• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.375-401
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• 2023

A school library is where students develop their skills to cope with future uncertainty and can utilize various information materials to build their capability and response abilities to changes. Teachers' perception is crucial as their guidance is essential for the student to use the school library. Most studies, however, focused on quantitative measurement of the importance of the teachers' perception as an external environment, and there is a lack of specific categorization of different types of perceptions on the role of the school library. This study aims to examine types of perceptions about the school library among elementary school teachers. To do so, this study used Latent Profile Analysis (LPA), a person-centered approach, to identify teachers' complex perceptions about the role and importance of the school library, which were difficult to review in previous studies, and the teachers' most representative types of perceptions. Based on the findings from the above, this study is meaningful in proposing customized measures to operate and promote the school library depending on teachers' perceptions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.5 s.96
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• pp.455-464
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• 2005

We have proposed a model of a thermal voltage converter(TVC) using the trans-impedance of lossy transmission line and developed a calculation program for ac-dc transfer difference of the TVC. The proposed TVC consists of a thermo-element(f) and a range resistor wire connected in series at the center of coaxial cylinder. The range resistor wire is used to extend the measurement range of the n. The calculated ac-dc transfer differences of the proposed TVC by simulation agree well with the measured values within the uncertainties. The simulated and measured values are agreed within $1{\mu}V/V$ from 40 Hz to 10kHz, within $5{\mu}V/V$ from 20kHz to 100MHz, and within $12{\mu}V/V$ from 200kHz to 1 MHz.

• Journal of the Korean Magnetics Society
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• v.16 no.3
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• pp.182-185
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• 2006

In this work, we have constructed 3-axis flux-gate magnetometer for the attitude control of satellite. The constructed magnetometer shows uncertainty of ${\pm}1%$, noise level of $0.2nT/\sqrt{Hz}$ at 1 Hz under 1W power consumption. Environment test for satellite component, acceleration test and thermal cycle test were carried out. For the acceleration test, magnetometer was vibrated frequency ranging from 10 Hz to 1 kHz at 15 g (g : gravitational acceleration at earth), and for thermal cycle test, 4 times of thermal cycle were carried out temperature ranging from $-55^{\circ}C\;to\;+80^{\circ}C$ under vacuum of $1x10^{-6}Torr$.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.8
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• pp.861-868
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• 2011

Flowmeters that measure the amount of fluid passing through conduits must kept accurate by comparison and the periodic calibration. The reference meters used are clamp-on meters that mount sensors on the outer wall of the pipe. They are called 1-path, 2-path or 4-path flowmeters depending on the number of sensors. We selected a flowmeter mainly used for K-water as test a flowmeter. We carried out experiments to find the intrinsic error of the flowmeter and errors in the downstream of a double bent pipe. The results show that there are the sensor locations that meet the tolerance. We suggested the angle of the sensor, the straight run from the downstream of the bent pipe and the number of sensors. So it is possible to improve the water treatment process and increase the accounted water rate by upgraded flow measurement technology.

• Fire Science and Engineering
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• v.31 no.5
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• pp.12-18
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• 2017

The present study has been conducted to predict the mass burning flux of methanol pool fire using liquid vaporization model in FDS and examine the effect of thermal properties of liquid fuel such as radiative fraction and mean absorption coefficient. A series of calculation for the pool diameter of 5 cm to 200 cm were performed and the size of computational domain was determined by the scale of the pool diameter. The reference grid size was determined by the grid sensitivity analysis and the computational grids consisted of approximately 750,000 cells. For the methanol pool fire, the mass burning flux predicted by liquid vaporization model of FDS followed the trend of transient characteristics as a function of pool diameter and showed good agreement within measurement uncertainty range of previous studies. The mass burning flux increased with increasing the radiative fraction and the mean absorption coefficient greatly affected on relatively small pool diameter.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.611-618
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• 2020

The reliability of the results of LCC analysis is determined by accurate analytical procedures and energy data from which the uncertainty is removed. Until now, systems that can automatically measure these energy data and produce databases have not been commercialized. Therefore this paper proposes a concept model of an S-LCC platform that can automatically collect and analyze electric energy consumption data of equipment systems using the IOT, which is the core tool in the Fourth Industrial Revolution and operates the equipment system efficiently using the analyzed results. The proposed concept model was developed by the convergence of existing BLCS and IOT and was comprised of five modules: Facility Control Module, LCC Analysis Module, Energy Consumption Control Module, Efficiency Analysis Module, and Maintenance Standard Reestablishment Module. Using the results of LCC analysis deduced from this system, the deterioration condition of an equipment system can be identified in real-time. The results can be used as the baseline data to re-establish standards for the maintenance factor, replacement frequency, and lifetime of existing equipment, and establish new maintenance standards for new equipment. If the S-LCC platform is established, it would increase the reliability of LCC analysis, reduce the labor force for entering data and improve accuracy, and would also change disregarded data into big data with high potential.

