• 한국진공학회:학술대회논문집
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.90.1-90.1
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• 2013

Nature utilizes various of the colorization process. Some species of birds can express their mood of tempers by changing their collagen structures on skin. For example, turkey can change their skin color by expansion of the collagen structures, which are associated with the distinct color changes. Here, we developed bioinspired virus-based colorimetric sensors which can be genetically tuned for target molecule. Using M 13 bacteriophage, we fabricated responsive self-assembled color matrices composed of quasi-ordered fiber bundle structures. These virus matrices can exhibit color change by stimuli through fiber bundle structure modulation. Upon exposure of volatile organic compounds, the resulting multi-colored matrices exhibited distinct color changes with different ratios that can be recognized by the naked eyes. Using the directed evolutionary approaches, we genetically engineered the virus matrix to incorporate binding motif for explosive detection (i.e., trinitrotoluene (TNT)). Through utilizing a common handheld device (i.e., iPhone), we could distinguish TNT molecules down to 20 ppb in a selective manner. Our novel biomimetic virus colorimetric sensor can overcome current limitation for low response selectivity.

• Journal of Microbiology and Biotechnology
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• 제19권11호
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• pp.1470-1474
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• 2009

This paper describes the development a of direct multiplex reverse transcription-nested polymerase chain reaction (PCR) method, devised for simultaneous detection and typing of influenza viruses. This method combines the direct reverse transcription reaction without RNA purification with the enhancement of sensitivity and specificity of nested PCR. The method successfully detected three major human influenza viruses: influenza virus A subtype 1 (H1N1) and subtype 3 (H3N2), and influenza B virus (B). The minimum number of virus particles (pfu/ml) necessary for detection in spiked saliva samples was 200 (H1N1), 140 (H3N2), and 4.5 (B). The method's sensitivity and simplicity will be convenient for use in clinical laboratories for the detection and subtyping of influenza and possibly other RNA viruses.

• The Plant Pathology Journal
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• 제36권6호
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• pp.651-657
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• 2020

Lotus is one of the most important aquatic vegetables in China. Previously, we detected sweet potato latent virus from lotus (SPLV-lotus) and found that it has highly significant sequence diversity with SPLV-sweet potato isolates (SPLV-sp). Here, we developed serological methods for the detection of SPLV-lotus in Chinese lotus cultivation areas. Based on the high sensitivity of SPLV-lotus coat protein antiserum, rapid, sensitive and large-scale diagnosis methods of enzyme-linked immunosorbent assay (ELISA) and dot blot in lotus planting area were developed. The established ELISA and dot blot diagnostic methods can be used to detect SPLV-lotus from samples successfully. And our results also showed that the SPLV-lotus and sweet potato isolates appeared clearly distinction in serology. Our study provides a high-throughput, sensitive, and rapid diagnostic method based on serology that can detect SPLV on lotus, which is suggested to be included in viral disease management approach due to its good detection level.

• Journal of Veterinary Science
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• 제21권1호
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• pp.4.1-4.9
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• 2020

Fast and accurate detection of viral RNA pathogens is important in apiculture. A polymerase chain reaction (PCR)-based detection method has been developed, which is simple, specific, and sensitive. In this study, we rapidly (in 1 min) synthesized cDNA from the RNA of deformed wing virus (DWV)-infected bees (Apis mellifera), and then, within 10 min, amplified the target cDNA by ultra-rapid qPCR. The PCR products were hybridized to a DNA-chip for confirmation of target gene specificity. The results of this study suggest that our method might be a useful tool for detecting DWV, as well as for the diagnosis of RNA virus-mediated diseases on-site.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.202-209
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• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

• Journal of Microbiology
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• 제44권1호
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• pp.72-76
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• 2006

Plasma-derived products are produced from plasma via fractionation and chromatography techniques, but can also be produced by other methods. In the performance of nucleic acid amplification tests (NAT) with plasma-derived products, it is necessary to include an internal control for the monitoring of all procedures. In order to avoid false negative results, we confirmed the usefulness of the bovine viral diarrhoea virus (BVDV) for use as an internal control in the detection of hepatitis C virus (HCV) RNA in plasma-derived products. These products, which were spiked with BVDV, were extracted and then NAT was performed. Specificity and sensitivity were determined via the adjustment of primer concentrations and annealing temperatures. BVDV detection allows for validation in the extraction, reverse transcription, and amplification techniques used for HCV detection in plasma-derived products.

