• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.196-209
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• 2022

This study compared and analyzed the spatial division function and role of partitions by comparing the entire space and the spatial changes before and after the installation of partitions in <Donggwoldo>, which was manufactured in the late Joseon Dynasty. As a research method, a set standard was prepared to decompose the space of <Donggwoldo> into a unit space, and the standard was set according to the role and height of the space by classifying it into a main space, sub space, and transition space. Two convex maps were prepared according to before and after the installation of the Panjang, and the values of connectivity, control, and integration, which are spatial syntax variables, were calculated and analyzed. The results of the study are as follows. First, the partition in <Donggwoldo(東闕圖)> did not affect the overall spatial arrangement and control or connection of Donggwol, but the movement and access of space is limited to specific areas. Second, the partition was a facility intensively distributed in Naejeon(內殿) and Donggung(東宮) to be used actively in the way of space utilization. It shows that the unit space increased rapidly due to the installation of the partition. Since the partition was installed in the spaces that were open and under high control in the case of Naejeon(內殿), it helped to secure private spaces as closed ones under low control. On the other hand, for Donggung(東宮), the spaces were compartmented and divided with the partition to guide the movement path through narrow gates of the partition and increase the depth of the space. This helped to create spaces that are free and can be hidden as it increased the number of spaces coming through. Third, In addition to the functions of "eye blocking, space division, and movement path control" revealed in prior research, the partition has created a "space that is easy to control" within a specific area. The installation of the partition reduced the scale through the separation of spaces, but it occurred the expansion of the movement path and space. Also, the partition functioned to strengthen hiding and closure or increase openness as well through space division. This study is significant in that it revealed the value of the spatial control function of panjang through the analysis of spatial control and depth by analyzing the function of the partition with a mathematical model in addition to the analysis and study of the function and role of panjang. In addition, it is valuable in that it has prepared a framework for analysis tools that can be applied to traditional residential complexes similar to palaces by applying space syntax to <Donggungdo> to create convex spaces according to unit space division and connection types of palace architecture and landscape elements.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.