• (The) Research of the performance art and culture
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• no.43
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• pp.293-322
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• 2021

The present study examined the scientific awareness appearing in Korean tokusatsu series by focusing on Vectorman: Warriors of the Earth. As a work representing Korean tokusatsu series, Vectorman: Warriors of the Earth achieved the greatest success among tokusatsu series. This work was released thanks to the continued popularity of Japanese tokusatsu since the mid-1980s and the trend of robot animations. Due to the chronic problems regarding Korean children's programs-the oversupply of imported programs and repeated reruns-the need for domestically produced children's programs has continued to come to the fore. However, as the popularity of Korean animation waned beginning in the mid-1990s, inevitably the burden fr producing animation increased. As a result, Vectorman: Warriors of the Earth was produced as a tokusatsu rather than an animation, and because this was a time when an environment for using special effects technology was being fostered in broadcasting stations, computer visual effects were actively used for the series. The response to the new domestically produced tokusatsu series Vectorman: Warriors of the Earth was explosive. The Vectorman series explained the abilities of cosmic beings by using specific scientific terms such as DNA synthesis, brain cell transformation, and special psychological control device instead of ambiguous words like the scientific technology of space. Although the series is unable to describe in detail about the process and cause, the way it defines technology using concrete terms rather than science fiction shows how scientific imagination is manifesting in specific forms in Korean society. Furthermore, the equal relationship between Vectorman and the aliens shows how the science of space, explained with the scientific terms of earth, is an expression of confidence regarding the advancement of Korean scientific technology which represents earth. However, the female characters fail to gain entry into the domain of science and are portrayed as unscientific beings, revealing limitations in terms of scientific awareness.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.3
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• pp.32-45
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• 2014

The study attempts to interpret original location and landscape composition of Yowol-pavilion Garden under the premise that tablet and poetry are important criteria for inference of unique location and landscape composition of a pavilion garden. The study raises the meaning, status, and value of Yowol Pavilion Garden as a cultural asset. The results of the study are as follows. First, Yowol-pavilion Garden was a place where famous Confucius scholars in Joseon Dynasty in 16th Century, including Kim, Kyung-Woo, the owner of the garden, used to share the taste for the arts and poetries with their colleagues. Along with a main characteristic of Yowol Pavilion Garden as a hideout for the Confucius scholars who stayed away from a political turmoil, the new place characteristic of the garden, a bridgehead for the formation of regional identity, was discovered in the record of "Joseon-Hwanyeo-Seungram Honam-Eupji JangSeong-Eupji", As described in "The first creative poetry of Yowol-pavilion", the intention for the creation of Yowol-pavilion Garden and the motive for its landscape composition is interpreted as a space of rivalry where the world, reality and ideals are mixed up. Second, related to outstanding scenic factors and natural phenomena when taking a view from the pavilion, the name of the house 'Yowol', which means 'Greeting the moon rising on the Mt. Wolbong' is the provision of nature and taste for the arts, and is directly connected to the image of leaving the worldly. In other words, the name was identified to be the one that reflected the intention for landscape composition to follow the provision of nature separating from joy and sorrow of the mundane world. Third, as for the location, it was confirmed through "YeongGwang-Soksu-Yeoji-Seungram" that Yowol-pavilion Garden was a place where the person who made the pavilion prepared for relaxation after stepping down from a government post, and literature and various poetry show that it was also a place of outstanding scenic where Yellow-dragon River meandered facing Mt. Wolbong. Especially, according to an interview with a keeper, the visual perception frequency of the nightscape of Yowol-pavilion Garden is the highest when viewing by considering the east, the direction of Yellow-dragon River, as Suksigak[normal angle's view], towards Yowel-pavilion from the keeper's house. In addition, he said that the most beautiful landscape with high perception strength is when the moon came up from the left side of Yowol-pavilion, cuts across the Lagerstroemia india heal in front of Yowol-pavilion, and crosses the meridian between Mt. Wolbong peaks facing Yowol-pavilion. Currently, the exposure of Yowol-pavilion Garden is $SE\;141.2^{\circ}$, which is almost facing southeast. It is assumed that the exposure of Yowol-pavilion Garden was determined considering the optimized direction for appreciating the trace of the moon and the intention of securing the visibility as well as topographic conditions. Furthermore, it is presumed that the exposure of Yowol-pavilion Garden was determined so that the moon is reflected on the water of Yellow-dragon River and the moon and its reflection form a symmetry. Fourth, currently, Yowol-pavilion Garden is divided into 'inner garden sphere' composed of Yowol-pavilion, meeting place of the clan and administration building, and 'outer garden sphere' which is inclusive of entrance space, Crape Myrtle Community Garden and Pine Tree Forest in the back. Further, Yowol-pavilion Garden has been deteriorated as the edge was expanded to 'Small lake[Yong-so] and Gardens of aquatic plants sphere' and recently-created 'Yellow-dragon Pavilion and park sphere'. Fifth, at the time it was first made, Yowol-pavilion Garden was borderless gardens consisting of mountains and water taking a method of occupying a specific space of nearby nature centering around pavilion by embracing landscape viewed from the pavilion, but interpreted current complex landscapes are identified to be entirely different from landscapes of the original due to 'Different Changes', 'Fragmentation' and 'Apart piece' in many parts. Lastly, considering that Yowol-pavilion Garden belongs to the Cultural Properties Protection Zone, though not the restoration to the landscapes of the original described in tablet and literature record, at least taking a measure from the aspect of land use for minimizing adverse effect on landscape and visual damage is required.

• 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.