• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.1
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• pp.71-84
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• 1999

The most of intrusion detection methods do not detect intrusion when it happens. To solve the problem, we are studying a real-time intrusion detection. Because a previous intrusion detection system(IDS) is running on the host level, it difficult to port and to extend to other system on the network level that distributed environment. Also IDS provides the confidentiality of messages when it sends each other. This paper proposes a model of real-time intrusion detection using agents. It applies to distributed environment using an extensibility and communication mechanism among agents, supports a portability, an extensibility and a confidentiality of IDS.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.39-46
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• 2009

Many lip region detection methods have been developed in PC environment. But the existing methods are difficult to run on real-time in resource limited mobile devices. To solve the problem, this paper proposes a real-time lip region detection method for lipreading in Mobile device. It detects face region by using adaptive face color information. After that, it detects lip region by using geometrical relation between eyes and lips. The proposed method is implemented in a smart phone with Intel PXA 270 embedded processor and 386MB memory. Experimental results show that the proposed method runs at the speed 9.5 frame/see and the correct detection rate was 98.8% for 574 images.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.668-670
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• 1999

We have developed a automatic surface inspection system for cold Rolled strips in steel making process for several years. We have experienced the various kinds of surface inspection systems, including linear CCD camera type and the laser type inspection system which was installed in cold rolled strips production lines. But, we did not satisfied with these inspection systems owing to insufficient detection and classification rate, real time processing performance and limited line speed of real production lines. In order to increase detection and computing power, we have used the Dark Field illumination with Infra_Red LED, Bright Field illumination with Xenon Lamp, Parallel Computing Processor with Area typed CCD camera and full software based image processing technique for the ease up_grading and maintenance. In this paper, we introduced the automatic inspection system and real time image processing technique using the Object Detection, Defect Detection, Classification algorithms. As a result of experiment, under the situation of the high speed processed line(max 1000 meter per minute) defect detection is above 90% for all occurred defects in real line, defect name classification rate is about 80% for most frequently occurred 8 defect, and defect grade classification rate is 84% for name classified defect.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.695-698
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• 2000

Round-cornering machines are mainly used for cornering of stiffners for ship buildings. In the present time they have been operated manually by operators. so they are need to be operated automatically without regard to any shapes of stiffners. We developed the automatic round cornering system which consists of CCd Camera, PC and laser diode to detect automatically the edge of stiffners to be processed

• Proceedings of the Microbiological Society of Korea Conference
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• 2003.05a
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• pp.118-121
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• 2003

A method for detection and quantification of aceticlastic methanogens using a real-time PCR with a TaqMan probe was developed. Two sets of primers and probes targeting the family Methanosarcinaceae and Methanosaetaceae were designed by using the Ribosormal Database Project (RDP) II, and softwares for phylogenetic probe design and sequence analysis. Target-group specificity of each set of primers and probe was verified by testing DNAs isolated from pure cultures of 28 archaeal strains purchased from DSMZ. Cell numbers in the 28 archaeal cultures and in the samples from anaerobic processes were quantified using a real-time PCR with the sets of primers and probe. In conclusion, the real-time PCR assay was very specific for the corresponding target methanogenic family and was proved to be a powerful method for quantification of aceticlastic methanogens in anaerobic processes.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.11
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• pp.804-815
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• 1988

Real-time image processing algorithms to detect position and orientation of rectangular type electronic components are developed. The position detection algorithm is implemented with the use of projection method which is insensitive to noise. Also dynamic thresholding method of projection is employed in order to distinguish between the boundary of a component and any marking on the component. The orientation is determined by Hough transform of boundary candidates of a component, which is obtained a priori by a simple edge detection method. For real-time processing of both position and orientation for a component which is not aligned well, parallel processing method of image data is proposed and tested in real-time.

• Journal of Korean society of Dental Hygiene
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• v.15 no.6
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• pp.1063-1071
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• 2015

Objectives: The purpose of the study is to investigate the quantitative detection of periodontal pathogens before and after scaling by real-time polymerase chain reaction. Methods: Participants were voluntarily recruited at D university, and saliva samples were extracted before and after scaling. Multiple real-time polymerase chain reactions were used to analyze characteristics and the amount of nine kinds of periodontal pathogens; Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Prevotella intermedia, Fusobacterium nucleatum, Parvimonas micra, Campylobacter rectus, and Eikenella corrodens. Results: After scaling, most periodontal pathogens except Eikenella corrodens were significantly decreased in all subjects(p<0.05). In addition, the percentage of microorganisms associated with disease, the microorganism risk index of periodontitis and the prevalence of red complex, orange complex, and Aggregatibacter actinomycetemcomitans was also significantly reduced after scaling(p<0.05). Conclusions: Scaling decreased in the amount of major periodontal pathogens and periodontitis prevalence rate.

• Journal of the Korean Geophysical Society
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• v.8 no.1
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• pp.7-14
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• 2005

Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG) sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.889-893
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• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.