• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Hospice and Palliative Care
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• v.6 no.1
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• pp.22-33
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• 2003

Purpose : The purpose of this study was to evaluate the present status of patients' satisfaction and the reasons for any satisfaction or dissatisfaction in cancer pain management Methods : A cross-sectional survey was used to obtain the feedback about pain management. The results of the survey were collected from 59 in- or out-patient who had cancer treatment at two of the teaching hospitals in Seoul from July, 2002 to November, 2002. The data was obtained by a structured questionnaire based on the American Cancer Society Patient Outcome Questionnaire(APS-POQ) and other previous research. The clinical information for all patients were compiled by reviewing their medical records. Resuts : 1) The subjects' mean score of the worst pain was 6.77, the average pain score was 3.80, and the pain score after management was 2.93 for the past 24 hours. The mean score of total pain interference was $25.03{\pm}12.82$. Many of the subjects had false beliefs about pain such as 'the experience of pain is a sign that the illness has gotten worse', 'pain medicine should be 'saved' in case the pain gets worse' and 'people get addicted to pain medicine easily'. 2) 66.1% of the subjects were properly medicated with analgesics. 33.9% of the subjects reported use of various methods in controlling pain other than the prescribed medication. Only 33.9% of the subjects had a chance to be educated about pain management by doctors or nurses. 3) The mean score of patients' satisfaction with pain management was $4.19{\pm}1.14$. 72.9% of the subjects answered 'satisfied' with pain management. The reasons for dissatisfaction were 'the pain was not relieved even after the pain management', 'I was not quickly and promptly treated when I complained of pain', 'doctors and nurses didn't pay much attention to my complaints of pain.', and 'there was no appropriate information given on the methods of administration, effect duration and side effects of pain medicine.' The reasons for satisfaction were: 'the pain was relieved after the pain management.', 'doctors and nurses quickly and promptly controlled my pain.', 'doctors and nurses paid enough attention to my complaints of pain.' and 'trust in my physician'. 4) In pain severity or pain interference, no significant difference was found between the satisfied group and dissatisfied group. On the belief 'good patients avoid talking about pain', a significant difference was found between the satisfied group and dissatisfied group. Conclusions : The patients' satisfaction with cancer pain management has increased over the years but still about 30% of patients reported to be 'not satisfied' for various reasons. The results of this study suggest that patients' education should be done to improve satisfaction in the pain management program.

• Restorative Dentistry and Endodontics
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• v.34 no.2
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• pp.87-94
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• 2009

The purpose of this study was to assess the current materials, methods and difficulties according to the year of licence and educational background of Korean dentists in Class II direct composite resin restorations. Total 17 questions were included in the questionnaire. Questions were broadly divided into two parts: first. operator's information. and second. the materials and methods used in Class II posterior composite restoration. The questionnaire was sent to dentists enrolled in Korean Dental Association via e-mail. Total 12,193 e-mails were distributed to dentists. 2,612 e-mails were opened, and 840 mails (32.2%) were received from respondents. The data was statically analyzed by chi-square test using SPSS(v. 12.0.1, SPSS Inc. Chicago, IL, USA). Male dentists among respondents was 79%. 60.3% of the respondents acquired their licences recently (1998-2007), and 77% practiced in private offices. 83.4% have acquired their knowledge through school lectures, conferences and seminars. For the Class II restorations, gold inlays were preferred by 65.7% of respondents, while direct composite resin restorations were used by 12.1 % amalgam users were only 4.4% of respondents. For the restorative technique, 74.4% of respondents didn't use rubber dam as needed. For the matrix. mylar strip (53.4%), metal matrix (33.8%) and Palodent system (6.5%) were used. 99.6% of respondents restored the Class II cavity by incremental layering. Obtaining of the tight interproximal contact was considered as the most difficult procedure (57.2%) followed by field isolation (21 %). Among various bonding systems, 22.6% of respondents preferred SE Bond and 20.2% used Single Bond. Z-250 was used most frequently among a variety of composite resins.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.149-163
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• 2016

