• 전기학회논문지
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• 제59권11호
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• pp.2038-2042
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• 2010

In this paper, we confirmed the thermal & optical properties for improving the heat transfer coefficient by changing the via hole size and in FR4 PCB with the same area. Osram 1W power LED Package (Golden Dragon) was used and the K-factor which is relative constant between LED junction temperature and forward bias was measured with power source meter(KEITHLEY 2430) to measure the thermal resistance from PCB configuration. As results, thermal resistance in metal PCB came out to the lowest as $26 [^{\circ}C/W]$ and thermal resistance in FR4 PCB without via-holes emerged as the highest as $69 [^{\circ}C/W]$. However thermal resistance of FR4 PCB could have decreased until $32[^{\circ}C/W]$ in 0.6 mm by using the via hole. Also, the luminous flux could have improved, too.

• 한국재료학회지
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• 제18권3호
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• pp.117-122
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• 2008

Micro-sized bumps on a multi-layered build-up PCB were fabricated by pulse-reverse copper electroplating. The values of the current density and brightener content for the electroplating were optimized for suitable performance with maximum efficiency. The micro-bumps thus electroplated were characterized using a range of analytical tools that included an optical microscope, a scanning electron microscope, an atomic force microscope and a hydraulic bulge tester. The optical microscope and scanning electron microscope analyses results showed that the uniformity of the electroplating was viable in the current density range of $2-4\;A/dm^2$; however, the uniformity was slightly degraded as the current density increased. To study the effect of the brightener concentration, the concentration was varied from zero to 1.2 ml/L. The optimum concentration for micro-bump electroplating was found to be 0.6 ml/L based on an examination of the electroplating properties, including the roughness, yield strength and grain size.

• 한국광학회지
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• 제19권4호
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• pp.255-261
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• 2008

광 백 플레인이나 광 연결용으로 활용될 수 있는 연성 광 PCB의 핵심 요소인 광 배선(도파로)의 전파 특성을 분석하였으며, 광배선 제작 공정에서 발생할 수 있는 구조적 오차로 인한 전파 손실 발생 문제를 다루었다.제작 공차 분석을 통해 전파 손실을 -1 dB/mm 이하로 유지하기 위해서는 광 배선 측벽 각도가 $1^{\circ}$ 이내로 제어되어야 하며, 결합 손실과 구부러짐 손실을 각각 -1 dB 이하로 유지하기 위해서는 광원과 광 배선 간격은 $160\;{\mu}m$ 이내, 횡방향 정렬 오차는 ${\pm}15\;{\mu}m$ 이내, 광원 각도는 $6^{\circ}$ 이하로 정렬되어야 하며, 광 배선의 구부러짐 반경은 5 mm 이상이 되어야 함을 알 수 있었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.160-165
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• 1998

The sub-resonance modes can be easily excited by the assembling tolerance in the asymmetric type optical pick-up actuators, compared with the symmetric type. In this paper, we propose the novel method for reducing the vibration due to the sub-resonance modes where undesirable modes can be decreased by adding the damping, which can be achieved by increasing the flexibility of holder PCB, against to the sub-resonance modes. Using the finite element method, the change of mode shapes is investigated as the shape of holder PCB is modified. Experimental results support that the proposed method reduces remarkably the vibration of sub-resonance modes of the optical pick-up actuator.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.6-10
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• 2021

Recognition of characters printed or marked on the PCB components from images captured using cameras is an important task in PCB components inspection systems. Previous optical character recognition (OCR) of PCB components typically consists of two stages: character segmentation and classification of each segmented character. However, character segmentation often fails due to corrupted characters, low image contrast, etc. Thus, OCR without character segmentation is desirable and increasingly used via deep neural networks. Typical implementation based on deep neural nets without character segmentation includes convolutional neural network followed by recurrent neural network (RNN). However, one disadvantage of this approach is slow execution due to RNN layers. LPRNet is a segmentation-free character recognition network with excellent accuracy proved in license plate recognition. LPRNet uses a wide convolution instead of RNN, thus enabling fast inference. In this paper, LPRNet was adapted for recognizing characters printed on PCB components with fast execution and high accuracy. Initial training with synthetic images followed by fine-tuning on real text images yielded accurate recognition. This net can be further optimized on Intel CPU using OpenVINO tool kit. The optimized version of the network can be run in real-time faster than even GPU.

