• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.884-894
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• 2011

We proposed a new algorithm for detection of first(S1) and second heart sound(S2). Many researches for detecting primary components and those algorithms have good performance at normal heart sound, but the performance is degraded at abnormal heart sound which is contain murmurs generated by heart disease. Therefore we proposed the S1, S2 detection algorithm using three-order Shannon energy difference. Using S1, S2's character which has large energy difference than murmurs, it is reduced noise and detected S1, S2. According to simulation results, not only normal heart sound but also abnormal heart sound, the proposed algorithm has better performance than former study at abnormal heart sound.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.141-147
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• 2008

Several contaminated bacteria such as Lactobacillus brevis and Pediococcus damnosus in beer production cause beer spoilage by producing off flavours and turbidity. Detection of these organisms is complicated by the strict anaerobic conditions and lengthy incubation times required for their cultivation, consequently there is a need for more rapid detection methods. Recently, two contaminated strains were isolated from vessel of beer production and identified as Lactobacillus species by API kit identificaton as well as 16S-23S ITS sequencing analyses. Two isolated strains were named as Lactobacillus sp. HLA1 and Lactobacillus HLB2, respectively. A polymerase chain reaction (PCR) method was developed for the rapid and specific detection of Lactobacillus sp.. Two sets of primer pairs (HLA1-F/HLA1-R and HLB2-F/HLB2-R) were designed for the amplification of a 1576 base pair (bp) fragment of the HLA1 16S-23S rRNA gene and 1888 bp fragement of the HLB2 16S-23S rRNA. Amplified PCR products were highly specific to detect corresponding bacteria when other contaminated strains were used as PCR templates. However, detection of both strains were limited when $100{\mu}{\ell}$ of cultured samples were mixed with $100m{\ell}$ of beer sample in arbitrary manner. The sensitivity of the assay still needs to be improved for direct detection of the small amounts of bacteria present in beer.

• Journal of Electrochemical Science and Technology
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• v.14 no.3
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• pp.252-261
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• 2023

Glucose detection is particularly important for clinical diagnosis and personal prevention and control. Herein, the smartphone-based amperometric glucose sensors were constructed using the NiS/CuS nanorods (NRs) as sensing electrodes. The NiS/CuS NRs were prepared through a facile hydrothermal process accompanied by the subsequent vulcanization treatment. The morphological and structural properties of NiS/CuS NRs were characterized with SEM, EDS, XRD, and XPS. Electrochemical measurements including cyclic voltammetry, chronoamperometry, and electrochemical impedance spectroscopy display that NiS/CuS NRs can act as highly efficient electrocatalyst for glucose detection. The NiS/CuS NRs electrodes present a wide detection range of 1-8000 µM for glucose sensing with the sensitivity of 956.38 µA·mM^-1·cm^-2. The detection limit was 0.35 µM (S/N=3). When employed in smartphone-based glucose sensing device, they also display a high sensitivity of 738.09 µA·mM^-1·cm^-2 and low detection limit of 1.67 µM. Moreover, the smartphone-based glucose sensing device also presents favorable feasibility in determination of glucose in serum samples with the recoveries ranging between 99.5 and 105.8%. The results may provide a promising viewpoint to design other new portable glucose sensors.

• Korean Journal of Food Science and Technology
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• v.31 no.6
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• pp.1628-1634
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• 1999

The polymerase chain reaction (PCR) for the sensitive and specific detection of Listeria monocytogenes was employed by using LM 1 and LM 2 primers which were based on the listeriolysin O gene. The direct use of cell suspension as DNA template, without DNA extraction or lysis step, was suitable and specific enough to detect L. monocytogenes at the level of $10^2$ CFU or less per PCR for the pure culture and milk sample, however, the detection sensitivity became blunt for other food samples such as kimchi and chicken. The nested PCR, in which L-1 and L-2 (both designed from listeriolysin O gene) were employed as inner primers, was specific for detecting L. monocytogenes and enhanced the detection limit by 10 times. The PCR using LM 1 and LM 2 primers was very effective to detect L. monocytogenes from foods in terms of the specificity and time consumed, i. e. within $4{\sim}8\;hrs$ (nested PCR).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.3001-3008
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• 2013

