• 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.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2003.11a
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• pp.145-156
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• 2003

This paper for real time object tracking in this treatise detect histogram analysis that is accumulation value of binary conversion density and edge information and body that move by real time use of difference Image techniques and proposed method to object tracking. Firstly, we extract edge that can reduce quantity of data keeping information about form of input image in object detection. Object is extracted by performing difference image and binarization in edge image. Area of detected object is determined by threshold value that divide sum of horizontal accumulation value about binary conversion density by value that add horizontalityㆍverticality maximum accumulation value. Object is tracked by comparing similarity with object that is detected in previous frame and present frame. As experiment result, proposed algorithm could improve the object detection speed, and could track object by real time and could track local movement.

• Microbiology and Biotechnology Letters
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• v.43 no.3
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• pp.267-274
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• 2015

Biopharmaceuticals and the cell substrates used for their manufacture are currently tested for porcine adventitious viruses due to the widespread use of porcine trypsin in cell culture. Porcine transmissible gastroenteritis virus (PTGV) is one of the major adventitious porcine viruses causing contaminated during the manufacture of biopharmaceuticals. Therefore, rapid and sensitive detection of PTGV is essential in ensuring the safety of biopharmaceuticals. A TaqMan probe real-time RT-PCR method was developed for the quantitative detection of PTGV contamination in cell substrates, raw materials, manufacturing processes, and final products, as well as PTGV clearance validation. Specific primers for the amplification of PTGV RNA were selected, and PTGV RNA was quantified by use of a specific TaqMan probe. Specificity, limit of detection (LOD), and robustness of the method was validated according to international guidelines on the validation of nucleic acid amplification tests. The sensitivity of the assay was calculated to be 1.10 × 10⁰ TCID₅₀/ml. The real-time RT-PCR method was validated to be reproducible, very specific to PTGV, and robust. The established real-time RT-PCR assay was successfully applied to the validation of Chinese Hamster Ovary (CHO)-K1 cells artificially infected with PTGV.

• Proceedings of the KOR-KST Conference
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• 1995.12a
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• pp.77-107
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• 1995

This paper documents the development of a fuzzy logic based incident detection model for urban diamond interchanges. Research in incident detection for intersections and arterials is at a very initial stage. Existing algorithms are still far from being robust in dealing with the difficulties related with data availability and the multi-dimensional nature of the incident detection problem. The purpose of this study is to develop a new real-time incident detection model for urban diamond interchanges. The development of the algorithm is based on fuzzy logic. The incident detection model developed through this research is capable of detecting lane¬blocking incidents when their effects are manifested by certain patterns of deterioration in traffic conditions and, thereby, adjustments in signal control strategies are required. The model overcomes the boundary condition problem inherent in conventional threshold-based concepts. The model captures system-wide incident effects utilizing multiple measures for more accurate and reliable detection, and serves as a component module of a real-time traffic adaptive diamond interchange control system. The model is designed to be readily scalable and expandable for larger systems of arterial streets. The prototype incident detection model was applied to an actual diamond interchange to investigate its performance. A simulation study was performed to evaluate the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy logic based approach to incident detection is promising.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1345-1360
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• 2016

In this paper, we propose a new real-time human detection under omni-directional cameras for visual surveillance purpose, based on CNN with unified detection and AGMM. Compared to CNN-based state-of-the-art object detection methods. YOLO model-based object detection method boasts of very fast object detection, but with less accuracy. The proposed method adapts the unified detecting CNN of YOLO model so as to be intensified by the additional foreground contextual information obtained from pre-stage AGMM. Increased computational time incurred by additional AGMM processing is compensated by speed-up gain obtained from utilizing 2-D input data consisting of grey-level image data and foreground context information instead of 3-D color input data. Through various experiments, it is shown that the proposed method performs better with respect to accuracy and more robust to environment changes than YOLO model-based human detection method, but with the similar processing speeds to that of YOLO model-based one. Thus, it can be successfully employed for embedded surveillance application.

