• IE interfaces
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• v.20 no.3
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• pp.339-352
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• 2007

Beyond SERVQUAL-based service quality research, we develop a measurement model of public service quality that would provide researchers and practitioners in the public sector with a foundation for systematic investigation and implementation. Firstly, we explore the attributes of public service quality that lead to customer satisfaction by using the critical incident technique (CIT). We identified four dimensions of public service qualities. We also found that the critical attributes of service quality differ according to the types of customers. Secondly, to achieve a high degree of empirical confidence, we conduct statistical tests and analyses on the classification scheme and on the attributes of service quality that we derived from the CIT analysis. Through these analyses, we could remove the redundancy among attributes and group the attributes into new constructs, which are mutually exclusive and exhaustive; we built a more sophisticated measurement model of service quality.

• Journal of Preventive Medicine and Public Health
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• v.50 no.1
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• pp.38-59
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• 2017

Objectives: Few attempts have been made to develop a generic health-related quality of life (HRQoL) instrument and to examine its validity and reliability in Korea. We aimed to do this in our present study. Methods: After a literature review of existing generic HRQoL instruments, a focus group discussion, in-depth interviews, and expert consultations, we selected 30 tentative items for a new HRQoL measure. These items were evaluated by assessing their ceiling effects, difficulty, and redundancy in the first survey. To validate the HRQoL instrument that was developed, known-groups validity and convergent/discriminant validity were evaluated and its test-retest reliability was examined in the second survey. Results: Of the 30 items originally assessed for the HRQoL instrument, four were excluded due to high ceiling effects and six were removed due to redundancy. We ultimately developed a HRQoL instrument with a reduced number of 20 items, known as the Health-related Quality of Life Instrument with 20 items (HINT-20), incorporating physical, mental, social, and positive health dimensions. The results of the HINT-20 for known-groups validity were poorer in women, the elderly, and those with a low income. For convergent/discriminant validity, the correlation coefficients of items (except vitality) in the physical health dimension with the physical component summary of the Short Form 36 version 2 (SF-36v2) were generally higher than the correlations of those items with the mental component summary of the SF-36v2, and vice versa. Regarding test-retest reliability, the intraclass correlation coefficient of the total HINT-20 score was 0.813 (p<0.001). Conclusions: A novel generic HRQoL instrument, the HINT-20, was developed for the Korean general population and showed acceptable validity and reliability.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.64-73
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• 2011

Oil price prediction is an important issue for the regulators of the government and the related industries. When employing the time series techniques for prediction, however, it becomes difficult and challenging since the behavior of the series of oil prices is dominated by quantitatively unexplained irregular external factors, e.g., supply- or demand-side shocks, political conflicts specific to events in the Middle East, and direct or indirect influences from other global economical indices, etc. Identifying and quantifying the relationship between oil price and those external factors may provide more relevant prediction than attempting to unclose the underlying structure of the series itself. Technically, this implies the prediction is to be based on the vectoral data on the degrees of the relationship rather than the series data. This paper proposes a novel method for time series prediction of using Semi-Supervised Learning that was originally designed only for the vector types of data. First, several time series of oil prices and other economical indices are transformed into the multiple dimensional vectors by the various types of technical indicators and the diverse combination of the indicator-specific hyper-parameters. Then, to avoid the curse of dimensionality and redundancy among the dimensions, the wellknown feature extraction techniques, PCA and NLPCA, are employed. With the extracted features, a timepointspecific similarity matrix of oil prices and other economical indices is built and finally, Semi-Supervised Learning generates one-timepoint-ahead prediction. The series of crude oil prices of West Texas Intermediate (WTI) was used to verify the proposed method, and the experiments showed promising results : 0.86 of the average AUC.

• The Journal of the Acoustical Society of Korea
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• v.22 no.6
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• pp.452-456
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• 2003

We discuss how to reduce the number of inverse matrix and its dimensions requested in MLLR framework for speaker adaptation. To find a smaller set of variables with less redundancy, we adapt PCA (principal component analysis) and ICA (independent component analysis) that would give as good a representation as possible. The amount of additional computation when PCA or ICA is applied is as small as it can be disregarded. 10 components for ICA and 12 components for PCA represent similar performance with 36 components for ordinary MLLR framework. If dimension of SI model parameter is n, the amount of computation of inverse matrix in MLLR is proportioned to O(n⁴). So, compared with ordinary MLLR, the amount of total computation requested in speaker adaptation is reduced by about 1/81 in MLLR with PCA and 1/167 in MLLR with ICA.