Seafarers are an essential resource in maritime industries, which provide navigation skills, vessel maneuvering skills and fishing skills in the fishery industry. They also work as a driving force in pilotage, port operation, vessel traffic service, and marine safety. Other areas in maritime services, which rely on seafarer include safety management of ships, supervisory activities, and maritime accident assessment. In these ways, Korean seafarers have contributed to the growth of Korean economy. However, there have been issues of high separation rate, shortage of supply, multi-nationality, multiplicity of culture caused by employment of foreign seafarers, and aging. The present paper finds that maritime officers and fishery officers demonstrate differences in the statistics of on-board job taking and separation: the separation rate of fishery officers is higher than that of maritime officers. The existing data and statistics by the Korea Seafarer's Welfare & Employment Center could be improved by changing its structure from time series to panel data. The Korea Seafarer's Welfare & Employment Center is the ideal institution for collecting the panel data, as it has already accumulated and published relevant statistics regarding seafarer. The basic design method of the panel data is to adopt and improve it by including the information on ratings of maritime and fishery industries, ranks in a ship, personal information, family life, and career goal. Panel data are useful in short- and long-term forecasts of supply of Korean seafarers; demand evaluation of education, training, and reeducation of the seafarers; demographical dynamic analysis on Korean seafarers; inducement policy of long-term on board job taking in harmony with man-power demands in marine industries such as pilotage service; implementation of job attractiveness policy on Korean seafarers; and employment stabilization of Korean seafarers.

• Management & Information Systems Review
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• v.36 no.1
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• pp.59-80
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• 2017

Due to the recent deepening youth unemployment aftereffect, government, companies and universities seek a youth unemployment resolution method and jobs creating measures. But there are indications that the Good Job the university students prefer are limited and sudden rise of the youth unemployment rate mirrors the situation in Japan 20 years ago. Thus, based on the preceding research, this research attempted to perform comparative analysis on Korean and Japanese university students' employment preparation activities and perceived organizational support affect their Awareness of Good Job. To achieve the goal, 2013 GOMS 5,380 copies provided by Korea Employment Information Service are used in the case of Korea and total 5,636 copies within 256 questionnaires targeted to Japanese university students are used in the case of Japan. The results of analysis are as follows. The effect relationship between the perception of organizational support and awareness of Good Job showed a positive influence both in Korea and Japan. The effect relationship between employment preparation activities and awareness of Good Job showed a meaningful effect in Korea whereas it showed no effect in Japan. In the relationship between activities of employment preparation and awareness of Good Job, moderating effect of gender and major field of study didn't show any effect either in Korea or Japan. The results of this research are as follows. First, because it is verified that the support of university has positive influence on the university students' awareness of Good Job, it seems that universities need to intensify the support for the students' welfare enhancement, education satisfaction and the structural support system. Second, the gap of attitude of employment preparation activities and awareness of Good Job between Korea and Japan occurred due to the levels of social structure, welfare and wage differences in the two countries. Therefore, if measures of policy to resolve the welfare and wage gaps between conglomerates and smaller enterprises are enacted, the awareness of younger generations to the Good Job will show a corresponding effect.

• Korean Journal of Culture and Social Issue
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• v.15 no.3
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• pp.399-429
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• 2009

The purpose of this research examines the factors that influence happiness among Korean adolescents by focusing on psychological resource (as measured by self-efficacy), relational resource (as measured by social support) and financial resource (as measured by family's monthly income). In addition, the influence of academic achievement on happiness is examined. To examine the influence of socio-economic status and family's monthly income, adolescents living in three different districts in Seoul (from working to middle to upper class districts) were randomly selected and interviewed in their home. A total of 190 elementary school, middle school, high school and university students (male=83, female=107) completed the resiliency of efficacy scale developed by Bandura (1995) and emotional support and happiness scale developed by the present researchers, in addition to background information. The results of the path analysis are as follows. First, the most important predictor of happiness among Korean adolescents is relational resources. In other words, emotional support received from significant others was most predictive of happiness; more than 60 times the effect of family's monthly income, three times the effect of academic achievement, and two times the effect of resiliency of efficacy. The second most important factor that predicted the happiness of Korean adolescents was psychological resource (i.e., resiliency of efficacy), which had 30 times the effect of family's monthly income. In addition resiliency of efficacy played a mediating role between emotional support on one hand and happiness on the other. Third, those respondents who had higher academic achievement reported higher levels of happiness, which had 20 times the effect of family's monthly income. Fourth, family monthly income did not predict happiness among Korean adolescents. Fifth, socio-economic status and school level did not have direct influence on happiness but had mediating influence through their influence on emotional support. In other words, those respondents with higher socio-economic status and elementary school students were more likely to receive social support from significant others, which in turn increased their happiness. These results indicate that the most important predictor of happiness among Korean adolescents is emotional support, followed by resiliency of effic acy and academic achievement, indicating that those adolescents from wealthy families are not necessarily happier.

