• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.91-100
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• 2007

Many manufacturing devices must execute motions as quickly as possible to achieve profitable high-volume production. Most of them have devices having flexibility and a time delay of one sampling is added to the plants when they are controlled by fast discrete controllers, which brings about non-minimum phase zeros. This paper develops a control strategy that combines feedforward and feedback control with command shaping for such devices. First, the feedback controller is designed to increase damping and eliminate steady-state error. Next, the feedforward controller is designed to speed up the transient response. Finally, an appropriate reference profile is generated using command-shaping techniques to ensure fast point-to-point motions with minimum residual vibration. The particular focus of the paper is to understand the interactions between these individual control components. The resulting control strategy is demonstrated on a model of a high-speed semiconductor manufacturing machine.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.123-130
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• 2003

We define a broad class of rotation designs whose monthly sample is balanced in interview time, level of recall, and rotation group, and whose rotation scheme is time-invariant. The necessary and sufficient conditions are obtained for such designs. Using these conditions, we derive a minimum variance unbiased generalized composite estimator (MVUGCE). To examine the existence of time-in-sample bias and recall bias, we also propose unbiased estimators and their variances. Numerical examples investigate the impacts of design gap, non-sampling error sources, and two types of correlations on the variance of MVUGCE.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.979-982
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• 2001

In CNC machining, demands on precision machining of free formed surface model are increasing. Most of the CAD/CAM systems provide the NURBS(Non-Uniform Rational B-Spline) interpolator. NURBS is defined with NURBS parameter by control point, weight value and knot value. This paper shows the realtime NURBS interpolation algorithms and compared with each other. One is based on the equal length of curve segments rather than equal increment of the parameter Δu. The other is to limit the interpolation error to any desired level by adjusting the feedrate considering the curvature of the shape and sampling time.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1863-1866
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• 2003

In this study, respiratory motion is modeled by a 2-Dimensional linear expanding-shrinking movement. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimated, a reconstruction algorithm based on superposition method was used to removed the MRI artifact. For the purpose of estimating unknown motion parameters, we applied the spectrum shift method to find the respiratory fluctuation function, the x directional expansion coefficient and its center, and also we used the minimum energy method to find the y directional expansion coefficient and its center. The effectiveness of this presented method is shown by Computer simulations.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.58-61
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• 2003

In this study, a planar respiratory motion is modeled by a 2-D linear expanding-shrinking movement. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimated, a construction algorithm based on superposition method was used to remove the MRI artifact. For the purpose of estimating unknown motion parameters, we used the spectrum shift method to find the respiratory fluctuation function, the x directional expansion coefficient and its center, and we also used the minimum energy method to find the y directional expansion coefficient and its center. Finally the effectiveness of this presented method is shown by computer simulations.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.4
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• pp.482-490
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• 2017

The radar signal processing procedure is divided into the pre-processing such as frequency down converting, down sampling, pulse compression, and etc, and the post-processing such as doppler filtering, extracting target information, detecting, tracking, and etc. The former is generally designed using FPGA because the procedure is relatively simple even though there are large amounts of ADC data to organize very quickly. On the other hand, in general, the latter is parallel processed by multiple DSPs because of complexity, flexibility and real-time processing. This paper presents the radar signal processor design using FPGA which includes not only the pre-processing but also the post-processing such as doppler filtering, bore-sight error, NCI(Non-Coherent Integration), CFAR(Constant False Alarm Rate) and etc.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.324-329
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• 2023

Different types of deterministic solution methods were used to solve neutron transport equations corresponding to half-space and slab albedo problems. In these types of solution methods, in addition to the error of the numerical solutions, the obtained results contain truncation and discretization errors. In the present work, a non-analog Monte Carlo method is provided to simulate the half-space and slab albedo problems with Inönü and Anlı-Güngör strongly anisotropic scattering functions. For each scattering function, the sampling method of the direction of the scattered neutrons is presented. The effects of different beams with different angular dependencies and the effects of different scattering parameters on the reflection probability are investigated using the developed Monte Carlo method. The validity of the Monte Carlo method is also confirmed through the comparison with the published data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.943-950
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• 2000

In this paper, an asynchronous multi-rate optical wireless pulse position modulation-code division multiple access (PPM-CDMA) is proposed for an indoor non-directed diffuse channel. As a signature sequence for CDMA, an optical orthogonal code (OOC) is used and an interference cancellation scheme is applied to improve the bit error rate. It is known that the optical PPM-CDMA has advantages due to its power efficiency. Moreover, it provides multi-rate services by varying the modulation level with fixed pulse duration. In the proposed multi-rate PPM-CDMA system with fixed pulse duration, chip rate and sampling time do not change for each transmission rate and this simplifies overall system structure.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.5
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• pp.533-541
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• 2007

The Zienkiewicz-Zhu(Z/Z) error estimate is slightly modified for the hierarchical p-refinement, and is then applied to L-shaped plates subjected to bending to demonstrate its effectiveness. An adaptive procedure in finite element analysis is presented by p-refinement of meshes in conjunction with a posteriori error estimator that is based on the superconvergent patch recovery(SPR) technique. The modified Z/Z error estimate p-refinement is different from the conventional approach because the high order shape functions based on integrals of Legendre polynomials are used to interpolate displacements within an element, on the other hand, the same order of basis function based on Pascal's triangle tree is also used to interpolate recovered stresses. The least-square method is used to fit a polynomial to the stresses computed at the sampling points. The strategy of finding a nearly optimal distribution of polynomial degrees on a fixed finite element mesh is discussed such that a particular element has to be refined automatically to obtain an acceptable level of accuracy by increasing p-levels non-uniformly or selectively. It is noted that the error decreases rapidly with an increase in the number of degrees of freedom and the sequences of p-distributions obtained by the proposed error indicator closely follow the optimal trajectory.