• Journal of the Korean Home Economics Association
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• v.20 no.4
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• pp.83-89
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• 1982

The purpose of this study was to analyze the 45 measuring items for the clothing construction in order to observe the factorial structure of items and to extract the common factor and the special unique factor from data. The sample for the study was drawn randomly out of senior high schoolgirls in Seoul urban area. The size of sample was 301 girls between age 16 and 18. The method of analysis was applied by the principal component analysis with orthogonal rotation after extraction of 9 major factors. All of the above data was analyzed by the computer installed at Seoul National University. From these analyses, the major findings can be summerized as follows: 1. The results of factor analysis generally indicated that the first factor was clustered with 15 items, length measures and height measures. The eigenvalue of the first factor was 16.5 and the cumulative percentage of variables 36.6%. 2. The second factor was clustered with width measures, girth measures and weight of 19 items. The eigenvalue of the second factor was 6.5 and the cumulative percentage of variables 51.0%.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.203-223
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• 2022

We propose a Bayesian approach to cumulative logistic regression model for the ordinal response based on the orthogonal principal components via singular value decomposition considering the multicollinearity among predictors. The advantage of the suggested method is considering dimension reduction and parameter estimation simultaneously. To evaluate the performance of the proposed model we conduct a simulation study with considering a high-dimensional and highly correlated explanatory matrix. Also, we fit the suggested method to a real data concerning sprout- and scab-damaged kernels of wheat and compare it to EM based proportional-odds logistic regression model. Compared to EM based methods, we argue that the proposed model works better for the highly correlated high-dimensional data with providing parameter estimates and provides good predictions.

• Journal of Korea Water Resources Association
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• v.39 no.9 s.170
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• pp.767-777
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• 2006

The goal of this study is to improve Huff's method which is the most popular method for rainfall time distribution in Korea. As the first step, we reevaluated the context of Huff's original research motivations, geography and rainfall pattern of study area, and compared that to Korean situations. In original Huff's results, no change in temporal distribution characteristics were found for different rainfall durations. This was found to be different from Korean situations. Furthermore, results from the MOCT(Ministry of Construction and Transportation) version of Huff's method is on a gage basis not on a watershed basis, thus making it difficult to select cumulative rainfall curves representative of a watershed. In addition, all rainfall data regardless of their magnitude were used in the MOCT version of Huff' method which is different from original Huff's which screened out data by using a threshold value of 25.4mm. For both point and areal mean rainfall, time distribution characteristics of rainfall for various durations were found to be different. This was statistically proven by K-S test at 5% significance level as some cumulative rainfall curves developed from the rainfall data of certain durations were found to be not significant with cumulative rainfall curves developed from the rainfall data of all durations. Therefore, in order to apply Huff's method to Korean situations, it is recommended that dimensionless cumulative curve must be developed for various rainfall duration intervals using rainfall data greater than a certain threshold value.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.1
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• pp.75-85
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• 2021

Evaluating the quantitative damage to rocks through acoustic emission (AE) has become a research focus. Most studies mainly used one or two AE parameters to evaluate the degree of damage, but several AE parameters have been rarely used. In this study, several data-driven models were employed to reflect the combined features of AE parameters. Through uniaxial compression tests, we obtained mechanical and AE-signal data for five granite specimens. The maximum amplitude, hits, counts, rise time, absolute energy, and initiation frequency expressed as the cumulative value were selected as input parameters. The result showed that gradient boosting (GB) was the best model among the support vector regression methods. When GB was applied to the testing data, the root-mean-square error and R between the predicted and actual values were 0.96 and 0.077, respectively. A parameter analysis was performed to capture the parameter significance. The result showed that cumulative absolute energy was the main parameter for damage prediction. Thus, AE has practical applicability in predicting rock damage without conducting mechanical tests. Based on the results, this study will be useful for monitoring the near-field rock mass of nuclear waste repository.

• Journal of Distribution Science
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• v.20 no.9
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• pp.73-81
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• 2022

Purpose: This study aimed to examine whether key audit matters (KAMs) readability influences investor reaction. Research design, data, and methodology: The signaling theory was applied to explain the behavior of investors when they receive useful information for their decisions. Data were collected from 1,866 firm-year observations from Thai listed companies in both the Stock Exchange of Thailand (SET) and the Market for Alternative Investment (MAI) for the fiscal years of 2016-2019. The study was based on secondary data, which were collected from the SET Market Analysis and Reporting Tool (SETSMART) database and the Stock Exchange of Thailand's website (www.set.or.th). A statistical regression method was used with panel data analysis to evaluate possible associations between KAMs readability and investor reaction. The study relied on popular readability measures (Fog Index). Moreover, investor reaction was measured by absolute cumulative abnormal return and abnormal trading volume. Results: It was found that the KAMs readability has positive significance on both absolute cumulative abnormal return and abnormal trading volume. Conclusion: This study showed a significant contribution to the implication of KAMs in an emerging economy. The results reveal that more readable KAMs disclosure distributed new insights and useful information to investors and led to reducing the information gap between auditors and investors.

