• Journal of Microbiology and Biotechnology
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• v.33 no.8
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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.

• Proceedings of the KSR Conference
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• 2011.10a
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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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• 2008.02a
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• pp.205-209
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• 2008

Recently, for development of hardware systems, it has been comercially developed for lane detection system of assistive funtion to drivers. There are so many driving systems that is capable of detecting lane for ideal environment like quite visible lane and sweep curve just like highway, but these kinds of system are hard to apply for self driving system because it is difficult to detect lane in dynamic environment, which have rapid curve or only one sided lane For this paper, we proposed intelligent driving system that is able to detect the lane in case of rapid curve by labeling, or one sided lane by lane prediction. based on experimental results, we prove our lane detection system is able to detect lane not only in ideal environment, but also environment which have rapid curve or one sided lane.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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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.

• Korean Journal of Veterinary Research
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• v.47 no.4
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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.

• Journal of Applied Reliability
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• v.14 no.1
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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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• v.31 no.2 s.115
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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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.

• Journal of Korea Multimedia Society
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• v.15 no.6
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• pp.722-730
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• 2012

Recently, eye image information has been widely used for iris recognition or gaze detection in biometrics or human computer interaction. According as long distance camera-based system is increasing for user's convenience, the noises such as eyebrow, forehead and skin areas which can degrade the accuracy of eye detection are included in the captured image. And fast processing speed is also required in this system in addition to the high accuracy of eye detection. So, we compared the most widely used algorithms for eye detection such as AdaBoost eye detection algorithm, adaptive template matching+AdaBoost algorithm, CAMShift+AdaBoost algorithm and rapid eye detection method. And these methods were compared with images including light changes, naive eye and the cases wearing contact lens or eyeglasses in terms of accuracy and processing speed.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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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.