• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.43-50
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• 2014

In case of all patients who receive radiation therapy, a treatment plan is established and all steps of treatment are planned in the same geometrical condition. In case of head and neck cancer patients who undergo simulated treatment through computed tomography (CT), patients are fixed onto a table for planning, but laid on the top of the treatment table in the radiation therapy room. This study excogitated and fabricated an adjustable holder for head and neck cancer patients to fix patient's position and geometrical discrepancies when performing radiation therapy on head and neck cancer patients, and compared the error before and after adjusting the position of patients due to difference in weight to evaluate the correlation between patients' weight and range of error. Computed tomography system(High Advantage, GE, USA) is used for phantom to maintain the supine position to acquire the images of the therapy site for IMRT. IMRT 4MV X-rays was used by applying the LINAC(21EX, Varian, U.S.A). Treatment planning system (Pinnacle, ver. 9.1h, Philips, Madison, USA) was used. The setup accuracy was compared with each measurement was repeated five times for each weight (0, 15, and 30Kg) and CBCT was performed 30 times to find the mean and standard deviation of errors before and after the adjustment of each weight. SPSS ver.19.0(SPSS Inc., Chicago, IL,USA) statistics program was used to perform the Wilcoxon Rank test for significance evaluation and the Spearman analysis was used as the tool to analyze the significance evaluation of the correlation of weight. As a result of measuring the error values from CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.4{\pm}0.8mm$, $0.8{\pm}0.4mm$, 0 for 0Kg before the adjustment. In 15Kg CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.2{\pm}0.8mm$, $1.2{\pm}0.4mm$, $2.0{\pm}0.4mm$. After adjusting position was X,Y,Z axis was $0.2{\pm}0.4mm$, $0.4{\pm}0.5mm$, $0.4{\pm}0.5mm$. In 30Kg CBCT before and after adjusting the position due to the weight difference, X,Y,Z axis was $0.8{\pm}0.4mm$, $2.4{\pm}0.5mm$, $4.4{\pm}0.8mm$. After adjusting position was X,Y,Z axis was $0.6{\pm}0.5mm$, $1.0{\pm}0mm$, $0.6{\pm}0.5mm$. When the holder for the head and neck cancer was used to adjust the ab.0ove error value, the error values from CBCT were $0.2{\pm}0.8mm$ for the X axis, $0.40{\pm}0.54mm$ for Y axis, and 0 for Z axis. As a result of statistically analyzing each value before and after the adjustment the value was significant with p<0.034 at the Z axis with 15Kg of weight and with p<0.038 and p<0.041 at the Y and Z axes respectively with 30Kg of weight. There was a significant difference with p<0.008 when the analysis was performed through Kruscal-Wallis in terms of the difference in the adjusted values of the three weight groups. As it could reduce the errors, patients' reproduction could be improved for more precise and accurate radiation therapy. Development of an adjustable device for head and neck cancer patients is significant because it improves the reproduction of existing equipment by reducing the errors in patients' position.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Journal of Korean Historical Folklife
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• no.52
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• pp.7-46
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• 2017

