one another over age. We present closed-form expressions...

Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance.

Science.gov (United States)

Chang, Hsien-Yen; Richards, Thomas M; Shermock, Kenneth M; Elder Dalpoas, Stacy; J Kan, Hong; Alexander, G Caleb; Weiner, Jonathan P; Kharrazi, Hadi

2017-12-01

Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models. We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization. We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill rates: primary 0-7 days, primary 0-30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders. The overall, primary 0-7, and 0-30 days fill rates were 72.30%, 59.82%, and 67.33%. The fill rates were similar between sexes but varied across different medication classifications, whereas the youngest had the highest rate. Adding fill rates modestly improved the performance of all models in explaining medical costs (improving concurrent R by 1.15% to 2.07%), followed by total costs (0.58% to 1.43%), and pharmacy costs (0.07% to 0.65%). The impact was greater for concurrent costs compared with prospective costs. Base models without diagnosis information showed the highest improvement using prescription fill rates. Prescription fill rates can modestly enhance claims-based risk prediction models; however, population-level improvements in predicting utilization are limited.

Generalization of exponential based hyperelastic to hyper-viscoelastic model for investigation of mechanical behavior of rate dependent materials.

Science.gov (United States)

Narooei, K; Arman, M

2018-03-01

In this research, the exponential stretched based hyperelastic strain energy was generalized to the hyper-viscoelastic model using the heredity integral of deformation history to take into account the strain rate effects on the mechanical behavior of materials. The heredity integral was approximated by the approach of Goh et al. to determine the model parameters and the same estimation was used for constitutive modeling. To present the ability of the proposed hyper-viscoelastic model, the stress-strain response of the thermoplastic elastomer gel tissue at different strain rates from 0.001 to 100/s was studied. In addition to better agreement between the current model and experimental data in comparison to the extended Mooney-Rivlin hyper-viscoelastic model, a stable material behavior was predicted for pure shear and balance biaxial deformation modes. To present the engineering application of current model, the Kolsky bars impact test of gel tissue was simulated and the effects of specimen size and inertia on the uniform deformation were investigated. As the mechanical response of polyurea was provided over wide strain rates of 0.0016-6500/s, the current model was applied to fit the experimental data. The results were shown more accuracy could be expected from the current research than the extended Ogden hyper-viscoelastic model. In the final verification example, the pig skin experimental data was used to determine parameters of the hyper-viscoelastic model. Subsequently, a specimen of pig skin at different strain rates was loaded to a fixed strain and the change of stress with time (stress relaxation) was obtained. The stress relaxation results were revealed the peak stress increases by applied strain rate until the saturated loading rate and the equilibrium stress with magnitude of 0.281MPa could be reached. Copyright © 2017 Elsevier Ltd. All rights reserved.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

Science.gov (United States)

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-02-07

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small

Modeling Electric Discharges with Entropy Production Rate Principles

Directory of Open Access Journals (Sweden)

Thomas Christen

2009-12-01

Full Text Available Under which circumstances are variational principles based on entropy production rate useful tools for modeling steady states of electric (gas discharge systems far from equilibrium? It is first shown how various different approaches, as Steenbeck’s minimum voltage and Prigogine’s minimum entropy production rate principles are related to the maximum entropy production rate principle (MEPP. Secondly, three typical examples are discussed, which provide a certain insight in the structure of the models that are candidates for MEPP application. It is then thirdly argued that MEPP, although not being an exact physical law, may provide reasonable model parameter estimates, provided the constraints contain the relevant (nonlinear physical effects and the parameters to be determined are related to disregarded weak constraints that affect mainly global entropy production. Finally, it is additionally conjectured that a further reason for the success of MEPP in certain far from equilibrium systems might be based on a hidden linearity of the underlying kinetic equation(s.

Relaxed Poisson cure rate models.

Science.gov (United States)

Rodrigues, Josemar; Cordeiro, Gauss M; Cancho, Vicente G; Balakrishnan, N

2016-03-01

The purpose of this article is to make the standard promotion cure rate model (Yakovlev and Tsodikov, ) more flexible by assuming that the number of lesions or altered cells after a treatment follows a fractional Poisson distribution (Laskin, ). It is proved that the well-known Mittag-Leffler relaxation function (Berberan-Santos, ) is a simple way to obtain a new cure rate model that is a compromise between the promotion and geometric cure rate models allowing for superdispersion. So, the relaxed cure rate model developed here can be considered as a natural and less restrictive extension of the popular Poisson cure rate model at the cost of an additional parameter, but a competitor to negative-binomial cure rate models (Rodrigues et al., ). Some mathematical properties of a proper relaxed Poisson density are explored. A simulation study and an illustration of the proposed cure rate model from the Bayesian point of view are finally presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of physically based constitutive models characterizing armor steel over wide temperature and strain rate ranges

International Nuclear Information System (INIS)

Xu, Zejian; Huang, Fenglei

2012-01-01

Both descriptive and predictive capabilities of five physically based constitutive models (PB, NNL, ZA, VA, and RK) are investigated and compared systematically, in characterizing plastic behavior of the 603 steel at temperatures ranging from 288 to 873 K, and strain rates ranging from 0.001 to 4500 s −1 . Determination of the constitutive parameters is introduced in detail for each model. Validities of the established models are checked by strain rate jump tests performed under different loading conditions. The results show that the RK and NNL models have better performance in the description of material behavior, especially the work-hardening effect, while the PB and VA models predict better. The inconsistency that is observed between the capabilities of description and prediction of the models indicates the existence of the minimum number of required fitting data, reflecting the degree of a model's requirement for basic data in parameter calibration. It is also found that the description capability of a model is dependent to a large extent on both its form and the number of its constitutive parameters, while the precision of prediction relies largely on the performance of description. In the selection of constitutive models, the experimental data and the constitutive models should be considered synthetically to obtain a better efficiency in material behavior characterization

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

Energy Technology Data Exchange (ETDEWEB)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira [Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Research and Clinical Collaborations, Siemens Healthcare, Erlangen 91052 (Germany); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ (United Kingdom); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Radiation Oncology, Centro di Riferimento Oncologico, Aviano 33081 (Italy); Department of Medical Physics, Centro di Riferimento Oncologico, Aviano 33081 (Italy)

2010-04-15

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term {alpha} and the dose per fraction. The estimated values of {alpha} and OER from data fitting were 0.396 Gy{sup -1} and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Correlation of a hypoxia based tumor control model with observed local control rates in nasopharyngeal carcinoma treated with chemoradiotherapy

International Nuclear Information System (INIS)

Avanzo, Michele; Stancanello, Joseph; Franchin, Giovanni; Sartor, Giovanna; Jena, Rajesh; Drigo, Annalisa; Dassie, Andrea; Gigante, Marco; Capra, Elvira

2010-01-01

Purpose: To extend the application of current radiation therapy (RT) based tumor control probability (TCP) models of nasopharyngeal carcinoma (NPC) to include the effects of hypoxia and chemoradiotherapy (CRT). Methods: A TCP model is described based on the linear-quadratic model modified to account for repopulation, chemotherapy, heterogeneity of dose to the tumor, and hypoxia. Sensitivity analysis was performed to determine which parameters exert the greatest influence on the uncertainty of modeled TCP. On the basis of the sensitivity analysis, the values of specific radiobiological parameters were set to nominal values reported in the literature for NPC or head and neck tumors. The remaining radiobiological parameters were determined by fitting TCP to clinical local control data from published randomized studies using both RT and CRT. Validation of the model was performed by comparison of estimated TCP and average overall local control rate (LCR) for 45 patients treated at the institution with conventional linear-accelerator-based or helical tomotherapy based intensity-modulated RT and neoadjuvant chemotherapy. Results: Sensitivity analysis demonstrates that the model is most sensitive to the radiosensitivity term α and the dose per fraction. The estimated values of α and OER from data fitting were 0.396 Gy -1 and 1.417. The model estimate of TCP (average 90.9%, range 26.9%-99.2%) showed good correlation with the LCR (86.7%). Conclusions: The model implemented in this work provides clinicians with a useful tool to predict the success rate of treatment, optimize treatment plans, and compare the effects of multimodality therapy.

Universal Rate Model Selector: A Method to Quickly Find the Best-Fit Kinetic Rate Model for an Experimental Rate Profile

Science.gov (United States)

2017-08-01

k2 – k1) 3.3 Universal Kinetic Rate Platform Development Kinetic rate models range from pure chemical reactions to mass transfer...14 8. The rate model that best fits the experimental data is a first-order or homogeneous catalytic reaction ...Avrami (7), and intraparticle diffusion (6) rate equations to name a few. A single fitting algorithm (kinetic rate model ) for a reaction does not

On-line monitoring and modelling based process control of high rate nitrification - lab scale experimental results

Energy Technology Data Exchange (ETDEWEB)

Pirsing, A. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Wiesmann, U. [Technische Univ. Berlin (Germany). Inst. fuer Verfahrenstechnik; Kelterbach, G. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Schaffranietz, U. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Roeck, H. [Technische Univ. Berlin (Germany). Inst. fuer Mess- und Regelungstechnik; Eichner, B. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Szukal, S. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie; Schulze, G. [Technische Univ. Berlin (Germany). Inst. fuer Anorganische und Analytische Chemie

1996-09-01

This paper presents a new concept for the control of nitrification in highly polluted waste waters. The approach is based on mathematical modelling. To determine the substrate degradation rates of the microorganisms involved, a mathematical model using gas measurement is used. A fuzzy-controller maximises the capacity utilisation efficiencies. The experiments carried out in a lab-scale reactor demonstrate that even with highly varying ammonia concentrations in the influent, the nitrogen concentrations in the effluent can be kept within legal limits. (orig.). With 11 figs.

A new constitutive model for prediction of impact rates response of polypropylene

Directory of Open Access Journals (Sweden)

Buckley C.P.

2012-08-01

Full Text Available This paper proposes a new constitutive model for predicting the impact rates response of polypropylene. Impact rates, as used here, refer to strain rates greater than 1000 1/s. The model is a physically based, three-dimensional constitutive model which incorporates the contributions of the amorphous, crystalline, pseudo-amorphous and entanglement networks to the constitutive response of polypropylene. The model mathematics is based on the well-known Glass-Rubber model originally developed for glassy polymers but the arguments have herein been extended to semi-crystalline polymers. In order to predict the impact rates behaviour of polypropylene, the model exploits the well-known framework of multiple processes yielding of polymers. This work argues that two dominant viscoelastic relaxation processes – the alpha- and beta-processes – can be associated with the yield responses of polypropylene observed at low-rate-dominant and impact-rates dominant loading regimes. Compression test data on polypropylene have been used to validate the model. The study has found that the model predicts quite well the experimentally observed nonlinear rate-dependent impact response of polypropylene.

Kalman Filter or VAR Models to Predict Unemployment Rate in Romania?

Directory of Open Access Journals (Sweden)

Simionescu Mihaela

2015-06-01

Full Text Available This paper brings to light an economic problem that frequently appears in practice: For the same variable, more alternative forecasts are proposed, yet the decision-making process requires the use of a single prediction. Therefore, a forecast assessment is necessary to select the best prediction. The aim of this research is to propose some strategies for improving the unemployment rate forecast in Romania by conducting a comparative accuracy analysis of unemployment rate forecasts based on two quantitative methods: Kalman filter and vector-auto-regressive (VAR models. The first method considers the evolution of unemployment components, while the VAR model takes into account the interdependencies between the unemployment rate and the inflation rate. According to the Granger causality test, the inflation rate in the first difference is a cause of the unemployment rate in the first difference, these data sets being stationary. For the unemployment rate forecasts for 2010-2012 in Romania, the VAR models (in all variants of VAR simulations determined more accurate predictions than Kalman filter based on two state space models for all accuracy measures. According to mean absolute scaled error, the dynamic-stochastic simulations used in predicting unemployment based on the VAR model are the most accurate. Another strategy for improving the initial forecasts based on the Kalman filter used the adjusted unemployment data transformed by the application of the Hodrick-Prescott filter. However, the use of VAR models rather than different variants of the Kalman filter methods remains the best strategy in improving the quality of the unemployment rate forecast in Romania. The explanation of these results is related to the fact that the interaction of unemployment with inflation provides useful information for predictions of the evolution of unemployment related to its components (i.e., natural unemployment and cyclical component.

Lapse rate modeling

DEFF Research Database (Denmark)

De Giovanni, Domenico

2010-01-01

prepayment models for mortgage backed securities, this paper builds a Rational Expectation (RE) model describing the policyholders' behavior in lapsing the contract. A market model with stochastic interest rates is considered, and the pricing is carried out through numerical approximation...

Lapse Rate Modeling

DEFF Research Database (Denmark)

De Giovanni, Domenico

prepayment models for mortgage backed securities, this paper builds a Rational Expectation (RE) model describing the policyholders' behavior in lapsing the contract. A market model with stochastic interest rates is considered, and the pricing is carried out through numerical approximation...

Measuring the impact of marginal tax rate reform on the revenue base of South Africa using a microsimulation tax model

Directory of Open Access Journals (Sweden)

Yolande Jordaan

2015-08-01

Full Text Available This paper is primarily concerned with the revenue and tax efficiency effects of adjustments to marginal tax rates on individual income as an instrument of possible tax reform. The hypothesis is that changes to marginal rates affect not only the revenue base, but also tax efficiency and the optimum level of taxes that supports economic growth. Using an optimal revenue-maximising rate (based on Laffer analysis, the elasticity of taxable income is derived with respect to marginal tax rates for each taxable-income category. These elasticities are then used to quantify the impact of changes in marginal rates on the revenue base and tax efficiency using a microsimulation (MS tax model. In this first paper on the research results, much attention is paid to the structure of the model and the way in which the database has been compiled. The model allows for the dissemination of individual taxpayers by income groups, gender, educational level, age group, etc. Simulations include a scenario with higher marginal rates which is also more progressive (as in the 1998/1999 fiscal year, in which case tax revenue increases but the increase is overshadowed by a more than proportional decrease in tax efficiency as measured by its deadweight loss. On the other hand, a lowering of marginal rates (to bring South Africa’s marginal rates more in line with those of its peers improves tax efficiency but also results in a substantial revenue loss. The estimated optimal individual tax to gross domestic product (GDP ratio in order to maximise economic growth (6.7 per cent shows a strong response to changes in marginal rates, and the results from this research indicate that a lowering of marginal rates would also move the actual ratio closer to its optimum level. Thus, the trade-off between revenue collected and tax efficiency should be carefully monitored when personal income tax reform is being considered.

Prediction of PWSCC in nickel base alloys using crack growth rate models

International Nuclear Information System (INIS)

Thompson, C.D.

1995-01-01

The Ford/Andresen slip dissolution SCC model, originally developed for stainless steel components in BWR environments, has been applied to Alloy 600 and Alloy X-750 tested in deaerated pure water chemistry. A method is described whereby the crack growth rates measured in compact tension specimens can be used to estimate crack growth in a component. Good agreement was found between model prediction and measured SCC in X-750 threaded fasteners over a wide range of temperatures, stresses, and material condition. Most data support the basic assumption of this model that cracks initiate early in life. The evidence supporting a particular SCC mechanism is mixed. Electrochemical repassivation data and estimates of oxide fracture strain indicate that the slip dissolution model can account for the observed crack growth rates, provided primary rather than secondary creep rates are used. However, approximately 100 cross-sectional TEM foils of SCC cracks including crack tips reveal no evidence of enhanced plasticity or unique dislocation patterns at the crack tip or along the crack to support a classic slip dissolution mechanism. No voids, hydrides,, or microcracks are found in the vicinity of the crack tips creating doubt about classic hydrogen related mechanisms. The bulk oxide films exhibit a surface oxide which is often different than the oxide found within a crack. Although bulk chromium concentration affects the rate of SCC, analytical data indicates the mechanism does not result from chromium depletion at the grain boundaries. The overall findings support a corrosion/dissolution mechanism but not one necessarily related to slip at the crack tip. (author). 12 refs, 27 figs

Decay rates of quarkonia and potential models

International Nuclear Information System (INIS)

Rai, Ajay Kumar; Pandya, J N; Vinodkumar, P C

2005-01-01

The decay rates of cc-bar and b-barb mesons have been studied with contributions from different correction terms. The corrections based on hard processes involved in the decays are quantitatively studied in the framework of different phenomenological potential models

Tax Rate and Tax Base Competition for Foreign Direct Investment

OpenAIRE

Peter Egger; Horst Raff

2011-01-01

This paper argues that the large reduction in corporate tax rates and only gradual widening of tax bases in many countries over the last decades are consistent with tougher international competition for foreign direct investment (FDI). To make this point we develop a model in which governments compete for FDI using corporate tax rates and tax bases. The model’s predictions regarding the slope of policy reaction functions and the response of equilibrium tax parameters to trade costs and mark...

Selecting Products Considering the Regret Behavior of Consumer: A Decision Support Model Based on Online Ratings

Directory of Open Access Journals (Sweden)

Xia Liang

2018-05-01

Full Text Available With the remarkable promotion of e-commerce platforms, consumers increasingly prefer to purchase products online. Online ratings facilitate consumers to choose among products. Thus, to help consumers effectively select products, it is necessary to provide decision support methods for consumers to trade online. Considering the decision makers are bounded rational, this paper proposes a novel decision support model for product selection based on online ratings, in which the regret aversion behavior of consumers is formulated. Massive online ratings provided by experienced consumers for alternative products associated with several evaluation attributes are obtained by software finders. Then, the evaluations of alternative products in format of stochastic variables are conducted. To select a desirable alternative product, a novel method is introduced to calculate gain and loss degrees of each alternative over others. Considering the regret behavior of consumers in the product selection process, the regret and rejoice values of alternative products for consumer are computed to obtain the perceived utility values of alternative products. According to the prior order of the evaluation attributes provided by the consumer, the prior weights of attributes are determined based on the perceived utility values of alternative products. Furthermore, the overall perceived utility values of alternative products are obtained to generate a ranking result. Finally, a practical example from Zol.com.cn for tablet computer selection is used to demonstrate the feasibility and practically of the proposed model.

Martingale Regressions for a Continuous Time Model of Exchange Rates

OpenAIRE

Guo, Zi-Yi

2017-01-01

One of the daunting problems in international finance is the weak explanatory power of existing theories of the nominal exchange rates, the so-called “foreign exchange rate determination puzzle”. We propose a continuous-time model to study the impact of order flow on foreign exchange rates. The model is estimated by a newly developed econometric tool based on a time-change sampling from calendar to volatility time. The estimation results indicate that the effect of order flow on exchange rate...

A model of clearance rate regulation in mussels

Science.gov (United States)

Fréchette, Marcel

2012-10-01

Clearance rate regulation has been modelled as an instantaneous response to food availability, independent of the internal state of the animals. This view is incompatible with latent effects during ontogeny and phenotypic flexibility in clearance rate. Internal-state regulation of clearance rate is required to account for these patterns. Here I develop a model of internal-state based regulation of clearance rate. External factors such as suspended sediments are included in the model. To assess the relative merits of instantaneous regulation and internal-state regulation, I modelled blue mussel clearance rate and growth using a DEB model. In the usual standard feeding module, feeding is governed by a Holling's Type II response to food concentration. In the internal-state feeding module, gill ciliary activity and thus clearance rate are driven by internal reserve level. Factors such as suspended sediments were not included in the simulations. The two feeding modules were compared on the basis of their ability to capture the impact of latent effects, of environmental heterogeneity in food abundance and of physiological flexibility on clearance rate and individual growth. The Holling feeding module was unable to capture the effect of any of these sources of variability. In contrast, the internal-state feeding module did so without any modification or ad hoc calibration. Latent effects, however, appeared transient. With simple annual variability in temperature and food concentration, the relationship between clearance rate and food availability predicted by the internal-state feeding module was quite similar to that observed in Norwegian fjords. I conclude that in contrast with the usual Holling feeding module, internal-state regulation of clearance rate is consistent with well-documented growth and clearance rate patterns.

Prediction of interest rate using CKLS model with stochastic parameters

International Nuclear Information System (INIS)

Ying, Khor Chia; Hin, Pooi Ah

2014-01-01

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ (j) of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ (j) , we assume that φ (j) depends on φ (j−m) , φ (j−m+1) ,…, φ (j−1) and the interest rate r j+n at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r j+n+1 of the interest rate at the next time point when the value r j+n of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r j+n+d at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters

Prediction of interest rate using CKLS model with stochastic parameters

Energy Technology Data Exchange (ETDEWEB)

Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

2014-06-19

The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater

International Nuclear Information System (INIS)

Turkdogan-Aydinol, F. Ilter; Yetilmezsoy, Kaan

2010-01-01

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R V ), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 (±3)% and an average volumetric TCOD removal rate of 6.87 (±3.93) kg TCOD removed /m 3 -day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98.

A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater

Energy Technology Data Exchange (ETDEWEB)

Turkdogan-Aydinol, F. Ilter, E-mail: aydin@yildiz.edu.tr [Yildiz Technical University, Faculty of Civil Engineering, Department of Environmental Engineering, 34220 Davutpasa, Esenler, Istanbul (Turkey); Yetilmezsoy, Kaan, E-mail: yetilmez@yildiz.edu.tr [Yildiz Technical University, Faculty of Civil Engineering, Department of Environmental Engineering, 34220 Davutpasa, Esenler, Istanbul (Turkey)

2010-10-15

A MIMO (multiple inputs and multiple outputs) fuzzy-logic-based model was developed to predict biogas and methane production rates in a pilot-scale 90-L mesophilic up-flow anaerobic sludge blanket (UASB) reactor treating molasses wastewater. Five input variables such as volumetric organic loading rate (OLR), volumetric total chemical oxygen demand (TCOD) removal rate (R{sub V}), influent alkalinity, influent pH and effluent pH were fuzzified by the use of an artificial intelligence-based approach. Trapezoidal membership functions with eight levels were conducted for the fuzzy subsets, and a Mamdani-type fuzzy inference system was used to implement a total of 134 rules in the IF-THEN format. The product (prod) and the centre of gravity (COG, centroid) methods were employed as the inference operator and defuzzification methods, respectively. Fuzzy-logic predicted results were compared with the outputs of two exponential non-linear regression models derived in this study. The UASB reactor showed a remarkable performance on the treatment of molasses wastewater, with an average TCOD removal efficiency of 93 ({+-}3)% and an average volumetric TCOD removal rate of 6.87 ({+-}3.93) kg TCOD{sub removed}/m{sup 3}-day, respectively. Findings of this study clearly indicated that, compared to non-linear regression models, the proposed MIMO fuzzy-logic-based model produced smaller deviations and exhibited a superior predictive performance on forecasting of both biogas and methane production rates with satisfactory determination coefficients over 0.98.

Bayes estimation of the general hazard rate model

International Nuclear Information System (INIS)

Sarhan, A.

1999-01-01

In reliability theory and life testing models, the life time distributions are often specified by choosing a relevant hazard rate function. Here a general hazard rate function h(t)=a+bt c-1 , where c, a, b are constants greater than zero, is considered. The parameter c is assumed to be known. The Bayes estimators of (a,b) based on the data of type II/item-censored testing without replacement are obtained. A large simulation study using Monte Carlo Method is done to compare the performance of Bayes with regression estimators of (a,b). The criterion for comparison is made based on the Bayes risk associated with the respective estimator. Also, the influence of the number of failed items on the accuracy of the estimators (Bayes and regression) is investigated. Estimations for the parameters (a,b) of the linearly increasing hazard rate model h(t)=a+bt, where a, b are greater than zero, can be obtained as the special case, letting c=2

47 CFR 65.800 - Rate base.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Rate base. 65.800 Section 65.800 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES (CONTINUED) INTERSTATE RATE OF RETURN PRESCRIPTION PROCEDURES AND METHODOLOGIES Rate Base § 65.800 Rate base. The rate base shall...

Improving Prediction Accuracy of a Rate-Based Model of an MEA-Based Carbon Capture Process for Large-Scale Commercial Deployment

Directory of Open Access Journals (Sweden)

Xiaobo Luo

2017-04-01

Full Text Available Carbon capture and storage (CCS technology will play a critical role in reducing anthropogenic carbon dioxide (CO2 emission from fossil-fired power plants and other energy-intensive processes. However, the increment of energy cost caused by equipping a carbon capture process is the main barrier to its commercial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been made to achieve optimal design and operation through process modeling, simulation, and optimization. Accurate models form an essential foundation for this purpose. This paper presents a study on developing a more accurate rate-based model in Aspen Plus® for the monoethanolamine (MEA-based carbon capture process by multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamic model, physical properties calculations, and a process model at the pilot plant scale, covering a wide range of pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacial area were updated by coding Fortran subroutines in Aspen Plus®. The validation results show that the correlation combination for the thermodynamic model used in this study has higher accuracy than those of three other key publications and the model prediction of the process model has a good agreement with the pilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combined cycle gas turbine (CCGT power plant. Shorter packing height and lower specific duty were achieved using this accurate model.

Experimental validation of a rate-based model for CO2 capture using an AMP solution

DEFF Research Database (Denmark)

Gabrielsen, Jostein; Svendsen, H. F.; Michelsen, Michael Locht

2007-01-01

Detailed experimental data, including temperature profiles over the absorber, for a carbon dioxide (CO"2) absorber with structured packing in an integrated laboratory pilot plant using an aqueous 2-amino-2-methyl-1-propanol (AMP) solution are presented. The experimental gas-liquid material balance...... was within an average of 3.5% for the experimental conditions presented. A predictive rate-based steady-state model for CO"2 absorption into an AMP solution, using an implicit expression for the enhancement factor, has been validated against the presented pilot plant data. Furthermore, a parameter...

Exchange rate predictability and state-of-the-art models

OpenAIRE

Yeșin, Pınar

2016-01-01

This paper empirically evaluates the predictive performance of the International Monetary Fund's (IMF) exchange rate assessments with respect to future exchange rate movements. The assessments of real trade-weighted exchange rates were conducted from 2006 to 2011, and were based on three state-of-the-art exchange rate models with a medium-term focus which were developed by the IMF. The empirical analysis using 26 advanced and emerging market economy currencies reveals that the "diagnosis" of ...

ECONOMETRIC APPROACH TO DIFFERENCE EQUATIONS MODELING OF EXCHANGE RATES CHANGES

Directory of Open Access Journals (Sweden)

Josip Arnerić

2010-12-01

Full Text Available Time series models that are commonly used in econometric modeling are autoregressive stochastic linear models (AR and models of moving averages (MA. Mentioned models by their structure are actually stochastic difference equations. Therefore, the objective of this paper is to estimate difference equations containing stochastic (random component. Estimated models of time series will be used to forecast observed data in the future. Namely, solutions of difference equations are closely related to conditions of stationary time series models. Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models and their variants. However, GARCH models will not be analyzed because the purpose of this research is to predict the value of the exchange rate in the levels within conditional mean equation and to determine whether the observed variable has a stable or explosive time path. Based on the estimated difference equation it will be examined whether Croatia is implementing a stable policy of exchange rates.

Estimation of rates-across-sites distributions in phylogenetic substitution models.

Science.gov (United States)

Susko, Edward; Field, Chris; Blouin, Christian; Roger, Andrew J

2003-10-01

Previous work has shown that it is often essential to account for the variation in rates at different sites in phylogenetic models in order to avoid phylogenetic artifacts such as long branch attraction. In most current models, the gamma distribution is used for the rates-across-sites distributions and is implemented as an equal-probability discrete gamma. In this article, we introduce discrete distribution estimates with large numbers of equally spaced rate categories allowing us to investigate the appropriateness of the gamma model. With large numbers of rate categories, these discrete estimates are flexible enough to approximate the shape of almost any distribution. Likelihood ratio statistical tests and a nonparametric bootstrap confidence-bound estimation procedure based on the discrete estimates are presented that can be used to test the fit of a parametric family. We applied the methodology to several different protein data sets, and found that although the gamma model often provides a good parametric model for this type of data, rate estimates from an equal-probability discrete gamma model with a small number of categories will tend to underestimate the largest rates. In cases when the gamma model assumption is in doubt, rate estimates coming from the discrete rate distribution estimate with a large number of rate categories provide a robust alternative to gamma estimates. An alternative implementation of the gamma distribution is proposed that, for equal numbers of rate categories, is computationally more efficient during optimization than the standard gamma implementation and can provide more accurate estimates of site rates.

Base Rates: Both Neglected and Intuitive

Science.gov (United States)

Pennycook, Gordon; Trippas, Dries; Handley, Simon J.; Thompson, Valerie A.

2014-01-01

Base-rate neglect refers to the tendency for people to underweight base-rate probabilities in favor of diagnostic information. It is commonly held that base-rate neglect occurs because effortful (Type 2) reasoning is required to process base-rate information, whereas diagnostic information is accessible to fast, intuitive (Type 1) processing…

Influence of government controls over the currency exchange rate in the evolution of Hurst's exponent: An autonomous agent-based model

Science.gov (United States)

Chávez Muñoz, Pablo; Fernandes da Silva, Marcus; Vivas Miranda, José; Claro, Francisco; Gomez Diniz, Raimundo

2007-12-01

We have studied the performance of the Hurst's index associated with the currency exchange rate in Brazil and Chile. It is shown that this index maps the degree of government control in the exchange rate. A model of supply and demand based in an autonomous agent is proposed, that simulates a virtual market of sale and purchase, where buyer or seller are forced to negotiate through an intermediary. According to this model, the average of the price of daily transactions correspond to the theoretical balance proposed by the law of supply and demand. The influence of an added tendency factor is also analyzed.

Rate-based modelling of combined SO2 removal and NH3 recycling integrated with an aqueous NH3-based CO2 capture process

International Nuclear Information System (INIS)

Li, Kangkang; Yu, Hai; Qi, Guojie; Feron, Paul; Tade, Moses; Yu, Jingwen; Wang, Shujuan

2015-01-01

Highlights: • A rigorous, rate-based model for an NH 3 –CO 2 –SO 2 –H 2 O system was developed. • Model predictions are in good agreement with pilot plant results. • >99.9% of SO 2 was captured and >99.9% of slipped ammonia was reused. • The process is highly adaptable to the variations of SO 2 /NH 3 level, temperatures. - Abstract: To reduce the costs of controlling emissions from coal-fired power stations, we propose an advanced and effective process of combined SO 2 removal and NH 3 recycling, which can be integrated with the aqueous NH 3 -based CO 2 capture process to simultaneously achieve SO 2 and CO 2 removal, NH 3 recycling and flue gas cooling in one process. A rigorous, rate-based model for an NH 3 –CO 2 –SO 2 –H 2 O system was developed and used to simulate the proposed process. The model was thermodynamically and kinetically validated by experimental results from the open literature and pilot-plant trials, respectively. Under typical flue gas conditions, the proposed process has SO 2 removal and NH 3 reuse efficiencies of >99.9%. The process is strongly adaptable to different scenarios such as high SO 2 levels in flue gas, high NH 3 levels from the CO 2 absorber and high flue gas temperatures, and has a low energy requirement. Because the process simplifies flue gas desulphurisation and resolves the problems of NH 3 loss and SO 2 removal, it could significantly reduce the cost of CO 2 and SO 2 capture by aqueous NH 3

Validation of the generalized model of two-phase thermosyphon loop based on experimental measurements of volumetric flow rate

Science.gov (United States)

Bieliński, Henryk

2016-09-01

The current paper presents the experimental validation of the generalized model of the two-phase thermosyphon loop. The generalized model is based on mass, momentum, and energy balances in the evaporators, rising tube, condensers and the falling tube. The theoretical analysis and the experimental data have been obtained for a new designed variant. The variant refers to a thermosyphon loop with both minichannels and conventional tubes. The thermosyphon loop consists of an evaporator on the lower vertical section and a condenser on the upper vertical section. The one-dimensional homogeneous and separated two-phase flow models were used in calculations. The latest minichannel heat transfer correlations available in literature were applied. A numerical analysis of the volumetric flow rate in the steady-state has been done. The experiment was conducted on a specially designed test apparatus. Ultrapure water was used as a working fluid. The results show that the theoretical predictions are in good agreement with the measured volumetric flow rate at steady-state.