• 정보처리학회논문지C
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• 제13C권5호
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• pp.559-566
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• 2006

연결요청(connection request) 패킷의 전송비율을 일정 비율 이하로 제한함으로써 월 발생을 탐지하는 바이러스 쓰로틀링(virus throttling)은 대표적인 웜 조기 탐지 기술 중의 하나이다. 기존 바이러스 쓰로틀링은 비율 제한기의 주기를 고정시키고 지연 큐 길이를 감시하여 웜 발생 여부를 판단한다. 본 논문에서는 가중치 평균 지연 큐 길이를 적용하여 비율 제한기의 주기를 자율적으로 조절하는 알고리즘을 제안하고, 가중치 평균 지연 큐 길이에 따른 다양한 주기결정 기법을 제시한다. 실험결과 제안 알고리즘은 웜 탐지시간에는 크게 영향을 미치지 않으면서도 연결설정 지연시간을 단축하여 사용자가 느끼는 불편함을 줄여 줄 수 있음을 확인하였다.

• The Plant Pathology Journal
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• 제29권1호
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• pp.105-109
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• 2013

Raman spectroscopy provides many advantages compared to other common analytical techniques due to its ability of rapid and accurate identification of unknown specimens as well as simple sample preparation. Here, we described potential of Raman spectroscopic technique as an efficient and high throughput method to detect plants infected by economically important viruses. To enhance the detection sensitivity of Raman measurement, surface enhanced Raman scattering (SERS) was employed. Spectra of extracts from healthy and Turnip yellow mosaic virus (TYMV) infected Chinese cabbage leaves were collected by mixing with gold (Au) nanoparticles. Our result showed that TYMV infected plants could be discriminated from non-infected healthy plants, suggesting the current method described here would be an alternative potential tool to screen virus-infection of plants in fields although it needs more studies to generalize the technique.

• Journal of Microbiology and Biotechnology
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• 제22권12호
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• pp.1776-1781
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• 2012

Multiple viruses such as Lily symptomless virus (LSV), Lily mottle virus (LMoV), and cucumber mosaic virus (CMV) are the most prevalent viruses infecting lilies in Korea. Leaf samples and bulbs showing characteristic symptoms of virus infection were collected from Gangwon, Chungnam, and Jeju provinces of Korea in 2008-2011. Coat protein (CP) genes of LSV and LMoV were amplified from collected samples by reverse transcription-polymerase chain reaction (RT-PCR) and cloned into a pET21d(+) expression vector to generate recombinant CPs. The resulting carboxy-terminal His-tagged CPs were expressed in Escherichia coli strain BL21(DE3) by isopropyl-1-thio-${\beta}$-D-galactoside induction. The recombinant proteins were purified using Ni-NTA agarose beads, and the purified proteins were used as an immunogen to produce polyclonal antibodies in rabbits. The resulting polyclonal antisera recognized specifically LSV and LMoV from infected plant tissues in Western blotting assays. Indirect enzymelinked immunosorbent assay and immunocapture RT-PCR using these polyclonal antisera were developed for the sensitive, efficient, economic, and rapid detection of Lily viruses. These results suggest that large-scale bulb tests and economic detection of Lily viruses in epidemiological studies can be performed routinely using these polyclonal antisera.

• The Plant Pathology Journal
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• 제34권6호
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• pp.575-579
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• 2018

Apple stem grooving virus (ASGV) is considered to cause the most economically important viral disease in pears in Korea. The current PCR-based methods used to diagnose ASGV are time-consuming in terms of target detection. In this study, a novel assay for specific ASGV detection that is based on reverse transcription-recombinase polymerase amplification is described. This assay has been shown to be reproducible and able to detect as little as $4.7ng/{\mu}l$ of purified RNA obtained from an ASGV-infected plant. The major advantage of this assay is that the reaction for the target virus is completed in 1 min, and amplification only requires an incubation temperature of $42^{\circ}C$. This assay is a promising alternative method for pear breeding programs or virus-free certification laboratories.