• 한국연소학회:학술대회논문집
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• 2002.11a
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• pp.173-184
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• 2002

In order to evaluate the devolatilization models of pulverized coal, various devolatilization models are examined for the numerical analysis of Drop Tube Furnace.The results of analysis are compared with the experimental results. A numerical study was conducted to explore the sensitivities of the predictions to variation of the model parameters. It helps to elucidate the source of the discrepancies. Three different wall temperature conditions of the DTF, 1100, 1300 and $1500^{\circ}C$ were considered in this analysis. Two fuels are U.S.A. Alaska coal and Australia Drayton coal. The results of analysis with constant rate model, single kinetic rate model and two competing rate modes well presented fast volatile matter release in the early devolatilization. However, in the latter devolatilization they did not coincide with experimental results which presented tardy volatile matter release on account of pyrolysis of high molecular substance. On the other hand, the results of analysis with DAEM(Distribute Activation Energy Model) coincided with experiment al results in overall devolatilization.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.61-69
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• 2001

This paper presents a two stage game model which examines the effect of learning-by-doing and spillover. Increases in the firm’s cumulative experience lower its unit cost in future period. However, the firm’s rival also enjoys the experience via spillover. Unlike previous theoretical research model, a cost asymmetric market entry game model is developed between the incumbent firm and new entrant. Mathematical results show that the incumbent firm exploits the learning curve to gain future cost advantage, and that the diffusion of learning to the new entrant induces the incumbent firm to choose decreasing output strategically. As a main result, we show that the relative magnitude between the learning and spillover rate determines the market share ratio of competing firms.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.397-419
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• 2017

A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.349-360
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• 2023

Dynamic Nelson-Siegel model is widely used in modeling term structure of interest rates for financial products. In this study, we explain dynamic Nelson-Siegel model from the perspective of the state space model and explore Bayesian approaches that can be applied to that model. By applying SOFR term rate data to the Bayesian dynamic Nelson-Siegel model, we confirm the performance and compare it with other competing models such as Vasicek model, dynamic Nelson-Siegel model based on the frequentist approach, and the two-factor Bayesian dynamic Nelson-Siegel model. We also confirm that the Bayesian dynamic Nelson-Siegel model outperformed its competitors on SOFR term rate data based on RMSE.

• Journal of the Korean Society of Combustion
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• v.7 no.1
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• pp.44-51
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• 2002

This paper presents an atomization model for sprays under flash boiling conditions. The atomization is represented by the secondary breakup of a bubble/droplet system, and the breakup is considered as the results of two competing mechanisms, aerodynamic force and bubble growth. The model was applied to predict the atomization of a hollow-cone spray from pintle injector under flash boiling conditions. In the regimes this study considered, sprays are atomized by bubble growth, which produces smaller SMD#s than aerodynamic forces alone. With decreasing ambient pressures, the spray thickness, fuel vaporization rate and vapor radial penetration increases, and the drop size decreases. With increasing the fuel and ambient temperatures to some extent, the effect of flash boiling and air entrainment completely change the spray pattern.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.325-337
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• 2017

In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

• Membrane Journal
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• v.13 no.4
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• pp.257-267
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• 2003

For the treatment of reactive phenolic resin waste, a simulation model of pervaporative dehydration process has been developed through hollow fiber membrane module. Some of basic parameters were determined directly from dehydration of the waste liquid through a flat sheet membrane to get realistic values. The simulation model was verified by comparing the simulated values with experimental data obtained from hollow fiber membrane module. Hollow fiber membranes with active layer coated on inside fiber were used, and feed flew through inside hollow fiber. Feed flow rate affected membrane performances and reaction by providing a corresponding temperature distribution of feed along with fiber length. Feed temperature is also a crucial factor to determine dehydration and reaction behavior by two competing ways; increasing temperature increases permeation rate as well as water formation rate. Once the permeate pressure is well below the saturated vapor pressure of feed, permeate pressure had a slightly negative effect on permeation performance by slightly reducing driving force. As the pressure approached the vapor pressure of feed, dehydration performances declined considerably due to the activity ratio of feed and permeate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.579-603
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• 2018

