• Journal of Welding and Joining
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• v.16 no.6
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• pp.86-96
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• 1998

This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.82-89
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• 2023

Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.290-297
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• 2003

A time-series database is a set of data sequences, each of which is a list of changing values corresponding to an object. Subsequence matching under time warping is defined as an operation that finds such subsequences whose time warping distance to a given query sequence are below a tolerance from a time-series database. In this paper, we first point out the characteristics of the previous methods for time-series sequence matching under time warping, and then discuss the approaches for applying them to whole matching as well as subsequence matching. Also, we perform quantitative performance evaluation via a series of experiments with real-life data. There have not been such researches in the literature that compare the performances of all the previous methods of subsequence matching under time warping. Thus, our results would be used as a good reference for showing their relative performances.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.111-116
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• 2004

An experiment was carried out to confirm the validity of time series evaluation of supersonic mixing condition by using catalytic reaction on a platinum wire. Geseous hydrogen was injected parallel to supersonic freestream (M$\infty$ $\approx$ 1.81) from a slit injector, which was located at backward facing step. Time series condition of supersonic mixing was evaluated by using W-type probe which has a platinum wire and reference wire (nickel wire). The evaluation was by simultaneously measuring each electric circuit which kept the temperature of wire constant. Investigations were also conducted for helium, air and no secondary injectant cases to compare with the hydrogen injectant case. The results indicated that it was possible to measure the time series behavior of air and hydrogen supersonic mixing layer or coherent motion of turbulence by using this evaluation.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.219-227
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• 2007

The time series models have been used to analyze and predict the network traffic. In this paper, we compare the performance of the time series models for prediction of network traffic. The feasibility study showed that a class of nonlinear time series models can be outperformed than the linear time series models to predict the network traffic.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.50-56
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• 2021

An accurate evaluation of three-dimensional (3D) Time-Domain Green Function (TDGF) in infinite water depth is essential for ship's hydrodynamic analysis. Various numerical algorithms based on the TDGF properties are considered, including the ascending series expansion at small time parameter, the asymptotic expansion at large time parameter and the Taylor series expansion combines with ordinary differential equation for the time domain analysis. An efficient method (referred as "Present Method") for a better accuracy evaluation of TDGF has been proposed. The numerical results generated from precise integration method and analytical solution of Shan et al. (2019) revealed that the "Present method" provides a better solution in the computational domain. The comparison of the heave hydrodynamic coefficients in solving the radiation problem of a hemisphere at zero speed between the "Present method" and the analytical solutions proposed by Hulme (1982) showed that the difference of result is small, less than 3%.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.869-876
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• 2012

In this paper, we applied seasonal time series models such as ARIMA, FARIMA, AR-GARCH and Holt-Winters in consideration of seasonality to forecast short-term electricity demand data. The results for performance evaluation on the time series models show that seasonal FARIMA and seasonal Holt-Winters models perform adequately under the criterion of Mean Absolute Percentage Error(MAPE).

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.917-923
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• 2012

We perform a comparison of time series models that include seasonal ARIMA, Fractional ARIMA, and Holt-Winters models; in addition, we also consider hourly and daily air passenger data. The results of the performance evaluation of the models show that the Holt-Winters methods outperforms other models in terms of MAPE.

• Journal of Information Display
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• v.10 no.4
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• pp.188-194
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• 2009

Conventional stereoscopic (3D) displays using binocular parallax generate unnatural conflicts between convergence and accommodation. These conflicts can affect the observer's ability to fuse binocular images and may cause visual fatigue. In this study, time series changes in visual fatigue and depth sensation when viewing stereoscopic images with changing parallax were examined. In particular, the physiological changes, including the subjective symptoms of visual fatigue, when viewing five parallax conditions, were examined. Then a comparative analysis of the 2D and 3D conditions was performed based on the visual function. To obtain data regarding the visual function, the time series changes in the spontaneous-blinking rate before and during the viewing of 3D images were measured. The time series change results suggest that 2D and 3D images cause significantly different types of visual fatigue over the range of binocular disparity.