• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.49-60
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• 1995

This paper is a study on the design and implementation of the Korean Text-to-Speech system which is used for a small and simple system. In this paper, a parameter synthesis method is chosen for speech syntheiss method, we use PARCOR(PARtial autoCORrelation) coefficient which is one of the LPC analysis. And we use phoneme for synthesis unit which is the basic unit for speech synthesis. We use PARCOR, pitch, amplitude as synthesis parameter of voice, we use residual signal, PARCOR coefficients as synthesis parameter of unvoice. In this paper, we could obtain the 60% intelligibility by using the residual signal as excitation signal of unvoiced sound. The result of synthesis experiment, synthesis of a word unit is available. The controlling of phoneme duration is necessary for synthesizing of a sentence unit. For setting up the synthesis system, PC 486, a 70[Hz]-4.5[KHz] band pass filter for speech input/output, amplifier, and TMS320C30 DSP board was used.

• Computers and Concrete
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• v.14 no.5
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• pp.577-597
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• 2014

This paper aims to develop a prediction model for the hardened properties of waste LCD glass that is used in concrete by analyzing a series of laboratory test results, which were obtained in our previous study. We also summarized the testing results of the hardened properties of a variety of waste LCD glass concretes and discussed the effect of factors such as the water-binder ratio (w/b), waste glass content (G) and age (t) on the concrete compressive strength, flexural strength and ultrasonic pulse velocity. This study also applied a hyperbolic function, an exponential function and a power function in a non-linear regression analysis of multiple variables and established the prediction model that could consider the effect of the water-binder ratio (w/b), waste glass content (G) and age (t) on the concrete compressive strength, flexural strength and ultrasonic pulse velocity. Compared with the testing results, the statistical analysis shows that the coefficient of determination $R^2$ and the mean absolute percentage error (MAPE) were 0.93-0.96 and 5.4-8.4% for the compressive strength, 0.83-0.89 and 8.9-12.2% for the flexural strength and 0.87-0.89 and 1.8-2.2% for the ultrasonic pulse velocity, respectively. The proposed models are highly accurate in predicting the compressive strength, flexural strength and ultrasonic pulse velocity of waste LCD glass concrete. However, with other ranges of mixture parameters, the predicted models must be further studied.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.184-192
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• 2011

In this study, we introduce a identification methodology for FCM-based fuzzy model. The two underlying design mechanisms of such networks involve Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on FCM clustering method for efficient processing of data and the optimization of model was carried out using PSO. The premise part of fuzzy rules does not construct as any fixed membership functions such as triangular, gaussian, ellipsoidal because we build up the premise part of fuzzy rules using FCM. As a result, the proposed model can lead to the compact architecture of network. In this study, as the consequence part of fuzzy rules, we are able to use four types of polynomials such as simplified, linear, quadratic, modified quadratic. In addition, a Weighted Least Square Estimation to estimate the coefficients of polynomials, which are the consequent parts of fuzzy model, can decouple each fuzzy rule from the other fuzzy rules. Therefore, a local learning capability and an interpretability of the proposed fuzzy model are improved. Also, the parameters of the proposed fuzzy model such as a fuzzification coefficient of FCM clustering, the number of clusters of FCM clustering, and the polynomial type of the consequent part of fuzzy rules are adjusted using PSO. The proposed model is illustrated with the use of Automobile Miles per Gallon(MPG) and Boston housing called Machine Learning dataset. A comparative analysis reveals that the proposed FCM-based fuzzy model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• Imaging Science in Dentistry
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• v.46 no.1
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• pp.1-7
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• 2016

Purpose: This study assessed the accuracy of age estimates produced by a regression equation derived from lower third molar development in a Thai population. Materials and Methods: The first part of this study relied on measurements taken from panoramic radiographs of 614 Thai patients aged from 9 to 20. The stage of lower left and right third molar development was observed in each radiograph and a modified Gat score was assigned. Linear regression on this data produced the following equation: Y=9.309+1.673 mG+0.303S (Y=age; mG=modified Gat score; S=sex). In the second part of this study, the predictive accuracy of this equation was evaluated using data from a second set of panoramic radiographs (539 Thai subjects, 9 to 24 years old). Each subject's age was estimated using the above equation and compared against age calculated from a provided date of birth. Estimated and known age data were analyzed using the Pearson correlation coefficient and descriptive statistics. Results: Ages estimated from lower left and lower right third molar development stage were significantly correlated with the known ages (r=0.818, 0.808, respectively, $P{\leq}0.01$). 50% of age estimates in the second part of the study fell within a range of error of ${\pm}1year$, while 75% fell within a range of error of ${\pm}2years$. The study found that the equation tends to estimate age accurately when individuals are 9 to 20 years of age. Conclusion: The equation can be used for age estimation for Thai populations when the individuals are 9 to 20 years of age.

