• Mycobiology
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• v.41 no.2
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• pp.86-93
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• 2013

Sequence characterized amplified region (SCAR) markers are one of the most effective and accurate tools for microbial identification. In this study, we applied SCAR markers for the rapid and accurate detection of Phytophthora katsurae, the casual agent of chestnut ink disease in Korea. In this study, we developed seven SCAR markers specific to P. katsurae using random amplified polymorphic DNA (RAPD), and assessed the potential of the SCAR markers to serve as tools for identifying P. katsurae. Seven primer pairs (SOPC 1F/SOPC 1R, SOPC 1-1F/SOPC 1-1R, SOPC 3F/SOPC 3R, SOPC 4F/SOPC 4R, SOPC 4F/SOPC 4-1R, SOPD 9F/SOPD 9R, and SOPD 10F/SOPD 10R) from a sequence derived from RAPD fragments were designed for the analysis of the SCAR markers. To evaluate the specificity and sensitivity of the SCAR markers, the genomic DNA of P. katsurae was serially diluted 10-fold to final concentrations from 1 mg/mL to 1 pg/mL. The limit of detection using the SCAR markers ranged from $100{\mu}g/mL$ to 100 ng/mL. To identify the limit for detecting P. katsurae zoospores, each suspension of zoospores was serially diluted 10-fold to final concentrations from $10{\times}10^5$ to $10{\times}10^1$ zoospores/mL, and then extracted. The limit of detection by SCAR markers was approximately $10{\times}10^1$ zoospores/mL. PCR detection with SCAR markers was specific for P. katsurae, and did not produce any P. katsurae-specific PCR amplicons from 16 other Phytophthora species used as controls. This study shows that SCAR markers are a useful tool for the rapid and effective detection of P. katsurae.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.17-24
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• 2009

This paper suggests the background image and the algorism of detecting an accident at crossroads by using the sequence of traffic light at crossroads, which is installed within the crossroads, in order to detect an accident within crossroads. A method of using the existing image contains a problem that the accident-detection ratio gets lower in a situation that noise occurs loudly given using new accident model, the confused situation, or sound source. This study used the accident detection by developing a filter of using the property of histogram in the sequence of traffic light at crossroads and the background image, in order to reduce misjudgment of an accident caused by external shadow, vehicle stoppage, vehicle headlight, and externally environmental influence. As a result of experimenting by acquiring 15 actual accident images in order to examine the performance of the suggested algorism, the accident was detected in all the 15 videos. Even as for a new accident model, the accident within crossroads could be detected.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.41-47
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• 2001

In this paper, I propose a detection algorithm that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. The proposed algorithm consists of four processes: generation of the difference image between the input image and the reference image. multilevel quantization of the difference image, and multistage merging in the quantized image, detection of the moving object using a back propagation in a neural network. The test results show that the proposed algorithm can detect moving objects very effectively in noisy environment.

• Bulletin of the Korean Chemical Society
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• v.26 no.3
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• pp.379-383
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• 2005

This research aims to develop DNA chip array without an indicator. We fabricated microelectrode array by photolithography technology. Several DNA probes were immobilized on an electrode. Then, indicator-free target DNA was hybridized by an electrical force and measured electrochemically. Cyclic-voltammograms (CVs) showed a difference between DNA probe and mismatched DNA in an anodic peak. Immobilization of probe DNA and hybridization of target DNA could be confirmed by fluorescent. This indicator-free DNA chip microarray resulted in the sequence-specific detection of the target DNA quantitatively ranging from $10^{-18}\;M\;to\;10^{-5}$ M in the buffer solution. This indicator-free DNA chip resulted in a sequence-specific detection of the target DNA.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.83-86
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• 2007

In the blind Maximum-likelihood (ML) detection for Orthogonal Space-Time Block Codes (OSTBC), the problem of ambiguity in determining the symbols has been a great concern. A solution to this problem is to apply semi-blind ML detection, i.e., the blind ML decoding with pilot symbols or training sequence. In order to increase the performance, the number of pilot symbols or length of training sequence should be increased. Unfortunately, this leads to a significant decrease in system spectral efficiency. This work presents an approach to resolve the aforementioned issue by introducing a new method for constructing transmitted information symbol. Thus, by transmitting information symbols drawn from different modulation constellation, the ambiguity can be easily eliminated in blind detection. Also, computer simulations are implemented to verify the performance of the proposed approach.

• Journal of Dairy Science and Biotechnology
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• v.38 no.4
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• pp.169-188
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• 2020

Salmonella spp. is the most common cause of gastrointestinal food poisoning worldwide, and human salmonellosis is mostly caused by the consumption of contaminated food. Therefore, the development of rapid detection methods for Salmoenlla spp. and rapid identification of the source of infection by subtyping are important for the surveillance and monitoring of food-borne salmonellosis. Therefore, this review introduces (1) History and nomenclature of Salmoenlla spp., (2) Epidemiology of Salmoenlla spp., (3) Detection methods for Salmoenlla spp. - conventional culture method, genetic detection method, molecular detection methods, and aptamer, and (4) Subtyping methods for Salmoenlla spp. - pulsed-field gel electrophoresis and repetitive sequence-based polymerase chain reaction (PCR).

• Journal of Korean Society of Forest Science
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• v.96 no.4
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• pp.425-431
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• 2007

To investigate genetic diversity and PCR detection of Rhizina undulata, PCR detection and sequence analysis of rDNA ITS region of R. undulata in soil were analyzed and developed. The length of partial 18S rDNA from four R. undulata isolates were 1,375 nt. The sequence similarity of R. undulata isolates was 100%. The rDNA ITS regions of R. undulata isolates were 585 nt long. Nucleotide sequencing of the ITS regions showed that PDK-1, PTT-1 and PDJ-9 isolates had 100% sequence identity. But, PDS-5 isolate differed from the three isolates by two nucleotide substitution. R. undulata-specific primers designed by the sequence of ITS region were used in PCR detection of R. undulata. PCR products about 525 bp size, which is specific to R. undulata, were amplified from total DNAs of R. undulata isolates. To assay the sensitivity of PCR detection by R. undulata ITS-specific primer, purely cultured mycelial suspension of R. undulata was serially diluted and mixed with 100g of sterile sandy loam soil, respectively. And then, PCR products of total DNAs extracted from each mycelium-soil mixtures were analysed. The PCR protocol could detected up to 1ng mycelium of R. undulata within 100g of soil.

• ETRI Journal
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• v.30 no.4
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• pp.495-505
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• 2008

This paper presents a parallel processing searcher structure for the initial synchronization of a direct sequence ultra-wideband (DS-UWB) system, which is suitable for the digital implementation of baseband functionalities with a 1.32 Gsample/s chip rate analog-to-digital converter. An initial timing acquisition algorithm and a data demodulation method are also studied. The proposed searcher effectively acquires initial symbol and frame timing during the preamble transmission period. A hardware efficient receiver structure using 24 parallel digital correlators for binary phase-shift keying DS-UWB transmission is presented. The proposed correlator structure operating at 55 MHz is shared for correlation operations in a searcher, a channel estimator, and the demodulator of a RAKE receiver. We also present a pseudo-random noise sequence generated with a primitive polynomial, $1+x^2+x^5$, for packet detection, automatic gain control, and initial timing acquisition. Simulation results show that the performance of the proposed parallel processing searcher employing the presented pseudo-random noise sequence outperforms that employing a preamble sequence in the IEEE 802.15.3a DS-UWB proposal.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.229-232
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• 2009

Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.