• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.7
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• pp.1247-1257
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• 1997

The purpose of this study was to classify size specifications of Korean adult male for the men's ready·made garments, especially jacket and dress shirts. Concept of the comfort and fitness has become a major concern in the basic function of the ready-made garments. Data were collected by the real anthropometric measurement and by the photographic sources. Sample size was 1.290 subjects as the sample and their age range was from 19 to 54 pean old by the stratified sampling method. 66 variables from the direct anthropometric data in total were applied to analyze. ANOVA in SAS package was applied to the data and the expected frequency distribution of 10.000 men was calculated by the extraction of density function. Control dimensions for jacket and dress shirts has been designated by Bcorean Apparel Sizing System (KS-K). Therefore this study was performed to classify size specifications by the control dimensions and at the same interval of KS-K. The drop values of 15, 12 and 9 has the high coverage rate of 22.1%, 21.0% and 18.8% respectively and are composed of the majority of 61.9% of the subjects. According to the drop values, size specifications and distribution of control and reference dimensions are predicted. About 65.75% of the expected frequency distribution without stature were covered by 19 size specification.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.769-778
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• 2020

The purpose of this study was to examine the role of profitability as a mediating variable in influencing firm value. This study uses a sample of manufacturing companies listed on the Indonesia Stock Exchange from 2016 to 2018. The data used is panel data, with data analysis using multiple regression. Based on the Sobel test, profitability plays a role in mediating the effect of firm size on firm value. The effect of firm size on firm value is indirect, however, through profitability. Therefore, the market price of the shares of large-scale companies will increase if the resulting profitability is high. The capital structure and managerial ownership directly influence firm value. The results showed that managerial ownership and firm size had a positive effect on profitability, while capital structure had no effect on profitability. Capital structure and managerial ownership have a negative effect on firm value, while firm size and profitability have a positive effect on firm value. The main finding of this study is that profitability acts as an intervening variable in mediating the relationship between firm size and firm value.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.1
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• pp.80-89
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• 2021

In Korea, marine fish landed at ports are randomly sampled on a periodic basis (e.g., daily or weekly), and body sizes (e.g., lengths and weights) of those sampled fish are measured. The motivation for our study is whether or not such measurements reflect the size distribution, especially the length distribution of fish landed (= a population), because such length measurements are key data for a length-based assessment model. The current sampling method is to sample fish landed at ports by body size group (e.g., very small, small, medium, large, very large), using the sampling weights as the number of boxes by body size group. In this study, we showed that length composition data about fish sampled by the current method did not represent the length frequency distribution of the fish landed, and suggested that an alternative sampling method should be applied of using the sampling weights as the number of fish landed by body size group. We also introduced a method for determining an appropriate sample size.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.547-559
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• 2023

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.594-596
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• 2003

Due to the fact that the composition and variability of aerosols is considered rather complex, it is difficult to employ a simple and straightforward physical model in calculating the aerosol size distribution in the absence of actual data. This complicates the already difficult retrieval of various atmospheric parameters from remotely sensed data. Thus, the main purpose of this study is trying to find an effective aerosol size coefficient that is stable, and can depict the particle size distribution. This paper also attempts to construct an 'effective aerosol size coefficient' database for each respective season, where it can quickly and effectively supply pertinent information of the atmosphere's opacity.

• Journal of Korea Technology Innovation Society
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• v.2 no.2
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• pp.169-186
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• 1999

This study empirically investigates innovative behaviors of the firm. In so doing, a Probit was employed and estimated. We used the raw data of the "corporate innovation survey"(CIS), which, in consent with OECD efforts, is regularly undertaken by the Science and Technology Policy Institute(SIEPI). The data set includes more than 3400 firms in the manufacturing sector. Three types of innovation, i.e., new product, product improvement and process innovation, are studied, assuming that determinants of innovation are firm′s age. number of employees as the size of firm, ratio of foreign ownership and innovation costs. To investigate the relationship between firm′s innovation behavior and the size, we estimate the Probit including the quadratic term of the firm size. Empirical findings showed that the sign of the quadratic term of the firm size turned out to be negative. It means that the probability of firm's making innovation shows the inversed-U relationship with the firm size. Such an empirical result may have a significant implication for the industrial policy.

• Proceedings of the Korea Concrete Institute Conference
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• 1998.04a
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• pp.321-326
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• 1998

Shear failure of reinforced concrete beams is serious problem due to sudden brittle failure and many experimental results proved that size effect in shear behavior is an important feature of reinforced concrete members. For this reason, the structural safety of the reinforced concrete beams for shear has been checked by applying empirical design formula, which includes the size-effect, derived from experimental data. However, as the sizes of reinforced concrete members become extremely large, experiments sometimes become very difficult so that the formula or the experimental data could not be obtained and size-effect analyses of shear behavior become significant. In this study, size-effect analysis of shear behavior in reinforced concrete beams is performed by modeling tension stiffening/shear stiffening on reinforced concrete and the tension softening/shear softening on plain concrete. Then, the influences of models in the size-effect analyses of shear behavior in reinforced concrete beams are analyzed.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.3
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• pp.177-183
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• 2022

To measure the size and weight of the fish, we developed an automatic fish size measurement system using a deep neural network, where the YOLO (You Only Look Once)v3 model was used. To detect fish, an IP camera with infrared function was installed over the fish pool to acquire image data and used as input data for the deep neural network. Using the bounding box information generated as a result of detecting the fish and the structure for which the actual length is known, the size of the fish can be obtained. A GUI (Graphical User Interface) program was implemented using LabVIEW and RTSP (Real-Time Streaming protocol). The automatic fish size measurement system shows the results and stores them in a database for future work.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.33-43
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• 2002

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.521-530
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• 2021

Objectives: This was to examine and explore the elements of Size Korea 6th 3D head anthropometric database and to provide basic information for the selection of respirators in Korea. Methods: This was a pilot study for the first year of work in a two-year-project initiated at KOSHA in 2021. 3D head dimensions data were obtained from the Size Korea Center managing the Size Korea 6th 3D national anthropometry survey databases. The 3D head dimensions data, including 45 dimensions, were used in line with ISO standards (e.g., ISO/TS 16976-2) for examinations, comparisons, statistical analyses, etc. Results: A total of 3,088 subjects were finally determined in this study. The main features were: Male subjects were 52.5%; the highest age group was 15-29 at 36.7%; unhealthy weight group based on BMI was 31.7%; and survey area was the capital region. For the 6th 3D head dimensions data with 45 items, the means and standard deviations for 'Face length' were 115.9±7.5 cm for males and 107.3±6.9 cm for females respectively while those for 'Face width' item were not available since there was no such item in the data. Numerous findings were discussed accordingly. Conclusions: This study showed that there were likely requirements for improvements in the 6th 3D head anthropometric data as follows: Standardization of Korean and English terms; addition of head dimensions items missed in the Size Korea survey; and reliability of generalizability for subjects, suggesting that the study results can be used for further studies or improvement of respirator selection in Korea.