Precision comparison of the erosion rates derived from 137Cs measurements models with predictions based on empirical relationship

International Nuclear Information System (INIS)

Yang Mingyi; Liu Puling; Li Liqing

2004-01-01

The soil samples were collected in 6 cultivated runoff plots with grid sampling method, and the soil erosion rates derived from 137 Cs measurements were calculated. The models precision of Zhang Xinbao, Zhou Weizhi, Yang Hao and Walling were compared with predictions based on empirical relationship, data showed that the precision of 4 models is high within 50m slope length except for the slope with low slope angle and short length. Relatively, the precision of Walling's model is better than that of Zhang Xinbao, Zhou Weizhi and Yang Hao. In addition, the relationship between parameter Γ in Walling's improved model and slope angle was analyzed, the ralation is: Y=0.0109 X 1.0072 . (authors)

Learning to maximize reward rate: a model based on semi-Markov decision processes.

Science.gov (United States)

Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

2014-01-01

WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

Empirical Model for Predicting Rate of Biogas Production | Adamu ...

African Journals Online (AJOL)

Rate of biogas production using cow manure as substrate was monitored in two laboratory scale batch reactors (13 liter and 108 liter capacities). Two empirical models based on the Gompertz and the modified logistic equations were used to fit the experimental data based on non-linear regression analysis using Solver tool ...

DEPENDENCE OF X-RAY BURST MODELS ON NUCLEAR REACTION RATES

Energy Technology Data Exchange (ETDEWEB)

Cyburt, R. H.; Keek, L.; Schatz, H. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Amthor, A. M. [Department of Physics and Astronomy, Bucknell University, Lewisburg, PA 17837 (United States); Heger, A.; Meisel, Z.; Smith, K. [Joint Institute for Nuclear Astrophysics (JINA), Michigan State University, East Lansing, MI 48824 (United States); Johnson, E. [Department of Physics and Astronomy, Michigan State University, East Lansing, MI 48824 (United States)

2016-10-20

X-ray bursts are thermonuclear flashes on the surface of accreting neutron stars, and reliable burst models are needed to interpret observations in terms of properties of the neutron star and the binary system. We investigate the dependence of X-ray burst models on uncertainties in (p, γ ), ( α , γ ), and ( α , p) nuclear reaction rates using fully self-consistent burst models that account for the feedbacks between changes in nuclear energy generation and changes in astrophysical conditions. A two-step approach first identified sensitive nuclear reaction rates in a single-zone model with ignition conditions chosen to match calculations with a state-of-the-art 1D multi-zone model based on the Kepler stellar evolution code. All relevant reaction rates on neutron-deficient isotopes up to mass 106 were individually varied by a factor of 100 up and down. Calculations of the 84 changes in reaction rate with the highest impact were then repeated in the 1D multi-zone model. We find a number of uncertain reaction rates that affect predictions of light curves and burst ashes significantly. The results provide insights into the nuclear processes that shape observables from X-ray bursts, and guidance for future nuclear physics work to reduce nuclear uncertainties in X-ray burst models.

Tantalum strength model incorporating temperature, strain rate and pressure

Science.gov (United States)

Lim, Hojun; Battaile, Corbett; Brown, Justin; Lane, Matt

Tantalum is a body-centered-cubic (BCC) refractory metal that is widely used in many applications in high temperature, strain rate and pressure environments. In this work, we propose a physically-based strength model for tantalum that incorporates effects of temperature, strain rate and pressure. A constitutive model for single crystal tantalum is developed based on dislocation kink-pair theory, and calibrated to measurements on single crystal specimens. The model is then used to predict deformations of single- and polycrystalline tantalum. In addition, the proposed strength model is implemented into Sandia's ALEGRA solid dynamics code to predict plastic deformations of tantalum in engineering-scale applications at extreme conditions, e.g. Taylor impact tests and Z machine's high pressure ramp compression tests, and the results are compared with available experimental data. Sandia National Laboratories is a multi program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

A Generalized Adsorption Rate Model Based on the Limiting-Component Constraint in Ion-Exchange Chromatographic Separation for Multicomponent Systems

DEFF Research Database (Denmark)

such that conventional LDF (linear driving force) type models are extended to inactive zones without loosing their generality. Based on a limiting component constraint, an exchange probability kernel is developed for multi-component systems. The LDF-type model with the kernel is continuous with time and axial direction....... Two tuning parameters such as concentration layer thickness and function change rate at the threshold point are needed for the probability kernels, which are not sensitive to problems considered....

RATING MODELS AND INFORMATION TECHNOLOGIES APPLICATION FOR MANAGEMENT OF ADMINISTRATIVE-TERRITORIAL COMPLEXES

Directory of Open Access Journals (Sweden)

O. M. Pshinko

2016-12-01

Full Text Available Purpose. The paper aims to develop rating models and related information technologies designed to resolve the tasks of strategic planning of the administrative and territorial units’ development, as well as the tasks of multi-criteria control of inhomogeneous multiparameter objects operation. Methodology. When solving problems of strategic planning of administrative and territorial development and heterogeneous classes management of objects under control, a set of agreed methods is used. Namely the multi-criteria properties analysis for objects of planning and management, diagnostics of the state parameters, forecasting and management of complex systems of different classes. Their states are estimated by sets of different quality indicators, as well as represented by the individual models of operation process. A new information technology is proposed and created to implement the strategic planning and management tasks. This technology uses the procedures for solving typical tasks, that are implemented in MS SQL Server. Findings. A new approach to develop models of analyze and management of complex systems classes based on the ratings has been proposed. Rating models development for analysis of multicriteria and multiparameter systems has been obtained. The management of these systems is performed on the base of parameters of the current and predicted state by non-uniform distribution of resources. The procedure of sensitivity analysis of the changes in the rating model of inhomogeneous distribution of resources parameters has been developed. The information technology of strategic planning and management of heterogeneous classes of objects based on the rating model has been created. Originality. This article proposes a new approach of the rating indicators’ using as a general model for strategic planning of the development and management of heterogeneous objects that can be characterized by the sets of parameters measured on different scales

Gaussian Mixture Model of Heart Rate Variability

Science.gov (United States)

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Variable selection for mixture and promotion time cure rate models.

Science.gov (United States)

Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

2016-11-16

Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

The fitting parameters extraction of conversion model of the low dose rate effect in bipolar devices

International Nuclear Information System (INIS)

Bakerenkov, Alexander

2011-01-01

The Enhanced Low Dose Rate Sensitivity (ELDRS) in bipolar devices consists of in base current degradation of NPN and PNP transistors increase as the dose rate is decreased. As a result of almost 20-year studying, the some physical models of effect are developed, being described in detail. Accelerated test methods, based on these models use in standards. The conversion model of the effect, that allows to describe the inverse S-shaped excess base current dependence versus dose rate, was proposed. This paper presents the problem of conversion model fitting parameters extraction.

Mathematical model for predicting molecular-beam epitaxy growth rates for wafer production

International Nuclear Information System (INIS)

Shi, B.Q.

2003-01-01

An analytical mathematical model for predicting molecular-beam epitaxy (MBE) growth rates is reported. The mathematical model solves the mass-conservation equation for liquid sources in conical crucibles and predicts the growth rate by taking into account the effect of growth source depletion on the growth rate. Assumptions made for deducing the analytical model are discussed. The model derived contains only one unknown parameter, the value of which can be determined by using data readily available to MBE growers. Procedures are outlined for implementing the model in MBE production of III-V compound semiconductor device wafers. Results from use of the model to obtain targeted layer compositions and thickness of InP-based heterojunction bipolar transistor wafers are presented

Using Dynamic Transmission Modeling to Determine Vaccination Coverage Rate Based on 5-Year Economic Burden of Infectious Disease: An Example of Pneumococcal Vaccine.

Science.gov (United States)

Wen, Yu-Wen; Wu, Hsin; Chang, Chee-Jen

2015-05-01

Vaccination can reduce the incidence and mortality of an infectious disease and thus increase the years of life and productivity for the entire society. But when determining the vaccination coverage rate, its economic burden is usually not taken into account. This article aimed to use a dynamic transmission modeling (DTM), which is based on a susceptible-infectious-recovered model and is a system of differential equations, to find the optimal vaccination coverage rate based on the economic burden of an infectious disease. Vaccination for pneumococcal diseases was used as an example to demonstrate the main purpose. 23-Valent pneumococcal polysaccharide vaccines (PPV23) and 13-valent pneumococcal conjugate vaccines (PCV13) have shown their cost-effectiveness in elderly and children, respectively. Scenarios analysis of PPV23 to elderly aged 65+ years and of PCV13 to children aged 0 to 4 years was applied to assess the optimal vaccination coverage rate based on the 5-year economic burden. Model parameters were derived from Taiwan's National Health Insurance Research Database, government data, and published literature. Various vaccination coverage rates, the vaccine efficacy, and all epidemiologic parameters were substituted into DTM, and all differential equations were solved in R Statistical Software. If the coverage rate of PPV23 for the elderly and of PCV13 for the children both reach 50%, the economic burden due to pneumococcal disease will be acceptable. This article provided an alternative perspective from the economic burden of diseases to obtain a vaccination coverage rate using the DTM. This will provide valuable information for vaccination policy decision makers. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Improving Rice Modeling Success Rate with Ternary Non-structural Fertilizer Response Model.

Science.gov (United States)

Li, Juan; Zhang, Mingqing; Chen, Fang; Yao, Baoquan

2018-06-13

Fertilizer response modelling is an important technical approach to realize metrological fertilization on rice. With the goal of solving the problems of a low success rate of a ternary quadratic polynomial model (TPFM) and to expand the model's applicability, this paper established a ternary non-structural fertilizer response model (TNFM) based on the experimental results from N, P and K fertilized rice fields. Our research results showed that the TNFM significantly improved the modelling success rate by addressing problems arising from setting the bias and multicollinearity in a TPFM. The results from 88 rice field trials in China indicated that the proportion of typical TNFMs that satisfy the general fertilizer response law of plant nutrition was 40.9%, while the analogous proportion of TPFMs was only 26.1%. The recommended fertilization showed a significant positive linear correlation between the two models, and the parameters N 0 , P 0 and K 0 that estimated the value of soil supplying nutrient equivalents can be used as better indicators of yield potential in plots where no N or P or K fertilizer was applied. The theoretical analysis showed that the new model has a higher fitting accuracy and a wider application range.

Neural Networks Modelling of Municipal Real Estate Market Rent Rates

Directory of Open Access Journals (Sweden)

Muczyński Andrzej

2016-12-01

Full Text Available This paper presents the results of research on the application of neural networks modelling of municipal real estate market rent rates. The test procedure was based on selected networks trained on the local real estate market data and transformation of the detected dependencies – through established models – to estimate the potential market rent rates of municipal premises. On this basis, the assessment of the adequacy of the actual market rent rates of municipal properties was made. Empirical research was conducted on the local real estate market of the city of Olsztyn in Poland. In order to describe the phenomenon of market rent rates formation an unidirectional three-layer network and a network of radial base was selected. Analyses showed a relatively low degree of convergence of the actual municipal rent rents with potential market rent rates. This degree was strongly varied depending on the type of business ran on the property and its’ social and economic impact. The applied research methodology and the obtained results can be used in order to rationalize municipal property management, including the activation of rental policy.

The Multi-state Latent Factor Intensity Model for Credit Rating Transitions

NARCIS (Netherlands)

Koopman, S.J.; Lucas, A.; Monteiro, A.

2008-01-01

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the

External validation of three dimensional conformal radiotherapy based NTCP models for patient-rated xerostomia and sticky saliva among patients treated with intensity modulated radiotherapy

International Nuclear Information System (INIS)

Beetz, Ivo; Schilstra, Cornelis; Luijk, Peter van; Christianen, Miranda E.M.C.; Doornaert, Patricia; Bijl, Henk P.; Chouvalova, Olga; Heuvel, Edwin R. van den; Steenbakkers, Roel J.H.M.; Langendijk, Johannes A.

2012-01-01

Purpose: The purpose of this study was to investigate the ability of predictive models for patient-rated xerostomia (XER 6M ) and sticky saliva (STIC 6M ) at 6 months after completion of primary (chemo)radiation developed in head and neck cancer patients treated with 3D-conformal radiotherapy (3D-CRT) to predict outcome in patients treated with intensity modulated radiotherapy (IMRT). Methods and materials: Recently, we published the results of a prospective study on predictive models for patient-rated xerostomia and sticky saliva in head and neck cancer patients treated with 3D-CRT (3D-CRT based NTCP models). The 3D-CRT based model for XER 6M consisted of three factors, including the mean parotid dose, age, and baseline xerostomia (none versus a bit). The 3D-CRT based model for STIC 6M consisted of the mean submandibular dose, age, the mean sublingual dose, and baseline sticky saliva (none versus a bit). In the current study, a population consisting of 162 patients treated with IMRT was used to test the external validity of these 3D-CRT based models. External validity was described by the explained variation (R 2 Nagelkerke) and the Brier score. The discriminative abilities of the models were calculated using the area under the receiver operating curve (AUC) and calibration (i.e. the agreement between predicted and observed outcome) was assessed with the Hosmer–Lemeshow “goodness-of-fit” test. Results: Overall model performance of the 3D-CRT based predictive models for XER 6M and STIC 6M was significantly worse in terms of the Brier score and R 2 Nagelkerke among patients treated with IMRT. Moreover the AUC for both 3D-CRT based models in the IMRT treated patients were markedly lower. The Hosmer–Lemeshow test showed a significant disagreement for both models between predicted risk and observed outcome. Conclusion: 3D-CRT based models for patient-rated xerostomia and sticky saliva among head and neck cancer patients treated with primary radiotherapy or

General extrapolation model for an important chemical dose-rate effect

International Nuclear Information System (INIS)

Gillen, K.T.; Clough, R.L.

1984-12-01

In order to extrapolate material accelerated aging data, methodologies must be developed based on sufficient understanding of the processes leading to material degradation. One of the most important mechanisms leading to chemical dose-rate effects in polymers involves the breakdown of intermediate hydroperoxide species. A general model for this mechanism is derived based on the underlying chemical steps. The results lead to a general formalism for understanding dose rate and sequential aging effects when hydroperoxide breakdown is important. We apply the model to combined radiation/temperature aging data for a PVC material and show that this data is consistent with the model and that model extrapolations are in excellent agreement with 12-year real-time aging results from an actual nuclear plant. This model and other techniques discussed in this report can aid in the selection of appropriate accelerated aging methods and can also be used to compare and select materials for use in safety-related components. This will result in increased assurance that equipment qualification procedures are adequate

"An Asymptotic Expansion Approach to Currency Options with a Market Model of Interest Rates under Stochastic Volatility Processes of Spot Exchange Rates"

OpenAIRE

Akihiko Takahashi; Kohta Takehara

2007-01-01

This paper proposes an asymptotic expansion scheme of currency options with a libor market model of interest rates and stochastic volatility models of spot exchange rates. In particular, we derive closed-form approximation formulas for the density functions of the underlying assets and for pricing currency options based on the third order asymptotic expansion scheme; we do not model a foreign exchange rate's variance such as in Heston[1993], but its volatility that follows a general time-inho...

Modeling for Dose Rate Calculation of the External Exposure to Gamma Emitters in Soil

International Nuclear Information System (INIS)

Allam, K. A.; El-Mongy, S. A.; El-Tahawy, M. S.; Mohsen, M. A.

2004-01-01

Based on the model proposed and developed in Ph.D thesis of the first author of this work, the dose rate conversion factors (absorbed dose rate in air per specific activity of soil in nGy.hr - 1 per Bq.kg - 1) are calculated 1 m above the ground for photon emitters of natural radionuclides uniformly distributed in the soil. This new and simple dose rate calculation software was used for calculation of the dose rate in air 1 m above the ground. Then the results were compared with those obtained by five different groups. Although the developed model is extremely simple, the obtained results of calculations, based on this model, show excellent agreement with those obtained by the above-mentioned models specially that one adopted by UNSCEAR. (authors)

Neural networks based identification and compensation of rate-dependent hysteresis in piezoelectric actuators

International Nuclear Information System (INIS)

Zhang, Xinliang; Tan, Yonghong; Su, Miyong; Xie, Yangqiu

2010-01-01

This paper presents a method of the identification for the rate-dependent hysteresis in the piezoelectric actuator (PEA) by use of neural networks. In this method, a special hysteretic operator is constructed from the Prandtl-Ishlinskii (PI) model to extract the changing tendency of the static hysteresis. Then, an expanded input space is constructed by introducing the proposed hysteretic operator to transform the multi-valued mapping of the hysteresis into a one-to-one mapping. Thus, a feedforward neural network is applied to the approximation of the rate-independent hysteresis on the constructed expanded input space. Moreover, in order to describe the rate-dependent performance of the hysteresis, a special hybrid model, which is constructed by a linear auto-regressive exogenous input (ARX) sub-model preceded with the previously obtained neural network based rate-independent hysteresis sub-model, is proposed. For the compensation of the effect of the hysteresis in PEA, the PID feedback controller with a feedforward hysteresis compensator is developed for the tracking control of the PEA. Thus, a corresponding inverse model based on the proposed modeling method is developed for the feedforward hysteresis compensator. Finally, both simulations and experimental results on piezoelectric actuator are presented to verify the effectiveness of the proposed approach for the rate-dependent hysteresis.

Affinity functions for modeling glass dissolution rates

Energy Technology Data Exchange (ETDEWEB)

Bourcier, W.L. [Lawrence Livermore National Lab., CA (United States)

1997-07-01

Glass dissolution rates decrease dramatically as glass approach ''saturation'' with respect to the leachate solution. Most repository sites are chosen where water fluxes are minimal, and therefore the waste glass is most likely to dissolve under conditions close to ''saturation''. The key term in the rate expression used to predict glass dissolution rates close to ''saturation'' is the affinity term, which accounts for saturation effects on dissolution rates. Interpretations of recent experimental data on the dissolution behaviour of silicate glasses and silicate minerals indicate the following: 1) simple affinity control does not explain the observed dissolution rate for silicate minerals or glasses; 2) dissolution rates can be significantly modified by dissolved cations even under conditions far from saturation where the affinity term is near unity; 3) the effects of dissolved species such as Al and Si on the dissolution rate vary with pH, temperature, and saturation state; and 4) as temperature is increased, the effect of both pH and temperature on glass and mineral dissolution rates decrease, which strongly suggests a switch in rate control from surface reaction-based to diffusion control. Borosilicate glass dissolution models need to be upgraded to account for these recent experimental observations. (A.C.)

Evaluating crown fire rate of spread predictions from physics-based models

Science.gov (United States)

C. M. Hoffman; J. Ziegler; J. Canfield; R. R. Linn; W. Mell; C. H. Sieg; F. Pimont

2015-01-01

Modeling the behavior of crown fires is challenging due to the complex set of coupled processes that drive the characteristics of a spreading wildfire and the large range of spatial and temporal scales over which these processes occur. Detailed physics-based modeling approaches such as FIRETEC and the Wildland Urban Interface Fire Dynamics Simulator (WFDS) simulate...

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Availability analysis of subsea blowout preventer using Markov model considering demand rate

Directory of Open Access Journals (Sweden)

Sunghee Kim

2014-12-01

Full Text Available Availabilities of subsea Blowout Preventers (BOP in the Gulf of Mexico Outer Continental Shelf (GoM OCS is investigated using a Markov method. An updated β factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the β factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.

State-Space Dynamic Model for Estimation of Radon Entry Rate, based on Kalman Filtering

Czech Academy of Sciences Publication Activity Database

Brabec, Marek; Jílek, K.

2007-01-01

Roč. 98, - (2007), s. 285-297 ISSN 0265-931X Grant - others:GA SÚJB JC_11/2006 Institutional research plan: CEZ:AV0Z10300504 Keywords : air ventilation rate * radon entry rate * state-space modeling * extended Kalman filter * maximum likelihood estimation * prediction error decomposition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.963, year: 2007

Risky forward interest rates and swaptions: Quantum finance model and empirical results

Science.gov (United States)

Baaquie, Belal Ehsan; Yu, Miao; Bhanap, Jitendra

2018-02-01

Risk free forward interest rates (Diebold and Li, 2006 [1]; Jamshidian, 1991 [2 ]) - and their realization by US Treasury bonds as the leading exemplar - have been studied extensively. In Baaquie (2010), models of risk free bonds and their forward interest rates based on the quantum field theoretic formulation of the risk free forward interest rates have been discussed, including the empirical evidence supporting these models. The quantum finance formulation of risk free forward interest rates is extended to the case of risky forward interest rates. The examples of the Singapore and Malaysian forward interest rates are used as specific cases. The main feature of the quantum finance model is that the risky forward interest rates are modeled both a) as a stand-alone case as well as b) being driven by the US forward interest rates plus a spread - having its own term structure -above the US forward interest rates. Both the US forward interest rates and the term structure for the spread are modeled by a two dimensional Euclidean quantum field. As a precursor to the evaluation of put option of the Singapore coupon bond, the quantum finance model for swaptions is tested using empirical study of swaptions for the US Dollar -showing that the model is quite accurate. A prediction for the market price of the put option for the Singapore coupon bonds is obtained. The quantum finance model is generalized to study the Malaysian case and the Malaysian forward interest rates are shown to have anomalies absent for the US and Singapore case. The model's prediction for a Malaysian interest rate swap is obtained.

Pipe fracture evaluations for leak-rate detection: Probabilistic models

International Nuclear Information System (INIS)

Rahman, S.; Wilkowski, G.; Ghadiali, N.

1993-01-01

This is the second in series of three papers generated from studies on nuclear pipe fracture evaluations for leak-rate detection. This paper focuses on the development of novel probabilistic models for stochastic performance evaluation of degraded nuclear piping systems. It was accomplished here in three distinct stages. First, a statistical analysis was conducted to characterize various input variables for thermo-hydraulic analysis and elastic-plastic fracture mechanics, such as material properties of pipe, crack morphology variables, and location of cracks found in nuclear piping. Second, a new stochastic model was developed to evaluate performance of degraded piping systems. It is based on accurate deterministic models for thermo-hydraulic and fracture mechanics analyses described in the first paper, statistical characterization of various input variables, and state-of-the-art methods of modem structural reliability theory. From this model. the conditional probability of failure as a function of leak-rate detection capability of the piping systems can be predicted. Third, a numerical example was presented to illustrate the proposed model for piping reliability analyses. Results clearly showed that the model provides satisfactory estimates of conditional failure probability with much less computational effort when compared with those obtained from Monte Carlo simulation. The probabilistic model developed in this paper will be applied to various piping in boiling water reactor and pressurized water reactor plants for leak-rate detection applications

Mesoscopic modeling of DNA denaturation rates: Sequence dependence and experimental comparison

Energy Technology Data Exchange (ETDEWEB)

Dahlen, Oda, E-mail: oda.dahlen@ntnu.no; Erp, Titus S. van, E-mail: titus.van.erp@ntnu.no [Department of Chemistry, Norwegian University of Science and Technology (NTNU), Høgskoleringen 5, Realfagbygget D3-117 7491 Trondheim (Norway)

2015-06-21

Using rare event simulation techniques, we calculated DNA denaturation rate constants for a range of sequences and temperatures for the Peyrard-Bishop-Dauxois (PBD) model with two different parameter sets. We studied a larger variety of sequences compared to previous studies that only consider DNA homopolymers and DNA sequences containing an equal amount of weak AT- and strong GC-base pairs. Our results show that, contrary to previous findings, an even distribution of the strong GC-base pairs does not always result in the fastest possible denaturation. In addition, we applied an adaptation of the PBD model to study hairpin denaturation for which experimental data are available. This is the first quantitative study in which dynamical results from the mesoscopic PBD model have been compared with experiments. Our results show that present parameterized models, although giving good results regarding thermodynamic properties, overestimate denaturation rates by orders of magnitude. We believe that our dynamical approach is, therefore, an important tool for verifying DNA models and for developing next generation models that have higher predictive power than present ones.

An empirical model to predict infield thin layer drying rate of cut switchgrass

International Nuclear Information System (INIS)

Khanchi, A.; Jones, C.L.; Sharma, B.; Huhnke, R.L.; Weckler, P.; Maness, N.O.

2013-01-01

A series of 62 thin layer drying experiments were conducted to evaluate the effect of solar radiation, vapor pressure deficit and wind speed on drying rate of switchgrass. An environmental chamber was fabricated that can simulate field drying conditions. An empirical drying model based on maturity stage of switchgrass was also developed during the study. It was observed that solar radiation was the most significant factor in improving the drying rate of switchgrass at seed shattering and seed shattered maturity stage. Therefore, drying switchgrass in wide swath to intercept the maximum amount of radiation at these stages of maturity is recommended. Moreover, it was observed that under low radiation intensity conditions, wind speed helps to improve the drying rate of switchgrass. Field operations such as raking or turning of the windrows are recommended to improve air circulation within a swath on cloudy days. Additionally, it was found that the effect of individual weather parameters on the drying rate of switchgrass was dependent on maturity stage. Vapor pressure deficit was strongly correlated with the drying rate during seed development stage whereas, vapor pressure deficit was weakly correlated during seed shattering and seed shattered stage. These findings suggest the importance of using separate drying rate models for each maturity stage of switchgrass. The empirical models developed in this study can predict the drying time of switchgrass based on the forecasted weather conditions so that the appropriate decisions can be made. -- Highlights: • An environmental chamber was developed in the present study to simulate field drying conditions. • An empirical model was developed that can estimate drying rate of switchgrass based on forecasted weather conditions. • Separate equations were developed based on maturity stage of switchgrass. • Designed environmental chamber can be used to evaluate the effect of other parameters that affect drying of crops

A High Performance Impedance-based Platform for Evaporation Rate Detection.

Science.gov (United States)

Chou, Wei-Lung; Lee, Pee-Yew; Chen, Cheng-You; Lin, Yu-Hsin; Lin, Yung-Sheng

2016-10-17

This paper describes the method of a novel impedance-based platform for the detection of the evaporation rate. The model compound hyaluronic acid was employed here for demonstration purposes. Multiple evaporation tests on the model compound as a humectant with various concentrations in solutions were conducted for comparison purposes. A conventional weight loss approach is known as the most straightforward, but time-consuming, measurement technique for evaporation rate detection. Yet, a clear disadvantage is that a large volume of sample is required and multiple sample tests cannot be conducted at the same time. For the first time in literature, an electrical impedance sensing chip is successfully applied to a real-time evaporation investigation in a time sharing, continuous and automatic manner. Moreover, as little as 0.5 ml of test samples is required in this impedance-based apparatus, and a large impedance variation is demonstrated among various dilute solutions. The proposed high-sensitivity and fast-response impedance sensing system is found to outperform a conventional weight loss approach in terms of evaporation rate detection.

Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews

OpenAIRE

Cheng, Zhiyong; Ding, Ying; Zhu, Lei; Kankanhalli, Mohan

2018-01-01

Although latent factor models (e.g., matrix factorization) achieve good accuracy in rating prediction, they suffer from several problems including cold-start, non-transparency, and suboptimal recommendation for local users or items. In this paper, we employ textual review information with ratings to tackle these limitations. Firstly, we apply a proposed aspect-aware topic model (ATM) on the review text to model user preferences and item features from different aspects, and estimate the aspect...

Modeling emission rates and exposures from outdoor cooking

Science.gov (United States)

Edwards, Rufus; Princevac, Marko; Weltman, Robert; Ghasemian, Masoud; Arora, Narendra K.; Bond, Tami

2017-09-01

Approximately 3 billion individuals rely on solid fuels for cooking globally. For a large portion of these - an estimated 533 million - cooking is outdoors, where emissions from cookstoves pose a health risk to both cooks and other household and village members. Models that estimate emissions rates from stoves in indoor environments that would meet WHO air quality guidelines (AQG), explicitly don't account for outdoor cooking. The objectives of this paper are to link health based exposure guidelines with emissions from outdoor cookstoves, using a Monte Carlo simulation of cooking times from Haryana India coupled with inverse Gaussian dispersion models. Mean emission rates for outdoor cooking that would result in incremental increases in personal exposure equivalent to the WHO AQG during a 24-h period were 126 ± 13 mg/min for cooking while squatting and 99 ± 10 mg/min while standing. Emission rates modeled for outdoor cooking are substantially higher than emission rates for indoor cooking to meet AQG, because the models estimate impact of emissions on personal exposure concentrations rather than microenvironment concentrations, and because the smoke disperses more readily outdoors compared to indoor environments. As a result, many more stoves including the best performing solid-fuel biomass stoves would meet AQG when cooking outdoors, but may also result in substantial localized neighborhood pollution depending on housing density. Inclusion of the neighborhood impact of pollution should be addressed more formally both in guidelines on emissions rates from stoves that would be protective of health, and also in wider health impact evaluation efforts and burden of disease estimates. Emissions guidelines should better represent the different contexts in which stoves are being used, especially because in these contexts the best performing solid fuel stoves have the potential to provide significant benefits.

Index Option Pricing Models with Stochastic Volatility and Stochastic Interest Rates

NARCIS (Netherlands)

Jiang, G.J.; van der Sluis, P.J.

2000-01-01

This paper specifies a multivariate stochastic volatility (SV) model for the S&P500 index and spot interest rate processes. We first estimate the multivariate SV model via the efficient method of moments (EMM) technique based on observations of underlying state variables, and then investigate the

Model Uncertainty and Exchange Rate Forecasting

NARCIS (Netherlands)

Kouwenberg, R.; Markiewicz, A.; Verhoeks, R.; Zwinkels, R.C.J.

2017-01-01

Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show

Risk management under a two-factor model of the term structure of interest rates

OpenAIRE

Manuel Moreno

1997-01-01

This paper presents several applications to interest rate risk management based on a two-factor continuous-time model of the term structure of interest rates previously presented in Moreno (1996). This model assumes that default free discount bond prices are determined by the time to maturity and two factors, the long-term interest rate and the spread (difference between the long-term rate and the short-term (instantaneous) riskless rate). Several new measures of ``generalized duration" are p...

Noise Reduction of MEMS Gyroscope Based on Direct Modeling for an Angular Rate Signal

Directory of Open Access Journals (Sweden)

Liang Xue

2015-02-01

Full Text Available In this paper, a novel approach for processing the outputs signal of the microelectromechanical systems (MEMS gyroscopes was presented to reduce the bias drift and noise. The principle for the noise reduction was presented, and an optimal Kalman filter (KF was designed by a steady-state filter gain obtained from the analysis of KF observability. In particular, the true angular rate signal was directly modeled to obtain an optimal estimate and make a self-compensation for the gyroscope without needing other sensor’s information, whether in static or dynamic condition. A linear fit equation that describes the relationship between the KF bandwidth and modeling parameter of true angular rate was derived from the analysis of KF frequency response. The test results indicated that the MEMS gyroscope having an ARW noise of 4.87°/h0.5 and a bias instability of 44.41°/h were reduced to 0.4°/h0.5 and 4.13°/h by the KF under a given bandwidth (10 Hz, respectively. The 1σ estimated error was reduced from 1.9°/s to 0.14°/s and 1.7°/s to 0.5°/s in the constant rate test and swing rate test, respectively. It also showed that the filtered angular rate signal could well reflect the dynamic characteristic of the input rate signal in dynamic conditions. The presented algorithm is proved to be effective at improving the measurement precision of the MEMS gyroscope.