• Journal of Korean Medicine Rehabilitation
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• v.24 no.4
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• pp.155-162
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• 2014

Objectives Advanced researches on the relationship between obesity and heart rate variability (HRV), heretofore, focused on characteristics of HRV depending on the state of obesity. However, the previous researches have not quantified predictive power of HRV toward the obesity-related variables, which is rather more meaningful for clinicians who regularly treat obese patients. Hence, we designed a research to investigate whether HRV could predict serum levels of obesity-related metabolites. Methods Ninety obese premenopausal women meeting the inclusion criteria were recruited. The HRV test, blood sampling, and measurement of physical traits were conducted. Multiple regression analysis of the measurement data was carried out, putting obesity-related metabolites (insulin, glucose, triglyceride, hs-CRP, HDL, LDL, total cholesterol) as outcome variables and the others as predictors. To select appropriate predictive variables, the Akaike's Information Criterion (AIC) was applied. Normality and homoskedasticity of residuals for each model were tested to identify if there were any violations of the regression analysis's basic assumption. Logarithm transformation was used for the values of the concentration of metabolites and the HRV. Results The regression model including Total Power (TP) value and BMI had significant predictive power for serum insulin concentration (F(2, 88)=835.7, p<0.001, $R^2=0.95$). The regression coefficient of ln (TP) was -0.1002. However, it was not sure if the HRV could predict concentrations of other metabolites. Conclusions The results suggest that the Total Power (TP) value of the HRV can predict the level of serum insulin. If the BMI could be assumed as being constant, when the TP value is multiplied by n, the predicted change of insulin could be drawn by multiplying $n^{-0.1002}$. The uncertainty of this model can be assumed as approximately 5%.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.821-831
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• 2013

Recently image velocimetries, including particle image velocimetry (PIV) and surface image velocimetry (SIV), are often used to measure flow velocities in laboratories and rivers. The most difficult point in using image velocimetries may be how to determine the sizes of the interrogation areas and the measurement uncertainties. Especially, it is a little hard for unskilled users to use these instruments, since any standardized measuring techniques or measurement uncertainties are not well evaluated. Sometimes the user's skill and understanding on the instruments may make a wide gap between velocity measurement results. The present study aims to evaluate image velocimetry's uncertainties due to the changes in the sizes of interrogation areas and searching areas with the error analyses. For the purpose, we generated 12 series of artificial images with known velocity fields and various numbers and sizes of particles. The analysis results showed that the accuracy of velocity measurements of the image velocimetry was significantly affected by the change of the size of interrogation area. Generally speaking, the error was reduced as the size of interrogation areas became small. For the same sizes of interrogation areas, the larger particle sizes and the larger number of particles resulted smaller errors. Especially, the errors of the image velocimetries were more affected by the number of particles rather than the sizes of them. As the sizes of interrogation areas were increased, the differences between the maximum and the minimum errors seemed to be reduced. For the size of the interrogation area whose average errors were less than 5%, the differences between the maximum and the minimum errors seemed a little large. For the case, in other words, the uncertainty of the velocity measurements of the image velocimetry was large. In the viewpoint of the particle density, the size of the interrogation area was small for large particle density cases. For the cases of large number of particle and small particle density, however, the minimum size of interrogation area became smaller.

• Korean Journal of Biological Psychiatry
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• v.17 no.3
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• pp.136-144
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• 2010

Objectives : The $2^{nd}$ to $4^{th}$ digit length(2D : 4D) ratio reflects the amount of exposure and sensitivity to the prenatal sex hormone and it is considered to be the most convenient and useful way to understand the influence of sex hormone in the determination of human behavioral traits. This study was carried out to find the correlation between the 2D : 4D ratio and characteristics of temperament and character in Korean university students. We assumed that 2D : 4D ratio would show a strong correlation with temperament which is defined to be an inclination of an automatical emotional response to a stimulus. Methods : Participants were 104 university students who completed 2 self-report measures : Temperament and Character Inventory(TCI), Temperament Test. We examined the 2D : 4D ratio of each subject by measuring the lengths of the $2^{nd}$ and $4^{th}$ fingers using a photocopy measurement. We performed statistical analyses using correlation test and t-test to examine the relationship between 2D : 4D ratio and psychological characteristics. Results : We found out the typical sex difference in 2D : 4D ratio. Women had significantly higher 2D : 4D ratio than men. TCI-Character factor(TCI-C) didn't show any significant correlation with the 2D : 4D ratio. TCI-Tempterament factor(TCI-T) and the item of Temperament Test showed a significant correlation with the 2D : 4D ratio. In correlation analysis of the total group including all women and men, the 2D : 4D ratio showed a significant positive correlation in a subscale(shyness with stranger) of harm avoidance scales in TCI-T. In correlation analysis of women's group, the 2D : 4D ratio showed a significant positive correlation in two subscales( fear of uncertainty) and[shyness to stranger] of harm avoidance scales in TCI-T. In correlation analysis of men's group, the 2D : 4D ratio showed a significant negative correlation with a sanguine temperament item of the Temperament Test. Conclusion : The results suggest that the amount of exposure to sex hormone in the prenatal period seems to have an impact on the determination of temperament and characteristics.