• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.49-53
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• 2021

The Fenton reaction is often used to evaluate the chemical durability of polymer membranes of Proton Exchange Membrane Fuel Cells (PEMFC). However, due to the violent reaction between hydrogen peroxide and iron ions, it is difficult to compare experimental data because of low reproducibility. In this study, we tried to find the reaction conditions to improve the reproducibility of the durability test of the membrane by the Fenton reaction. The hydrogen peroxide concentration was fixed at 30%, the iron ion concentration, temperature, stirring speed, and sample size were varied, and the fluorine ion concentration of the Nafion polymer membrane deteriorated by radicals was measured. When the iron ion concentration was increased or the membrane sample size was increased, and the reaction temperature was increased to 80 ℃, the experimental deviation increased, so an iron ion concentration of 10 ppm, a temperature of 70 ℃, and a sample size of 0.5 ㎠ were suitable.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.451-459
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• 2017

There are many researches showing that when a process change has occurred, variable sampling intervals (VSI) control chart is better than the fixed sampling interval (FSI) control chart in terms of reducing the required time to signal. When the process engineers use VSI control procedure, frequent switching between different sampling intervals can be a complicating factor. However, average number of samples to signal (ANSS), which is the amount of required samples to signal, and average time to signal (ATS) do not provide any control statistics about switching performances of VSI charts. In this study, we evaluate numerical switching performances of multivariate VSI EWMA chart including average number of switches to signal (ANSW) and average switching rate (ASWR). In addition, numerical study has been carried out to examine how to improve the performance of considered chart with accumulate-combine approach under several different smoothing constant and sample size. In conclusion, process engineers, who want to manage the correlation coefficients of related quality variables, are recommended to make sample size as large and smoothing constant as small as possible under permission of process conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2094-2112
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• 2019

Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has poor performance in handling scale change and obscured objects, this paper proposes an anti-occlusion and scale adaptive tracking algorithm in the basis of KCF. The average Peak-to Correlation Energy and the peak value of correlation filtering response are used as the confidence indexes to determine whether the target is obscured. In the case of non-occlusion, we modify the searching scheme of the KCF. Instead of searching for a target with a fixed sample size, we search for the target area with multiple scales and then resize it into the sample size to compare with the learnt model. The scale factor with the maximum filter response is the best target scaling and is updated as the optimal scale for the following tracking. Once occlusion is detected, the model updating and scale updating are stopped. Experiments have been conducted on the OTB benchmark video sequences for compassion with other state-of-the-art tracking methods. The results demonstrate the proposed method can effectively improve the tracking success rate and the accuracy in the cases of scale change and occlusion, and meanwhile ensure a real-time performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4326-4344
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• 2021

The SinGAN is one of generative adversarial networks that can be trained on a single nature image. It has poor ability to learn more global features from nature image, and losses much local detail information when it generates arbitrary size image sample. To solve the problem, a non-linear function is firstly proposed to control downsampling ratio that is ratio between the size of current image and the size of next downsampled image, to increase the ratio with increase of the number of downsampling. This makes the low-resolution images obtained by downsampling have higher proportion in all downsampled images. The low-resolution images usually contain much global information. Therefore, it can help the model to learn more global feature information from downsampled images. Secondly, the attention mechanism is introduced to the generative network to increase the weight of effective image information. This can make the network learn more local details. Besides, in order to make the output image more natural, the TVLoss function is introduced to the loss function of SinGAN, to reduce the difference between adjacent pixels and smear phenomenon for the output image. A large number of experimental results show that our proposed model has better performance than other methods in generating random samples with fixed size and arbitrary size, image harmonization and editing.

