• Journal of the Korean Society of Costume
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• v.61 no.1
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• pp.34-46
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• 2011

The purposes of this study are to classify apparel service quality elements using the Kano's model, and to identify how much service quality can increase the degree of customer satisfaction when the service quality is fully fulfilled. Women over 20 years-old from metropolitan areas participated in the study. Data from 254 questionnaires were used for the statistical analysis. The results were as follows: First, 17 service quality elements were categorized into one-dimensional quality which could lead to both satisfaction and dissatisfaction, and 3 services quality elements were categorized into indifferent quality which neither result in satisfaction nor dissatisfaction. Second, potential customer satisfaction improvement(PCSI) Index was developed using Kano model and CS coeffient. Findings of this study provide both industry and academic researchers with a guide to increase customer satisfaction in fashion retail store.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.92-100
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• 2003

Using a quarter car model, an analytic method for performance estimation of a vehicle suspension system with respect to frequency response, RMS response and performance index is presented. From frequency response function, compromization of response performance to the whole frequency range is verified and from RMS response and performance index, sensitivity of ride md handling characteristics are examined. Using a full car model, sweet area(stable ride area) are determined and performance sensitivity is estimated according to the change of feedback gains. In order to esimate the output sensitivity, response we is displayed using a 3-dimensional contour plot. Design data n suggested for optimal design parameter esimation, which maximize the performance of the given suspension system.

• Journal of the Korean Mathematical Society
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• v.47 no.2
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• pp.385-407
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• 2010

To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

• Bulletin of the Korean Mathematical Society
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• v.46 no.2
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• pp.209-227
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• 2009

We examine a unified approach of calculating the closed form solutions of option price under stochastic volatility models using stochastic calculus and the Fourier inversion formula. In particular, we review and derive the option pricing formulas under Heston and correlated Stein-Stein models using a systematic and comprehensive approach which were derived individually earlier. We compare the empirical performances of the two stochastic volatility models and the Black-Scholes model in pricing KOSPI 200 index options.

• Computers and Concrete
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• v.5 no.1
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• pp.21-36
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• 2008

Steel fiber reinforced concrete is increasingly used day by day in various structural applications. An extensive experimentation was carried out with w/cm ratio ranging from 0.25 to 0.40, and fiber content ranging from zero to1.5 percent by volume with an aspect ratio of 80 and silica fume replacement at 5%, 10% and 15%. The influence of steel fiber content in terms of fiber reinforcing index on the compressive strength of high-performance fiber reinforced concrete (HPFRC) with strength ranging from 45 85 MPa is presented. Based on the test results, equations are proposed using statistical methods to predict 28-day strength of HPFRC effecting the fiber addition in terms of fiber reinforcing index. A strength model proposed by modifying the mix design procedure, can utilize the optimum water content and efficiency factor of pozzolan. To examine the validity of the proposed strength model, the experimental results were compared with the values predicted by the model and the absolute variation obtained was within 5 percent.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.285-295
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• 2024

Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed based on a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index values of PSS alternatives are solved by the integration of the stakeholders' vague assessment comments presented in the form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solving of PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcome the shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closeness of seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with the highest RE closeness is selected as the best alternative. The results of comparison examples show that the presented model can compensate for the shortcomings of existing traditional methods.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1049-1060
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• 2009

The expansion of volatility in Korean Stock Market made it more difficult for the individual to invest directly and increased the weight of indirect investment through a fund. The purpose of this study is to construct the EIF(enhanced index fund) model achieves an excessive return among several types of fund. For this purpose, this paper propose portfolio optimization model to manage an index fund by using GA(genetic algorithm), and apply the trading amount and the closing price of standard index to earn an excessive return add to index fund return. The result of the empirical analysis of this study suggested that the proposed model is well represented the trend of KOSPI 200 and the new investment strategies using this can make higher returns than Buy-and-Hold strategy by an index fund, if an appropriate number of stocks included.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.293-300
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• 2016

Traditional databases exploit a record-based model, where the attributes of a record are placed contiguously in a slow hard disk to achieve high performance. On the other hand, for read-intensive data analysis systems, the column-based compressed database has become a proper model because of its superior read performance. Currently, flash memory SSD is largely recognized as the preferred storage media for high-speed analysis systems. This paper introduces a compressed column-storage model and proposes a new index and its data management scheme for a high-capacity data warehouse system. The proposed index management scheme is based on the asymmetric index duplication and achieves superior search performance using the master index and compact index, particularly for large read-mostly databases. In addition, the data management scheme contributes to the read performance and high reliability by compressing the related columns and replicating them in two mirrored SSD. Based on the results of the performance evaluation under the high workload conditions, the data management scheme outperforms the traditional scheme in terms of the search throughput and response time.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.209-223
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• 2024

Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.523-531
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• 2007

In this paper, we are going to develop a newly designed indexing scheme which is compatible to manage the moving objects and propose a cost model of the scheme. We propose a dynamic hashing index that insertion/delete costs are low. The dynamic hashing structure is that apply dynamic hashing techniques to combine a hash and a tree to a spatial index. We analyzed the dynamic index structure and the cost model by the frequent position update of moving objects and verified through a performance assessment experiment. The results of our extensive experiments show that the newly proposed indexing schemes(Dynamic Hashing Index) are much more efficient than the traditional the fixed grid and R-tree.