• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.5-17
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• 2000

The physical and mechanical properties of the sedimentary rocks deposited in Taegu and Kyongbuk region have been measured in the laboratory and at the field. Four kinds of rocks such as the shale, the mudstone, the siltstone and the sandstone were the object of this study. In sedimentary rock joint, bedding made it impossible to extract cores for uniaxial compressive test. Some correlations between the uniaxial compressive strength and the other characteristic values such as Point load index, Schmidt hammer rebound, Brazilian strength, P-wave velocity and Absorption ratio are made. The chemical and mineral compositions are also investigated by the XRF and XRD analysis. In addition, the weathering grade of rocks are classified by the quantitative indices of Point load index, Schmidt hammer rebound and Absorption ratio.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.43-51
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• 2014

TFT-LCD image includes a defect of various properties. TFT-LCD image have a recognizable defects in the human inspector. On the other hand, it is difficult to detect defects that difference between the background and defect is very low. In this paper, we proposed sequentially detect algorithm from pixels included in the defect region to limited defects. And blob analysis methods using the blob size and gray difference are applied to the defect candidate image. Finally, we detect an accurate defect blob to distinguish the noise. The experimental results show that the proposed method finds the various defects reliably.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.11-16
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• 2021

In this paper, a quality inspection system was developed to identify the defective assembly of connectors used in automobile wiring. For waterproof connectors, an internal seal must be inserted for waterproofing. However, there are cases where it is omitted or double-inserted during production. An automatic inspection jig was designed using photosensors and touch switches to classify good and bad connector components. In the case of the existing visual inspection, 6,400 connectors were inspected when 5 people inspected for 8 hours. However, when using the inspection jig developed under the same conditions, 20,000 pieces were inspected. In other words, the productivity is greatly improved compared to the conventional visual inspection.

• Proceedings of the KSAR Conference
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• 2002.06a
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• pp.30-30
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• 2002

본 연구는 돼지 액상정액의 품질을 간편하게 육안적으로 식별하기 위한 방법을 개발하기 위하여 채취된 정액을 페놀레드(0.5%)가 첨가된 BTS보존액에 정액과 회석액비율을 1:1로 희석하여 1-2시간 17℃까지 냉각시킨 후 최종정자수가 3×10/sup 9/ sperm/80㎖ 되도록 최종 추가조정 희석한 후 17℃에서 1, 3 및 5일 동안 보관한 정액의 활력과 pH를 조사하고 페놀레드 색상변화를 Figure 1과 같이 pH 6.2-8.0까지의 색상을 10등급으로 나누고 pH 7.0 수준을 표준색상으로 하여 색상 변화를 조사한 결과는 다음과 같다. 돼지 액상정액을 17℃에서 1, 3 및 5일 동안 각각 보관하였을 때 정자 활력은 71.9%, 59.8% 및 53.9%였으며, 이 때 pH 는 각각 6.89, 6.84 및 7.06으로 적정 색상을 나타내었다. (중략)

• Composites Research
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• v.26 no.3
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• pp.195-200
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• 2013

This study aims to detecting and analyzing the defects of damaged carbon fiber reinforced composites after impacts, particularly focusing on barely visible impact damages. The impact test was progressed by a drop-weight machine and applied to introduce simulated damages on laminated composites used in aircrafts. Various nondestructive testing (NDT) techniques were applied to identify the defects on the specimens with different levels of impact energies. Based on the measurements data, the levels of the barely visible impacts, and the applicability and effectiveness of the detection methods were discussed. Generally, the results demonstrated that their inner damages contained bigger footprints than those on the surfaces. However, when the damage energy was low, it was found that the inner damage size could be smaller than those appeared on the surfaces.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.33-42
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• 2020

