• Current Optics and Photonics
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• v.6 no.5
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• pp.445-452
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• 2022

We developed an adaptive optics test bench using an optical simulator and two rotating phase plates that mimicked the atmospheric turbulence at Bohyunsan Observatory. The observatory was reported to have a Fried parameter with a mean value of 85 mm and standard deviation of 13 mm, often expressed as 85 ± 13 mm. First, we fabricated several phase plates to generate realistic atmospheric-like turbulence. Then, we selected a pair from among the fabricated phase plates to emulate the atmospheric turbulence at the site. The result was 83 ± 11 mm. To address dynamic behavior, we emulated the atmospheric disturbance produced by a wind flow of 8.3 m/s by controlling the rotational speed of the phase plates. Finally, we investigated how closely the atmospheric disturbance simulation emulated reality with an investigation of the measurements on the optical table. The verification confirmed that the simulator showed a Fried parameter of 87 ± 15 mm as designed, but a little slower wind velocity (7.5 ± 2.5 m/s) than expected. This was because of the nonlinear motion of the phase plates. In conclusion, we successfully mimicked the atmospheric disturbance of Bohyunsan Observatory with an error of less than 10% in terms of Fried parameter and wind velocity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.337-352
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• 2023

In general, Rainfall-Runoff model parameter set is optimized using the entire data to calculate unique parameter set. However, Korea has a large precipitation deviation according to the season, and it is expected to even worsen due to climate change. Therefore, the need for hydrological data considering seasonal characteristics. In this study, we conducted regional sensitivity analysis(RSA) using the conceptual Rainfall-Runoff model, GR4J aimed at the Soyanggang dam basin, and clustered combining the RSA results with hydrometeorological data using Self-Organizing map(SOM). In order to consider the climate characteristics in parameter estimation, the data was divided based on clustering, and a calibration approach of the Rainfall-Runoff model was developed by comparing the objective functions of the Global Optimization method. The performance of calibration was evaluated by statistical techniques. As a result, it was confirmed that the model performance during the Cold period(November~April) with a relatively low flow rate was improved. This is expected to improve the performance and predictability of the hydrological model for areas that have a large precipitation deviation such as Monsoon climate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.1
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• pp.29-39
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• 1997

The need of transformation parameters from local geodetic datums to a geocentric coordinate system is becoming more common, with the increasing application of satellite positioning techniques to LIS/GIS survey with cadastral management. In this paper, the national transformation parameters between the Korean geodetic coordinates which is based on the Bessel 1841 ellipsoid and the WGS84 ellipsoid are determined by the least square methods with weighted parameter constraints. Three-dimensional geocentric coordinates are based on GPS observation at 31 stations in the geodetic network, the datum parameters are computed within a standard deviation of less than 1 meter. In South Korea, the national transformation parameters with Bessel geoid-heights are useful for GPS baseline processing and for middle-scale map/database transformation.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.52-65
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• 1997

This paper presents a design technique of self tuning fuzzy controller for load frequency control of power system. The proposed parameter self tuning algorithm of fuzzy controller is based on the gradient method using four direction vectors which make error between inference values of fuzzy controller and output values of the specially selected optimal controller reduce steepestly. Using input-output data pair obtained from optimal controller, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed gradient method. The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones for reductions of undershoot and steady-state load frequency deviation and for minimization of settling time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.78-85
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• 2007

This paper presents a segmental scheme for regions-composed images in local normalization process. The scheme is based on local statistics computed through a moving window. The normalization algorithm uses linear or nonlinear functions to transfer the pixel distribution and the homogeneous affine of regions which is corrupted by additive noise. It adjusts the mean and standard deviation for nearest-neighbor interpoint distance between current and the normalized image signals and changes the segmentation performance according to local statistics and parameter variation adaptively. The performance of newly advanced local normalization algorithm is evaluated and compared to the performance of conventional normalization methods. Experimental results are presented to show the region segmentation properties of these approaches.

• Journal of Korean Ophthalmic Optics Society
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• v.1 no.2
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• pp.7-11
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• 1996

The size of pupil with pupillary light reflex is determined by the amount of a luminance. and it is dependent with the distribution function of the retinal illuminance which is the amount of transmittance for the external light due to the size of pupil, and the detector of cone and rod due to the amount of the luminance. The change of the pupil size with the luminance can be expressed with the mathematical model $$y(x)={\alpha}+{\beta}\frac{1}{1+{e}{x}{p}(x-x_0)/{\theta}}$$ where ${\alpha}$ is the size of the pupil diameter in a maximum value of the luminance, ${\beta}$ is the deviation of the pupil's diameter between maximum and minimum, ${\theta}$ is the parameter showed the degree of a sensitivity. Comparing with the experimental value of P.Moon et al, We known that the equation of the model is very compatible.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.835-837
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• 2012

In this paper, we have been analyzed conduction path by device parameter of double gate(DG) structure that have top gate and bottom gate. The Possion equation is used to analytical. The change of conduction path have been investigated for various channel lengths, channel thickness and gate oxide thickness using this model, given that these parameters are very important in design of DGMOSFET. The optimum channel doping concentration is determined as the deviation of conduction path is considered according to channel doping concentration.

• Transactions of Materials Processing
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• v.29 no.4
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• pp.218-228
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• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.173-182
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• 2005

The Performance of U-tube ground heat exchanger for geothermal heat Pump systems depends on the thermal properties of the soil, as well as grout or backfill materials in the borehole. In-situ tests provide a means of estimating some of these properties. In this study, in-situ thermal response tests were completed on two vertical boreholes, 130 m deep with 62 mm diameter high density polyethylene U-tubes. The tests were conducted by adding a monitored amount of heat to water over a $17\~18$ hour period for each vertical boreholes. By monitoring the water temperatures entering and exiting the loop and heat load, overall thermal conductivity values of grout/soil formation were determined. Two parameter estimation models for evaluation of thermal response test data were compared when applied on the same temperature response data. One model is based on line-source theory and the other is a numerical one-dimensional finite difference model. The average thermal conductivity deviation between measured data and these models is of the magnitude $1\%$ to $5\%$.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.8
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• pp.695-703
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• 2005

The objective of this study is to determine the effective thermal conductivity and thermal resistance values in test boreholes with three different fill materials. To evaluate these heat transfer properties, in-situ tests on four vertical boreholes were conducted by adding a monitored amount of heat to water over various test lengths. Two parameter estimation models, line-source and numerical one-dimensional models, for evaluation of thermal response test data were compared when applied on the same four data sets. Results show that the average thermal conductivity deviation between measured data and these two models is in the range of $3.03\%$ to $4.45\%$. The effect of increasing grout thermal conductivity from 1.34 to 1.82 $W/m^{\circ}C$ resulted in overall increases in effective formation thermal conductivity by $11.1\%$ to $51.9\%$ and reductions in borehole thermal resistance by $11.6\%$ to $26.1\%$.