• (The) Research of the performance art and culture
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• no.41
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• pp.219-255
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• 2020

This article was triggered by Victor H. Mair's book 'Painting and performance'. The book explained that Buddhist paintings are common in the area where Buddhism was spread, and there are also performances using them. And although it has nothing to do with Buddhism, it has been shown that this form of performance can be global. However, the problem was not 'Korea'. It was because there was no record or transmission of the corresponding performance soon. In this situation, the landing method of Samcheok stable temple was announced in 2018. On the one hand, the academic community is very pleased, but on the other hand, it is troubled. The worries are summed up as 'synchronic and diachronic universality'. Is the landing method inherited from the Samcheok stable temple a unique type of temple? Otherwise, it is a question of whether it has been passed down or is it universal at the national level. However, prior to this essential question, we do not yet know the full picture of the stable landing method. So this article was prepared to show the overall outline of the stable landing method. There is a 'picture' in common throughout the landing method, and understanding how to operate it in various ways is the first step in understanding the landing method. There are five repertoires (which are called main halls) that are considered important, and more than that. What these repertoires have in common is the narrative structure of a Buddhist character. In this narrative, the most important thing is the revised figure, and it was the earthly method to inform the contents of the revised figure in various ways. In the case of Byeonsangdo, which serves as a clue to the narrative, there was a problem that could not be seen in the evening without light, which required special design. It is the way of shadow play and Yeongdeung. In other words, there are three types of performances in the landing method. The first is the method of using reparation, and the second is the method of using shadow. The third is the way of eternity. This method is not a selection based on the contents of the repertoire, but a selection based on the performance environment. If there is light and you can see the picture, use reparation. However, in the evening, it was impossible to see it dark (when there was no electricity in the past). The use of the visual method as a tool in this method is to confirm the transition to a visual culture that is a step further from the level of culture. Moreover, unlike the epic narrative, the power of the implied image provided an opportunity for viewers to experience the mystery of Buddhism through emotional stimulation.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.