• Journal of Korean Society of Disaster and Security
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• v.12 no.1
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• pp.11-21
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• 2019

This study assessed the risk of disaster by using QRE(Quick Risk Estimation - UNISDR Roll Model City of Basic Evaluation Tool) tools for three natural disasters and sixteen social disasters managed by the Seoul Metropolitan Government. The criteria for selecting 19 disaster types in Seoul are limited to disasters that occur frequently in the past and cause a lot of damage to people and property if they occur. We also considered disasters that are likely to occur in the future. According to the results of the QRE tools for disaster type in Seoul, the most dangerous type of disaster among the Seoul city disasters was "suicide accident" and "deterioration of air quality". Suicide risk is high and it is not easy to take measures against the economic and psychological problems of suicide. This corresponds to the Risk ratings(Likelihood ranking score & Severity rating) "M6". In contrast, disaster types with low risk during the disaster managed by the city of Seoul were analyzed as flooding, water leakage, and water pollution accidents. In the case of floods, there is a high likelihood of disaster such as localized heavy rains and typhoons. However, the city of Seoul has established a comprehensive plan to reduce floods and water every five years. This aspect is considered to be appropriate for disaster prevention preparedness and relatively low disaster risk was analyzed. This corresponds to the disaster Risk ratings(Likelihood ranking score & Severity rating) "VL1". Finally, the QRE tool provides the city's leaders and disaster managers with a quick reference to the risk of a disaster so that decisions can be made faster. In addition, the risk assessment using the QRE tool has helped many aspects such as systematic evaluation of resilience against the city's safety risks, basic data on future investment plans, and disaster response.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.138-148
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• 2022

The 1920s and 1930s were when new trends became prominent in Korean housing architecture. This study began with a curiosity about the appearance of residential gardens during the transition period, when housing types were changing. Since gardens are constantly evolving and living spaces, it is not easy to give a clear picture of their evolution. However, through popular magazines and newspaper articles published in the 1920-30s, this study investigated how people perceived the gardens socially and how they engaged in gardening. First, the study of Gyeongseong's urbanization process revealed that people perceived gardens as a way to give natural beauty to the urban environment. Therefore, the creation of a residential garden was strongly encouraged. Second, the housing improvement movement, which the architects actively discussed during this period, emphasized that a garden is a factor that can help improve the quality of the residential environment in terms of hygiene and landscape aesthetics. Third, since the media provided information on gardening, it was confirmed that the number of people engaged in gardening as a hobby increased. As designers and gardeners who had received a modern education became more active, the concept of "designed gardens" was formed. Lastly, although the houses were divided into various types, the shapes of the gardens did not show a significant difference according to the architecture type. They tended to embrace the time's ideal garden design and style. Therefore, even in a traditional hanok, Western-style gardens were naturally harmonized into the overall architecture, and exotic plant species could be found. Although the gardens found in media images were limited to those belonging to the homes of the intelligentsia, it can be seen that representativeness was secured, considering the popularity and ripple effect of the media. Therefore, this study contributes to the literature as it confirmed the ideal gardens and gardening methods in the 1920s and 30s.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.685-698
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• 2023

This study aimed to identify binge-eating behavior and food addiction in Korean population and to determine their associations with obesity, eating behaviors, mental health and cognitive characteristics. We collected clinical questionnaire scores related to eating problems (e.g. binge eating, food addiction, food cravings), mental health (e.g. depression), and cognitive functions (e.g. impulsivity, emotion regulation) in 257 Korean adults in the normal and the obese weight ranges. Binge-eating and food addiction were most frequent in obese women (binge-eating: 46.6%, food addiction: 29.3%) when we divided the participants into 4 groups depending on gender and obesity status. The independence test using the data with propensity score matching confirmed that binge-eating and food addiction were more prevalent in obese individuals. Finally, we constructed the logistic regression models using forward selection method to evaluate the influence of various clinical questionnaire scores on binge-eating and food addiction respectively. Binge-eating was significantly associated with the clinical scales of eating disorders, food craving, state anxiety, and emotion regulation (cognitive reappraisal) as well as food addiction. Food addiction demonstrated the significant effect of food craving, binge-eating, the interaction of obesity and age, and years of education. In conclusion, we found that binge-eating and food addiction are much more frequent in females and obese individuals. Both binge-eating and food addiction commonly involved eating problems (e.g. food craving), but there was difference in mental health and cognitive risk factors. Therefore, it is required to distinguish food addiction from binge-eating and investigate intrinsic and environmental risk factors for each pathology.