• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.4
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• pp.14-26
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• 2011

Imdaejeong Wonlim is located on the verge of Sangsa Village in Sapyeong-ri, Daepyeong-myeon, Hwasun-gun Gyeongsangnam-do toward Northwest. It was planned by Sa-ae, Minjuhyeon in 1862 on the basis of Gobanwon built by Nam Eongi in 16th century against the backdrop of Mt. Bongjeong and facing Sapyeong Stream. As water flows from west to east in the shape of crane, this area is a propitious site standing for prosperity and happiness. This area shows a distinct feature of Wonlim surrounding the Imdaejeong with multi layers as consisting of 5 districts - front yard where landmark stone with engraved letters of 'Janggujiso of Master Sa-ea' and junipers are harmoniously arranged, internal garden of upper pavilion ranging from a pavilion to square pond with a little island in the middle, Sugyeongwon of under pavilionu consisting of 2 ponds with a painting of three taoist hermits, forest of Mt. Bonggeong and external garden including Sapyeong Stream and farmland. According to documentation and the results of on-site investigation, it is certainly proved that Imdaejeong Wonlim was motivated by Byeoseo Wonlim which realized the idea of 'going back to hometown after resignation' following the motives of Janggujiso, a hideout aimed to accomplish the ideology, 'training mind and fostering innate nature,' on the peaceful site surrounded by water and mountain, as well as motives of Sesimcheo(洗心處) to be unified with morality of Mother Nature, etc. In addition, it implies various imaginary landscapes such as Pihangji, Eupcheongdang, square pond with an island and painting of three Taoist hermits based on a notion that 'the further scent flies away, the fresher it becomes,' which is originated from Aelyeonseol(愛蓮說). In terms of technique of natural landscape treatment, divers techniques are found in Imdaejeong Wonlim such as distant view of Mt. Bongjeong, pulling view with an intention of transparent beauty of moonlight, circle view of natural and cultural sceneries on every side, borrowed scenary of pastoral rural life adopted as an opposite view, looked view of Sulyundaero, over looked view of pond, static view in pavilion and paths, close view of water space such as stream and pond, mushroom-and-umbrella like view of Imdaejeong, vista of pond surrounded by willows, imaginary view of engraved letters meaning 'widen knowledge by studying objectives' and selected view to comprise sunrise and sunset at the same time. In the beginning of construction, various plants seemed to be planted, albeit different from now, such as Ginkgo biloba, Phyllostachys spp., Salix spp., Pinus densiflora, Abies holophylla, Morus bombycis, Juglans mandschurica, Paulownia coreana, Prunus mume, Nelumbo nucifera, etc. Generally, it reflected dignity of Confucianism or beared aspect of semantic landscape implying Taoist taste and idea of Phoenix wishing a prosperity in the future. Furthermore, a diversity of planting methods were pursued for such as liner planting for the periphery of pond, bosquet planting and circle planting adopted around the pavilion, spot planting using green trees, solitary planting of monumentally planted Paulownia coreana and opposite planting presenting the Abies holophylla into yin and yang.

• Korean Journal of Heritage: History & Science
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• v.53 no.3
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• pp.62-79
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• 2020