A lattice hydrodynamic model based on delayed feedback control considering the effect of flow rate difference

Science.gov (United States)

Wang, Yunong; Cheng, Rongjun; Ge, Hongxia

2017-08-01

In this paper, a lattice hydrodynamic model is derived considering not only the effect of flow rate difference but also the delayed feedback control signal which including more comprehensive information. The control method is used to analyze the stability of the model. Furthermore, the critical condition for the linear steady traffic flow is deduced and the numerical simulation is carried out to investigate the advantage of the proposed model with and without the effect of flow rate difference and the control signal. The results are consistent with the theoretical analysis correspondingly.

On a Corporate Bond Pricing Model with Credit Rating Migration Risksand Stochastic Interest Rate

Directory of Open Access Journals (Sweden)

Jin Liang

2017-10-01

Full Text Available In this paper we study a corporate bond-pricing model with credit rating migration and astochastic interest rate. The volatility of bond price in the model strongly depends on potential creditrating migration and stochastic change of the interest rate. This new model improves the previousexisting models in which the interest rate is considered to be a constant. The existence, uniquenessand regularity of the solution for the model are established. Moreover, some properties includingthe smoothness of the free boundary are obtained. Furthermore, some numerical computations arepresented to illustrate the theoretical results.

On rate-state and Coulomb failure models

Science.gov (United States)

Gomberg, J.; Beeler, N.; Blanpied, M.

2000-01-01

We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified

Relationship between soil erodibility and modeled infiltration rate in different soils

Science.gov (United States)

Wang, Guoqiang; Fang, Qingqing; Wu, Binbin; Yang, Huicai; Xu, Zongxue

2015-09-01

The relationship between soil erodibility, which is hard to measure, and modeled infiltration rate were rarely researched. Here, the soil erodibility factors (K and Ke in the USLE, Ki and K1 in the WEPP) were calculated and the infiltration rates were modeled based on the designed laboratory simulation experiments and proposed infiltration model, in order to build their relationship. The impacts of compost amendment on the soil erosion characteristics and relationship were also studied. Two contrasting agricultural soils (bare and cultivated fluvo-aquic soils) were used, and different poultry compost contents (control, low and high) were applied to both soils. The results indicated that the runoff rate, sediment yield rate and soil erodibility of the bare soil treatments were generally higher than those of the corresponding cultivated soil treatments. The application of composts generally decreased sediment yield and soil erodibility but did not always decrease runoff. The comparison of measured and modeled infiltration rates indicated that the model represented the infiltration processes well with an N-S coefficient of 0.84 for overall treatments. Significant negative logarithmic correlations have been found between final infiltration rate (FIR) and the four soil erodibility factors, and the relationship between USLE-K and FIR demonstrated the best correlation. The application of poultry composts would not influence the logarithmic relationship between FIR and soil erodibility. Our study provided a useful tool to estimate soil erodibility.

Innovative model-based flow rate optimization for vanadium redox flow batteries

Science.gov (United States)

König, S.; Suriyah, M. R.; Leibfried, T.

2016-11-01

In this paper, an innovative approach is presented to optimize the flow rate of a 6-kW vanadium redox flow battery with realistic stack dimensions. Efficiency is derived using a multi-physics battery model and a newly proposed instantaneous efficiency determination technique. An optimization algorithm is applied to identify optimal flow rates for operation points defined by state-of-charge (SoC) and current. The proposed method is evaluated against the conventional approach of applying Faraday's first law of electrolysis, scaled to the so-called flow factor. To make a fair comparison, the flow factor is also optimized by simulating cycles with different charging/discharging currents. It is shown through the obtained results that the efficiency is increased by up to 1.2% points; in addition, discharge capacity is also increased by up to 1.0 kWh or 5.4%. Detailed loss analysis is carried out for the cycles with maximum and minimum charging/discharging currents. It is shown that the proposed method minimizes the sum of losses caused by concentration over-potential, pumping and diffusion. Furthermore, for the deployed Nafion 115 membrane, it is observed that diffusion losses increase with stack SoC. Therefore, to decrease stack SoC and lower diffusion losses, a higher flow rate during charging than during discharging is reasonable.

Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin

Science.gov (United States)

Paris, Adrien; Dias de Paiva, Rodrigo; Santos da Silva, Joecila; Medeiros Moreira, Daniel; Calmant, Stephane; Garambois, Pierre-André; Collischonn, Walter; Bonnet, Marie-Paule; Seyler, Frederique

2016-05-01

In this study, rating curves (RCs) were determined by applying satellite altimetry to a poorly gauged basin. This study demonstrates the synergistic application of remote sensing and watershed modeling to capture the dynamics and quantity of flow in the Amazon River Basin, respectively. Three major advancements for estimating basin-scale patterns in river discharge are described. The first advancement is the preservation of the hydrological meanings of the parameters expressed by Manning's equation to obtain a data set containing the elevations of the river beds throughout the basin. The second advancement is the provision of parameter uncertainties and, therefore, the uncertainties in the rated discharge. The third advancement concerns estimating the discharge while considering backwater effects. We analyzed the Amazon Basin using nearly one thousand series that were obtained from ENVISAT and Jason-2 altimetry for more than 100 tributaries. Discharge values and related uncertainties were obtained from the rain-discharge MGB-IPH model. We used a global optimization algorithm based on the Monte Carlo Markov Chain and Bayesian framework to determine the rating curves. The data were randomly allocated into 80% calibration and 20% validation subsets. A comparison with the validation samples produced a Nash-Sutcliffe efficiency (Ens) of 0.68. When the MGB discharge uncertainties were less than 5%, the Ens value increased to 0.81 (mean). A comparison with the in situ discharge resulted in an Ens value of 0.71 for the validation samples (and 0.77 for calibration). The Ens values at the mouths of the rivers that experienced backwater effects significantly improved when the mean monthly slope was included in the RC. Our RCs were not mission-dependent, and the Ens value was preserved when applying ENVISAT rating curves to Jason-2 altimetry at crossovers. The cease-to-flow parameter of our RCs provided a good proxy for determining river bed elevation. This proxy was validated

QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification

KAUST Repository

Sudhakaran, Sairam; Amy, Gary L.

2013-01-01

. In this study, quantitative structure activity relationships (QSAR) models for O3 and AOP processes were developed, and rate constants, kOH and kO3, were predicted based on target compound properties. The kO3 and kOH values ranged from 5 * 10-4 to 105 M-1s-1

Predictive Finite Rate Model for Oxygen-Carbon Interactions at High Temperature

Science.gov (United States)

Poovathingal, Savio

An oxidation model for carbon surfaces is developed to predict ablation rates for carbon heat shields used in hypersonic vehicles. Unlike existing empirical models, the approach used here was to probe gas-surface interactions individually and then based on an understanding of the relevant fundamental processes, build a predictive model that would be accurate over a wide range of pressures and temperatures, and even microstructures. Initially, molecular dynamics was used to understand the oxidation processes on the surface. The molecular dynamics simulations were compared to molecular beam experiments and good qualitative agreement was observed. The simulations reproduced cylindrical pitting observed in the experiments where oxidation was rapid and primarily occurred around a defect. However, the studies were limited to small systems at low temperatures and could simulate time scales only of the order of nanoseconds. Molecular beam experiments at high surface temperature indicated that a majority of surface reaction products were produced through thermal mechanisms. Since the reactions were thermal, they occurred over long time scales which were computationally prohibitive for molecular dynamics to simulate. The experiments provided detailed dynamical data on the scattering of O, O2, CO, and CO2 and it was found that the data from molecular beam experiments could be used directly to build a model. The data was initially used to deduce surface reaction probabilities at 800 K. The reaction probabilities were then incorporated into the direct simulation Monte Carlo (DSMC) method. Simulations were performed where the microstructure was resolved and dissociated oxygen convected and diffused towards it. For a gas-surface temperature of 800 K, it was found that despite CO being the dominant surface reaction product, a gas-phase reaction forms significant CO2 within the microstructure region. It was also found that surface area did not play any role in concentration of

Influence of satellite-derived photolysis rates and NOx emissions on Texas ozone modeling

Science.gov (United States)

Tang, W.; Cohan, D. S.; Pour-Biazar, A.; Lamsal, L. N.; White, A. T.; Xiao, X.; Zhou, W.; Henderson, B. H.; Lash, B. F.

2015-02-01

Uncertain photolysis rates and emission inventory impair the accuracy of state-level ozone (O3) regulatory modeling. Past studies have separately used satellite-observed clouds to correct the model-predicted photolysis rates, or satellite-constrained top-down NOx emissions to identify and reduce uncertainties in bottom-up NOx emissions. However, the joint application of multiple satellite-derived model inputs to improve O3 state implementation plan (SIP) modeling has rarely been explored. In this study, Geostationary Operational Environmental Satellite (GOES) observations of clouds are applied to derive the photolysis rates, replacing those used in Texas SIP modeling. This changes modeled O3 concentrations by up to 80 ppb and improves O3 simulations by reducing modeled normalized mean bias (NMB) and normalized mean error (NME) by up to 0.1. A sector-based discrete Kalman filter (DKF) inversion approach is incorporated with the Comprehensive Air Quality Model with extensions (CAMx)-decoupled direct method (DDM) model to adjust Texas NOx emissions using a high-resolution Ozone Monitoring Instrument (OMI) NO2 product. The discrepancy between OMI and CAMx NO2 vertical column densities (VCDs) is further reduced by increasing modeled NOx lifetime and adding an artificial amount of NO2 in the upper troposphere. The region-based DKF inversion suggests increasing NOx emissions by 10-50% in most regions, deteriorating the model performance in predicting ground NO2 and O3, while the sector-based DKF inversion tends to scale down area and nonroad NOx emissions by 50%, leading to a 2-5 ppb decrease in ground 8 h O3 predictions. Model performance in simulating ground NO2 and O3 are improved using sector-based inversion-constrained NOx emissions, with 0.25 and 0.04 reductions in NMBs and 0.13 and 0.04 reductions in NMEs, respectively. Using both GOES-derived photolysis rates and OMI-constrained NOx emissions together reduces modeled NMB and NME by 0.05, increases the model

Prediction of creamy mouthfeel based on texture attribute ratings of dairy desserts

NARCIS (Netherlands)

Weenen, H.; Jellema, R.H.; Wijk, de R.A.

2006-01-01

A quantitative predictive model for creamy mouthfeel in dairy desserts was developed, using PLS multivariate analysis of texture attributes. Based on 40 experimental custard desserts, a good correlation was obtained between measured and predicted creamy mouthfeel ratings. The model was validated by

Expectation Maximization Algorithm for Box-Cox Transformation Cure Rate Model and Assessment of Model Misspecification Under Weibull Lifetimes.

Science.gov (United States)

Pal, Suvra; Balakrishnan, Narayanaswamy

2018-05-01

In this paper, we develop likelihood inference based on the expectation maximization algorithm for the Box-Cox transformation cure rate model assuming the lifetimes to follow a Weibull distribution. A simulation study is carried out to demonstrate the performance of the proposed estimation method. Through Monte Carlo simulations, we also study the effect of model misspecification on the estimate of cure rate. Finally, we analyze a well-known data on melanoma with the model and the inferential method developed here.

Individual-based modeling of fish: Linking to physical models and water quality.

Energy Technology Data Exchange (ETDEWEB)

Rose, K.A.

1997-08-01

The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.

Science.gov (United States)

Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L

2016-11-05

The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Developing models for the prediction of hospital healthcare waste generation rate.

Science.gov (United States)

Tesfahun, Esubalew; Kumie, Abera; Beyene, Abebe

2016-01-01

An increase in the number of health institutions, along with frequent use of disposable medical products, has contributed to the increase of healthcare waste generation rate. For proper handling of healthcare waste, it is crucial to predict the amount of waste generation beforehand. Predictive models can help to optimise healthcare waste management systems, set guidelines and evaluate the prevailing strategies for healthcare waste handling and disposal. However, there is no mathematical model developed for Ethiopian hospitals to predict healthcare waste generation rate. Therefore, the objective of this research was to develop models for the prediction of a healthcare waste generation rate. A longitudinal study design was used to generate long-term data on solid healthcare waste composition, generation rate and develop predictive models. The results revealed that the healthcare waste generation rate has a strong linear correlation with the number of inpatients (R(2) = 0.965), and a weak one with the number of outpatients (R(2) = 0.424). Statistical analysis was carried out to develop models for the prediction of the quantity of waste generated at each hospital (public, teaching and private). In these models, the number of inpatients and outpatients were revealed to be significant factors on the quantity of waste generated. The influence of the number of inpatients and outpatients treated varies at different hospitals. Therefore, different models were developed based on the types of hospitals. © The Author(s) 2015.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

Science.gov (United States)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Modeling the Interest Rate Term Structure: Derivatives Contracts Dynamics and Evaluation

Directory of Open Access Journals (Sweden)

Pedro L. Valls Pereira

2005-06-01

Full Text Available This article deals with a model for the term structure of interest rates and the valuation of derivative contracts directly dependent on it. The work is of a theoretical nature and deals, exclusively, with continuous time models, making ample use of stochastic calculus results and presents original contributions that we consider relevant to the development of the fixed income market modeling. We develop a new multifactorial model of the term structure of interest rates. The model is based on the decomposition of the yield curve into the factors level, slope, curvature, and the treatment of their collective dynamics. We show that this model may be applied to serve various objectives: analysis of bond price dynamics, valuation of derivative contracts and also market risk management and formulation of operational strategies which is presented in another article.

Sensitivity of the polypropylene to the strain rate: experiments and modeling

International Nuclear Information System (INIS)

Abdul-Latif, A.; Aboura, Z.; Mosleh, L.

2002-01-01

Full text.The main goal of this work is first to evaluate experimentally the strain rate dependent deformation of the polypropylene under tensile load; and secondly is to propose a model capable to appropriately describe the mechanical behavior of this material and especially its sensitivity to the strain rate. Several experimental tensile tests are performed at different quasi-static strain rates in the range of 10 -5 s -1 to 10 -1 s -1 . In addition to some relaxation tests are also conducted introducing the strain rate jumping state during testing. Within the framework of elastoviscoplasticity, a phenomenological model is developed for describing the non-linear mechanical behavior of the material under uniaxial loading paths. With the small strain assumption, the sensitivity of the polypropylene to the strain rate being of particular interest in this work, is accordingly taken into account. As a matter of fact, since this model is based on internal state variables, we assume thus that the material sensitivity to the strain rate is governed by the kinematic hardening variable notably its modulus and the accumulated viscoplastic strain. As far as the elastic behavior is concerned, it is noticed that such a behavior is slightly influenced by the employed strain rate rage. For this reason, the elastic behavior is classically determined, i.e. without coupling with the strain rate dependent deformation. It is obvious that the inelastic behavior of the used material is thoroughly dictated by the applied strain rate. Hence, the model parameters are well calibrated utilizing several experimental databases for different strain rates (10 -5 s -1 to 10 -1 s -1 ). Actually, among these experimental results, some experiments related to the relaxation phenomenon and strain rate jumping during testing (increasing or decreasing) are also used in order to more perfect the model parameters identification. To validate the calibrated model parameters, simulation tests are achieved

Improvement of specific growth rate of Pichia pastoris for effective porcine interferon-α production with an on-line model-based glycerol feeding strategy.

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Gao, Min-Jie; Zheng, Zhi-Yong; Wu, Jian-Rong; Dong, Shi-Juan; Li, Zhen; Jin, Hu; Zhan, Xiao-Bei; Lin, Chi-Chung

2012-02-01

Effective expression of porcine interferon-α (pIFN-α) with recombinant Pichia pastoris was conducted in a bench-scale fermentor. The influence of the glycerol feeding strategy on the specific growth rate and protein production was investigated. The traditional DO-stat feeding strategy led to very low cell growth rate resulting in low dry cell weight (DCW) of about 90 g/L during the subsequent induction phase. The previously reported Artificial Neural Network Pattern Recognition (ANNPR) model-based glycerol feeding strategy improved the cell density to 120 g DCW/L, while the specific growth rate decreased from 0.15 to 0.18 to 0.03-0.08 h(-1) during the last 10 h of the glycerol feeding stage leading to a variation of the porcine interferon-α production, as the glycerol feeding scheme had a significant effect on the induction phase. This problem was resolved by an improved ANNPR model-based feeding strategy to maintain the specific growth rate above 0.11 h(-1). With this feeding strategy, the pIFN-α concentration reached a level of 1.43 g/L, more than 1.5-fold higher than that obtained with the previously adopted feeding strategy. Our results showed that increasing the specific growth rate favored the target protein production and the glycerol feeding methods directly influenced the induction stage. Consequently, higher cell density and specific growth rate as well as effective porcine interferon-α production have been achieved by our novel glycerol feeding strategy.

Probabilistic Modeling of the Fatigue Crack Growth Rate for Ni-base Alloy X-750

International Nuclear Information System (INIS)

Yoon, Jae Young; Nam, Hyo On; Hwang, Il Soon; Tae Hyun Lee

2012-01-01

The Bayesian inference was employed to reduce the uncertainties contained in EAC modeling parameters that have been established from experiments with Alloy X-750. Corrosion fatigue crack growth rate model(FCGR) was developed by fitting into Paris' Law of measured data from the several fatigue tests conducted either in constant load or constant ΔK mode. From fitting the data to Paris' Law, the parameters C and m of Paris' Law model were assumed to obey the Gaussian distribution. These parameters characterizing the corrosion fatigue crack growth behavior of X-750 were updated to reduce the uncertainty in the model by using the Bayesian inference method. (author)

A review of air exchange rate models for air pollution exposure assessments.

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Breen, Michael S; Schultz, Bradley D; Sohn, Michael D; Long, Thomas; Langstaff, John; Williams, Ronald; Isaacs, Kristin; Meng, Qing Yu; Stallings, Casson; Smith, Luther

2014-11-01

A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.

Characterizing and modeling the pressure- and rate-dependent elastic-plastic-damage behaviors of polypropylene-based polymers

KAUST Repository

Pulungan, Ditho Ardiansyah; Yudhanto, Arief; Goutham, Shiva; Lubineau, Gilles; Yaldiz, Recep; Schijve, Warden

2018-01-01

Polymers in general exhibit pressure- and rate-dependent behavior. Modeling such behavior requires extensive, costly and time-consuming experimental work. Common simplifications may lead to severe inaccuracy when using the model for predicting

Characteristics of quantum dash laser under the rate equation model framework

KAUST Repository

Khan, Mohammed Zahed Mustafa

2010-09-01

The authors present a numerical model to study the carrier dynamics of InAs/InP quantum dash (QDash) lasers. The model is based on single-state rate equations, which incorporates both, the homogeneous and the inhomogeneous broadening of lasing spectra. The numerical technique also considers the unique features of the QDash gain medium. This model has been applied successfully to analyze the laser spectra of QDash laser. ©2010 IEEE.

Measurement and Modeling of Respiration Rate of Tomato (Cultivar Roma) for Modified Atmosphere Storage.

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Kandasamy, Palani; Moitra, Ranabir; Mukherjee, Souti

2015-01-01

Experiments were conducted to determine the respiration rate of tomato at 10, 20 and 30 °C using closed respiration system. Oxygen depletion and carbon dioxide accumulation in the system containing tomato was monitored. Respiration rate was found to decrease with increasing CO2 and decreasing O2 concentration. Michaelis-Menten type model based on enzyme kinetics was evaluated using experimental data generated for predicting the respiration rate. The model parameters that obtained from the respiration rate at different O2 and CO2 concentration levels were used to fit the model against the storage temperatures. The fitting was fair (R2 = 0.923 to 0.970) when the respiration rate was expressed as O2 concentation. Since inhibition constant for CO2 concentration tended towards negetive, the model was modified as a function of O2 concentration only. The modified model was fitted to the experimental data and showed good agreement (R2 = 0.998) with experimentally estimated respiration rate.

Unprecedented rates of land-use transformation in modeled climate change mitigation pathways

Science.gov (United States)

Turner, P. A.; Field, C. B.; Lobell, D. B.; Sanchez, D.; Mach, K. J.

2017-12-01

Integrated assessment models (IAMs) generate climate change mitigation scenarios consistent with global temperature targets. To limit warming to 2°, stylized cost-effective mitigation pathways rely on extensive deployments of carbon dioxide (CO2) removal (CDR) technologies, including multi-gigatonne yearly carbon removal from the atmosphere through bioenergy with carbon capture and storage (BECCS) and afforestation/reforestation. These assumed CDR deployments keep ambitious temperature limits in reach, but associated rates of land-use transformation have not been evaluated. For IAM scenarios from the IPCC Fifth Assessment Report, we compare rates of modeled land-use conversion to recent observed commodity crop expansions. In scenarios with a likely chance of limiting warming to 2° in 2100, the rate of energy cropland expansion supporting BECCS exceeds past commodity crop rates by several fold. In some cases, mitigation scenarios include abrupt reversal of deforestation, paired with massive afforestation/reforestation. Specifically, energy cropland in crop. If energy cropland instead increases at rates equal to recent soybean and oil palm expansions, the scale of CO2 removal possible with BECCS is 2.6 to 10-times lower, respectively, than the deployments <2° IAM scenarios rely upon in 2100. IAM mitigation pathways may favor multi-gigatonne biomass-based CDR given undervalued sociopolitical and techno-economic deployment barriers. Heroic modeled rates for land-use transformation imply that large-scale biomass-based CDR is not an easy solution to the climate challenge.

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

Directory of Open Access Journals (Sweden)

Minh Vu Trieu

2017-03-01

Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

Science.gov (United States)

Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

2017-03-01

This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

An Improved Computing Method for 3D Mechanical Connectivity Rates Based on a Polyhedral Simulation Model of Discrete Fracture Network in Rock Masses

Science.gov (United States)

Li, Mingchao; Han, Shuai; Zhou, Sibao; Zhang, Ye

2018-06-01

Based on a 3D model of a discrete fracture network (DFN) in a rock mass, an improved projective method for computing the 3D mechanical connectivity rate was proposed. The Monte Carlo simulation method, 2D Poisson process and 3D geological modeling technique were integrated into a polyhedral DFN modeling approach, and the simulation results were verified by numerical tests and graphical inspection. Next, the traditional projective approach for calculating the rock mass connectivity rate was improved using the 3D DFN models by (1) using the polyhedral model to replace the Baecher disk model; (2) taking the real cross section of the rock mass, rather than a part of the cross section, as the test plane; and (3) dynamically searching the joint connectivity rates using different dip directions and dip angles at different elevations to calculate the maximum, minimum and average values of the joint connectivity at each elevation. In a case study, the improved method and traditional method were used to compute the mechanical connectivity rate of the slope of a dam abutment. The results of the two methods were further used to compute the cohesive force of the rock masses. Finally, a comparison showed that the cohesive force derived from the traditional method had a higher error, whereas the cohesive force derived from the improved method was consistent with the suggested values. According to the comparison, the effectivity and validity of the improved method were verified indirectly.

Development of a QTL-environment-based predictive model for node addition rate in common bean.

Science.gov (United States)

Zhang, Li; Gezan, Salvador A; Eduardo Vallejos, C; Jones, James W; Boote, Kenneth J; Clavijo-Michelangeli, Jose A; Bhakta, Mehul; Osorno, Juan M; Rao, Idupulapati; Beebe, Stephen; Roman-Paoli, Elvin; Gonzalez, Abiezer; Beaver, James; Ricaurte, Jaumer; Colbert, Raphael; Correll, Melanie J

2017-05-01

This work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day - 1 ) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50-90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions.

Enhancement of leak rate estimation model for corroded cracked thin tubes

International Nuclear Information System (INIS)

Chang, Y.S.; Jeong, J.U.; Kim, Y.J.; Hwang, S.S.; Kim, H.P.

2010-01-01

During the last couple of decades, lots of researches on structural integrity assessment and leak rate estimation have been carried out to prevent unanticipated catastrophic failures of pressure retaining nuclear components. However, from the standpoint of leakage integrity, there are still some arguments for predicting the leak rate of cracked components due primarily to uncertainties attached to various parameters in flow models. The purpose of present work is to suggest a leak rate estimation method for thin tubes with artificial cracks. In this context, 23 leak rate tests are carried out for laboratory generated stress corrosion cracked tube specimens subjected to internal pressure. Engineering equations to calculate crack opening displacements are developed from detailed three-dimensional elastic-plastic finite element analyses and then a simplified practical model is proposed based on the equations as well as test data. Verification of the proposed method is done through comparing leak rates and it will enable more reliable design and/or operation of thin tubes.

Further Results on Dynamic Additive Hazard Rate Model

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Zhengcheng Zhang

2014-01-01

Full Text Available In the past, the proportional and additive hazard rate models have been investigated in the works. Nanda and Das (2011 introduced and studied the dynamic proportional (reversed hazard rate model. In this paper we study the dynamic additive hazard rate model, and investigate its aging properties for different aging classes. The closure of the model under some stochastic orders has also been investigated. Some examples are also given to illustrate different aging properties and stochastic comparisons of the model.

Modeling of the interest rate policy of the central bank of Russia

Science.gov (United States)

Shelomentsev, A. G.; Berg, D. B.; Detkov, A. A.; Rylova, A. P.

2017-11-01

This paper investigates interactions among money supply, exchange rates, inflation, and nominal interest rates, which are regulating parameters of the Central bank policy. The study is based on the data received from Russian source in 2002-2016. The major findings are 1) the interest rate demonstrates almost no relation with inflation; 2) ties of money supply and the nominal interest rate are strong; 3) money supply and inflation show meaningful relations only in comparison to their growth rates. We have developed a dynamic model, which can be used in forecasting of macroeconomic processes.

Stationarity test with a direct test for heteroskedasticity in exchange rate forecasting models

Science.gov (United States)

Khin, Aye Aye; Chau, Wong Hong; Seong, Lim Chee; Bin, Raymond Ling Leh; Teng, Kevin Low Lock

2017-05-01

Global economic has been decreasing in the recent years, manifested by the greater exchange rates volatility on international commodity market. This study attempts to analyze some prominent exchange rate forecasting models on Malaysian commodity trading: univariate ARIMA, ARCH and GARCH models in conjunction with stationarity test on residual diagnosis direct testing of heteroskedasticity. All forecasting models utilized the monthly data from 1990 to 2015. Given a total of 312 observations, the data used to forecast both short-term and long-term exchange rate. The forecasting power statistics suggested that the forecasting performance of ARIMA (1, 1, 1) model is more efficient than the ARCH (1) and GARCH (1, 1) models. For ex-post forecast, exchange rate was increased from RM 3.50 per USD in January 2015 to RM 4.47 per USD in December 2015 based on the baseline data. For short-term ex-ante forecast, the analysis results indicate a decrease in exchange rate on 2016 June (RM 4.27 per USD) as compared with 2015 December. A more appropriate forecasting method of exchange rate is vital to aid the decision-making process and planning on the sustainable commodities' production in the world economy.

Influence of the formation- and passivation rate of boron-oxygen defects for mitigating carrier-induced degradation in silicon within a hydrogen-based model

International Nuclear Information System (INIS)

Hallam, Brett; Abbott, Malcolm; Nampalli, Nitin; Hamer, Phill; Wenham, Stuart

2016-01-01

A three-state model is used to explore the influence of defect formation- and passivation rates of carrier-induced degradation related to boron-oxygen complexes in boron-doped p-type silicon solar cells within a hydrogen-based model. The model highlights that the inability to effectively mitigate carrier-induced degradation at elevated temperatures in previous studies is due to the limited availability of defects for hydrogen passivation, rather than being limited by the defect passivation rate. An acceleration of the defect formation rate is also observed to increase both the effectiveness and speed of carrier-induced degradation mitigation, whereas increases in the passivation rate do not lead to a substantial acceleration of the hydrogen passivation process. For high-throughput mitigation of such carrier-induced degradation on finished solar cell devices, two key factors were found to be required, high-injection conditions (such as by using high intensity illumination) to enable an acceleration of defect formation whilst simultaneously enabling a rapid passivation of the formed defects, and a high temperature to accelerate both defect formation and defect passivation whilst still ensuring an effective mitigation of carrier-induced degradation

Strain Rate Dependant Material Model for Orthotropic Metals

International Nuclear Information System (INIS)

Vignjevic, Rade

2016-01-01

In manufacturing processes anisotropic metals are often exposed to the loading with high strain rates in the range from 10"2 s"-"1 to 10"6 s"-"1 (e.g. stamping, cold spraying and explosive forming). These types of loading often involve generation and propagation of shock waves within the material. The material behaviour under such a complex loading needs to be accurately modelled, in order to optimise the manufacturing process and achieve appropriate properties of the manufactured component. The presented research is related to development and validation of a thermodynamically consistent physically based constitutive model for metals under high rate loading. The model is capable of modelling damage, failure and formation and propagation of shock waves in anisotropic metals. The model has two main parts: the strength part which defines the material response to shear deformation and an equation of state (EOS) which defines the material response to isotropic volumetric deformation [1]. The constitutive model was implemented into the transient nonlinear finite element code DYNA3D [2] and our in house SPH code. Limited model validation was performed by simulating a number of high velocity material characterisation and validation impact tests. The new damage model was developed in the framework of configurational continuum mechanics and irreversible thermodynamics with internal state variables. The use of the multiplicative decomposition of deformation gradient makes the model applicable to arbitrary plastic and damage deformations. To account for the physical mechanisms of failure, the concept of thermally activated damage initially proposed by Tuller and Bucher [3], Klepaczko [4] was adopted as the basis for the new damage evolution model. This makes the proposed damage/failure model compatible with the Mechanical Threshold Strength (MTS) model Follansbee and Kocks [5], 1988; Chen and Gray [6] which was used to control evolution of flow stress during plastic

Testing and Modeling Fuel Regression Rate in a Miniature Hybrid Burner

Directory of Open Access Journals (Sweden)

Luciano Fanton

2012-01-01

Full Text Available Ballistic characterization of an extended group of innovative HTPB-based solid fuel formulations for hybrid rocket propulsion was performed in a lab-scale burner. An optical time-resolved technique was used to assess the quasisteady regression history of single perforation, cylindrical samples. The effects of metalized additives and radiant heat transfer on the regression rate of such formulations were assessed. Under the investigated operating conditions and based on phenomenological models from the literature, analyses of the collected experimental data show an appreciable influence of the radiant heat flux from burnt gases and soot for both unloaded and loaded fuel formulations. Pure HTPB regression rate data are satisfactorily reproduced, while the impressive initial regression rates of metalized formulations require further assessment.

A model for inverse dose-rate effects - low dose-rate hyper-sensibility in response to targeted radionuclide therapy

International Nuclear Information System (INIS)

Murray, I.; Mather, S.J.

