• Quality Improvement in Health Care
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• v.7 no.2
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• pp.230-242
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• 2000

Background : The measuring instruments for customer satisfaction in hospitals are often composed of some dimensions reflecting the conceptive complexity of them. Then, overall satisfaction would be expected to be equal the 'weighted' sum of scores by dimensions because the importance rated by customers may be different across the dimensions. But the issue of how to weight the dimensions with importance is not yet solved. We examined 3 sets of weighting methods as to make effect on predictive power against overall satisfaction. Methods : We conducted a survey included 483 subjects who had visited or admitted to a university hospital, using the short form questionnaire being developed by The Korean Society of Quality Assurance in Health Care for out-patient and in-patient. By using a multiple linear regression model, we compared among changes of explanatory powers against overall satisfaction as dependent variable after weighting 4 dimensions of the survey questionnaire as independent variables with importance scores of dimensions perceived by consumers. And we compared the feasibility of each weighting, methods by checking missing cases. Results : There were no weighting methods increasing the explanatory power after applying them. The method of absolute scoring was found higher explanatory-power than others, but this finding had no statistical significance. Regarding the number of missing value, method of absolutely scoring had the least cases. Conclusion : Our findings suggested that weighting the dimensions with importance might have little significance in the cases of scales having items highly correlated, such as consumers' satisfaction. Though asking with items to be answered absolutely, customers might be rating relatively in some degree and this method produced least missing cases. Considering these points, in the cases when weighting the dimensions with importance would be required, we suggest that weighting method by absolute scoring might be better than others.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.45-67
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• 2014

National Innovative Capability (NIC) is an important decisive factor where economic growth is concerned. As such, it is very important to measure and manage NIC. The composite index approach is one of the widely used approaches to measuring NIC, but there have been insufficient reviews of its feasibility and reliability. This paper conducted an analysis of the feasibility and reliability of the report on the last three years (i.e. 2011 through 2013) of the Innovation Union Scoreboard (IUS) of the EU, which is the most representative means of measuring NIC. It turned out that its reliability meets the recommended criteria as a result of Chronbach's alpha-based test of the models of IUS-related composite index. However, neither the absolute fit index nor the incremental fit index was found to meet the recommended criteria in a construct validity analysis. It also turned out that predictive validity is very low as a result of panel linear regression analysis of sectors and items of IUS-related composite index. This paper presents a number of considerations to be made when measuring national innovative capability using the composite index approach, as well as major policy suggestions based on the results of the analysis.

• Journal of Nutrition and Health
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• v.30 no.3
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• pp.336-348
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• 1997

The objectives of this study were to examine the growth pattern of infants by anthropometric measurement according to the 5 feeding practices of infants with the subject of two hundred healthy newborn babies from their birth till sixty month of age at intervals of two months. Breast group(BF, n=38), formula group(FF, n=102) and mixed group(ME, n=14) were fed breast milk, formula milk, breast and formula milk, from birth till 6 mo. of age, respectively. Convert 1 group (C1F, n=14) and covert 2 group(CF, n=32) were fed breast milk and mixed milk at 2 mo. of age afterthat switched to formula milk, respectively. From these, the following results were made. All the infants of this study showed superiority to Korean standard growth rate in regards to each growth item for each month age. In the case of males, at their birth, the subscapular skinfold thickness and the total skin fold thickness in the BF group was significantly larger than in MF group and FF group(p<0.05). At 6th month age, the chese circumference of MF group was 45.9cm, and significantly larger than those of BF, FF and C2F groups(p<0.05). In the case of females, at theri birth and 2nd month age, there was no difference among all the feeding groups in regards to each growth rate. At 4th month age, the Kauf index of C1F group was 16.21 and significantly lower than those of four groups(p<0.05). And total skinfold thickness in BF group was larger than in C1F group. The increase rate per month age of all growth items were larger at 2nd month age than at the later months both in males and in females. And until 2nd month age males showed more increase than females in regards to each growth item but after 2nd month age, this sapect did not show up. Multiple linear regression was used to determine predictive factors for infant growth. It was expected that at 6th month age, in the measurement of head circumference and chest circumference and cross-sectional fat area, BF-males were bigger by 22-39% of the explanation index than the infants of other groups. As a result, in spite of the significant lower intakes of energy and nutrients in breast-fed infants than in formula-fed infants, breast-fed infants showed more growth than the average of Korean infant standard growth rate at every month age, and showed no significant growth difference among feeding groups.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.23-35
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• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2027-2035
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• 2001

