• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.58.2-58.2
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• 2012

Wilson and Bappu (1957), for the first time, and other precedent studies (Lutz & Kelker 1975; Pasquini et al. 1988; Dupree & Smith 1995; Wallerwstein et al. 1999; Pace et al. 2003) found a tight correlation (called Wilson-Bappu relationship - WBR) between stellar absolute visual magnitude and the width of the Ca II K line emission feature for late type stars. Here we re-visit WBR to claim that WBR can be an excellent indicator of stellar surface gravity of late type stars as well as a good indicator of distance. We have analyzed 103 high-resolution spectra of G, K and M type stars obtained by UVES and BOES by following the method by Pace et al. (2003) for measuring the widths of Ca II K lines(W). WBR found in our samples is Mv=33.26-17.79logW and the correlation is very tight. In this study, the stellar gravity(log g) has been derived using Kurucz ALAS9 model grid and MOOG code, which can determine $T_{eff}$ and [M/H] too.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8C
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• pp.771-776
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• 2006

We present a suboptimum decoding method for space-time trellis codes, which include maximum $likelihood(ML)^{[1]}$ and principal ratio $combining(PRC)^{[2]}$, over quasi-static flat fading channels. In the proposed scheme, the receive antennas are divided into K groups and the PRC is applied to each group, showing a flexible performances between ML and PRC. When K is determined, we also propose the optimum grouping rules and performance index(PI), which simply anticipate the relative performances. Moreover the performances are also evaluated when receive antennas are correlated. Finally, Computer simulations corroborate those theoretical results.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.64.1-64.1
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• 2013

High energy photons and mechanical energy produced by the process of star formation result in copious FIR molecular and atomic lines, which are important coolants of the system. Photons thermally or mechanically induced could dissociate water in the dense envelope to change relative abundances among the species O, OH, and H2O. Here we analyze OH emission lines toward embedded young stellar objects (YSOs) observed as part of the Herschel open time key program, 'Dust, Ice, and Gas In Time (DIGIT)' in order to study the physical conditions of associated gas and the energy budget loaded on the OH line emission. According to our analysis of the Herschel/PACS spectra, OH emission peaks at the central spaxel in most of sources, but several sources show spatially extended emission structures. In the extended emission sources, the distribution of OH emission is correlated with that of [OI] emission and extended along the outflow directions. Considering the diversity of source properties, ratios between detected OH lines are relatively constant among sources. In addition, each OH line has strong correlation with bolometric luminosity. For detail analyses with rotation diagram and non-LTE LVG model, we present the results from GSS30-IRS1 and Elias29.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.258-263
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• 2010

Sound localization algorithm usually adapts three step process: sampling sound signals, estimating time difference of arrival between microphones, estimate location of sound source. To apply this process in indoor environment, sound localization algorithm must be strong enough against reverberant and noisy condition. Additionally, calculation efficiency must be considered in implementing real-time sound localization system. To implement real-time robust sound localization system we adapt four low cost condenser microphones which reduce the cost and total calculation load. And to get TDOA(Time Differences of Arrival) of microphones we adapt GCC-PHAT(Generalized Cross Correlation-Phase Transform) which is robust algorithm to the reverberant and noise environment. The position of sound source was calculated by using iterative least square algorithm which produce highly accurate position data.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.83-87
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• 2007

Correlation Propagation Neural Networks is proposed for On-line interpolation. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed. 1-D CPNN hardware has been implemented with general purpose analog ICs to test the interpolation capability of the proposed neural networks. Experiments with static and dynamic signals have been done upon the CPNN hardware.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.55-56
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• 2023

Recently, large and high-rise buildings are increasing, and accordingly, concrete weight reduction is required. Lightweight aggregate concrete can provide economic feasibility and large space, but safety can be reduced due to problems such as low strength and poor durability. Since the development of such low strength of concrete is important in the early construction stage, it is necessary to evaluate the vertical formwork demolding period at the early age. The correlation was analyzed by measuring the compressive strength and ultrasonic pulse velocity. As a result, the ultrasonic pulse rates of normal and lightweight aggregate concrete at the time of 5 MPa expression, which is the time of vertical mold deformation, were 3.07 km/s and 2.77 km/s for W/B 41, and 2.89 km/s and 2.73 km/s for W/B 33.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4117-4135
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• 2020

Due to the angle of view, illumination and scene diversity, real-time dynamic face detection and recognition is no small difficulty in those unrestricted environments. In this study, we used the intrinsic correlation between detection and calibration, using a multi-task cascaded convolutional neural network(MTCNN) to improve the efficiency of face recognition, and the output of each core network is mapped in parallel to a compact Euclidean space, where distance represents the similarity of facial features, so that the target face can be identified as quickly as possible, without waiting for all network iteration calculations to complete the recognition results. And after the angle of the target face and the illumination change, the correlation between the recognition results can be well obtained. In the actual application scenario, we use a multi-camera real-time monitoring system to perform face matching and recognition using successive frames acquired from different angles. The effectiveness of the method was verified by several real-time monitoring experiments, and good results were obtained.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.3
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• pp.427-435
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• 1997

Conditional sampling techniques are utilized to investigate the relation between the wall skin-friction and stream wise velocity fluctuations in a turbulent boundary layer. Conditionally averaged results using a peak detection and the VITA (variable-interval time-averaging) technique show that a high skin friction is associated with high frequency components of the wall skin-friction fluctuations. The conditionally averaged wall skin-friction fluctuations obtained by using the VITA technique have a positively-skewed characteristics compared with the conditionally averaged stream wise velocity fluctuations. It is confirmed that there exists a phase shift between the wall skin-friction and stream wise velocity fluctuations, which was also found from the long-time averaged space-time correlations. The amount of phase shift between the wall skin-friction and stream wise velocity fluctuations is the same as that from the long-time averaged space-time correlations and does not change despite the variation of the detection threshold.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.551-554
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• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.