• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.117-126
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• 1994

This paper describes an application step of a $R^{-{\theta}}$ method which measures circular movements in machining centers. The detection of composite errors of circular movements and a high precision cutting method in machining centers were investigated by the analysis of data measured by $R^{\theta }$method which can detect the rotating angle and is applicable to variable measuring radius. When the error by squareness error and unbalance of position-loop-gain were mixed, the detection method of each error was proposed. Although the errors by squarenss error and backlash compensation were mixed, the errors by squareness error be detected. If the errors by unbalance of position-loop-gain and backlash compensation were mixed, the errors by unbalance of position-loop-gain could not detected. A high precision cutting mehod, which uses the NC program compensated by using feed-back data from error measured by the $R^{\theta }$method, was proposed.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.303-308
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• 2012

One dimensional line edge detection sensor was investigated for the application to detect line or edge of wide sheet winding to cylindrical roller. Line edge detection sensor was realized using align-free 1:1 optical system having 1 convex lens and by processing sum or difference of signals from two photo-diodes in a bi-cell photodetector. Line width up to 0.1mm on object having various materials and colors was detectable, and the deviation of wound sheet was found to be under 0.2mm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1710-1715
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• 2014

In this paper, we propose a novel on-chip test logic for TSV fault detection in 3-dimensional integrated circuits. The proposed logic called OTT realizes the input signal delay-based TSV test method introduced earlier. OTT only includes one F/F, two MUXs, and some additional logic for signal delay. Thus, it requires small silicon area suitable for TSV testing. Both pre-bond and post-bond TSV tests are able to use OTT for short or open fault as well as small delay fault detection.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.1-8
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• 2008

This paper presents a real-time algorithm for collision detection, collision avoidance and guidance. Three-dimensional point-mass aircraft models are used. For collision detection, conflict probability is calculated by using the Monte-Carlo Simulation. Time at the closest point of approach(CPA) and distance at CPA are needed to determine the collision probability, being compared to certain threshold values. For collision avoidance, one of possible maneuver options is chosen to minimize the collision probability. For guidance to a designated way-point, proportional navigation guidance law is used. Two scenarios on encounter situation are studied to demonstrate the performance of proposed algorithm.

• Smart Structures and Systems
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• v.23 no.4
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• pp.393-403
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• 2019

Applying more features gives us better accuracy in modeling; however, increasing the inputs causes the curse of dimensions. In this paper, a new structure has been proposed for fault detecting and identifying (FDI) of high-dimensional systems. This structure consist of two structure. The first part includes Auto-Encoders (AE) as Deep Neural Networks (DNNs) to produce feature engineering process and summarize the features. The second part consists of the Local Model Networks (LMNs) with LOcally LInear MOdel Tree (LOLIMOT) algorithm to model outputs (multiple models). The fault detection is based on these multiple models. Hence the residuals generated by comparing the system output and multiple models have been used to alarm the faults. To show the effectiveness of the proposed structure, it is tested on single-shaft industrial gas turbine prototype model. Finally, a brief comparison between the simulated results and several related works is presented and the well performance of the proposed structure has been illustrated.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.73-74
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• 2022

Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.10
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• pp.833-837
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• 2013

Since holographic data storages read and write information on a volume and the information is processed per page, it has the advantage of high recording density and data transfer rate. However, there are two major drawbacks like 2-dimensional intersymbol interference and interpage interference as the density between pixels increases. Furthermore, a bright page that contains many ON pixels influences the reliable detection of the neighboring pages, which causes the less number of pages stored in the storage volume. We propose a sparse-ON pixel two-dimensional modulation code with the code rate 6/8 for increasing the number of pages stored in the volume. The proposed code is compared to conventional 6/8 balanced code, and it shows similar or a little bit better performance than that of the balanced code. Therefore, the proposed code can increase the recording capacity without loss of the performance.

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.91-98
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• 2019

Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

• Journal of the Korean Society of Safety
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• v.18 no.4
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• pp.98-104
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• 2003

Various nondestructive evaluation (NDE) techniques have been studied to locate steel rebars of dowel, and to detect invisible damage such as voids and cracks inside concrete and debonding between rebars and concrete caused by corrosions and earthquakes. In this study, the aurhors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars of dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna array was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. This paper presents the analytical expressions of numerical focusing procedures for 3D image reconstruction and numerical simulation to study the resolution of the system and the effectiveness of multi-frequency technique. Also, the design of 4?4 antenna array with switching devices is introduced as a preliminary study for the final design of whole array.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.49-57
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• 2005

The proposed algorithm is to achieve the robust optical flow detection which is applicable for the case that the outlier rate is over 80%. If the outlier rate of optical flows is over 30%, the discrimination between the inliers and outlier with the conventional algorithm is very difficult. The proposed algorithm is to overcome such difficulty with three steps of grouping algorithm; 1) constructing the 2D histogram with two axies of the lengths and the directions of optical flows. 2) sorting the number of optical flows in each bin of the two-dimensional histogram in the descending order and removing some bins with lower number of optical flows than threshold. 3) increasing the resolution of the two-dimensional histogram if the number of optical flows in a specific bin is over 20% and decreasing the resolution if the number of optical flows is less than 10%. Such processing is repeated until the number of optical flows falls into the range of 10%-20% in all the bins. The proposed algorithm works well on the different kinds of images with many of wrong optical flows. Experimental results are included.