• Bulletin of the Korean Chemical Society
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• v.29 no.12
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• pp.2355-2360
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• 2008

• Molecules and Cells
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• v.45 no.7
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• pp.502-511
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• 2022

Bacterial volatile compounds (BVCs) exert beneficial effects on plant protection both directly and indirectly. Although BVCs have been detected in vitro, their detection in situ remains challenging. The purpose of this study was to investigate the possibility of BVCs detection under in situ condition and estimate the potentials of in situ BVC to plants at below detection limit. We developed a method for detecting BVCs released by the soil bacteria Bacillus velezensis strain GB03 and Streptomyces griseus strain S4-7 in situ using solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME-GC-MS). Additionally, we evaluated the BVC detection limit in the rhizosphere and induction of systemic immune response in tomato plants grown in the greenhouse. Two signature BVCs, 2-nonanone and caryolan-1-ol, of GB03 and S4-7 respectively were successfully detected using the soil-vial system. However, these BVCs could not be detected in the rhizosphere pretreated with strains GB03 and S4-7. The detection limit of 2-nonanone in the tomato rhizosphere was 1 µM. Unexpectedly, drench application of 2-nonanone at 10 nM concentration, which is below its detection limit, protected tomato seedlings against Pseudomonas syringae pv. tomato. Our finding highlights that BVCs, including 2-nonanone, released by a soil bacterium are functional even when present at a concentration below the detection limit of SPME-GC-MS.

• 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).

• Genomics & Informatics
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• v.7 no.1
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• pp.32-37
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• 2009

The quality assurance (QA) is of utmost importance in biobanks when archived biomaterials are distributed to biomedical researchers. For sample authentication and cross-contamination detection, the two fundamental elements of QA, STR genotyping is usually utilized. However, the incorporated number of STR markers is highly redundant for biobanking purposes, resulting in time and cost inefficiency. An index to measure the cross-contamination detection capability of an STR marker, the mixture probability (MP), was developed. MP as well as other forensic parameters for STR markers was validated using STR genotyping data on 2328 normal Koreans with the commercial AmpFlSTR kit. For Koreans, 7 STR marker (D2S1338, FGA, D18S51, D8S1179, D13S317, D21S11, vWA) set was sufficient to provide discrimination power of ${\sim}10^{-10}$ and cross-contamination detection probability of ${sim}1$. Interestingly, similar marker sets were obtained from African Americans, Caucasian Americans, and Hispanic Americans under the same level of discrimination power. Only a small subset of commonly used STR markers is sufficient for QA purposes in biobanks. A procedure for selecting optimal STR markers is outlined using STR genotyping results from normal Korean population.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.567-569
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• 2003

Because of the limited land resources, an efficient land use management to reach the sustainable development policy has become an urgent call in Taiwan. A long-term project entitled 'National land use monitoring program-the establishment of a land use change detection system' has been jointly conducted by both National Central University and Ministry of Interior since year of 2001. The main aim of the project is to use the remote sensing images to detect the land use changes on a national scale. This plan has been put into practice and indeed provides an effective assistance for land management.

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1432-1438
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• 2015

We present a methodology to detect moving shadows in video sequences, which is considered as a challenging and critical problem in the most visual surveillance systems since 1980s. While most previous moving shadow detection methods used hand-crafted features such as chromaticity, physical properties, geometry, or combination thereof, our method can automatically learn features to classify whether image segments are shadow or foreground by using a deep learning architecture. Furthermore, applying Markov Random Field enables our system to refine our shadow detection results to improve its performance. Our algorithm is applied to five different challenging datasets of moving shadow detection, and its performance is comparable to that of state-of-the-art approaches.

• International Journal of Contents
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• v.2 no.3
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• pp.22-26
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• 2006

In this paper we introduce a new circle detection algorithm for occluded on/off pupil and iris boundary extraction. The proposed algorithm employs 7-step processing to detect a center and radius of occluded on/off eye images using the property of the chords. The algorithm deals with two types of occluded pupil and iris boundary information; one is composed of circle-shaped, incomplete objects, which is called occluded on iris images and the other type consists of arc objects in which circular information has partially disappeared, called occluded off iris images. This method shows that the center and radius of iris boundary can be detected from as little as one-third of the occluded on/off iris information image. It is also shown that the proposed algorithm computed the center and radius of the incomplete iris boundary information which has partially occluded and disappeared. Experimental results on RGB images and IR images show that the proposed method has encouraging performance of boundary detection for pupil and iris segmentation. The experimental results show satisfactorily the detection of circle from incomplete circle shape information which is occluded as well as the detection of pupil/iris boundary circle of the occluded on/off image.

• Archives of Pharmacal Research
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• v.16 no.3
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• pp.227-230
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• 1993

A new device to detect methamphetamine (MA), amphetamine(A) and its metabolites in urine was developed using the paper strip method and the test tube method of dry chemical reagents. The reagent containing tetrabromophenolphthalein ethyl ester (TBPE) and borax. For the TBPE paper strip method, a device was prepared with a window at each end of the reagent paper strip ; one window is for the sample application, and the other window is for the methylene chloride. The diffused sample from one window reacts with reagent in the paper and produces color at the point where it meets with methylene chloride which has diffused form the other side. A positive smaple produces as red-purple color and the negative sample a greenish color, with a detection limit of 5-10 ppm. The result can be obtained within one minute. For the TBPE test tube method which contains dry reagents, the detection limit is 5 ppm and the result can be obtaineed within 30 seconds, however the carry-on is not as convenient as the paper strip method. The performance of both methods were evlauated by comparing with the results of gas chromatography (GC) and fluorescence polarizaiton immunoassay (FPIA). The results were proven that both methods were useful as primary screening reagents to detect MA in urine and in dry powder.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.30-44
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• 2022

The advent of deep learning-based algorithms has facilitated researches on target detection from synthetic aperture radar(SAR) imagery. While most of them concentrate on detection tasks for ships with open SAR ship datasets and for aircraft from SAR scenes of airports, there is relatively scarce researches on the detection of SAR ground vehicle targets where several adverse factors such as high false alarm rates, low signal-to-clutter ratios, and multiple targets in close proximity are predicted to degrade the performances. In this paper, a dataset of ground vehicle targets acquired from TerraSAR-X(TSX) satellite SAR images is presented. Then, both detection and instance segmentation are simultaneously carried out on this dataset based on the deep learning-based Mask R-CNN. Finally, this paper shows the future research directions to further improve the performances of detecting the SAR ground vehicle targets.

• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.873-881
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• 2017

Prevention of drowsy driving is one of the important issues for safe driving. In this study, the algorithm for detection of drowsy driving has been developed. The algorithm was implemented by applying template matching and line profile, which detects eye blink. The accuracy of eye detection and blink detection was $97.45{\pm}3.67%$ and $98.50{\pm}0.92%$, which was resulted from the verification experiment that 21 subjects participated. Consequently, the algorithm is expected to be used to prevent sleep-deprived driving.