• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.

• Journal of Oral Medicine and Pain
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• v.35 no.4
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• pp.265-273
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• 2010

Understanding patients' expectation for health visits and providing appropriate care may increase patients' satisfaction with health care, leading to more positive treatment outcome. The study aimed to investigate expectations of the patients with temporomandibular disorders (TMD) at their first visit to university-based orofacial pain clinic and to evaluate any relation with duration of pain, presence of previous treatment, pain severity and pain interference. Inclusion criterion was patients aged over and 18 years old and diagnosed as TMD during 3 months' period from Aug to Nov 2010. They were asked to complete the questionnaires for patients' expectation and the Brief Pain Inventory (BPI) at waiting room prior to consultation. 322 TMD patients participated in the study(M:F=1:1.5, mean age=36 years old). The study indicated that the most important top 3 expectations were 'cure of pain', 'understanding their problem' and 'doctor-patient communication' in order. This finding was not affected by gender, duration and previous treatment history but affected by sub-category of TMD and BPI pain severity and pain interference. 'Pain relief' and 'understanding their problems' were relatively highlighted in the patients with muscle disorders and combination (joint-muscle) disorders of TMD than those with joint disorders who wanted communication and further investigation relatively more (p=0.000). While expectation for pain relief was expected more with increase of pain severity and interference, patients with mild level of pain severity and interference expected communication and further investigation relatively more (p=0.000, 0.017, respectively). Based on the results of the study, though pain relief was the primary concern for TMD patients suffering from pain, their satisfaction with care may be increased by explanation for etiology and mechanism of TMD to make them understand their problems better and doctor-patient communication and collaborative decision-making for treatment. Importance of patient-centered consultations and availability of written material or web sites for patient information should be stressed out.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.3
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• pp.67-75
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• 2017

The culture of Gugok (九曲) and Dongcheon (洞天), which tries to reach the ideological culmination in Confucianism, was widespread throughout the Joseon dynasty. This was an extension of the spirit of studying and honoring Zhu Xi (學朱子, 尊朱子); thereby, Confucian scholars in Joseon expressed the will to follow the teachings of Zhu Xi (朱子) and comforted themselves that they were in the course of attaining the truth. As a realization of this expression of will, scholars designated and operated various scenic sites as Gugoks, following the example of Zhu Xi's Mui Gugok (武夷九曲), and Dongcheons, as a representation of the utopia. These designations are widespread nationwide, with around sixty Gugok locations that have now been reported in academia. However, the actual number of Gugoks exceeds this number, and many of them are currently not identified concerning the exact locations. Therefore, the purpose of this study is to identify the locations of Gugoks and Dongcheons scattered around Seoul, Gyeonggi and Gangwon regions. For the coordinates of Gugoks and Dongcheons, this study referred to the literature, web search and the books published by local cultural institutes. Based on the collected information, the researchers conducted field trips to investigate whether the record exists as a real location and, if so, acquired their coordinates. This study also provides the tables of Gugok or Dongcheon that only exists in the imagination, existed before but now are lost, or are inaccessible. Eight locations in Seoul, Gyeonggi, and Gangwon regions are understood as Gugok. Among them, Gogun Gugok and Okgye Gugok have relatively clear locations and records. Byeokgye Gugok and Suhoe Gugok, on the other hand, has many locations and titles overlapped, and their established time and managers are unclear. As for Ui Gugok in Seoul, it is known to be set by Hong Yangho, but some parts of its locations are confirmed, others are in dispute, and many locations are damaged. Thirty-eight locations in Seoul, Gyeonggi, and Gangwon regions are understood as Dongcheon. There are sixteen Dongcheons in Seoul area. Among them, those including Dohwa Dongcheon, Yangsan Dongcheon, and Ssangnyu Dongcheon actually exist but are forbidden to be accessed. There are thirteen Dongcheons in Gyeonggi area. The exact location of Onsu Dongcheon cannot be confirmed because of the development; Gwirae Dongcheon has historical records, but the actual existence cannot be confirmed. There are nine Dongcheons in Gangwon area. The researcher judged that Hwaeum Dongcheon is the misspelled record of Hwaeumdong Jeongsaji (華陰洞精舍址), which is located at the upstream of Gogun Gugok.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.

