• 한국시뮬레이션학회논문지
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• 제2권1호
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• pp.46-54
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• 1993

Analytic and simulation models for prioritized token ring are presented in this paper. Its protocol is based on prioritized token ring with reservation (R-PTR). Since the protocol of the R-PTR is simple and the performance of the R-PTR is not inferior to that of the IEEE-PTR under almost all traffic load environments, we use the R-PTR as our token ring model. By using the properties of Markovian process, the expressions for average throughput and average packet transmission delay are derived. The results obtained from the analytic model are compared with that of the discrete event simulation model.

• Journal of Microbiology and Biotechnology
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• 제20권4호
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• pp.737-748
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• 2010

Glutaminase production in Zygosaccharomyces rouxii by solid-state fermentation (SSF) is detailed. Substrates screening showed best results with oatmeal (OM) and wheatbran (WB). Furthermore, a 1:1 combination of OM:WB gave 0.614 units/gds with artificial sea water as a moistening agent. Evaluation of additional carbon, nitrogen, amino acids, and minerals supplementation was done. A central composite design was employed to investigate the effects of four variables (viz., moisture content, glucose, corn steep liquor, and glutamine) on production. A 4-fold increase in enzyme production was obtained. Studies were undertaken to analyze the time-course model, the microbial growth, and nutrient utilization during SSF. A logistic equation ($R^2$=0.8973), describing the growth model of Z. rouxii, was obtained with maximum values of ${\mu}_m$ and $X_m$ at $0.326h^{-1}$ and 7.35% of dry matter weight loss, respectively. A goodfit model to describe utilization of total carbohydrate ($R^2$=0.9906) and nitrogen concentration ($R^2$=0.9869) with time was obtained. The model was used successfully to predict enzyme production ($R^2$=0.7950).

• 대한산업공학회지
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• 제41권5호
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• pp.425-438
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• 2015

This study proposes a three-stage model of R&BD performance which captures commercialization outcomes as well as conventional R&D performance. The model is composed of three factors : inputs (R&D budgets and researchers), outputs (patents and papers), and outcomes (technical fees, products sales, and cost savings). Three stages are defined for each transformation process between the three factors : efficiency stage from input to output (stage 1), effectiveness stage from output to outcome (stage 2), and productivity stage from input to outcome (stage 3). The performance of each stage is measured by data envelopment analysis (DEA). DEA is a non-parametric efficiency measurement technique that has widely been used in R&D performance measurement. We measure the performance of 171 projects of 6 public R&BD programs managed by Seoul Business Agency using the proposed three-stage model. In order to provide a balanced and holistic view of R&BD performance, the R&BD performance map is also constructed based on performance of efficiency and productivity stages.

• 시스템엔지니어링학술지
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• 제16권1호
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• pp.1-8
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• 2020

In this paper we proposed to develop the reliability growth planning for the One-shot system using the PM2-Discrete model. The PM2-Discrete is the methodology specifically developed for discrete systems and is the first quantitative method available for formulating detailed plans in the discrete usage domain. First, the parameters RG, RI, T, MS and d of the PM2-Discrete model are set. Second, the case analysis was performed on One-shot system A. Third, the input parameter values were applied to drive the R(t) equation. Finally, using RGA 11 Software, the reliability Growth Planning Curve of One-shot system A was constructed. Also, the sensitivity analyses are performed for the changes of model parameters. The results of this study can be usefully used in establishing the reliability growth planning curve of the One-shot system.

• 운동과학
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• 제21권2호
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• pp.231-242
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• 2012