• The Journal of Fisheries Business Administration
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• v.28 no.2
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• pp.1-18
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• 1997

The purpose of this study is to investigate empirically the characteristics of financial structure by using 76 fisheries corporations in Korea, and to suggest implications of the empirical results for government's financial policy for fisheries corporations. For the empirical test, we choose the following factors as the explanatory variables of cross-sectional regression analysis:firm-size(SIZE), collateral value of assets(TFATA), business risk(BRISK), growth(GROWTH), effective tax(ET), profitability(PROFIT). Two different debt ratios are used as dependent variables. One is defined as the ratio of total debt to total assets and the other is as that of long-term debt to total asset in terms of book value. The sample consists of 76 fisheries firms and sample period is 14 years from 1982 till 1995. From the results of cross-sectional regression analysis, the adjusted R$^2$values were high, 16∼79% and the overall F values indicated to be statistically significant. The results of cross sectional regression analysis show that the characteristics of financial structure fur fisheries corporations are as follows ; (1) Firm-size and collateral value of assets are the major factors of financial structure for fisheries corporations. That is, the larger firm-size the higher is debt ratio. This means that financial institutions conventionally lend more collateral loans with fixed assets like land, building rather than management capacities or credits. (2) To be consistent with a pecking-order theory, the higher is profitability the lower is debt ratio in fisheries corporations. (3) Corporations with high effective tax rate have lower financial leverage. Although the empirical results are inconsistent with traditional static trade-off theory, we think it would be attributed to government's various tax shelterings for fisheries which are likely to reduce tax shield effect of interests.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.231-240
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• 2010

If only fixed effects exist in a 4 $\times$ 4 balanced incomplete block design, powers of FR statistic for testing a main effect show the highest level with a few replications. Under the exponential and double exponential distributions, FR statistic shows relatively high powers with big differences as compared with the F statistic. Further in a traditional balanced incomplete block design, powers of FR statistic having a fixed main effect and a random block effect show superior preference for all situations without regard to the effect size of a main effect, the parameter size and the type of population distributions of a block effect. Powers of FR statistic increase in a high speed as replications increase. Overall power preference of FR statistic for testing a main effect is caused by unique characteristic of a balanced incomplete block design having one main and block effect with missing observations, which sensitively responds to small increase of main effect and sample size.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.141-148
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• 2020

This paper analyzes factors affecting the debt maturity structure of enterprises listed on the Vietnam stock market. The panel data of research sample includes 549 non-financial listed enterprises on the Vietnam stock market from 2009 to 2019. The Generalized Least Square (GLS) tool is employed to address econometric issues and to improve the accuracy of the regression coefficients. In this research, debt maturity structure is the dependent variable. Capital structures, fixed assets, liquidity, firm size, asset maturity, profitability, corporate income tax, gross domestic product, inflation rate, credit growth scale are independent variables in the study. The model results show, that among the factors affecting the structure of debt maturity, the capital structure, asset structure, and firm size have the highest estimation coefficients, which shows that capital structure, asset structure, and firm size plays an important role in the decision-making process of debt maturity structure. The empirical results show that there are differences in the impact of these factors on the debt maturity structures in state-owned enterprises and non-state enterprises listed on the Vietnam stock market. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to determine the target debt maturity structure in enterprises.

• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.293-301
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• 2013

The purpose of this study is to introduce the limit of previously used six sigma quality process evaluation metrics, $Z_{st}$ and $P_{pk}$, and a solution to overcome this drawback by using a metric based on performance evaluation of Z-factor quality innovation. Case analysis on projects from national six sigma contest from 2011 to 2012 is performed and literature review on new drug development HTS (High Throughput Screening) is used to propose innovative performance evaluation metrics. This research shows that experimental study on six sigma evaluation metric, $Z_{st}$ and $P_{pk}$, have no significance difference between industrial type (Manufacturing, Semi-Public Institute, Public Institute) and CTQ type (Product Technology Type CTQ, Process Technology Type CTQ). Following discovery characterize this quality improvement as fixed target type project. As newly developed moving target type of quality innovation performance metric Z-Factor is used for evaluating experimental study, hypothetical analysis suggests that $Z_{st}$ and $P_{pk}$ share different relationship or even show reciprocal relationship. Constraints of the study are relatively small sample size of only 37 projects from past 2 years and conflict on having interview and communication with six sigma quality practitioner for qualitative experimental study. Both moving target type six sigma innovation project and fixed target type improvement project or quality circle enables efficient ways for a better understanding and quality practitioner use by applying quality innovation performance metric. Downside of fixed target type quality performance evaluation metric, $Z_{st}$ and $P_{pk}$, is presented through experimental study. In contrast, advantage of this study is that high throughput requiring product technology, process technology and quantum leap typed innovation effect is evaluated based on precision and accuracy and Z-Factor that enables relative comparison between enterprises is proposed and implemented.

