• Journal of Microbiology and Biotechnology
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• v.24 no.3
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• pp.297-312
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• 2014

Food safety is increasingly becoming an important public health issue, as foodborne diseases present a widespread and growing public health problem in both developed and developing countries. The rapid and precise monitoring and detection of foodborne pathogens are some of the most effective ways to control and prevent human foodborne infections. Traditional microbiological detection and identification methods for foodborne pathogens are well known to be time consuming and laborious as they are increasingly being perceived as insufficient to meet the demands of rapid food testing. Recently, various kinds of rapid detection, identification, and monitoring methods have been developed for foodborne pathogens, including nucleic-acid-based methods, immunological methods, and biosensor-based methods, etc. This article reviews the principles, characteristics, and applications of recent rapid detection methods for foodborne pathogens.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.843-848
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• 2008

Most of face detection technique uses information from the face of the movement. The traditional face detection method is to use difference picture method ate used to detect movement. However, most do not consider this mathematical approach using real-time or real-time implementation of the algorithm is complicated, not easy. This paper, the first to detect real-time facial image is converted YCbCr and RGB video input. Next, you convert the difference between video images of two adjacent to obtain and then to conduct Glassfire Labeling. Labeling value compared to the threshold behavior Area recognizes and converts video extracts. Actions to convert video to conduct face detection, and detection of facial characteristics required for the extraction and use of AdaBoost algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3258-3273
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• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.69-73
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• 2023

Commercially used organic scintillation materials (1,4 di[2-(5phenyloxazolyl)] benzene) have low solubility in solvents and a wide emission energy range, which causes a decrease in detection efficiency. In this study, an organic liquid scintillator with improved detection efficiency was developed using 7-Diethylamino-4-methylcoumarin material to compensate for the disadvantages of existing organic scintillation detectors. And to evaluate the applicability of radiation measurement, the performance of a commercial plastic detector was compared. As a result of analyzing the ⁶⁰Co detection characteristics by applying 7-Diethylamino-4-methylcoumarin as an alternative to 1,4 di[2-(5phenyloxazolyl)] benzene, the detection efficiency was improved around 2% compared with commercial scintillator when the 7-Diethylamino-4-methylcoumarin content was 0.04 wt%. Based on the results of this study, the possibility of improving detection efficiency through scintillator material modification was confirmed. In addition, since it is possible to discriminate nuclide through the spectrum correction algorithm, it will be possible to inspect and classify various decommissioning wastes generated during the decommissioning process.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1291-1295
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• 2004

This paper proposed a new approach for endpoint detection of isolated speech, which proves to significantly improve the endpoint detection performance. The proposed algorithm relies on the root mean square energy (rms energy), zero crossing rate and spectral characteristics of the speech signal where the Euclidean distance measure is adopted using cepstral coefficients to accurately detect the endpoint of isolated speech. The algorithm offers better performance than traditional energy-based algorithm. The vocabulary for the experiment includes English digit from one to nine. These experimental results were conducted by 360 utterances from a male speaker. Experimental results show that the accuracy of the algorithm is quite acceptable. Moreover, the computation overload of this algorithm is low since the cepstral coefficients parameters will be used in feature extraction later of speech recognition procedure.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.767-775
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• 2008

Methods used for exploring marine resources and spaces include positioning a probe under water and then recalling it after a specified time. Hydro-acoustic Releasers are commonly used for positioning and retrieving of such exploration equipment. The most important factor in this kind of system is the reliability for recalling the instruments. The frequently used ultrasonic signal detection method can detect ultrasonic signals using a fixed comparator, but because of increased rates of errors due to outside interferences, information is repetitively acquired. This study presents an effective ultrasonic signal detection algorithm using the characteristics of a resonance and adaptive comparator Combined with the FSK+ASK modulator. As a result, approximately 8.8% of ultrasonic wave communication errors caused by background noise and transmission losses were reduced for effectively detecting ultrasonic waves. Furthermore, the resonance circuit's quality factor was enhanced (Q = 120 to 160). As such, the bias voltage of the transistor (Vb= 3.3 to 6.8V) was increased thereby enhancing the frequency's selectivity.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.421-424
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• 2005

X-ray is currently most effective method in detecting small malignant breast tumors but has the several problems due to suppressing breast, ionizing radiation and not detecting small cancer. In this paper, a new method is proposed by using dielectric characteristics of pathological tissues and time delay of backscattered response. We have developed a detection algorithm and verified it by numerical simulation and measurement for a prototype system. For a prototype system, we have fabricated experimental model(artificial breast with a cancer) and UWB(ultra-wideband) antenna. The results of the measurement simulation show an excellent detection capability of a cancer tissue. It is found that a good UWB antenna is a key element of such detection system. Further study is ongoing to develop a commercial system.

• ETRI Journal
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• v.30 no.2
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• pp.335-337
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• 2008

An eye detection method for facial images using Zernike moments with a support vector machine (SVM) is proposed. Eye/non-eye patterns are represented in terms of the magnitude of Zernike moments and then classified by the SVM. Due to the rotation-invariant characteristics of the magnitude of Zernike moments, the method is robust against rotation, which is demonstrated using rotated images from the ORL database. Experiments with TV drama videos showed that the proposed method achieved a 94.6% detection rate, which is a higher performance level than that achievable by the method that uses gray values with an SVM.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.408-411
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• 2008

In this paper, a new DC ground fault detection system is proposed, which is suitable for photovoltaic power generation systems. The proposed ground fault systems is superposition of divide resistance and detection circuit. The proposed system has the characteristics of a simplified structure, reduced cost and volume compared with those of the conventional ground fault system for DC source. The operation principle of the proposed systems is described and verified by simulation result.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.6
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• pp.537-545
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• 2002

This paper presents a new method of detecting rotor position in Toroidal Switched Reluctance Motor(TSRM). In this paper, low cost and robust characteristics of rotor position detection method are focused in order to compensate for disadvantage of existing sensors. Search coils wound around stator poles are used for detection of rotor position in TSRM. Rotor position detection is achieved through electromotive force patterns induced by time-varying flux linkage in the search coils and then adequate phase is excited for drive. The validity of the method is verified by experimental results.