• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.444-453
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• 2018

The study addresses the analysis on the financial determinants of corporate research and development (R&D) expenditure in finance. Overall level of R&D spending was estimated as one of the top-tier on a global basis and a majority of the expenditure was invested by large domestic firms in private sector. Consequently, financial factors that influence R&D intensity were empirically tested in the first hypothesis by using conditional quantile regression model for firms listed in KOSPI stock market in the post-era of the global financial turmoil. Firms in the groups of high- and low-R&D intensity were statistically compared to detect financial differences in the second hypothesis which was accompanied by the test of multi-logit model that included firms without R&D outlay. Concerning the results of the hypothesis tests, R&D spending of the prior fiscal year, firm size, business risk and advertising expense overall showed statistically significant impacts to determine the level. As an extended study of [1] that had examined financial factors of R&D intensity at the macro-level, the results of the present study are anticipated to contribute to maximizing shareholders' wealth in advance or emerging capital markets, when applied to find an optimal level of R&D expenditure.

• Journal of Korean Association for Spatial Structures
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• v.6 no.1 s.19
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• pp.83-90
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• 2006

The GF(Gust Factor) method is usually used as a method to evaluate equivalent static wind loads for general structures. The GF method is performed on the assumption that the shape of the equivalent static wind load profile is typically similar to that of mean wind loads. The shape of fluctuating wind loads could be quite different with that of the mean wind loads in case of large-span structures. So, the effect of higher modes as well as first mode must be considered to evaluate the wind loads. In this study, the ACS (Advanced Conditional Sampling) method is suggested to evaluate of equivalent static wind loads after investigating about GF and LRC method. The An method ran derive effective static wind loads by combining wind pressures and inertia forces of a structure chosen at a maximum load effect. The maximum load effect is assessed with the time history analysis using pressure data measured in wind tunnel tests. Equivalent static wind loads evaluated using ACS, GF, and LRC methods are compared to verify the effectiveness of ACS method.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.2
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• pp.226-241
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• 2010

This study details the history and characteristics of consumption values, text style analyses, and appeal types expressed in magazine commercials from 1955 to 2008. This study analyzes the level of the social structure of commercial expression for each period. Consumption values based on the categories of consumption values by Sheth (1991) were classified through a total commercials analysis. Analyses on closing types of sentences, types of sentences, and rhetorical figures were executed focusing on headline text and text style. Appealing types were composed of rational, emotional, and ethical appeals. For analysis, the crosstab analysis and chi-square test of SPSS are used. The results are as follow. Seven values were constructed, functional value, social value, emotional value, conditional value, epistemic value, fashionable value, and indistinct value. The ratio of emotional value was the highest and functional value, epistemic value conditional value, fashionable value, social value, and indistinct value followed. The emotional value social value, conditional value, fashionable value, and epistemic value that focused on the emotion of consumers increased, while the functional value decreased. Sentences that use narrative styles, hyperboles, and metaphors that increased the interest of readers were dominantly used in the headline texts. For sentence expression, a declarative sentence in a sentence type, exciting curiosity in the expression method where hyperbole and figures of speech in rhetorical expressions are used most often. Emotional appeal was used almost twice more than the reasonable appeal for appeal types of the total commercial. The lower level of reasonable appeal is information that provides the product function. Interest and expression (such as pleasure and achievement) were used most often for emotional appeal. These results show that the most important issue is the emotional value in consumption in understanding the consumer. Marketing managers should also be aware of the functional value as well as an emotional value.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.61-73
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• 2016

We consider the wild bootstrap Ljung-Box (LB) test for autocorrelation in residuals of fitted multivariate time series models. The asymptotic chi-square distribution under the IID assumption is traditionally used for the LB test; however, size distortion tends to occur in the usage of the LB test, due to the conditional heteroskedasticity of financial time series. In order to overcome such defects, we propose the wild bootstrap LB test for autocorrelation in residuals of fitted vector autoregressive and error correction models. The simulation study and real data analysis are conducted for finite sample performance.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.325-329
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• 2001

This paper tests existence of precautionary saving motive under health uncertainty, using household level panel data from Korea. For this purpose, this paper considers a dynamic health capital model with health uncertainty and derives testable equations for changes in consumption and medical expenditures. Under this framework, households who face future health uncertainty will exhibit precautionary behavior by depressing consumption or increasing investment in health. To test this hypothesis, the paper uses the conditional variance of health as the direct measure of health uncertainty, obtained by estimating a multinomial logit model. Empirical results using the Korean Household Panel Study (KHPS, 1993 - 1997) suggest that Korean elderly households follow the precautionary behavior to insure against future health risk.

• The Journal of Asian Finance, Economics and Business
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• v.2 no.3
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• pp.17-22
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• 2015

This paper examines the effect of impulsiveness of euro on Indian stock market. In order to examine the problem, we select rupee-euro exchange rates and S&P CNX NIFTY and BSE30 SENSEX to represent stock price. We select euro as it considered as second most widely used currency at the international level after dollar. The data are collected a daily basis over a period of 3-Apr-2007 to 30-Mar-2012. The statistical and time series properties of each and every variable have examined using the conventional unit root such as ADF and PP test. Adopting a generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) model, the study suggests a negative relationship between exchange rate and stock prices in India. Even though India is a major trade partner of European Union, the study couldn't find any significant statistical effect of fluctuations in Euro-rupee exchange rates on stock prices. The study also reveals that shocks to exchange rate have symmetric effect on stock prices and exchange rate fluctuations have permanent effects on stock price volatility in India.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.905-926
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• 1998

We propose a modified mid P-value method to reduce the conservativeness for the inference of conditional associations in three-way contingency tables. This improves the ordinary mfd P-value method. For $2{\times} 2${\times} K$ tables, we propose confidence intervals for an assumed common odds ratio based on inverting two separate one-sided tests using the modified mid P-value. Also, an alternative and usually even better ways of constructing intervals, based on Inverting a two-sided test, are presented. The actual probability of coverage of a 100($1-\alpha$)% confidence interval is centered about the nominal level, but the modified mid P-value approach gives actual coverage probability even closer to the nominal level than the ordinary mid P-value approach.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.2
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• pp.67-72
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• 2001

대상으로 하는 시스템의 입출력신호에 근거하여, 시스템의 수학적 모델을 결정하는 것을 총칭하여 시스템식별이라 한다. 본 논문에서는 지진응답 관측치를 입출력신호로 하여 조건부대치를 최적치로 판단하는 비선형근사필터법을 사용한 건축구조물의 지진응답추정 및 파라미터식별에 관하여 논한다. 비선형근사필터법에 의한 건축구조물식별의 유효성의 적용성을 판단하기 위해, 진동대를 사용하여 강구조시험체의 진동실험을 행하고 결과적으로 얻어진 시험체의 수학적 모델에 대한 지진응답 수치해석결과와 진동실험에서의 관측기록을 비교하여 본 식별법의 타당성을 보인다.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.1 s.139
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• pp.68-78
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• 2005

The purpose of this study was to examine the women consumers' clothing consumption value and involvement according to size of the city. 538 females living in Seoul(large city) and Jecheon(small city) were surveyed for this study. For data analysis, factor analysis, t-test, and regression were used. For clothing consumption value, five factors of value were founded and labeled as functional, emotional, epistemic, social and conditional value. Three factors of clothing involvement were also identified as clothing/fashion, symbolism and reasonability involvement. Size of the city influenced total clothing consumption value and involvement. Also, size of the city influenced clothing consumption value and involvement factors. When the cities were divided into two groups(large and small city), they showed different clothing consumption values and involvements according to the demographic variables.