• The Korean Journal of Pain
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• v.34 no.1
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• pp.82-93
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• 2021

Background: This study used bibliometric analysis of articles published about the topic of regional anesthesia from 1980-2019 with the aim of determining which countries, organizations, and authors were effective, engaged in international cooperation, and had the most cited articles and journals. Methods: All articles published from 1980-2019 included in the Web of Science database and found using the keywords regional anesthesia/anaesthesia, spinal anesthesia/anaesthesia, epidural anesthesia/anaesthesia, neuraxial anesthesia/anaesthesia, combined spinal-epidural, and peripheral nerve block in the title section had bibliometric analysis performed. Correlations between the number of publications from a country with gross domestic product (GDP), gross domestic product (at purchasing power parity) per capita (GDP PPP), and human development index (HDI) values were investigated with the Spearman correlation coefficient. The number of articles that will be published in the future was estimated with linear regression analysis. Results: Literature screening found 11,156 publications. Of these publications, 6,452 were articles. The top 4 countries producing articles were United States of America (n = 1,583), Germany (585), United Kingdom (510), and Turkey (386). There was a significant positive correlation found between the GDP, GDP PPP, and HDI markers for global countries with publication productivity (r = 0.644, P < 0.001; r = 0.623, P < 0.001, r = 0.542, P < 0.001). The most productive organizations were Harvard University and the University of Toronto. Conclusions: This comprehensive study presenting a holistic summary and evaluation of 6,452 articles about this topic may direct anesthesiologists, doctors, academics, and students interested in this topic.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.

• Journal of Construction Engineering and Project Management
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• v.2 no.1
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• pp.27-34
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• 2012

Recent requirements in component management of building systems have focused on the requirement for improving methods and metric tools to support component condition assessment and appropriate decisions for infrastructure owned facilities. Although engineers and researchers have focused on developing methodologies for component assessment in recent years but there is not enough attention dedicate to facilities and components that have been constructed. This paper is a literature study of scientific papers within the topic of component condition index system (CCIS) in the period 1976 to 2009. Infrastructure component condition index had existed for some 40 years. The purpose of this paper is to provide an overview of CCIS to identify the suitable method for component condition assessment during its service life. This paper finds that the focus of CCIS, surveyed in several aspects during the 40 years that have been investigated, from technology to measurement and from assessment function to component maintenance as an integrated part of the infrastructure component management. This study offers help to researchers in understanding the selection of an appropriate method for component condition assessment in building and non-building systems.

• Journal of Korean Medical classics
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• v.36 no.4
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• pp.25-40
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• 2023

Objectives : This paper studies the Tangaek-Unhoei(湯液韻彙) index of herbal medicine in the Inje-Ji(仁濟志) of the Imwon-Gyeongje-Ji(林園經濟志), which contains about 4,800 formulas. Created by 19th-century Joseon scholar Seo, Yugu, it not only lists the formulas according to their names, but also provides index by topic, which enabled the collection and effective application of massive medical information. Methods : We quantitatively examined the nearly 4,800 herbal medicines in the Tangaek-Unhoei and their categorization. Any uncommon or particular categorization was examined further by analyzing the original text. Results & Conclusions : The prescriptions contained in the Inje-Ji are categorized under 26 headings. They are listed according to the 106 units of the Chinese character dictionary and organized by double headings. This unique index makes it easy to browse the contents of such a vast book containing massive medicinal knowledge. In addition, the fifty or so remedies called 'Fang(方)' exemplify the author's attitude toward medicinal knowledge, which is both rational and inclusive. This is an attitude that should be recognized beyond tradition.

• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.17-20
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• 2014

본 연구는 동시출현 단어분석 기법을 이용하여 최근 전세계적으로 많은 주목을 받고 있는 빅데이터(Big Data) 관련 연구 동향과 연구 영역을 분석하는 것을 목적으로 한다. 이를 위하여 인용색인데이터베이스인 Web of Science SCIE(Science Citation Index Expanded)에서 분석 대상 논문을 수집하였다. 논문 수집을 위한 검색식은 은 Title(논문 제목), Abstract(초록), Author Keywords(저자 키워드), Keywords $Plus^{(R)}$의 네 가지 필드를 동시에 검색하는 주제어(topic)가 "big data"를 포함하고 있는 논문 563편을 대상으로 동시출현단어 분석을 수행하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.29-42
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• 2019

In order to expand the qualitative aspects of public facility, this study used SNS data to derive user-oriented preference factors for public facilities and then were quantified in terms of supply side and demand side. To derive preference factor, LDA, one of topic modeling, was used and attraction index was calculated for each facility. In addition we analyzed spatial accessibility to measure the degree of service experience of users by using 2SFCA model. The study area covered public libraries of Seoul, Korea. As a result of study, five topics were extracted as preference factors for the public library: Circumstance, Scale of facility, Cultural program, Parenting, Books and materials. In particular topic of circumstance and parenting were newly derived preference factors unknown in previous studies. As a result of calculating attraction index for each library, the index of Songpa Library, Jungdok Library, and Namsan Library was high. Songpa library has received good evaluation in parenting factor, and Jungdok & Namsan library in circumstance factor. The accessibility of each region seems to better in center of Seoul where public libraries are crowded, but shrinking toward the outskirts. We expect that the proposed method will contribute to user-oriented public facility evaluation and policy decision making.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.29-31
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• 2006

The most crucial requirement of a power system is o supply quality electric energy to customers without interrution. This problem is directly related to reliability of power system. Reliability assessment of power system has been an important topic for the past several decades. This paper deals with reliability assessment of a 154kV power substation n KEPCO. In his paper, exponential distribution is used to calculate reliablity index. The failure rate data that are utilited for reliablity index based on the realistic system. Also, FTA(Fault Tree Analysis) is used to compute substation reliablity

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7909-7911
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• 2014

Gastric cancer is the fourth most common malignancy worldwide. Poor prognosis in gastric cancer is linked with hypoalbuminemia. Previous studies demonstrated relationships between gastric cancer and chronic inflammation. The aim of this study was to assess the prognostic value of preoperative inflammation-based prognostic scores regarding hospital mortality after gastrectomy. Unlike other recent articles on the same topic; we could only verify prognostic value of prognostic nutritional index for in hospital mortality after surgery.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.27-47
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• 2022

The purpose of the study is to develop a unit catalog system that can be linked with the curriculum. As for the research method, first, unit subject words were extracted through the analysis of middle school curriculum and science textbooks in all grades. Based on this, we designed a unit catalog system that has a unit book catalog by connecting books related to the unit topic of the subject, an index word catalog that organizes unit subject words into index words, and a grade and school level linked subject linked to the unit topic as a subsystem. Using the Notion program, a unit catalog system was implemented on the web using a middle school science unit 1 as a sample. To evaluate the system, experiments and surveys were conducted targeting students, and very positive results were shown in terms of satisfaction with the system and intention to use it in the future. Meanwhile, this study was limited to middle school science departments, but it was proposed to expand the application to all grades and subjects.

• Informatization Policy
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• v.29 no.4
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• pp.43-66
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• 2022

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.