• Journal of Sasang Constitutional Medicine
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• v.25 no.4
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• pp.289-296
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• 2013

Objectives This study was aimed to validate Sasang Constitution Questionnaire for Japanese (SSCQ-J). Methods Sasang Constitution Questionnaire for Patients (SSCQ-P) was developed by joint researches between the Society of Sasang Constitutional Medicine and Korea Institute of Oriental Medicine. We translated SSCQ-P into Japanese and modified some items of that for Japanese. By getting approval from the Institutional Review Board（IRB）of School of Medicine, Keio University, we conducted a questionnaire survey of patients who visited Oriental Medicine Center from early January until mid-February 2011. The total of 364 patients filled out that Questionnaire and gave an interview with a Sasang constitution specialist. Using this Questionnaire data, we made Sasang constitutional classification functions and calculated diagnostic accuracy rate of SSCQ-J using discrimination analysis. Results 1. Male group's diagnostic accuracy rate of SSCQ-J was 77.01% and female was 78.10%. 2. Diagnostic accuracy of SSCQ-J was a little higher than SSCQ-P Conclusions 1. SSCQ-J can be considered to have good discriminant power compared with SSCQ-P 2. Further research with SSCQ-J will be helpful in the comparison study on the usual symptoms between Korean and Japanese as well as development of good discriminant function.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.287-295
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• 2013

This paper developed advanced gravity model for higher estimation accuracy, that deals with residuals. Previously studied paper using gravity model's residual, residual calculated that observed O-D value minus derived O-D value from gravity model, and this residual added to the target year's estimated value from gravity model. In this paper, residuals calculated on gravity model parameter estimation process, and this residual is revealed the same value that observed O-D value devided by derived O-D value from gravity model. And case study resulted that developed new gravity model that applied accordance rate of observed O-D value and derived O-D value from gravity model has higher estimation accuracy than other gravity models as basic gravity model and residual plused gravity model.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.346-355
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• 2017

Atrial fibrillation (AF) and Congestive heart failure (CHF) are increasingly widespread, costly, deadly diseases and are associated with significant morbidity and mortality. In this study, we analyzed three statistical methods for automatic detection of AF and CHF based on the randomness, variability and complexity of the heart beat interval, which is RRI time series. Specifically, we used short RRI time series with 16 beats and employed the normalized root mean square of successive RR differences (RMSSD), the sample entropy and the Shannon entropy. The detection performance was analyzed using four large well documented databases, namely the MIT-BIH Atrial fibrillation (n=23), the MIT-BIH Normal Sinus Rhythm (n=18), the BIDMC Congestive Heart Failure (n=13) and the Congestive Heart Failure RRI databases (n=25). Using thresholds by Receiver Operating Characteristic (ROC) curves, we found that the normalized RMSSD provided the highest accuracy. The overall sensitivity, specificity and accuracy for AF and CHF were 0.8649, 0.9331 and 0.9104, respectively. Regarding CHF detection, the detection rate of CHF (NYHA III-IV) was 0.9113 while CHF (NYHA I-II) was 0.7312, which shows that the detection rate of CHF with higher severity is higher than that of CHF with lower severity. For the clinical 24 hour data (n=42), the overall sensitivity, specificity and accuracy for AF and CHF were 0.8809, 0.9406 and 0.9108, respectively, using normalized RMSSD.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.166-176
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• 2002

A homonym could be disambiguated by another words in the context as nouns, predicates used with the homonym. This paper using semantic information (co-occurrence data) obtained from definitions of part of speech (POS) tagged UMRD-S$^1$), In this research, we have analyzed the result of an experiment on a homonym disambiguation system based on statistical model, to which Bayes'theorem is applied, and suggested a model established of the weight of sense rate and the weight of distance to the adjacent words to improve the accuracy. The result of applying the homonym disambiguation system using semantic information to disambiguating homonyms appearing on the dictionary definition sentences showed average accuracy of 98.32% with regard to the most frequent 200 homonyms. We selected 49 (31 substantives and 18 predicates) out of the 200 homonyms that were used in the experiment, and performed an experiment on 50,703 sentences extracted from Sejong Project tagged corpus (i.e. a corpus of morphologically analyzed words) of 3.5 million words that includes one of the 49 homonyms. The result of experimenting by assigning the weight of sense rate(prior probability) and the weight of distance concerning the 5 words at the front/behind the homonym to be disambiguated showed better accuracy than disambiguation systems based on existing statistical models by 2.93%,

