• Health Policy and Management
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• v.27 no.3
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• pp.211-218
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• 2017

Background: Korea set up new diagnosis related group (DRG) as demonstration project in 2009. The new DRG was reformed in 2016. The main purpose of study is to identify the effect of reform on accuracy of payment. Methods: This study collected inpatient data from a hospital which contains medical information and cost from 2015 to 2016. The dependent variables were accuracy of total, bundled, unbundled payment, and payment for procedures. To analyze the effect of reform, this study conducted a multi-variate regression analysis adjusting for confounding variables. Results: The accuracy of payment increased after policy reform. The accuracy of total, bundled, unbundled payment, and payment for procedures significantly increased 3.90%, 2.92%, 9.03%, and 14.57% after policy reform, respectively. The accuracy of unbundled payment showed the largest increase among dependent variables. Conclusion: The results of study imply that policy reform enhanced the accuracy of payment. The government needs to monitor side effects such as increase of non-covered services. Also, leads to a considerable improvement in the value of cost unit accounting as a strategic play a role in development of DRG.

• Journal of Electrochemical Science and Technology
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• v.15 no.2
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• pp.299-313
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• 2024

Electrochemical machining (ECM) is an effective manufacturing method for difficult-to-machine materials and is widely used in the precision manufacturing of aerospace components. In recent years, the requirements for the machining accuracy and surface integrity of ECM have become increasingly stringent. To further improve the machining quality, this work investigated the intricate laws between electrolyte filtration accuracy and machining quality. Electrolytes with different filtration accuracies were compared, and a numerical simulation was used to evaluate the change in temperature and bubble rate of the flow field in the machining area. Experiments were conducted on ECM of Ti-6Al-4V (TC4) alloy workpieces using electrolytes with different filtration accuracy. The workpiece machining accuracy and surface quality were analyzed, and the repetition accuracy of the workpiece was evaluated. The intricate laws between electrolyte filtration accuracy and machining quality were explored. It was found that when the electrolyte filtration accuracy is improved, so too is the machining quality of the ECM. However, once the filtration accuracy has reached a certain value, the machining quality has extremely limited improvement. By evaluating the repetition accuracy of processed workpieces in electrolytes with different filtration accuracies, it was found that when the filtration accuracy reaches a certain value, there is no positive correlation between the repetition accuracy and filtration accuracy. The result shows that, for the workpiece material and conditions considered in this paper, an electrolyte with 0.5㎛ filtration accuracy is suitable for the wide application of precision ECM.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.532-541
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• 2014

The ship-borne mobile down range telemetry antenna system having 4.6 m reflector antenna and 3-axis mounting structure at S-band requires the precise pointing accuracy at sea for the launch mission. Using the LEO satellites tracking, a method to determine and verify the antenna pointing and tracking performance, and to find the pointing bias which dominantly contributes to the pointing inaccuracy, is presented. Based upon the tests conducted on the Jeju sea and Pacific sea, the pointing bias is determined and its origin is also identified as the drift of the heading angle of the gyrocompass. The applied systematic correction taking into account the pointing bias, and the achieved improvement of the pointing accuracy are shown. Thanks to the correction, it is presented that this antenna tracked the launcher(KSLV-I) stably within the required pointing accuracy in the following KSLV-I third launch.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.693-695
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• 2018

In this paper, we propose the improvement of Hangul OCR accuracy through deep learning. OCR is a program that senses printed and handwritten characters in an optical way and encodes them digitally. In the case of the most commonly used Tesseract OCR, the accuracy of English recognition is high. However, Hangul has lower accuracy because it has less learning data for a complex structure. Therefore, in this study, we propose a method to improve the accuracy of Hangul OCR by extracting the character region from the desired image through image processing and using deep learning using it as learning data. It is expected that OCR, which has been developed only by existing alphanumeric and several languages, can be applied to various languages.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.71-78
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• 2006

Sun sensors are frequently implemented by satellites for attitude sensing, due to its simple manufacturability and light weight. A modeling of sun sensors has an important effect on the accuracy of satellite attitude determination. This paper addresses a new modeling of a 2-axis miniature fine sun sensor with improved accuracy. Unlike other previous algebraic modeling methods, the newly suggested physical modeling method takes into account the shadowing effect of the slit thickness. It was shown that a newly proposed sun sensor modeling provides a substantial accuracy improvement of 29% compared to the generic algebraic modeling. The proposed sensor modeling was validated using 2-axis fine sun sensors with FOV(Field of View) of ${\pm}60^{\circ}$ mounted on HAUSAT-2 small satellite, currently under development by SSRL(Space System Research Lab.) at Hankuk Aviation University, Korea.