• Proceedings of the Korean Magnestics Society Conference
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• 2012.11a
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• pp.104-105
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• 2012

The temperature dependence of the effective magnetic anisotropy constant K(T) of ferrite nanoparticles is obtained based on the measurements of SQUID magnetometry. For this end, a very simple but intuitive and direct method for determining the temperature dependence of anisotropy constant K(T) in nanoparticles is introduced in this study. The anisotropy constant at a given temperature is determined by associating the particle size distribution f(r) with the anisotropy energy barrier distribution $f_A(T)$. In order to estimate the particle size distribution f(r), the first quadrant part of the hysteresis loop is fitted to the classical Langevin function weight-averaged with the log?normal distribution, slightly modified from the original Chantrell's distribution function. In order to get an anisotropy energy barrier distribution $f_A(T)$, the temperature dependence of magnetization decay $M_{TD}$ of the sample is measured. For this measurement, the sample is cooled from room temperature to 5 K in a magnetic field of 100 G. Then the applied field is turned off and the remanent magnetization is measured on stepwise increasing the temperature. And the energy barrier distribution $f_A(T)$ is obtained by differentiating the magnetization decay curve at any temperature. It decreases with increasing temperature and finally vanishes when all the particles in the sample are unblocked. As a next step, a relation between r and $T_B$ is determined from the particle size distribution f(r) and the anisotropy energy barrier distribution $f_A(T)$. Under the simple assumption that the superparamagnetic fraction of cumulative area in particle size distribution at a temperature is equal to the fraction of anisotropy energy barrier overcome at that temperature in the anisotropy energy barrier distribution, we can get a relation between r and $T_B$, from which the temperature dependence of the magnetic anisotropy constant was determined, as is represented in the inset of Fig. 1. Substituting the values of r and $T_B$ into the $N{\acute{e}}el$-Arrhenius equation with the attempt time fixed to $10^{-9}s$ and measuring time being 100 s which is suitable for conventional magnetic measurement, the anisotropy constant K(T) is estimated as a function of temperature (Fig. 1). As an example, the resultant effective magnetic anisotropy constant K(T) of manganese ferrite decreases with increasing temperature from $8.5{\times}10^4J/m^3$ at 5 K to $0.35{\times}10^4J/m^3$ at 125 K. The reported value for K in the literatures is $0.25{\times}10^4J/m^3$. The anisotropy constant at low temperature region is far more than one order of magnitude larger than that at 125 K, indicative of the effects of inter?particle interaction, which is more pronounced for smaller particles.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.41-53
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• 2019

Building a target capital structure is one of the most important decisions in corporate financial management. The purpose of this article is to identify the determinants of capital structure and adjustment mechanism toward the target leverage. The partial adjustment model was applied on a sample of 306 non-financial companies listed on Vietnam stock exchange market during the period of 2008-2017. By the fixed effect model estimation method, the research results have discovered the factors of growth opportunities, firm size, tangible fixed assets and firm's unique characteristics have a positive effect on the target capital structure of enterprises. Besides, profitability and dividend payment have a negative effect on the target capital structure of enterprises. Accordingly, the research results show that the average adjustment speed toward target leverage of the firms is 90.03%. Research results also demonstrate firms have higher or lower debt ratio than the target debt ratio, capital surplus or capital deficit also have an impact on the adjustment rate toward the target capital structure. The research results are consistent with the Dynamic Trade-off Theory. From this result, this article has provided policy implications for non-financial companies listed on Vietnam's stock market in building a reasonable target capital structure according to operating timeline to maximize enterprise value.