• Korean journal of communication and information
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• v.32
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• pp.113-146
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• 2006

This study explored how media and interpersonal communication affected voters in Busan mayoral by-election, focusing on the mutual relations among media use and attentive use of political campaign, interpersonal communication, and voting participation. Also, comparative analysis between image factor and the factor of political party influencing the decision of a candidate were examined. Additionally, it was analysed differential media effects on candidates' image. According to the results, the local media use and attentive use of political campaign had the influence on the increase of interpersonal communication about the election. Voters who had much interpersonal discussion with others participated more than voters who had less interpersonal discussion. Media use did not directly affect the participation of voting, but indirectly contributed to participation of voting through interpersonal discussion. The assumption of differential media effects on candidates image was partly proved. There were statistically significant differences in the factor of competence of candidates' image among three experimental groups (attentive use of TV discussion program, Internet web sites of two candidates, and printing materials of political advertisement). Furthermore, with three main vote variables, issues, candidates image, party identification, the results of comparative analysis between image factor and the factor of political party influencing the choice of a candidate suggested that a sense of oneness with a party was highly related to the choice of the candidates of the party, however, candidates' image was not related to the decision of a candidate. Political party had more impact on for whom to vote than candidates' image in this study.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.34 no.3
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• pp.98-114
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• 2016

The this study aimed to expand urban heritage using Public Goods and to suggest the assemblage of urban heritage and urban spaces in order to improve landscape conservation and management scheme of urban heritage exposed to a rapidly changing urban environment. The results obtained in this study were summarized as follows: First, in order to improve understanding of the heritage in urban spaces, urban heritage were illustrated on a 1:1000 map with all the public facilities surrounding it using a cultural heritage conservation map listed on the Cultural Heritage Administration's web site, standards for changing present condition, and a topographic map. Second, the status and changes of urban heritage and surroundings were analyzed using the minutes of Historical Cultural Heritage Division Committee for 10 years from 2005 to 2014 to create a status map of urban heritage. Land uses surrounding the urban heritage were investigated the areas of conservation potential and the places that can enhance the to find out values of urban heritage. Also, a profile was created to examine the site characteristics surrounding urban heritage, and photos were taken at important heritage areas and public facilities in order to record the field. Third, analyzed were the relationship of the distance, location, function, and distribution between urban heritage and public facilities surrounding the heritage. using visual features and moving routes in order to identify their impacts on urban heritage and their functions as potential resources. In addition, the role of Public Goods in urban spaces and the plan for revitalizing surrounding areas asset were examined. Fourth, selections were made on Public Goods that have direct or indirect effects on urban heritage. The role of public asset was investigated through visual, areal, and linear elements. The results were summarized to suggest improvement landscape and management mauser on of urban heritage.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of vocational education research
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• v.35 no.4
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• pp.19-46
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• 2016

The purpose of this study is to analyze the curriculum implementation of the Nursing-Specialized Vocational High School by researching on operation, organization and environment of the program of Nursing. This study aims to improve the curriculum of the Nursing-Specialized Vocational High School. This study has analyzed previous existing studies, Link of School info, Educational Statistics and data indicating establishment, operation and curriculum of the department of Nursing which have been collected from web sites of institutions and associations relevant to Nurse Education. The major results of this study are as follows: 1) As of the first semester of the year 2016, out of a total of thirty eight Specialized Vocational High Schools and Meister High Schools in the country, 6.4% of the schools have nursing educational programs. These schools have established the programs under various names, such as Health Nursing, Dental Health Nursing, Nursing, Nursing and Medical Tourism, Accounting in Nursing and Nursing Management, etc. Since 2012, enrollment rates have increased while post-graduation employment rates have decreased, with the average employment rate of Specialized Vocational High School graduates having reached up to 46% by 2015. 2) The Nursing-Specialized Vocational High School aims to create skilled Nurses Assistant such as Nurse Aide and Care giver. The program is successful in providing necessary courses to acquire required certification and proficient field experience but requires revisional changes in order to create a long-term program of sufficient qualification. The official requirement of 780 hours of field practice was completed during the three educational breaks from the first year of high school to the second year, while the curriculum was conducted separately in the field hospitals. 3) An average of two laboratory classrooms were available based on the facility requirement standard of Cities and Provinces Educational Policies. In order to secure proficient instructors of Nursing education, establishment of specific indicated subjects, regional placement, in-service education, research and supervision are essential for establishing excellence and continual improvement.