The elderly in the Joseon Dynasty consistently attracted attention from the national herb as objects of social respect. Based on the Confucian ideology, the old man was considered to be a receiving body, since he was a person with complete character as a man. The elderly, who have the character of being a slave, transcended their status, and both the souls and the people were transcended beyond their identities and attributes and became objects of respect. The perception of the elderly is divided by age. The persons who are 50 years old and start to be in physical decline were regarded as senior citizens. However, this was just mentioned as an inflection point between the prime of manhood and senior citizens and was not defined as the elderly. As a public duty called a national work ends when they are 60 years old, the age is truly the lowest limit of senior citizens who are applicable to all the social beings. However, because their public duties end when they are 60 years old and they were regarded as general members of society, special benefits were not granted to them. In the caste system and bureaucratic society, senior citizens' treatment were differently done by age. For the senior citizens who are 70 years old, various benefits were just granted to high government officials. Bokho(復戶) and Seojeong were first given to them. And the retirement age of government officials was not specially set. It was done in the way to treat Jonno with exceptional respect by Chisa(致仕: regular retirement). It is the most respectful treatment given to high government officials and ministers. For the senior citizens who are 80 years old, Yangnoyeon(養老宴) was held for both of Yangmin and Cheonmin as an measure to treat them considerately. In addition, official ranks(官品) with social value were allowed by giving them Noinjik (老人職). Official ranks given to Seoin and Cheonin were the best Jonno(尊老) policy. However, the Jonno policy related to senior citizens was different according to position and official ranks as follows: Kings were subjected to social treatment when they were 60 years old. High government officials and royal relatives of the senior grade of the second court rank were subjected to social treatment when they were 70 years old. And general Seoin and slaves were subjected to social treatment when they were respectively 80 and 90 years old. Senior citizens were individually supported. However, social value was granted because the nation supervised it. As Bokho and Sijeong were assigned according to position and official ranks and kinds of things were different, the social limit was clearly shown. Social order was put above the ideology called Jonno thought. However, Jonno acts by age and position did not stay at the individual level and the nation took care of the senior citizens who are the members of society in various ways based on Jonno thought. Society tried to take care of the senior citizens who had difficulties in their activities because of being in physical decline. The nation increased the existence value of the senior citizens by giving things(賜物) including chairs, rice, meat, and ice economically, exoneration(免罪), the reduction system, and wergild legally, and Noinjik called Gaja(加資) socially to them and changing them to the members of society. Yangnoyeon and Gaja held targeting people of every class by transcending position and official ranks make the point that the senior citizens who are more than 80 years old are subject to social jonno clear. That is, the senior citizens were subject to respect for the elderly as the persons who were socially respected transcending their position when they got to be 80 years old.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.4
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• pp.58-67
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• 2020

The present study was conducted as part of basic research for selecting species of street trees with historical value in Seoul. It also made up a list of traditional landscape trees for a variety of alternatives. The following results are shown below. As to the history of street trees in Korea, records on to-be-estimated street trees are found in historical documents written in King Yangwon during the second year of Goguryeo Dynasty (546) and King Myeongjong during 27 year of Goryeo (1197). However, it is assumed that lack of clarity is found in historical records. During the 23 year of King Sejong in the early Joseon Dynasty (1441), the record showed that the state planted street trees as guideposts on the postal road. The records revealed that Ulmus spp. and Salix spp. were planted as guidance trees. The street tree system was performed in the early Joseon Dynasty as recorded in the first year of King Danjong document. Pinus densiflora, Pinus koraiensis, Pyrus pyrifolia var. culta, Castanea crenata, Styphnolobium japonicum and Salix spp. were planted along the avenue at both left and right sides. Morus alba were planted on streets during the five year of King Sejo (1459). As illustrated in pieces Apgujeong by painter Jeongseon and Jinheonmajeongsaekdo in the reign of King Yeongjo, street trees were planted. This arrangement is associated with a number of elements such as king procession, major entrance roads in Seoul, place for horse markets, prevention of roads from flood and indication. In the reign of King Jeongjo, there are many cases related to planting Pinus densiflora, Abies holophylla and Salix spp. for king procession. Turning king roads and related areas into sanctuaries is considered as technique for planting street trees. During the 32 year of King Gojong after opening ports (1985), the state promoted planting trees along both sides of roads. At the time, many Populus davidiana called white poplars were planted as rapidly growing street trees. There are 17 taxa in the Era of Three Kingdoms records, 31 taxa in Goryeo Dynasty records and 55 taxa in Joseon Dynasty records, respectively, described in historical documents to be available for being planted as street trees in Seoul. 16 taxa are recorded in three periods, which are Era of Three Kingdoms, Goryeo Dynasty and Joseon Dynasty. These taxa can be seen as relatively excellent ones in terms of historical value. The introduction of alien plants and legal improvement in the Japanese colonial period resulted in modernization of street tree planting system. Under the six-year street tree planting plan (1934-1940) implemented as part of expanding metropolitan areas outside the capital launched in 1936, four major street trees of top 10 taxa were a Populus deltoides, Populus nigra var. italica, Populus davidiana, Populus alba. The remaining six trees were Salix babylonica, Robinia pseudoacacia, platanus orientalis, Platanus occidentalis, Ginkgo biloba, and Acer negundo. Beginning in the mid- and late 1930s, platanus orientalis, Platanus occidentalis were introduced into Korea as new taxa of street trees and planted in many regions. Beginning on 1942, Ailanthus altissima was recommended as street trees for the purpose of producing silks. In 1957 after liberation, major street tree taxa included Platanus occidentalis, Ginkgo biloba, Populus nigra var. italica, Ailanthus altissima, Populus deltoides and Salix babylonica. The rank of major street tree species planted in the Japanese colonial period had changed. Tree planting trend around that period primarily representing Platanus occidentalis and Ginkgo biloba still holds true until now.

