• The Journal of the Korean dental association
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• v.24 no.6 s.205
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• pp.541-547
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• 1986

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.909-910
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• 2013

• Restorative Dentistry and Endodontics
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• v.24 no.4
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• pp.560-569
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• 1999

Blood supply rather than nerve supply implies pulp vitality. To evaluate pulp vitality clinically, electric pulp test and thermal test which are based on sensory nerve response have been used in addition to many auxiliary data such as past dental history, visual inspection, radiographic examination, percussion, palpation and transillumination test. However, reactivity of the nerves to the stimulation is not synonymous with normalcy. Therefore measurement of pulpal blood flow using a laser Doppler flowmeter became a new trial to test the pulp vitality. The purpose of the present study was to evaluate normal pulpal blood flow level of maxillary teeth in adult to provide a guideline in determining the vitality of dental pulp. Pulpal blood flow was measured in maxillary central and lateral incisors, canines, first and second premolars and first molars of seventy nine adults of 22 - 30 years old using a laser Doppler flowmeter (PeriFlux 4001, Perimed Co., Stockholm, Sweden, 780 nm infrared laser, 1mW). For directly-made splints, silicone rubber impressions were taken directly from the mouth. For indirectly-made splints, alginate impressions were taken from the mouth and stone cast were made. After making depressions on the buccal surfaces of the cast teeth to indicate the hole positions, second impressions with vinyl polysyloxane putty were taken from the cast. Holes for the laser probes were made at the putty impressions 4mm above the gingival level. Laser probe (PF416 dental probe, 1.5mm) was inserted in the prepared hole and the splint was set in the mouth. After 10 minutes of patient relaxing, pulpal blood flow was recorded for 5 minutes on each tooth. The recorded flow was saved in the computer and calculated with a software 'Perisoft' version 5.1. Pulpal blood flow was also recorded in six teeth of five individuals with no response to electric pulp test and cold test, with periapical radiolucency, or with history of root canal treatment to compare with nonvital teeth. The difference between the mean flow values of each group of teeth were analyzed using one-way ANOVA and Duncan's Multiple Range test. The results were as follows: 1. The average pulpal blood flow values of all the tested teeth of each location were between 9 - 16 Perfusion Unit. Pulpal blood flow value was highest in maxillary lateral incisors, followed by first premolars, second premolars, canines, central incisors, and then first molars (p<0.01). 2. In six anterior teeth, indirectly-made splint group showed higher pulpal blood flow values than directly-made splint group (p<0.01). In posterior teeth, however, there was no significant flow value difference between directly-made splint group and indirectly-made splint one (p>0.05). 3. Teeth with vital pulps showed higher signal values than teeth with nonvital pulps (p<0.01), and the flow photographs showed heartbeat-synchronous fluctuations and vasomotions, while those were absent in non vital tooth.

• Journal of the korean academy of Pediatric Dentistry
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• v.27 no.1
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• pp.103-107
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• 2000

Traditionally, EPT and thermal tests were used as diagnostic methods for pulp vitality test. The thermal and electrical stimulation tests are the methods to determine the vitality of a tooth based on its neuronal response. These have certain limitations, one of them is the difficulty of approaching the correct result in case of treatment of children. The reason is management problem caused by the unpleasant stimulation. Also, the response from patients are not objective, and false positive or false negative could be happened. Recently, laser doppler flowmetry and pulse oximeter which evaluate vascular integrity are introduced in an effort of overcoming to limitation of traditional methods. The principle of pulse oximeter is to and out level of oxygen saturation by ratio of the two pulses between emitted light and detected light penetrating them to the termination of body, such as ears or fingers. From this point of view, it can be applied to a tooth to determine its vitality. The objective of this study lies mainly on varifying pulse oximeter as a method of determining tooth vitality and providing basic data of its clinical implementation. The result of the research showed that level of oxygen saturation in vital teeth was average of 96.3% and 0.0% in pulpless teeth. As a comprehensive result, pulse oximeter could be an useful diagnostic equipment in determining of tooth vitality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.453-458
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• 2016

One of the most common applications of machine vision is quality inspections in automated production. In this study, a welding inspection system that is controlled by a PC and a PLC equipped with a multi-camera setup was developed. The system was designed to measure the primary dimensions, such as the length and width of the welding areas. The TCP/IP protocols and multi-threading techniques were used for parallel control of the optical components and physical distribution. A coaxial light was used to maintain uniform lighting conditions and enhance the image quality of the weld areas. The core image processing system was established through a combination of various algorithms from the OpenCV library. The proposed vision inspection system was fully validated for an actual weld production line and was shown to satisfy the functional and performance requirements.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4115-4120
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• 2010

In manual inspection of Lead Screw of computers many workers are needed to inspect samples, and its main disadvantage is that such types of inspection system not only gives low production, but also gives low perfection. Besides, in manual inspection system, the inspection cost of samples is higher than that of the automatic inspection system. Therefore, in this study to compensate these shortcomings, an automatic inspection system is developed. For the inspection of the surfaces and different dimensional parameters of computer Lead screw, a $360^{\circ}$ rotating machine vision system is developed. From the detailed analysis of the inspection results using the present developed inspection system, it is observed that the developed Lead Screw automatic inspection system is superior to those of manually inspection system.