In this paper, we present an audio stream delivery using the AMR (Adaptive Multi-Rate) coder that was adopted by ETSI and 3GPP as a standard vocoder for next generation IMT-2000 service in which includes combined sender (FEC) and receiver reconstruction technique in the Internet. By use of the media-specific FEC scheme, the possibility to recover lost packets can be much increased due to the addition of repair data to a main data stream, by which the contents of lost packets can be recovered. The AMR codec is based on the code-excited linear predictive (CELP) coding model. So we use a frame erasure concealment for CELP-based coders. The proposed scheme is evaluated with ITU-T G.729 (CS-ACELP) coder and AMR - 12.2 kbit/s through the SNR (Signal to Noise Ratio) and the MOS (Mean Opinion Score) test. The proposed scheme provides 1.1 higher in Mean Opinion Score value and 5.61 dB higher than AMR - 12.2 kbit/s in terms of SNR in 10% packet loss, and maintains the communicab1e quality speech at frame erasure rates lop to 20%.

• Korean Journal of Biological Psychiatry
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• v.16 no.3
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• pp.181-189
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• 2009

Objectives : N100 amplitude slope(the intensity dependence of the cortical auditory evoked potentials) is widely considered as an indirect indicator of central serotonergic neurotransmission. However, there are only a few studies about N100 amplitude slopes of major psychiatric disorders. In this study, we examined N100 amplitude slope differences among major depressive disorder(MDD), bipolar disorder(BD), schizophrenia (SCZ) and normal controls(NC). Methods : We measured the N100 amplitude slopes of 35 patients with MDD, 33 patients with BD, 27 patients with SCZ and 35 NC subjects. Amplitude differences from N1 to P2 at the five different sound intensities(55, 65, 75, 85 and 95dB) were examined at Cz electrode. The N100 amplitude slope was calculated as the linear regression of five N1/P2 peak-to-peak amplitudes across stimulus intensities. Results : BD patients showed significantly reduced N100 amplitude slope compared with NC(0.54${\pm}$0.70 vs. 0.96${\pm}$0.72, p=0.035). N100 amplitude slope of SCZ patients was significantly reduced compared with NC(0.50${\pm}$0.47 vs. 0.96${\pm}$0.72, p=0.027). N100 amplitude slope of BD patients was significantly lower than that of MDD patients(0.54${\pm}$0.70 vs. 0.94${\pm}$0.60, p=0.046). SCZ patients also showed significant reduction of N100 amplitude slope compared with MDD patients(0.50${\pm}$0.47 vs. 0.94${\pm}$0.60, p=0.036). There was no significant difference of N100 amplitude slope between MDD patients and NC(0.94${\pm}$0.60 vs. 0.96${\pm}$0.72, p=1.000). Conclusion : Interestingly, the N100 amplitude slopes of BD and SCZ were reduced compared to NC and MDD patients. Our results suggest the predictive use of N100 amplitude slope in making differential diagnoses of major psychiatric disorders. Clinical implications of N100 amplitude slope in major psychiatric disorders were discussed.

