With the recent surge in YouTube usage, there has been a proliferation of user-generated videos where individuals evaluate cosmetics. Consequently, many companies are increasingly utilizing evaluation videos for their product marketing and market research. However, a notable drawback is the manual classification of these product review videos incurring significant costs and time. Therefore, this paper proposes a deep learning-based cosmetics search algorithm to automate this task. The algorithm consists of two networks: One for detecting candidates in images using shape features such as circles, rectangles, etc and Another for filtering and categorizing these candidates. The reason for choosing a Two-Stage architecture over One-Stage is that, in videos containing background scenes, it is more robust to first detect cosmetic candidates before classifying them as specific objects. Although Two-Stage structures are generally known to outperform One-Stage structures in terms of model architecture, this study opts for Two-Stage to address issues related to the acquisition of training and validation data that arise when using One-Stage. Acquiring data for the algorithm that detects cosmetic candidates based on shape and the algorithm that classifies candidates into specific objects is cost-effective, ensuring the overall robustness of the algorithm.

효율적인 산림관리와 경영이 이루어지기 위해서는 일정한 공간단위를 가지는 산림의 구획(Zoning)이 정의되어야 한다. 현재 국유림은 임･소반 기준으로, 공･사유림은 필지 단위를 기준으로 공간을 구획하여 활용하고 있다. 이러한 이원적인 공간구획체 계는 통일된 산림계획, 경영, 관리가 어려우며 장기적인 공간단위의 정보 구축과 생성, 관리에도 어려움을 끼칠 수 있다. 이에, 본 연구에서는 DEM(Digital Elevation Model) 기반으로 추출한 산줄기 유역을 소개하고 활용성 검토를 위해 현재 산림관리 단위인 임･소반도, 경영계획구, 산지/산림 관련 주제도와 중첩 분석을 수행하였다. 이를 통해 표준산림관리단위의 대안으로 제안한 각 규모별 산림유역 단위의 공간적 적합성을 검토하고 산림관리, 산림 디지털 공간자료 구축 및 관리 등의 분야에서 산줄기 내포 유역 기반 표준산림관리단위의 활용 방안을 제안하였다.

In this study, indoor radon concentrations were measured in 56 multiple-use facilities located in Gwangju area from December 2017 to December 2018. The average indoor radon concentration in underground space was 51.70 Bq/m3, and that of the 1st floor was 38.73 Bq/m3, indicating that the indoor radon concentration of underground space was higher than that of the 1st floor. The indoor radon concentration was investigated according to the presence or absence of underground space. The concentration of radon on the 1st floor with underground space was 37.25 Bq/m3, and the concentration of radon on the ground floor without underground space was 47.94 Bq/m3. In the absence of underground space, indoor radon concentration was high. The indoor radon concentration of buildings over 30 years old was 87.26 Bq/m3, indicating a significantly higher indoor radon concentration compared to those of buildings less than 30 years old. The indoor radon concentration was investigated according to the operation of a ventilator. The indoor radon concentration of space without an operating ventilator was 52.17 Bq/m3, and that of space with a ventilator in operation for more than 8 hours per day was 36.31 Bq/m3. This result shows that the indoor radon concentration in the space with an operating ventilator is lower than the space where the ventilator is not in operation. The indoor radon concentration in the space with an operating ventilation system was lower than that on the same floor of the same building, and the indoor radon concentration of enclosed space was about 4.4 times higher than that of open space in the same building. In addition, the indoor radon concentration was measured according to the spatial features. The concentration of indoor radon of enclosed space was 64.76 Bq/m3, which is higher than those of an open space and an active space.