• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.130-140
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• 1998

Studies present a guide to parameter estimation of software reliability models using SAS JMP. In this paper, we consider only software reliability growth model(SRGM), where mean value function has a S-shaped growth curve, such as Yamada et al. model, and ohba inflection model. Besides these stochastic SRGM, deterministic SRGM's, by fitting Logistic and Gompertz growth curve, have been widely used to estimate the error content of software systems. Introductions or guide lines of JMP are concerned. Estimation of parameters of Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is accomplished by using JMP. The differences between Yamada et al. model and Logistic model is discussed, along with the variability in the estimates or error sum of squares. This paper have shown that JMP can be an effective tool I these research.

• Journal of Preventive Medicine and Public Health
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• v.26 no.3 s.43
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• pp.442-456
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• 1993

Financial stability is the foremost prerequisite for the continuous growth and development of hospitals. The present study aimed at developing a deterministic model using the factors which affect the hospitals profitability and at discovering which factor affected the hospital profitability. The study conducted questionnaire surveys on all general hospitals, with the exception of special hospitals, with over eighty hospital beds. Of the 274 subject hospitals, 136 of them, consituting 49.6% of the whole, were used in the study. The results are as follows. 1. In the deterministic model, outpatient revenue was affected more by the number of physician visits than by outpatient service intensity. Inpatient revenue was found to be affected more by the number of discharged patients than by inpatient service intensity. However, the increase rate of the service intensity not only contributed in stepping up the operating margin by $4{\sim}8%$ in outpatient and $3{\sim}6%$ in inpatient, but it was statistically significant. 2. Among the factors which determined the operating cost within the deterministic model, the number of patients had a greater impact on the operating cost than the resource consumption per patient. 3. The resource consumption per patient were proved to have the greatest effect on the profitability within the probabilistic model. The management cost per adjusted patient, in particular, was proven to have a statistically significant effect on the profitability in all hospitals.

• Interaction and multiscale mechanics
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• v.1 no.3
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• pp.369-379
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• 2008

A combined stochastic diffusion and mean-field model is developed for a systematic study of the grain growth in a pure single-phase polycrystalline material. A corresponding Fokker-Planck continuity equation is formulated, and the interplay/competition of stochastic and curvature-driven mechanisms is investigated. Finite difference results show that the stochastic diffusion coefficient has a strong effect on the growth of small grains in the early stage in both two-dimensional columnar and three-dimensional grain systems, and the corresponding growth exponents are ~0.33 and ~0.25, respectively. With the increase in grain size, the deterministic curvature-driven mechanism becomes dominant and the growth exponent is close to 0.5. The transition ranges between these two mechanisms are about 2-26 and 2-15 nm with boundary energy of 0.01-1 J $m^{-2}$ in two- and three-dimensional systems, respectively. The grain size distribution of a three-dimensional system changes dramatically with increasing time, while it changes a little in a two-dimensional system. The grain size distribution from the combined model is consistent with experimental data available.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.493-510
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• 2020

Purpose: As of July 31, there were 14,336 confirmed cases of COVID-19 in South Korea, including 301 deaths. Since the daily confirmed number of cases hit 909 on February 29, the spread of the disease had gradually decreased due to the active implementation of preventive control interventions, and the daily confirmed number had finally recorded a single digit on April 19. Since May, however, the disease has re-emerged and retaining after June. In order to eradicate the disease, it is necessary to suggest suitable forward preventive strategies by predicting future infectivity of the disease based on the cases so far. Therefore, in this study, we aim to evaluate the transmission potential of the disease in early phases by estimating basic reproduction number and assess the preventive control measures through effective reproduction number. Methods: We used publicly available cases and deaths data regarding COVID-19 in South Korea as of July 31. Using ensemble model integrated stochastic linear birth model and deterministic linear growth model, the basic reproduction number and the effective reproduction number were estimated. Results: Estimated basic reproduction number is 3.1 (95% CI: 3.0-3.2). Effective reproduction number was the highest with 7 on February 15, decreased as of April 20. Since then, the value is gradually increased to more than unity. Conclusion: Preventive policy such as wearing a mask and physical distancing campaigns in the early phase of the outbreak was fairly implemented. However, the infection potential increased due to weakening government policy on May 6. Our results suggest that it seems necessary to implement a stronger policy than the current level.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.781-802
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• 2011

