• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.25-31
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• 2005

We know that the Hurst Exponent (HE) is a real number in [0, 1] which denotes randomness of time series. in this research, we suggest non-linear analysis of human biological signals through HE. The feasibility of human biological signals using inductive incitement provides Some diagnosis for active treatment. In our experiment, we measured the heartbeat through the MCG, 29 healthy and 34 abnormal subjects ostensibly. The raw data of acupuncture incitement are supported by opinions of gross examination and pathological diagnosis. The mean values of HE are 0.345, 0.755 and 0.805 for the periods of before, during and after acupuncture treatment, respectively in case of abnormal subjects. On the other hand, the mean values, 0.808, 0.797 and 0.785 are for normal cases, correspondingly. From this data, we show that HE is very significant in abnormal controls according to an acupuncture incitement, and the incitement effect is evidently extracted in abnormal subjects. But, in normal subjects, the incitement effect is meaningless.

• Economic and Environmental Geology
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• v.40 no.6
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• pp.739-749
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• 2007

The seismic velocity at the formation varies widely with physical properties in the layers. These features on seismic shot gathers are not capable of reproducing normally by numerical modeling of homogeneous medium, so that we need that of random inhomogeneous medium instead. In this study, we conducted Gaussian autocorrelation function (ACF), exponential autocorrelation function and von Karman autocorrelation function for getting inhomogeneous velocity model and applied a simple geological model. According to the results, von Karman autocorrelation function showed short wavelength to the inhomogeneous velocity medium. For numerical modeling for a gas hydrate, we determined a geological model based on field data set gathered in the East sea. The numerical modeling results showed that the von Karman autocorrelation function could properly describe scattering phenomena in the gas hydrate velocity model which contains an inhomogeneous layer. Besides, bottom-simulating-reflectors and scattered waves which appear at seismic shot gather of the field data showed properly in the inhomogeneous numerical modeling.

• Knowledge Management Research
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• v.22 no.4
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• pp.119-133
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• 2021

As a large amount of data is produced in each industry, a number of time series pattern prediction studies are being conducted to make quick business decisions. However, there is a limit to predicting specific patterns in nonlinear time series data due to the uncertainty inherent in the data, and there are difficulties in making strategic decisions in corporate management. In addition, in recent decades, various studies have been conducted on data such as demand/supply and financial markets that are suitable for industrial purposes to predict time series data of irregular random walk models, but predict specific rules and achieve sustainable corporate objectives There are difficulties. In this study, the prediction results were compared and analyzed using the Chaos analysis method for roulette data and financial market data, and meaningful results were derived. And, this study confirmed that chaos analysis is useful for finding a new method in analyzing time series data. By comparing and analyzing the characteristics of roulette games with the time series of Korean stock index future, it was derived that predictive power can be improved if the trend is confirmed, and it is meaningful in determining whether nonlinear time series data with high uncertainty have a specific pattern.