• Journal of Korea Port Economic Association
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• v.22 no.4
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• pp.59-79
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• 2006

In this paper, we analyse the comparative competitiveness of the 10 major logistic hub cities in China. First, using the input distance function, we calculated the technical efficiencies and the opportunity costs of the transport infra structure investments. Then, based on not only these supply side factors but also demand side, the overall comparative competitiveness by cities are analyzed. Our main findings are as follows: early developed, larger cities such as Shanghai, Guangzhou, Shenzhen are technically efficient but their opportunity costs of the additional transport investments are higher than the other cities. We also found that overall competitiveness of these larger and leading logistic hub cities are dominant over the small and newly developed logistic cities.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.261-264
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• 2006

소프트웨어 개발 후 인도 전 테스트 단계중에 발생되는 테스트 노력 소요량을 고려한 소프트웨어 신뢰도 성장 모델을 제시하여 테스트 노력소요량 동태를 시간함수인 로지스틱 곡선으로 설명한다. 그러므로, 본 논문에서는 로지스틱 테스트노력 곡선이 소프트웨어의 개발/테스트 노력곡선으로 적절하게 표현될 수 있다는 것과 실제 데이터를 근거로 하여 적용하여서 예측성이 매우 좋은 능력을 가지고 있다는 것을 보이고자 한다.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.3
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• pp.239-246
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• 2003

Individual items are produced continuously from an industrial process. Each item is checked to determine whether it satisfies a lower screening limit for the quality characteristic which is the weight of an expensive ingredient. If it does, it is sold at a regular price; if it does not, it is reprocessed or sold at a reduced price. The process mean may be adjusted to a higher value in order to reduce the proportion of the nonconforming items. Using a higher process mean, however, may result in a higher production cost. In this paper, the optimal process mean and lower screening limit are determined in situations where the probability that an item functions well is given by a logistic function of the quality characteristic. Profit models are constructed which involve four price/cost components; selling prices, cost from an accepted nonconforming item, and reprocessing and inspection costs. Methods of finding the optimal process mean and lower screening limit are presented and numerical examples are given.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.6
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• pp.180-189
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• 2012

This study was carried out to suggest an experiment based for selecting Sedum, which can adapt well with heat tolerance in extensive green roof system. The heat tolerance of Sedum subject to laboratory high temperature treatment and heat processing time were evaluated using electrolyte leakage, chlorophyll content and regrowth test, and the relation between soil water content and heat tolerance were researched. Logistic model of nonlinear regression analysis was used to evaluate the lethal temperatures that were predicted with the range of $45.0{\sim}48.1^{\circ}C$(soil water content 5%), $47.5{\sim}49.3^{\circ}C$(10%), $48.6{\sim}52.8^{\circ}C$(15%) in 6-hours high-temperature treatment. The higher the soil water content, the stronger the heat resistance property of Sedum. there is. The higher the treatment temperature, the lower the chlorophyll content, and the less the soil water content, the faster the chlorophyll decomposition. The order of hot-temperature resistance was S. reflexum>S. takevimense>S. middendorffianum>S. album>S. sieboldii>S. spurium when soil water content was 5%. The order of hot-temperature resistance was S. album>S. reflexum>S. spurium>S. takevimense>S. middendorffianum>S. sieboldii when soil water content was 15%. The more of soil water content, S. album, S. reflexum, S. spurium had stronger tolerant of hot temperature. These results were consistent with those from the regrowth test and the heat tolerance tested by electrolyte leakage evaluation.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.61-73
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• 2009

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or Logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimater and maximum likelihood estimater for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.137-146
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• 2023

The dropout of university freshmen is a very important issue in the financial problems of universities. Moreover, the dropout rate is one of the important indicators among the external evaluation items of universities. Therefore, universities need to predict dropout students in advance and apply various dropout prevention programs targeting them. This paper proposes a method to predict such dropout students in advance. This paper is about a method for predicting dropout students. It proposes a method to select dropouts by applying logistic regression using a shift sigmoid classification function using only quantitative data from the first semester of the first year, which most universities have. It is based on logistic regression and can select the number of prediction subjects and prediction accuracy by using the shift sigmoid function as an classification function. As a result of the experiment, when the proposed algorithm was applied, the number of predicted dropout subjects varied from 100% to 20% compared to the actual number of dropout subjects, and it was found to have a prediction accuracy of 75% to 98%.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.323-336
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• 2002

In this paper we consider the modified continual reassessment method in which a cohort consists of three patients. Simulation has been a main research tool in the investigation of CRM. In this paper we propose complete enumeration as an alternative of simulation. Using new method we show that the expected toxicity rate at the MTD converges to the target toxicity rate well as the sample size increases.