• Tuberculosis and Respiratory Diseases
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• v.59 no.3
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• pp.286-297
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• 2005

Background : Non-small cell lung cancer (NSCLC) is a common cause of cancer-related death in North America and Korea, with an overall 5-year survival rate of between 4 and 14%. The TNM staging system is the best prognostic index for operable NSCLC . However, epidermal growth factor receptor (EGFR), matrix metalloproteinase-9(MMP-9), and C-erbB-2 have all been implicated in the pathogenesis of NSCLC and might provide prognostic information. Methods : Immunohistochemical staining of 81 specimens from a resected primary non-small cell lung cancer was evaluated in order to determine the role of the biological markers on NSCLC . Immunohistochemical staining for EGFR, MMP-9, and C-erbB-2 was performed on paraffin-embedded tissue sections to observe the expression pattern according to the pathologic type and surgical staging. The correlations between the expression of each biological marker and the survival time was determined. Results : When positive immunohistochemical staining was defined as the extent area>20%(more than Grade 2), the positive rates for EGFR, MMP-9, and C-erbB-2 staining were 71.6%, 44.3%, and 24.1% of the 81 patients, respectively. The positive rates of EGFR and MMP-9 stain for NSCLC according to the surgical stages I, II, and IIIa were 75.0% and 41.7%, 66.7% and 47.6%, and 76.9% and 46.2%, respectively. The median survival time of the EGFR(-) group, 71.8 months, was significantly longer than that of the EGFR(+) group, 33.5 months.(p=0.018, Kaplan-Meier Method, log-rank test).. The MMP-9(+) group had a shorter median survival time than the MMP-9(-) group, 35.0 and 65.3 months, respectively (p=0.2). The co-expression of EGFR and MMP-9 was associated with a worse prognosis with a median survival time of 26.9 months, when compared with the 77 months for both negative-expression groups (p=0.0023). There were no significant differences between the C-erbB-2(+) and C-erbB-2 (-) groups. Conclusion : In NSCLC, the expression of EGFR might be a prognostic factor, and the co-expression of EGFR and MMP-9 was found to be associated with a poor prognosis. However, C-erbB-2 expression had no prognostic significance.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.4
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• pp.14-23
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• 2014

