• Annals of Laboratory Medicine
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• 제38권6호
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• pp.578-584
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• 2018

Background: Accurate, rapid, and cost-effective screening tests for hepatitis B virus (HBV) and hepatitis C virus (HCV) infection may be useful in laboratories that cannot afford automated chemiluminescent immunoassays (CLIAs). We evaluated the diagnostic performance of a novel rapid automated fluorescent lateral flow immunoassay (LFIA). Methods: A fluorescent LFIA using a small bench-top fluorescence reader, Automated Fluorescent Immunoassay System (AFIAS; Boditech Med Inc., Chuncheon, Korea), was developed for qualitative detection of hepatitis B surface antigen (HBsAg), antibody to HBsAg (anti-HBs), and antibody to HCV (anti-HCV) within 20 minutes. We compared the diagnostic performance of AFIAS with that of automated CLIAs-Elecsys (Roche Diagnostics GmbH, Penzberg, Germany) and ARCHITECT (Abbott Laboratories, Abbott Park, IL, USA)-using 20 seroconversion panels and 3,500 clinical serum samples. Results: Evaluation with the seroconversion panels demonstrated that AFIAS had adequate sensitivity for HBsAg and anti-HCV detection. From the clinical samples, AFIAS sensitivity and specificity were 99.8% and 99.3% for the HBsAg test, 100.0% and 100.0% for the anti-HBs test, and 98.8% and 99.1% for the anti-HCV test, respectively. Its agreement rates with the Elecsys HBsAg, anti-HBs, and anti-HCV detection assays were 99.4%, 100.0%, and 99.0%, respectively. AFIAS detected all samples with HBsAg genotypes A-F and H and anti-HCV genotypes 1, 1a, 1b, 2a, 2b, 4, and 6. Cross-reactivity with other infections was not observed. Conclusions: The AFIAS HBsAg, anti-HBs, and anti-HCV tests demonstrated diagnostic performance equivalent to current automated CLIAs. AFIAS could be used for a large-scale HBV or HCV screening in low-resource laboratories or low-to middle-income areas.

• 한국시뮬레이션학회논문지
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• 제21권4호
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• pp.1-9
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• 2012

본 논문에서는 유한 용량 자동생산 시스템의 효율적인 운용을 위하여 기존에 제안된 은행가(BA) 알고리즘의 단점을 개선시킨 2단계 Look-ahead 은행가 알고리즘을 제안하였다. 제안된 알고리즘은 각 job 단위 별 전체 남은 공정의 처리 가능성뿐만 아니라 job들 간의 부분적인 이동 가능성을 동시에 고려하여 시스템 내부에 존재하는 job들의 완성 가능성을 결정함으로서 기존 알고리즘의 안전 상태 식별 능력을 향상시켰다. 수치 실험을 통해 제안된 알고리즘의 향상된 성능을 (i) 안전 상태 탐색율과 (ii) 시스템 Throughput을 기준으로 확인하였으며, paired t-test를 통해 검증하였다.

• 대한화학회지
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• 제33권4호
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• pp.388-398
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• 1989

기체 감응막전극을 이용하여 수용액 중의 아질산이온을 연속${\cdot}$자동화법으로 정량하는 방법을 개발하였다. 이 방법에서 최종검출기로 쓴 이온선택성 전극은 관형 PVC막 pH 전극이었다. 장치계의 최적조건에서 구한 아질산이온 표준시료에 대한 전극의 감응기울기는 63.5mV/decade 이었으며, 직선감응 범위는 $2.5{\times}10^{-4}\; M{\sim}7.5 {\times} $10^{-2}$M 이었고, 검출한계는 $8.0{\times} 10^{-5}$M이었다. 이 방법은 다른 정량법보다 산성기체종의 방해를 적게 받을 뿐만 아니라 정량에 필요한 시간도 훨씬 단축할 수 있었다.

• Journal of Astronomy and Space Sciences
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• 제36권2호
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• pp.97-103
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• 2019

An automated signal-acquisition method for the NASA's space geodesy satellite laser ranging (SGSLR) system is described as a selection of two system parameters with specified probabilities. These parameters are the correlation parameter: the minimum received pulse number for a signal-acquisition and the frame time: the minimum time for the correlation parameter. The probabilities specified are the signal-detection and false-acquisition probabilities to distinguish signals from background noise. The steps of parameter selection are finding the minimum set of values by fitting a curve and performing a graph-domain approximation. However, this selection method is inefficient, not only because of repetition of the entire process if any performance values change, such as the signal and noise count rate, but also because this method is dependent upon system specifications and environmental conditions. Moreover, computation is complicated and graph-domain approximation can introduce inaccuracy. In this study, a new method is proposed to select the parameters via a conditional equation derived from characteristics of the signal-detection and false-acquisition probabilities. The results show that this method yields better efficiency and robustness against changing performance values with simplicity and accuracy and can be easily applied to other satellite laser ranging (SLR) systems.