To diagnose the cardiac valve abnormalities using analysis of phonocardiogram, first of all, accurate detection of S1, S2 components is needed for heart sound segmentation. In this paper, a new method that uses the third moment characteristics of an envelope of the PCG is proposed for accurate detection of S1 and S2 components of the heart sound with cardiac murmurs. The envelope of the PCG is obtained from the short-time energy profile, and its third moment profile with slope information is used for accurate time gating of the S1, S2 components. Experimental results have shown that the proposed method is superior to the conventional second moment method for detection of S1 and S2 regions from the heart sound signals with cardiac murmurs.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2126-2134
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• 2015

The present study suggests a localization method for the first (S₁) and the second (S₂) feature of heart sounds, based on an algorithm involving frequency filtering, energy detection, and interval regulation. Localization accuracy was evaluated by comparing the algorithm with the traditional Hilbert transform-based localization method. Results show that the sensitivity and the positive predictivity value of proposed method, respectively, were 97.27 % and 99.94 % in S₁ detection and 94.99 % and 100 % in S₂ detection.

• KNOM Review
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• v.23 no.1
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• pp.10-17
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• 2020

As the threat of Distributed Denial-of-Service attacks that exploit weakly secure IoT devices has spread, research on source-side Denial-of-Service attack detection is being activated to quickly detect the attack and the location of attacker. In addition, a collaborative source-side attack detection technique that shares detection results of source-side networks located at individual sites is also being activated to overcome regional limitations of source-side detection. In this paper, we evaluate the performance of a collaborative source-side DDoS attack detection using statistical weights. The statistical weight is calculated based on the detection rate and false positive rate corresponding to the time zone of the individual source-side network. By calculating weighted sum of the source-side DoS attack detection results from various sites, the proposed method determines whether a DDoS attack happens. As a result of the experiment based on actual DNS request to traffic, it was confirmed that the proposed technique reduces false positive rate 2% while maintaining a high attack detection rate.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2E
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• pp.72-78
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• 2009

Heart sound segmentation into its components, S1, systole, S2 and diastole is the first step of analysis and the most important part in the automatic diagnosis of heart sounds. Conventionally, the Shannon energy envelope peak detection method has been popularly used due to its superior performance in locating S1 and S2. Recently, the HMM has been shown to be quite suitable in modeling the heart sound signal and its use in segmenting the heart sound signal has been suggested with some success. In this paper, we compared the two methods for heart sound segmentation using a common database. Experimental tests carried out on the 4 different types of heart sound signals showed that the segmentation accuracy relative to the manual segmentation was 97.4% in the HMM based method which was larger than 91.5% in the peak detection method.

• Journal of Oral Medicine and Pain
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• v.20 no.2
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• pp.515-528
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• 1995

The human genomic deoxyribonucleic acid(DNA) was extracted from the pulp, dentin of 22 teeth by clelex, phenol methods. Samples of the tooth-derived DNA were amplified by polymerase chain reaction(PCR), electrophosed for sex determination by detection of X-Y homologus amelogenin gene and D1S80 locus detection The following results have been achieved. 1. Chelex and phenol method are effective to sex determination in the pulp and dentin 2. Chelex method is not suitable for detection of D1S80 locus. 3. Concentration and purity of DNA for teeth using chelex method is lower than using phenol method. From the above investigation, chelex method is simple, rapid for sex determination, but it is not suitable for detection of VNTRs.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.594-600
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• 2010

Many studies are DDoS in Internet network, but the study is the fact that is not enough in a voice network. Therefore, we designed the extended TRW algorithm that was a DDoS attack traffic detection algorithm for the voice network which used an IP data network to solve upper problems in this article and evaluated it. The algorithm that is proposed in this paper analyzes TRW algorithm to detect existing DDoS attack in Internet network and, design connection and end connection to apply to a voice network, define probability function to count this. For inspect the algorithm, Set a threshold and using NS-2 Simulator. We measured detection rate by an attack traffic type and detection time by attack speed. At the result of evaluation 4.3 seconds for detection when transmitted INVITE attack packets per 0.1 seconds and 89.6% performance because detected 13,453 packet with attack at 15,000 time when transmitted attack packet.