2015-01-01

Full text of publication follows. The aim of this work was to test the hypothesis that the Linear-Quadratic (LQ) model of cell survival, developed for external beam radiotherapy (EBRT), could be extended to targeted radionuclide therapy (TRT) in order to predict dose-response relationships in a cell line exhibiting low dose hypersensitivity (LDH). Methods: aliquots of the PC-3 cancer cell line were treated with either EBRT or an in-vitro model of TRT (Irradiation of cell culture with Y-90 EDTA over 24, 48, 72 or 96 hours). Dosimetry for the TRT was calculated using radiation transport simulations with the Monte Carlo PENELOPE code. Clonogenic as well as functional biological assays were used to assess cell response. An extension of the LQ model was developed which incorporated a dose-rate threshold for activation of repair mechanisms. Results: accurate dosimetry for in-vitro exposures of cell cultures to radioactivity was established. LQ parameters of cell survival were established for the PC-3 cell line in response to EBRT. The standard LQ model did not predict survival in PC-3 cells exposed to Y 90 irradiation over periods of up to 96 hours. In fact cells were more sensitive to the same dose when irradiation was carried out over 96 hours than 24 hours. I.e. at a lower dose-rate. Deviations from the LQ predictions were most pronounced below a threshold dose-rate of 0.5 Gy/hr. These results led to an extension of the LQ model based upon a dose-rate dependent sigmoid model of single strand DNA repair. This extension to the model resulted in predicted cell survival curves that closely matched the experimental data. Conclusion: the LQ model of cell survival to radiation has been shown to be largely predictive of response to low dose-rate irradiation. However, in cells displaying LDH, further adaptation of the model was required. (authors)

Beyond Rating Curves: Time Series Models for in-Stream Turbidity Prediction

Science.gov (United States)

Wang, L.; Mukundan, R.; Zion, M.; Pierson, D. C.

2012-12-01

The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies over 1 billion gallons of water per day to more than 9 million customers. DEP's "West of Hudson" reservoirs located in the Catskill Mountains are unfiltered per a renewable filtration avoidance determination granted by the EPA. While water quality is usually pristine, high volume storm events occasionally cause the reservoirs to become highly turbid. A logical strategy for turbidity control is to temporarily remove the turbid reservoirs from service. While effective in limiting delivery of turbid water and reducing the need for in-reservoir alum flocculation, this strategy runs the risk of negatively impacting water supply reliability. Thus, it is advantageous for DEP to understand how long a particular turbidity event will affect their system. In order to understand the duration, intensity and total load of a turbidity event, predictions of future in-stream turbidity values are important. Traditionally, turbidity predictions have been carried out by applying streamflow observations/forecasts to a flow-turbidity rating curve. However, predictions from rating curves are often inaccurate due to inter- and intra-event variability in flow-turbidity relationships. Predictions can be improved by applying an autoregressive moving average (ARMA) time series model in combination with a traditional rating curve. Since 2003, DEP and the Upstate Freshwater Institute have compiled a relatively consistent set of 15-minute turbidity observations at various locations on Esopus Creek above Ashokan Reservoir. Using daily averages of this data and streamflow observations at nearby USGS gauges, flow-turbidity rating curves were developed via linear regression. Time series analysis revealed that the linear regression residuals may be represented using an ARMA(1,2) process. Based on this information, flow-turbidity regressions with

A microcomputer-based model for identifying urban and suburban roadways with critical large truck accident rates

International Nuclear Information System (INIS)

Brogan, J.D.; Cashwell, J.W.

1992-01-01

This paper presents an overview of techniques for merging highway accident record and roadway inventory files and employing the combined data set to identify spots or sections on highway facilities in urban and suburban areas with unusually high large truck accident rates. A statistical technique, the rate/quality control method, is used to calculate a critical rate for each location of interest. This critical rate may then be compared to the location's actual accident rate to identify locations for further study. Model enhancements and modifications are described to enable the technique to be employed in the evaluation of routing alternatives for the transport of radioactive material

Mechanistic Modeling of Water Replenishment Rate of Zeer Refrigerator

Directory of Open Access Journals (Sweden)

B. N. Nwankwojike

2017-06-01

Full Text Available A model for predicting the water replenishment rate of zeer pot refrigerator was developed in this study using mechanistic modeling approach and evaluated at Obowo, Imo State, Nigeria using six fruits, tomatoes, guava, okra, banana, orange and avocado pear. The developed model confirmed zeer pot water replenishment rate as a function of ambient temperature, relative humidity, wind speed, thermal conductivity of the pot materials and sand, density of air and water vapor, permeability coefficient of clay and heat transfer coefficient of water into air, circumferential length, height of pot, geometrical profile of the pot, heat load of the food preserved, heat flow into the device and gradient at which the pot is placed above ground level. Compared to the conventional approach of water replenishment, performance analysis results revealed 44% to 58% water economy when the zeer pot’s water was replenished based on the model’s prediction; while there was no significant difference in the shelf-life of the fruits preserved with both replenishment methods. Application of the developed water replenishment model facilitates optimal water usage in this system, thereby reducing operational cost of zeer pot refrigerator.

A global reference for caesarean section rates (C-Model): a multicountry cross-sectional study.

Science.gov (United States)

Souza, J P; Betran, A P; Dumont, A; de Mucio, B; Gibbs Pickens, C M; Deneux-Tharaux, C; Ortiz-Panozo, E; Sullivan, E; Ota, E; Togoobaatar, G; Carroli, G; Knight, H; Zhang, J; Cecatti, J G; Vogel, J P; Jayaratne, K; Leal, M C; Gissler, M; Morisaki, N; Lack, N; Oladapo, O T; Tunçalp, Ö; Lumbiganon, P; Mori, R; Quintana, S; Costa Passos, A D; Marcolin, A C; Zongo, A; Blondel, B; Hernández, B; Hogue, C J; Prunet, C; Landman, C; Ochir, C; Cuesta, C; Pileggi-Castro, C; Walker, D; Alves, D; Abalos, E; Moises, Ecd; Vieira, E M; Duarte, G; Perdona, G; Gurol-Urganci, I; Takahiko, K; Moscovici, L; Campodonico, L; Oliveira-Ciabati, L; Laopaiboon, M; Danansuriya, M; Nakamura-Pereira, M; Costa, M L; Torloni, M R; Kramer, M R; Borges, P; Olkhanud, P B; Pérez-Cuevas, R; Agampodi, S B; Mittal, S; Serruya, S; Bataglia, V; Li, Z; Temmerman, M; Gülmezoglu, A M

2016-02-01

To generate a global reference for caesarean section (CS) rates at health facilities. Cross-sectional study. Health facilities from 43 countries. Thirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10,045,875 women giving birth from 43 countries for model testing. We hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Area under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. According to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (www.who.int/reproductivehealth/publications/maternal_perinatal_health/c-model/en/). This article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS. The C-Model provides a customized benchmark for caesarean section rates in health facilities and systems. © 2015 World Health Organization; licensed by John Wiley & Sons Ltd on behalf of Royal College of Obstetricians and Gynaecologists.

Evidence-Based Adequacy Model for School Funding: Success Rates in Illinois Schools that Meet Targets

Science.gov (United States)

Murphy, Gregory J.

2012-01-01

This quantitative study explores the 2010 recommendation of the Educational Funding Advisory Board to consider the Evidence-Based Adequacy model of school funding in Illinois. This school funding model identifies and costs research based practices necessary in a prototypical school and sets funding levels based upon those practices. This study…

Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

International Nuclear Information System (INIS)

Guilani, Pedram Pourkarim; Azimi, Parham; Niaki, S.T.A.; Niaki, Seyed Armin Akhavan

2016-01-01

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series–parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a genetic algorithm is developed to solve the problem. - Highlights: • The redundancy allocation problem of a series–parallel system is aimed. • Components possess an increasing failure rate based on Weibull distribution. • An optimization method via simulation is proposed for modeling. • A genetic algorithm is developed to solve the problem.

Rate based failure detection

Science.gov (United States)

Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

2018-01-02

This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or data paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.

Equivalence of interest rate models and lattice gases.

Science.gov (United States)

Pirjol, Dan

2012-04-01

We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t(1),t(2))=-Cov[x(t(1)),x(t(2))]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e(-γ|x-y|)-e(-γ(x+y))). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.

A new lattice hydrodynamic model based on control method considering the flux change rate and delay feedback signal

Science.gov (United States)

Qin, Shunda; Ge, Hongxia; Cheng, Rongjun

2018-02-01

In this paper, a new lattice hydrodynamic model is proposed by taking delay feedback and flux change rate effect into account in a single lane. The linear stability condition of the new model is derived by control theory. By using the nonlinear analysis method, the mKDV equation near the critical point is deduced to describe the traffic congestion. Numerical simulations are carried out to demonstrate the advantage of the new model in suppressing traffic jam with the consideration of flux change rate effect in delay feedback model.

Shilling attack detection for recommender systems based on credibility of group users and rating time series.

Science.gov (United States)

Zhou, Wei; Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user's credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method.

A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers

Science.gov (United States)

Meng, Huan; Dong, Jun; Ferraro, Ralph; Yan, Banghua; Zhao, Limin; Kongoli, Cezar; Wang, Nai-Yu; Zavodsky, Bradley

2017-06-01

Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in-cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar-orbiting satellites, namely, NOAA-18, NOAA-19, Metop-A, Metop-B, and Suomi-NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite-based statistical model and a set of numerical weather prediction model-based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one-dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

Science.gov (United States)

Ibrahim, R. I.; Ngataman, N.; Abrisam, W. N. A. Wan Mohd

2017-09-01

Improvement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.

Prediction of 222 Rn exhalation rates from phosphogypsum based stacks. Part I: parametric mathematical modeling

International Nuclear Information System (INIS)

Rabi, Jose A.; Mohamad, Abdulmajeed A.

2004-01-01

Radon-222 is a radionuclide exhaled from phosphogypsum by-produced at phosphate fertilizer industries. Alternative large-scale application of this waste may indicate a material substitute for civil engineering provided that environmental issues concerning its disposal and management are overcome. The first part of this paper outlines a steady-state two-dimensional model for 222 Rn transport through porous media, inside which emanation (source term) and decay (sink term) exist. Boussinesq approach is evoked for the laminar buoyancy-driven interstitial air flow, which is also modeled according to Darcy-Brinkman formulation. In order to account for simultaneous effects of entailed physical parameters, governing equations are cast into dimensionless form. Apart from usual controlling parameters like Reynolds, Prandtl, Schmidt, Grashof and Darcy numbers, three unconventional dimensionless groups are put forward. Having in mind 222 Rn transport in phosphogypsum-bearing porous media, the physical meaning of those newly introduced parameters and representative values for the involved physical parameters are presented. A limiting diffusion-dominated scenario is addressed, for which an analytical solution is deduced for boundary conditions including an impermeable phosphogypsum stack base and a non-zero fixed concentration activity at the stack top. Accordingly, an expression for the average Sherwood number corresponding to the normalized 222 Rn exhalation rate is presented

Modelling plastic deformation of metals over a wide range of strain rates using irreversible thermodynamics

International Nuclear Information System (INIS)

Huang Mingxin; Rivera-Diaz-del-Castillo, Pedro E J; Zwaag, Sybrand van der; Bouaziz, Olivier

2009-01-01

Based on the theory of irreversible thermodynamics, the present work proposes a dislocation-based model to describe the plastic deformation of FCC metals over wide ranges of strain rates. The stress-strain behaviour and the evolution of the average dislocation density are derived. It is found that there is a transitional strain rate (∼ 10 4 s -1 ) over which the phonon drag effects appear, resulting in a significant increase in the flow stress and the average dislocation density. The model is applied to pure Cu deformed at room temperature and at strain rates ranging from 10 -5 to 10 6 s -1 showing good agreement with experimental results.

Permanence for a Delayed Nonautonomous SIR Epidemic Model with Density-Dependent Birth Rate

Directory of Open Access Journals (Sweden)

Li Yingke

2011-01-01

Full Text Available Based on some well-known SIR models, a revised nonautonomous SIR epidemic model with distributed delay and density-dependent birth rate was considered. Applying some classical analysis techniques for ordinary differential equations and the method proposed by Wang (2002, the threshold value for the permanence and extinction of the model was obtained.

A measurement-based performability model for a multiprocessor system

Science.gov (United States)

Ilsueh, M. C.; Iyer, Ravi K.; Trivedi, K. S.

1987-01-01

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

A sediment graph model based on SCS-CN method

Science.gov (United States)

Singh, P. K.; Bhunya, P. K.; Mishra, S. K.; Chaube, U. C.

2008-01-01

SummaryThis paper proposes new conceptual sediment graph models based on coupling of popular and extensively used methods, viz., Nash model based instantaneous unit sediment graph (IUSG), soil conservation service curve number (SCS-CN) method, and Power law. These models vary in their complexity and this paper tests their performance using data of the Nagwan watershed (area = 92.46 km 2) (India). The sensitivity of total sediment yield and peak sediment flow rate computations to model parameterisation is analysed. The exponent of the Power law, β, is more sensitive than other model parameters. The models are found to have substantial potential for computing sediment graphs (temporal sediment flow rate distribution) as well as total sediment yield.

A Constitutive Model for Superelastic Shape Memory Alloys Considering the Influence of Strain Rate

Directory of Open Access Journals (Sweden)

Hui Qian

2013-01-01

Full Text Available Shape memory alloys (SMAs are a relatively new class of functional materials, exhibiting special thermomechanical behaviors, such as shape memory effect and superelasticity, which enable their applications in seismic engineering as energy dissipation devices. This paper investigates the properties of superelastic NiTi shape memory alloys, emphasizing the influence of strain rate on superelastic behavior under various strain amplitudes by cyclic tensile tests. A novel constitutive equation based on Graesser and Cozzarelli’s model is proposed to describe the strain-rate-dependent hysteretic behavior of superelastic SMAs at different strain levels. A stress variable including the influence of strain rate is introduced into Graesser and Cozzarelli’s model. To verify the effectiveness of the proposed constitutive equation, experiments on superelastic NiTi wires with different strain rates and strain levels are conducted. Numerical simulation results based on the proposed constitutive equation and experimental results are in good agreement. The findings in this paper will assist the future design of superelastic SMA-based energy dissipation devices for seismic protection of structures.

Hybrid attacks on model-based social recommender systems

Science.gov (United States)

Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

2017-10-01

With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

QSAR models for oxidation of organic micropollutants in water based on ozone and hydroxyl radical rate constants and their chemical classification

KAUST Repository

Sudhakaran, Sairam

2013-03-01

Ozonation is an oxidation process for the removal of organic micropollutants (OMPs) from water and the chemical reaction is governed by second-order kinetics. An advanced oxidation process (AOP), wherein the hydroxyl radicals (OH radicals) are generated, is more effective in removing a wider range of OMPs from water than direct ozonation. Second-order rate constants (kOH and kO3) are good indices to estimate the oxidation efficiency, where higher rate constants indicate more rapid oxidation. In this study, quantitative structure activity relationships (QSAR) models for O3 and AOP processes were developed, and rate constants, kOH and kO3, were predicted based on target compound properties. The kO3 and kOH values ranged from 5 * 10-4 to 105 M-1s-1 and 0.04 to 18 * (109) M-1 s-1, respectively. Several molecular descriptors which potentially influence O3 and OH radical oxidation were identified and studied. The QSAR-defining descriptors were double bond equivalence (DBE), ionisation potential (IP), electron-affinity (EA) and weakly-polar component of solvent accessible surface area (WPSA), and the chemical and statistical significance of these descriptors was discussed. Multiple linear regression was used to build the QSAR models, resulting in high goodness-of-fit, r2 (>0.75). The models were validated by internal and external validation along with residual plots. © 2012 Elsevier Ltd.

Biomineralization-inspired synthesis of chitosan/hydroxyapatite biocomposites based on a novel bilayer rate-controlling model.

Science.gov (United States)

Hu, Jing-Xiao; Ran, Jia-Bing; Chen, Si; Shen, Xin-Yu; Tong, Hua

2015-12-01

In order to prepare sophisticated biomaterials using a biomimetic approach, a deeper understanding of biomineralization is needed. Of particular importance is the control and regulation of the mineralization process. In this study, a novel bilayer rate-controlling model was designed to investigate the factors potentially influencing mineralization. In the absence of a rate-controlling layer, nano-scale hydroxyapatite (HA) crystallites exhibited a spherical morphology, whereas, in the presence of a rate-controlling layer, HA crystallites were homogeneously dispersed and spindle-like in structure. The mineralization rate had a significant effect on controlling the morphology of crystals. Furthermore, in vitro tests demonstrated that the reaction layer containing spindle-like HA crystallites possessed superior biological properties. These results suggest that a slow mineralization rate is required for controlling the morphology of inorganic crystallites, and consumption by the rate-controlling layer ensured that the ammonia concentration remained low. This study demonstrates that a biomimetic approach can be used to prepare novel biomaterials containing HA crystallites that have different morphologies and biological properties. Copyright © 2015 Elsevier B.V. All rights reserved.

Laser Rate Equation Based Filtering for Carrier Recovery in Characterization and Communication

DEFF Research Database (Denmark)

Piels, Molly; Iglesias Olmedo, Miguel; Xue, Weiqi

2015-01-01

We formulate a semiconductor laser rate equationbased approach to carrier recovery in a Bayesian filtering framework. Filter stability and the effect of model inaccuracies (unknown or un-useable rate equation coefficients) are discussed. Two potential application areas are explored: laser...... characterization and carrier recovery in coherent communication. Two rate equation based Bayesian filters, the particle filter and extended Kalman filter, are used in conjunction with a coherent receiver to measure frequency noise spectrum of a photonic crystal cavity laser with less than 20 nW of fiber...

Polynomial Chaos Expansion Approach to Interest Rate Models

Directory of Open Access Journals (Sweden)

Luca Di Persio

2015-01-01

Full Text Available The Polynomial Chaos Expansion (PCE technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of random basis. The PCE methodology has been developed as a mathematically rigorous Uncertainty Quantification (UQ method which aims at providing reliable numerical estimates for some uncertain physical quantities defining the dynamic of certain engineering models and their related simulations. In the present paper, we use the PCE approach in order to analyze some equity and interest rate models. In particular, we take into consideration those models which are based on, for example, the Geometric Brownian Motion, the Vasicek model, and the CIR model. We present theoretical as well as related concrete numerical approximation results considering, without loss of generality, the one-dimensional case. We also provide both an efficiency study and an accuracy study of our approach by comparing its outputs with the ones obtained adopting the Monte Carlo approach, both in its standard and its enhanced version.

Spallation model for the high strain rates range

Science.gov (United States)

Dekel, E.; Eliezer, S.; Henis, Z.; Moshe, E.; Ludmirsky, A.; Goldberg, I. B.

1998-11-01

Measurements of the dynamic spall strength in aluminum and copper shocked by a high power laser to pressures of hundreds of kbars show a rapid increase in the spall strength with the strain rate at values of about 107 s-1. We suggest that this behavior is a result of a change in the spall mechanism. At low strain rates the spall is caused by the motion and coalescence of material's initial flaws. At high strain rates there is not enough time for the flaws to move and the spall is produced by the formation and coalescence of additional cavities where the interatomic forces become dominant. Material under tensile stress is in a metastable condition and cavities of a critical radius are formed in it due to thermal fluctuations. These cavities grow due to the tension. The total volume of the voids grow until the material disintegrates at the spall plane. Simplified calculations based on this model, describing the metal as a viscous liquid, give results in fairly good agreement with the experimental data and predict the increase in spall strength at high strain rates.

Models for financial crisis detection in Indonesia based on bank deposits, real exchange rate and terms of trade indicators

Science.gov (United States)

Sugiyanto; Zukhronah, Etik; Nur Aini, Anis

2017-12-01

Several times Indonesia has experienced to face a financial crisis, but the crisis occurred in 1997 had a tremendous impact on the economy and national stability. The impact of the crisis fall the exchange rate of rupiah against the dollar so it is needed the financial crisis detection system. Some data of bank deposits, real exchange rate and terms of trade indicators are used in this paper. Data taken from January 1990 until December 2016 are used to form the models with three state. Combination of volatility and Markov switching models are used to model the data. The result suggests that the appropriate model for bank deposit and terms of trade is SWARCH (3,1), and for real exchange rates is SWARCH (3,2).

Vehicle-specific emissions modeling based upon on-road measurements.

Science.gov (United States)

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

Analysis of a Farquhar-von Caemmerer-Berry leaf-level photosynthetic rate model for Populus tremuloides in the context of modeling and measurement limitations

International Nuclear Information System (INIS)

Lenz, Kathryn E.; Host, George E.; Roskoski, Kyle; Noormets, Asko; Sober, Anu; Karnosky, David F.

2010-01-01

The balance of mechanistic detail with mathematical simplicity contributes to the broad use of the Farquhar, von Caemmerer and Berry (FvCB) photosynthetic rate model. Here the FvCB model was coupled with a stomatal conductance model to form an [A,g s ] model, and parameterized for mature Populus tremuloides leaves under varying CO 2 and temperature levels. Data were selected to be within typical forest light, CO 2 and temperature ranges, reducing artifacts associated with data collected at extreme values. The error between model-predicted photosynthetic rate (A) and A data was measured in three ways and found to be up to three times greater for each of two independent data sets than for a base-line evaluation using parameterization data. The evaluation methods used here apply to comparisons of model validation results among data sets varying in number and distribution of data, as well as to performance comparisons of [A,g s ] models differing in internal-process components. - A photosynthetic rate model is parameterized for Populus tremuloides and evaluated based on its ability to predict dependent as well as independent data.

The dissolution rate of silicate glasses and minerals: an alternative model based on several activated complexes

International Nuclear Information System (INIS)

Berger, G.

1997-01-01

Most of the mineral reactions in natural water-rock systems progress at conditions close to the chemical equilibrium. The kinetics of these reactions, in particular the dissolution rate of the primary minerals, is a major constrain for the numerical modelling of diagenetic and hydrothermal processes. In the case of silicates, recent experimental studies have pointed out the necessity to better understand the elementary reactions which control the dissolution process. This article presents several models that have been proposed to account for the observed dissolution rate/chemical affinity relationships. The case of glasses (R7T7), feldspars and clays, in water, in near neutral pH aqueous solutions and in acid/basic media, are reviewed. (A.C.)

Total dose and dose rate models for bipolar transistors in circuit simulation.

Energy Technology Data Exchange (ETDEWEB)

Campbell, Phillip Montgomery; Wix, Steven D.

2013-05-01

The objective of this work is to develop a model for total dose effects in bipolar junction transistors for use in circuit simulation. The components of the model are an electrical model of device performance that includes the effects of trapped charge on device behavior, and a model that calculates the trapped charge densities in a specific device structure as a function of radiation dose and dose rate. Simulations based on this model are found to agree well with measurements on a number of devices for which data are available.

Exchange-Rate-Based Stabilization under Imperfect Credibility

OpenAIRE

Guillermo Calvo; Carlos A. Végh Gramont

1991-01-01

This paper analyzes stabilization policy under predetermined exchange rates in a cash-in-advance, staggered-prices model. Under full credibility, a reduction in the rate of devaluation results in an immediate and permanent reduction in the inflation rate, with no effect on output or consumption. In contrast, a non-credible stabilization results in an initial expansion of output, followed by a later recession. The inflation rate of home goods remains above the rate of devaluation throughout th...

Nonparametric modeling of US interest rate term structure dynamics and implications on the prices of derivative securities

NARCIS (Netherlands)

Jiang, GJ

1998-01-01

This paper develops a nonparametric model of interest rate term structure dynamics based an a spot rate process that permits only positive interest rates and a market price of interest rate risk that precludes arbitrage opportunities. Both the spot rate process and the market price of interest rate

A novel multitemporal insar model for joint estimation of deformation rates and orbital errors

KAUST Repository

Zhang, Lei; Ding, Xiaoli; Lu, Zhong; Jung, Hyungsup; Hu, Jun; Feng, Guangcai

2014-01-01

be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long

A Matérn model of the spatial covariance structure of point rain rates

KAUST Repository

Sun, Ying; Bowman, Kenneth P.; Genton, Marc G.; Tokay, Ali

2014-01-01

It is challenging to model a precipitation field due to its intermittent and highly scale-dependent nature. Many models of point rain rates or areal rainfall observations have been proposed and studied for different time scales. Among them, the spectral model based on a stochastic dynamical equation for the instantaneous point rain rate field is attractive, since it naturally leads to a consistent space–time model. In this paper, we note that the spatial covariance structure of the spectral model is equivalent to the well-known Matérn covariance model. Using high-quality rain gauge data, we estimate the parameters of the Matérn model for different time scales and demonstrate that the Matérn model is superior to an exponential model, particularly at short time scales.

A Matérn model of the spatial covariance structure of point rain rates

KAUST Repository

Sun, Ying

2014-07-15

It is challenging to model a precipitation field due to its intermittent and highly scale-dependent nature. Many models of point rain rates or areal rainfall observations have been proposed and studied for different time scales. Among them, the spectral model based on a stochastic dynamical equation for the instantaneous point rain rate field is attractive, since it naturally leads to a consistent space–time model. In this paper, we note that the spatial covariance structure of the spectral model is equivalent to the well-known Matérn covariance model. Using high-quality rain gauge data, we estimate the parameters of the Matérn model for different time scales and demonstrate that the Matérn model is superior to an exponential model, particularly at short time scales.

Modeling and predicting historical volatility in exchange rate markets

Science.gov (United States)

Lahmiri, Salim

2017-04-01

Volatility modeling and forecasting of currency exchange rate is an important task in several business risk management tasks; including treasury risk management, derivatives pricing, and portfolio risk evaluation. The purpose of this study is to present a simple and effective approach for predicting historical volatility of currency exchange rate. The approach is based on a limited set of technical indicators as inputs to the artificial neural networks (ANN). To show the effectiveness of the proposed approach, it was applied to forecast US/Canada and US/Euro exchange rates volatilities. The forecasting results show that our simple approach outperformed the conventional GARCH and EGARCH with different distribution assumptions, and also the hybrid GARCH and EGARCH with ANN in terms of mean absolute error, mean of squared errors, and Theil's inequality coefficient. Because of the simplicity and effectiveness of the approach, it is promising for US currency volatility prediction tasks.

Prediction of pure water stress corrosion cracking (PWSCC) in nickel base alloys using crack growth rate models

International Nuclear Information System (INIS)

Thompson, C.D.; Krasodomski, H.T.; Lewis, N.; Makar, G.L.

1995-01-01

The Ford/Andresen slip dissolution SCC model, originally developed for stainless steel components in BWR environments, has been applied to Alloy 600 and Alloy X-750 tested in deaerated pure water chemistry. A method is described whereby the crack growth rates measured in compact tension specimens can be used to estimate crack growth in a component. Good agreement was found between model prediction and measured SCC in X-750 threaded fasteners over a wide range of temperatures, stresses, and material condition. Most data support the basic assumption of this model that cracks initiate early in life. The evidence supporting a particular SCC mechanism is mixed. Electrochemical repassivation data and estimates of oxide fracture strain indicate that the slip dissolution model can account for the observed crack growth rates, provided primary rather than secondary creep rates are used. However, approximately 100 cross-sectional TEM foils of SCC cracks including crack tips reveal no evidence of enhanced plasticity or unique dislocation patterns at the crack tip or along the crack to support a classic slip dissolution mechanism. No voids, hydrides, or microcracks are found in the vicinity of the crack tips creating doubt about classic hydrogen related mechanisms. The bulk oxide films exhibit a surface oxide which is often different than the oxides found within a crack. Although bulk chromium concentration affects the rate of SCC, analytical data indicates the mechanism does not result from chromium depletion at the grain boundaries. The overall findings support a corrosion/dissolution mechanism but not one necessarily related to slip at the crack tip

Data-driven techniques to estimate parameters in a rate-dependent ferromagnetic hysteresis model

International Nuclear Information System (INIS)

Hu Zhengzheng; Smith, Ralph C.; Ernstberger, Jon M.

2012-01-01

The quantification of rate-dependent ferromagnetic hysteresis is important in a range of applications including high speed milling using Terfenol-D actuators. There exist a variety of frameworks for characterizing rate-dependent hysteresis including the magnetic model in Ref. , the homogenized energy framework, Preisach formulations that accommodate after-effects, and Prandtl-Ishlinskii models. A critical issue when using any of these models to characterize physical devices concerns the efficient estimation of model parameters through least squares data fits. A crux of this issue is the determination of initial parameter estimates based on easily measured attributes of the data. In this paper, we present data-driven techniques to efficiently and robustly estimate parameters in the homogenized energy model. This framework was chosen due to its physical basis and its applicability to ferroelectric, ferromagnetic and ferroelastic materials.

CEAI: CCM based Email Authorship Identification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah

2013-01-01

In this paper we present a model for email authorship identification (EAI) by employing a Cluster-based Classification (CCM) technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature-set to include some...... more interesting and effective features for email authorship identification (e.g. the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell). We also included Info Gain feature selection based...... reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM)-based models, as well as the models proposed by Iqbal et al. [1, 2]. The proposed model attains an accuracy rate of 94% for 10...

Chemistry resolved kinetic flow modeling of TATB based explosives

Science.gov (United States)

Vitello, Peter; Fried, Laurence E.; William, Howard; Levesque, George; Souers, P. Clark

2012-03-01

Detonation waves in insensitive, TATB-based explosives are believed to have multiple time scale regimes. The initial burn rate of such explosives has a sub-microsecond time scale. However, significant late-time slow release in energy is believed to occur due to diffusion limited growth of carbon. In the intermediate time scale concentrations of product species likely change from being in equilibrium to being kinetic rate controlled. We use the thermo-chemical code CHEETAH linked to an ALE hydrodynamics code to model detonations. We term our model chemistry resolved kinetic flow, since CHEETAH tracks the time dependent concentrations of individual species in the detonation wave and calculates EOS values based on the concentrations. We present here two variants of our new rate model and comparison with hot, ambient, and cold experimental data for PBX 9502.

Discrete Discriminant analysis based on tree-structured graphical models

DEFF Research Database (Denmark)

Perez de la Cruz, Gonzalo; Eslava, Guillermina

The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression.......The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...

What explains usage of mobile physician-rating apps? Results from a web-based questionnaire.

Science.gov (United States)

Bidmon, Sonja; Terlutter, Ralf; Röttl, Johanna

2014-06-11

Consumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking. This study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage. A total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses. The suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients' value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients' value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of using apps for health-related information

Volatility modeling for IDR exchange rate through APARCH model with student-t distribution

Science.gov (United States)

Nugroho, Didit Budi; Susanto, Bambang

2017-08-01

The aim of this study is to empirically investigate the performance of APARCH(1,1) volatility model with the Student-t error distribution on five foreign currency selling rates to Indonesian rupiah (IDR), including the Swiss franc (CHF), the Euro (EUR), the British pound (GBP), Japanese yen (JPY), and the US dollar (USD). Six years daily closing rates over the period of January 2010 to December 2016 for a total number of 1722 observations have analysed. The Bayesian inference using the efficient independence chain Metropolis-Hastings and adaptive random walk Metropolis methods in the Markov chain Monte Carlo (MCMC) scheme has been applied to estimate the parameters of model. According to the DIC criterion, this study has found that the APARCH(1,1) model under Student-t distribution is a better fit than the model under normal distribution for any observed rate return series. The 95% highest posterior density interval suggested the APARCH models to model the IDR/JPY and IDR/USD volatilities. In particular, the IDR/JPY and IDR/USD data, respectively, have significant negative and positive leverage effect in the rate returns. Meanwhile, the optimal power coefficient of volatility has been found to be statistically different from 2 in adopting all rate return series, save the IDR/EUR rate return series.

Fair premium rate of the deposit insurance system based on banks' creditworthiness

OpenAIRE

Yoshino, Naoyuki; Taghizadeh-Hesary, Farhad; Nili, Farhad

2017-01-01

Purpose: Deposit insurance is a key element in modern banking, as it guarantees the financial safety of deposits at depository financial institutions. It is necessary to have at least a dual fair premium rate system based on the creditworthiness of financial institutions, as considering a singular premium system for all banks will have a moral hazard. In this paper, we develop a theoretical as well as an empirical model for calculating dual fair premium rates. Design/methodology/approach: Our...

