• Journal of Microbiology and Biotechnology
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• 제33권8호
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• pp.1101-1110
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• 2023

Streptococcus mutans is the primary causative agent of caries, which is one of the most common human diseases. Thus, rapid and early detection of cariogenic bacteria is critical for its prevention. This study investigated the combination of loop-mediated isothermal amplification (LAMP) and microfluid technology to quantitatively detect S. mutans. A low-cost, rapid microfluidic chip using LAMP technology was developed to amplify and detect bacteria at 2.2-2.2 × 10⁶ colony-forming units (CFU)/ml and its detection limits were compared to those of standard polymerase chain reaction. A visualization system was established to quantitatively determine the experimental results, and a functional relationship between the bacterial concentration and quantitative results was established. The detection limit of S. mutans using this microfluidic chip was 2.2 CFU/ml, which was lower than that of the standard approach. After quantification, the experimental results showed a good linear relationship with the concentration of S. mutans, thereby confirming the effectiveness and accuracy of the custom-made integrated LAMP microfluidic system for the detection of S. mutans. The microfluidic system described herein may represent a promising simple detection method for the specific and rapid testing of individuals at risk of caries.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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• pp.768-773
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• 2011

Today's urban transit system is regarded as the important public transportation service which saves passengers' time and provides the safety. Many researches focus on the rapid and protective responses that minimize the losses when dangerous situation occurs. In this paper we proposed the early fire detection and corresponding rapid response method in urban transit system by combining automatic fire detection for video input and the sensor system. The fire detection method consists of two parts, spark detection and smoke detection. At the spark detection, the RGB color of input video is converted into HSV color and the frame difference is obtained in temporal direction. The region with high R values is considered as fire region candidate and stepwise fire detection rule is applied to calculate its size. At the smoke detection stage, we used the smoke sensor network to secure the credibility of spark detection. The proposed system can be implemented at low prices. In the future work, we would improve the detection algorithm and the accuracy of sensor location in the network.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.205-209
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• 2008

최근 하드웨어의 발달로 영상처리를 사용한 운전자 보조 기능의 차선인식 시스템이 상용화 되고 있다. 하지만 고속도로 주행과 같은 차선이 확실하고 곡률이 완만한 비교적 이상적인 상황에서의 차선인식을 전제로 만들어진 시스템이 많아 시내도로와 같이 상대적으로 곡률이 크고 일부 차선이 확실치 않은 장소에서는 차선인식이 힘들어 무인 자동차 제어에는 적용하기 힘들다. 본 논문은 무인차량의 자동주행을 위해 labeling과 차선예측을 통해 급격한 곡선 차로나 차선이 한쪽만 그려져 있는 경우에도 강인하게 차선인식이 가능한 시스템을 제안한다. 제안된 방법을 이용하여 이상적인 경우가 아닌 급격한 곡선차로가 있거나, 차선이 한쪽만 있는 실제 환경의 경우에서도 차선인식이 가능함을 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.561-564
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• 2002

With Rapid Prototyping system, the efficient packing in a fixed work volume reduces build time when multiple parts are built in a process. In this paper, an efficient and rapid packing algorithm is developed for SLS system that has cylindrical workspace. A genetic algorithm is implemented to place as many part as possible in a vat. For fast computation, a collision detection algorithm "k-DOPs Tree" is implemented.

• 대한수의학회지
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• 제47권4호
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• pp.399-407
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• 2007

Cause of high lethality and dissemination to human being, new development of rapid method for the detection of highly pathogenic Avian Influenza Virus (AIV) is still necessary. For the detection of AIV subtype H5N1, typical pathogenic AIV, new method to confirm sub-typing of this virus is also needed. For the purpose of ultra-rapid detection and sub-typing of hemagglutinin and neuraminidase of AIV, this study was planned. As the results we could demonstrate an ultra-rapid multiplex real-time PCR (URMRT PCR) for the detection of AIV In this study, the URMRT PCR were optimized with synthesized AIV H5- and AIV Nl-specific DNA templates and GenSpector TMC, which is a semiconductor process technology based real-time PCR system with high frequencies of temperature monitoring. Under eight minutes, the amplifications of two AIV subtype-specific PCR products were successfully and independently detected by 30 cycled ultra-rapid PCR, including melting point analysis, from $1{\times}10^3$ copies of mixed template DNA. The URMRT PCR for the detection of AIV H5N 1 developed in this study could be expected to apply not only detections of different AIVs, but also various pathogens. It was also discussed that this kind of the fastest PCR based detection method could be improved by advance of related technology in near future.