In this paper we propose a QoS-enhanced intelligent stochastic optimal fair real-time packet scheduler, QUEST, for 4G LTE traffic in routers. The objective of this research is to maximize the system QoS subject to the constraint that the processor utilization is kept nearly at 100 percent. The QUEST has following unique advantages. First, it solves the challenging problem of starvation for low priority process - buffered streaming video and TCP based; second, it solves the major bottleneck of the scheduler Earliest Deadline First's failure at heavy loads. Finally, QUEST offers the benefit of arbitrarily pre-programming the process utilization ratio.Three classes of multimedia 4G LTE QCI traffic, conversational voice, live streaming video, buffered streaming video and TCP based applications have been considered. We analyse two most important QoS metrics, packet loss rate (PLR) and mean waiting time. All claims are supported by discrete event and Monte Carlo simulations. The simulation results show that the QUEST scheduler outperforms current state-of-the-art benchmark schedulers. The proposed scheduler offers 37 percent improvement in PLR and 23 percent improvement in mean waiting time over the best competing current scheduler Accuracy-aware EDF.

• Korea Journal of Hospital Management
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• v.12 no.3
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• pp.47-67
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• 2007

This paper aims at suggesting several ways lo change financial vulnerability and to improve managerial capability of local public hospitals (LPHs) in Korea through the identification of factors affecting profitability. Several findings of the research are as follows: To begin with, LPHs exhibited a statistically significant difference in their profitability from one another, according to tile analyses of their profitable margins from tile general characteristics. It depends on the number of hospitals in the area, the population of the hospital-built area, the number of competing hospitals, the number of staff per 100 beds, the opening of special clinic, the educational function, and the capacity of rooms. However, there was no variable in the managerial characteristics, presenting a significant difference, in contrast with hospitals which have been managed by private companies and made a great amount of profits. Second, according to the analyses of profit differences in behavioral effort-characteristics, a statistically significant difference was revealed upon the basis of the efforts to improve the clinic service, invite special patients, and shorten the period of being hospitalized. Third, the result of analyses about the difference of profitability from medical care and finance is statistically significant in the rate of labor cost, the rate of management cost, bed-occupancy rate, and the period of being hospitalized. Fourth, according to the analyses of the factors influencing the net profit ratio of the entire capital, Adjusted explanatory power(Adjusted $R^2$) was shown up to 65.2%, which is high. To compare the adjusted explanatory power stage by stage, the first stage model applying only two variables such as structural and strategic characteristics exhibited 23.8%, and the second stage model adding financial characteristics showed 51.5%. The explanatory power was much improved up to 65.2% when the third stage model incorporated the outcome of medical care performance. When the return on investment(ROI) was examined by using the multi-variate linear regression analysis at the final model of third stage, it was found that ROI had a positive relationship with the increase rate of patients, labor costs per doctor, and medical care rate of socially protected inpatients. However, it revealed that ROI had a negative relationship with the ratio of labor costs, the number of patients per managerial staff, and occupancy rate of rooms, respectively. The research suggests that in order for LPHs to increase profitability, LPH, should make efforts not only to attract patients to the hospitals without any discrimination of the patients depending on their financial status, but also to develop efficient management methods to reduce labor costs.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.4
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• pp.107-121
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• 2015

Diffusion of innovation is the process in which an innovation is communicated through certain channels over time among the members of a social system. The literatures have emphasized the importance of interpersonal network influences on individuals in convincing them to adopt innovations and thereby promoting its diffusion. In particular, the behavior of opinion leaders who lead in influencing others' opinion is important in determining the rate of adoption of innovation in a system. Centrality has been recognized as a good indicator that quantifies a node's influences on others in a given network. However, recent studies have questioned its relevance on various different types of diffusion processes. In this regard, this study aims at examining the effect of a node exhibiting high centrality on expediting diffusion of innovations. In particular, we considered the situation where two innovations compete with each other to be adopted by potential adopters who are personally connected with each other. In order to analyze this competitive diffusion process, we developed a simulation model and conducted regression analyses on the outcomes of the simulations performed. The results suggest that the effect of a node with high centrality can be substantially reduced depending upon the type of a network structure or the adoption thresholds of potential adopters in a network.