Of concern in the paper is a Holling-Tanner predator-prey model with modified version of the Leslie-Gower functional response. Dynamical behaviours such as stability, permanence and Hopf bifurcation have been carried out deterministically. Using the normal form theory and center manifold theorem, the explicit formulae determining the stability and direction of Hopf bifurcation have been derived. The deterministic model is extended to a stochastic one by perturbing the growth equation of prey and predator by white and colored noises and finally the mean square stability of the stochastic model systems is investigated analytically. An extensive quantitative analysis has been performed based on numerical computation so as to validate the applicability of the proposed mathematical model.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.637-644
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.149-160
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• 1995

We consider the problem of optimal adaptive estiamtion of the euclidean parameter vector $\theta$ of the univariate non-linerar autogressive time series model ${X_t}$ which is defined by the following system of stochastic difference equations ; $X_t = \sum^p_{i=1} \theta_i \cdot T_i(X_{t-1})+e_t, t=1, \cdots, n$, where $\theta$ is the unknown parameter vector which descrives the deterministic dynamics of the stochastic process ${X_t}$ and ${e_t}$ is the sequence of white noises with unknown density $f(\cdot)$. Under some general growth conditions on $T_i(\cdot)$ which guarantee ergodicity of the process, we construct a sequence of adaptive estimatros which is locally asymptotic minimax (LAM) efficient and also attains the least possible covariance matrix among all regular estimators for arbitrary symmetric density.

• ALGAE
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• v.17 no.3
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• pp.187-194
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• 2002

A seaweed biofilter/production system of being developed to reduce the environmental impact of marine fish farm effluent in coastal ecosystems as a part of an integrated aquaculture system. Several known seaweed taxa and their cultivars have been considered as candidate biofilter organisms based on their species-specific physiological properties such as nutrient uptake kinetics and their economic value. Porphyra is an excellent cadidate and shows efficient nutrient extraction properties. Rates of ammonium uptake were maintained at around 3 ${\mu}moles{\cdot}g{\cdot}dw^{-1}{\cdot}min^{-1}$ at 150 ${\mu}M$ inorganic nitrogen at $10^{\circ}C$. Ulva is another possible biofilter candidate with an uptake rate of 1.9 ${\mu}moles{\cdot}g{\cdot}dw^{-1}{\cdot}min^{-1}$ under same conditions. A simple uptake/growth and harvest model was applied to estimate the efficiency of the biofilter/production system. The model was deterministic and used a compartment model structure based on difference equations. The efficiency of Porpyra filter was estimated over 17% of ${NH_4}^+$ removal from the contimuous supply of 100 ${\mu}mole{\cdot}l^{-1}\;{NH_4}^+\;at\;100l{\cdot}sec^{-1}$ flow rate.

• Journal of Preventive Medicine and Public Health
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• v.22 no.4 s.28
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• pp.542-554
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• 1989

The skyrocketing inflation of medical costs has become a major health problem among most developed countries. Korea, which recently covered the entire population with National Health Insurance, is facing the same problem. The proportion of health expenditure to GNP has increased from 3% to 4.8% during the last decade. This was remarkable, if we consider the rapid economic growth during that time. A few policy analysts began to raise cost containment as an agenda, after recognizing the importance of medical cost inflation. In order to Prepare an appropriate alternative for the agenda, it is necessary to find out reasons for the cost inflation. Then, we should focus on the reasons which are controllable, and those whose control are socially desirable. This study is designed to articulate the theory of medical cost inflation through literature reviews, to find out reasons for cost inflation, by analyzing aggregated data with a deterministic model. Finally to identify determinants of changes in both medical demand and service intensity which are major reasons for cost inflation. The reasons for cost inflation are classified into cost push inflation and demand pull inflation, The former consists of increases in price and intensity of services, while the latter is made of consumer derived demand and supplier induced demand. We used a time series (1983-1987), and cross sectional (over regions) data of health insurance. The deterministic model reveals, that an increase in service intensity is a major cause of inflation in the case of inpatient care, while, more utilization, is a primary attribute in the case of physician visits. Multiple regression analysis shows that an increase in hospital beds is a leading explanatory variable for the increase in hospital care. It also reveals, that an introduction of a deductible clause, an increase in hospital beds and degree of urbanization, are statistically significant variables explaining physician visits. The results are consistent with the existing theory, The magnitude of service intensity is influenced by the level of co-payment, the proportion of old age and an increase in co-payment. In short, an increase in co-payment reduced the utilization, but it induced more intensities or services. We can conclude that the strict fee regulation or increase in the level of co-payment can not be an effective measure for cost containment under the fee for service system. Because the provider can react against the regulation by inducing more services.