There has been difficulties in identifying objects by relying on the naked eye in various surveillance systems. There is a growing need for automated surveillance systems to replace soldiers in the field of military surveillance operations. Even though the object detection technology is developing rapidly in the civilian domain, but the research applied to the military is insufficient due to a lack of data and interest. Thus, in this paper, we applied one of deep learning algorithms, Convolutional Neural Network-based binary classification to develop an autonomous identification model of both friend and foe helicopters (AH-64, Mi-17) among the military weapon systems, and evaluated the model performance by considering accuracy, precision, recall and F-measure. As the result, the identification model demonstrates 97.8%, 97.3%, 98.5%, and 97.8 for accuracy, precision, recall and F-measure, respectively. In addition, we analyzed the feature map on convolution layers of the identification model in order to check which area of imagery is highly weighted. In general, rotary shaft of rotating wing, wheels, and air-intake on both of ally and foe helicopters played a major role in the performance of the identification model. This is the first study to attempt to classify images of helicopters among military weapons systems using CNN, and the model proposed in this study shows higher accuracy than the existing classification model for other weapons systems.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.116-123
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• 2007

Despite the number of backlight manufacturer is increased as the market of flat panel display equipments and related development devices is enlarged, the inspection based on the human eye is still used in many backlight production lines. The defects such as particle, spot and scratch on the light emitting surface of the backlight prevent the LCD device from displaying the colors correctly. From that manual inspection it is difficult to maintain the quality of backlight consistently because the accuracy and the speed of the inspection may change with the physical condition of the operater. In this paper we studied on the development of automatic backlight surface defect inspection system. For this, we made up of the computer vision system and we developed the main program with various user interfaces to operate the inspection system effectively. And we developed the image processing module to extract the defect information. Furthermore, we presented the labeling process to reconstruct defect regions using the labeling table and the defect index. From the experimental results, we found that our system can detect all defect regions identified from human eye and it is sufficient to substitute for the conventional surface inspection.

• 한국문화재보존과학회:학술대회논문집
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• 2005.11a
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• pp.290-295
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• 2005

본 실험은 경주 월성해자와 일정교지에서 발굴된 고목재를 시료로 사용하였다. 월성 해자 5점, 일정교지 2점으로 총 7점을 대상으로 수종분석과 연륜연대 해석을 실시하였다. 수종분석은 광학현미경을 사용하여 식별을 하였으며, 연륜연대 해석은 연륜측정후 연륜분석 컴퓨터프로그램과 그래프 일치도를 육안으로 비교하여 실시하였다. 7개의 시료 전부 밤나무였다. 밤나무는 현재 평남과 함남 이남에 분포하는 수종으로 특히 따뜻한 남부지방에 살기 적합한 수종이다. 각 시료간의 상대연도를 확인한 결과는 월성해자 목재의 수령은 $31{\sim}37$년 일정교지는 45년으로 확인 되었다. 월성해자의 각 시료들은 동시대이나 벌채기간은 6년 차이가 났다. 일정교지의 시료에서는 일치성을 확인하지 못했다.

• Journal of Korean Society of Forest Science
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• v.15 no.1
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• pp.39-41
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• 1972

Yew heartwood from different species was analysed by thin-layer chromatography for its phenolic content. A separation could be made between the species examined on the basis of the occurrence of heartwood phenols.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.215-218
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• 2012

농업에 있어 해충 방제는 중요한 일이다. 특히, 볼록총채벌레는 최근 감귤원 해충 피해의 주요 해충으로 인식되어 주기적인 예찰이 이루어지고 있으나 성충의 크기가 0.8mm 정도로 작아 육안 식별에 어려움이 있다. 본 논문에서는 예찰 트랩에 포집된 볼록총채벌레를 자동으로 판별하기 위한 전처리 알고리즘을 제안하였다. 광학 현미경의 배율을 30, 40, 50배로 조정하여 영상을 획득하였고, 제안한 알고리즘을 적용하여 판별 성능을 측정한 결과, 50배율에서 가장 높은 판별율을 보였으나 더 많은 볼록총채벌레 영상을 대상으로 알고리즘을 테스트하고 개선할 필요가 있다.