• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.60.2-60.2
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• 2011

We introduce the preliminary results of flux monitoring of BL Lac object 0716+714 with the KVN Ulsan 21m radio telescope. This radio source is well known as the intraday variable (IDV) source which is characterized by the rapid flux variation on the time scale of a day or less. In general, the IDV phenomenon is interpreted as the effect of refractive scintillation in the interstellar medium or the evidence of intrinsic flux variation. In previous observations that took a few days, however, it had not been detected the flux variation of short time scale but the monotonic increase and decrease. Therefore, to investigate the longer time scale of 0716+714, we had the flux variation monitoring at 22GHz and 43GHz simultaneously for 9 months from October 2010 to June 2011. We present here the structure functions and the cross correlation functions between different frequencies as well as the light curves.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.282-282
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• 2000

The analysis of the radiation effect on matter has been performed using stochastic methods. Recently, It was discovered that the detector pulses of radiation can be analysed using deterministic method that utilizes the chaotic behaviour with an attractor found in a noise region. We acquired a time series for pulse tram of Am-241 using scintillation detector and reconstructed a phase space, then performed new analysis for the radiation detection signal by applying embedding theory, Lyapunov exponent, correlation dimension, autocorrelation dimension, and power spectrum.

• Proceedings of the KSPS conference
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• 2005.04a
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• pp.25-28
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• 2005

The purpose of this paper is to represent values of acoustic cues for Korean oral stops in the multi-dimensional space, and to attempt to find possible relationships among acoustic cues through correlation coefficient analyses. The acoustic cues used for differentiation of 3 types of Korean stops are closure duration, voice onset time and fundamental frequency of a vowel after a stop. The values of these cues are plotted in the two and three dimensional space and see what the critical cues are for complete separation of different types of stops. Correlation coefficient analyses show that there are statistically significant relationships among acoustic cues but they are not strong enough to make a conjecture that there is a possible articulatory relationship among the mechanisms employed by the acoustic cues.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.226-235
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• 1998

This study proposes the analysis and evaluation of method of time series of ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. The features are extracted from time series data for analysis of weld defects quantitatively. For this purpose, analysis objectives in this study are fractal dimension, Lyapunov exponent, and strange attractor on hyperspace. The Lyapunov exponent is a measure of rate in which phase space diverges nearby trajectories. Chaotic trajectories have at least one positive Lyapunov exponent, and the fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal(correlation) dimensions and Lyapunov exponents show the mean value of 4.663, and 0.093 relatively in case of learning, while the mean value of 4.926, and 0.090 in case of testing in slag inclusion(weld defects) are shown. Therefore, the proposed chaotic feature extraction can be enhancement of precision rate for ultrasonic pattern recognition in defecting signals of weld zone, such as slag inclusion.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.543-552
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• 1996

The goal of this paper is to developed a DSP based power analyzing and control system by 3-Dimensional (3-D) space current co-ordinates. A developed system is made up of 486-PC and DSP (Digital Signal Processor) board, Active Power Filter, Non-linear thyristor load, and Power analyzing and control program for Windows. Power is analyzed using signal processing techniques based on the correlation between voltage and current waveforms. Since power analysis algorithm is performed by DSP, power analysis is achieved in real-time even under highly dynamic nonlinear loading conditions. Combining control algorithm with power analysis algorithm is performed by DSP, power analysis is achieved in real-time even under highly dynamic nonlinear loading conditions. Combining control algorithm with power analysis algorithm, flexibility of the proposed system which has both power analysis mode and control mode, is greatly enhanced. Non-active power generated while speed of induction motor is controlled by modulating firing angle of thyristor converter, is compensated by Active Power Filter for verifying a developed system. Power analysis results, before/after compensation, are numerically obtained and evaluated. From these results, various graphic screens for time/frequency/3-D current co-ordinate system are displayed on PC. By real-time analysis of power using a developed system, power quality is evaluated, and compared with that of conventional current co-ordinate system. (author). refs., figs. tabs.

