• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.51-56
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• 2019

Purpose: The usefulness of using single-electron radiation for secondary radiotherapy of breast cancer patients after surgery is assessed and the use of a combine of different energy. Methods and materials : In this study, 40 patients (group A) using energy 6 MeV and 9 MeV, and 19 patients (group B) using a combine of 9 MeV and 12 MeV were studied among 59 patients who performed secondary care using combine electronic radiation. Each patient in each group, 6 MeV, 9 MeV, Combine(6 MeV / 9 MeV) and 9 MeV, 12 MeV, Combine (9 MeV / 12 MeV) were developed in different ways, and the maximum doses delivered to the original hospital, D95, D5, and $V_3$, $V_5$, $V_{10}$ were compared. Result: The D95 mean value of Group A treatment plan was $785.33{\pm}225.37cGy$, $1121.79{\pm}87.02cGy$ at 9 MeV, and $1010.98{\pm}111.17cGy$ at 6 MeV / 9 MeV, and the mean value at 6 MeV / 9 MeV was most appropriate for the dose. The mean values of the low dose area $V_3$ and $V_5$ in the lung of the breast direction being treated were $3.24{\pm}3.49%$ and $0.72{\pm}1.55%$ at 6 MeV, the highest 9 MeV at $7.25{\pm}4.59%$, $3.07{\pm}2.64%$, the lowest at 6 MeV. Maximum and average lung dose was $727.78{\pm}137.27cGy$ at 6 MeV / 9 MeV, $49.16{\pm}24.44cGy$, highest 9 MeV at $998.97{\pm}114.35cGy$, $85.33{\pm}41.18cGy$, and lowest 6 MeV at $387.78{\pm}208.88cGy$, $9.27{\pm}6.60cGy$. The value of $V_{10}$ was all close to zero. Group B appeared in the pattern of Group A. Conclusion: Relative differences in low-dose areas of the lungs $V_3$ and $V_5$ were seen and were most effective in the dose transfer of tumor bed in the application of combined energy. It is thought that the method of using electronic energy in further radiation treatments for breast cancer is a more effective way to use the energy effect of limiting energy resources, and that if you think about it again, it could be a little more beneficial radiation treatment for patients.

• Korean Journal of Heritage: History & Science
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• v.42 no.3
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• pp.4-24
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• 2009

This paper examined archaeological resources that discuss how Silla entered the Gangneung area, the coastal region along the East Sea that has been excavated most actively. Silla expanded its territories while organizing the its system as an ancient state and acquired several independent townships in various regions, stretching its forces to the East Sea area faster than any other ancient states of the time. In particular, many early relics and heritages of Silla have been found in Gangneung, the center of the East Sea area. Many archaeological resources prove these circumstances of that time and provide brief texts that are valuable for our interpretation of historical facts. In this respect, it was possible for me to examine these resources to answer my question as to why early relics and heritages of Silla are found in the Gangneung area. Based on my research on Silla's advancement into the Gangneung area, I have acquired the following results: How did Silla rule this area after conquering Yeguk in the Gangneung area? After conquering the Gangneung area, Silla attempted an indirect ruling at first. Later, Silla adopted a direct ruling system. I divided the indirect ruling period into two phases: introduction and settlement. In detail, Silla's earthenware and stone chamber tombs first appeared in Hasi-dong in the fourth quarter of the 4th Century and the tombs spread to Chodang-dong in the second quarter of the 5th Century. A belt with dragon pattern openwork, which seems to be from the second quarter of the 5th Century, was found to tell us that the Gangneung region began receiving rewards from Silla during this time. Thus, the period from the fourth quarter of the 4th Century to the second quarter of the 5th Century is designated as the 1st Phase (Introduction) of indirect ruling in terms of aechaeological findings. This is when Silla was first advanced to the Gangneung area and tolerated independent administration of the conquered. In the third and fourth quarters of the 5th Century, old mound tombs appeared and burials of relics that symbolized power emerged. In the third quarter of the 5th Century, stone chamber tombs were prevalent, but wooden chamber tombs, stone mounded wooden chamber tombs, and lateral entrance stone chamber tombs began to emerge. Also, tombs that were clustered in Hasi-dong and Chodang-dong began to scatter to Byeongsan-dong, Yeongjin-ri, and Bangnae-ri nearby. Steel pots were the symbol of power that emerged at this time. In