• ETRI Journal
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• v.37 no.6
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• pp.1154-1164
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• 2015

This paper proposes a fully sensorless driver for a permanent magnet synchronous motor (PMSM) integrated with a digital motor controller and an analog pre-driver, including sensing circuits and estimators. In the motor controller, a position estimator estimates the back electromotive force and rotor position using a sliding-mode observer. In the pre-driver, drivers for the power devices are designed with a level shifter and isolation technique. In addition, a current sensing circuit measures a three-phase current. All of these circuits are integrated in a single chip such that the driver achieves control of the speed with high accuracy. Using an IC fabricated using a $0.18{\mu}m$ BCDMOS process, the performance was verified experimentally. The driver showed stable operation in spite of the variation in speed and load, a similar efficiency near 1% compared to a commercial driver, a low speed error of about 0.1%, and therefore good performance for the PMSM drive.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.73-78
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• 2018

This study focuses on presenting the IT program module provided by BKLS measure in order to solve the problem of capital cost due to information asymmetry of external investors and corporate executives. Barron at al(1998) set up a BKLS measure to guide the market by intermediate analysts. The BKLS measure was measured by using the changes in the analyst forecast dispersion and analyst mean forecast error squared. This study suggests a model of the algorithm that the BKLS measure can be provided to all investors immediately by IT program in order to deliver the meaningful value in the domestic capital market as measured. This is a method of generating and analyzing real-time or non-real-time prediction models by transferring the predicted estimates delivered to the Big Data Log Analysis System through the statistical DB to the statistical forecasting engine. Because BKLS measure is not carried out in a concrete method, it is practically very difficult to estimate the BKLS measure. It is expected that the BKLS measure of Barron at al(1998) introduced in this study and the model of IT module provided in real time will be the starting point for the follow-up study for the introduction and realization of IT technology in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.1907-1914
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• 1998

This paper proposes the adaptive connection admission cotrol using the variale MRR(measurement reflection ratio) and the distribution of the number of cells arriving during the fixed interval. This distribution is estimated from the measured number of cells arriving at the output buffer during the fixed interval and traffic parameters specified by user. MRR is varied by the difference of estimated distribution and measurement distribution. As MRR is adaptively varied by estimated distribution error of accepted connections, it quickly reduces estimation error. Also, the scheduling scheme is proposed for multiplexed traffic with various traffic characteristics. For each traffic class, this scheme estimates adaptively equivalent bandwidth and schedules according to equivalent bandwidth ratio of each traffic class, so it improves cell loss rate and link utilization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1499-1509
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• 2000

In this paper, we propose an efficient channel estimation technique for space-time coded orthogonal frequency-division multiplexing (OFDM) systems with transmitter and receiver diversity. The proposed technique estimates uniquely all channel frequency responses needed in a decoder of space-time coded OFDM systems using "comb-type" raining symbols. The computational complexity of the proposed technique is reduced dramatically, compared with the previous minimum mean-squared error (MMSE) technique, due to the processing is made all in the frequency-domain. Also, several other techniques for mitigating random noise effect and tracking channel variation are discussed to further improve the performance of the proposed approach. The performances of the proposed approach are demonstrated by computer simulation for mobile wireless channels. channels.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.293-300
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• 2015

Recently, multiuser diversity(MUD) technique is used to improve the performance of OFDM transmission systems. With STBC antenna diversity technique, the performance of OFDM systems can be also improved. Pilot symbol is used for the channel estimation in OFDM systems. However, imperfect channel estimates in this systems degrade the performance. The performance of MUD STBC OFDM systems using pilot symbol, gauged by the bit error rate, is analyzed considering the channel estimation error. Result shows that MUD can improve the required power by a factor of approximately 5 dB for users number 32.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.237-252
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• 2013

An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model, autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.2
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• pp.257-267
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• 2019

The paper aims to test long-term and short-term causality from four exchange rates, the Korean won/$US, the Korean won/Euro, the Korean won/Japanese yen, and the Korean won/Chinese yuan, to the Korea Composite Stock Price Index in the presence of several macroeconomic variables using monthly data from January 1986 to June 2018. The results of Johansen cointegration tests show that there exists at least one cointegrating equation, which indicates that long-run causality from an exchange rate to the Korean stock market will exist. The results of vector error correction estimates show that: for long-term causality, the coefficient of the error correction term is significant with a negative sign, that is, long-term causality from exchange rates to the Korean stock market is observed. For short-term causality, the coefficient of the Japanese yen exchange rate is significant with a positive sign, that is, short-term causality from the Japanese yen exchange rate to the Korean stock market is observed. The coefficient of the financial crises i.e. 1997-1999 Asian financial crisis and 2007-2008 global financial crisis on the endogenous variables in the model and the Korean economy is significant. The result indicates that the financial crises have considerably affected the Korean economy, especially a negative effect on money supply.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.35-42
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• 2002

The results of our observation in May 2000 indicated that the SeaWiFS algorithm (O'Reilley et al., 1998), which was adopted for OSMI data processing, overestimated the actual chlorophyll values. This was rather unexpected in that there were good reasons to expect that the bio-optical properties of East/Japan Sea belonged to Case 1 water and in such case, the OC2 algorithm would give unbiased estimates of actual chlorophyll a values. In November 2000, a cruise conducted bio-optical surveys in the same area. This time we added HPLC (High Performance Liquid Chromatography) method for measuring chlorophyll a concentration to the standard fluorometric method, which we hale been using during the past Fluorometric method with acidification is known to result in under/overestimation of chlorophyll values in many parts of the world oceans, while it is easier and cheaper than HPLC method. To our surprise, the comparison of HPLC chlorophyll and fluorometric chlorophyll values show that fluorometric values gave an underestimation up to 50%. This error was due to the presence of accessory pigments such as chlorophyll b. Considering this error, our precious result of May 2000(Yoo et al., 2000) might have to be reinterpreted. Calculation of reflectance at 490 and 555nm, however, indicated that this is not still enough to explain the discrepancies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.23-34
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• 2020

The paper revisits the author's previous paper to examine short-run and long-run dynamic relationships between macroeconomic variables and stock prices in Korea. The data is updated to the period for which monthly data are available from January 1986 to June 2018 (390 observations) retrieved from the Bank of Korea. The results of Johansen cointegration test indicate that at least one cointegrating equation exists, confirming there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Korea. The results of vector error correction estimates confirm that: 1) the coefficient of the error correction term is significant with a negative sign, which is, a long-run dynamic relationship is observed between macroeconomic variables and stock prices; 2) for short-run dynamics, the nominal exchange rate of the Korean won per the US dollar is positively related to stock prices, while interest rates are negatively related to stock prices in the short-run; 3) the coefficient of global financial crises is insignificant, that is, the changes of stock prices are determined largely by their own dynamics in the model. The results suggest only that the global financial crises neither cause instability in the cointegrating vector, nor affect significant changes in the endogenous variables in the model.

• ETRI Journal
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• v.43 no.4
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.