The rock-carved seated Avalokiteśvara statue at Ganghwa Bomunsa Temple is a giant rock-carved Buddhist statue that was built in 1928 during the Japanese colonial era. Although it is a year-recorded Buddhist statue that occupies a prominent place in modern Korean Buddhist sculpture history, it has not been the subject of in-depth discussion due to weak research on modern Buddhist sculptures. In this study, to examine the various significant aspects of the rock-carved Seated Avalokiteśvara statue at Bomunsa Temple as a modern Buddhist sculpture, I have managed to determine its construction year, artificers, and patrons by deciphering the inscription around the rock-carved statue; in addition I have researched the effects of the rock shapes and landforms on the formation of the Buddhist statue by comparing and analyzing the points of view of both artificers and worshipers. I have also identified the specific circumstances of the time of construction from interviews with the descendants of artificers. A monk from Geumgangsan Mountain, Lee Hwaeung, took the role of sponsor and chief painter to construct the rock-carved seated Avalokiteśvara statue at Bomunsa temple. In the beginning of its construction in 1928, more than 100 donators jointly sponsored the construction of the statue. Gansong Jeon Hyoungphil sponsored alone at the time of the place of worship's expansion in 1938. Bomunsa Temple has been regarded as one of the top-three sacred places of Avalokiteśvara Bodhisattva together with Naksansa Temple in Yang Yang and Boriam in Nam Hae, due to the construction of the rock-carved statue. It took about three months to construct the statue. Lee Hwaeung drew a rough sketch and then Un Songhag and five masons from Ganghwa Island took part in the carving process. We can observe the line drawing technique around the rock-carved statue because the statue was carved based on the rough sketch of the monk painter. The aspect of Lee Hwaeung as a painter is revealed; therefore, we can identify the clue of painting pattern leading to Seogongchulyou- Hwaunghyoungjin- Ilonghyegag. The rock-carved seated Avalokiteśvara statue at Bomunsa Temple is a typical Avalokiteśvara that wears a jeweled crown and holds Kundica. It makes a strong impression as it has a big square-shaped face and a short neck and is unsophisticated in general. The artificers solved the issue of visual distortion of the rock-carved statue caused by carving on a 10-meter high and 40-degree sloping rock by controlling motion to its maximum, omitting detailed expression by emphasizing symmetry, and adjusting the head-to-body proportion to be almost one-to-one. In this study, especially, I presume the unified form of sacred sculptures and Buddhist altars, without making a Buddhist altar like the rock-carved seated Avalokiteśvara statue at Bomunsa Temple, to be a key characteristic of modern Buddhist sculptures. Furthermore, I make newly clear that the six letters of Sanskrit carved on nimbus, which had been interpreted as a Six-Syllable Mantra, are a combination with Jeongbeopgye and Sabang Mantras. In addition, three iron rings driven on eaves rock were used as a reference point, and after construction they were used as a decoration for the Bodhisattva with hanging wind chimes.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.227-234
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• 2022

Seok Jeon Hwang Wook (18913~1999), a descendant of a traditional literary writer in the western part of Honam, did not join the flow of modern and contemporary calligraphy and painting. And throughout his life, he enjoyed himself without losing the appearance of a scholar, immersed himself in traditional calligraphy, and gained spotlight at his late age for his original hand grabbing calligraphy. Immediately after the Korean War, all of his property was lost due to his two sons' left-wing activities, causing great pain at home. Even in the most painful and difficult time in human history, he relied on brushes, poetry, and gayageum to keep his upright scholarly spirit and national love. And beyond the pleasures of the worldly senses, he played with self-satisfaction in the 'true pleasure(大樂)' without greed. In the course of his studies, he focused on honing the fonts of Wang Hui-ji, Gu Yang-sun, An Jin-gyeong, Jo Maeng-bu, and Xin-wi and Lee Sam-man without a special teacher. In particular, he faced a crisis of having to give up his brush due to tremor that came after his 60th birthday, but he showed a strong will. He transformed it into a new style of art, such as developing hand grabbing calligraphy(握筆法) with a strong and strong energy that no one could match. From 1965 to 1983, 'right hand grabbing calligraphy' was used, and from 1984 to 1993, 'left hand grabbing calligraphy' was used. She made her name as a calligrapher widely known in 1973 (age 76) with her first solo exhibition, The Calligraphy Exhibition commemorating her 60th wedding anniversary. His writing method is naturally rough and sloppy by breaking away from the previous calligraphy methods and artificial technique, and is unfamiliar yet full of muscle. And the calm, strong and rough chuhoegsa(錐劃沙) and the heavy yet majestic ininni(印印泥) individual handwriting expressed a strange feeling and achieved original Seokjeon calligraphy that went beyond the existing calligraphy writing methods, and his indomitable calligraphy spirit was As a unique existence in the history of calligraphy, he still remains as a model.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.