the fourth quarter of the 5th Century, stone chamber tombs were still dominating, but wooden chamber tombs, stone mounded wooden chamber tombs, and lateral entrance stone chamber tombs became more popular. More crowns, crown ornaments, big daggers, and belts were bestowed by Silla, mostly in Chodang-dong and Byeongsan-dong. The period from the third quarter to the fourth quarter of the 5th Century was designated as the 2nd Phase (Settlement) of indirect ruling in terms of aechaeological findings. At this time, Silla bestowed items of power to the ruling class of the Gangneung area and gave equal power to the rulers of Chodang-dong and Byeongsan-dong to keep them restrained by each other. However, Silla converted the ruling system to direct ruling once it recognized the Gangneung area as the base of its expedition of conquest to the north. In the first quarter of the 6th Century, old mound tombs disappeared and small/medium-sized mounds appeared in the western inlands and the northern areas. In this period, the tunnel entrance stone chamber tombs were large enough for people to enter with doors. A cluster of several tunnel entrance stone chamber tombs was formed in Yeongjin-ri and Bangnae-ri at this time, probably with the influence of Silla's direct ruling. In the first quarter of the 6th Century, Silla dispatched officers from the central government to complete the local administration system and replaced the ruling class of Chodang-dong and Byeongsan-dong with that of Silla-friendly Yeonjin-ri and Bangnae-ri to reorganize the local administration system and gain full control of the Gangneung area.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Heritage: History & Science
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• v.49 no.2
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• pp.86-103
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• 2016

'Sukchunjeahdo' illustration-book, which was left by Han, Pil-gyo(韓弼敎 : 1807~1878)in the late Joseon Dynasty, includes pictorial record paintings containing government offices, Eupchi, and Feng Shui condition drawn by Gyehwa(界畵) method Sabangjeondomyobeop(四方顚倒描法) and is the rare historical material that help to understand spatial structure and landscape characteristics. Youngyuhyun(永柔縣) and Sincheongun(信川郡) town, the case sites of this study, show Feng Shui foundation structure and placement rules of government offices in the Joseon Period are applied such as 3Dan 1Myo(三壇一廟 : Sajikdan, Yeodan, Seonghwangdan, Hyanggyo), 3Mun 3Jo(三門三朝 : Oeah, Dongheon, Naeah) and Jeonjohuchim(前朝後寢) etc. by setting the upper and lower hierarchy of the north south central axis. The circulation system is the pattern that roads are segmented around the marketplace of the entrance of the town and the structure is that heading to the north along the internal way leads to the government office and going out to the main street leads to the major city. Baesanimsu(背山臨水 : Mountain in backward and water in front) foundation, back hill pine forest, intentionally created low mountains and town forest etc. showed landscape aesthetics well suited for the environmental comfort condition such as microclimate control, natural disaster prevention, psychological stability reflecting color constancy principle etc. and tower pavilions were built throughout the scenic spot, reflecting life philosophy and thoughts of contemporaries such as physical and mental discipline, satisfied at the reality of poverty, returning to nature etc. For government office landscape, shielding and buffer planting, landscape planting etc. were considered around Gaeksa(客舍), Dongheon(東軒), Naeah(內衙) backyard and deciduous tree s and flowering trees were cultivated as main species and in case of Gaeksa, tiled pavilions and pavilions topped with poke weed in tetragonal pond were introduced to Dongheon and Naeah and separate pavilions were built for the purpose of physical and mental discipline and military training such as archery. Back hill pine tree forest formed back landscape and zelkova, pear trees, willow trees, old pine trees, lotus, flowering trees etc. were cultivated as gardening trees and Feng-Shui forest with willow trees as its main species was created for landscape and practical purposes. On the other hand, various cultural landscape elements etc. were introduced such as pavilions, pond serving as fire protection water(square and circle), stone pagoda and stone Buddha, fountains and wells, monument houses, flagpoles etc. In case of Sincheongun town forest(邑藪), Manhagwan(挽河觀), Moonmujeong(文武井), Sangjangdae(上場岱) and Hajangdae(下場岱) Market place, Josanshup<(造山藪 : Dongseojanglim(東西長林)>, Namcheon(南川) etc. were combined and community cultural park with the nature of modern urban park was operated. In this context, government office landscape shows the garden management aspect where square pond and pavilions, flowering trees are harmonized around side pavilion and backyard. Also, environmental design technique not biased to aesthetics and ideological moral philosophy and comprehensively considering functionality (shielding and fire prevention, microclimate control, etc.) and environmental soundness etc. is working.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.93-109