Modeling analysis of pulsed magnetization process of magnetic core based on inverse Jiles-Atherton model

Science.gov (United States)

Liu, Yi; Zhang, He; Liu, Siwei; Lin, Fuchang

2018-05-01

The J-A (Jiles-Atherton) model is widely used to describe the magnetization characteristics of magnetic cores in a low-frequency alternating field. However, this model is deficient in the quantitative analysis of the eddy current loss and residual loss in a high-frequency magnetic field. Based on the decomposition of magnetization intensity, an inverse J-A model is established which uses magnetic flux density B as an input variable. Static and dynamic core losses under high frequency excitation are separated based on the inverse J-A model. Optimized parameters of the inverse J-A model are obtained based on particle swarm optimization. The platform for the pulsed magnetization characteristic test is designed and constructed. The hysteresis curves of ferrite and Fe-based nanocrystalline cores at high magnetization rates are measured. The simulated and measured hysteresis curves are presented and compared. It is found that the inverse J-A model can be used to describe the magnetization characteristics at high magnetization rates and to separate the static loss and dynamic loss accurately.

Analysis of Factors that Influence Infiltration Rates using the HELP Model

International Nuclear Information System (INIS)

Dyer, J.; Shipmon, J.

2017-01-01

The Hydrologic Evaluation of Landfill Performance (HELP) model is used by Savannah River National Laboratory (SRNL) in conjunction with PORFLOW groundwater flow simulation software to make longterm predictions of the fate and transport of radionuclides in the environment at radiological waste sites. The work summarized in this report supports preparation of the planned 2018 Performance Assessment for the E-Area Low-Level Waste Facility (LLWF) at the Savannah River Site (SRS). More specifically, this project focused on conducting a sensitivity analysis of infiltration (i.e., the rate at which water travels vertically in soil) through the proposed E-Area LLWF closure cap. A sensitivity analysis was completed using HELP v3.95D to identify the cap design and material property parameters that most impact infiltration rates through the proposed closure cap for a 10,000-year simulation period. The results of the sensitivity analysis indicate that saturated hydraulic conductivity (Ksat) for select cap layers, precipitation rate, surface vegetation type, and geomembrane layer defect density are dominant factors limiting infiltration rate. Interestingly, calculated infiltration rates were substantially influenced by changes in the saturated hydraulic conductivity of the Upper Foundation and Lateral Drainage layers. For example, an order-of-magnitude decrease in Ksat for the Upper Foundation layer lowered the maximum infiltration rate from a base-case 11 inches per year to only two inches per year. Conversely, an order-of-magnitude increase in Ksat led to an increase in infiltration rate from 11 to 15 inches per year. This work and its results provide a framework for quantifying uncertainty in the radionuclide transport and dose models for the planned 2018 E-Area Performance Assessment. Future work will focus on the development of a nonlinear regression model for infiltration rate using Minitab 17® to facilitate execution of probabilistic simulations in the GoldSim® overall

Analysis of Factors that Influence Infiltration Rates using the HELP Model

Energy Technology Data Exchange (ETDEWEB)

Dyer, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Shipmon, J. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-09-28

The Hydrologic Evaluation of Landfill Performance (HELP) model is used by Savannah River National Laboratory (SRNL) in conjunction with PORFLOW groundwater flow simulation software to make longterm predictions of the fate and transport of radionuclides in the environment at radiological waste sites. The work summarized in this report supports preparation of the planned 2018 Performance Assessment for the E-Area Low-Level Waste Facility (LLWF) at the Savannah River Site (SRS). More specifically, this project focused on conducting a sensitivity analysis of infiltration (i.e., the rate at which water travels vertically in soil) through the proposed E-Area LLWF closure cap. A sensitivity analysis was completed using HELP v3.95D to identify the cap design and material property parameters that most impact infiltration rates through the proposed closure cap for a 10,000-year simulation period. The results of the sensitivity analysis indicate that saturated hydraulic conductivity (Ksat) for select cap layers, precipitation rate, surface vegetation type, and geomembrane layer defect density are dominant factors limiting infiltration rate. Interestingly, calculated infiltration rates were substantially influenced by changes in the saturated hydraulic conductivity of the Upper Foundation and Lateral Drainage layers. For example, an order-of-magnitude decrease in Ksat for the Upper Foundation layer lowered the maximum infiltration rate from a base-case 11 inches per year to only two inches per year. Conversely, an order-of-magnitude increase in Ksat led to an increase in infiltration rate from 11 to 15 inches per year. This work and its results provide a framework for quantifying uncertainty in the radionuclide transport and dose models for the planned 2018 E-Area Performance Assessment. Future work will focus on the development of a nonlinear regression model for infiltration rate using Minitab 17® to facilitate execution of probabilistic simulations in the GoldSim® overall

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

Directory of Open Access Journals (Sweden)

Kezi Yu

Full Text Available In this paper, we propose an application of non-parametric Bayesian (NPB models for classification of fetal heart rate (FHR recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP and the Chinese restaurant process with finite capacity (CRFC. Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR recordings in a real-time setting.

Sensitivity of tropospheric heating rates to aerosols: A modeling study

International Nuclear Information System (INIS)

Hanna, A.F.; Shankar, U.; Mathur, R.

1994-01-01

The effect of aerosols on the radiation balance is critical to the energetics of the atmosphere. Because of the relatively long residence of specific types of aerosols in the atmosphere and their complex thermal and chemical interactions, understanding their behavior is crucial for understanding global climate change. The authors used the Regional Particulate Model (RPM) to simulate aerosols in the eastern United States in order to identify the aerosol characteristics of specific rural and urban areas these characteristics include size, concentration, and vertical profile. A radiative transfer model based on an improved δ-Eddington approximation with 26 spectral intervals spanning the solar spectrum was then used to analyze the tropospheric heating rates associated with these different aerosol distributions. The authors compared heating rates forced by differences in surface albedo associated with different land-use characteristics, and found that tropospheric heating and surface cooling are sensitive to surface properties such as albedo

Stochastic interest rates model in compounding | Galadima ...

African Journals Online (AJOL)

Stochastic interest rates model in compounding. ... in finance, real estate, insurance, accounting and other areas of business administration. The assumption that future rates are fixed and known with certainty at the beginning of an investment, ...

The numerical evaluation on non-radiative multiphonon transition rate from different electronic bases

International Nuclear Information System (INIS)

Zhu Bangfen.

1985-10-01

A numerical calculation on the non-radiative multiphonon transition probability based on the adiabatic approximation (AA) and the static approximation (SA) has been accomplished in a model of two electronic levels coupled to one phonon mode. The numerical results indicate that the spectra based on different approximations are generally different apart from those vibrational levels which are far below the classical crossing point. For large electron-phonon coupling constant, the calculated transition rates based on AA are more reliable; on the other hand, for small transition coupling the transition rates near or beyond the cross region are quite different for two approximations. In addition to the diagonal non-adiabatic potential, the mixing and splitting of the original static potential sheets are responsible for the deviation of the transition rates based on different approximations. The relationship between the transition matrix element and the vibrational level shift, the Huang-Rhys factor, the separation of the electronic levels and the electron-phonon coupling is analysed and discussed. (author)

Inflation, Exchange Rates and Interest Rates in Ghana: an Autoregressive Distributed Lag Model

Directory of Open Access Journals (Sweden)

Dennis Nchor

2015-01-01

Full Text Available This paper investigates the impact of exchange rate movement and the nominal interest rate on inflation in Ghana. It also looks at the presence of the Fisher Effect and the International Fisher Effect scenarios. It makes use of an autoregressive distributed lag model and an unrestricted error correction model. Ordinary Least Squares regression methods were also employed to determine the presence of the Fischer Effect and the International Fisher Effect. The results from the study show that in the short run a percentage point increase in the level of depreciation of the Ghana cedi leads to an increase in the rate of inflation by 0.20%. A percentage point increase in the level of nominal interest rates however results in a decrease in inflation by 0.98%. Inflation increases by 1.33% for every percentage point increase in the nominal interest rate in the long run. An increase in inflation on the other hand increases the nominal interest rate by 0.51% which demonstrates the partial Fisher effect. A 1% increase in the interest rate differential leads to a depreciation of the Ghana cedi by approximately 1% which indicates the full International Fisher effect.

Combining rate-based and cap-and-trade emissions policies

International Nuclear Information System (INIS)

Fischer, Carolyn

2003-12-01

Rate-based emissions policies (like tradable performance standards, TPS) fix average emissions intensity, while cap-and-trade (CAT) policies fix total emissions. This paper shows that unfettered trade between rate-based and cap-and-trade programs always raises combined emissions, except when product markets are related in particular ways. Gains from trade are fully passed on to consumers in the rate-based sector, resulting in more output and greater emissions allocations. We consider several policy options to offset the expansion, including a tax, an 'exchange rate' to adjust for relative permit values, output-based allocation (OBA) for the rate-based sector, and tightening the cap. A range of combinations of tighter allocations could improve situations in both sectors with trade while holding emissions constant

A Comparison of Moment Rates for the Eastern Mediterranean Region from Competitive Kinematic Models

Science.gov (United States)

Klein, E. C.; Ozeren, M. S.; Shen-Tu, B.; Galgana, G. A.

2017-12-01

Relatively continuous, complex, and long-lived episodes of tectonic deformation gradually shaped the lithosphere of the eastern Mediterranean region into its present state. This large geodynamically interconnected and seismically active region absorbs, accumulates and transmits strains arising from stresses associated with: (1) steady northward convergence of the Arabian and African plates; (2) differences in lithospheric gravitational potential energy; and (3) basal tractions exerted by subduction along the Hellenic and Cyprus Arcs. Over the last twenty years, numerous kinematic models have been built using a variety of assumptions to take advantage of the extensive and dense GPS observations made across the entire region resulting in a far better characterization of the neotectonic deformation field than ever previously achieved. In this study, three separate horizontal strain rate field solutions obtained from three, region-wide, GPS only based kinematic models (i.e., a regional block model, a regional continuum model, and global continuum model) are utilized to estimate the distribution and uncertainty of geodetic moment rates within the eastern Mediterranean region. The geodetic moment rates from each model are also compared with seismic moment release rates gleaned from historic earthquake data. Moreover, kinematic styles of deformation derived from each of the modeled horizontal strain rate fields are examined for their degree of correlation with earthquake rupture styles defined by proximal centroid moment tensor solutions. This study suggests that significant differences in geodetically obtained moment rates from competitive kinematic models may introduce unforeseen bias into regularly updated, geodetically constrained, regional seismic hazard assessments.

A critique of recent models for human error rate assessment

International Nuclear Information System (INIS)

Apostolakis, G.E.

1988-01-01

This paper critically reviews two groups of models for assessing human error rates under accident conditions. The first group, which includes the US Nuclear Regulatory Commission (NRC) handbook model and the human cognitive reliability (HCR) model, considers as fundamental the time that is available to the operators to act. The second group, which is represented by the success likelihood index methodology multiattribute utility decomposition (SLIM-MAUD) model, relies on ratings of the human actions with respect to certain qualitative factors and the subsequent derivation of error rates. These models are evaluated with respect to two criteria: the treatment of uncertainties and the internal coherence of the models. In other words, this evaluation focuses primarily on normative aspects of these models. The principal findings are as follows: (1) Both of the time-related models provide human error rates as a function of the available time for action and the prevailing conditions. However, the HCR model ignores the important issue of state-of-knowledge uncertainties, dealing exclusively with stochastic uncertainty, whereas the model presented in the NRC handbook handles both types of uncertainty. (2) SLIM-MAUD provides a highly structured approach for the derivation of human error rates under given conditions. However, the treatment of the weights and ratings in this model is internally inconsistent. (author)

A numerical evaluation of prediction accuracy of CO2 absorber model for various reaction rate coefficients

Directory of Open Access Journals (Sweden)

Shim S.M.

2012-01-01

Full Text Available The performance of the CO2 absorber column using mono-ethanolamine (MEA solution as chemical solvent are predicted by a One-Dimensional (1-D rate based model in the present study. 1-D Mass and heat balance equations of vapor and liquid phase are coupled with interfacial mass transfer model and vapor-liquid equilibrium model. The two-film theory is used to estimate the mass transfer between the vapor and liquid film. Chemical reactions in MEA-CO2-H2O system are considered to predict the equilibrium pressure of CO2 in the MEA solution. The mathematical and reaction kinetics models used in this work are calculated by using in-house code. The numerical results are validated in the comparison of simulation results with experimental and simulation data given in the literature. The performance of CO2 absorber column is evaluated by the 1-D rate based model using various reaction rate coefficients suggested by various researchers. When the rate of liquid to gas mass flow rate is about 8.3, 6.6, 4.5 and 3.1, the error of CO2 loading and the CO2 removal efficiency using the reaction rate coefficients of Aboudheir et al. is within about 4.9 % and 5.2 %, respectively. Therefore, the reaction rate coefficient suggested by Aboudheir et al. among the various reaction rate coefficients used in this study is appropriate to predict the performance of CO2 absorber column using MEA solution. [Acknowledgement. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF, funded by the Ministry of Education, Science and Technology (2011-0017220].

Application of transient burning rate model of solid propellant in electrothermal-chemical launch simulation

Directory of Open Access Journals (Sweden)

Yan-jie Ni

2016-04-01

Full Text Available A 30 mm electrothermal-chemical (ETC gun experimental system is employed to research the burning rate characteristics of 4/7 high-nitrogen solid propellant. Enhanced gas generation rates (EGGR of propellants during and after electrical discharges are verified in the experiments. A modified 0D internal ballistic model is established to simulate the ETC launch. According to the measured pressure and electrical parameters, a transient burning rate law including the influence of EGGR coefficient by electric power and pressure gradient (dp/dt is added into the model. The EGGR coefficient of 4/7 high-nitrogen solid propellant is equal to 0.005 MW−1. Both simulated breech pressure and projectile muzzle velocity accord with the experimental results well. Compared with Woodley's modified burning rate law, the breech pressure curves acquired by the transient burning rate law are more consistent with test results. Based on the parameters calculated in the model, the relationship among propellant burning rate, pressure gradient (dp/dt and electric power is analyzed. Depending on the transient burning rate law and experimental data, the burning of solid propellant under the condition of plasma is described more accurately.

Radionuclide release rates from spent fuel for performance assessment modeling

International Nuclear Information System (INIS)

Curtis, D.B.

1994-01-01

In a scenario of aqueous transport from a high-level radioactive waste repository, the concentration of radionuclides in water in contact with the waste constitutes the source term for transport models, and as such represents a fundamental component of all performance assessment models. Many laboratory experiments have been done to characterize release rates and understand processes influencing radionuclide release rates from irradiated nuclear fuel. Natural analogues of these waste forms have been studied to obtain information regarding the long-term stability of potential waste forms in complex natural systems. This information from diverse sources must be brought together to develop and defend methods used to define source terms for performance assessment models. In this manuscript examples of measures of radionuclide release rates from spent nuclear fuel or analogues of nuclear fuel are presented. Each example represents a very different approach to obtaining a numerical measure and each has its limitations. There is no way to obtain an unambiguous measure of this or any parameter used in performance assessment codes for evaluating the effects of processes operative over many millennia. The examples are intended to suggest by example that in the absence of the ability to evaluate accuracy and precision, consistency of a broadly based set of data can be used as circumstantial evidence to defend the choice of parameters used in performance assessments

A GPS Satellite Clock Offset Prediction Method Based on Fitting Clock Offset Rates Data

Directory of Open Access Journals (Sweden)

WANG Fuhong

2016-12-01

Full Text Available It is proposed that a satellite atomic clock offset prediction method based on fitting and modeling clock offset rates data. This method builds quadratic model or linear model combined with periodic terms to fit the time series of clock offset rates, and computes the model coefficients of trend with the best estimation. The clock offset precisely estimated at the initial prediction epoch is directly adopted to calculate the model coefficient of constant. The clock offsets in the rapid ephemeris (IGR provided by IGS are used as modeling data sets to perform certain experiments for different types of GPS satellite clocks. The results show that the clock prediction accuracies of the proposed method for 3, 6, 12 and 24 h achieve 0.43, 0.58, 0.90 and 1.47 ns respectively, which outperform the traditional prediction method based on fitting original clock offsets by 69.3%, 61.8%, 50.5% and 37.2%. Compared with the IGU real-time clock products provided by IGS, the prediction accuracies of the new method have improved about 15.7%, 23.7%, 27.4% and 34.4% respectively.

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

Science.gov (United States)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach

Science.gov (United States)

Aloui, Chaker; Jammazi, Rania

2015-10-01

In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.

On a sparse pressure-flow rate condensation of rigid circulation models

Science.gov (United States)

Schiavazzi, D. E.; Hsia, T. Y.; Marsden, A. L.

2015-01-01

Cardiovascular simulation has shown potential value in clinical decision-making, providing a framework to assess changes in hemodynamics produced by physiological and surgical alterations. State-of-the-art predictions are provided by deterministic multiscale numerical approaches coupling 3D finite element Navier Stokes simulations to lumped parameter circulation models governed by ODEs. Development of next-generation stochastic multiscale models whose parameters can be learned from available clinical data under uncertainty constitutes a research challenge made more difficult by the high computational cost typically associated with the solution of these models. We present a methodology for constructing reduced representations that condense the behavior of 3D anatomical models using outlet pressure-flow polynomial surrogates, based on multiscale model solutions spanning several heart cycles. Relevance vector machine regression is compared with maximum likelihood estimation, showing that sparse pressure/flow rate approximations offer superior performance in producing working surrogate models to be included in lumped circulation networks. Sensitivities of outlets flow rates are also quantified through a Sobol’ decomposition of their total variance encoded in the orthogonal polynomial expansion. Finally, we show that augmented lumped parameter models including the proposed surrogates accurately reproduce the response of multiscale models they were derived from. In particular, results are presented for models of the coronary circulation with closed loop boundary conditions and the abdominal aorta with open loop boundary conditions. PMID:26671219

On a problematic procedure to manipulate response biases in recognition experiments: the case of "implied" base rates.

Science.gov (United States)

Bröder, Arndt; Malejka, Simone

2017-07-01

The experimental manipulation of response biases in recognition-memory tests is an important means for testing recognition models and for estimating their parameters. The textbook manipulations for binary-response formats either vary the payoff scheme or the base rate of targets in the recognition test, with the latter being the more frequently applied procedure. However, some published studies reverted to implying different base rates by instruction rather than actually changing them. Aside from unnecessarily deceiving participants, this procedure may lead to cognitive conflicts that prompt response strategies unknown to the experimenter. To test our objection, implied base rates were compared to actual base rates in a recognition experiment followed by a post-experimental interview to assess participants' response strategies. The behavioural data show that recognition-memory performance was estimated to be lower in the implied base-rate condition. The interview data demonstrate that participants used various second-order response strategies that jeopardise the interpretability of the recognition data. We thus advice researchers against substituting actual base rates with implied base rates.

Evolution of the rate of biological aging using a phenotype based computational model.

Science.gov (United States)

Kittas, Aristotelis

2010-10-07

In this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P(d)) or beneficial (P(b)) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P(d)/P(b), the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P(d) and P(b) and the amount of the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results. 2010 Elsevier Ltd. All rights reserved.

The importance of the strain rate and creep on the stress corrosion cracking mechanisms and models

International Nuclear Information System (INIS)

Aly, Omar F.; Mattar Neto, Miguel; Schvartzman, Monica M.A.M.

2011-01-01

Stress corrosion cracking is a nuclear, power, petrochemical, and other industries equipment and components (like pressure vessels, nozzles, tubes, accessories) life degradation mode, involving fragile fracture. The stress corrosion cracking failures can produce serious accidents, and incidents which can put on risk the safety, reliability, and efficiency of many plants. These failures are of very complex prediction. The stress corrosion cracking mechanisms are based on three kinds of factors: microstructural, mechanical and environmental. Concerning the mechanical factors, various authors prefer to consider the crack tip strain rate rather than stress, as a decisive factor which contributes to the process: this parameter is directly influenced by the creep strain rate of the material. Based on two KAPL-Knolls Atomic Power Laboratory experimental studies in SSRT (slow strain rate test) and CL (constant load) test, for prediction of primary water stress corrosion cracking in nickel based alloys, it has done a data compilation of the film rupture mechanism parameters, for modeling PWSCC of Alloy 600 and discussed the importance of the strain rate and the creep on the stress corrosion cracking mechanisms and models. As derived from this study, a simple theoretical model is proposed, and it is showed that the crack growth rate estimated with Brazilian tests results with Alloy 600 in SSRT, are according with the KAPL ones and other published literature. (author)

A simplified model for predicting malaria entomologic inoculation rates based on entomologic and parasitologic parameters relevant to control.

Science.gov (United States)

Killeen, G F; McKenzie, F E; Foy, B D; Schieffelin, C; Billingsley, P F; Beier, J C

2000-05-01

Malaria transmission intensity is modeled from the starting perspective of individual vector mosquitoes and is expressed directly as the entomologic inoculation rate (EIR). The potential of individual mosquitoes to transmit malaria during their lifetime is presented graphically as a function of their feeding cycle length and survival, human biting preferences, and the parasite sporogonic incubation period. The EIR is then calculated as the product of 1) the potential of individual vectors to transmit malaria during their lifetime, 2) vector emergence rate relative to human population size, and 3) the infectiousness of the human population to vectors. Thus, impacts on more than one of these parameters will amplify each other's effects. The EIRs transmitted by the dominant vector species at four malaria-endemic sites from Papua New Guinea, Tanzania, and Nigeria were predicted using field measurements of these characteristics together with human biting rate and human reservoir infectiousness. This model predicted EIRs (+/- SD) that are 1.13 +/- 0.37 (range = 0.84-1.59) times those measured in the field. For these four sites, mosquito emergence rate and lifetime transmission potential were more important determinants of the EIR than human reservoir infectiousness. This model and the input parameters from the four sites allow the potential impacts of various control measures on malaria transmission intensity to be tested under a range of endemic conditions. The model has potential applications for the development and implementation of transmission control measures and for public health education.

Estimation of unemployment rates using small area estimation model by combining time series and cross-sectional data

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Muchlisoh, Siti; Kurnia, Anang; Notodiputro, Khairil Anwar; Mangku, I. Wayan

2016-02-01

Labor force surveys conducted over time by the rotating panel design have been carried out in many countries, including Indonesia. Labor force survey in Indonesia is regularly conducted by Statistics Indonesia (Badan Pusat Statistik-BPS) and has been known as the National Labor Force Survey (Sakernas). The main purpose of Sakernas is to obtain information about unemployment rates and its changes over time. Sakernas is a quarterly survey. The quarterly survey is designed only for estimating the parameters at the provincial level. The quarterly unemployment rate published by BPS (official statistics) is calculated based on only cross-sectional methods, despite the fact that the data is collected under rotating panel design. The study purpose to estimate a quarterly unemployment rate at the district level used small area estimation (SAE) model by combining time series and cross-sectional data. The study focused on the application and comparison between the Rao-Yu model and dynamic model in context estimating the unemployment rate based on a rotating panel survey. The goodness of fit of both models was almost similar. Both models produced an almost similar estimation and better than direct estimation, but the dynamic model was more capable than the Rao-Yu model to capture a heterogeneity across area, although it was reduced over time.

Task-based dermal exposure models for regulatory risk assessment.

Science.gov (United States)

Warren, Nicholas D; Marquart, Hans; Christopher, Yvette; Laitinen, Juha; VAN Hemmen, Joop J

2006-07-01

The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

What Explains Usage of Mobile Physician-Rating Apps? Results From a Web-Based Questionnaire

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Terlutter, Ralf; Röttl, Johanna

2014-01-01

Background Consumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking. Objective This study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage. Methods A total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses. Results The suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients’ value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients’ value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of

Distributed Fair Auto Rate Medium Access Control for IEEE 802.11 Based WLANs

Science.gov (United States)

Zhu, Yanfeng; Niu, Zhisheng

Much research has shown that a carefully designed auto rate medium access control can utilize the underlying physical multi-rate capability to exploit the time-variation of the channel. In this paper, we develop a simple analytical model to elucidate the rule that maximizes the throughput of RTS/CTS based multi-rate wireless local area networks. Based on the discovered rule, we propose two distributed fair auto rate medium access control schemes called FARM and FARM+ from the view-point of throughput fairness and time-share fairness, respectively. With the proposed schemes, after receiving a RTS frame, the receiver selectively returns the CTS frame to inform the transmitter the maximum feasible rate probed by the signal-to-noise ratio of the received RTS frame. The key feature of the proposed schemes is that they are capable of maintaining throughput/time-share fairness in asymmetric situation where the distribution of SNR varies with stations. Extensive simulation results show that the proposed schemes outperform the existing throughput/time-share fair auto rate schemes in time-varying channel conditions.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

Science.gov (United States)

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

[NDVI difference rate recognition model of deciduous broad-leaved forest based on HJ-CCD remote sensing data].

Science.gov (United States)

Wang, Yan; Tian, Qing-Jiu; Huang, Yan; Wei, Hong-Wei

2013-04-01

The present paper takes Chuzhou in Anhui Province as the research area, and deciduous broad-leaved forest as the research object. Then it constructs the recognition model about deciduous broad-leaved forest was constructed using NDVI difference rate between leaf expansion and flowering and fruit-bearing, and the model was applied to HJ-CCD remote sensing image on April 1, 2012 and May 4, 2012. At last, the spatial distribution map of deciduous broad-leaved forest was extracted effectively, and the results of extraction were verified and evaluated. The result shows the validity of NDVI difference rate extraction method proposed in this paper and also verifies the applicability of using HJ-CCD data for vegetation classification and recognition.

A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates.

Science.gov (United States)

An, Qian; Kang, Jian; Song, Ruiguang; Hall, H Irene

2016-04-30

Human immunodeficiency virus (HIV) infection is a severe infectious disease actively spreading globally, and acquired immunodeficiency syndrome (AIDS) is an advanced stage of HIV infection. The HIV testing rate, that is, the probability that an AIDS-free HIV infected person seeks a test for HIV during a particular time interval, given no previous positive test has been obtained prior to the start of the time, is an important parameter for public health. In this paper, we propose a Bayesian hierarchical model with two levels of hierarchy to estimate the HIV testing rate using annual AIDS and AIDS-free HIV diagnoses data. At level one, we model the latent number of HIV infections for each year using a Poisson distribution with the intensity parameter representing the HIV incidence rate. At level two, the annual numbers of AIDS and AIDS-free HIV diagnosed cases and all undiagnosed cases stratified by the HIV infections at different years are modeled using a multinomial distribution with parameters including the HIV testing rate. We propose a new class of priors for the HIV incidence rate and HIV testing rate taking into account the temporal dependence of these parameters to improve the estimation accuracy. We develop an efficient posterior computation algorithm based on the adaptive rejection metropolis sampling technique. We demonstrate our model using simulation studies and the analysis of the national HIV surveillance data in the USA. Copyright © 2015 John Wiley & Sons, Ltd.

Model Predictive Control based on Finite Impulse Response Models

DEFF Research Database (Denmark)

Prasath, Guru; Jørgensen, John Bagterp

2008-01-01

We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

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Orkun eÖnal

2014-09-01

Full Text Available A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress – equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Forecasting the mortality rates of Malaysian population using Heligman-Pollard model

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Ibrahim, Rose Irnawaty; Mohd, Razak; Ngataman, Nuraini; Abrisam, Wan Nur Azifah Wan Mohd

2017-08-01

Actuaries, demographers and other professionals have always been aware of the critical importance of mortality forecasting due to declining trend of mortality and continuous increases in life expectancy. Heligman-Pollard model was introduced in 1980 and has been widely used by researchers in modelling and forecasting future mortality. This paper aims to estimate an eight-parameter model based on Heligman and Pollard's law of mortality. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in order to estimate the parameters. Statistical Package for the Social Sciences (SPSS) will be applied to forecast all the parameters according to Autoregressive Integrated Moving Average (ARIMA). The empirical data sets of Malaysian population for period of 1981 to 2015 for both genders will be considered, which the period of 1981 to 2010 will be used as "training set" and the period of 2011 to 2015 as "testing set". In order to investigate the accuracy of the estimation, the forecast results will be compared against actual data of mortality rates. The result shows that Heligman-Pollard model fit well for male population at all ages while the model seems to underestimate the mortality rates for female population at the older ages.

Modeling Long Term Corn Yield Response to Nitrogen Rate and Crop Rotation

Directory of Open Access Journals (Sweden)

Laila Alejandra Puntel

2016-11-01

Full Text Available Improved prediction of optimal N fertilizer rates for corn (Zea mays L. can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM to simulate corn and soybean (Glycine max L. yields, the economic optimum N rate (EONR using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1 applied to corn. Our objectives were to: a quantify model prediction accuracy before and after calibration, and report calibration steps; b compare crop model-based techniques in estimating optimal N rate for corn; and c utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simultaneously simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration, which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration. For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-yr mean differences in EONR’s were within the historical N rate error range (40 to 50 kg N ha-1. However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching with precipitation. We concluded that long term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add

Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

Science.gov (United States)

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

2016-01-01

Improved prediction of optimal N fertilizer rates for corn ( Zea mays L. ) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean ( Glycine max L. ) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha -1 ) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha -1 ). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward

Testing the Monetary Model for Exchange Rate Determination in South Africa: Evidence from 101 Years of Data

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Riané de Bruyn

2013-03-01

Full Text Available Evidence in favor of the monetary model of exchange rate determination for the South African Rand is, at best, mixed. A co-integrating relationship between the nominal exchange rate and monetary fundamentals forms the basis of the monetary model. With the econometric literature suggesting that the span of the data, not the frequency, determines the power of the co-integration tests and the studies on South Africa primarily using short-span data from the post-Bretton Woods era, we decided to test the long-run monetary model of exchange rate determination for the South African Rand relative to the US Dollar using annual data from 1910 – 2010. The results provide some support for the monetary model in that long-run co-integration is found between the nominal exchange rate and the output and money supply deviations. However, the theoretical restrictions required by the monetary model are rejected. A vector error-correction model identifies both the nominal exchange rate and the monetary fundamentals as the channel for the adjustment process of deviations from the long-run equilibrium exchange rate. A subsequent comparison of nominal exchange rate forecasts based on the monetary model with those of the random walk model suggests that the forecasting performance of the monetary model is superior.

Models of Anaylzing the Influence of Factors on Forming Profit Rate

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Klara S. Jakovčević

2014-04-01

Full Text Available The analysis in this paper is focused on identifying the impact of individual factors on the elements of the profit rate. The primary aim of this work is a methodological overview of solutions for understanding the full content of the profit rate as a cause of economic quality as well as indicators of the results of reproduction. Application of model analysis of profit rate factors was performed in an enterprise from Serbia that manufactures construction materials from baked clay. The aim is of application is to test the range in determining elements and factors of economic success of the enterprise, and quantification of changes in its assumptions. The results are useful guideline for the management to take organizational measures to increase the economic success of the enterprise. This means eliminating the negative, emphasizing the positive impact of objectively, and organizational factors to make higher economic success. Based on empirical research, it could be concluded that the proposed quantitative models of analyzing the dynamics of enterprise business quality could be applied in practice.

Male sexual strategies modify ratings of female models with specific waist-to-hip ratios.

