• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.3
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• pp.38-49
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• 2015

This study aims to contemplated spatial recognition in Soswaewon Garden through garden visitors poetry. It was content analysis in poetry and extract frequency from words based on relationship of author. The results were as follows. First, relationship of authors who wrote Soswaewon Garden poetry was formed in companionship. In the Yang, San-Bo(梁山甫), poetry was written by Song, Soon(宋純), Kim, Un-Geo(金彦据) and Kim, In-Hu(金麟厚) as the central figure. Especially Kim, In-Hu was playing an important role in Soswaewon Garden poetry. He was wrote many of poetry and keep friends with Yang, Ja-Jeong(梁子渟) too. In the Yang, Ja-Jung, relationship of previous generation was sustained. In addition, Ko, Gyeong-Myeong(高敬命) and Kim, Seong-Won and Jeong, Chul(鄭澈) is more closely related than others. Because blood relationship by marriage. In the Yang, Jin-Tae(梁晋泰), He formed a relationship with a celebrity and attend to international activity. Since then Yang, Jin-Tae periord, Yang, Gyeong-Ji(梁敬之) and Yang, Chae-Ji(梁采之) formed relationship of previous generation was sustained. And surrounding people was written poetry as hold a banquet. Second, plant and ornament is a popular object for writing poetry. Bamboo grove and Fine tree with a high frequency of plant element in poetry. Bamboo grove is a typical species of trees in Soswaewon Garden. It was enclosed the Soswaewon Garden. Fine tree was often used target of poetry as a single tree. Meanwhile, ornament of the wall has been used most frequently. Descendants wrote a poem to see it because Kim, In-Hu's poetry was left. This phenomenon is involves respect for the ancient sages with high frequency. In addition, behavior of viewing the landscape was mainly appeared. Third, spatial recognition of Soswaewon Garden can be divided into landscape cognition, behavior cognition and emotional cognition. In a aspect of landscape cognition, early Soswaewon Garden was recognized as a pavilion. That was used garden name to 'Soswaewon Garden' since Yang, Ja-Jung's period. That is to say, Soswaewon Garden expanded from pavilion area surrounded by trees into the whole appearance is equipped garden area. Behavior cognition was consisting drink and enjoys a landscape. In the Yang, San-Bo, authors enjoyed drinking and viewing a landscape besides walking, writing poetry, viewing the moon. But after Yang, San-Bo's period other than drinking and enjoy a landscape has appeared a low frequency. These results were changed from internal place to blood relationship into external place to companionship. In the Yang, San-Bo's emotional cognition was sorrow and yearning about leave to Soswaewon Garden with an idly atmosphere. Pleasant emotion was sustained all generation. And emotion of respect for the ancient sages was appeared since Yang, Cheon-un.

• 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.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.39-53
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• 2013

The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.

• Journal of Korean Society of Forest Science
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• v.98 no.1
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• pp.66-81
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• 2009

From a new perspective of "humans and the culture of forming and conserving the environment", the sustainable forest management can be reformulated under the concept of "cultural sustainability". Cultural sustainability is based on the emphasis of the high contribution to sustainability of the culture of forming and conserving the environment. This study extracts the implications to cultural sustainability for the modern world by investigating a historical case of the culturo-social pine forestry in the Joseon period of Korea. In the legendary and recorded acts by the first king Taejo, Seonggye Yi, Korean red pine (Pinus densiflora) was the "Royal tree" of Joseon and also the "Sajik tree" related intimately with the Great Sajik Ritual valued as the top rank within the national ritual regime that sustained the Royal Virtue Politics in Confucian political ideology. Into the Neo-Confucian faith and royal rituals of Joseon, elements of geomancy (Feng shui), folk religion, and Buddhism had been amalgamated. The deities worshipped or revered at the Sajik shrine were Earth-god (Sa) and crop-god (Jik). And it is the Earth god and the concrete entity, Sajik tree, that contains the legacy of sylvan religion descended from the ancient times and had been incorporated into the Confucian faith and ritual regime. Korean red pine as the Royal-Sajik tree played a critical role of sustaining the religio-political justification for the rule of the Joseon's Royalty. The religio-political symbolism of Korean red pine was represented in diverse ways. The same pine was used as the timber material of shrine buildings established for the national rituals under Neo-Confucian faith by the royal court of Joseon kingdom before the modern Korea. The symbolic role of pine had also been expressed in the forms of royal tomb forests, the Imposition Forest (Bongsan) for royal coffin timber (Whangjangmok), and the creation, protection, conservation and bureaucratic management of the pine forests in the Inner-four and Outer-four mountains for the capital fortress at Seoul, where the king and his family inhabit. The religio-political management system of pine forests parallels well with the kingdom's economic forest management system, called "Pine Policy", with an array of pine cultivation forests and Prohibition Forests (Geumsan) in the earlier period, and that of Imposition Forests in the later period. The royal pine culture with the economic forest management system had influenced on the public consciousness and the common people seem to have coined Malrimgat, a pure Korean word that is interchangeable with the Chinesecharacter words of prohibition-cultivation land or forest (禁養地, 禁養林) practiced in the royal tomb forests, and Prohibition and Imposition Forests, which contained prohibition landmarks (Geumpyo) made of stone and rock on the boundaries. A culturo-social forestry, in which Sajik altar, royal tomb forests, Whangjang pine Prohibition and Imposition forests and the capital Inner-four and Outer-four mountain forests consist, was being put into practice in Joseon. In Joseon dynastry, the Neo-Confucian faith and royal rituals with geomancy, folk religion, and Buddhism incorporated has also played a critical humanistic role for the culturo-social pine forestry, the one higher in values than that of the economic pine forestry. The implications have been extracted from the historical case study on the Royal-Sajik tree and culturo-social forestry of Joseon : Cultural sustainability, in which the interaction between humans and environment maintains a long-term culturo-natural equilibrium or balance for many generations, emphasizes the importance that the modern humans who form and conserve environment need to rediscover and transform their culturo-natural legacy into conservation for many generations and produce knowledge of sustainability science, the transdisciplinary knowledge for the interaction between environment and humans, which fulfills the cultural, social and spiritual needs.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.220-237
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• 2021

