• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.768-772
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• 2001

The paper deals with the control of the synchronous reluctance machine without position sensor. A method for the computation of the transformation angle out of terminal voltages and currents is presented. The injection of test signals allows operation at zero speed. Fundamental for this control scheme is the exact modelling of the machine, where especially the saturable inductances are of central interest. The accuracy of the angle estimation method over the whole operating range including field-weakening is discussed in detail. The implementation of the angle estimation method in a rotor-oriented control scheme and practical results are demonstrated.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.32-32
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• 2011

• Fire Science and Engineering
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• v.17 no.3
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• pp.1-6
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• 2003

In this study, it reviewed about evacuation performance of a specified Office Building. assessment tools is FAST 3.1.7 (Estimation of Flash Over, Estimation of Layer Height Down Flow Time), SIMULEX 32-bit (Estimation of Evacuation Time), JASMINE 3.25d. (Smoke Flow Assessment of a specified time) Result from Fire Scenario # 1, Flash Over is not generated in Compartment. Evacuation Time is estimated 25.2 sec by SIMULEX 32-bit. layer height until this time (25.2 sec) was estimated 2.4 m by FAST 3.1.7. After ignition until this time (25.2 sec), smoke was not release to the a corridor. In consequence, We concluded that people in building are completing the safe evacuation without the damage of smoke. Result from Fire Scenario # 1, Flash Over generated 6 min 33.2 sec in Compartment. Evacuation Time is estimated 1 min 25.5 sec by SIMULEX 32-bit. layer height down flow time is 1 min 40.8 sec by FAST 3.1.7 and 5 min 23 sec by theoretical calculation. Also, total building evacuation time was estimated 2 min 26.6 sec. After ignition until this time (2 min 26.6 sec), smoke released to the a corridor but it amount was few little. Therefore, generated smoke in compartment not effected to the people in buildings.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1155-1168
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• 2016

This paper considers a probability density estimation problem of climate values. In particular, we focus on estimating probability densities of summer extreme temperature over South Korea. It is known that the probability density of climate values at one location is similar to those at near by locations and one doesn't follow well known parametric distributions. To accommodate these properties, we use a mixture of conditional autoregressive species sampling model, which is a nonparametric Bayesian model with a spatial dependency. We apply the model to a dataset consisting of summer maximum temperature and minimum temperature over South Korea. The dataset is obtained from University of East Anglia.

• Survey Research
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• v.11 no.1
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• pp.1-18
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• 2010

We compare various imputation methods for compensating wave nonresponse that are commonly adopted in many panel surveys. Unlike the cross-sectional survey, the panel survey is involved a time-effect in nonresponse in a sense that nonresponse may happen for some but not all waves. Thus, responses in neighboring waves can be used as powerful predictors for imputing wave nonresponse such as in longitudinal regression imputation, carry-over imputation, nearest neighborhood regression imputation and row-column imputation method. For comparison, we carry out a simulation study on a few income data from the Korean Welfare Panel Study based on two performance criteria: predictive accuracy and estimation accuracy. Our simulation shows that the ratio and row-column imputation methods are much more effective in terms of both criteria. Regression, longitudinal regression and carry-over imputation methods performed better in predictive accuracy, but less in estimation accuracy. On the other hand, nearest neighborhood, nearest neighbor regression and hot-deck imputation show higher performance in estimation accuracy but lower predictive accuracy. Finally, the mean imputation shows much lower performance in both criteria.

• Journal of Korean Dental Science
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• v.15 no.1
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• pp.31-50
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• 2022

Purpose: This study was to investigate the types of imaging modalities, analytical methods for age estimation, and the age of the subjects in research on age estimation using dental radiography through a scoping review, and to investigate the overall trends in age estimation studies. Materials and Methods: A scoping review was designed according to the Arksey and O'Malley guidelines and the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. Three electronic databases were used as search sources (Medline, Embase, and Cochrane Library). Studies were classified according to the three main components of the research question. "What are the imaging modalities, analytical methods, and target age in dental imaging-based age estimation studies?" Result: The final 198 studies were selected by two reviewers. The most common imaging modality used in studies was panoramic radiography (69.7%), and studies using cone-beam computed tomography have increased over time. Analytical methods for age estimation were 62.6% in studies based on tooth development and 26.3% in studies using pulp/tooth ratio. The subject age was 27.8% for children and 27.3% for adults. Studies conducted in all age groups comprised the smallest category (5.2%). Conclusion: Panoramic radiography has been the most used types of imaging modalities for age estimation, and the most common analytical method was analysis of tooth development. Most studies targeted specific ages, and very few involved all age groups. Dental age estimation studies should be carried out with appropriate consideration of the imaging modality that is analyzed, the methods that are used, and the age that is targeted.

• ETRI Journal
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• v.15 no.2
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• pp.35-51
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• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.44-50
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• 2012

ECMA-392 is the first CR (cognitive radio) specification for personal/portable devices in TV white space. In ECMA-392, in addition to the long preamble of 2 OFDM symbols, 4 pilot sub-carriers per OFDM symbol are repeatedly transmitted with the period of 13 OFDM symbols. In this paper, we consider channel estimation schemes using both long preamble and pilot sub-carriers: we propose channel estimation schemes in which a first order recursive filter is used, and present a method for reducing channel estimation delay. Computer simulation results indicate that the proposed schemes perform well over slow Rayleigh fading channels.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.1
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• pp.85-90
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• 2013

This paper presents a study on terrain referenced navigation (TRN). The extended Kalman filter (EKF) is adopted as a filter method. A Jacobian matrix of measurement equations in the EKF consists of terrain slope terms, and accurate slope estimation is essential to keep filter stability. Two slope estimation methods are proposed in this study. Both methods are based on the least-squares approach. One is planar regression searching the best plane, in the least-squares sense, representing the terrain map over the region, determined by position error covariance. It is shown that the method could provide a more accurate solution than the previously developed linear regression approach, which uses lines rather than a plane in the least-squares measure. The other proposed method is weighted planar regression. Additional weights formed by Gaussian pdf are multiplied in the planar regression, to reflect the actual pdf of the position estimate of EKF. Monte Carlo simulations are conducted, to compare the performance between the previous and two proposed methods, by analyzing the filter properties of divergence probability and convergence speed. It is expected that one of the slope estimation methods could be implemented, after determining which of the filter properties is more significant at each mission.

• Journal of KIBIM
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• v.1 no.2
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• pp.12-18
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• 2011

The BIM techniques which manages information over the life cycle of construction project based on the 3-dimensional model are developing in the direction of integrated construction management including planning, design, analysis, estimation, 3D simulation and so on. The estimation model based on the BIM has different detail level and model information. In this study, the LOD of estimation model is catched for the bridge structures. The library classes are defined with construction information classification system, and the quantities of resources are calculated by class parameter using Microstation API. Finally, the automated estimation system using BIM based library is verified by the integrated model for adjustments of level of detail.