• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2093-2099
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• 2011

Speech signal and car noise signal such as muffler noise are segregated from the one which has both signals mixed using statistical method. To classify speech signal from the other in segregated signals, FFT coefficients were obtained for all segments of a signal where each segment consists of 128 elements of a signal. For several coefficients of FFT corresponding to the low frequencies of a signal, autocovariances are calculated between coefficients of same order of all segments of a signal. Then they were averaged over autocovariances. Linear equation was eatablished for the those autocovariances using the linear regression method for each siganl. The coefficient of the slope of the line gives reference to compare and decide what the speech signal is. It is what this paper proposes. The results show it is very useful.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.340-343
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• 2011

To distinguish between a group of speech signals and nonspeech signals, you can use several features in domains like frequency, quefrency and time. It is very important to use features that differentiate two signal groups. As a feature to separate two signal groups, autocorrelation method was proposed and the variances between groups were studied. Autocovariances were just calculated for the time domain signal. Signals were divided into segments which consist of 128 data to be transformed to the frequency and quefrency domains. Autocovariances between each coefficient of segments in FFTs and quefrencies were found and they were averaged over wide spectrum. It is clear that the autocovariances in frequency domain show great differences between groups of signals.

• Electrical & Electronic Materials
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• v.9 no.3
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• pp.246-250
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• 1996

In optical soliton transmission systems with nonlinear dispersive materials, which is utilized for ultra-long and high bit rate transmission, it is shown that the value of initial time difference between adjacent solitons is analyzed for optimum bit rate. The method is inducted by uncorrelation condition with minimum interaction forces in initial covariance coefficient between adjacent solitons. When the initial time difference is 6 times of soliton pulse width by the results, it is shown that the reliability is maintained with more than 90% within transmission length of soliton period. multiplied by 93.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.21-32
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• 2023

The amount of money processed in medicine from the Korea Consumer Agency was studied by the various time series models. The medical data set from the Korea Consumer Agency were consisted of counseling, damage relief and conciliation. For the analysis of time series, autoregressive moving average model, vector autoregressive model and the transfer function model were used. We considered the stationarity and cross correlation function for the identification and fitting. As a result, the transfer function model showed a better prediction. Whereas, the vector autoregressive model also provided good information for the degree and duration of the influence of variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.208-217
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• 2018

This study was designed to examine the influence of academic stress, anxiety, interpersonal dependency, and hopelessness on female high school students and their level of depression. The study subjects were 684 students attending an all-female high school in C city. Data were collected by self-administered questionnaires between November 1st, 2016 and December 31st, 2016. The data were analyzed using the SPSSWIN(ver. 21.0) program. The mean values of the level of depression were analyzed by the t-test and ANOVA. The correlation coefficientswereobtained by Pearson correlation analysis and acovariance structure analysis was performed on the factors affecting the level of depression. It was found that the level of depression among all of the subjects was significantly higher within the group with a higher level of academic stress, anxiety, interpersonal dependency, and hopelessness. Thus, the level of depression was positively correlated with the levels of academic stress, anxiety, interpersonal dependency, and hopelessness. The factor that had the most influence on depression was the anxiety factor, followed by interpersonal dependency and academic stress. This result suggests that the level of depression in female high school students has a causal relationship with academic stress, anxiety, interpersonal behavioral characteristics, and hopelessness. Therefore, the most effective strategy to reduce the level of depression among female high school students would appear to be efforts to decrease their academic stress, anxiety, and interpersonal dependency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.629-640
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• 2016

This study was conducted to investigate the influence of job stress, fatigue symptoms and job satisfaction on turnover intention among dental hygienists. Overall, 516 dental hygienists who work in dental clinics were surveyed using a standardized self-administered questionnaire from April 1 to June 30, 2015. Mean turnover intention was compared to each independent variable tested by t-tests and ANOVA, correlation among turnover intention, job stress, fatigue symptoms and job satisfaction was calculated by Pearson's correlation coefficient, and covariance structure analysis was used to evaluate whether turnover intention was associated with job stress, fatigue symptoms and job satisfaction. Turnover intention was significantly higher among subjects with higher job stress and fatigue, as well as those with lower job satisfaction. Additionally, turnover intention was significantly positively correlated with job stress and fatigue symptoms, while turnover intention was negatively correlated with job satisfaction. Covariance structure analysis revealed job stress had a greater impact on turnover intention than fatigue and job satisfaction, high job stress and fatigue, the lower the job satisfaction showed that the effect of increasing the turnover intention. Overall, these results indicate that turnover intention of dental hygienists are more heavily influenced by job satisfaction and job stress than fatigue. Therefore, efforts are needed to reduce job stress and fatigue, as well as to improve job satisfaction to reduce the degree of turnover intention among dental hygienists.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.323-332
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• 2007

We present a new type of portmanteau test in the frequency domain which is derived from the discrete cosine transform(DCT). For the stationary time series, DCT coefficients are asymptotically independent and their variances are expressed by linear combinations of autocovariances. The covariance matrix of DCT coefficients for white noises is diagonal matrix whose diagonal elements is the variance of time series. A simple way to test the independence of time series is that we divide DCT coefficients into two or three parts and then compare sample variances. We also do this by testing the slope in the linear regression model of which the response variables are absolute values or squares of coefficients. Simulation results show that the proposed tests has much higher powers than Ljung-Box test in most cases of our experiments.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1480-1490
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• 2008

Design of a linear predictor and matching of an entropy coder is the art of lossless audio coding. In this paper, we use the covariance method and the Choleskey decomposition for calculating linear prediction coefficients instead of the autocorreation method and the Levinson-Durbin recursion. These results are compared to the polynomial predictor. Both of them, the predictor which has small prediction error is selected. For the entropy coding, we use the Golomb-Rice coder using the block-based parameter estimation method and the sequential adaptation method with LOCO-land RLGR. The proposed predictor and the block-based parameter estimation have $2.2879%{\sim}0.3413%$ improved compression ratios compared to FLAC lossless audio coder which use the autocorrelation method and the Levinson-Durbin recursion. The proposed predictor and the LOCO-I adaptation method could improved by $2.2879%{\sim}0.3413%$. But the proposed predictor and the RLGR adaptation method got better results with specific signals.