• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.521-521
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• 2016

상수도 관망은 수원에서 수요절점까지 물을 안정적으로 공급하는 것을 목표로 한다. 상수도 관망의 최적설계는 수리학적 제한조건 (절점의 수압, 관로의 유속)을 만족하는 범위에서 비용을 최소화하는 설계안을 얻는 것으로 Savic and Walters (1997)는 유전 알고리즘 (Genetic Algorithms, Holland 1975)을 적용한 상수도 관망 설계 프로그램인 GANET를 제안하였고, Maier et al. (1996)은 개미군집알고리즘 (Ant Colony Optimization Algorithm, Dorigo et al. 1996)을 상수도 관망 최적설계에 적용한 후 그 결과가 유전 알고리즘에 비해 우수함을 증명하는 등 상수도 관망 최적설계에 관한 연구가 활발히 진행되어 오고 있다. 유전알고리즘은 선택, 교차, 돌연변이의 반복계산 과정을 통하여 최적해를 찾는 최적화 기법이다. 이 과정에서 결정변수는 유전자 (Gene)의 집합으로 표현되며, 염색체 (Chromosome) 내에서 근접한 유전 인자들은 일종의 Building Block을 형성하게 된다. Building Block은 좋은 해를 갖는 유전 인자를 높은 확률로 보관하여 지역해에 빠질 가능성을 줄이는 반면, 유전형 (Genotype)이 표현형 (Phenotype)을 충분히 모방하여 표현하지 못한 경우 오히려 최적해의 탐색을 방해할 수 있다는 한계점을 갖는다. 유전 알고리즘을 상수도 관망 최적설계에 적용하였을 때에도 이 한계점은 여실히 드러난다. 관로의 관경을 결정변수로 설정한 후 유전형으로 표현하였을 때, 관망도 상에서 근접하지 않은 두 관로가 염색체 내에서 연속으로 나열된다면 두 관로 간의 연관성이 실제보다 크게 고려되기 때문이다. 한편, 하모니써치 (Harmony Search, Geem et al. 2001) 알고리즘은 즉흥 연주 (Improvisation)를 통해 최상의 화음을 만들어내는 현상으로부터 착안하여 만들어진 최적화기법으로 연산 기법은 무작위선택, 기억회상, 피치조정 등으로 구성되어 있으며, 결정변수에 해당하는 연주자가 독립적으로 행동하며 해를 탐색한다는 점에서 유전알고리즘과 큰 차이를 갖는다. 본 연구에서는 유전알고리즘의 Building Block에 의해 발생하는 오류를 개선하고자, 상수도 관망 최적설계 연구에 많이 사용되는 Hanoi 관망 (Fujiwara and Khang 1990) 관로의 정렬 순서를 여러 가지 기준으로 설정하여 관망데이터를 구축한 후 하모니써치와 유전 알고리즘을 적용하여 최적화를 수행하였고 그 결과를 비교하였다. 그 결과 유전 알고리즘과 달리 하모니써치 알고리즘의 경우, 관로의 나열 순서와 상관없이 우수한 최적해 탐색 결과를 보이는 것을 확인할 수 있었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.79-86
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• 2021

In order to increase the probability of success in big data projects, quantified techniques are required to analyze the root cause of risks from complex causes and establish optimal countermeasures. To this end, this study measures risk factors and relationships through SNA analysis and presents a way to respond to risks based on them. In other words, it derives a dependency network matrix by utilizing the results of correlation analysis between risk groups in the big data projects presented in the preliminary study and performs SNA analysis. In order to derive the dependency network matrix, partial correlation is obtained from the correlation between the risk nodes, and activity dependencies are derived by node by calculating the correlation influence and correlation dependency, thereby producing the causal relationship between the risk nodes and the degree of influence between all nodes in correlation. Recognizing the root cause of risks from networks between risk factors derived through SNA between risk factors enables more optimized and efficient risk management. This study is the first to apply SNA analysis techniques in relation to risk management response, and the results of this study are significant in that it not only optimizes the sequence of risk management for major risks in relation to risk management in IT projects but also presents a new risk analysis technique for risk control.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.53-63
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• 2018

