• Journal of Sensor Science and Technology
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• v.14 no.6
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• pp.430-437
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• 2005

In this paper, we proposed a biologically inspired light-adaptive edge detection circuit based on the human retina. A saturating resistive network was suggested for light adaptation and simulated by using HSPICE. The light adaptation mechanism of the edge detection circuit was quantitatively analyzed by using a simple model of the saturating resistive element. A light-adaptive capability of the edge detection circuit was confirmed by using the one-dimensional array of the 128 pixels with various levels of input light intensity. Experimental data of the saturating resistive element was compared with the simulated results. The entire capability of the edge detection circuit, implemented with the saturating resistive network, was investigated through the two-dimensional array of the $64{\times}64$ pixels

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1361-1371
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• 2020

Fonts have developed as a visual element, and their influence has rapidly increased around the world. Research on font automation is actively being conducted mainly in English because Hangul is a combination character and the structure is complicated. In the previous study to solve this problem, the stroke element of the character was automatically extracted by applying the object detection by component. However, the previous research was only for similarity, so it was tested on various print style fonts, but it has not been tested on other characters. In order to extract the stroke elements of all characters and fonts, we performed a performance analysis experiment according to the expansion character in the Hangul stroke element extraction training. The results were all high overall. In particular, in the font expansion type, the extraction success rate was high regardless of having done the training or not. In the character expansion type, the extraction success rate of trained characters was slightly higher than that of untrained characters. In conclusion, for the perfect Hangul stroke element extraction model, we will introduce Semi-Supervised Learning to increase the number of data and strengthen it.

• Journal of IKEEE
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• v.11 no.1 s.20
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• pp.30-37
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• 2007

This paper proposes a detection method of position of OFF-switch. Each switch has the parallel path with a serial combination of passive element, its parallel path has each different frequency characteristics. Frequency characteristic of ON-switch reveals a flat spectrum irrelevant to frequency characteristic of passive element connected in parallel to its each terminal and frequency characteristic of OFF-switch reveals the same characteristic as one of passive element connected in parallel. Detection of position of OFF-switch is done by measuring the similarity of each spectrum corresponding to frequency characteristic of passive element connected in parallel to OFF-switch. The measure of their similarity is to calculate Euclidean distance between their test spectrum and reference spectrum. The spectrum with the smallest distance among reference spectrum is recognized as the spectrum of OFF-switch. The real time digital signal processing system is implemented to detect the position of OFF-switch by using spectrum matching.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.438-444
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• 2019

In this paper, we proposed a 16-element array antenna design to improve signal detection performances. The array antenna characteristics, such as mutual coupling, pattern deviation, and half power beamwidth of the active element, were examined to obtain an optimal spacing between individual elements. The single element of the array antenna consists of an indirect feed using L-shaped feed and shorted radiating patch to achieve a broadband operation. Root mean square(RMS) errors based on the incident angle of the signal were calculated to verify the signal detection performance of the proposed antenna. The results demonstrate that the proposed array antenna with optimal spacing is suitable for detecting interference signals with low RMS error.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.3
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• pp.185-192
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• 2015

Since real-time monitoring systems, such as early fault detection, have been very important, an infrared thermography technique was proposed as a new diagnosis method. This study focused on damage detection and temperature characteristic analysis of ball bearings using the non-destructive, infrared thermography method. In this paper, for the reliability assessment, infrared experimental data were compared with finite element analysis (FEA) results from ANSYS. In this investigation, the temperature characteristics of ball bearing were analyzed under various loading conditions. Finally, it was confirmed that the infrared thermography technique was useful for the real-time detection of damage to bearings.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.773-780
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• 2009

This study proposed a face region detection algorithm using fuzzy inference of pixel hue and intensity. The proposed algorithm is composed of light compensate and face detection. The light compensation process performs calibration for the change of light. The face detection process evaluates similarity by generating membership functions using as feature parameters hue and intensity calculated from 20 skin color models. From the extracted face region candidate, the eyes were detected with element C of color model CMY, and the mouth was detected with element Q of color model YIQ, the face region was detected based on the knowledge of an ordinary face. The result of experiment are conducted with frontal face color images of face as input images, the method detected the face region regardless of the position and size of face images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.15-20
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• 2016

Compared to the MIMO system using the spatial multiplexing methods and the MIMO system using the diversity scheme achieved a high rate, but the lower the diversity gain to improve the data transmission reliability should separate the spatial stream at the MIMO receiver. In this paper, we compared Channel capacity detection methods with the Lattice code, the 3-user interference channel and linear channel interference detection methods ZF (Zero Forcing) and MMSE (Minimum Mean Square Error) detection methods. The channel is a Diagonal channel. In other words, Diagonal channel is confirmed by the inverse matrix satisfies the properties of Jacket are element-wise inverse to $[H]_N[H]_N^{-1}=[I]_N$.

• Structural Engineering and Mechanics
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• v.39 no.1
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• pp.77-91
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• 2011

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by wavelet-based elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.243-248
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• 2014

In this paper, we propose a method to recognize the facial expressions by selecting face elements and finding its status. The face elements are selected by using image area segmentation method and the facial expression is decided by using the normal distribution of the change rate of the face elements. In order to recognize the proper facial expression, we have built database of facial expressions of 90 people and propose a method to decide one of the four expressions (happy, anger, stress, and sad). The proposed method has been simulated and verified by face element detection rate and facial expressions recognition rate.