• KIEAE Journal
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• v.4 no.4
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• pp.11-18
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• 2004

In this study, the measurement system was developed for the measurement of pollutants from building materials, and specimens were made with concrete, gypsum board, mortar and wall paper. Characteristics of VOCs and TVOC concentration and Emission Factor as a function of time were assessed, and the conclusion was drawn as follows. (1) From predicting TVOC concentration decrease of specimen 7 with the wall paper attached to the concrete, the graph may become linear by converting the value of y-axis into the log function, and the prediction equation can be expressed as $y=34906{\ast}e^{-0.0093{\ast}time}$. Moreover, chi-square value was 0.83 which is relatively high value, indicating that TVOC concentration can be properly predicted if the same materials are used indoors. (2) From predicting VOCs Emission Factor decrease of specimen 7, the prediction equation can be expressed as $EF=15111{\ast}e^{-0.0093{\ast}time}$, and chi-square value was 0.83. (3) From predicting TVOC concentration decrease of specimen 7, prediction equation can be considered to be $y=254323{\ast}(1-e^{-0.1046{\ast}time})$, and chi-square was 0.994 which is significantly high value, indicating that indoor TVOC concentration can be properly predicted if the same materials are used indoors. Furthermore, the prediction of concentration decrease using cumulative value of hourly measured concentration is considered to be more accurate than that using just hourly measured value directly. (4) From predicting Emission Factor decrease with cumulative hourly data of Emission Factor, chi-square appeared to be higher than that by just using hourly data of Emission Factor directly. Therefore, the prediction of Emission Factor with cumulative hourly data can provide more reliable prediction equation than the case by using just hourly concentration directly.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.187-193
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• 2006

This paper shows how to use continuation-ratio logits for the analysis of structured polytomous data. Here, response categories are considered to have a nested binary structure. Thus, conditionally nested binary random variables can be defined in each step. Two types of factors are considered as independent variables affecting response probabilities. For the purpose of analyzing categorical data with binary nested strutures a continuation-ratio mixed model is suggested. Estimation procedure for the unknown parameters in a suggested model is also discussed in detail by an example.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.2
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• pp.156-161
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• 2012

Marine biomass is considered an important substrate for anaerobic digestion to recovery energy i.e. methane. Nevertheless, marine biomass has attracted little attention by researchers compared to terrestrial feedstock for anaerobic digestion. In this study, biochemical methane potential (BMP) test was used to evaluate generation of renewable energy from starfish. A cumulative biogas yield of $748{\pm}67mL\;g^{-1}VS^{-1}$ was obtained after 60 days of digestion. The cumulative methane yield of $486{\pm}28mL\;CH_4\;g^{-1}VS^{-1}$ was obtained after 60 days of digestion. The methane content of the biogas was approximately 70%. The calculated data applying the modified Gompertz equation for the cumulative $CH_4$ production showed good correlation with the experimental result obtained from this batch study. Since the result obtained from this study is comparable to results with other substrates, marine biomass can be co-digested with food waste or swine wastewater to produce $CH_4$ gas that will help to reduce the gap in global energy demand.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.583-591
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• 2004

In this study, methodologies for the rational organization of air pollution monitoring network were examined by understanding the characteristics of temporal and spatial distribution of secondary air pollution, whose significance would increase hereafter. The data on $O_3$ and $NO_2$ concentrations during high ozone period in 1998~1999 recorded at the nine air pollution monitoring station in Busan were analysed using principal component analysis (PCA) and cumulative semivariogram. It was found that the ozone concentration was deeply associated with the daily emission characteristics or the $O_3$ precusors, and nitrogen dioxide concentration largely depends on the emission strength of regional sources. According to the spatial distribution analysis of ozone and nitrogen dioxide in Busan using cumulative semivariograms, the number of monitoring stations for the secondary air pollution can be reduced in east-west direction, but reinforced in north-south direction to explain the spacial variability. More scientific and rational relocation of air pollution monitoring network in Busan would be needed to investigate pollution status accurately and to plan and implement the pollution reduction policies effectively.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1057-1065
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• 2010

In this paper we discuss some cautionary notes in using the Pearson chi-squared test statistic for the goodness-of-fit of the ordinal response model. If a model includes continuous type explanatory variables, the resulting table from the t of a model is not a regular one in the sense that the cell boundaries are not fixed but randomly determined by some other criteria. The chi-squared statistic from this kind of table does not have a limiting chi-square distribution in general and we need to be very cautious of the use of a chi-squared type goodness-of-t test. We also study the limiting distribution of the chi-squared type statistic for testing the goodness-of-t of cumulative logit models with ordinal responses. The regularity conditions necessary to the limiting distribution will be reformulated in the framework of the cumulative logit model by modifying those of Moore and Spruill (1975). Due to the complex limiting distribution, a parametric bootstrap testing procedure is a good alternative and we explained the suggested method through a practical example of an ordinal response dataset.