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Brase, Gary L; Walker, Gary

2004-06-01

Female waist-to-hip ratio (WHR) has generally been an important general predictor of ratings of physical attractiveness and related characteristics. Individual differences in ratings do exist, however, and may be related to differences in the reproductive tactics of the male raters such as pursuit of short-term or long-term relationships and adjustments based on perceptions of one's own quality as a mate. Forty males, categorized according to sociosexual orientation and physical qualities (WHR, Body Mass Index, and self-rated desirability), rated female models on both attractiveness and likelihood they would approach them. Sociosexually restricted males were less likely to approach females rated as most attractive (with 0.68-0.72 WHR), as compared with unrestricted males. Males with lower scores in terms of physical qualities gave ratings indicating more favorable evaluations of female models with lower WHR. The results indicate that attractiveness and willingness to approach are overlapping but distinguishable constructs, both of which are influenced by variations in characteristics of the raters.

Credit Rating via Dynamic Slack-Based Measure And It´s Optimal Investment Strategy

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A. Delavarkhalafi

2015-01-01

Full Text Available In this paper we check the credit rating of firms applied for a loan. In this regard we introduce a model, named Dynamic Slack-Based Measure (DSBM for measuring credit rating of applicant companies. Selection of financial ratios that represent the financial state of a company -in the best possible way- is one of the most challenging parts of any credit rating analysis. At first, ranking needs to identify the appropriate variables. Therefore we introduce five financial variables to provide a ranking. As noted above, we assess the performance of these firms. Then we introduce the dynamic model of SBM and theorems, also we discuss the overall structure of DSBM. Then we will present the implementation and the simulation model. After that, we propose a stochastic controlled dynamic system model to express the optimal strategy. Banks expect companies selected with DSBM model, act in accordance with this strategy. This stochastic dynamic system is originated from the balance sheets of firms applying for a loan. Finally we evaluate the performance of the system and strategy problem.

Intuitive Understanding of Base Rates

DEFF Research Database (Denmark)

Austin, Laurel

Purpose: This study examines whether physicians and other adults intuitively understand that the probability a positive test result is a true positive (positive predictive value, PPV) depends on the base rate of disease in the population tested. In particular, this research seeks to examine perce...

Credit Rating via Dynamic Slack-Based Measure And It´s Optimal Investment Strategy

OpenAIRE

A. Delavarkhalafi; A. Poursherafatan

2015-01-01

In this paper we check the credit rating of firms applied for a loan. In this regard we introduce a model, named Dynamic Slack-Based Measure (DSBM) for measuring credit rating of applicant companies. Selection of financial ratios that represent the financial state of a company -in the best possible way- is one of the most challenging parts of any credit rating analysis. At first, ranking needs to identify the appropriate variables. Therefore we introduce five financial variables to provide a ...

Effects of population based screening for Chlamydia infections in the Netherlands limited by declining participation rates.

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Boris V Schmid

Full Text Available BACKGROUND: A large trial to investigate the effectiveness of population based screening for chlamydia infections was conducted in the Netherlands in 2008-2012. The trial was register based and consisted of four rounds of screening of women and men in the age groups 16-29 years in three regions in the Netherlands. Data were collected on participation rates and positivity rates per round. A modeling study was conducted to project screening effects for various screening strategies into the future. METHODS AND FINDINGS: We used a stochastic network simulation model incorporating partnership formation and dissolution, aging and a sexual life course perspective. Trends in baseline rates of chlamydia testing and treatment were used to describe the epidemiological situation before the start of the screening program. Data on participation rates was used to describe screening uptake in rural and urban areas. Simulations were used to project the effectiveness of screening on chlamydia prevalence for a time period of 10 years. In addition, we tested alternative screening strategies, such as including only women, targeting different age groups, and biennial screening. Screening reduced prevalence by about 1% in the first two screening rounds and leveled off after that. Extrapolating observed participation rates into the future indicated very low participation in the long run. Alternative strategies only marginally changed the effectiveness of screening. Higher participation rates as originally foreseen in the program would have succeeded in reducing chlamydia prevalence to very low levels in the long run. CONCLUSIONS: Decreasing participation rates over time profoundly impact the effectiveness of population based screening for chlamydia infections. Using data from several consecutive rounds of screening in a simulation model enabled us to assess the future effectiveness of screening on prevalence. If participation rates cannot be kept at a sufficient level

Estimation of an optimal chemotherapy utilisation rate for cancer: setting an evidence-based benchmark for quality cancer care.

Science.gov (United States)

Jacob, S A; Ng, W L; Do, V

2015-02-01

There is wide variation in the proportion of newly diagnosed cancer patients who receive chemotherapy, indicating the need for a benchmark rate of chemotherapy utilisation. This study describes an evidence-based model that estimates the proportion of new cancer patients in whom chemotherapy is indicated at least once (defined as the optimal chemotherapy utilisation rate). The optimal chemotherapy utilisation rate can act as a benchmark for measuring and improving the quality of care. Models of optimal chemotherapy utilisation were constructed for each cancer site based on indications for chemotherapy identified from evidence-based treatment guidelines. Data on the proportion of patient- and tumour-related attributes for which chemotherapy was indicated were obtained, using population-based data where possible. Treatment indications and epidemiological data were merged to calculate the optimal chemotherapy utilisation rate. Monte Carlo simulations and sensitivity analyses were used to assess the effect of controversial chemotherapy indications and variations in epidemiological data on our model. Chemotherapy is indicated at least once in 49.1% (95% confidence interval 48.8-49.6%) of all new cancer patients in Australia. The optimal chemotherapy utilisation rates for individual tumour sites ranged from a low of 13% in thyroid cancers to a high of 94% in myeloma. The optimal chemotherapy utilisation rate can serve as a benchmark for planning chemotherapy services on a population basis. The model can be used to evaluate service delivery by comparing the benchmark rate with patterns of care data. The overall estimate for other countries can be obtained by substituting the relevant distribution of cancer types. It can also be used to predict future chemotherapy workload and can be easily modified to take into account future changes in cancer incidence, presentation stage or chemotherapy indications. Copyright © 2014 The Royal College of Radiologists. Published by

Modeling dose-rate on/over the surface of cylindrical radio-models using Monte Carlo methods

International Nuclear Information System (INIS)

Xiao Xuefu; Ma Guoxue; Wen Fuping; Wang Zhongqi; Wang Chaohui; Zhang Jiyun; Huang Qingbo; Zhang Jiaqiu; Wang Xinxing; Wang Jun

2004-01-01

Objective: To determine the dose-rates on/over the surface of 10 cylindrical radio-models, which belong to the Metrology Station of Radio-Geological Survey of CNNC. Methods: The dose-rates on/over the surface of 10 cylindrical radio-models were modeled using the famous Monte Carlo code-MCNP. The dose-rates on/over the surface of 10 cylindrical radio-models were measured by a high gas pressurized ionization chamber dose-rate meter, respectively. The values of dose-rate modeled using MCNP code were compared with those obtained by authors in the present experimental measurement, and with those obtained by other workers previously. Some factors causing the discrepancy between the data obtained by authors using MCNP code and the data obtained using other methods are discussed in this paper. Results: The data of dose-rates on/over the surface of 10 cylindrical radio-models, obtained using MCNP code, were in good agreement with those obtained by other workers using the theoretical method. They were within the discrepancy of ±5% in general, and the maximum discrepancy was less than 10%. Conclusions: As if each factor needed for the Monte Carlo code is correct, the dose-rates on/over the surface of cylindrical radio-models modeled using the Monte Carlo code are correct with an uncertainty of 3%

Cost-related model for transit rates in electric power distribution networks

International Nuclear Information System (INIS)

Collstrand, F.

1994-02-01

The planned deregulation of the swedish electrical power market will require a new structure of the electrical energy rates. In this report different models of transit rates are studied. The report includes studies of literature and a proposal to a rate structure and is made specifically for Malmoe Energi AB. The differences between various methods of calculating the transfer cost are illustrated. Further, the build-up of the tariff structure and its base elements are discussed. The costs are divided on different categories of costumers and shows the cost for each customer. The new regulations should apply simultaneously to all networks, independent of the voltage level. The transit cost should be based on a number of basic elements: capital cost, operation and maintenance, losses, measuring and administration. Capital cost and operation and maintenance should be charged as power fees, the loss cost as an energy fee and the measuring and administration cost as a fixed fee. The customer bill should be split into two parts, one for the transit cost and one for the energy usage. 15 refs., 37 tabs., 6 figs

Automated Prediction of Catalytic Mechanism and Rate Law Using Graph-Based Reaction Path Sampling.

Science.gov (United States)

Habershon, Scott

2016-04-12

In a recent article [ J. Chem. Phys. 2015 , 143 , 094106 ], we introduced a novel graph-based sampling scheme which can be used to generate chemical reaction paths in many-atom systems in an efficient and highly automated manner. The main goal of this work is to demonstrate how this approach, when combined with direct kinetic modeling, can be used to determine the mechanism and phenomenological rate law of a complex catalytic cycle, namely cobalt-catalyzed hydroformylation of ethene. Our graph-based sampling scheme generates 31 unique chemical products and 32 unique chemical reaction pathways; these sampled structures and reaction paths enable automated construction of a kinetic network model of the catalytic system when combined with density functional theory (DFT) calculations of free energies and resultant transition-state theory rate constants. Direct simulations of this kinetic network across a range of initial reactant concentrations enables determination of both the reaction mechanism and the associated rate law in an automated fashion, without the need for either presupposing a mechanism or making steady-state approximations in kinetic analysis. Most importantly, we find that the reaction mechanism which emerges from these simulations is exactly that originally proposed by Heck and Breslow; furthermore, the simulated rate law is also consistent with previous experimental and computational studies, exhibiting a complex dependence on carbon monoxide pressure. While the inherent errors of using DFT simulations to model chemical reactivity limit the quantitative accuracy of our calculated rates, this work confirms that our automated simulation strategy enables direct analysis of catalytic mechanisms from first principles.

Modelling of the change in national exchange rate model depending on the economic parameters of a natural gas cogeneration system: Turkey case

International Nuclear Information System (INIS)

Inan, Aslan; Izgi, Ercan; Ay, Selim

2009-01-01

In this paper, to what extent a cogeneration system's fixed and variable costs and profits are affected from the exchange rate model implemented in the country is examined. An autoproductor system, as known, uses a part of its electrical energy production for its own requirements while selling the remaining energy to the regional energy corporation. As a function of the load factor and the fuel cost, the production cost and energy sale income of the system are influenced much by the exchange rate model of the country. A cost analysis of a natural gas cogeneration (autoproductor) system has been performed for the numerical application, based on the monetary program supported by the IMF commenced in January 2000. In order to investigate the effect of the change in exchange rate model (introducing the floating exchange rate model) on the fuel cost, both the characteristics of the IMF program and some various forecasting methods have been utilized

Inverse modelling of radionuclide release rates using gamma dose rate observations

Science.gov (United States)

Hamburger, Thomas; Evangeliou, Nikolaos; Stohl, Andreas; von Haustein, Christoph; Thummerer, Severin; Wallner, Christian

2015-04-01

Severe accidents in nuclear power plants such as the historical accident in Chernobyl 1986 or the more recent disaster in the Fukushima Dai-ichi nuclear power plant in 2011 have drastic impacts on the population and environment. Observations and dispersion modelling of the released radionuclides help to assess the regional impact of such nuclear accidents. Modelling the increase of regional radionuclide activity concentrations, which results from nuclear accidents, underlies a multiplicity of uncertainties. One of the most significant uncertainties is the estimation of the source term. That is, the time dependent quantification of the released spectrum of radionuclides during the course of the nuclear accident. The quantification of the source term may either remain uncertain (e.g. Chernobyl, Devell et al., 1995) or rely on estimates given by the operators of the nuclear power plant. Precise measurements are mostly missing due to practical limitations during the accident. The release rates of radionuclides at the accident site can be estimated using inverse modelling (Davoine and Bocquet, 2007). The accuracy of the method depends amongst others on the availability, reliability and the resolution in time and space of the used observations. Radionuclide activity concentrations are observed on a relatively sparse grid and the temporal resolution of available data may be low within the order of hours or a day. Gamma dose rates, on the other hand, are observed routinely on a much denser grid and higher temporal resolution and provide therefore a wider basis for inverse modelling (Saunier et al., 2013). We present a new inversion approach, which combines an atmospheric dispersion model and observations of radionuclide activity concentrations and gamma dose rates to obtain the source term of radionuclides. We use the Lagrangian particle dispersion model FLEXPART (Stohl et al., 1998; Stohl et al., 2005) to model the atmospheric transport of the released radionuclides. The

Validity of observer ratings of the five-factor model of personality traits: a meta-analysis.

Science.gov (United States)

Oh, In-Sue; Wang, Gang; Mount, Michael K

2011-07-01

Conclusions reached in previous research about the magnitude and nature of personality-performance linkages have been based almost exclusively on self-report measures of personality. The purpose of this study is to address this void in the literature by conducting a meta-analysis of the relationship between observer ratings of the five-factor model (FFM) personality traits and overall job performance. Our results show that the operational validities of FFM traits based on observer ratings are higher than those based on self-report ratings. In addition, the results show that when based on observer ratings, all FFM traits are significant predictors of overall performance. Further, observer ratings of FFM traits show meaningful incremental validity over self-reports of corresponding FFM traits in predicting overall performance, but the reverse is not true. We conclude that the validity of FFM traits in predicting overall performance is higher than previously believed, and our results underscore the importance of disentangling the validity of personality traits from the method of measurement of the traits.

Model-Based Knowing: How Do Students Ground Their Understanding About Climate Systems in Agent-Based Computer Models?

Science.gov (United States)

Markauskaite, Lina; Kelly, Nick; Jacobson, Michael J.

2017-12-01

This paper gives a grounded cognition account of model-based learning of complex scientific knowledge related to socio-scientific issues, such as climate change. It draws on the results from a study of high school students learning about the carbon cycle through computational agent-based models and investigates two questions: First, how do students ground their understanding about the phenomenon when they learn and solve problems with computer models? Second, what are common sources of mistakes in students' reasoning with computer models? Results show that students ground their understanding in computer models in five ways: direct observation, straight abstraction, generalisation, conceptualisation, and extension. Students also incorporate into their reasoning their knowledge and experiences that extend beyond phenomena represented in the models, such as attitudes about unsustainable carbon emission rates, human agency, external events, and the nature of computational models. The most common difficulties of the students relate to seeing the modelled scientific phenomenon and connecting results from the observations with other experiences and understandings about the phenomenon in the outside world. An important contribution of this study is the constructed coding scheme for establishing different ways of grounding, which helps to understand some challenges that students encounter when they learn about complex phenomena with agent-based computer models.

Staff background paper on performance-based rate making

International Nuclear Information System (INIS)

Fraser, J.; Brownell, B.

1998-10-01

An alternative to the traditional cost of service (COS) regulation for electric utilities in British Columbia has been proposed. The alternative to pure COS regulation is performance-based rate making (PBR). PBR partially decouples a utility's rates from its costs and ties utility profits to performance relative to specific benchmarks. The motivation underlying PBR is that ideally, it provides incentives for utilities to cost-effectively achieve pre-defined goals. This report describes the design of PBR mechanisms, base rate PBR formulas, base rate PBR in other jurisdictions including New York, California, Maine and New Jersey. The report also describes gas procurement PBR in other jurisdictions, as well as British Columbia Utilities' Commission's own experience with PBR. In general, PBR has the potential to provide resource efficiency, allocative efficiency, support for introduction of new services, and reduced regulatory administrative costs. 15 refs., 4 tabs

A Minimalistic Resource Allocation Model to Explain Ubiquitous Increase in Protein Expression with Growth Rate.

Directory of Open Access Journals (Sweden)

Uri Barenholz

Full Text Available Most proteins show changes in level across growth conditions. Many of these changes seem to be coordinated with the specific growth rate rather than the growth environment or the protein function. Although cellular growth rates, gene expression levels and gene regulation have been at the center of biological research for decades, there are only a few models giving a base line prediction of the dependence of the proteome fraction occupied by a gene with the specific growth rate. We present a simple model that predicts a widely coordinated increase in the fraction of many proteins out of the proteome, proportionally with the growth rate. The model reveals how passive redistribution of resources, due to active regulation of only a few proteins, can have proteome wide effects that are quantitatively predictable. Our model provides a potential explanation for why and how such a coordinated response of a large fraction of the proteome to the specific growth rate arises under different environmental conditions. The simplicity of our model can also be useful by serving as a baseline null hypothesis in the search for active regulation. We exemplify the usage of the model by analyzing the relationship between growth rate and proteome composition for the model microorganism E.coli as reflected in recent proteomics data sets spanning various growth conditions. We find that the fraction out of the proteome of a large number of proteins, and from different cellular processes, increases proportionally with the growth rate. Notably, ribosomal proteins, which have been previously reported to increase in fraction with growth rate, are only a small part of this group of proteins. We suggest that, although the fractions of many proteins change with the growth rate, such changes may be partially driven by a global effect, not necessarily requiring specific cellular control mechanisms.

Analytical Modeling of the High Strain Rate Deformation of Polymer Matrix Composites

Science.gov (United States)

Goldberg, Robert K.; Roberts, Gary D.; Gilat, Amos

2003-01-01

The results presented here are part of an ongoing research program to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to high strain rate impact loads. State variable constitutive equations originally developed for metals have been modified in order to model the nonlinear, strain rate dependent deformation of polymeric matrix materials. To account for the effects of hydrostatic stresses, which are significant in polymers, the classical 5 plasticity theory definitions of effective stress and effective plastic strain are modified by applying variations of the Drucker-Prager yield criterion. To verify the revised formulation, the shear and tensile deformation of a representative toughened epoxy is analyzed across a wide range of strain rates (from quasi-static to high strain rates) and the results are compared to experimentally obtained values. For the analyzed polymers, both the tensile and shear stress-strain curves computed using the analytical model correlate well with values obtained through experimental tests. The polymer constitutive equations are implemented within a strength of materials based micromechanics method to predict the nonlinear, strain rate dependent deformation of polymer matrix composites. In the micromechanics, the unit cell is divided up into a number of independently analyzed slices, and laminate theory is then applied to obtain the effective deformation of the unit cell. The composite mechanics are verified by analyzing the deformation of a representative polymer matrix composite (composed using the representative polymer analyzed for the correlation of the polymer constitutive equations) for several fiber orientation angles across a variety of strain rates. The computed values compare favorably to experimentally obtained results.

Cybernetic modeling based on pathway analysis for Penicillium chrysogenum fed-batch fermentation.

Science.gov (United States)

Geng, Jun; Yuan, Jingqi

2010-08-01

A macrokinetic model employing cybernetic methodology is proposed to describe mycelium growth and penicillin production. Based on the primordial and complete metabolic network of Penicillium chrysogenum found in the literature, the modeling procedure is guided by metabolic flux analysis and cybernetic modeling framework. The abstracted cybernetic model describes the transients of the consumption rates of the substrates, the assimilation rates of intermediates, the biomass growth rate, as well as the penicillin formation rate. Combined with the bioreactor model, these reaction rates are linked with the most important state variables, i.e., mycelium, substrate and product concentrations. Simplex method is used to estimate the sensitive parameters of the model. Finally, validation of the model is carried out with 20 batches of industrial-scale penicillin cultivation.

A Contribution to Nyquist-Rate ADC Modeling - Detailed Algorithm Description

Directory of Open Access Journals (Sweden)

J. Zidek

2012-04-01

Full Text Available In this article, the innovative ADC modeling algorithm is described. It is well suitable for nyquist-rate ADC error back annotation. This algorithm is the next step of building a support tool for IC design engineers. The inspiration for us was the work [2]. Here, the ADC behavior is divided into HCF (High Code Frequency and LCF (Low Code Frequency separated independent parts. This paper is based on the same concept but the model coefficients are estimated in a different way only from INL data. The HCF order recognition part was newly added as well. Thanks to that the HCF coefficients number is lower in comparison with the original Grimaldi’s work (especially for converters with low ratio between HCF and “random” part of INL. Modeling results are demonstrated on a real data set measured by ASICentrum on chargeredistribution type SAR ADC chip. Results are showed not only by coefficient values but also by the Model Coverage metrics. Model limitations are also discussed.

EXCHANGE-RATES FORECASTING: EXPONENTIAL SMOOTHING TECHNIQUES AND ARIMA MODELS

Directory of Open Access Journals (Sweden)

Dezsi Eva

2011-07-01

Full Text Available Exchange rates forecasting is, and has been a challenging task in finance. Statistical and econometrical models are widely used in analysis and forecasting of foreign exchange rates. This paper investigates the behavior of daily exchange rates of the Romanian Leu against the Euro, United States Dollar, British Pound, Japanese Yen, Chinese Renminbi and the Russian Ruble. Smoothing techniques are generated and compared with each other. These models include the Simple Exponential Smoothing technique, as the Double Exponential Smoothing technique, the Simple Holt-Winters, the Additive Holt-Winters, namely the Autoregressive Integrated Moving Average model.

A simulation model for the determination of tabarru' rate in a family takaful

Science.gov (United States)

Ismail, Hamizun bin

2014-06-01

The concept of tabarru' that is incorporated in family takaful serves to eliminate the element of uncertainty in the contract as a participant agree to relinquish as donation certain portion of his contribution. The most important feature in family takaful is that it does not guarantee a definite return on a participant's contribution, unlike its conventional counterpart where a premium is paid in return for a guaranteed amount of insurance benefit. In other words, investment return on contributed funds by the participants are based on actual investment experience. The objective of this study is to set up a framework for the determination of tabarru' rate by simulation. The model is based on binomial death process. Specifically, linear tabarru' rate and flat tabarru' rate are introduced. The results of the simulation trials show that the linear assumption on the tabarru' rate has an advantage over the flat counterpart as far as the risk of the investment accumulation on maturity is concerned.

Dose rate effect models for biological reaction to ionizing radiation in human cell lines

International Nuclear Information System (INIS)

Magae, Junji; Ogata, Hiromitsu

2008-01-01

, suggesting that dose rate effect predicted by MOE model is dependent on DNA repair system. Dose rate effect in a resting normal fibroblast cultured in serum-depleted medium also followed MOE model. In contrast, dose-rate effect was observed in these cell lines deficient of DNA repair system, when they were cultured for more than several month. This dose rate effect did not fit MOE model, and followed a model based on elimination of damaged cells. In conclusion, dose rate effect in growth inhibition and micronucleus formation in cultured cell lines is dependent on dose rate and irradiation time: In higher range of dose rates and short irradiation time, biological effect is determined by dose but not dose rate, and dose rate effect is not observed. In middle range of dose rates and irradiation time, dose rate effect is dependent on DNA repair system, and follows MOE model. In low range of dose-rates and irradiation time longer than several months, dose rate effect is mainly dependent on elimination of damaged cells, and biological effect is determined by dose rate rather than total dose. Our results suggest that dose rate and irradiation time should be included in estimation of long-term radiation risk at low dose rates. (author)

Discounted cost model for condition-based maintenance optimization

International Nuclear Information System (INIS)

Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van

2010-01-01

This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.

On Optimizing H. 264/AVC Rate Control by Improving R-D Model and Incorporating HVS Characteristics

Directory of Open Access Journals (Sweden)

Jiang Gangyi

2010-01-01

Full Text Available The state-of-the-art JVT-G012 rate control algorithm of H.264 is improved from two aspects. First, the quadratic rate-distortion (R-D model is modified based on both empirical observations and theoretical analysis. Second, based on the existing physiological and psychological research findings of human vision, the rate control algorithm is optimized by incorporating the main characteristics of the human visual system (HVS such as contrast sensitivity, multichannel theory, and masking effect. Experiments are conducted, and experimental results show that the improved algorithm can simultaneously enhance the overall subjective visual quality and improve the rate control precision effectively.

Monetary models and exchange rate determination: The Nigerian ...

African Journals Online (AJOL)

Monetary models and exchange rate determination: The Nigerian evidence. ... income levels and real interest rate differentials provide better forecasts of the ... partner can expect to suffer depreciation in the external value of her currency.

Attaining the rate-independent limit of a rate-dependent strain gradient plasticity theory

DEFF Research Database (Denmark)

El-Naaman, Salim Abdallah; Nielsen, Kim Lau; Niordson, Christian Frithiof

2016-01-01

The existence of characteristic strain rates in rate-dependent material models, corresponding to rate-independent model behavior, is studied within a back stress based rate-dependent higher order strain gradient crystal plasticity model. Such characteristic rates have recently been observed...... for steady-state processes, and the present study aims to demonstrate that the observations in fact unearth a more widespread phenomenon. In this work, two newly proposed back stress formulations are adopted to account for the strain gradient effects in the single slip simple shear case, and characteristic...... rates for a selected quantity are identified through numerical analysis. Evidently, the concept of a characteristic rate, within the rate-dependent material models, may help unlock an otherwise inaccessible parameter space....

Modeling baroreflex regulation of heart rate during orthostatic stress

DEFF Research Database (Denmark)

Olufsen, Mette; Tran, Hien T.; Ottesen, Johnny T.

2006-01-01

. The model uses blood pressure measured in the finger as an input to model heart rate dynamics in response to changes in baroreceptor nerve firing rate, sympathetic and parasympathetic responses, vestibulo-sympathetic reflex, and concentrations of norepinephrine and acetylcholine. We formulate an inverse...... in healthy and hypertensive elderly people the hysteresis loop shifts to higher blood pressure values and its area is diminished. Finally, for hypertensive elderly people the hysteresis loop is generally not closed indicating that during postural change from sitting to standing, the blood pressure resettles......During orthostatic stress, arterial and cardiopulmonary baroreflexes play a key role in maintaining arterial pressure by regulating heart rate. This study, presents a mathematical model that can predict the dynamics of heart rate regulation in response to postural change from sitting to standing...

Three-dimensional modeling for deformation of austenitic NiTi shape memory alloys under high strain rate

Science.gov (United States)

Yu, Hao; Young, Marcus L.

2018-01-01

A three-dimensional model for phase transformation of shape memory alloys (SMAs) during high strain rate deformation is developed and is then calibrated based on experimental results from an austenitic NiTi SMA. Stress, strain, and martensitic volume fraction distribution during high strain rate deformation are simulated using finite element analysis software ABAQUS/standard. For the first time, this paper presents a theoretical study of the microscopic band structure during high strain rate compressive deformation. The microscopic transformation band is generated by the phase front and leads to minor fluctuations in sample deformation. The strain rate effect on phase transformation is studied using the model. Both the starting stress for transformation and the slope of the stress-strain curve during phase transformation increase with increasing strain rate.

The Prediction of Exchange Rates with the Use of Auto-Regressive Integrated Moving-Average Models

Directory of Open Access Journals (Sweden)

Daniela Spiesová

2014-10-01

Full Text Available Currency market is recently the largest world market during the existence of which there have been many theories regarding the prediction of the development of exchange rates based on macroeconomic, microeconomic, statistic and other models. The aim of this paper is to identify the adequate model for the prediction of non-stationary time series of exchange rates and then use this model to predict the trend of the development of European currencies against Euro. The uniqueness of this paper is in the fact that there are many expert studies dealing with the prediction of the currency pairs rates of the American dollar with other currency but there is only a limited number of scientific studies concerned with the long-term prediction of European currencies with the help of the integrated ARMA models even though the development of exchange rates has a crucial impact on all levels of economy and its prediction is an important indicator for individual countries, banks, companies and businessmen as well as for investors. The results of this study confirm that to predict the conditional variance and then to estimate the future values of exchange rates, it is adequate to use the ARIMA (1,1,1 model without constant, or ARIMA [(1,7,1,(1,7] model, where in the long-term, the square root of the conditional variance inclines towards stable value.

Modeling oil production based on symbolic regression

International Nuclear Information System (INIS)

Yang, Guangfei; Li, Xianneng; Wang, Jianliang; Lian, Lian; Ma, Tieju

2015-01-01

Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak

Decision-case mix model for analyzing variation in cesarean rates.

Science.gov (United States)

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

Probabilistic Modeling of the Fatigue Crack Growth Rate for Ni-base Alloy X-750

International Nuclear Information System (INIS)

Yoon, J.Y.; Nam, H.O.; Hwang, I.S.; Lee, T.H.

2012-01-01

Extending the operating life of existing nuclear power plants (NPP's) beyond 60 years. Many aging problems of passive components such as PWSCC, IASCC, FAC and Corrosion Fatigue; Safety analysis: Deterministic analysis + Probabilistic analysis; Many uncertainties of parameters or relationship in general probabilistic analysis such as probabilistic safety assessment (PSA); Bayesian inference: Decreasing uncertainties by updating unknown parameter; Ensuring the reliability of passive components (e.g. pipes) as well as active components (e.g. valve, pump) in NPP's; Developing probabilistic model for failures; Updating the fatigue crack growth rate (FCGR)

Stage-discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin

OpenAIRE

Paris, Adrien; Dias de Paiva, Rodrigo; Santos da Silva, Joecila; Medeiros Moreira, Daniel; Calmant, Stephane; Garambois, Pierre-André; Collischonn, Walter; Bonnet, Marie-Paule; Seyler, Frederique

2016-01-01

In this study, rating curves (RCs) were determined by applying satellite altimetry to a poorly gauged basin. This study demonstrates the synergistic application of remote sensing and watershed modeling to capture the dynamics and quantity of flow in the Amazon River Basin, respectively. Three major advancements for estimating basin-scale patterns in river discharge are described. The first advancement is the preservation of the hydrological meanings of the parameters expressed by ...

Arduino-based noise robust online heart-rate detection.

Science.gov (United States)

Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

2017-04-01

This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

Success rate evaluation of clinical governance implementation in teaching hospitals in Kerman (Iran) based on nine steps of Karsh's model.

Science.gov (United States)

Vali, Leila; Mastaneh, Zahra; Mouseli, Ali; Kardanmoghadam, Vida; Kamali, Sodabeh

2017-07-01

One of the ways to improve the quality of services in the health system is through clinical governance. This method aims to create a framework for clinical services providers to be accountable in return for continuing improvement of quality and maintaining standards of services. To evaluate the success rate of clinical governance implementation in Kerman teaching hospitals based on 9 steps of Karsh's Model. This cross-sectional study was conducted in 2015 on 94 people including chief executive officers (CEOs), nursing managers, clinical governance managers and experts, head nurses and nurses. The required data were collected through a researcher-made questionnaire containing 38 questions with three-point Likert Scale (good, moderate, and weak). The Karsh's Model consists of nine steps including top management commitment to change, accountability for change, creating a structured approach for change, training, pilot implementation, communication, feedback, simulation, and end-user participation. Data analysis using descriptive statistics and Mann-Whitney-Wilcoxon test was done by SPSS software version 16. About 81.9 % of respondents were female and 74.5 have a Bachelor of Nursing (BN) degree. In general, the status of clinical governance implementation in studied hospitals based on 9 steps of the model was 44 % (moderate). A significant relationship was observed among accountability and organizational position (p=0.0012) and field of study (p=0.000). Also, there were significant relationships between structure-based approach and organizational position (p=0.007), communication and demographic characteristics (p=0.000), and end-user participation with organizational position (p=0.03). Clinical governance should be implemented by correct needs assessment and participation of all stakeholders, to ensure its enforcement in practice, and to enhance the quality of services.

The Influence of Base Rate and Case Information on Health-Risk Perceptions: A Unified Model of Self-Positivity and Self-Negativity

OpenAIRE

Dengfeng Yan; Jaideep Sengupta

2013-01-01

This research examines how consumers use base rate (e.g., disease prevalence in a population) and case information (e.g., an individual's disease symptoms) to estimate health risks. Drawing on construal level theory, we propose that consumers' reliance on base rate (case information) will be enhanced (weakened) by psychological distance. A corollary of this premise is that self-positivity (i.e., underestimating self-risk vs. other-risk) is likely when the disease base rate is high but the cas...

