• Journal of Microbiology and Biotechnology
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• v.27 no.4
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• pp.816-824
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• 2017

Human noroviruses are widespread and contagious viruses causing nonbacterial gastroenteritis. Real-time reverse transcription quantitative PCR (real-time RT-qPCR) is currently the gold standard for the sensitive and accurate detection of these pathogens and serves as a critical tool in outbreak prevention and control. Different surveillance teams, however, may use different assays, and variability in specimen conditions may lead to disagreement in results. Furthermore, the norovirus genome is highly variable and continuously evolving. These issues necessitate the re-examination of the real-time RT-qPCR's robustness in the context of accurate detection as well as the investigation of practical strategies to enhance assay performance. Four widely referenced real-time RT-qPCR assays (Assays A-D) were simultaneously performed to evaluate characteristics such as PCR efficiency, detection limit, and sensitivity and specificity with RT-PCR, and to assess the most accurate method for detecting norovirus genogroups I and II. Overall, Assay D was evaluated to be the most precise and accurate assay in this study. A ZEN internal quencher, which decreases nonspecific fluorescence during the PCR, was added to Assay D's probe, which further improved the assay performance. This study compared several detection assays for noroviruses, and an improvement strategy based on such comparisons provided useful characterizations of a highly optimized real-time RT-qPCR assay for norovirus detection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.2D
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• pp.129-136
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• 2012

In the US, Japan and Germany the Aerial-Based Vehicle Detection System, which collects real-time traffic data using the Unmanned Aerial Vehicle (UAV), helicopters or fixed-wing aircraft has been developed for the last several years. Therefore, this study was done to find out whether the Aerial-Based Vehicle Detection System could be used for real-time traffic data collection. For this purpose the study was divided into two parts. In the first part the possibility of retrieving real-time traffic data such as travel speed from the aerial photographic image using the image processing technique was examined. In the second part the quality of the retrieved real-time traffic data was examined to find out whether the data are good enough to be used as traffic information source. Based on the results of examinations we could conclude that it would not be easy for the Aerial- Based Vehicle Detection System to replace the present Vehicle Detection System due to technological difficulties and high cost. However, the system could be effectively used to make the emergency traffic management plan in case of incidents such as abrupt heavy rain, heavy snow, multiple pile-up, etc.

• Journal of Food Hygiene and Safety
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• v.26 no.2
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• pp.114-119
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• 2011

In this study, two duplex real-time PCR approach with melting curve analysis is presented for the detection of Escherichia coli O157:H7, Listeria monocytogenes, Salmonella spp. and Staphylococcus aureus, which are important food-borne bacterial pathogens usually present in fresh and/or minimally processed vegetables. Reaction conditions were adjusted for the simultaneous amplification and detection of specific fragments in the ${\beta}$-glucuronidase (uidA, E. coli), thermonuclease (nuc, S. aureus), hemolycin (hly, L. monocytogenes) and tetrathionate reductase (ttr, Salmonella spp.) genes. Melting curve analysis using a SYBR Green I real-time PCR approach showed characteristic $T_m$ values demonstrating the specific and efficient amplification of the four pathogens; $80.6{\pm}0.9^{\circ}C$, $86.9{\pm}0.5^{\circ}C$, $80.4{\pm}0.6^{\circ}C$ and $88.1{\pm}0.11^{\circ}C$ for S. aureus, E. coli O157:H7, L. monocytogenes and Salmonella spp., respectively. For all the pathogens, the two duplex, real-time PCR was equally sensitive to uniplex real-time PCR, using same amounts of purified DNA, and allowed detection of 10 genome equivalents. When our established duplex real-time PCR assay was applied to artificially inoculated fresh lettuce, the detection limit was $10^3$ CFU/g for each of these pathogens without enrichment. The results from this study showed that the developed duplex real-time PCR with melting curve analysis is promising as a rapid and cost-effective test method for improving food safety.