The purpose of this study is to contribute in building credibility of the methodology of the appearance of the traditional colors and the interpretation of the meaning of those appearances by analyzing the spatial construction and configuration and the traditional colors that appear in spatial elements about the scenery component that appear in Seyeonjeong. We conducted a literature research about the traditional colors, the background of the creation of Seyeonjeong, and etc. For the contents for the empirical analysis, we took the scenery and space elements in the poems, such as Eobusasisa and O-u-ga, and the contents of poems related to ojeongsaek (five Korean traditional colors) based on the Yin-Yang and the Five Elements ideology Particularly, after dividing the spatial elements appearing in Seyoenjeong into visual, synesthetic, symbolic/cognitive spatial element, we further distinguished the visual space into positions and directions of the of the spaces and the scenery of the season; the synesthetic space into seasons, time and five senses; and the symbolic/cognitive space into chiljeong (or the seven passions) and sadan (or the four clues). Then we carried out the study by analyzing the correlation between the intention of the garden creation and the meaning of the spaces, through the analysis of ojeongsaek system for each spatial element. Firstly, spatial structure and format that appear in Seyeonjeong can be divided into two directional axes of southeast and northwest according to the flat form of the Seyeongjeong's rectangular palace, with Seyeongjoeng as the center. Secondly, in spatial component element, the frequencies of appearance of the traditional colors of Seyoenjeong are 33.2% for white, 20.8% for blue, 20.8% for black, 18.7% for red and 6.3% for yellow. Thirdly, based on the analysis of the traditional colors the most frequent appearance of 'white' left a room for interpretation like the creation of Seyeonjeong was to enjoy secular living without lingering political feelings so that the high mountains remain clear and clean. Also, the predominant frequency of appearance of blue, similar frequency of appearance of black and red, and the least frequent appearance of yellow is in agreement with or can be at least interpreted related to Yun Seon-do's intention for creating Seyeonjeong not for political rank or power but as a place to enjoy nature, through which he can build on his knowledge, and to lead rest of his life as a noble being through plays, like dancing and writing poems. Fourthly, these interpretations of the analysis of the frequency of appearance of the traditional colors of Seyeongjong shows the reliability, validity, and consistency of the methodology of the analysis of the frequency of appearance of the traditional colors and the interpretation of the meanings in the context that the color white appears most frequently in Soswewon as well and that the background life of the Soswewon's creator Yangsanbo can be interpreted in a similarly way. Above all, this study is significant from the fact that we proposed a theory about the method of analysis and interpretation of the traditional colors in a traditional landscape space. Moreover, there is a great significance of discovering that traditional colors appear in traditional spaces and this can be used as a methodological framework to interpret things like, intention for creation of (buildings/architectures).

• Radiation Oncology Journal
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• v.15 no.4
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• pp.349-356
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• 1997

Purpose : To evaluate the efficacy of hyperfractionated radiation therapy in carcinoma of the cervix, especially on huge exophytic and endophytic stage Ib, IIa and IIb Materials and Materials : Fourty one patients with carcinoma of the cervix treated with hyperfractionated radiation therapy at the Department of Therapeutic Radiology, Dongsan Hospital, Keimyung University. School of Medicine from Jul, 1991 to Apr, 1994. According to FIGO s1aging system, therewere stage Ib (3 patients) IIa (6 patients) with exophytic ($\geq$5cm in dinmeter) and huge endophytic mass. and IIb (32 patients) with median age of 55 yeavs old. Radiation therapy consisted of hyperfractionated external irradition to the whole pelvis (120cGy/fraction, 2 fraction/day (minimum interval of 6 hours), 3600-5520cGy) and boost parametrial doses (for a total of 4480-6480cGy) with midline shield $(4\times10cm)$, and combined with intracavitary irradiation (up to 7480-8520cGy in Ib, IIa and 8480-9980cGy in IIb to point A). The maximum and mean follow up durations were 70 and 47 months respectively . Results : Five year local control rate was $78\%$ and the actuarial overall five year survival rate was $66.1\%$ for all patients, $44.4\%$ for stage Ib, IIa and $71.4\%$ for stage IIb. In bulky IIb (above 5cm in tumor size, 11 patients) five year local control rate and five rear survival rate was $88.9\%,\;73\%$ respectively Pelvic lymph node status (negative : $74\%,\;positive:25\%$, p=0.0015) was significant Prognostic factor affecting to five rear survival rate. There was marginally significant survival difference by total dose to A point ($>84Gy\;:\;70\%,\;>84Gy\;:\;42.8\%$, p=0.1). We consider that the difference of total dose to A point by stage (mean Ib,IIa : 79Gy. IIb 89Gy P=0.001) is one of the causes in worse local control and survival of Ib,IIa than IIb The overall recurrence rate was $39\%$ (16/41). The rates of local failure alone. distant failure alone. and combined local and distant failure were $9.7\%,\;19.5\%,\;and\;9.7\%$, respectively. Two Patients developed leukopenia ($\geq$ grade 3) and Three patients develoued grade 3 gastrointestinal complication. Above grade 3 complication was not noted. There was no treatment related death noted. Conclusion : We thought that it may be necessary to increase A point dose to more than 85Gy in hyperfractionated radiotherapy of huge exophytic and endophvtic stage Ib,IIa. We considered that hyperfractionated radiation therapy may be tolerable in huge exophytic and endophytic stage IIb cervical carcinoma with acceptable morbidity and possible survival gain but this was results in small patient group and will be confirmed by long term follow up in many patients.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.29-44
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• 2017