본 연구의 목적은 운동부하검사에서 일반적으로 많이 사용하는 Bruce protocol을 이용한 최대하 운동의 대사반응, 주요 시점의 심박수 기록 및 1,200 m 달리기 기록을 이용하여 최대산소섭취량을 추정하는 모형을 개발하고 모형간 추정의 타당도를 분석하는 데 있다. 연구대상은 성인 남성 255명(1,200 m 달리기는 133명)이며 Bruce protocol을 이용하여 최대운동부하검사를 실시하였고, 3분인 1단계와 6분인 2단계 종료 시점의 대사반응을 측정하였다. 측정항목은 VO₂(㎖㎖/kg/min), VCO₂(㎖/kg/min), VE(L/min) 및 HR(bpm), HR가 150 bpm과 170 bpm에 도달하는 시간, Bruce protocol 6분과 3분 심박수 차이, 1,200 m 달리기 기록 등이었다. 신체자료와 최대하 운동 중 대사반응을 이용하여 최대산소섭취량을 산출하는 모형을 개발하기 위하여 다중회귀분석을 실시하였다. 모든 변수를 동시투입법으로 분석한 전체모형의 R은 0.642이고(p<.01) 추정의 표준오차(SEE)는 4.38 ㎖/kg/min, 변동계수(CV)는 10.8%이었으나(p<.01), 다중공선성이 나타났다. 단계별분석법으로 분석한 3분모형1과 모형2의 R은 0.341과 0.461이고, SEE는 6.05와 5.72 ㎖/kg/min, CV는 14.9와 14.1%로 나타났고(p<.01), 다중공선성이 나타나지 않았다. 6분모형1과 모형2의 R은 0.350과 0.456이었고(p<.01), SEE는 6.03과 5.74 ㎖/kg/min, 변동계수(CV)는 14.9와 14.2%로 나타났으며(p<.01), 다중공선성이 나타나지 않았다. 6분HR-3분HR 모형의 R은 0.150, HR150모형은 0.151, HR170모형은 0.154로 나소 낮게 나타났고, SEE는 6.36~6.37 ㎖/kg/min으로 유사하게 나타났고, CV도 15.7%로 유사하게 나타났다. 1,200 m 달리기 모형의 R은 0.444이고, SEE는 4.82 ㎖/kg/min, CV는 11.9%로 나타났다. 결론적으로 Bruce protocol을 이용하여 실시한 최대산소섭취량 추정 방법 중 실용적인 유용성과 간편성을 고려하면 대사반응을 이용한 6분모형과 3분모형이 적합한 모형으로 나타났고, 심박수 모형과 달리기 모형은 추정의 정확도가 다소 낮게 나타났다.

• 한국경영과학회지
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• 제23권1호
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• pp.43-65
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• 1998

This paper develops a two-echelon inventory model with time-weighted partial backorders. The presented model assumed to follow continuous review (Q. r) policy for both the retailers and the central warehouse under stochastic demand. A heuristic method to find an optimum-tending solution for total variable system cost per year incurred at the central warehouse and retailers in a system is suggested. To show the usefulness of the above model, numericla examples are illustrated for verification and validation purpose.

• 대한방사선기술학회지:방사선기술과학
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• 제43권6호
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• 기술혁신연구
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• 제10권2호
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• pp.91-105
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• 2002

This paper extends the empirical analysis on R&D based growth model so that the nonstationary panel unit root testing methods can be used to distinguish the exogenous growth model and R&D based growth model for the 1981-1999 period with fourteen OECD economies including Korea. Our results show that first, using U.S. and Group mean as benchmarking, the stochastic R&D productivity convergence to benchmarking is not supported in our data set. Second, the empirical results for stochastic nonconvergence to the U.S. or group mean also are robustness to panel unit root methods. We, therefore, find strong support for the implications for R&D based growth model.

• Journal of Applied and Pure Mathematics
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• 제4권1_2호
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• pp.27-36
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• 2022

An innovation diffusion model is proposed model consists of three classes, namely, a non-adopter class, adopter class innovation-I, and adopter class innovation-II in a partially competitive and cooperative market. The proposed model is analyzed with the help of the qualitative theory of a system of ordinary differential equations. Basic influence numbers associated with first and second innovation $R_{0_1}$ and $R_{0_2}$ respectively in the absence of each other are quantified. Then the overall basic influence number (R₀) of the system is assessed for analyzing stability in the market in different situations. Sensitivity analysis of basic influence numbers associated with first and second innovation in the absence of each other is carried out. Numerical simulation supports our analytical findings.

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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• pp.63-85
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• 2016

Purpose While the popularity of C2C auction platforms such as eBay is gradually decreased, this domain is still undermined to explain online bidding behaviors. Online bidders sometimes engage in impulsive bidding due to some of the online auction characteristics. Therefore, this study develops and tests a model of the impulsive bidding exhibited by online bidders in C2C auction platforms. Based on S-O-R framework, our model posits that both perceived time-pressure and competition intensity affect cognitive absorption which ultimately influences the impulsive bidding. Design/methodology/approach This study collected survey data from 214 C2C auction participants, who have prior experience on impulsive bidding and tested both measurement model and structural model by using CB-SEM (covariate-based structural equation modelling) technique. In this study, by using AMOS 20.0, we tested the measurement model for its overall fit, item reliability, and validity and further conducted the structural model to test our proposed hypotheses. Findings Based on our results, we found that perceived tim-pressure and competition intensity were positively related to cognitive absorption. We also found that the cognitive absorption was positively associated with impulsive bidding behavior. In this study, by developing our research model in S-O-R framework, we provide an alternative theoretical mechanism to describe online impulsive bidding behavior.