• Korean Institute of Interior Design Journal
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• no.41
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• pp.137-145
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• 2003

This research analyzed the space scheme in connection with complexity, one of the new changes in the discount stores, and has a goal of predicting the direction of space scheme in the upcoming complexity era. The research was conducted in the following way. Firstly, this researcher tried to grasp what kinds of changes were required in the overall distribution industry socially and economically. Secondly, the characteristic and situation of discount stores were scrutinized. Thirdly, the domestic stores' complexity status was classified and types of those were elicited. Fourthly, the time-series change and use were analyzed. The result of this analysis reveals that the types of complexity can be divided by location and adjustment to environmental changes. The time-series analysis shows that total operating area, the number of parked cars and the tenant ratio have increased dramatically in 2000 and 2003. And, according to the correlation analysis between factors, the tenant ratio has, a strong correlation with other two factors. Self-complexity takes the basic form of living facilities and complexity with other facilities is combined with other cultural, sales, educational and administrative ones. Mass-complexity is merged with the stadiums, parks or station sites. As you've seen, the concept of complex shopping mall for the realization of one stop shopping and convenience will continue in the days to come. It is desirable that the study on the large-scale shopping spaces will be conducted continually for the preparedness of future life style.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.123.1-123.1
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• 2012

We have compared near-real time Kp forecast models based on neural network (NN) and support vector machine (SVM) algorithms. We consider four models as follows: (1) a NN model using ACE solar wind data; (2) a SVM model using ACE solar wind data; (3) a NN model using ACE solar wind data and preliminary kp values from US ground-based magnetometers; (4) a SVM model using the same input data as model 3. For the comparison of these models, we estimate correlation coefficients and RMS errors between the observed Kp and the predicted Kp. As a result, we found that the model 3 is better than the other models. The values of correlation coefficients and RMS error of the model 3 are 0.93 and 0.48, respectively. For the forecast evaluation of models for geomagnetic storms ($Kp{\geq}6$), we present contingency tables and estimate statistical parameters such as probability of detection yes (PODy), false alarm ratio (FAR), bias, and critical success index (CSI). From a comparison of these statistical parameters, we found that the SVM models (model 2 and model 4) are better than the NN models (model 1 and model 3). The values of PODy and CSI of the model 4 are the highest among these models (PODy: 0.57 and CSI: 0.48). From these results, we suggest that the NN models are better than the SVM models for predicting Kp and the SVM models are better than the NN models for forecasting geomagnetic storms.

• The Journal of Sustainable Design and Educational Environment Research
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• v.18 no.3
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• pp.28-38
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• 2019

For students and staff members who spend long periods of time in school, schools must meet a variety of needs such as learning, rest, experience, exchange, play, culture, meeting, and meals. The purpose of this study is to provide basic data aim at improving the school environment by investigating and analyzing the characteristics of middle school students'. For this purpose, the theoretical data collection : case studies and questionnaires, were conducted to analyze the correlation between student's activities and the space utilization of the school. First of all, a questionnaire survey was conducted on 301 middle school students in Ulsan. The t-test and ANOVA analysis were conducted on the questionnaire results to examine whether there was any difference in the perception of school space. The analysis showed significant correlation between interaction with school space according to the characteristics of students' activities. However, there are problems such as the use of space for various.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.51.2-51.2
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• 2010

We have investigated 63 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O'Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (${\Delta}$peak), and the difference of Dst minimum time (${\Delta}$peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of ${\Delta}$peak of 12.54 nT, and a MAD of ${\Delta}$peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of ${\Delta}$peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of ${\Delta}$peak of SH structure of Temerin and Li model are very lower than those of other models.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.38.2-38.2
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• 2010

We have examined the occurrence probability of solar proton events (SPEs) and their peak fluxes depending three flare parameters (X-ray peak flux, longitude, and impulsive time). For this we used NOAA SPEs from 1976 to 2006, and their associated X-ray flare data. As a result, we selected 166 proton events that were associated with major flares; 85 events associated with X-class flares and 81 events associated with M-class flares. Especially the occurrence probability strongly depends on these three parameters. In addition, the relationship between X-ray flare peak flux and proton peak flux as well as its correlation coefficient are strongly dependent on longitude and impulsive time. Among NOAA SPEs from 1997 to 2006, most of the events are related to both flares and CMEs but a few fraction of events (5/93) are only related with CMEs. We carefully identified the sources of these events using LASCO CME catalog and SOHO MDI data. Specifically, we examined the directions of CMEs related with the events and the history of active regions. As a result, we were able to determine active regions which are likely to produce SPEs without ambiguity as well as their longitudes at the time of SPEs by considering solar rotation rate. From this study, we found that the longitudes of five active regions are all between $90^{\circ}W$ and $120^{\circ}W$. When the flare peak time is assume to be the CME event time, we confirmed that the dependence of their rise times (proton peak time - flare peak time) on longitude are consistent with the previous empirical formula. These results imply that five events should be also associated with flares which were not observed because they occurred from back-side. Now we are examining the occurrence probability of SPEs depending on CME parameters. Finally, we will discuss the future prospects on the development of an empirical SPE forecast model based on the information of flares and CMEs.