• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• Journal of Microbiology and Biotechnology
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• v.22 no.4
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• pp.530-534
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• 2012

A real-time PCR assay was developed and validated inhouse specifically for the detection of Clostridium perfringens (Cl. perfringens) in meats and vegetables by comparing with the culture method. The detection limit of the real-time PCR assay in phosphate-buffered saline was $10^2$ CFU/ml. When the two methods were compared in food samples inoculated with Cl. perfringens, the culture method detected 52 positives, whereas real-time PCR detected 51 positives out of 160 samples. The difference was without statistical significance (p>0.05). Real-time PCR assay is an option for quality assurance laboratories to perform standard diagnostic tests, considering its detection ability and time-saving efficiency.

• Journal of Microbiology and Biotechnology
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• v.20 no.10
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• pp.1463-1470
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• 2010

E. coli has long been widely used as a host system for the manufacture of recombinant proteins intended for human therapeutic use. When considering the impurities to be eliminated during the downstream process, residual host cell DNA is a major safety concern. The presence of residual E. coli host cell DNA in the final products is typically determined using a conventional slot blot hybridization assay or total DNA Threshold assay. However, both the former and latter methods are time consuming, expensive, and relatively insensitive. This study thus attempted to develop a more sensitive real-time PCR assay for the specific detection of residual E. coli DNA. This novel method was then compared with the slot blot hybridization assay and total DNA Threshold assay in order to determine its effectiveness and overall capabilities. The novel approach involved the selection of a specific primer pair for amplification of the E. coli 16S rRNA gene in an effort to improve sensitivity, whereas the E. coli host cell DNA quantification took place through the use of SYBR Green I. The detection limit of the real-time PCR assay, under these optimized conditions, was calculated to be 0.042 pg genomic DNA, which was much higher than those of both the slot blot hybridization assay and total DNA Threshold assay, where the detection limits were 2.42 and 3.73 pg genomic DNA, respectively. Hence, the real-time PCR assay can be said to be more reproducible, more accurate, and more precise than either the slot blot hybridization assay or total DNA Threshold assay. The real-time PCR assay may thus be a promising new tool for the quantitative detection and clearance validation of residual E. coli host cell DNA during the manufacturingprocess for recombinant therapeutics.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.324-332
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• 2010

The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.48-58
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• 1998

In this paper, we proposed a new algorithm using characteristics of th ereconstructed phase trajectory by topological mapping developed for a real-tiem detection of the QRS complexes of ECG signals. Using fill-factor algorithm and mutual information algorithm which are in genral used to find out the chaotic characteristics of sampled signals, we inferred the proper mapping parameter, time delay, in ECG signals and investigated QRS detection rates with varying time delay in QRS complex detection. And we compared experimental time dealy with the theoretical one. As a result, it shows that the experimental time dealy which is proper in topological mapping from ECG signals is 20ms and theoretical time delays of fill-factor algorithm and mutual information algorithm are 20.+-.0.76ms and 28.+-.3.51ms, respectively. From these results, we could easily infer that the fill-factor algorithm in topological mapping from one-dimensional sampled ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper time delay. Also with the proposed algorithm which is very simple and robust to low-frequency noise as like baseline wandering, we could detect QRS complex in real-time by simplifying preprocessing stages. For the evaluation, we implemented the proposed algorithm in C-language and applied the MIT/BIH arrhythmia database of 48 patients. The proposed algorithm provides a good performance, a 99.58% detection rate.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.38-45
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• 2017

Attacking of computer and network is increasing as information processing technology heavily depends on computer and network. To prevent the attack of system and network, host and network based intrusion detection system has developed. But previous rule based system has a lot of difficulties. For this reason demand for developing a intrusion detection system which detects and cope with the attack of system and network resource in real time. In this paper we develop a real time intrusion detection system which is combination of APEX and LS-SVM classifier. Proposed system is for nonlinear data and guarantees convergence. While real time processing system has its advantages, such as memory efficiency and allowing a new training data, it also has its disadvantages of inaccuracy compared to batch way. Therefore proposed real time intrusion detection system shows similar performance in accuracy compared to batch way intrusion detection system, it can be deployed on a commercial scale.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.1
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• pp.23-28
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• 2012

In this paper, we proposed and developed a fast and efficient real time face detection and recognition which can be run on embedded system instead of high performance desktop. In the face detection process, we detect a face by finding eye part which is one of the most salient facial features after applying various image processing methods, then in the face recognition, we finally recognize the face by comparing the current face with the prepared face database using a template matching algorithm. Also we optimized the algorithm in our system to be successfully used in the embedded system, and performed the face detection and recognition experiments on the embedded board to verify the performance. The developed method can be applied to automatic door, mobile computing environment and various robot.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.974-977
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• 2003

The GPS/INS integration system navigation can provide improved navigation performance and has been widely used as a main navigation system for military and commercial vehicles. When two navigation systems are tightly coupled and the structure is complicated, a fault in either the GPS or the INS can lead to a disastrous failure of the whole integration system. This paper proposes a real-time fault detection method for an AGPS/INS integration system. The proposed fault detection method comprises a BIT and a fault detection algorithm based on chi-square test. It is implemented by real-time software modules to apply the AGPS/INS integration system and van test is carried out to evaluate its performance.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• Journal of Microbiology
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• v.41 no.4
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• pp.320-326
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• 2003

In order to identify Vibrio vulnificus in the Yellow Sea near Gunsan, Korea during the early and late summers, the efficiency of the real-time quantitative TaqMan PCR was compared to the efficiency of the conventional PCR and Biolog identification system^TM. Primers and a probe were designed from the hemolysin/cytolysin gene sequence of V. vulnificus strains. The number of positive detections by real-time quantitative TaqMan PCR, conventional PCR, and the Biolog identification system from seawater were 53 (36.8%), 36 (25%), and 10 strains (6.9%), respectively, among 144 samples collected from Yellow Sea near Gunsan, Korea. Thus, the detection method of the real-time quantitative TaqMan PCR assay was more effective in terms of accuracy than that of the conventional PCR and Biolog system. Therefore, our results showed that the real-time TaqMan probe and the primer set developed in this study can be applied successfully as a rapid screening tool for the detection of V. vulnificus.