• Journal of the Korean earth science society
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• v.41 no.3
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• pp.211-221
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• 2020

This study classified outer-ring galaxies using 25,308 galaxies within z=0.05 from the SDSS DR7, which are larger than R_pet>6 arcsec and whose minor-to-major axis ratio (b/a)<0.6. We selected 531 galaxies that have ring-like structures by visual inspection of the color images of 25,308 galaxies; these galaxies with ring-like structures served as a primary sample from which we selected 90 outer-ring galaxies. The final sample of 69 outer-ring galaxies was selected by examining the photometric properties of the candidate galaxies. Their properties were determined by conducting surface photometry on their u, g, r, i, and z images. The frequency of the outer-ring galaxies was found to be 0.3% of the local galaxies. We examined the environment of the outer-ring galaxies using two measures of environment, namely, the projected distance to the nearest-neighbor galaxy and the local background density. We did not observe any notable difference between outer-ring and other galactic environments.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.53.2-53.2
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• 2013

외부 고리를 갖는 은하들(Outer ring galaxies)을 SDSS dr7 목록에서 분류하여, 이들이 갖는 특징과 링 구조(Ring structure)를 형성하는데 외부환경의 요인이 있는지 조사하고자 했다. z<0.05, b/a>0.6, R>6"의 조건에서 25,308개의 은하들을 추출하였고, SDSS image tool을 이용하여 531개의 외부 고리 은하(Outer ring galaxies)또는 외부고리를 갖고 있는 것처럼 보이는 은하(Ring-like galaxies)를 육안으로 분류하였다. 5개(u, g, r, i, z)의 필터로 관측되어진 CCD 이미지의 분석으로 최종적으로 69개의 외부고리 은하(Outer ring galaxies)를 선정하였다. 통계적으로 전체 은하에서 외부 고리 은하가 차지하는 비율이 약 0.2726%라는 결과를 얻게 되었고, 은하들의 주변의 환경을 조사한 결과 배경밀도와 비리얼 반경에 있어서 다른 형태의 고리를 갖고 있는 은하들과의 유의미한 특이점은 보이지 않았다.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.579-590
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• 2022

In this study, we aimed to develop a Python-based outer-ring galaxy analysis algorithm according to the data science process. We assumed that the potential users are citizen scientists, including students and teachers. In the actual classification studies using real data of galaxies, a specialized software called IRAF is used, thereby limiting the general public's access to the software. Therefore, an image analysis algorithm was developed for the outer-ring galaxies as targets, which were compared with those of the previous research. The results of this study were compared with those of studies conducted using IRAF to verify the performance of the newly developed image analysis algorithm. Among the 69 outer-ring galaxies in the first test, 50 cases (72.5%) showed high agreement with the previous research. The remaining 19 cases (27.5%) showed differences that were caused by the presence of bright stars overlapped in the line of sight or weak brightness in the inner galaxy. To increase the usability of the finished product that has undergone a supplementary process, all used data, algorithms, Python code files, and user manuals were loaded in GitHub and made available as shared educational materials.