This study carried out the conservation treatment for the mattress put on the bed, which is one of 4 items in National Folklore Cultural Heritage, the Red-lacquered Furniture with the inlaid mother-of-pearl design used by Empress Sunjeonghyo (presumed), after identifying the characteristics of the manufacturing techniques and the used materials. And the study intends to compare it with the mattress placed in the Daejojeong in the Changdeokgung Palace in order to identify the characteristics of mattresses domestically used during the 1920s and 1930s. From the analysis of the mattress presumably used by Empress Sunjeonghyo, it was identified that the mattress frame was made of pinaceous hemlock spruce while the webbing and twine in the structural parts were made of jute. The findings are as follows: the burlap had a filling material that was made of jute; the straw mat was made from Oryza; and, the rest of the filling material was cotton. Rayon was used for the top cover while cotton was used for the bottom. As a result of research on the materials and the inner structure, it was found that mattress was manufactured in the form of the upholstery style mainly found in chairs and day-beds in Western furniture. Based on analysis results, materials identical to the original were adopted during the conservation treatment. Next, the process of dismantling, cleaning, repair, reinforcement and assembling was conducted. During the dismantling process, the top cover was newly discovered and some letters (Yokohama, Kobe, and Joseon) were found in the burlap filling, but there was no trace which can clarify its maker or production place. dry cleaning was carried out on the structural parts, filling materials, and the cover, and then the repair and reinforcement were done, preserving the existing materials in the upholstery structure and using the same materials for conservation. The webbing in the structural parts was reinforced using materials identical to the original, and the twine was used for arranging and fixing the springs into wooden frames. For the damaged cotton cloth and burlap, reinforcement materials identical to the original were put over it and sown. For the damaged area of the top cover, reinforcement cloth was cut and then added inside and the damaged area was sown. Assembling was carried out in the reverse order of the dismantling. After the burlap identical to the original material was inserted into the areas in contact with the springs and then fastened, a filling pad, reinforcement cloth, a straw mat, cotton cloth, cotton felt, wide cotton cloth for protecting the cover, and the cover were layered and fastened with tacks. The two mattresses used by Empress Sunjeonghyo differed only by the period of production and followed the same Western upholstery style consisting of the frames, filling materials, and covers. During the conservation treatment process, a velvet cover was newly discovered and the traces of repair in the past were found. Furthermore, identifying straw mats, straw bags, and straws for filling material, this study confirmed changes in the materials used according to the production environment. In the future, it is expected to see changes in the conservation materials during the conservation treatment and manufacturing techniques used for chairs and sofas in the upholstery style belonging to the modern cultural artifacts.

• Journal of the Daesoon Academy of Sciences
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• v.29
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• pp.71-100
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• 2017

This study focuses on examining 'the Supreme God and Celestial Worthy of the Ninth Heaven Who Spreads the Sound of the Thunder Corresponding to Primordial Origin', which Daesoon Jinrihoe believes in as the highest divinity. The name of this divinity was first found in Chinese Daoist scriptures. This study starts by considering the global propagation of virtue and then research connected to this topic. There are two alternative names for this divinity in relation to his human avatar, Kang Jeungsan, the subject of faith in Daesoon Jinrihoe. One is 'the Lord God of Great Creation in the Ninth Heaven' meaning the divinity before assuming a human avatar, and the other is 'the Celestial Worthy of Universal Transformation' the same divinity after he discarded his human avatar and returned to his celestial post. To understand how the belief system of Daesoon Jinrihoe differs from that of Daoism, it is necessary to study the divinity's change from being 'the Lord God of Great Creation in the Ninth Heaven' to becoming 'the Celestial Worthy of Universal Transformation'. If this distinction is not made clear, it brings about confusing arguments concerning the term 'Supreme God (Sangje)' as used in Daoism and Daesoon Jinrihoe. In order to offer a specific explanation, this study suggests three possible directions. The first hypothesis is that although these two names, 'the Celestial Worthy of the Ninth Heaven Who Spreads the Sound of the Thunder Corresponding to Primordial Origin' from Daoism and 'the Supreme God of the Ninth Heaven Who Spreads the Sound of the Thunder Corresponding to Primordial Origin' from Daesoon Jinrihoe, are similar, they actually have nothing to do with one another. The second hypothesis is that they are in fact the same divinity. Lastly, the third hypothesis is that they are closely connected, however, the former (the Celestial Worthy of the Ninth Heaven Who Spreads the Sound of the Thunder Corresponding to Primordial Origin) is a position needed to fulfill the mission of Jeungsan, whereas the latter (the Supreme God of the Ninth Heaven Who Spreads the Sound of the Thunder Corresponding to Primordial Origin) is a name received after the human avatar passes and the deity returns to the Noebu, 'the department of lightning'. These hypotheses face certain problems such as arbitrary mixing, the need for the theoretical clarity, and argumental weakness. Therefore, by leaving some unresolved questions, this study encourages future follow-up studies.