• Title/Summary/Keyword: 사상기법

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A Study on the Painting's Aesthetic of Gongjae Yoon Duseo (공재(恭齋) 윤두서(尹斗緖)의 회화심미(繪畵審美) 고찰)

  • Kim, Doyoung
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.175-183
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    • 2021
  • Gongjae Yoon DuSeo(1668~1715), from Haenam in the late Joseon Dynasty, is a scholar-born painter who was active during King Sukjong. He is the person who created the foundation as a pioneer of realist paintings in the late Joseon period during the transition from the middle to the latter period. He was born in Namin's prestigious family, but he ended his career as part of a partisan fight and immersed himself in painting and learning. 18C, the beginning of the late Joseon Dynasty, was a period when Silhak emerged and the Jinkyung era opened with awareness of nationalism. At this time, by incorporating the Silhak thought into the art world, the real reformed aesthetic consciousness was demonstrated to pioneer common people's customs, the application of Western painting methods, the pursuit of realist techniques, and the introduction of Namjongmuninhwa. His view of painting, who thoroughly learned the old things and pursued change, must have both the form and spirit that he can achieve 'HwaDo' only when it has the science of 'learning and knowledge' and the technical elements of 'practice and quality' emphasized. He has worked in a variety of reconciliations. In particular, portrait paintings are characterized by ihyeongsasin's realistic expressions of aesthetics. His masterpiece, 「Self-portrait」, excels in extreme-realistic depiction and innovation in composition, and stands out with an unconventional experimentation spirit that expresses his mind and thoughts in a painting with a sense of resentment. His landscape paintings combine to express the form as it is and mental notions, and beautifully embodied Do as a form, thus achieving ihyeongmido, which reached the level of'joyfulness forgotten even the heart of joy'. On the other hand, the generalization of the common people using various common people's lives as the subject of an open-mindedness aimed at gaining the facts of ihyeongsajin, a passive protest against corrupt power and an expression of a spirit of love. Since then, his painting style has been passed down from generation to generation to his eldest son Yoon Deok-hee and his grandson Yoon Yong, leading the change and revival of calligraphy art in the late Joseon Dynasty.

Development of disaster severity classification model using machine learning technique (머신러닝 기법을 이용한 재해강도 분류모형 개발)

  • Lee, Seungmin;Baek, Seonuk;Lee, Junhak;Kim, Kyungtak;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.261-272
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    • 2023
  • In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.