The traditional mass media function of conveying information and forming public opinion has rapidly changed into an environment in which information and opinions are shared through social media with the development of ICT technology, and such social media further strengthens its influence. In other words, it has been confirmed that the influence of the public opinion through the production and sharing of public opinion on political, social and economic changes is increasing, and this change is already in use on the political campaign. In addition, efforts to grasp and reflect the opinions of the public by utilizing social media are being actively carried out not only in the political area but also in the public area. The purpose of this study is to explore the possibility of using social media based public opinion in educational policy. We collected media data, analyzed the main topic and probability of occurrence of each topic, and topic trends. As a result, we were able to catch the main interest of the public(the 'Domestic Computer Education Time' accounted for 43.99%, and 'Prime Project Selection' topics was 36.81% and 'Artificial Intelligence Program' topics was 7.94%). In addition, we could get a suggestion that flexible policies should be established according to the timing of the curriculum and the subject of the policy even if the category of the policy is same.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.427-434
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• 2022

Atrial fibrillation treatment includes 3D RFCA and Cryo-balloon ablation. Both procedures have in common that they enter after understanding the structure of the heart using angiography equipment. Therefore, there is a disadvantage that the effect of exposure according to the procedure time can be a threat to both the patient and the operator, so this study aims to confirm the relationship between the total ablation time and the effect of radiation exposure. We used follow-up data (retrospective) from 41 patients who underwent coronary angiography and arrhythmia at the same time from March 2019 to July 2022. The range for total ablation time was based on the recorded data from the start to the end of the total ablation. The end point of 3D RFCA was when the ablation was completed for 4 pulmonary veins, and in the case of Cryo-balloon ablation, the data that succeeded in electrical insulation were included. As a result of analyzing the total ablation time, the time taken for Cryo-balloon ablation was 1037.29±103.66 s, which was 2448.61 s faster than 3D RFCA using 3485.9±405.71 s, and was statistically significant. (p<0.05) As a result of analyzing the total fluoroscopy time, the exposure time for 3D RFCA was 2573.75±239.08 s, which was less by 1717.15 s than the exposure time for Cryo-balloon ablation, 4290.9±420.42 s, and was statistically significant. In the case of total area dose product, 3D RFCA was 59.04±13.1 uGy/m², which was lower than Cryo-balloon ablation 980.6±658.07 uGy/m² by 921.56 uGy/m², which was statistically significant. As the insulation time of the Cryo-balloon ablation is shorter than that of the 3D RFCA, the method using the Cryo-balloon ablation is considered to be effective when the patient's condition is not good and a quick procedure is required. However, in patients with permanent Atrial fibrillation, there is a high probability of structural changes in the heart, so it is considered that 3D RFCA is better than Cryo-balloon ablation, which is difficult to manipulate.

• Science of Emotion and Sensibility
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• v.16 no.1
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• pp.53-64
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• 2013

Folksonomies have potential problems caused by synonyms, tagging level, neologisms and so forth when retrieving music by tags. These problems can be tackled by introducing the mood intensity (Arousal and Valence value) of music as its internal tag. That is, if moods of music pieces and their mood tags are all represented internally by numeric values, A (Arousal) value and V (Valence) value, and they are retrieved by these values, then music pieces having similar mood with the mood tag of a query can be retrieved based on the similarity of their AV values though their tags are not exactly matched with the query. As a prerequisite study, in this paper, we propose the mapping table defining the relation between AV values and folksonomy tags. For analysis of the association between AV values and tags, ANOVA tests are performed on the test data collected from the well known music retrieval site last.fm. The results show that the P values for A values and V values are 0.0, which means the null hypotheses could be rejected and the alternative hypotheses could be adopted. Consequently, it is verified that the distribution of AV values depends on folksonomy tags.

• 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 the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1465-1475
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• 2016

In order to secure safe meals, the hazards of microorganisms associated with food poisoning accident should be monitored and controlled in real situations. It is necessary to determined the correlation between existing common bacteria number (aerobic plate count; APC) and RLU (relative light unit) in cookware. In this paper, we investigate the correlation between ATP (RUL) and APC (CFU) by using three types of transform (inverse, square root, log transforms) of raw data in two steps. Among these transforms, the log transform at the first step has been found to be optimal for the data of cutting board, knife, soup bowl (stainless), and tray (carbon). The square root-inverse and the square root-square root transform at the second step have been shown to be optimal respectively for the cup and for the soup bowl (carbon) data.