• Spatial Information Research
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• v.9 no.2
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• pp.263-275
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• 2001

With increasing of utilization of 1/1,000 Digital-Map being constructed with NGIS project, it is entering upon the stage that problem as the inspection of position accuracy of Digital-Map before its use. This paper evaluated position accuracy of Digital-Map being based on the construction of college facility management system into small area and presented modification/renovation of Digital-Map on area being occurred position error. With a view to evaluation of position error to building using RTK survey, position error was shown more than 0.5mm that is prescribed in survey-law. In order to acquire good position accuracy, first we carried out Static survey to college and selected control point. And, we evaluated coordinate value to important building from control point and compared these results with RTK survey results. Second, we carried out Affine transform based on the control point of building being surveyed with RTK, transformed pre-constructed Digital-Map and compared these results with RTK Survey results. We analyzed first and second method and presented improvement method of position accuracy of Digital-Map suited on small area.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.367-372
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• 2012

This paper presents a development of an analog type magnetic positioning system and its positioning accuracy improvement using fuzzy inference system. As the magnetic positioning system used on a magnet-gyro guidance system for AGV(automatic guided vehicle), it measures a position of magnet embedded in floor of the work place. The existing product of the magnetic positioning system is very expensive in Korea because it is being sold in a foreign country exclusively. Moreover, the positioning accuracy of the product is low because it uses digital type unipolar hall sensors. Hence, we developed the magnetic positioning system by ourselves and improved the positioning accuracy of the developed magnetic positioning system using fuzzy inference system. For experiment, we used the analog type magnetic positioning system which we have developed, and compared the performance of the proposed method with the performance of the existing positioning method for the magnetic positioning system. In experimental results, we verified that the proposed method improved the positioning accuracy of the magnetic positioning system.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.77-84
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• 2013

Most research on the inkjet printing technology has focused on the development of inkjet head itself, and of process, not on the landing accuracy of the droplets to a target. Thus, this paper presents the modeling and experimental verification on the static landing accuracy and precision of the droplets from the magnetostrictive inkjet head. A simple model based on the angle deviation of a nozzle tip and on a distance to a substrate is considered, assuming that there is no ambient effect. The angle deviation of the nozzle tip is determined by using its digital image with the aid of a pixel calculation program, and the distance to the substrate is set to 1 mm. Three experiments have planned and preformed. The first experiment is to collect the initial data for the landing distribution of the droplets. The second experiment is to collect the repeatability data of the stage used. Then, these data are used to rederive the equation for the final landing position of the droplet. The final experiment is to verify the equation and to show the calibration results. The respective landing accuracy of the droplet after calibration on the x-axis and on y axis has improved from $338.51{\mu}m$ and $-133.63{\mu}m$ to $7.06{\mu}m$ and $13.11{\mu}m$. The respective percent improvement on the x-axis and on y axis reaches about 98 and about 90. The respective landing precision of the droplet after calibration on the x-axis and on y axis has improved from ${\pm}182.6{\mu}m$ and ${\pm}182.88{\mu}m$ to ${\pm}24.64{\mu}m$ and ${\pm}42.76{\mu}m$. The respective percent improvement on the x-axis and on y axis reaches about 87 and about 77.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.243-253
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• 2002

These days, the application range of digital photogrammetry is being extended actively, so the great variety of research is being progressed about improvement of measurement accuracy. This method can acquisite a high analysis accuracy and can acquisite easily image. But, So this method require a much processing time and effort by increasing a data amount, as the automation of processing must be completed for efficiency improvement of processing. In this study, the automation of image processing stage is established for multi-image aquisition and analysis about a radio telescope. Also, the precise measurement and the accuracy on object were intended to be improved. As a result of this study, the accuracy on the object which demands precise measurement was enhanced from multi image analysis, and also the assembly accuracy of the object could be checked by precise measurement and curve fitting.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.48-54
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• 2019

This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.