• Korean Journal of Culture and Social Issue
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• v.30 no.3
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• pp.239-265
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• 2024

The purpose of this study was to compare the predictive accuracy of traditional prediction models (methods) and machine learning algorithms in predicting suicidal behaviors. The research aimed to go beyond a systematic review level and scientifically examine the predictive capabilities of these two techniques through meta-analysis, analyzing variables identified through domestic research, particularly at the regional level. In order to achieve this, a total of 124 studies, including 50 studies utilizing machine learning and 74 studies employing traditional methods, were included in the meta-analysis. The results of the study revealed that the integrated area under the curve (AUC) for studies using traditional methods was .770, which was lower than the integrated AUC value of .853 for studies using machine learning. Particularly, studies conducted in Asia (AUC = .944) demonstrated higher accuracy compared to studies in Western countries (AUC = .820) and Korea (AUC = .864). Additional analysis of the moderating effects in domestic research indicated that a higher proportion of males and the prediction of suicide attempts were associated with higher prediction accuracy. On the other hand, prediction accuracy was lower when the prediction target was suicide deaths and when studies utilized neural network analysis. This study synthesized various research findings on the prediction of suicidal behaviors, verified the effectiveness of prediction using machine learning, and holds significance in exploring variables applicable in the context of South Korea.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.51-54
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• 2015

추천 시스템의 대표적인 연구 중 하나인 콘텐츠 기반 추천 시스템 연구는 TV 프로그램이나 영화의 줄거리, 장르, 리뷰 등의 콘텐츠의 메타데이터를 이용한다. 그러나 이러한 연구들은 콘텐츠 관련 정보에만 의존할 뿐, 시청자의 프로파일과 콘텐츠의 정보를 함께 고려하지 않는다. 본 논문에서는 시청자의 프로파일 중 연령과 콘텐츠의 정보인 프로그램의 줄거리를 활용한 TV 프로그램 추천 시스템을 제안한다. 본 추천 시스템은 시청자를 연령에 따라 분류한 후, LDA 알고리즘을 이용하여 시청자의 시청 TV 프로그램의 줄거리를 분류된 나이에 따라 각각의 줄거리 토픽 모델로 생성한다. 이를 기준으로 시청자가 원하는 시간대에 방송되는 프로그램들의 줄거리 토픽벡터와 시청자의 선호도 토픽벡터의 유사도를 비교해 가장 유사도가 높은 TV 프로그램을 시청자에게 추천하는 방식이다. 본 논문에서는 연구의 효용성을 검증하기 위해 줄거리만을 사용한 경우와 줄거리와 연령을 동시에 활용한 경우를 비교 실험하였다. 실험을 통해 프로그램의 줄거리만을 사용한 경우보다 연령을 동시에 활용한 경우의 추천 시스템 성능이 개선된 것을 확인할 수 있었다.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.81-90
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• 2021

There are various optimization problems in real world and research continues to solve them. An optimization problem is the problem of finding a combination of parameters that maximizes or minimizes the objective function. Harmony search is a population-based metaheuristic algorithm for solving optimization problems and it is designed to mimic the improvisation of jazz music. Harmony search has been actively applied to optimization problems in various fields such as civil engineering, computer science, energy, medical science, and water quality engineering. Harmony search has a simple working principle and it has the advantage of finding good solutions quickly in constrained optimization problems. Especially there are various application cases showing high accuracy with a low number of iterations by improving the solution through the empirical derivative. In this paper, we explain working principle of Harmony search and classify the leading research in recent 3 years, review them according to category, and suggest future research directions. The research is divided into review by field, algorithmic analysis and theory, and application to real world problems. Application to real world problems is classified according to the purpose of optimization and whether or not they are hybridized with other metaheuristic algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• The Korean Journal of Archival Studies
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• no.54
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• pp.81-109
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• 2017

This study suggests an analysis of the reviews provided by international archival professionals on the RiC-CM draft published by ICA EGAD. Some implications for the Korean archival management environment were also suggested. Some professional reviews were accessible through the internet. Italian archival professionals held workshops at various levels for the analysis and discussion of the draft. Duranti, the project director of InterPARES, also gave opinions about the draft in cluding the perspective of digital preservation. In the review of Artefactual, the draft was discussed in terms of system implementation. Reed, the director of Recordkeeping Innovation, also gave a feedback based on the record management experiences in Australia. Some implications can be suggested based on these professional opinions. First, we should try to build a test bed for the adoption of RiC to archival description in the Korean environment. Second, a minimum level of data elements that can secure authenticity and integrity will also be needed. Third and lastly, rich authority data for agents and functions related to archival records and records groups are essential to take full advantage of the standard.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.179-195
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• 2020

