• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.1-6
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• 2010

The lens distortion in the machine vision system is inevitable phenomenon. Distortion is getting worse, due to the selection of lens in the trend of reducing prices and size of the system. In this trend, the distortion correction becomes more important. But, the traditional correction methods has problems, such as complexity and requiring more operations. Effective distorted digital image correction is the precondition of target detection and recognition based on vision inspection. To overcome the disadvantage of traditional distortion correction algorithms, such as complex modeling, massive computation and marginal information loss, an image distortion correction algorithm based on photogrammetry method is proposed in this paper. In our method, we use the lattice image as the measurement target. Through the experimental results, we could find that we can reduce the processing time by 4ms. And also the inspection failure rate of our method was reduced by 2.3% than human-eyes inspection method.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.136-144
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• 1997

Usually triangular patches are used to transfer geometric shape in Rapid Prototyping CAM system. STL, a list of triangles, is de facto standard in RP industry. Because STL does not have topological infoma- tion, it can cause errornous results. So STL should be verified before using. After adding support structures to anchor the part to the platform and to prevent sagging or distortion, slicing and layer by layer manufactur- ing process are done. But triangular patch is surface model and cannot provide sufficient information on geometry in the above processes. So, geometric modeling is necessary in verifying STL, adding support structures and slicing. It is natural that triangle based modeling is the best when tringular patches are used as input. Considering support structures, solid and faces coexist in RP process. Therefore non-manifold modeler is required. In this study, triangle based non-manifold geometric modeling is proposed for RP sys- tem consistent with STL input.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.125-126
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• 2009

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.191-196
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• 2010

In this paper, modeling of the non-ideal frequency response, especially "notch-and-spike" magnitude phenomenon and phase lag distortion, are discussed. To characterize the non-ideal frequency response, a new electro-mechanical simulation model based on SPICE is proposed using the driving loop of the capacitive vibratory gyroscope. The parasitic components of the driving loop are found to be the major factors of non-ideal frequency response, and it is verified with the measurement results.

• Macromolecular Research
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• v.17 no.10
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• pp.797-806
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• 2009

The mechanical and thermal behaviors of polyamide-6/clay nanocomposites were studied using the continuum-based, micromechanical models such as Mori-Tanaka, Halpin-Tsai and shear lag. Mechanic-based model prediction provides a better understanding regarding the dependence of the nanocomposites' reinforcement efficiency on conventional filler structural parameters such as filler aspect ratio ($\alpha$), filler orientation (S), filler weight fraction (${\Psi}_f$), and filler/matrix stiffness ratio ($E_f/E_m$). For an intercalated and exfoliated nanocomposite, an effective, filler-based, micromechanical model that includes effective filler structural parameters, the number of platelets per stack (n) and the silicate inter-layer spacing ($d_{001}$), is proposed to describe the mesoscopic intercalated filler and the nanoscopic exfoliated filler. The proposed model nicely captures the experimental modulus behaviors for both intercalated and exfoliated nanocomposites. In addition, the model prediction of the heat distortion temperature is examined for nanocomposites with different filler aspect ratio. The predicted heat distortion temperature appears to be reasonable compared to the heat distortion temperature obtained by experimental tests. Based on both the experimental results and model prediction, the reinforcement efficiency and heat resistance of the polyamide-6/clay nanocomposites definitely depend on both conventional (${\alpha},\;S,\;{\Psi}_f,\;E_f/E_m$) and effective (n, $d_{001}$) filler structural parameters.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.261-264
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• 2004

In this paper, we identify the memory effect of high power(125W) laterally diffused metal oxide-semiconductor(LDMOS) RF Power Amplifier(PA) by two tone IMD measurement. We measure two tone IMD by changing the tone spacing and the power level. Different asymmetric IMD is founded at different center frequency measurements. We propose the Tapped Delay Line-Neural Network(TDNN) technique as the modeling method of LDMOS PA based on two tone IMD data. TDNN's modeling accuracy is highly reasonable compared to the memoryless adaptive modeling method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.2
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• pp.65-71
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• 2013

Nonlinear loads with harmonics exist in an actual power system where harmonic currents make voltage distortion. The sum of reactive power measured at individual load is different from the measured reactive power at a bus in a power system with linear and non-linear loads. In this study, ANN(artificial neural network) load modeling technique with consideration of harmonics is introduced for more accurate component load modeling and an impact coefficient is proposed for aggregation of component loads. Results of this research show more accurate load modeling method. Since precise data for power system analysis can be acquired, the proposed method will be used for power system planning and maintenance.

• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.587-591
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• 1996

Usually triangular patches are used to transfer geometric shape in Rpaid Prototyping CAM system. STL, a list of triangles, is de facto in RP industry. Because STL has no topology data, it can cause errornous results. So, STL should be verified before using. After adding support structures to anchor the part to the platform and to prevent sagging or distortion, slicing and layer by layer manufacturing process are done. But triangular patch is surface model and cannot provide dufficient information on geometry in the above processes. So, geometric modeling is necessary in verifying STL, adding support structures, and slicing. It is natural that triangle based modeling is the best when traingular patches are used as input. Considering support structures, solid and faces coexist in RP process. Therefore non-manifold modeler is required. In this study, triangle based non-manifold geometric modeling is proposed for RP system consitent with STL input.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.40.3-40.3
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• 2018

This dissertation presents the results on two-dimensional Redshift space distortion (hereafter RSD) analyses of the large-scale structure of the universe using spectroscopic data and on improvement of modeling of the RSD effect. RSD is an effect caused by galaxies' peculiar velocity on their clustering feature in observation along the line of sight and is thus intimately connected to the growth rate of the structure in the universe, from which we can test the origin of cosmic acceleration and Einstein's theory of gravity at cosmic scales in the end. However, there are several challenges in modeling precise and accurate RSD effect, such as non-linearities and the existence of an exotic component, e.g. massive neutrino. As part of endeavors for modeling more precise and accurate galaxy clustering in redshift space, this dissertation includes a series of works for this issue. (More detailed descriptions were omitted.)