• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.579-582
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• 2001

The performance of a coherent rake receiver of DS-CDMA systems is significantly affected by the accuracy of channel estimation. The performance of the channel estimator can be improved by employing a channel estimation filter (CEF) whose impulse response is adjusted according to the channel condition. In this paper, we consider the design of an adaptive channel estimator for DS-CDMA systems with a pilot channel. The proposed channel estimator estimates the channel condition, which can be performed without haying exact a priori information on the operating condition. The estimated channel condition adjusts the impulse response of the CEF. Numerical results show that the use of the proposed channel estimator can provide BER performance quite robust to a wide range of channel condition.

• Communications for Statistical Applications and Methods
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• v.23 no.4
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• pp.287-296
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• 2016

Subjects on one side of the covariate population can be allocated to the inferior treatment when there is interaction between the covariate and treatment along with a response-adaptive (RA) design without covariate adjustment. An RA design allows a newly entered subject to have a better chance so that the subject is treated by a superior treatment based on cumulative information from previous subjects. A covariate-adjusted response-adaptive (CARA) is the same as RA design and additionally adjusts the allocation based on individual covariate information. A comparison has been made for the sequential estimation procedure with and without covariate adjustment to see how ignoring significantly interactive covariate affects the correct treatment allocation. Using logistic models, we present simulation results regarding the coverage probability of treatment effect, correct allocation, and stopping time.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.13-18
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• 2012

This paper presents a velocity disturbance estimation system for the stable fine seek control using a genetic algorithm. To estimate accurately the velocity disturbance in spite of the uncertainties of fine actuator, the system utilizes an objective function to minimize the differences of the frequency characteristics between the nominal velocity control loop and the extremal velocity control loops. The objective function is considered by applying a genetic algorithm and the velocity disturbance is estimated by the measurable velocity, the adjusted velocity controller, and the fine actuator model. The proposed velocity disturbance estimation system is applied to the fine seek control system of a DVD recording device and is evaluated through the experimental results.

• Journal of Korean Society of Steel Construction
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• v.24 no.5
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• pp.571-582
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• 2012

Prestressed composite girders provide efficient composite action by applying prestress to the sub-encasing concrete. In this study, an enhanced prestressed composite girder with forms suspended from the steel girder is utilized. Long-term behavior of the prestressed composite girder is estimated using age-adjusted effective modulus method, which is verified experimentally using measurements obtained from an in-service bridge. Then, parametric study is carried out to investigate the influences caused by ambient temperature, humidity, prestressing and concrete casting date.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.7-15
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• 2017

Ambient Adjusted line Rating(AAR) method for overhead transmission lines considering Risk Tolerance(RT) was proposed in this paper. AAR is suitable for system operators to plan their operation strategy and maintenance schedule because this can be designed as a seasonal line rating. Several candidate transmission lines are chosen to apply the proposed method in the paper. As a result, it is shown that system reliability was significantly enhanced through maximizing transfer capability, solving the system constraints.

• Journal of Oral Medicine and Pain
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• v.46 no.2
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• pp.21-32
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• 2021

Purpose: The purpose of the present study was to investigate the correlation between age and 34 radiomorphometric parameters on panoramic radiographs, and to provide generalized linear models (GLMs) as a non-invasive, inexpensive, and accurate method to the forensic judgement of living individual's age. Methods: The study included 417 digital panoramic radiographs of Korean individuals (178 males and 239 females, mean age: 32.57±17.81 years). Considering the skeletal differences between the sexes, GLMs were obtained separately according to sex, as well as across the total sample. For statistical analysis and to predict the accuracy of the new GLMs, root mean squared error (RMSE) and adjusted R-squared (R²) were calculated. Results: The adjusted R²-values of the developed GLMs in the total sample, and male and female groups were 0.623, 0.637, and 0.660, respectively (p<0.001), while the allowable RMSE values were 8.80, 8.42, and 8.53 years, respectively. In the GLM of the total sample, the most influential predictor of greater age was decreased pulp area in the #36 first molar (beta=-26.52; p<0.01), followed by the presence of periodontitis (beta=10.24; p<0.01). In males, the most influential factor was the presence of periodontitis (beta=9.20; p<0.05), followed by the number of full veneer crowns (beta=2.19; p<0.001). In females, the most influential predictor was the presence of periodontitis (beta=18.10; p<0.001), followed by the tooth area of the #16 first molar (beta=-11.57; p<0.001). Conclusions: We established acceptable GLM for each sex and found out the predictors necessary to age estimation which can be easily found in panoramic radiographs. Our study provides reference that parameters such as the area of tooth and pulp, the number of teeth treated, and the presence of periodontitis should be considered in estimating age.

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• Journal of Power Electronics
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• v.17 no.1
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• pp.149-160
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• 2017

To improve the performance of sensorless induction motor (IM) drives, an adaptive speed estimation method based on a strong tracking extended Kalman filter with a least-square algorithm (LS-STEKF) for induction motors is proposed in this paper. With this method, a fading factor is introduced into the covariance matrix of the predicted state, which forces the innovation sequence orthogonal to each other and tunes the gain matrix online. In addition, the estimation error is adjusted adaptively and the mutational state is tracked fast. Simultaneously, the fading factor can be continuously self-tuned with the least-square algorithm according to the innovation sequence. The application of the least-square algorithm guarantees that the information in the innovation sequence is extracted as much as possible and as quickly as possible. Therefore, the proposed method improves the model adaptability in terms of actual systems and environmental variations, and reduces the speed estimation error. The correctness and the effectiveness of the proposed method are verified by experimental results.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.5
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• pp.35-44
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• 2011

In a spark ignition engine, a variable valve lift (VVL) system has been developed for high fuel efficiency and low power loss. However, changes in valve lift cause deviations of cylinder air charge which lead to individual cylinder equivalence ratio maldistribution. In this study, in order to reduce the maldistribution, we propose individual cylinder equivalence ratio estimation and control algorithms. The estimation algorithm calculates the equivalence ratio of each cylinder by using a mathematical engine model which includes air charging, fuel film, exhaust gas, and universal exhaust gas oxygen sensor (UEGO) dynamics at various valve lifts. Based on the results of estimated equivalence ratio, the injection quantity of each cylinder is adjusted to control the individual cylinder equivalence ratio. Estimation and control performance are validated by engine experiments. Experimental results represented that the equivalence ratio maldistribution and variation are decreased by the proposed algorithms.

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.