• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.65-70
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• 2002

An analysis method for calculating motion accuarcy of double sides hydrostatic table is proposed in this paper. In this method, profiles of each rails are assumed as periodic function, therefore it is represented as the sum of spacial frequencies. Bearing clearance at any position rail is depended on the variation of linear, angular motion error of table and the form errors of both sides of a rail. Finite element method is applied to calculate pressure distributions in bearing clearance. In order to simplify the analyzing process, double sides table model is converted into equivalent single side table model. Results calculated by the proposed modeling method agree well with the results directly caculated by double sides modeling method, and also agree well with experimental results. From the theoretical and experimental analysis, it is verified that the proposed analysis method is very effective to analyze the motion accuracy of double sides hydrostatic table.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.710-717
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• 2015

Projection stereolithography is an additive manufacturing method that uses beam projection to cure the photo-reactive resin used. The light source of a cross-section layer-form illuminates photo-curable resin for building a three-dimensional (3D) model. This method has high accuracy and a fast molding speed because the processing unit is a face instead of a dot. This study describes a Scalable Projection Stereolithography 3D Printing System for improving the accuracy of the stereolithography. In a conventional projection 3D printer, when printing a small sized model, many pixels are not used in the projection or curing. The proposed system solves this problem through an optical adjustment, and keeps using the original image as possible as filling the whole projection area. The experimental verification shows that the proposed system can maintain the highest level of precision regardless of the output size.

• Journal of Korean Society for Atmospheric Environment
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• v.16 no.2
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• pp.151-158
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• 2000

Since Pusan metropolitanarea where is composed complex terrain is connected to sea the sea-land breeze circulation and the mountain-valley circulation are apt to form A regional scale circulation system is formed at a region which has complex terrain because of curves of its and affect to the dispersion and advection of air pollutants. LCM Local Circulation Model which a propriety was verified described that sea breeze and valley wind at the daytime and land breeze and mountain wind at the nighttime were well devellped over the Pusan metropolital area. Next for the investigation of accuracy of simulated results an observed value at Kae-Kum and Su-Young on the pusan metropolitan area were compared with it at those points. From the comparison of the temperature and horizontal velocity between the results of LCM and an observed values they have a similar trend of a diurnal variation. For the prediction of dispersion and transportation of air pollutants the wind field should be calculated with high accuracy. A numerical simulation using LCM can provide more accuracy results around Pusan metropolitan area.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.8
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• pp.683-689
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• 2016

Servo mismatch, which affects positioning accuracy of multi-axis machine tools, is usually estimated via the circular test. However, due to mechanical restrictions in measuring instruments, the circular test using a double ball-bar is difficult to apply in miniaturized or super-large sized machine tools. Laser trackers are widely used to measure the form accuracy of parts and the positioning accuracy of driving systems. In this paper, a technique for the servo mismatch estimation of multi-axis machine tools is proposed via the circular test using a laser tracker. To verify the proposed technique, experiments using a double ball-bar and laser tracker are conducted in a 3-axis machine tool. The difference in the evaluation results is 0.05 msec. The servo mismatch for the miniaturized machine tool is also evaluated using the proposed technique.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.43-51
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• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.5
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• pp.862-874
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• 1989

A phase evil method and spectrum analysis were instrument error which is originated from measurement system and the form error of standard specimens. An instrument with a rotating table supported by an air bearing is calibrated using standard specimens. The phase of standard specimens was measured 12 times on the rotating table with rotating 30 in turn and its measurement magnification was set by 100000 times. As a result of data analysis of all the observations, read out at each of 144 orientations(per 2.5) from recorded datafiles, the error of the performance of the instrument and those of the standard specimens are evaluated and a systematic deviation of the instrument is determined. In the particular instrument used in the present experiment, the deviation of the instrument is determined with the accuracy of 15nm and those of standard specimens with the accuracy of 23, 13 n, respectively. The reproducibility of the instrument is investigated, too. If the instrument is calibrated by using the above standard specimens, then the accuracy of the measurement of roundness error can be improved to about 15nm.

• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1181-1194
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• 2019

A new moving-mesh Finite Volume Method (FVM) for the efficient solution of the two-dimensional neutron diffusion equation is introduced. Many other moving-mesh methods developed to solve the neutron diffusion problems use a relatively large number of sophisticated mathematical equations, and so suffer from a significant complexity of mathematical calculations. In this study, the proposed method is formulated based on simple mathematical algebraic equations that enable an efficient mesh movement and CV deformation for using in practical nuclear reactor applications. Accordingly, a computational framework relying on a new moving-mesh FVM is introduced to efficiently distribute the meshes and deform the CVs in regions with high gradient variations of reactor power. These regions of interest are very important in the neutronic assessment of the nuclear reactors and accordingly, a higher accuracy of the power densities is required to be obtained. The accuracy, execution time and finally visual comparison of the proposed method comprehensively investigated and discussed for three different benchmark problems. The results all indicated a higher accuracy of the proposed method in comparison with the conventional fixed-mesh FVM.

• Structural Engineering and Mechanics
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• v.76 no.6
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• pp.675-685
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• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.77-82
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• 2019

Diabetic retinopathy is a complicated form of diabetes due to circulatory disorder in the peripheral blood vessels of the retina. We segment the microvessel for diagnosing diabetic retinophathy. The conventional methods using filter and features can segment the thick blood vessels, but it has relatively weak for segmenting fine blood vessels. In pre-processing step, noise reduction filter and histogram equalization are applied to suppress the noise and enhance the image contrast. Then, deep learning technique is used for pixel-by-pixel segmentation. The accuracy of conventional methods is between 90% to 94%, while the proposed method has improved as 95% accuracy. There is a problem of segmentation error around the optic disc and exudate due to the network depth. However the accuracy can be improved by modifying the network architecture in the future.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).