In Internet commerce, consumers are heavily influenced by product reviews written by other users who have already purchased the product. However, as the product reviews accumulate, it takes a lot of time and effort for consumers to individually check the massive number of product reviews. Moreover, product reviews that are written carelessly actually inconvenience consumers. Thus many online vendors provide mechanisms to identify reviews that customers perceive as most helpful (Cao et al. 2011; Mudambi and Schuff 2010). For example, some online retailers, such as Amazon.com and TripAdvisor, allow users to rate the helpfulness of each review, and use this feedback information to rank and re-order them. However, many reviews have only a few feedbacks or no feedback at all, thus making it hard to identify their helpfulness. Also, it takes time to accumulate feedbacks, thus the newly authored reviews do not have enough ones. For example, only 20% of the reviews in Amazon Review Dataset (Mcauley and Leskovec, 2013) have more than 5 reviews (Yan et al, 2014). The purpose of this study is to analyze the factors affecting the usefulness of online product reviews and to derive a forecasting model that selectively provides product reviews that can be helpful to consumers. In order to do this, we extracted the various linguistic, psychological, and perceptual elements included in product reviews by using text-mining techniques and identifying the determinants among these elements that affect the usability of product reviews. In particular, considering that the characteristics of the product reviews and determinants of usability for apparel products (which are experiential products) and electronic products (which are search goods) can differ, the characteristics of the product reviews were compared within each product group and the determinants were established for each. This study used 7,498 apparel product reviews and 106,962 electronic product reviews from Amazon.com. In order to understand a review text, we first extract linguistic and psychological characteristics from review texts such as a word count, the level of emotional tone and analytical thinking embedded in review text using widely adopted text analysis software LIWC (Linguistic Inquiry and Word Count). After then, we explore the descriptive statistics of review text for each category and statistically compare their differences using t-test. Lastly, we regression analysis using the data mining software RapidMiner to find out determinant factors. As a result of comparing and analyzing product review characteristics of electronic products and apparel products, it was found that reviewers used more words as well as longer sentences when writing product reviews for electronic products. As for the content characteristics of the product reviews, it was found that these reviews included many analytic words, carried more clout, and related to the cognitive processes (CogProc) more so than the apparel product reviews, in addition to including many words expressing negative emotions (NegEmo). On the other hand, the apparel product reviews included more personal, authentic, positive emotions (PosEmo) and perceptual processes (Percept) compared to the electronic product reviews. Next, we analyzed the determinants toward the usefulness of the product reviews between the two product groups. As a result, it was found that product reviews with high product ratings from reviewers in both product groups that were perceived as being useful contained a larger number of total words, many expressions involving perceptual processes, and fewer negative emotions. In addition, apparel product reviews with a large number of comparative expressions, a low expertise index, and concise content with fewer words in each sentence were perceived to be useful. In the case of electronic product reviews, those that were analytical with a high expertise index, along with containing many authentic expressions, cognitive processes, and positive emotions (PosEmo) were perceived to be useful. These findings are expected to help consumers effectively identify useful product reviews in the future.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.171-191
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• 2020

This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.