• 정보보호학회논문지
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• 제26권2호
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• pp.397-404
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• 2016

최근 국내에서 불법 유해정보의 양은 꾸준히 증가하고 있으며, 중소기업, 공공기관 등의 게시판에 불법 유해정보 글들이 많이 게시되고 있다. 불법 유해정보를 통해 범죄로 이어질 가능성이 크기 때문에 이를 탐지하는 시스템이 필요하다. 현재 국내의 불법 유해정보 탐지는 인력에 의해 수동적으로 진행되고 있다. 본 논문에서는 공개출처정보(OSINT)를 통해 불법 유해정보 중 마약 판매 게시글의 URL 탐지를 자동화하는 연구를 진행하였다. 이 시스템은 마약 판매 게시글의 단어를 분석하고, 해당 단어로 검색어 사전을 만들었다. 검색어 사전 기반으로 검색되는 마약판매 의심 URL을 구글 검색엔진을 활용하여 자동으로 수집하였다. 수집 URL을 도메인별로 분류하였으며, 도메인을 수집 URL 개수별로 도식화하여 실제 불법 유해정보를 찾아내었다. 이 자동화 탐지 시스템을 활용하면 모니터 요원의 수동적인 탐지업무로 인한 시간과 노력의 소비 문제를 해결할 것으로 기대된다.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.1093-1096
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• 2002

In this paper, a new semi-automated cyber character generating method is presented. Local edge detection tools extract face contour from graphic image files. Some graphic manipulation process detailed touch to obtain neat face contour. This method shortens the making process dramatically while maintaining the good quality similar to real face image. Some of the processed images are illustrated for clear explanation.

• 제어로봇시스템학회논문지
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• 제3권4호
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• pp.406-414
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• 1997

A real-time inspection system is developed using line scan cameras. Several improved algorithms are proposed for real-time detection of defects in this automated inspection system. The major improved algorithms include the preprocessing, the threshold decision, and the clustering algorithms. The preprocessing algorithms are for exact binarization and the threshold decision algorithm is for fast detection of defects in 1-D binary images. The clustering algorithm is also developed for fast classifying of the defects. The system is applied to PCBs(Printed Circuit Boards) inspection. The typical defects in PCBs are pits, dent, wrinkle, scratch, and black spots. The results show that most defects are detected and classified successfully.

• 한국항만학회지
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• 제12권2호
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• pp.225-232
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• 1998

Todays, the efficient management of container has not been realized in container terminal, because of the excessive quantity of container transported and manual system. For the efficient and automated management of container in terminal, the automated container identifier recognition system in terminal is a significant problem. However, the identifier recognition rate is decreased owing to the difficulty of image preprocessing caused the refraction of container surface, the change of weather and the damaged identifier characters. Therefore, this paper proposes more accurate system for container identifier recognition as suggestion of LSPRD(Line-Scan Proper Region Detection) for stronger preprocessing against external noisy element and MBP(Momentum Back-Propagation) neural network to recognize the identifier.

• 비파괴검사학회지
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• 제33권6호
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• pp.519-523
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• 2013

A steam generator (SG) tube is an important component of a nuclear power plant (NPP). It works as a pressure boundary between the primary and secondary systems. The integrity of a SG tube can be assessed by an eddy current test every outage. The eddy current technique(adopting a bobbin probe) is currently the main technique used to assess the integrity of the tubing of a steam generator. An eddy current signal analyst for steam generator tubes continuously analyzes data over a given period of time. However, there are possibilities that the analyst conducting the test may get tired and cause mistakes, such as: missing indications or not being able to separate a true defect signal from one that is more complicated. This error could lead to confusion and an improper interpretation of the signal analysis. In order to avoid these possibilities, many countries of opted for automated analyses. Axial ODSCC (outside diameter stress corrosion cracking) defects on the tubes of OPR1000 steam generators have been found on the tube that are in contract with tube support plates. In this study, automated analysis software called CDS (computer data screening) made by Zetec was used. This paper will discuss the results of introducing an automated analysis system for an axial ODSCC on the tubes of an OPR1000 steam generator.

• 대한임베디드공학회논문지
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• 제12권6호
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• pp.395-403
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• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.