• The Journal of the Acoustical Society of Korea
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• v.24 no.1
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• pp.29-37
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• 2005

This paper proposes an automatic genre classification system for Korean traditional music. The Proposed system accepts and classifies queried input music as one of the six musical genres such as Royal Shrine Music, Classcal Chamber Music, Folk Song, Folk Music, Buddhist Music, Shamanist Music based on music contents. In general, content-based music genre classification consists of two stages - music feature vector extraction and Pattern classification. For feature extraction. the system extracts 58 dimensional feature vectors including spectral centroid, spectral rolloff and spectral flux based on STFT and also the coefficient domain features such as LPC, MFCC, and then these features are further optimized using SFS method. For Pattern or genre classification, k-NN, Gaussian, GMM and SVM algorithms are considered. In addition, the proposed system adopts MFC method to settle down the uncertainty problem of the system performance due to the different query Patterns (or portions). From the experimental results. we verify the successful genre classification performance over $97{\%}$ for both the k-NN and SVM classifier, however SVM classifier provides almost three times faster classification performance than the k-NN.

• Journal of Microbiology and Biotechnology
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• v.17 no.9
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• pp.1437-1444
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• 2007

A response surface model was developed for predicting the growth rates of Staphylococcus aureus in tryptic soy broth (TSB) medium as a function of combined effects of temperature, pH, and NaCl. The TSB containing six different concentrations of NaCl (0, 2, 4, 6, 8, and 10%) was adjusted to an initial of six different pH levels (pH 4, 5, 6, 7, 8, 9, and 10) and incubated at 10, 20, 30, and $40^{\circ}C$. In all experimental variables, the primary growth curves were well ($r^2=0.9000$ to 0.9975) fitted to a Gompertz equation to obtain growth rates. The secondary response surface model for natural logarithm transformations of growth rates as a function of combined effects of temperature, pH, and NaCl was obtained by SAS's general linear analysis. The predicted growth rates of the S. aureus were generally decreased by basic (pH 9-10) or acidic (pH 5-6) conditions and higher NaCl concentrations. The response surface model was identified as an appropriate secondary model for growth rates on the basis of correlation coefficient (r=0.9703), determination coefficient ($r^2=0.9415$), mean square error (MSE=0.0185), bias factor ($B_f=1.0216$), and accuracy factor ($A_f=1.2583$). Therefore, the developed secondary model proved reliable for predictions of the combined effect of temperature, NaCl, and pH on growth rates for S. aureus in TSB medium.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.809-825
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• 2017

The number of TV entertainment shows is increasing. Competition among programs in the entertainment market is intensifying since cable channels air many entertainment TV shows. There is now a need for research on program ratings and the number of episodes. This study presents predictive models for entertainment TV show ratings and number of episodes. We use various data mining techniques such as linear regression, logistic regression, LASSO, random forests, gradient boosting, and support vector machine. The analysis results show that the average program ratings before the first broadcast is affected by broadcasting company, average ratings of the previous season, starting year and number of articles. The average program ratings after the first broadcast is influenced by the rating of the first broadcast, broadcasting company and program type. We also found that the predicted average ratings, starting year, type and broadcasting company are important variables in predicting of the number of episodes.

• Korean Journal of Psychosomatic Medicine
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• v.15 no.1
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• pp.44-50
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• 2007

Objectives: previous studies have suggested the possible predisposing personality in fibromyalgia(FM). The aim of this study is to investigate the personality traits in female patients with FM compared to healthy female controls using the Temperament and Character Inventory(TCI) and furthermore, to evaluate the personality traits affecting the severity of the symptoms of FM. Methods Forty female patients with FM and 40 healthy female controls were examined using the TCI and the Hamilton depression rating scale. The FM patients were also evaluated the severity of the symptoms of FM using the fibromyalgia impact questionnaire(FIQ). Results : ANCOVA with age and depression levels as covariates showed that the FM patients scored significantly higher on the harm avoidance(F=2.187, p=0.047) and lower on the self-directedness(F=4.551, p=0.036) than the healthy controls. The FIQ scores showed positive correlation with the harm avoidance scores in the FM patients when adjusting for age and depression level(R=0.399, p=0.013) Multiple linear regression models revealed that the harm avoidance scores would affect the FIQ scores in FM patients(95% Cl=0.004-1.942, p=0.049). Conclusions : These results suggest that the female FM patients have distinctive temperament and character dimensions compared to the healthy female controls. Moreover, the harm avoidance may be the predictive personality to affect the severity of the symptoms of female FM patients.