• 한국산학기술학회논문지
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• 제13권11호
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• pp.5471-5478
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• 2012

본 논문에서는 SURF 알고리즘을 이용하여 PCB에 발생하는 불량 중 한 형태인 쇼트-서킷 불량을 탐지하는 기술을 제안한다. 제안하는 방법의 기본적인 절차는 SURF를 이용하여 샘플 영상과 입력된 영상에서 특징점 추출, 특징점 매칭 및 매칭 결과를 이용한 원근변환 수행, 검사 위치 관심영역 추출, 이진화 및 쇼트-서킷 추출, 결과 검증 순이다. 본 논문에서 제안하는 방식은 수작업으로 진행되는 후 공정의 특징 상, 검사하고자 하는 PCB의 놓여진 위치와 각도가 균일하지 않고 제각각으로 놓여 있는 경우에도 강건하게 쇼트-서킷 불량을 탐지하는 것에 중점을 두고 있다. 이 방법은 PCB가 놓여진 위치와 각도가 다양한 경우에도 불량을 탐지할 수 있음을 보이며, 탐지율 및 탐지시간 관점에서 기존의 수작업으로 검사하는 경우보다 우수함을 실험을 통하여 보인다.

• 광학과기술
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• 제8권2호
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• pp.30-36
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• 2004

최근 인터넷의 급속한 확산과 정보화 사회의 출현으로 정보통신 수요가 급격히 증가하게 되었으며, 이에 따라 대부분의 유선통신 방식이 광통신 방식으로 대체되고 있다. 또한 조만간 가정이나 사무실에까지 광섬유가 설치되어 초고속 대용량 정보 전달이 광에 의해 수행될 전망이다. 정보 전달이 광에 전적으로 의존함에 따라 정보 생성, 정보처리 및 가공, 정보 분배, 정보 저장까지도 광으로 처리하려는 개념은 자연스러운 발상이며, 이를 실현하려는 노력은 당연한 것이라 생각한다.(중략)

• 광학세계
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• 통권117호
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• pp.23-25
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• 2008

RF embedded 기판의 기술은 Module과 Package라는 응용 제품을 거치면서 최종적으로는 기존의 여러 가지 제품의 Mother Board(특히 휴대폰)에 접목 시키기 위한 노력이 계속 진행되고 있다. 업계 및 Research 기관의 조사 결과에 따르면 PCB 시장의 성장세와 맞물려 Embedded 시장규모는 큰 폭의 상승이 예상된다. 본 고에서는 높은 유전율을 가지는 강유전체 물질의 Embedded capacitor 적용을 위해 레이저 기술을 전자부품 제조현장에 적용하는 연구의 진행상황을 소개하고자 한다.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.225-234
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• 2019

Deep learning has become increasingly popular in both academic and industrial areas nowadays. Various domains including pattern recognition, Computer vision have witnessed the great power of deep neural networks. However, current studies on deep learning mainly focus on quality data sets with balanced class labels, while training on bad and imbalanced data set have been providing great challenges for classification tasks. We propose in this paper a method of data analysis-based data reduction techniques for selecting good and diversity data samples from a large dataset for a deep learning model. Furthermore, data sampling techniques could be applied to decrease the large size of raw data by retrieving its useful knowledge as representatives. Therefore, instead of dealing with large size of raw data, we can use some data reduction techniques to sample data without losing important information. We group PCB characters in classes and train deep learning on the ResNet56 v2 and SENet model in order to improve the classification performance of optical character recognition (OCR) character classifier.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 C
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• pp.1735-1736
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• 2006

As developing the information society, Lighting Emitted diode(LED) which is light source for illumination of next generation is attracted public attention. LED have many problem as narrow light view angle, high price, drift phenomenon of color coordinate, high heating problem for lower power, lower weight and small size. So, many researches have continued in a illumination as LED module type. in this problem, heating problem is very important and difficult and that is caused in decreasing phenomenon of brightness and drift phenomenon of color coordinate. so the problem of heating is urgent question for illumination of LED. In this paper, structural design of PCB changed as two type for solving the heating problem. also the properties of heating is analysed and optical properties is measured with heating image camera and spectrometer according to change in this design.