Empirical rate equation model and rate calculations of hydrogen generation for Hanford tank waste

International Nuclear Information System (INIS)

HU, T.A.

1999-01-01

Empirical rate equations are derived to estimate hydrogen generation based on chemical reactions, radiolysis of water and organic compounds, and corrosion processes. A comparison of the generation rates observed in the field with the rates calculated for twenty eight tanks shows agreement within a factor of two to three

Modeling study on the effects of pulse rise rate in atmospheric pulsed discharges

Science.gov (United States)

Zhang, Yuan-Tao; Wang, Yan-Hui

2018-02-01

In this paper, we present a modeling study on the discharge characteristics driven by short pulsed voltages, focusing on the effects of pulse rise rate based on the fluid description of atmospheric plasmas. The numerical results show that the breakdown voltage of short pulsed discharge is almost linearly dependent on the pulse rise rate, which is also confirmed by the derived equations from the fluid model. In other words, if the pulse rise rate is fixed as a constant, the simulation results clearly suggest that the breakdown voltage is almost unchanged, although the amplitude of pulsed voltage increases significantly. The spatial distribution of the electric field and electron density are given to reveal the underpinning physics. Additionally, the computational data and the analytical expression also indicate that an increased repetition frequency can effectively decrease the breakdown voltage and current density, which is consistent with the experimental observation.

Uncertainty estimation with bias-correction for flow series based on rating curve

Science.gov (United States)

Shao, Quanxi; Lerat, Julien; Podger, Geoff; Dutta, Dushmanta

2014-03-01

Streamflow discharge constitutes one of the fundamental data required to perform water balance studies and develop hydrological models. A rating curve, designed based on a series of concurrent stage and discharge measurements at a gauging location, provides a way to generate complete discharge time series with a reasonable quality if sufficient measurement points are available. However, the associated uncertainty is frequently not available even though it has a significant impact on hydrological modelling. In this paper, we identify the discrepancy of the hydrographers' rating curves used to derive the historical discharge data series and proposed a modification by bias correction which is also in the form of power function as the traditional rating curve. In order to obtain the uncertainty estimation, we propose a further both-side Box-Cox transformation to stabilize the regression residuals as close to the normal distribution as possible, so that a proper uncertainty can be attached for the whole discharge series in the ensemble generation. We demonstrate the proposed method by applying it to the gauging stations in the Flinders and Gilbert rivers in north-west Queensland, Australia.

BIM-Based Decision Support System for Material Selection Based on Supplier Rating

Directory of Open Access Journals (Sweden)

Abiola Akanmu

2015-12-01

Full Text Available Material selection is a delicate process, typically hinged on a number of factors which can be either cost or environmental related. This process becomes more complicated when designers are faced with several material options of building elements and each option can be supplied by different suppliers whose selection criteria may affect the budgetary and environmental requirements of the project. This paper presents the development of a decision support system based on the integration of building information models, a modified harmony search algorithm and supplier performance rating. The system is capable of producing the cost and environmental implications of different material combinations or building designs. A case study is presented to illustrate the functionality of the developed system.

Leak rate models and leak detection

International Nuclear Information System (INIS)

1992-01-01

Leak detection may be carried out by a number of detection systems, but selection of the systems must be carefully adapted to the fluid state and the location of the leak in the reactor coolant system. Computer programs for the calculation of leak rates contain different models to take into account the fluid state before its entrance into the crack, and they have to be verified by experiments; agreement between experiments and calculations is generally not satisfactory for very small leak rates resulting from narrow cracks or from a closing bending moment

Particle-based model for skiing traffic.

Science.gov (United States)

Holleczek, Thomas; Tröster, Gerhard

2012-05-01

We develop and investigate a particle-based model for ski slope traffic. Skiers are modeled as particles with a mass that are exposed to social and physical forces, which define the riding behavior of skiers during their descents on ski slopes. We also report position and speed data of 21 skiers recorded with GPS-equipped cell phones on two ski slopes. A comparison of these data with the trajectories resulting from computer simulations of our model shows a good correspondence. A study of the relationship among the density, speed, and flow of skiers reveals that congestion does not occur even with arrival rates of skiers exceeding the maximum ski lift capacity. In a sensitivity analysis, we identify the kinetic friction coefficient of skis on snow, the skier mass, the range of repelling social forces, and the arrival rate of skiers as the crucial parameters influencing the simulation results. Our model allows for the prediction of speed zones and skier densities on ski slopes, which is important in the prevention of skiing accidents.

Statistical inference, the bootstrap, and neural-network modeling with application to foreign exchange rates.

Science.gov (United States)

White, H; Racine, J

2001-01-01

We propose tests for individual and joint irrelevance of network inputs. Such tests can be used to determine whether an input or group of inputs "belong" in a particular model, thus permitting valid statistical inference based on estimated feedforward neural-network models. The approaches employ well-known statistical resampling techniques. We conduct a small Monte Carlo experiment showing that our tests have reasonable level and power behavior, and we apply our methods to examine whether there are predictable regularities in foreign exchange rates. We find that exchange rates do appear to contain information that is exploitable for enhanced point prediction, but the nature of the predictive relations evolves through time.

Identifiability of altimetry-based rating curve parameters in function of river morphological parameters

Science.gov (United States)

Paris, Adrien; André Garambois, Pierre; Calmant, Stéphane; Paiva, Rodrigo; Walter, Collischonn; Santos da Silva, Joecila; Medeiros Moreira, Daniel; Bonnet, Marie-Paule; Seyler, Frédérique; Monnier, Jérôme

2016-04-01

Estimating river discharge for ungauged river reaches from satellite measurements is not straightforward given the nonlinearity of flow behavior with respect to measurable and non measurable hydraulic parameters. As a matter of facts, current satellite datasets do not give access to key parameters such as river bed topography and roughness. A unique set of almost one thousand altimetry-based rating curves was built by fit of ENVISAT and Jason-2 water stages with discharges obtained from the MGB-IPH rainfall-runoff model in the Amazon basin. These rated discharges were successfully validated towards simulated discharges (Ens = 0.70) and in-situ discharges (Ens = 0.71) and are not mission-dependent. The rating curve writes Q = a(Z-Z0)b*sqrt(S), with Z the water surface elevation and S its slope gained from satellite altimetry, a and b power law coefficient and exponent and Z0 the river bed elevation such as Q(Z0) = 0. For several river reaches in the Amazon basin where ADCP measurements are available, the Z0 values are fairly well validated with a relative error lower than 10%. The present contribution aims at relating the identifiability and the physical meaning of a, b and Z0given various hydraulic and geomorphologic conditions. Synthetic river bathymetries sampling a wide range of rivers and inflow discharges are used to perform twin experiments. A shallow water model is run for generating synthetic satellite observations, and then rating curve parameters are determined for each river section thanks to a MCMC algorithm. Thanks to twin experiments, it is shown that rating curve formulation with water surface slope, i.e. closer from Manning equation form, improves parameter identifiability. The compensation between parameters is limited, especially for reaches with little water surface variability. Rating curve parameters are analyzed for riffle and pools for small to large rivers, different river slopes and cross section shapes. It is shown that the river bed

PSA-based evaluation and rating of operational events

International Nuclear Information System (INIS)

Gomez Cobo, A.

1997-01-01

The presentation discusses the PSA-based evaluation and rating of operational events, including the following: historical background, procedures for event evaluation using PSA, use of PSA for event rating, current activities

Estimating Rates of Permafrost Degradation and their Impact on Ecosystems across Alaska and Northwest Canada using the Process-based Permafrost Dynamics Model GIPL as a Component of the Integrated Ecosystem Model (IEM)

Science.gov (United States)

Marchenko, S. S.; Genet, H.; Euskirchen, E. S.; Breen, A. L.; McGuire, A. D.; Rupp, S. T.; Romanovsky, V. E.; Bolton, W. R.; Walsh, J. E.

2016-12-01

The impact of climate warming on permafrost and the potential of climate feedbacks resulting from permafrost thawing have recently received a great deal of attention. Permafrost temperature has increased in most locations in the Arctic and Sub-Arctic during the past 30-40 years. The typical increase in permafrost temperature is 1-3°C. The process-based permafrost dynamics model GIPL developed in the Geophysical Institute Permafrost Lab, and which is the permafrost module of the Integrated Ecosystem Model (IEM) has been using to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4fluxes and net C storage following permafrost thaw across Alaska and Northwest Canada. The IEM project is a multi-institutional and multi-disciplinary effort aimed at understanding potential landscape, habitat and ecosystem change across the IEM domain. The IEM project also aims to tie three scientific models together Terrestrial Ecosystem Model (TEM), the ALFRESCO (ALaska FRame-based EcoSystem Code) and GIPL so that they exchange data at run-time. The models produce forecasts of future fire, vegetation, organic matter, permafrost and hydrology regimes. The climate forcing data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the CMIP3 CCCMA-CGCM3.1 and MPI-ECHAM5/MPI-OM climate models for the future period (2009-2100). All data sets were downscaled to a 1 km resolution, using a differencing methodology (i.e., a delta method) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of thawed soils across the IEM domain. The modeling results indicate how different types of ecosystems affect the thermal state of permafrost and its stability. Although the rate of soil warming and permafrost degradation in peatland areas are slower than

Mechanical strength model for plastic bonded granular materials at high strain rates and large strains

International Nuclear Information System (INIS)

Browning, R.V.; Scammon, R.J.

1998-01-01

Modeling impact events on systems containing plastic bonded explosive materials requires accurate models for stress evolution at high strain rates out to large strains. For example, in the Steven test geometry reactions occur after strains of 0.5 or more are reached for PBX-9501. The morphology of this class of materials and properties of the constituents are briefly described. We then review the viscoelastic behavior observed at small strains for this class of material, and evaluate large strain models used for granular materials such as cap models. Dilatation under shearing deformations of the PBX is experimentally observed and is one of the key features modeled in cap style plasticity theories, together with bulk plastic flow at high pressures. We propose a model that combines viscoelastic behavior at small strains but adds intergranular stresses at larger strains. A procedure using numerical simulations and comparisons with results from flyer plate tests and low rate uniaxial stress tests is used to develop a rough set of constants for PBX-9501. Comparisons with the high rate flyer plate tests demonstrate that the observed characteristic behavior is captured by this viscoelastic based model. copyright 1998 American Institute of Physics

Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

Directory of Open Access Journals (Sweden)

Cunwu Han

2014-01-01

Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.

A model for C-14 tracer evaporative rate analysis (ERA)

International Nuclear Information System (INIS)

Gardner, R.P.; Verghese, K.

1993-01-01

A simple model has been derived and tested for the C-14 tracer evaporative rate analysis (ERA) method. It allows the accurate determination of the evaporative rate coefficient of the C-14 tracer detector in the presence of variable evaporation rates of the detector solvent and variable background counting rates. The evaporation rate coefficient should be the most fundamental parameter available in this analysis method and, therefore, its measurements with the proposed model should allow the most direct correlations to be made with the system properties of interest such as surface cleanliness. (author)

Mechanism of Strain Rate Effect Based on Dislocation Theory

International Nuclear Information System (INIS)

Kun, Qin; Shi-Sheng, Hu; Li-Ming, Yang

2009-01-01

Based on dislocation theory, we investigate the mechanism of strain rate effect. Strain rate effect and dislocation motion are bridged by Orowan's relationship, and the stress dependence of dislocation velocity is considered as the dynamics relationship of dislocation motion. The mechanism of strain rate effect is then investigated qualitatively by using these two relationships although the kinematics relationship of dislocation motion is absent due to complicated styles of dislocation motion. The process of strain rate effect is interpreted and some details of strain rate effect are adequately discussed. The present analyses agree with the existing experimental results. Based on the analyses, we propose that strain rate criteria rather than stress criteria should be satisfied when a metal is fully yielded at a given strain rate. (condensed matter: structure, mechanical and thermal properties)

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

Directory of Open Access Journals (Sweden)

Laila A. Puntel

2018-04-01

Full Text Available Historically crop models have been used to evaluate crop yield responses to nitrogen (N rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1 evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages; (2 determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3 quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77 using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81. Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively. At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR in 62% of the cases examined (n = 31 with an average error range of ±38 kg N ha−1 (22% of the average N rate. Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

Science.gov (United States)

Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Thorburn, Peter J.; Castellano, Michael J.; Moore, Kenneth J.; VanLoocke, Andrew; Heaton, Emily A.; Archontoulis, Sotirios V.

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate.

Science.gov (United States)

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Thorburn, Peter J; Castellano, Michael J; Moore, Kenneth J; VanLoocke, Andrew; Heaton, Emily A; Archontoulis, Sotirios V

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time ( R 2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity ( R 2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined ( n = 31) with an average error range of ±38 kg N ha -1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather

Parameter estimations in predictive microbiology: Statistically sound modelling of the microbial growth rate.

Science.gov (United States)

Akkermans, Simen; Logist, Filip; Van Impe, Jan F

2018-04-01

When building models to describe the effect of environmental conditions on the microbial growth rate, parameter estimations can be performed either with a one-step method, i.e., directly on the cell density measurements, or in a two-step method, i.e., via the estimated growth rates. The two-step method is often preferred due to its simplicity. The current research demonstrates that the two-step method is, however, only valid if the correct data transformation is applied and a strict experimental protocol is followed for all experiments. Based on a simulation study and a mathematical derivation, it was demonstrated that the logarithm of the growth rate should be used as a variance stabilizing transformation. Moreover, the one-step method leads to a more accurate estimation of the model parameters and a better approximation of the confidence intervals on the estimated parameters. Therefore, the one-step method is preferred and the two-step method should be avoided. Copyright © 2017. Published by Elsevier Ltd.

SCS-CN based time-distributed sediment yield model

Science.gov (United States)

Tyagi, J. V.; Mishra, S. K.; Singh, Ranvir; Singh, V. P.

2008-05-01

SummaryA sediment yield model is developed to estimate the temporal rates of sediment yield from rainfall events on natural watersheds. The model utilizes the SCS-CN based infiltration model for computation of rainfall-excess rate, and the SCS-CN-inspired proportionality concept for computation of sediment-excess. For computation of sedimentographs, the sediment-excess is routed to the watershed outlet using a single linear reservoir technique. Analytical development of the model shows the ratio of the potential maximum erosion (A) to the potential maximum retention (S) of the SCS-CN method is constant for a watershed. The model is calibrated and validated on a number of events using the data of seven watersheds from India and the USA. Representative values of the A/S ratio computed for the watersheds from calibration are used for the validation of the model. The encouraging results of the proposed simple four parameter model exhibit its potential in field application.

A Case-Based Learning Model in Orthodontics.

Science.gov (United States)

Engel, Francoise E.; Hendricson, William D.

1994-01-01

A case-based, student-centered instructional model designed to mimic orthodontic problem solving and decision making in dental general practice is described. Small groups of students analyze case data, then record and discuss their diagnoses and treatments. Students and instructors rated the seminars positively, and students reported improved…

Modeling the intracellular pathogen-immune interaction with cure rate

Science.gov (United States)

Dubey, Balram; Dubey, Preeti; Dubey, Uma S.

2016-09-01

Many common and emergent infectious diseases like Influenza, SARS, Hepatitis, Ebola etc. are caused by viral pathogens. These infections can be controlled or prevented by understanding the dynamics of pathogen-immune interaction in vivo. In this paper, interaction of pathogens with uninfected and infected cells in presence or absence of immune response are considered in four different cases. In the first case, the model considers the saturated nonlinear infection rate and linear cure rate without absorption of pathogens into uninfected cells and without immune response. The next model considers the effect of absorption of pathogens into uninfected cells while all other terms are same as in the first case. The third model incorporates innate immune response, humoral immune response and Cytotoxic T lymphocytes (CTL) mediated immune response with cure rate and without absorption of pathogens into uninfected cells. The last model is an extension of the third model in which the effect of absorption of pathogens into uninfected cells has been considered. Positivity and boundedness of solutions are established to ensure the well-posedness of the problem. It has been found that all the four models have two equilibria, namely, pathogen-free equilibrium point and pathogen-present equilibrium point. In each case, stability analysis of each equilibrium point is investigated. Pathogen-free equilibrium is globally asymptotically stable when basic reproduction number is less or equal to unity. This implies that control or prevention of infection is independent of initial concentration of uninfected cells, infected cells, pathogens and immune responses in the body. The proposed models show that introduction of immune response and cure rate strongly affects the stability behavior of the system. Further, on computing basic reproduction number, it has been found to be minimum for the fourth model vis-a-vis other models. The analytical findings of each model have been exemplified by

Improved model for the angular dependence of excimer laser ablation rates in polymer materials

Science.gov (United States)

Pedder, J. E. A.; Holmes, A. S.; Dyer, P. E.

2009-10-01

Measurements of the angle-dependent ablation rates of polymers that have applications in microdevice fabrication are reported. A simple model based on Beer's law, including plume absorption, is shown to give good agreement with the experimental findings for polycarbonate and SU8, ablated using the 193 and 248 nm excimer lasers, respectively. The modeling forms a useful tool for designing masks needed to fabricate complex surface relief by ablation.

A Comprehensive Prediction Model of Hydraulic Extended-Reach Limit Considering the Allowable Range of Drilling Fluid Flow Rate in Horizontal Drilling.

Science.gov (United States)

Li, Xin; Gao, Deli; Chen, Xuyue

2017-06-08

Hydraulic extended-reach limit (HERL) model of horizontal extended-reach well (ERW) can predict the maximum measured depth (MMD) of the horizontal ERW. The HERL refers to the well's MMD when drilling fluid cannot be normally circulated by drilling pump. Previous model analyzed the following two constraint conditions, drilling pump rated pressure and rated power. However, effects of the allowable range of drilling fluid flow rate (Q min  ≤ Q ≤ Q max ) were not considered. In this study, three cases of HERL model are proposed according to the relationship between allowable range of drilling fluid flow rate and rated flow rate of drilling pump (Q r ). A horizontal ERW is analyzed to predict its HERL, especially its horizontal-section limit (L h ). Results show that when Q min  ≤ Q r  ≤ Q max (Case I), L h depends both on horizontal-section limit based on rated pump pressure (L h1 ) and horizontal-section limit based on rated pump power (L h2 ); when Q min  drilling fluid flow rate, while L h2 keeps decreasing as the drilling fluid flow rate increases. The comprehensive model provides a more accurate prediction on HERL.

Structure and sensitivity analysis of individual-based predator–prey models

International Nuclear Information System (INIS)

Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

2012-01-01

The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

Rate Theory Modeling and Simulations of Silicide Fuel at LWR Conditions

Energy Technology Data Exchange (ETDEWEB)

Miao, Yinbin [Argonne National Lab. (ANL), Argonne, IL (United States); Ye, Bei [Argonne National Lab. (ANL), Argonne, IL (United States); Mei, Zhigang [Argonne National Lab. (ANL), Argonne, IL (United States); Hofman, Gerard [Argonne National Lab. (ANL), Argonne, IL (United States); Yacout, Abdellatif [Argonne National Lab. (ANL), Argonne, IL (United States)

2015-12-10

Uranium silicide (U₃Si₂) fuel has higher thermal conductivity and higher uranium density, making it a promising candidate for the accident-tolerant fuel (ATF) used in light water reactors (LWRs). However, previous studies on the fuel performance of U₃Si₂, including both experimental and computational approaches, have been focusing on the irradiation conditions in research reactors, which usually involve low operation temperatures and high fuel burnups. Thus, it is important to examine the fuel performance of U₃Si₂ at typical LWR conditions so as to evaluate the feasibility of replacing conventional uranium dioxide fuel with this silicide fuel material. As in-reactor irradiation experiments involve significant time and financial cost, it is appropriate to utilize modeling tools to estimate the behavior of U₃Si₂ in LWRs based on all those available research reactor experimental references and state-of-the-art density functional theory (DFT) calculation capabilities at the early development stage. Hence, in this report, a comprehensive investigation of the fission gas swelling behavior of U₃Si₂ at LWR conditions is introduced. The modeling efforts mentioned in this report was based on the rate theory (RT) model of fission gas bubble evolution that has been successfully applied for a variety of fuel materials at devious reactor conditions. Both existing experimental data and DFT-calculated results were used for the optimization of the parameters adopted by the RT model. Meanwhile, the fuel-cladding interaction was captured by the coupling of the RT model with simplified mechanical correlations. Therefore, the swelling behavior of U₃Si₂ fuel and its consequent interaction with cladding in LWRs was predicted by the rate theory modeling, providing valuable information for the development of U₃Si₂ fuel as an accident

The Hanford Site's Gable Mountain structure: A comparison of the recurrence of design earthquakes based on fault slip rates and a probabilistic exposure model

International Nuclear Information System (INIS)

Rohay, A.C.

1991-01-01

Gable Mountain is a segment of the Umtanum Ridge-Gable Mountain structural trend, an east-west trending series of anticlines, one of the major geologic structures on the Hanford Site. A probabilistic seismic exposure model indicates that Gable Mountain and two adjacent segments contribute significantly to the seismic hazard at the Hanford Site. Geologic measurements of the uplift of initially horizontal (11-12 Ma) basalt flows indicate that a broad, continuous, primary anticline grew at an average rate of 0.009-0.011 mm/a, and narrow, segmented, secondary anticlines grew at rates of 0.009 mm/a at Gable Butte and 0.018 mm/a at Gable Mountain. The buried Southeast Anticline appears to have a different geometry, consisting of a single, intermediate-width anticline with an estimated growth rate of 0.007 mm/a. The recurrence rate and maximum magnitude of earthquakes for the fault models were used to estimate the fault slip rate for each of the fault models and to determine the implied structural growth rate of the segments. The current model for Gable Mountain-Gable Butte predicts 0.004 mm/a of vertical uplift due to primary faulting and 0.008 mm/a due to secondary faulting. These rates are roughly half the structurally estimated rates for Gable Mountain, but the model does not account for the smaller secondary fold at Gable Butte. The model predicted an uplift rate for the Southeast Anticline of 0.006 mm/a, caused by the low open-quotes fault capabilityclose quotes weighting rather than a different fault geometry. The effects of previous modifications to the fault models are examined and potential future modifications are suggested. For example, the earthquake recurrence relationship used in the current exposure model has a b-value of 1.15, compared to a previous value of 0.85. This increases the implied deformation rates due to secondary fault models, and therefore supports the use of this regionally determined b-value to this fault/fold system

Vapor generation rate model for dispersed drop flow

International Nuclear Information System (INIS)

Unal, C.; Tuzla, K.; Cokmez-Tuzla, A.F.; Chen, J.C.

1991-01-01

A comparison of predictions of existing nonequilibrium post-CHF heat transfer models with the recently obtained rod bundle data has been performed. The models used the experimental conditions and wall temperatures to predict the heat flux and vapor temperatures at the location of interest. No existing model was able to reasonably predict the vapor superheat and the wall heat flux simultaneously. Most of the models, except Chen-Sundaram-Ozkaynak, failed to predict the wall heat flux, while all of the models could not predict the vapor superheat data or trends. A recently developed two-region heat transfer model, the Webb-Chen two-region model, did not give a reasonable prediction of the vapor generation rate in the far field of the CHF point. A new correlation was formulated to predict the vapor generation rate in convective dispersed droplet flow in terms of thermal-hydraulic parameters and thermodynamic properties. A comparison of predictions of the two-region heat transfer model, with the use of a presently developed correlation, with all the existing post-CHF data, including single-tube and rod bundle, showed significant improvements in predicting the vapor superheat and tube wall heat flux trends. (orig.)

Data analysis using the Binomial Failure Rate common cause model

International Nuclear Information System (INIS)

Atwood, C.L.

1983-09-01

This report explains how to use the Binomial Failure Rate (BFR) method to estimate common cause failure rates. The entire method is described, beginning with the conceptual model, and covering practical issues of data preparation, treatment of variation in the failure rates, Bayesian estimation of the quantities of interest, checking the model assumptions for lack of fit to the data, and the ultimate application of the answers

Process-Based Modeling of Constructed Wetlands

Science.gov (United States)

Baechler, S.; Brovelli, A.; Rossi, L.; Barry, D. A.

2007-12-01

Constructed wetlands (CWs) are widespread facilities for wastewater treatment. In subsurface flow wetlands, contaminated wastewater flows through a porous matrix, where oxidation and detoxification phenomena occur. Despite the large number of working CWs, system design and optimization are still mainly based upon empirical equations or simplified first-order kinetics. This results from an incomplete understanding of the system functioning, and may in turn hinder the performance and effectiveness of the treatment process. As a result, CWs are often considered not suitable to meet high water quality-standards, or to treat water contaminated with recalcitrant anthropogenic contaminants. To date, only a limited number of detailed numerical models have been developed and successfully applied to simulate constructed wetland behavior. Among these, one of the most complete and powerful is CW2D, which is based on Hydrus2D. The aim of this work is to develop a comprehensive simulator tailored to model the functioning of horizontal flow constructed wetlands and in turn provide a reliable design and optimization tool. The model is based upon PHWAT, a general reactive transport code for saturated flow. PHWAT couples MODFLOW, MT3DMS and PHREEQC-2 using an operator-splitting approach. The use of PHREEQC to simulate reactions allows great flexibility in simulating biogeochemical processes. The biogeochemical reaction network is similar to that of CW2D, and is based on the Activated Sludge Model (ASM). Kinetic oxidation of carbon sources and nutrient transformations (nitrogen and phosphorous primarily) are modeled via Monod-type kinetic equations. Oxygen dissolution is accounted for via a first-order mass-transfer equation. While the ASM model only includes a limited number of kinetic equations, the new simulator permits incorporation of an unlimited number of both kinetic and equilibrium reactions. Changes in pH, redox potential and surface reactions can be easily incorporated

Constrained convex minimization via model-based excessive gap

OpenAIRE

Tran Dinh, Quoc; Cevher, Volkan

2014-01-01

We introduce a model-based excessive gap technique to analyze first-order primal- dual methods for constrained convex minimization. As a result, we construct new primal-dual methods with optimal convergence rates on the objective residual and the primal feasibility gap of their iterates separately. Through a dual smoothing and prox-function selection strategy, our framework subsumes the augmented Lagrangian, and alternating methods as special cases, where our rates apply.

An Assessment of the Internal Rating Based Approach in Basel II

OpenAIRE

Simone Varotto

2008-01-01

The new bank capital regulation commonly known as Basel II includes a internal rating based approach (IRB) to measuring credit risk in bank portfolios. The IRB relies on the assumptions that the portfolio is fully diversified and that systematic risk is driven by one common factor. In this work we empirically investigate the impact of these assumptions by comparing the risk measures produced by the IRB with those of a more general credit risk model that allows for multiple systematic risk fac...

A Model for High-Strain-Rate Deformation of Uranium-Niobium Alloys

Energy Technology Data Exchange (ETDEWEB)

F.L.Addessio; Q.H.Zuo; T.A.Mason; L.C.Brinson

2003-05-01

A thermodynamic approach is used to develop a framework for modeling uranium-niobium alloys under the conditions of high strain rate. Using this framework, a three-dimensional phenomenological model, which includes nonlinear elasticity (equation of state), phase transformation, crystal reorientation, rate-dependent plasticity, and porosity growth is presented. An implicit numerical technique is used to solve the evolution equations for the material state. Comparisons are made between the model and data for low-strain-rate loading and unloading as well as for heating and cooling experiments. Comparisons of the model and data also are made for low- and high-strain-rate uniaxial stress and uniaxial strain experiments. A uranium-6 weight percent niobium alloy is used in the comparisons of model and experiment.

Alternate source term models for Yucca Mountain performance assessment based on natural analog data and secondary mineral solubility

International Nuclear Information System (INIS)

Murphy, W.M.; Codell, R.B.

1999-01-01

Performance assessment calculations for the proposed high level radioactive waste repository at Yucca Mountain, Nevada, were conducted using the Nuclear Regulatory Commission Total-System Performance Assessment (TPA 3.2) code to test conceptual models and parameter values for the source term based on data from the Pena Blanca, Mexico, natural analog site and based on a model for coprecipitation and solubility of secondary schoepite. In previous studies the value for the maximum constant oxidative alteration rate of uraninite at the Nopal I uranium body at Pena Blanca was estimated. Scaling this rate to the mass of uranium for the proposed Yucca Mountain repository yields an oxidative alteration rate of 22 kg/y, which was assumed to be an upper limit on the release rate from the proposed repository. A second model was developed assuming releases of radionuclides are based on the solubility of secondary schoepite as a function of temperature and solution chemistry. Releases of uranium are given by the product of uranium concentrations at equilibrium with schoepite and the flow of water through the waste packages. For both models, radionuclides other than uranium and those in the cladding and gap fraction were modeled to be released at a rate proportional to the uranium release rate, with additional elemental solubility limits applied. Performance assessment results using the Pena Blanca oxidation rate and schoepite solubility models for Yucca Mountain were compared to the TPA 3.2 base case model, in which release was based on laboratory studies of spent fuel dissolution, cladding and gap release, and solubility limits. Doses calculated using the release rate based on natural analog data and the schoepite solubility models were smaller than doses generated using the base case model. These results provide a degree of confidence in safety predictions using the base case model and an indication of how conservatism in the base case model may be reduced in future analyses

Alternate source term models for Yucca Mountain performance assessment based on natural analog data and secondary mineral solubility

Energy Technology Data Exchange (ETDEWEB)

Murphy, W.M.; Codell, R.B.

1999-07-01

Performance assessment calculations for the proposed high level radioactive waste repository at Yucca Mountain, Nevada, were conducted using the Nuclear Regulatory Commission Total-System Performance Assessment (TPA 3.2) code to test conceptual models and parameter values for the source term based on data from the Pena Blanca, Mexico, natural analog site and based on a model for coprecipitation and solubility of secondary schoepite. In previous studies the value for the maximum constant oxidative alteration rate of uraninite at the Nopal I uranium body at Pena Blanca was estimated. Scaling this rate to the mass of uranium for the proposed Yucca Mountain repository yields an oxidative alteration rate of 22 kg/y, which was assumed to be an upper limit on the release rate from the proposed repository. A second model was developed assuming releases of radionuclides are based on the solubility of secondary schoepite as a function of temperature and solution chemistry. Releases of uranium are given by the product of uranium concentrations at equilibrium with schoepite and the flow of water through the waste packages. For both models, radionuclides other than uranium and those in the cladding and gap fraction were modeled to be released at a rate proportional to the uranium release rate, with additional elemental solubility limits applied. Performance assessment results using the Pena Blanca oxidation rate and schoepite solubility models for Yucca Mountain were compared to the TPA 3.2 base case model, in which release was based on laboratory studies of spent fuel dissolution, cladding and gap release, and solubility limits. Doses calculated using the release rate based on natural analog data and the schoepite solubility models were smaller than doses generated using the base case model. These results provide a degree of confidence in safety predictions using the base case model and an indication of how conservatism in the base case model may be reduced in future analyses.

Low Base-Substitution Mutation Rate in the Germline Genome of the Ciliate Tetrahymena thermophila

Science.gov (United States)

2016-09-15

Tetrahymena thermophila, a model eukaryote. PLoS Biol. 4:e286. Farlow A, et al. 2015. The spontaneous mutation rate in the fission yeast Schizosaccharomyces...spontane- ous mutations in yeast . Proc Natl Acad Sci U S A. 105:9272–9277. Lynn DH, Doerder FP. 2012. The life and times of Tetrahymena. Methods Cell...Low Base-Substitution Mutation Rate in the Germline Genome of the Ciliate Tetrahymena thermophila Hongan Long1,2,y, David J. Winter3,*,y, Allan Y.-C

Rate-control algorithms testing by using video source model

DEFF Research Database (Denmark)

Belyaev, Evgeny; Turlikov, Andrey; Ukhanova, Anna

2008-01-01

In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set.......In this paper the method of rate control algorithms testing by the use of video source model is suggested. The proposed method allows to significantly improve algorithms testing over the big test set....

