• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.1
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• pp.76-83
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• 2012

In a real-time indoor place recognition system using image features detection, specific markers included in input image should be detected exactly and quickly. However because the same markers in image are shown up differently depending to movement, direction and angle of camera, it is required a method to solve such problems. This paper proposes a technique to extract the features of object without regard to change of the object scale. To support real-time operation, it adopts SURF(Speeded up Robust Features) which enables fast feature detection. Another feature of this system is the user mark designation which makes possible for user to designate marks from input image for location detection in advance. Unlike to use hardware marks, the feature above has an advantage that the designated marks can be used without any manipulation to recognize location in input image.

• Journal of Applied Biological Chemistry
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• v.64 no.3
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• pp.245-251
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• 2021

Codonopsis lanceolata (Deoduk) was grown in East Asia, including Korea, China, Japan, and Russia, and the roots of C. lanceolata have been used as functional foods and traditional medicine to treat symptoms of cough, bronchitis, asthma, tuberculosis, and dyspepsia. The phytochemicals of C. lanceolata have been reported such as phenylpropanoids, polyacetylenes, saponins, and flavonoids that are involved in pharmacological effects such as anti-obesity, anti-inflammation, anti-tumor, anti-oxidant, and anti-microbial activities. Selecting marker substances of the main producing area by MS-based metabolomics analysis is important to ensure the beneficial effect of C. lanceolata without side-effects because differences in cultivated areas of plants were related not only to the safety of medicinal plants but also to changes in chemical composition and biological efficacy. In our present study, ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with multivariate statistical analysis was applied to recognize the main producing area of C. lanceolata in South Korea. As a result of Principal Component Analysis and loading plot analysis of three groups, Inje (Kangwon-do), Hoengseong (Kangwon-do), and Muju (Jeonlabuk-do), several secondary metabolites of C. lanceolata including tangshenoside I, lancemaside A, and lancemaside G, were suggested as potential marker substances to distinguish the place of main producing area of C. lanceolata.