https://repository.kopri.re.kr/handle/201206/12723 국내 산-연 극지연구 진흥프로그램 (PIP) 2026-03-05T08:53:13Z https://repository.kopri.re.kr/handle/201206/14082 Title: Statistical optimization of phytol and polyunsaturated fatty acid production in the Antarctic microalga Micractinium variabile KSF0031 Authors: Kim, Eun Jae; Chae, Hyunsik; Koo, Man Hyung; 유지현; 김현중; Cho, Sung Mi; 홍광원; 이주영; Youn, Ui Joung; Kim, Sanghee; Choi, Han-Gu; Han, Se Jong Abstract: Polar microorganisms produce physiologically active substances to adapt to harsh environments, and these substances can be used as biomedical compounds. The green microalga Micractinium variabile KSF0031, which was isolated from Antarctica, produced phytol, a natural antimicrobial agent. Furthermore, several polyunsaturated fatty acids (PUFAs), including omega-3, exhibit antioxidant properties. Here statistical methods (Plackett-Burman design and Box-Behnken design) were used to optimize the culture medium of KSF0031 to improve biomass production, and K2HPO4, MgSO4·7H2O, and ammonium ferric citrate green (AFCg) were selected as significant components of the culture medium. Changes in the concentration of K2HPO4 and MgSO4·7H2O as positive factors and AFCg as a negative factor affected cell growth to a remarkable degree. The biomass production in a 100 L culture using the optimized medium for 24 d at 18°C was improved by 37.5% compared to that obtained using the original BG-11 medium. The quantities of PUFAs and phytol obtained were 13 mg g-1 dry cell weight (DCW) and 10.98 mg g-1 DCW, which represent improved yields of 11.70% and 48.78%, respectively. The results of this study could contribute to an improved production of phytol and fatty acids from Antarctic microalgae in the biomedical industry. 2022-01-01T00:00:00Z https://repository.kopri.re.kr/handle/201206/13013 Title: An Optimal Image-Selection Algorithm for Large-Scale Stereoscopic Mapping of UAV Images Authors: Lim, Pyung-chae; Rhee, Sooahm; Seo, Junghoon; Kim, Jae-In; Chi, Junhwa; Lee, Suk-bae; Kim, Taejung Abstract: Recently, the mapping industry has been focusing on the possibility of large-scale map- ping from unmanned aerial vehicles (UAVs) owing to advantages such as easy operation and cost reduction. In order to produce large-scale maps from UAV images, it is important to obtain precise orientation parameters as well as analyzing the sharpness of they themselves measured through image analysis. For this, various techniques have been developed and are included in most of the commercial UAV image processing software. For mapping, it is equally important to select images that can cover a region of interest (ROI) with the fewest possible images. Otherwise, to map the ROI, one may have to handle too many images, and commercial software does not provide information needed to select images, nor does it explicitly explain how to select images for mapping. For these reasons, stereo mapping of UAV images in particular is time consuming and costly. In order to solve these problems, this study proposes a method to select images intelligently. We can select a minimum number of image pairs to cover the ROI with the fewest possible images. We can also select optimal image pairs to cover the ROI with the most accurate stereo pairs. We group images by strips and generate the initial image pairs. We then apply an intelligent scheme to iteratively select optimal image pairs from the start to the end of an image strip. According to the results of the experiment, the number of images selected is greatly reduced by applying the proposed optimal image？composition algorithm. The selected image pairs produce a dense 3D point cloud over the ROI without any holes. For stereoscopic plotting, the selected image pairs were map the ROI successfully on a digital photogrammetric workstation (DPW) and a digital map covering the ROI is generated. The proposed method should contribute to time and cost reductions in UAV mapping. 2021-06-01T00:00:00Z https://repository.kopri.re.kr/handle/201206/11043 Title: Development of Polar Ice Core Electrical Conductivity Meter Authors: 김재형 2019-12-31T00:00:00Z https://repository.kopri.re.kr/handle/201206/13147 Title: Polar Glacier Structure Analysis Radar Localization Authors: 신승하 2019-12-13T00:00:00Z