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• 2020

Purpose: The radiochromic film (Gafchromic EBT3, Ashland Advanced Materials, USA) and 3-dimensional analysis system dosimetry checkTM (DC, MathResolutions, USA) were evaluated for patient-specific quality assurance (QA) of helical tomotherapy. Materials and Methods: Depending on the tumors' positions, three types of targets, which are the abdominal tumor (130.6㎤), retroperitoneal tumor (849.0㎤), and the whole abdominal metastasis tumor (3131.0㎤) applied to the humanoid phantom (Anderson Rando Phantom, USA). We established a total of 12 comparative treatment plans by the four geometric conditions of the beam irradiation, which are the different field widths (FW) of 2.5-cm, 5.0-cm, and pitches of 0.287, 0.43. Ionization measurements (1D) with EBT3 by inserting the cheese phantom (2D) were compared to DC measurements of the 3D dose reconstruction on CT images from beam fluence log information. For the clinical feasibility evaluation of the DC, dose reconstruction has been performed using the same cheese phantom with the EBT3 method. Recalculated dose distributions revealed the dose error information during the actual irradiation on the same CT images quantitatively compared to the treatment plan. The Thread effect, which might appear in the Helical Tomotherapy, was analyzed by ripple amplitude (%). We also performed gamma index analysis (DD: 3mm/ DTA: 3%, pass threshold limit: 95%) for pattern check of the dose distribution. Results: Ripple amplitude measurement resulted in the highest average of 23.1% in the peritoneum tumor. In the radiochromic film analysis, the absolute dose was on average 0.9±0.4%, and gamma index analysis was on average 96.4±2.2% (Passing rate: >95%), which could be limited to the large target sizes such as the whole abdominal metastasis tumor. In the DC analysis with the humanoid phantom for FW of 5.0-cm, the three regions' average was 91.8±6.4% in the 2D and 3D plan. The three planes (axial, coronal, and sagittal) and dose profile could be analyzed with the entire peritoneum tumor and the whole abdominal metastasis target, with planned dose distributions. The dose errors based on the dose-volume histogram in the DC evaluations increased depending on FW and pitch. Conclusion: The DC method could implement a dose error analysis on the 3D patient image data by the measured beam fluence log information only without any dosimetry tools for patient-specific quality assurance. Also, there may be no limit to apply for the tumor location and size; therefore, the DC could be useful in patient-specific QAl during the treatment of Helical Tomotherapy of large and irregular tumors.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.15-24
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• 2021

Purpose SPECT/CT was noted for its excellent correction method and qualitative functions based on fusion images in the early stages of dissemination, and interest in and utilization of quantitative functions has been increasing with the recent introduction of companion diagnostic therapy(Theranostics). Unlike PET/CT, various conditions like the type of collimator and detector rotation are a challenging factor for image acquisition and reconstruction methods at absolute quantification of SPECT/CT. Therefore, in this study, We want to find out the effect on the radioactivity concentration estimate by the increase or decrease of the total acquisition time according to the number of projections and the acquisition time per projection among SPECT/CT imaging conditions. Materials and Methods After filling the 9,293 ml cylindrical phantom with sterile water and diluting 99mTc 91.76 MBq, the standard image was taken with a total acquisition time of 600 sec (10 sec/frame × 120 frames, matrix size 128 × 128) and also volume sensitivity and the calibration factor was verified. Based on the standard image, the comparative images were obtained by increasing or decreasing the total acquisition time. namely 60 (-90%), 150 (-75%), 300 (-50%), 450 (-25%), 900 (+50%), and 1200 (+100%) sec. For each image detail, the acquisition time(sec/frame) per projection was set to 1.0, 2.5, 5.0, 7.5, 15.0 and 20.0 sec (fixed number of projections: 120 frame) and the number of projection images was set to 12, 30, 60, 90, 