A Constant Rate of Spontaneous Mutation in DNA-Based Microbes

Science.gov (United States)

Drake, John W.

1991-08-01

In terms of evolution and fitness, the most significant spontaneous mutation rate is likely to be that for the entire genome (or its nonfrivolous fraction). Information is now available to calculate this rate for several DNA-based haploid microbes, including bacteriophages with single- or double-stranded DNA, a bacterium, a yeast, and a filamentous fungus. Their genome sizes vary by ≈6500-fold. Their average mutation rates per base pair vary by ≈16,000-fold, whereas their mutation rates per genome vary by only ≈2.5-fold, apparently randomly, around a mean value of 0.0033 per DNA replication. The average mutation rate per base pair is inversely proportional to genome size. Therefore, a nearly invariant microbial mutation rate appears to have evolved. Because this rate is uniform in such diverse organisms, it is likely to be determined by deep general forces, perhaps by a balance between the usually deleterious effects of mutation and the physiological costs of further reducing mutation rates.

Building a better methane generation model: Validating models with methane recovery rates from 35 Canadian landfills.

Science.gov (United States)

Thompson, Shirley; Sawyer, Jennifer; Bonam, Rathan; Valdivia, J E

2009-07-01

The German EPER, TNO, Belgium, LandGEM, and Scholl Canyon models for estimating methane production were compared to methane recovery rates for 35 Canadian landfills, assuming that 20% of emissions were not recovered. Two different fractions of degradable organic carbon (DOC(f)) were applied in all models. Most models performed better when the DOC(f) was 0.5 compared to 0.77. The Belgium, Scholl Canyon, and LandGEM version 2.01 models produced the best results of the existing models with respective mean absolute errors compared to methane generation rates (recovery rates + 20%) of 91%, 71%, and 89% at 0.50 DOC(f) and 171%, 115%, and 81% at 0.77 DOC(f). The Scholl Canyon model typically overestimated methane recovery rates and the LandGEM version 2.01 model, which modifies the Scholl Canyon model by dividing waste by 10, consistently underestimated methane recovery rates; this comparison suggested that modifying the divisor for waste in the Scholl Canyon model between one and ten could improve its accuracy. At 0.50 DOC(f) and 0.77 DOC(f) the modified model had the lowest absolute mean error when divided by 1.5 yielding 63 +/- 45% and 2.3 yielding 57 +/- 47%, respectively. These modified models reduced error and variability substantially and both have a strong correlation of r = 0.92.

Satellite altimetry based rating curves throughout the entire Amazon basin

Science.gov (United States)

Paris, A.; Calmant, S.; Paiva, R. C.; Collischonn, W.; Silva, J. S.; Bonnet, M.; Seyler, F.

2013-05-01

The Amazonian basin is the largest hydrological basin all over the world. In the recent past years, the basin has experienced an unusual succession of extreme draughts and floods, which origin is still a matter of debate. Yet, the amount of data available is poor, both over time and space scales, due to factor like basin's size, access difficulty and so on. One of the major locks is to get discharge series distributed over the entire basin. Satellite altimetry can be used to improve our knowledge of the hydrological stream flow conditions in the basin, through rating curves. Rating curves are mathematical relationships between stage and discharge at a given place. The common way to determine the parameters of the relationship is to compute the non-linear regression between the discharge and stage series. In this study, the discharge data was obtained by simulation through the entire basin using the MGB-IPH model with TRMM Merge input rainfall data and assimilation of gage data, run from 1998 to 2010. The stage dataset is made of ~800 altimetry series at ENVISAT and JASON-2 virtual stations. Altimetry series span between 2002 and 2010. In the present work we present the benefits of using stochastic methods instead of probabilistic ones to determine a dataset of rating curve parameters which are consistent throughout the entire Amazon basin. The rating curve parameters have been computed using a parameter optimization technique based on Markov Chain Monte Carlo sampler and Bayesian inference scheme. This technique provides an estimate of the best parameters for the rating curve, but also their posterior probability distribution, allowing the determination of a credibility interval for the rating curve. Also is included in the rating curve determination the error over discharges estimates from the MGB-IPH model. These MGB-IPH errors come from either errors in the discharge derived from the gage readings or errors in the satellite rainfall estimates. The present

Self-rated health, multimorbidity and depression in Mexican older adults: Proposal and evaluation of a simple conceptual model.

Science.gov (United States)

Bustos-Vázquez, Eduardo; Fernández-Niño, Julián Alfredo; Astudillo-Garcia, Claudia Iveth

2017-04-01

Self-rated health is an individual and subjective conceptualization involving the intersection of biological, social and psychological factors. It provides an invaluable and unique evaluation of a person's general health status. To propose and evaluate a simple conceptual model to understand self-rated health and its relationship to multimorbidity, disability and depressive symptoms in Mexican older adults. We conducted a cross-sectional study based on a national representative sample of 8,874 adults of 60 years of age and older. Self-perception of a positive health status was determined according to a Likert-type scale based on the question: "What do you think is your current health status?" Intermediate variables included multimorbidity, disability and depressive symptoms, as well as dichotomous exogenous variables (sex, having a partner, participation in decision-making and poverty). The proposed conceptual model was validated using a general structural equation model with a logit link function for positive self-rated health. A direct association was found between multimorbidity and positive self-rated health (OR=0.48; 95% CI: 0.42-0.55), disability and positive self-rated health (OR=0.35; 95% CI: 0.30-0.40), depressive symptoms and positive self-rated health (OR=0.38; 95% CI: 0.34-0.43). The model also validated indirect associations between disability and depressive symptoms (OR=2.25; 95% CI: 2.01- 2.52), multimorbidity and depressive symptoms (OR=1.79; 95% CI: 1.61-2.00) and multimorbidity and disability (OR=1.98; 95% CI: 1.78-2.20). A parsimonious theoretical model was empirically evaluated, which enabled identifying direct and indirect associations with positive self-rated health.

Do Physicians Respond to Web-Based Patient Ratings? An Analysis of Physicians' Responses to More Than One Million Web-Based Ratings Over a Six-Year Period.

Science.gov (United States)

Emmert, Martin; Sauter, Lisa; Jablonski, Lisa; Sander, Uwe; Taheri-Zadeh, Fatemeh

2017-07-26

Physician-rating websites (PRWs) may lead to quality improvements in case they enable and establish a peer-to-peer communication between patients and physicians. Yet, we know little about whether and how physicians respond on the Web to patient ratings. The objective of this study was to describe trends in physicians' Web-based responses to patient ratings over time, to identify what physician characteristics influence Web-based responses, and to examine the topics physicians are likely to respond to. We analyzed physician responses to more than 1 million patient ratings displayed on the German PRW, jameda, from 2010 to 2015. Quantitative analysis contained chi-square analyses and the Mann-Whitney U test. Quantitative content techniques were applied to determine the topics physicians respond to based on a randomly selected sample of 600 Web-based ratings and corresponding physician responses. Overall, physicians responded to 1.58% (16,640/1,052,347) of all Web-based ratings, with an increasing trend over time from 0.70% (157/22,355) in 2010 to 1.88% (6377/339,919) in 2015. Web-based ratings that were responded to had significantly worse rating results than ratings that were not responded to (2.15 vs 1.74, PWeb to patient ratings differ significantly from nonresponders regarding several characteristics such as gender and patient recommendation results (PWeb to patient ratings. This is likely because of (1) the low awareness of PRWs among physicians, (2) the fact that only a few PRWs enable physicians to respond on the Web to patient ratings, and (3) the lack of an active moderator to establish peer-to-peer communication. PRW providers should foster more frequent communication between the patient and the physician and encourage physicians to respond on the Web to patient ratings. Further research is needed to learn more about the motivation of physicians to respond or not respond to Web-based patient ratings. ©Martin Emmert, Lisa Sauter, Lisa Jablonski, Uwe Sander

A Day-to-Day Route Choice Model Based on Reinforcement Learning

Directory of Open Access Journals (Sweden)

Fangfang Wei

2014-01-01

Full Text Available Day-to-day traffic dynamics are generated by individual traveler’s route choice and route adjustment behaviors, which are appropriate to be researched by using agent-based model and learning theory. In this paper, we propose a day-to-day route choice model based on reinforcement learning and multiagent simulation. Travelers’ memory, learning rate, and experience cognition are taken into account. Then the model is verified and analyzed. Results show that the network flow can converge to user equilibrium (UE if travelers can remember all the travel time they have experienced, but which is not necessarily the case under limited memory; learning rate can strengthen the flow fluctuation, but memory leads to the contrary side; moreover, high learning rate results in the cyclical oscillation during the process of flow evolution. Finally, both the scenarios of link capacity degradation and random link capacity are used to illustrate the model’s applications. Analyses and applications of our model demonstrate the model is reasonable and useful for studying the day-to-day traffic dynamics.

Fuzzy portfolio model with fuzzy-input return rates and fuzzy-output proportions

Science.gov (United States)

Tsaur, Ruey-Chyn

2015-02-01

In the finance market, a short-term investment strategy is usually applied in portfolio selection in order to reduce investment risk; however, the economy is uncertain and the investment period is short. Further, an investor has incomplete information for selecting a portfolio with crisp proportions for each chosen security. In this paper we present a new method of constructing fuzzy portfolio model for the parameters of fuzzy-input return rates and fuzzy-output proportions, based on possibilistic mean-standard deviation models. Furthermore, we consider both excess or shortage of investment in different economic periods by using fuzzy constraint for the sum of the fuzzy proportions, and we also refer to risks of securities investment and vagueness of incomplete information during the period of depression economics for the portfolio selection. Finally, we present a numerical example of a portfolio selection problem to illustrate the proposed model and a sensitivity analysis is realised based on the results.

75 FR 72581 - Assessments, Assessment Base and Rates

Science.gov (United States)

2010-11-24

... Part III Federal Deposit Insurance Corporation 12 CFR Part 327 Assessments, Assessment Base and... Assessments, Assessment Base and Rates AGENCY: Federal Deposit Insurance Corporation. ACTION: Notice of... Consumer Protection Act regarding the definition of an institution's deposit insurance assessment base...

Shale gas technology innovation rate impact on economic Base Case – Scenario model benchmarks

International Nuclear Information System (INIS)

Weijermars, Ruud

2015-01-01

Highlights: • Cash flow models control which technology is affordable in emerging shale gas plays. • Impact of technology innovation on IRR can be as important as wellhead price hikes. • Cash flow models are useful for technology decisions that make shale gas plays economic. • The economic gap can be closed by appropriate technology innovation. - Abstract: Low gas wellhead prices in North America have put its shale gas industry under high competitive pressure. Rapid technology innovation can help companies to improve the economic performance of shale gas fields. Cash flow models are paramount for setting effective production and technology innovation targets to achieve positive returns on investment in all global shale gas plays. Future cash flow of a well (or cluster of wells) may either improve further or deteriorate, depending on: (1) the regional volatility in gas prices at the wellhead – which must pay for the gas resource extraction, and (2) the cost and effectiveness of the well technology used. Gas price is an externality and cannot be controlled by individual companies, but well technology cost can be reduced while improving production output. We assume two plausible scenarios for well technology innovation and model the return on investment while checking against sensitivity to gas price volatility. It appears well technology innovation – if paced fast enough – can fully redeem the negative impact of gas price decline on shale well profits, and the required rates are quantified in our sensitivity analysis

An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

Energy Technology Data Exchange (ETDEWEB)

Kim, S. K.; Kang, G. B.; Ko, W. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2013-10-15

Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole.

An Adjusted Discount Rate Model for Fuel Cycle Cost Estimation

International Nuclear Information System (INIS)

Kim, S. K.; Kang, G. B.; Ko, W. I.

2013-01-01

Owing to the diverse nuclear fuel cycle options available, including direct disposal, it is necessary to select the optimum nuclear fuel cycles in consideration of the political and social environments as well as the technical stability and economic efficiency of each country. Economic efficiency is therefore one of the significant evaluation standards. In particular, because nuclear fuel cycle cost may vary in each country, and the estimated cost usually prevails over the real cost, when evaluating the economic efficiency, any existing uncertainty needs to be removed when possible to produce reliable cost information. Many countries still do not have reprocessing facilities, and no globally commercialized HLW (High-level waste) repository is available. A nuclear fuel cycle cost estimation model is therefore inevitably subject to uncertainty. This paper analyzes the uncertainty arising out of a nuclear fuel cycle cost evaluation from the viewpoint of a cost estimation model. Compared to the same discount rate model, the nuclear fuel cycle cost of a different discount rate model is reduced because the generation quantity as denominator in Equation has been discounted. Namely, if the discount rate reduces in the back-end process of the nuclear fuel cycle, the nuclear fuel cycle cost is also reduced. Further, it was found that the cost of the same discount rate model is overestimated compared with the different discount rate model as a whole

Steady State Investigations of DPF Soot Burn Rates and DPF Modeling

DEFF Research Database (Denmark)

Cordtz, Rasmus Lage; Ivarsson, Anders; Schramm, Jesper

2011-01-01

and soot mass concentrations are used as model boundary conditions. An in-house developed raw exhaust gas sampling technique is used to measure the soot concentration upstream the DPF which is also needed to find the DPF soot burn rate. The soot concentration is measured basically by filtering the soot...... characteristics are used to fit model constants of soot and filter properties. Measured DPF gas conversions and soot burn rates are used to fit model activation energies of four DPF regeneration reactions using O2 and NO2 as reactants. Modeled DPF pressure drops and soot burn rates are compared to the steady...... state DPF experiments in the temperature range between 260 and 480 °C. The model widely reproduces the experimental results. Especially the exponential soot burn rate versus temperature is accurately reproduced by the model....

CEAI: CCM-based email authorship identification model

Directory of Open Access Journals (Sweden)

Sarwat Nizamani

2013-11-01

Full Text Available In this paper we present a model for email authorship identification (EAI by employing a Cluster-based Classification (CCM technique. Traditionally, stylometric features have been successfully employed in various authorship analysis tasks; we extend the traditional feature set to include some more interesting and effective features for email authorship identification (e.g., the last punctuation mark used in an email, the tendency of an author to use capitalization at the start of an email, or the punctuation after a greeting or farewell. We also included Info Gain feature selection based content features. It is observed that the use of such features in the authorship identification process has a positive impact on the accuracy of the authorship identification task. We performed experiments to justify our arguments and compared the results with other base line models. Experimental results reveal that the proposed CCM-based email authorship identification model, along with the proposed feature set, outperforms the state-of-the-art support vector machine (SVM-based models, as well as the models proposed by Iqbal et al. (2010, 2013 [1,2]. The proposed model attains an accuracy rate of 94% for 10 authors, 89% for 25 authors, and 81% for 50 authors, respectively on Enron dataset, while 89.5% accuracy has been achieved on authors’ constructed real email dataset. The results on Enron dataset have been achieved on quite a large number of authors as compared to the models proposed by Iqbal et al. [1,2].

Ads' click-through rates predicting based on gated recurrent unit neural networks

Science.gov (United States)

Chen, Qiaohong; Guo, Zixuan; Dong, Wen; Jin, Lingzi

2018-05-01

In order to improve the effect of online advertising and to increase the revenue of advertising, the gated recurrent unit neural networks(GRU) model is used as the ads' click through rates(CTR) predicting. Combined with the characteristics of gated unit structure and the unique of time sequence in data, using BPTT algorithm to train the model. Furthermore, by optimizing the step length algorithm of the gated unit recurrent neural networks, making the model reach optimal point better and faster in less iterative rounds. The experiment results show that the model based on the gated recurrent unit neural networks and its optimization of step length algorithm has the better effect on the ads' CTR predicting, which helps advertisers, media and audience achieve a win-win and mutually beneficial situation in Three-Side Game.

INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

Science.gov (United States)

Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

2015-01-01

Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

Model-Based Power Plant Master Control

Energy Technology Data Exchange (ETDEWEB)

Boman, Katarina; Thomas, Jean; Funkquist, Jonas

2010-08-15

The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are

Modeling the shear rate and pressure drop in a hydrodynamic cavitation reactor with experimental validation based on KI decomposition studies.

Science.gov (United States)

Badve, Mandar P; Alpar, Tibor; Pandit, Aniruddha B; Gogate, Parag R; Csoka, Levente

2015-01-01

A mathematical model describing the shear rate and pressure variation in a complex flow field created in a hydrodynamic cavitation reactor (stator and rotor assembly) has been depicted in the present study. The design of the reactor is such that the rotor is provided with surface indentations and cavitational events are expected to occur on the surface of the rotor as well as within the indentations. The flow characteristics of the fluid have been investigated on the basis of high accuracy compact difference schemes and Navier-Stokes method. The evolution of streamlining structures during rotation, pressure field and shear rate of a Newtonian fluid flow have been numerically established. The simulation results suggest that the characteristics of shear rate and pressure area are quite different based on the magnitude of the rotation velocity of the rotor. It was observed that area of the high shear zone at the indentation leading edge shrinks with an increase in the rotational speed of the rotor, although the magnitude of the shear rate increases linearly. It is therefore concluded that higher rotational speeds of the rotor, tends to stabilize the flow, which in turn results into less cavitational activity compared to that observed around 2200-2500RPM. Experiments were carried out with initial concentration of KI as 2000ppm. Maximum of 50ppm of iodine liberation was observed at 2200RPM. Experimental as well as simulation results indicate that the maximum cavitational activity can be seen when rotation speed is around 2200-2500RPM. Copyright © 2014 Elsevier B.V. All rights reserved.

MONETARY MODELS AND EXCHANGE RATE DETERMINATION ...

African Journals Online (AJOL)

Power Party [PPP] based on the law of one price asserts that the change in the exchange rate between .... exchange in international economic transactions has made it vitally evident that the management of ... One lesson from this episode is to ...

A statistical modeling approach to build expert credit risk rating systems

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

2010-01-01

This paper presents an efficient method for extracting expert knowledge when building a credit risk rating system. Experts are asked to rate a sample of counterparty cases according to creditworthiness. Next, a statistical model is used to capture the relation between the characteristics...... of a counterparty and the expert rating. For any counterparty the model can identify the rating, which would be agreed upon by the majority of experts. Furthermore, the model can quantify the concurrence among experts. The approach is illustrated by a case study regarding the construction of an application score...

On cross-currency models with stochastic volatility and correlated interest rates

NARCIS (Netherlands)

Grzelak, L.A.; Oosterlee, C.W.

2010-01-01

We construct multi-currency models with stochastic volatility and correlated stochastic interest rates with a full matrix of correlations. We first deal with a foreign exchange (FX) model of Heston-type, in which the domestic and foreign interest rates are generated by the short-rate process of

Verification of Sulfate Attack Penetration Rates for Saltstone Disposal Unit Modeling

Energy Technology Data Exchange (ETDEWEB)

Flach, G. P. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2015-05-12

Recent Special Analysis modeling of Saltstone Disposal Units consider sulfate attack on concrete and utilize degradation rates estimated from Cementitious Barriers Partnership software simulations. This study provides an independent verification of those simulation results using an alternative analysis method and an independent characterization data source. The sulfate penetration depths estimated herein are similar to the best-estimate values in SRNL-STI-2013-00118 Rev. 2 and well below the nominal values subsequently used to define Saltstone Special Analysis base cases.

Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

International Nuclear Information System (INIS)

Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok; Yi, Sun

2016-01-01

In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

Model Reference Adaptive Control of the Air Flow Rate of Centrifugal Compressor Using State Space Method

Energy Technology Data Exchange (ETDEWEB)

Han, Jaeyoung; Jung, Mooncheong; Yu, Sangseok [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Yi, Sun [North Carolina A and T State Univ., Raleigh (United States)

2016-08-15

In this study, a model reference adaptive controller is developed to regulate the outlet air flow rate of centrifugal compressor for automotive supercharger. The centrifugal compressor is developed using the analytical based method to predict the transient behavior of operating and the designed model is validated with experimental data to confirm the system accuracy. The model reference adaptive control structure consists of a compressor model and a MRAC(model reference adaptive control) mechanism. The feedback control do not robust with variation of system parameter but the applied adaptive control is robust even if the system parameter is changed. As a result, the MRAC was regulated to reference air flow rate. Also MRAC was found to be more robust control compared with the feedback control even if the system parameter is changed.

Study on Rail Profile Optimization Based on the Nonlinear Relationship between Profile and Wear Rate

Directory of Open Access Journals (Sweden)

Jianxi Wang

2017-01-01

Full Text Available This paper proposes a rail profile optimization method that takes account of wear rate within design cycle so as to minimize rail wear at the curve in heavy haul railway and extend the service life of rail. Taking rail wear rate as the object function, the vertical coordinate of rail profile at range optimization as independent variable, and the geometric characteristics and grinding depth of rail profile as constraint conditions, the support vector machine regression theory was used to fit the nonlinear relationship between rail profile and its wear rate. Then, the profile optimization model was built. Based on the optimization principle of genetic algorithm, the profile optimization model was solved to achieve the optimal rail profile. A multibody dynamics model was used to check the dynamic performance of carriage running on optimal rail profile. The result showed that the average relative error of support vector machine regression model remained less than 10% after a number of training processes. The dynamic performance of carriage running on optimized rail profile met the requirements on safety index and stability. The wear rate of optimized profile was lower than that of standard profile by 5.8%; the allowable carrying gross weight increased by 12.7%.

A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model

Science.gov (United States)

Campbell, Stefan F.; Kaneshige, John T.

2010-01-01

Presented here is a Predictor-Based Model Reference Adaptive Control (PMRAC) architecture for a generic transport aircraft. At its core, this architecture features a three-axis, non-linear, dynamic-inversion controller. Command inputs for this baseline controller are provided by pilot roll-rate, pitch-rate, and sideslip commands. This paper will first thoroughly present the baseline controller followed by a description of the PMRAC adaptive augmentation to this control system. Results are presented via a full-scale, nonlinear simulation of NASA s Generic Transport Model (GTM).

Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence.

Directory of Open Access Journals (Sweden)

Megan A Cummins

2014-03-01

Full Text Available Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP. The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz and fast (2 Hz rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

Directory of Open Access Journals (Sweden)

Maja eStikic

2014-11-01

Full Text Available The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make deadly force decisions in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects’ performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback, and applied across a variety of training environments.

Experimental Study and Modelling of Poly (Methyl Methacrylate) and Polycarbonate Compressive Behavior from Low to High Strain Rates

Science.gov (United States)

El-Qoubaa, Z.; Colard, L.; Matadi Boumbimba, R.; Rusinek, A.

2018-03-01

This paper concerns an experimental investigation of Polycarbonate and Poly (methyl methacrylate) compressive behavior from low to high strain rates. Experiments were conducted from 0.001/s to ≈ 5000/s for PC and from 0.001/s to ≈ 2000/s for PMMA. The true strain-stress behavior is established and analyzed at various stain rates. Both PC and PMMA mechanical behavior appears as known, to be strain rate and temperature dependent. The DSGZ model is selected for modelling the strain-stress curves while the yield stress is reproduced using the cooperative model and a modified Eyring equation based on Eyring first process theory. All the three models predictions are in agreement with experiments performed on PC and PMMA.

Evaluating location specific strain rates, temperatures, and accumulated strains in friction welds through microstructure modeling

Directory of Open Access Journals (Sweden)

Javed Akram

2018-04-01

Full Text Available A microstructural simulation method is adopted to predict the location specific strain rates, temperatures, grain evolution, and accumulated strains in the Inconel 718 friction welds. Cellular automata based 2D microstructure model was developed for Inconel 718 alloy using theoretical aspects of dynamic recrystallization. Flow curves were simulated and compared with experimental results using hot deformation parameter obtained from literature work. Using validated model, simulations were performed for friction welds of Inconel 718 alloy generated at three rotational speed i.e., 1200, 1500, and 1500 RPM. Results showed the increase in strain rates with increasing rotational speed. These simulated strain rates were found to match with the analytical results. Temperature difference of 150 K was noticed from center to edge of the weld. At all the rotational speeds, the temperature was identical implying steady state temperature (0.89Tm attainment. Keywords: Microstructure modeling, Dynamic recrystallization, Friction welding, Inconel 718, EBSD, Hot deformation, Strain map

An alternative derivation of the stationary distribution of the multivariate neutral Wright-Fisher model for low mutation rates with a view to mutation rate estimation from site frequency data.

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Schrempf, Dominik; Hobolth, Asger

2017-04-01

Recently, Burden and Tang (2016) provided an analytical expression for the stationary distribution of the multivariate neutral Wright-Fisher model with low mutation rates. In this paper we present a simple, alternative derivation that illustrates the approximation. Our proof is based on the discrete multivariate boundary mutation model which has three key ingredients. First, the decoupled Moran model is used to describe genetic drift. Second, low mutation rates are assumed by limiting mutations to monomorphic states. Third, the mutation rate matrix is separated into a time-reversible part and a flux part, as suggested by Burden and Tang (2016). An application of our result to data from several great apes reveals that the assumption of stationarity may be inadequate or that other evolutionary forces like selection or biased gene conversion are acting. Furthermore we find that the model with a reversible mutation rate matrix provides a reasonably good fit to the data compared to the one with a non-reversible mutation rate matrix. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Markov chain aggregation for agent-based models

CERN Document Server

Banisch, Sven

2016-01-01

This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible. It presents a general framework of aggregation in agent-based and related computational models, one which makes use of lumpability and information theory in order to link the micro and macro levels of observation. The starting point is a microscopic Markov chain description of the dynamical process in complete correspondence with the dynamical behavior of the agent-based model (ABM), which is obtained by considering the set of all possible agent configurations as the state space of a huge Markov chain. An explicit formal representation of a resulting “micro-chain” including microscopic transition rates is derived for a class of models by using the random mapping representation of a Markov process. The type of probability distribution used to implement the stochastic part of the model, which defines the upd...

Coupling impervious surface rate derived from satellite remote sensing with distributed hydrological model for highly urbanized watershed flood forecasting

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Dong, L.

2017-12-01

Abstract: The original urban surface structure changed a lot because of the rapid development of urbanization. Impermeable area has increased a lot. It causes great pressure for city flood control and drainage. Songmushan reservoir basin with high degree of urbanization is taken for an example. Pixel from Landsat is decomposed by Linear spectral mixture model and the proportion of urban area in it is considered as impervious rate. Based on impervious rate data before and after urbanization, an physically based distributed hydrological model, Liuxihe Model, is used to simulate the process of hydrology. The research shows that the performance of the flood forecasting of high urbanization area carried out with Liuxihe Model is perfect and can meet the requirement of the accuracy of city flood control and drainage. The increase of impervious area causes conflux speed more quickly and peak flow to be increased. It also makes the time of peak flow advance and the runoff coefficient increase. Key words: Liuxihe Model; Impervious rate; City flood control and drainage; Urbanization; Songmushan reservoir basin

Biasing transition rate method based on direct MC simulation for probabilistic safety assessment

Institute of Scientific and Technical Information of China (English)

Xiao-Lei Pan; Jia-Qun Wang; Run Yuan; Fang Wang; Han-Qing Lin; Li-Qin Hu; Jin Wang

2017-01-01

Direct Monte Carlo (MC) simulation is a powerful probabilistic safety assessment method for accounting dynamics of the system.But it is not efficient at simulating rare events.A biasing transition rate method based on direct MC simulation is proposed to solve the problem in this paper.This method biases transition rates of the components by adding virtual components to them in series to increase the occurrence probability of the rare event,hence the decrease in the variance of MC estimator.Several cases are used to benchmark this method.The results show that the method is effective at modeling system failure and is more efficient at collecting evidence of rare events than the direct MC simulation.The performance is greatly improved by the biasing transition rate method.

Incorporating a Time Horizon in Rate-of-Return Estimations: Discounted Cash Flow Model in Electric Transmission Rate Cases

International Nuclear Information System (INIS)

Chatterjee, Bishu; Sharp, Peter A.

2006-01-01

Electric transmission and other rate cases use a form of the discounted cash flow model with a single long-term growth rate to estimate rates of return on equity. It cannot incorporate information about the appropriate time horizon for which analysts' estimates of earnings growth have predictive powers. Only a non-constant growth model can explicitly recognize the importance of the time horizon in an ROE calculation. (author)

Rate dependent inelastic behavior of polycrystalline solids using a dislocation model

International Nuclear Information System (INIS)

Werne, R.W.; Kelly, J.M.

1980-01-01

A rate dependent theory of polycrystalline plasticity is presented in which the solid is modeled as an isotropic continuum with internal variables. The rate of plastic deformation is shown to be a function of the deviatoric portion of the Cauchy stress tensor as well as two scalar internal variables. The scalar internal variables, which are the dislocation density and mobile fraction, are governed by rate equations which reflect the evolution of microstructural processes. The model has been incorporated into a two dimensional finite element code and several example multidimensional problems are presented which exhibit the rate dependence of the material model

Death Rates in the Calorie Model

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Martin Machay

2016-01-01

Full Text Available The Calorie model unifies the Classical demand and the supply in the food market. Hence, solves the major problem of Classical stationary state. It is, hence, formalization of the Classical theory of population. The model does not reflect the imperfections of reality mentioned by Malthus himself. It is the aim of this brief paper to relax some of the strong assumptions of the Calorie model to make it more realistic. As the results show the political economists were correct. The death resulting from malnutrition can occur way sooner than the stationary state itself. Moreover, progressive and retrograde movements can be easily described by the death rate derived in the paper. JEL Classification: J11, Q11, Q15, Q21, Y90.

Statistically Based Morphodynamic Modeling of Tracer Slowdown

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Borhani, S.; Ghasemi, A.; Hill, K. M.; Viparelli, E.

2017-12-01

Tracer particles are used to study bedload transport in gravel-bed rivers. One of the advantages associated with using of tracer particles is that they allow for direct measures of the entrainment rates and their size distributions. The main issue in large scale studies with tracer particles is the difference between tracer stone short term and long term behavior. This difference is due to the fact that particles undergo vertical mixing or move to less active locations such as bars or even floodplains. For these reasons the average virtual velocity of tracer particle decreases in time, i.e. the tracer slowdown. In summary, tracer slowdown can have a significant impact on the estimation of bedload transport rate or long term dispersal of contaminated sediment. The vast majority of the morphodynamic models that account for the non-uniformity of the bed material (tracer and not tracer, in this case) are based on a discrete description of the alluvial deposit. The deposit is divided in two different regions; the active layer and the substrate. The active layer is a thin layer in the topmost part of the deposit whose particles can interact with the bed material transport. The substrate is the part of the deposit below the active layer. Due to the discrete representation of the alluvial deposit, active layer models are not able to reproduce tracer slowdown. In this study we try to model the slowdown of tracer particles with the continuous Parker-Paola-Leclair morphodynamic framework. This continuous, i.e. not layer-based, framework is based on a stochastic description of the temporal variation of bed surface elevation, and of the elevation specific particle entrainment and deposition. Particle entrainment rates are computed as a function of the flow and sediment characteristics, while particle deposition is estimated with a step length formulation. Here we present one of the first implementation of the continuum framework at laboratory scale, its validation against

Modeling of the pyruvate production with Escherichia coli: comparison of mechanistic and neural networks-based models.

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Zelić, B; Bolf, N; Vasić-Racki, D

2006-06-01

Three different models: the unstructured mechanistic black-box model, the input-output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249-258 (2004); Zelić et al. Eng Life Sci 3:299-305 (2003); Zelić et al Biotechnol Bioeng 85:638-646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.