• Journal of Biomedical Engineering Research
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• v.37 no.5
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• pp.161-167
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• 2016

Recent technological advances in sensor fabrication and bio-signal processing enabled non-constraint and non-intrusive measurement of human bio-signals. Especially, non-constraint measurement of ECG makes it available to estimate various human health parameters such as heart rate. Additionally, non-constraint ECG measurement of wheelchair user provides real-time health parameter information for emergency response. For accurate emergency response with low false alarm rate, it is necessary to discriminate quality levels of ECG measured using non-constraint approach. Health parameters acquired from low quality ECG results in inaccurate information. Thus, in this study, a machine learning based approach for three-class classification of ECG quality level is suggested. Three sensors are embedded in the back seat, chest belt, and handle of automatic wheelchair. For the two sensors embedded in back seat and chest belt, capacitively coupled electrodes were used. The accuracy of quality level classification was estimated using Monte Carlo cross validation. The proposed approach demonstrated accuracy of 94.01%, 95.57%, and 96.94% for each channel of three sensors. Furthermore, the implemented algorithm enables classification of user posture by detection of contacted electrodes. The accuracy for posture estimation was 94.57%. The proposed algorithm will contribute to non-constraint and robust estimation of health parameter of wheelchair users.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.19-26
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• 2012

The rapid increase of information imposes new demands of content management. The purpose of automatic audio segmentation and classification is to meet the rising need for efficient content management. With this reason, this paper proposes a high-accuracy algorithm that segments audio signals and classifies them into different classes such as speech, music, silence, and environment sounds. The proposed algorithm utilizes support vector machine (SVM) to detect audio-cuts, which are boundaries between different kinds of sounds using the parameter sequence. We then extract feature vectors that are composed of statistical data and they are used as an input of fuzzy c-means (FCM) classifier to partition audio-segments into different classes. To evaluate segmentation and classification performance of the proposed SVM-FCM based algorithm, we consider precision and recall rates for segmentation and classification accuracy for classification. Furthermore, we compare the proposed algorithm with other methods including binary and FCM classifiers in terms of segmentation performance. Experimental results show that the proposed algorithm outperforms other methods in both precision and recall rates.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.1
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• pp.3-12
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• 1988

The objective of this paper is to study the characteristics of combination method to correct both angle and distance errors simultaneously based on the least square adjustment methods. Changing the standard errors of distance and angle, the simulation errors of triangultion, trilateration, and combination result in some 39.8%, 33.9%, and 26.3% respectively. As the above, combination method shows more consistent accuracy than other methods. When considering the weight factor about error elements with independence, the diminishing rate of simulated average standard error represents a various change in each method. But considering them simultaneously, it shows a remarkable rate of diminishing 75.5%, 74.1%, and 69.2% in each method. And also, by growing the weight factor, accuracy of triangulation method is growing, whereas that of trilateration is diminishing. Therefore, determining the reasonable weight factors of distance and angle errors simultaneously in the analytical combination method, this method is expected to be one of more accurate and more effective methods for determining horizontal positions on the earth.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.17-26
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• 2017

Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.86.1-86.1
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• 2011

We are developing a new universal spectropolarimeter on the Domeless Solar Telescope (DST) at the Hida Observatory to realize precise spectropolarimetric observations in a wide range of wavelength in visible and near infrared. The system aims to open a new window of plasma diagnostics by using Zeeman effect, Hanle effect, Stark effect, impact polarization, and atomic polarization for measuring the external magnetic field, electric field, or an anisotropy in the excitation of the atoms. The polarimeter is a successor of formerly developed polarimeter on DST, which make possible to observe a polarization in a photospheric spectral line with polarimetric accuracy of 10-2 (Kiyohara et al. 2004). The new system consists of a 60cm aperture vacuum telescope, a high dispersion vacuum spectrograph, polarization modulator / analyzer composed of a rotating waveplate whose retardation is constant for a wide range of wavelength and Wallaston prism, and a fast and large format CCD camera or IR camera. Spectral images in both orthogonal polarizations are taken simultaneously with a frame rate of ~20Hz while the waveplate rotates continuously in a rate of 1rev./sec. Thus It takes 5 ~ 60 sec to observe polarization with accuracy of 10-3 in a wide wavelength range (400 - 1100nm). We also examined a polarimetric model of the telescope with accuracy of 10-3 to calibrate instrumental polarization on some wavelengths. In this talk, I will focus on the performance of the instrument.