180 and 240 frames(fixed time per projection:10 sec). Based on the coefficients measured through the volume of interest in each acquired image, the percentage of variation about the contrast to noise ratio (CNR) was determined as a qualitative assessment, and the quantitative assessment was conducted through the percentage of variation of the radioactivity concentration estimate. At this time, the relationship between the radioactivity concentration estimate (cps/ml) and the actual radioactivity concentration (Bq/ml) was compared and analyzed using the recovery coefficient (RC_Recovery Coefficients) as an indicator. Results The results [CNR, radioactivity Concentration, RC] by the change in the number of projections for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.5%, +3.90%, 1.04] at -90%, [-77.9%, +2.71%, 1.03] at -75%, [-55.6%, +1.85%, 1.02] at -50%, [-33.6%, +1.37%, 1.01] at -25%, [-33.7%, +0.71%, 1.01] at +50%, [+93.2%, +0.32%, 1.00] at +100%. and also The results [CNR, radioactivity Concentration, RC] by the acquisition time change for each increase or decrease rate (-90%, -75%, -50%, -25%, +50%, +100%) of total acquisition time are as follows. [-89.3%, -3.55%, 0.96] at - 90%, [-73.4%, -0.17%, 1.00] at -75%, [-49.6%, -0.34%, 1.00] at -50%, [-24.9%, 0.03%, 1.00] at -25%, [+49.3%, -0.04%, 1.00] at +50%, [+99.0%, +0.11%, 1.00] at +100%. Conclusion In SPECT/CT, the total coefficient obtained according to the increase or decrease of the total acquisition time and the resulting image quality (CNR) showed a pattern that changed proportionally. On the other hand, quantitative evaluations through absolute quantification showed a change of less than 5% (-3.55 to +3.90%) under all experimental conditions, maintaining quantitative accuracy (RC 0.96 to 1.04). Considering the reduction of the total acquisition time rather than the increasing of the image acquiring time, The reduction in total acquisition time is applicable to quantitative analysis without significant loss and is judged to be clinically effective. This study shows that when increasing or decreasing of total acquisition time, changes in acquisition time per projection have fewer fluctuations that occur in qualitative and quantitative condition changes than the change in the number of projections under the same scanning time conditions.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.200-211
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• 2022

The celadon stools with an openwork ring design which consist of four items as one collection were excavated from Gaeseong, Gyeonggi-do Province. The celadon stools were designated and managed as treasures due to their high arthistorical value in the form of demonstrating the excellence of celadon manufacturing techniques and the fanciful lifestyles during the Goryeo Dynasty. However, one of the items, which appeared to have been repaired and restored in the past, suffered a decline in aesthetic value due to the aging of the treatment materials and the lack of skill on the part of the conservator, raising the need for re-treatment as a result of structural instability. An examination of the conservation condition prior to conservation treatment found structural vulnerabilities because physical damage had been artificially inflicted throughout the area that was rendered defective at the time of manufacturing. The bonded surfaces for the cracked areas and detached fragments did not fit, and these areas and fragments had deteriorated because the adhesive trickled down onto the celadon surface or secondary contaminants, such as dust, were on the adhesive surface. The study identified the position, scope, and conditions of the bonded areas at the cracks UV rays and microscopy in order to investigate the condition of repair and restoration. By conducting Fourier-transform infrared spectroscopy(FT-IR) and portable x-ray fluorescence spectroscopy on the materials used for the former conservation treatment, the study confirmed the use of cellulose resins and epoxy resins as adhesives. Furthermore, the analysis revealed the addition of gypsum(CaSO₄·2H₂O) and bone meal(Ca₁₀ (PO₄)₆(OH)₂) to the adhesive to increase the bonding strength of some of the bonded areas that sustained force. Based on the results of the investigation, the conservation treatment for the artifact would focus on completely dismantling the existing bonded areas and then consolidating vulnerable areas through bonding and restoration. After removing and dismantling the prior adhesive used, the celadon stool was separated into 6 large fragments including the top and bottom, the curved legs, and some of the ring design. After dismantling, the remaining adhesive and contaminants were chemically and physically removed, and a steam cleaner was