• Restorative Dentistry and Endodontics
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• v.27 no.5
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• pp.515-520
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• 2002

연구목적 : Cytokine은 유해 미생물에 대한 숙주의 방어기전으로서의 염증반응에서 숙주세포 상호간의 작용을 매개해 주는 역할을 하며, 치수조직에서도 그 존재가 확인된 바 있다. Interleukin-6와 Interleukin-10은 염증의 초기에 작용하는 cytokine으로 알려져 있으나, 치수 및 치근단 질환에서의 역할과 상호작용에 대해서는 잘 알려져 있지 않다. 본 연구에서는 성인의 치수염이 있는 치아에서 Interleukin-6와 Interleukin-10의 농도를 측정하고 이를 정상 치수와 비교함으로써 이들의 치수염에서의 작용을 연구하는 것을 목적으로 하였다. 방법 : 총 60개의 성인 치아들을 대상으로 하였다. 치수염으로 진단된 치아들을 실험군으로 하였고, 정상 치수를 가진 치아들을 대조군으로 하였다. 발치한 치아에서 치수조직을 적출하였다. ELISA를 사용하여 적출된 치수조직 내의 Interleukin-6와 Interleukin-10의 양을 측정하였으며, 그 결과를 Mann-Whitney rank sum test를 사용하여 통계학적 유의성을 검증하였다. 조직학적 검사를 위해서는 발치된 치아에서 치수조직을 적출하여 헤마톡실린-에오신 염색을 시행한 후 관찰하였다. 결과 : 1. Interleukin-6의 농도는 실험군에서 대조군보다 유의하게 높게 나타났다(p<0.05). 2. Interleukin-10의 농도는 실험군에서 대조군보다 유의하게 높게 나타났다(p<0.05). 3. 조직학적 관찰 결과 실험군에서 림프구의 침윤과 부분적인 조직의 괴사 등 염증반응의 양상을 관찰할 수 있었다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.193-198
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• 2001

생산현장 업무에서는 측정검사업무의 비중이 크다. 측정검사의 업무는 품질향상을 위한 활동이며 또한 고부가가치의 제품을 위해서도 중요하다. 고품질 고정밀도는 철저한 측정검사를 통하여 이루어진다. 제품의 치수를 정확히 측정하여 정밀도 있는 부품을 제작하고 불량부품이나 파손된 부품을 검사하여 제거함으로써 제품의 성은과 품질이 우수하게 인정된다. 이러한 측정검사작업의 정밀도향상, 생산성 향상을 위해서는 자동화가 필요하다. 측정검사의 자동화 (CAT : Computer Aided Testing)에는 영상처리를 이용하는 시각검사의 자동화가 중요한 분야이다. 영상처리를 이용한 시각검사의 대상은 결함검사, 두께검사, 형상칫수 검사, 물체의 위치, 방향, 종류의 파악 등이 있다.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.57-62
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• 2004

그레이팅(Grating)이라는 금속제품을 생산하는 5 업체에서는 설계 자동화 시스템인 GDS(Grating automatic Drawing System)를 통해 전체 설계도면(Plan Drawing)을 생성하고 GDS의 도면자료 자동생성 시스템(ASGS: Automatic Specification Generation System)을 통해 전체 도면상에 배치된 각각의 그레이팅에 대한 상세한 정보가 표현된 단품별 도면과 완성된 제품들에 대한 검사 기준을 표현한 검사도면을 생성하며 전체 제품에 대한 통계적인 정보를 생성한다. 그러나 도면자료 자동생성 시스템을 통해 자동 생성된 도면은 설계자들의 일반적인 치수 기입요령을 부분적으로 만족시키지 못하고 있으며 또 치수 표시간의 겹침 현상이 발생하여 설계자가 도면을 수정해야하는 번거로움이 있었다. 본 논문은 이러한 문제점을 해결하기 위해, 설계 전문가들의 치수 표시법을 지식으로 하는 규칙 기반 전문가 시스템을 구성하였다.

• Journal of IKEEE
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• v.28 no.3
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• pp.474-478
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• 2024

In this paper, we proposes a deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers. The proposed deep learning network is specifically designed for pharmaceutical containers by using data produced in real manufacturing environments, leading to more accurate quality inspection. Additionally, the use of an inline-capable deep learning network allows for an increase in inspection speed. The development of the deep learning network for quality inspection in the multi-camera inline inspection system consists of three steps. First, a dataset of approximately 10,000 images is constructed from the production site using one line camera for foreign substance inspection and three area cameras for dimensional inspection. Second, the pharmaceutical container data is preprocessed by designating regions of interest (ROI) in areas where defects are likely to occur, tailored for foreign substance and dimensional inspections. Third, the preprocessed data is used to train the deep learning network. The network improves inference speed by reducing the number of channels and eliminating the use of linear layers, while accuracy is enhanced by applying PReLU and residual learning. This results in the creation of four deep learning modules tailored to the dataset built from the four cameras. The performance of the proposed deep learning network for quality inspection in the multi-camera inline inspection system for pharmaceutical containers was evaluated through experiments conducted by a certified testing agency. The results show that the deep learning modules achieved a classification accuracy of 99.4%, exceeding the world-class level of 95%, and an average classification speed of 0.947 seconds, which is superior to the world-class level of 1 second. Therefore, the effectiveness of the proposed deep learning network for quality inspection in a multi-camera inline inspection system for pharmaceutical containers has been demonstrated.