• Title/Summary/Keyword: Hidden layers

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Sympathy in Unrest: Beyond Jonjae's Philosophy (불온한 공감 - 존재의 사유, 너머 -)

  • Kim, Kyoung-ho
    • The Journal of Korean Philosophical History
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    • no.52
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    • pp.9-35
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    • 2017
  • This article is to study the life and philosophy of Jonjae Gidaeseung, who was at strife with his days and did not negotiate with himself, with focus on two concepts of buron(不穩, unrest) and 'sympathy'. It is the fact that to study the traditional philosopher is likely to be enlightening. In order to prevent the risk, we need to define first the concept of unrest as including anxiety to critical resistance. Also, I would like to propose the concept of sympathy in order to grasp the function of his mind which judges whether his feelings and actions are valid from an emotional horizon of unrest. Methodologically this article is to adopt a transversal and correlative thinking by combining an east Asian Confucian traditional concept unrest with a modern one space. It is because this research is to show a significant meaning when we study highlighted and hidden layers of our life and politics in 'now-here' and the 'between space' even though this transversal and correlative study shows the horizon of his life. This article is to investigate how a case is structured by occurrences and divergences and reinterpret a meaning from an emotional horizon. This process is done centering on two terms Guchatuan(pursuing ease ignobly), and Suwolbingho(moon reflected in the water and ice in a bottle), which is the source of Bingwoldang. The two terms were used by Jonjae himself. The latter shows an opposite meaning from the first and is accordingly a way by which we can look into his life and days. My research of Jonjae's life and politics from the emotional-philosophical level is original in that it reveals emotional traces beyond his philosophical ideas which previous studies did not show. In this article, I showed that Gobong was ambitious and resolute, and definite in his judgment and therefore was not good at controlling his uprightness. Also he was too straightforward to purify a language. His unrest characters made him conflict with old ministers and high ranking officials and therefore they avoided him even thought he was excellent in writing and learning and talented. He was oriented toward living by goodness and right Ways, which is summed up as Gisesa(vague movement, situational advantage, and death).

The Diversification of Environmental Aesthetics and the Rise of Everyday Aesthetics - Theoretical Agendas and Issues of Yuriko Saito's Everyday Aesthetics - (환경미학의 다변화와 일상미학의 부상 - 유리코 사이토의 일상미학 이론의 의제와 쟁점을 중심으로 -)

  • Pae, Jeong-Hann
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.2
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    • pp.42-53
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    • 2023
  • This paper explores the recent development of environmental aesthetics and critically examines the main agendas, claims, issues, and implications of everyday aesthetics, which is emerging as an important branch of environmental aesthetics. Environmental aesthetics began in the context of cultural change and environmentalism in the 1960s and expanded in the second half of the 20th century with a solid theoretical foundation. At the beginning of the 21st century, it entered a process of diversification of objects and subjects. Having reached academic maturity, environmental aesthetics has expanded into theoretical territory considering the urban environment and the human environment, providing practical coordinates as a discourse for planning and designing urban environments and landscapes. The most notable achievement of environmental aesthetics since the mid-2000s is the establishment of 'everyday aesthetics'. Yuriko Saito, who is leading the research on everyday aesthetics, expanded the objects and scope of aesthetic theory to everyday objects, events, activities, and environments. She excavates the microscopic and sensory aspects of everyday life, which have been overlooked by conventional art-centered aesthetics, through the lens of aesthetics. She reinterprets various layers of phenomena in contemporary urban landscapes and analyzes how the 'power of the aesthetic' hidden in everyday life profoundly affects the quality of life and the state of the world. Saito examines the appreciation of the distinctive characteristics and ambiance inherent in everyday objects and environments and proposes a 'moral-aesthetic judgment' to alert citizens to the environmental, social, and political consequences of everyday aesthetic appreciation and response. This paper identifies the issues and implications of everyday aesthetics as first, the expansion of aesthetics and the ambiguous everyday, second, the moral-aesthetic judgment and the aesthetics of care, and third, urban regeneration landscapes and aesthetic literacy. In particular, the moral virtues of everyday aesthetics that Saito proposes, such as care, thoughtfulness, sensitivity, and respect, provide a critical reference for the practice of contemporary urban regeneration landscapes. The 'aesthetic literacy' is a key concept demonstrating why an environmental aesthetics perspective is necessary to interpret everyday urban environments and landscapes.

Estimation for Ground Air Temperature Using GEO-KOMPSAT-2A and Deep Neural Network (심층신경망과 천리안위성 2A호를 활용한 지상기온 추정에 관한 연구)

  • Taeyoon Eom;Kwangnyun Kim;Yonghan Jo;Keunyong Song;Yunjeong Lee;Yun Gon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.207-221
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    • 2023
  • This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.