used to clean the fractured surfaces to increase the bonding efficacy of the re-bonding. The bonding of the artifact involved applying the adhesive differently depending on the bonding area and size. The cyanoacrylate resin Loctite 401 was used on the bonding area that held the positions of the fragments, while the acrylic resin Paraloid B-72 20%(in xylene) was treated on cross sections for reversibility in the areas that provided structural stability before bonding the fragments using the epoxy resin Epo-tek 301-2. For areas that would sustain force, as in the top and bottom, kaolin was added to Epo-tek 301-2 in order to reinforce the bonding strength. For the missing parts of the ring design where a continuous pattern could be assumed, a frame was made using SN-sheets, and the ring design was then modeled and restored by connecting the damaged cross section with Wood epos. Other restoration areas that occurred during bonding were treated by being filled with Wood epos for aesthetic and structural stabilization. Restored and filled areas were color-matched to avoid the feeling of disharmony from differences of texture in case of exhibitions in the future. The investigation and treatment process involving a variety of scientific technology was systematically documented so as to be utilized as basic data for the conservation and maintenance.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.101-118
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• 2023

During the COVID-19 pandemic, the utilization rate of neighborhood parks and green spaces increased significantly, and the outbreak served as an opportunity to highlight the values and functions of neighborhood parks and green spaces for urban residents. This study aims to empirically analyze how citizens' movement and the use of neighborhood parks and green spaces changed before and after COVID-19 and examine the social and spatial characteristics that affected these changes. As a research method, first, people's mobility around neighborhood parks and green spaces before and after the COVID-19 pandemic were compared using signal data from telecommunication carriers. Through the analysis of changes in residence time and movement volume, the movement characteristics of citizens after COVID-19 and changes in walking-based park visits were examined. Second, the factors affecting the mobility change in neighborhood parks and green spaces were analyzed. The social and spatial characteristics that affect citizens' visits to neighborhood parks and green spaces before and after COVID-19 were examined through correlation and multiple regression analysis. Subsequently, through cluster analysis, the types of living areas for the post-COVID era were classified from the perspective of the supply and management of neighborhood parks and green spaces services, and directions for improving neighborhood parks and green spaces by type were presented. Major research findings are as follows: First, since the outbreak of COVID-19, activities within 500m of the residence have increased. The amount of stay and walking movement increased in both 2020 and 2021, which means that the need to review the quantitative standards and attractions of neighborhood parks and green spaces has increased considering the changed scope of the walking and living area. Second, the overall number of visits to neighborhood parks and green spaces by walking has increased since the outbreak of COVID-19. The number of visits to neighborhood parks and green spaces centered on the house and the workplace increased significantly. The park green policy in the post-COVID era should be promoted by discovering underprivileged areas, focusing on areas where residential, commercial, and business facilities are concentrated, and improving neighborhood parks and green services in quantitative and qualitative terms. Third, it was found that the higher the level of park green service, the higher the amount of walking movement. It is necessary to use indicators that contribute to improving citizens' actual park green services, such as walking accessibility, rather than looking at the criteria for securing green areas. Fourth, as a result of cluster analysis, five types of neighborhood parks and green spaces were derived in response to the post-COVID era. This suggests that it is necessary to consider the socioeconomic status and characteristics of living areas and the level of park green services required in future park green policies. This study has academic and policy significance in that it has laid the basis for establishing neighborhood parks and green spaces policy in response to the post-COVID era by using various analysis methodologies such as carrier signal data analysis, GIS analysis, and statistical analysis.