This study searched for the status of medical Systematic Review(SR) publications in Korea and elsewhere for last 10 years, closely analyzing SR research papers by co-authors of Korean librarians. Through interviews with Korean librarians participating in SR, the activities, roles, and difficulties of these librarians were identified, and the results of the interviews helped explore new ways to promote collaboration in SR research. The result of the studied showed that the number of domestic and foreign SR studies has recently increased, and the number of cases where Korean librarians participated in SR research being officially credited as a co-author or acknowledgment source was also grow. The SR librarians in the Korean medical libraries were not only search experts, data collectors, and reference writers, but also did various activities such as designing search strategies, SR search records with complete reproducibility, and DB search tutorship. To promote SR support librarians participated in the interview suggested recruiting new librarians, retraining current librarians, and reformation courses in library and information science. As it is expected that the level of information demand of users and expectations for librarians would also increase in near future, SR librarians' activities and contributions seem to offer a guideline for academic library services that the others should pursue.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.219-222
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• 2013

Recently, rapid innovation of Smartphone is changing the paradigm of our daily life. With the launch of Apple iPhone, there is an explosion of interest in Smartphone itself as well as Internet-based services using Smartphone are being revitalized. Smartphone users, opinion experts more than 99 percent of the economically active population is using, it has reached the saturation past the early stages of formation. Smartphone is equipped with a general purpose OS possible the implementation of high performance environment similar level as a personal computer. Also, it is a mobile communication terminal scalable which can be removed or installed various applications. New information technology like Smartphone gives us a very important and interesting research issue that is to find and prove the factors influencing the purchase intention. At this point, study identifying on the influence factors to the behavioral intention of Smartphone is very important. This study was targeted a total of 99 research papers that are setting up the related Smartphone in among the research papers published in domestic academic journals since 2008. Empirical research related behavioral intention using was summarized on the papers 76.

• Elastomers and Composites
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• v.44 no.3
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• pp.209-221
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• 2009

Polyolefins are important commodity polymers with the largest volume of business owing to their outstanding combination of cost performance and excellent physical properties. However, the lack of functional groups often has limited their end uses, such as compatibilizer, modifier and adhesive, where the interaction with other materials is especially important. The incorporation of functional groups as polymer segments to afford block or graft polyolefin copolymers has been extensively investigated in the context of the functional polyolefin hybrids. Living polymerization processes have been considered to be an efficient method to prepare the polyolefin hybrids with precisely controlled architecture and compositions. Among the living polymerization techniques, controlled/"living" radical polymerization (CRP) methods are very effective not only because of the controllability of polymerization but also because of the versatility of monomers and polymerization conditions. In this review paper, progresses on the preparations of polyolefin graft or block copolymers through CRP techniques are summarized. The commodity polymers such as polyisobutylene, polyethylene and polypropylene are combined with polar segments such as polyacrylate, polymethacrylate, polystyrene to yield functionalized polyolefins.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.113-122
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• 2024

This comprehensive study delves into the analysis of user review data across various metaverse platforms, employing advanced text mining techniques such as TF-IDF and Word2Vec to gain insights into user perceptions. The primary objective is to uncover the factors that contribute to user satisfaction and dissatisfaction, thereby providing a nuanced understanding of user experiences in the metaverse. Through TF-IDF analysis, the research identifies key words and phrases frequently mentioned in user reviews, highlighting aspects that resonate positively with users, such as the ability to engage in creative activities and social interactions within these virtual environments. Word2Vec analysis further enriches this understanding by revealing the contextual relationships between words, offering a deeper insight into user sentiments and the specific features that enhance their engagement with the platforms. A significant finding of this study is the identification of common grievances among users, particularly related to the processes of refunds and login, which point to broader issues within payment systems and user interface designs across platforms. These insights are critical for developers and operators of metaverse platforms, suggesting a focused approach towards enhancing user experiences by amplifying positive aspects. The research underscores the importance of continuous improvement in user interface design and the transparency of payment systems to foster a loyal user base. By providing a comprehensive analysis of user reviews, this study offers valuable guidance for the strategic development and optimization of metaverse platforms, ensuring they remain responsive to user needs and continue to evolve as vibrant, engaging virtual environments.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.707-721
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• 2022

In this study, a state-of-the-art review on urban inundation simulation technology was presented summarizing major achievements and limitations, and future research recommendations and challenges. More than 160 papers published in major domestic academic journals since the 2000s were analyzed. After analyzing the core themes and contents of the papers, the status of technological development was reviewed according to simulation methodologies such as physically-based and data-driven approaches. In addition, research trends for application purposes and advances in overseas and related fields were analyzed. Since more than 60% of urban inundation research used Storm Water Management Model (SWMM), developing new modeling techniques for detailed physical processes of dual drainage was encouraged. Data-based approaches have become a new status quo in urban inundation modeling. However, given that hydrological extreme data is rare, balanced research development of data and physically-based approaches was recommended. Urban inundation analysis technology, actively combined with new technologies in other fields such as artificial intelligence, IoT, and metaverse, would require continuous support from society and holistic approaches to solve challenges from climate risk and reduce disaster damage.