• 한국신뢰성학회지:신뢰성응용연구
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• 제14권1호
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• pp.37-43
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• 2014

This paper deals with a design of observer based fault detection filter for a boiler-turbine control system. The goal is to present a method for rapid sensor fault detection in order to enhance the reliability of boiler-turbine operation in the thermal power plant. Our fault detection filter can be designed via solutions of linear matrix inequalities. In order to demonstrate the efficacy of our design method, numerical simulations are provided.

• Journal of Biosystems Engineering
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• 제31권2호
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• pp.128-134
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• 2006

Frequent outbreaks of foodborne illness demand the need for rapid and sensitive methods for detection of these pathogens. Recent development of biosensor technology has a great potential to meet the need for rapid and sensitive pathogens detection from foods. An antibody-based fiber-optic biosensor and an automated reagents supply system to detect Listeria monocytogenes were developed. The biosensor for detection of Listeria monocytogenes in PBS and bacteria spiked food samples was evaluated. The automated reagents supply system eliminated cumbersome sample and detection antibody injection procedures that had been done manually. The biosensor could detect $10^4$ cfu/ml of Listeria monocytogenes in PBS. By using the fiber-optic biosensor, $2x10^8$ cfu/ml of Listeria monocytogenes in the food samples were detectable.

• 전기학회논문지
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• 제61권1호
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• pp.143-147
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• 2012

The rapid growth of camera technology can provide various types of information which was not previously provided. Furthermore, IP camera which has rapid data transfer rate and high resolution particularly provide a lot of useful functions beyond the existing simple surveillance capabilities. We are developing Real-Time Face Recognition Access Control System based on the camera technology, and improvement of face detection and recognition algorithms are vitally needed to realize that system. In this paper, we proposes a method to improve the computing speed and detection rate by adding new features to the existing Viola-Jones detection algorithm.

• 한국멀티미디어학회논문지
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• 제15권6호
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• pp.722-730
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• 2012

최근 생체 인식 분야나, HCI 분야 등에서 사람의 눈 영상 정보를 이용하여 홍채 인식을 하거나 시선위치 정보를 이용하는 연구가 활발히 진행 되고 있다. 특히 사용자의 편의성을 위한 원거리 카메라 기반시스템이 늘어나면서 눈 영상 촬영에 단순히 동공 중심 영역만 촬영 되는 것이 아니라, 눈썹, 이마, 피부영역 등 부정확한 검출을 일으킬 수 있는 요소가 포함되어 촬영되고 이러한 불필요한 요소들은 동공 중심영역의 검출 성능을 저하시킨다. 또한 앞서 얘기한 이용분야들은 실시간 환경에서 실행되는 시스템들로 정확한 검출 성능뿐만 아니라 빠른 실행시간도 요구 한다. 본 논문에서는 정확하고 빠른 눈동자 영역 검출을 위하여 기존에 가장 많이 사용하는 AdaBoost 눈 검출 알고리즘, 적응적 템플릿 정합+AdaBoost 알고리즘, CAMShift+AdBoost 알고리즘, rapid eye 검출 알고리즘에 대하여 분석하고, 조명변화와 콘택트 렌즈 및 안경 착용자와 미 착용자등 다양한 경우에 대해서 앞서 말한 알고리즘들을 적용하여 각 알고리즘 별로 정확도와 실행시간을 비교 분석하도록 한다.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.9-13
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• 2005

Computer security has become a critical issue with the rapid development of business and other transaction systems over the Internet. The application of artificial intelligence, machine learning and data mining techniques to intrusion detection systems has been increasing recently. But most research is focused on improving the classification performance of a classifier. Selecting important features from input data leads to simplification of the problem, and faster and more accurate detection rates. Thus selecting important features is an important issue in intrusion detection. Another issue in intrusion detection is that most of the intrusion detection systems are performed by off-line and it is not a suitable method for a real-time intrusion detection system. In this paper, we develop the real-time intrusion detection system, which combines an on-line feature extraction method with the Least Squares Support Vector Machine classifier. Applying the proposed system to KDD CUP 99 data, experimental results show that it has a remarkable feature extraction and classification performance compared to existing off-line intrusion detection systems.