• ETRI Journal
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• v.37 no.2
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• pp.251-261
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• 2015

We present a novel method for real-time automatic license plate detection in high-resolution videos. Although there have been extensive studies of license plate detection since the 1970s, the suggested approaches resulting from such studies have difficulties in processing high-resolution imagery in real-time. Herein, we propose a novel cascade structure, the fastest classifier available, by rejecting false positives most efficiently. Furthermore, we train the classifier using the core patterns of various types of license plates, improving both the computation load and the accuracy of license plate detection. To show its superiority, our approach is compared with other state-of-the-art approaches. In addition, we collected 20,000 images including license plates from real traffic scenes for comprehensive experiments. The results show that our proposed approach significantly reduces the computational load in comparison to the other state-of-the-art approaches, with comparable performance accuracy.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.113-120
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• 2020

Recently, the license plate OCR system has been commercialized in a variety of fields and preferred utilizing low-cost embedded systems using only cameras. This system has a high recognition rate of about 98% or more for the environments such as parking lots where non-vehicle is restricted; however, the environments where non-vehicle objects are not restricted, the recognition rate is about 50% to 70%. This low performance is due to the changes in the environment by non-vehicle objects in real-time situations that occur anomaly data which is similar to the license plates. In this paper, we implement the appropriate anomaly detection based on semi-supervised learning for the license plate OCR system in the real-time environment where the appearance of non-vehicle objects is not restricted. In the experiment, we compare systems which anomaly detection is not implemented in the preceding research with the proposed system in this paper. As a result, the systems which anomaly detection is not implemented had a recognition rate of 77%; however, the systems with the semi-supervised learning based on anomaly detection had 88% of recognition rate. Using the techniques of anomaly detection based on the semi-supervised learning was effective in detecting anomaly data and it was helpful to improve the recognition rate of real-time situations.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.146-149
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• 2009

Face detection and recognition in real-time video constitutes one of the recent topics in the field of computer vision. In this paper, we propose face detection and tracking algorithm using the skin color and haar-like feature in real-time video sequence. The proposed algorithm further includes color space to enhance the result using haar-like feature and skin color. Experiment results reveal the real-time video processing speed and improvement in the rate of tracking.

• Journal of Electrical Engineering and Technology
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• v.7 no.3
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• pp.429-435
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• 2012

In this study, a real-time architecture for the detection of clock jumps in the GPS clock behavior is proposed. GPS satellite atomic clocks have characteristics of a second order polynomial in the long term showing sudden jumps occasionally. As satellite clock anomalies influence on GPS measurements which could deliver wrong position information to users as a result, it is required to develop a real time technique for the detection of the clock anomalies especially on the real-time GPS applications such as aviation. The proposed strategy is based on Teager Energy operator, which can be immediately detect any changes in the satellite clock bias estimated from GPS carrier phase measurements. The verification results under numerous cases in the presence of clock jumps are demonstrated.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.46-53
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• 2015

This paper suggests a method of real time confidence interval estimation to detect abnormal states of sensor data. For real time confidence interval estimation, the mean square errors of the exponential smoothing method and moving average method, two of the time series analysis method, were compared, and the moving average method with less errors was applied. When the sensor data passes the bounds of the confidence interval estimation, the administrator is notified through alarms. As the suggested method is for real time anomaly detection in a ship, an Android terminal was adopted for better communication between the wireless sensor network and users. For safe navigation, an administrator can make decisions promptly and accurately upon emergency situation in a ship by referring to the anomaly detection information through real time confidence interval estimation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.10
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• pp.1522-1527
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• 2010

This study was conducted to find out the minimal time needed for detection of Salmonella spp. which exist at very low concentration in foods by using real-time PCR. The sal-F and sal-R sequences were used as primers and sal-P was used as a probe. The detection limit of Salmonella spp. was $3.77{\times}10^2\;cfu/mL$ in buffered peptone water (BPW). Microbial growth was monitored after artificially inoculated Salmonella spp. into BPW. The obtained growth curve was well fitted with the equation, y＝$0.0127x^2$+0.5927x-0.4317 ($R^2$=0.99), if assuming that 1 cell exists in 25 g sample (0.04 cfu/mL). The microbial concentration will be reduced to 10 fold by adding BPW during sample treatment, so actual initial concentration at the starting point of enrichment is 0.004 cfu/mL. At this condition, real-time PCR detection would be possible only when microbial concentration increase occurs to exceed the detection limit (377 cfu/mL). The time needed for microbial increase was calculated from the growth curve equation as 7 hours and 20 minutes. Therefore the total time required for detection was less than 10 hours including the PCR operating time.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1880-1884
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• 2004

The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.