• Journal of Korean Clinical Nursing Research
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• v.24 no.2
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• pp.227-234
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• 2018

Purpose: This study compared the temporal artery temperature (TAT) measured by infrared temporal artery thermometers to the axillary temperature (AT) measured by standard mercury-in-glass thermometers, and evaluated accuracy of the TAT measurement for clinical practice. Methods: A total of 247 adult inpatients in general wards in a tertiary medical center located in Seoul participated in the study. The TAT was measured within one minute after the AT measurement. Data were analyzed using descriptive statistics, paired t-test, Pearson correlation coefficient, linear regression, and the Bland-Altman plot. Results: There was a significant difference in mean temperature between AT and TAT, $36.89^{\circ}C$ (SD=0.70) versus $37.35^{\circ}C$ (SD=0.72). The Bland-Altman plots demonstrated the difference between the AT and TAT as -1.29 to +0.33. The specificity and sensitivity of the TAT in detecting fever were high. The positive predictive values were 57.5% and 71.0% when the AT were higher than $38.0^{\circ}C$ and the TAT fever cutoff levels were $38.0^{\circ}C$ and $38.3^{\circ}C$ respectively. Conclusion: TAT and AT were highly correlated and agreeable, indicating that TAT is as accurate as AT. The findings suggested that TAT measurement can be used in clinical practice. For accurate communication between medical personnel, medical institutions need to provide guidelines for temperature measurement, especially for the use of thermometer and measurement sites.

• Journal of muscle and joint health
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• v.29 no.3
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• pp.205-217
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• 2022

Purpose: This study aimed to investigate the factors affecting the subjective health status (SHS) of low-income older adults living alone. Methods: This is a cross-sectional correlational study using secondary data analysis. Sociodemographic and health-related characteristics were included in this analysis. The health-related characteristics were categorized into three domains: physical, characterized by the number of chronic diseases and fall-related factors, timed up and go, and grip strength; psychological, in terms of depression and loneliness; and social, in terms of social support. Data were analyzed using descriptive analysis, t-test, ANOVA, Pearson's correlation coefficient, and multiple linear regression analysis. Results: The mean SHS score was 2.46 out of five. Several factors influenced the SHS of low-income older adults living alone, including sex, age, level of education, monthly income, and the three domains. Four significant predictive factors of SHS in low-income older adults living alone were identified (42.5%): the number of chronic diseases, fear of falling, depression, and social support. Conclusion: SHS is a critical factor for older adults living alone on a low-income. Hence, evaluating SHS and developing interventions to improve it periodically is necessay. Such interventions should consider chronic disease management, screening and mediation for depression and fear of falling, and strengthening their social support systems.

• 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.

• Journal of Korean Society of Forest Science
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• v.78 no.4
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• pp.381-395
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• 1989

The main purpose of this research is to provide scientific informations about standard wage and performance tariffs in forest management with special reference to working time for thinning. To identify relationships between net working time and tree characteristics, three geographically different sample plots were established at Yangsan, Bongpyung and Jinan and 460 oaks, 372 Japanese larches, 232 red pine and 240 pitch pine mere selected at each sample plots. The results of statistical analysis using multiple regression are as follows ; 1. Five independent variables of breast height diameter(DBH), mid-diameter(MD) large end diameter(LD), log-length(L), No. of branches(NOB) were stable independent of worker and tree species. 2. Comparing correlation coefficient of five independent variables, the best predictive variables, breast height diameter and No. of branches, were selected. Breast height diameter and No. of branches were identified as the most important independent variables in terms of effect on the dependent variable of the working time. 3. Comparing coefficient of determination (Rp) and residual mean square (MSEp), the best Linear regression equation for each tree species was selected as follower : $WT=a+b1{\times}NOB+b2{\times}DBF$ 4. Proportion of hang-up time to total working time in thinning were 66% in oak stand, 74%, in Japanese larch stand, 55%, in red pine stand and 52% in pitch pine stand, respectively. 5. Based on the best regression equation, a table of working time was made by strata of number of branches and breast height diameter. 6. Total working time using the best regression equation in Table 5 can be predicted in terms of felling time, limbing time, hang-up time, i.e., total working time increases by 11 to 13 seconds with every 1 centimeter increase in breast height diameter from 7 to 16 centimeter.