• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.9
• /
• pp.547-553
• /
• 2003

In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.

• Journal of the Korean Solar Energy Society
• /
• v.29 no.4
• /
• pp.1-6
• /
• 2009

This paper estimates numerically cells the electrical characteristics of the PV module with environmental changes such as shunt resistance, series resistance, temperature, irradiance. Series resistance $R_s$ including diode characteristic resistance $r_d$ is derived from the p-n junction diode model. I-V characteristics of this model with series resistance $R_s$ are simulated on Matlab. Finally, theoretical I-V characteristics are compared with those of solar simulator. Those results agreed well within the manufacturer's maximum error range 3%

• The Korean Journal of Applied Statistics
• /
• v.22 no.5
• /
• pp.1007-1017
• /
• 2009

Forecasting for air demand such as passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison the performance between the univariate seasonal ARIMA models and the multivariate time series models. In this paper, we used real data to predict demand on international passenger and freight. And multivariate time series models are better than the univariate models based on the accuracy criteria.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.3
• /
• pp.136-141
• /
• 2000

This paper presents the design of an H$\infty$ based robust Static Synchronous Compensator (STATCOM) supplementary controller to suppress the subsynchronous resonance (SSR) in the series-compensated system. The IEEE second benchmark, System-l model is employed for this study. In order to design the effective controller, the modal controllability and observability indices to the oscillation modes are considered. Comprehensive time domain simulations using a nonlinear system model that the proposed STATCOM supplementary controller can suppress the SSR efficiently in spite of the variations of power system operating conditions.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.9 no.11
• /
• pp.1297-1304
• /
• 2014

Love which is one of the emotional of mankind, has been studied in sociology and psychology as a matter of grate concern. In this paper We represent romantic behaviors in the love equation of Romeo and Juliet as time series and phase portraits. Also we analyze the behavior's relation by using time series and phase portraits when external force applied as the third person between Romeo and Juliet.

• Journal of the Korean Society for Precision Engineering
• /
• v.10 no.4
• /
• pp.94-103
• /
• 1993

In this work, the imaginary part of the inner modulation transfer function of the cutting dynamics is introduced for tool wear monitoring. Time-series method is utilized to construct the general three dimensional cutting dynamics whose imaginary part of the inner modulation transfer funcition shows the proportionality to tool wear at the natural frequency of the machine tool dynamics. Thus model is reduced to single-input single-output model without altering the proportionality characteristics to tool wear and implemented to the dual computer system in which one computer performs measurement while the other calculates the imaginary part of the inner modulation transfer function of the cutting dynamics by the batch least square method. The values of the imaginary part at the natural requency of the machine tool structure in the cutting direction are compared to the one calculated during machining with a brand new tool to decide the current status of the tool. The experiments shows the relevance of the proposed concept.

• Communications for Statistical Applications and Methods
• /
• v.7 no.3
• /
• pp.731-739
• /
• 2000

Conditional least square estimators for the parameters of he NLAR(p) time series models are obtained. it is also shown that these estimators are consistent and asymptotically normal.

• Journal of the Korean Chemical Society
• /
• v.60 no.1
• /
• pp.82-87
• /
• 2016

• Spatial Information Research
• /
• v.20 no.4
• /
• pp.47-55
• /
• 2012

Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

• Journal of Korea Water Resources Association
• /
• v.42 no.8
• /
• pp.673-680
• /
• 2009

Alternatives to conventional water resources are being sought due to the scarcity and the poor quality of surface water. Riverbank filtration (RBF) is one of them and considered as a promising source of water supply in some cities. Changwon City has started RBF in 2001 and field data have been accumulated. This study is to develop a time-series model for groundwater level data collected from the pumping area of RBF. The site is Daesan-myeon, Changwon City, where groundwater level data have been measured for the last five years (Jan. 2003$\sim$Dec. 2007). Minute-based groundwater levels was averaged out to monthly data to see the long-term behavior. Time-series analysis was conducted according to the Box-Jenkins method. The resulted model turned out to be a seasonal ARIMA model, and its forecasting performance was satisfactory. We believe this study will provide a prototype for other riverbank filtration sites where the predictability of groundwater level is essential for the reliable supply of water.