• Food Science and Preservation
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• v.11 no.1
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• pp.122-125
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• 2004

Factor analysis is estimated using housewives's intention data in Seoul province. Rice consumers considered safety, high nutritive value, shape and cultivation region as important factors in buying rice. The factors of food safety are brand and quality certification mark. The differences of two housewife groups on safety factor are caused by residence type, employment existence and residence region. The marketing strategies for rice containing food safety target housewives living in apartment, Gang Nam region. Also selling extension for target consumers housewives should be employed.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.463-483
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• 2019

Since 2000, Korea's total fertility rate (TFR) has been different from that of Japan, Germany, and France where irreversible constants do not change easily in the fertility rate increasing or decreasing phase. It also showed a gradual increase from the minimum fertility level 1.08 in 2005 to 1.23 in 2015, which dropped to 1.17 in 2016, to 1.05 in 2017 and to 0.98 in 2018. This is similar to a double dip in the economic status of a recession. This paper investigates such a TFR increase and decrease factor that predicts the number of births affecting TFR, examines trends in the proportion of married and marital fertility rate broken down by TFR decomposition method. We also examined how these changes affect the change in TFR. According to the results, the number of births is estimated to be between 320 and 330 thousand in 2018, 300 thousand in 2020, 230 and 240 thousand in 2025. The proportion of married is steadily decreasing from 1981 to 2025, and the marital fertility rate is predicted to decline until 2002, then increase from 2003 to 2016 and decrease from 2017 to 2025. Finally, the trend of TFR in terms of number of births, TFR decomposition and statistical model is expected to show 0.98 in 2018, 0.93 to 1.11 in 2020 and 0.76 to 1.08 in 2025.

• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.555-563
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• 2019

Reduced thickness of the water pipes due to corrosion makes it difficult to perform the original functions since corrosion in metallic water pipes can occur over time. In this study, reliability model that can estimate the probability of pipe breakage is developed regarding corrosion depth increment according to service year. Probability of pipe breakage was calculated by FORM(First Order Reliability Method) and unsteady analysis was performed to analyze the statistical properties of water pressure. And KCIP(Korea Cast Iron Pipe) equation was adopted for the reliability function. Furthermore, change of pipe thickness was estimated by Nahal and Khelif equation and Romanoff equation. Therefore, pipe thickness was calculated due to change of corrosion depth and probability of pipe breakage was calculated and compared with 10, 20, 30 service years. From the results, probability of pipe breakage for network A is gradually increased from 6.8% to 8.6% according to service year of 10, 20, 30 when Nahal and Khelif equation is applied. And probability of pipe breakage for network A is also gradually increased from 6.4% to 8.9% according to service year of 10, 20, 30 when Romanoff equation is applied.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.201-221
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• 2019

The Korea Institute of Civil Engineering and Building Technology provides the documents and information on the construction technology through the Construction Technology Digital Library System to enhance the technological competitiveness of the construction engineers. The purpose of this study is to measure the monetary value of information service quality in order to improve the documents and information service quality provided by this system. For this purpose, a questionnaire model was designed to apply the DBDC- CVM. We surveyed the members of 300 this systems for the amount of information that they are willing to pay to maximize the quality of information service. The correlation between the dependent variable and the explanatory variables was analyzed with the basic statistics of the survey results. The independent variables affecting the dependent variable are statistically significant. The logit model is used to estimate the monetary value of individual respondents who are willing to pay for information service quality. In previous research, we measured the use value of information service. On the other hand, this study shows that the measurement of value based on information service quality is different from previous research.

• Korean Journal of Cognitive Science
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• v.32 no.2
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• pp.55-73
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• 2021

Psychological essentialism states that people believe some categories to have hidden and defining essential features which cause other features of the category (Gelman, 2003; Hirschfeld, 1996; Medin & Ortony, 1989). Essentialist belief on categories questions the Roschian argument (Rosch, 1973, 1978) that categories merely consist of clusters of correlated features. Unlike family resemblance categories, essentialized categories are likely to have clear between-category boundaries and high within-category coherence (Gelman, 2003; Prentice & Miller, 2007). Two experiments were conducted to test the effects of essentialist belief on category representation (i.e., between-category boundary, within-category coherence). Participants learned family resemblance and essentialized categories in their assigned conditions and then performed categorization task (Expt. 1) and frequency estimation task of category exemplars (Expt. 2). The results showed, in essentialized categories, both boundary intensification and greater category coherence. Theses results are likely to have arisen due to increased cue and category validity in essentialized categories and suggest that essentialist belief influences macroscopic representation of category structure.

• Knowledge Management Research
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• v.22 no.2
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• pp.247-268
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• 2021

Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.206-216
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• 2020

As the number of aging railway bridges in Korea increases, maintenance costs due to aging are increasing and continuous management is becoming more important. However, while the number of old facilities to be managed increases, there is a shortage of professional personnel capable of inspecting and diagnosing these old facilities. To solve these problems, this study presents an improved model that can detect Local damage to structures using machine learning techniques of AI technology. To construct a damage detection machine learning model, an analysis model of the bridge was set by referring to the design drawing of a non-ballasted plate-girder railroad bridge. Static strain data according to the damage scenario was extracted with the analysis model, and the Local damage index based on the reliability of the bridge was presented using statistical techniques. Damage was performed in a three-step process of identifying the damage existence, the damage location, and the damage severity. In the estimation of the damage severity, a linear regression model was additionally considered to detect random damage. Finally, the random damage location was estimated and verified using a machine learning-based damage detection classification learning model and a regression model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.477-483
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• 2021

In a military maintenance system, the standard maintenance man-hour of weapon systems is a tool to estimate the maintenance capabilities of maintenance units, provide standards for determining the maintenance needs and workload, and provide basic data for establishing a maintenance plan. The standard maintenance man-hours of major weapon systems have already been derived and used, but the standard maintenance man-hour in a wartime maintenance environment has not been computed. Therefore, the standard wartime maintenance man-hours need to be derived and This study proposes a process and method of computing the maintenance man-hours. In addition, this work suggests the criteria of collecting and screening data that is necessary for estimating the standard maintenance man-hours and introduces a methodology for analyzing the characteristics of maintenance man-hour distribution in the process. The proposed process first designs a model that reflects the wartime maintenance environment, selects statistical techniques, collects maintenance data, analyzes the descriptive statistics, estimates the distribution, and finally presents representative values of maintenance man-hour. Based on the proposed method, the standard wartime maintenance man-hours of the four weapon systems were calculated, and the distribution of the maintenance man-hours was analyzed to follow a lognormal distribution, and the method presented reliable results.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.41-49
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• 2022

The average acoustic distribution of American English speakers was statistically compared with the English-speaking patterns of gifted students in a Science Academy in Korea. By analyzing speech recordings, the duration time of which is much longer than in previous studies, this research identified the degree of acoustic proximity between the two parties and the predictability of English academic achievement of gifted high school students. Long-term spectral acoustic power distribution vectors were obtained for 2,048 center frequencies in the range of 20 Hz to 20,000 Hz by applying an long-term average speech spectrum (LTASS) MATLAB code. Three more variables were statistically compared to discover additional indices that can predict future English academic achievement: the receptive vocabulary size test, the cumulative vocabulary scores of English formative assessment, and the English Speaking Proficiency Test scores. Linear regression and correlational analyses between the four variables showed that the receptive vocabulary size test and the low-frequency vocabulary formative assessments which require both lexical and domain-specific science background knowledge are relatively more significant variables than a basic suprasegmental level English fluency in the predictability of gifted students' academic achievement.