• The Journal of Korean Academy of Prosthodontics
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• v.46 no.2
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• pp.157-168
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• 2008

Statement of problem: Over the past two decades, implant supported fixed prosthesis have been widely used. However, there are few studies conducted systematically and intensively on the splinting effect of implant systems in mandible. Purpose: The purpose of this study was to investigate the changes in stress distributions in the mandibular implants with splinting or non-splinting crowns by performing finite element analysis. Materials and methods: Cortical and cancellous bone were modeled as homogeneous, transversely isotropic, linearly elastic. Perfect bonding was assumed at all interfaces. Implant models were classified as follows. Group 1: $Br{{\aa}}nemark$ length 8.5mm 13mm splinting type Group 2: $Br{{\aa}}nemark$ length 8.5mm 13mm Non-splinting type Group 3: ITI length 8.5mm 13mm splinting type Group 4: ITI length 8.5mm 13mm Non-splinting type An load of 100N was applied vertically and horizontally. Stress levels were calculated using von Mises stresses values. Results: 1. The stress distribution and maximum von Mises stress of two-length implants (8.5mm, 13mm) was similar. 2. The stress of vertical load concentrated on mesial side of implant while the stress of horizontal load was distributed on both side of implant. 3. Stress of internal connection type was spreading through abutment screw but the stress of external connection type was concentrated on cortical bone level. 4. Degree of stress reduction was higher in the external connection type than in the internal connection type.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.49-63
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• 2018

Purpose : The purpose of this study is investigating the changes of treatment plan and comparing skin dose with or without the skin flash. To investigate optimal applications of the skin flash, the changes of skin dose of each plans by various thicknesses of skin flash were measured and analyzed also. Methods and Material : Anthropomorphic phantom was scanned by CT for this study. The 2 fields hybrid IMRT and the 6 fields static IMRT were generated from the Eclipse (ver. 13.7.16, Varian, USA) RTP system. Additional plans were generated from each IMRT plans by changing skin flash thickness to 0.5 cm, 1.0 cm, 1.5 cm, 2.0 cm and 2.5 cm. MU and maximum doses were measured also. The treatment equipment was 6MV of VitalBeam (Varian Medical System, USA). Measuring device was a metal oxide semiconductor field-effect transistor(MOSFET). Measuring points of skin doses are upper (1), middle (2) and lower (3) positions from center of the left breast of the phantom. Other points of skin doses, artificially moved to medial and lateral sides by 0.5 cm, were also measured. Results : The reference value of 2F-hIMRT was 206.7 cGy at 1, 186.7 cGy at 2, and 222 cGy at 3, and reference values of 6F-sIMRT were measured at 192 cGy at 1, 213 cGy at 2, and 215 cGy at 3. In comparison with these reference values, the first measurement point in 2F-hIMRT was 261.3 cGy with a skin flash 2.0 cm and 2.5 cm, and the highest dose difference was 26.1 %diff. and 5.6 %diff, respectively. The third measurement point was 245.3 cGy and 10.5 %diff at the skin flash 2.5 cm. In the 6F-sIMRT, the highest dose difference was observed at 216.3 cGy and 12.7 %diff. when applying the skin flash 2.0 cm for the first measurement point and the dose difference was the largest at the application point of 2.0 cm, not the skin flash 2.5 cm for each measurement point. In cases of medial 0.5 cm shift points of 2F-hIMRT and 6F-sIMRT without skin flash, the measured value was -75.2 %diff. and -70.1 %diff. at 2F, At -14.8, -12.5, and -21.0 %diff. at the 1st, 2nd and 3rd measurement points, respectively. Generally, both treatment plans showed an increase in total MU, maximum dose and %diff as skin flash thickness increased, except for some results. The difference of skin dose using 0.5 cm thickness of skin flash was lowest lesser than 20 % in every conditions. Conclusion : Minimizing the thickness of skin flash by 0.5 cm is considered most ideal because it makes it possible to keep down MUs and lowering maximum doses. In addition, It was found that MUs, maximum doses and differences of skin doses did not increase infinitely as skin flash thickness increase by. If the error margin caused by PTV or other factors is lesser than 1.0 cm, It is considered that there will be many advantages in with the skin flash technique comparing without it.