• Journal of Microbiology and Biotechnology
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• v.19 no.11
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• pp.1464-1469
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• 2009

To achieve more accurate and rapid detection of macrolide-lincosamide-streptogramin B resistance genes, erm(A), erm(B), and erm(C), we developed a TaqMan probe-based real-time PCR (Q-PCR) method and compared it with conventional PCR (C-PCR), which is the most widely using erm gene identification method. The detection limit of Q-PCR was 5 fg of genomic DNA or 5-8 CFU of bacterial cells of Staphylococcus aureus. The utilization of Q-PCR might shorten the time to erm detection from 3-4 h to about 50 min. These data indicated that Q-PCR assay appears to be not only highly sensitive and specific, but also the most rapid diagnostic method. Therefore, the appropriate application of the Q-PCR assay will permit rapid and accurate identification of erm genes from clinical and other samples.

• Journal of the Korea Safety Management & Science
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• v.23 no.1
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• pp.9-15
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• 2021

The leading source of occupational fatalities is a portable ladder in Korea because it is widely used in industry as work platform. In order to reduce victims, it is necessary to establish preventive measures for the accidents caused by portable ladder. Therefore, this study statistically analyzed injury death by portable ladder for recent 10 years to investigate the accident characteristics. Next, to monitor wearing of safety helmet in real-time while working on a portable ladder, this study developed an object detection model based on the You Only Look Once(YOLO) architecture, which can accurately detect objects within a reasonable time. The model was trained on 6,023 images with/without ladders and safety helmets. The performance of the proposed detection model was 0.795 for F1 score and 0.843 for mean average precision. In addition, the proposed model processed at least 25 frames per second which make the model suitable for real-time application.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.745-750
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• 2015

LiDAR(Light Detection and Ranging) technology provides realistic 3-dimension image information, and it has been widely utilized in various fields. However, the utilization of this technology in the military domain requires prompt responses to dynamically changing tactical environment and is therefore limited since LiDAR technology requires complex processing in order for extensive amounts of LiDAR data to be utilized. In this paper, we introduce an Unmanned Aircraft Platform Based Real-time LiDAR Data Processing Architecture that can provide real-time detection information by parallel processing and off-loading between the UAV processing and high-performance data processing areas. We also conducted experiments to verify the feasibility of our proposed architecture. Processing with ARM cluster similar to the UAV platform processing area results in similar or better performance when compared to the current method. We determined that our proposed architecture can be utilized in the military domain for tactical and combat purposes such as unmanned monitoring system.

• The Korean Journal of Malacology
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• v.27 no.4
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• pp.387-393
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• 2011

The objective of this study was to develop a real-time PCR method for the rapid detection and quantification of the protozoan pathogen Perkinsus olseni using a TaqMan probe. For the standard, genomic DNA was extracted from $10^5$ in vitro-cultured P. olseni trophozoites, and then 10-fold serial dilutions to the level of a single cell were prepared. To test the reliability of the technique, triplicates of genomic DNA were extracted from $5{\times}10^4$ cells and 10-fold serial dilutions to the level of 5 cells were prepared. The standards and samples were analyzed in duplicate using an $Exicycler^{TM}$ 96 real-time quantitative thermal block. For quantification, the threshold cycle ($C_T$) values of samples were compared with those obtained from standard dilutions. There was a strong linear relationship between the $C_T$ value and the log concentration of cells in the standard ($r^2$ = 0.996). Detection of DNA at a concentration as low as the equivalent of a single cell showed that the assay was sensitive enough to detect a single cell of P. olseni. The estimated number of P. olseni cells was similar to the original cell concentrations, indicating the reliability of P. olseni quantification by real-time PCR. Accordingly, the designed primers and probe may be used for the rapid detection and quantification of P. olseni from clam tissue, environmental water, and sediment samples.