This study deals with the analysis on the consciousness and image character of the internet shopping mall. As consciousness analysis result of internet shopping mall consumer, 'cheap price' and 'convenience' are evaluated high by reason that buy goods/ser

이 연구에서는 디지털 이미지 분석법을 활용하여 북동태평양 ODP Leg 204 시추 코아 시료에서 산출된 부유성 유공충 Neogloboquadrina pachyderma 권각의 감긴 방향을 컴퓨터 프로그래밍으로 결정하였다. 이것은 유공충 군집 이미지에서 N. pachyderma 개체를 자동 인식하게 한 것이며, N. pachyderma 권각 방향을 컴퓨터 프로그래밍으로 결정할 수 있도록 고안한 것이다. 이 알고리즘을 이용한 새로운 판독 방법을 사용한 결과 유공충 시료에 대한 정량 분석이 빠르게 수행될 수 있게 되었으며, 실제현미경을 통한 관찰 결과와 비교하였을 때 약 90% 만큼 높게 일치하였다. 이 수치는 컴퓨터를 이용한 디지털 이미지 분석이 미고생물학 분야에 성공적으로 적용될 수 있다는 점을 시사하고 있다.

As an efficient method to detect blending of general gravitational microlensing events, it is proposed to measure the shift of source star image centroid caused by microlensing. The conventional method to detect blending by this method is measuring the difference between the positions of the source star image point spread function measured on the images taken before and during the event (the PSF centroid shift, δθc,PSF). In this paper, we investigate the difference between the centroid positions measured on the reference and the subtracted images obtained by using the difference image analysis method (DIA centroid shift, δθc.DIA), and evaluate its relative usefulness in detecting blending over the conventional method based on δθc,PSF measurements. From this investigation, we find that the DIA centroid shift of an event is always larger than the PSF centroid shift. We also find that while δθc,PSF becomes smaller as the event amplification decreases, δθc.DIA remains constant regardless of the amplification. In addition, while δθc,DIA linearly increases with the increasing value of the blended light fraction, δθc,PSF peaks at a certain value of the blended light fraction and then eventually decreases as the fraction further increases. Therefore, measurements of δθc,DIA instead of δθc,PSF will be an even more efficient method to detect the blending effect of especially of highly blended events, for which the uncertainties in the determined time scales are high, as well as of low amplification events, for which the current method is highly inefficient.

본 연구는 실제 현장에서 적용할 수 있는 보다 구체적인 감성 데이터를 제공하기 위한 시도로서, 메이크업의 주요한 색채특성을 평가변인으로 하여 칼라 시뮬레이션 실험 및 분석을 실시하여, 최종적으로 색채감성 분석기법에 의한 이미지 유형별 예측모델을 작성하였다. 그 결과, 「품위있는.귀족적인」, 「깔끔한.여성스러운」, 「강렬한.도발적인」, 「캐주얼한.경쾌한」, 「수수한.부드러운」의 5가지 이미지유형이 추출되었고, 이미지유형별로 이미지와 색채특성간의 정량적 예측모델을 작성한 후, 그 결과를 토대로 이미지유형별 색채팔레트를 제시하였다.

It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

A well-maintained landscape can increase the competitiveness of a city. Gyeongju which is the famous ancient capital of Korea, has numerous historical resources. However, the disharmony between the historical landscape and the surrounding landscape weakens the competitiveness of the city. At present, most landscape analysis methods mainly focus on plans, photos, and animation, which have certain limitations in the expression of landscape spatial scale and materials. This study aimed to use the virtual walkthrough method to take the Wolseong District of Gyeongju historical areas as the object in order to evaluate the landscape visually. Compared with planar landscape analysis methods, such as photos and videos, the virtual walkthrough method is more immersive and intuitive to experience the spatial scale. The study results revealed images, visual characteristics, and visual influence factors of the landscape, which provide essential data for the construction and improvement of landscapes in similar historical areas in the future.

In this study, an analysis were conducted to utilize the thermal infrared image using drone to present the temperature correction method of thermal infrared image and the thermal environment by the type of land cladding. The analysis was applied to the temperature correction of the thermal infrared image and total eight thermal infrared images were produced based on the land surface temperature. The thermal infrared image compared accuracy through RMSE calculation. Based on the result of RMSE, the thermal infrared image corrected by the land surface temperature was relatively accurate and contained at 2.26 to 3.58. According to the results, it is expected that the aggregation and waters will perform the functions of the green park sufficiently to improve the thermal comfort and improve the microclimate stability using the thermal infrared image and the reclassified land cover map. The results of this study obtained by Drone and the usability of the drone thermal infrared image in the detection of the thermal environment. Finally, it is expected to contribute to the improvement and management of the thermal environment in the city by being used as a basic data for the improvement and management policy of the thermal environment. Moreover, the macro view is expected to contribute to the mitigation of urban temperature reduction and heat island.