• 인터넷정보학회논문지
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• 제21권6호
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• pp.133-139
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• 2020

Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

• Smart Structures and Systems
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• 제29권2호
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• 과학과기술
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• 6호통권445호
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• pp.32-34
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• 2006

이 글은 일본의 과학기술정책연구소(NJSTEP)의 ‘Science and Trends’ 2006년 3월호에 게재된 글을 필자가 요약해서 옮긴 것입니다.

• 전자통신동향분석
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• 제33권1호
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• pp.1-10
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• 2018

Artificial intelligence, which is based on deep learning, is emerging as a fundamental technology that will bring about future social changes. Artificial intelligence technology in IT is an essential intelligent system, and will overcome the performance limit of computing systems, and is expected to be the foundation for the development of computing environment destructively. The development of artificial intelligence technology in developed countries is a direction toward convergence with brain science. In this article, we will look at the prospect of artificial intelligence as the manifestation of imagination, as well as the technology and policy trends of artificial intelligence both at home and abroad, and discuss the direction of future technology development in terms of fusion with brain science.

• 마이크로전자및패키징학회지
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• 제20권3호
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• pp.11-18
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• 2013

Interest in copper nanoparticles has increased as an alternative for substituting silver nanoparticles because of its lower cost and less electromigration effect than silver. In this paper, the recent research trends and main results in wet-chemical synthesis of sub-100 nm Cu nanoparticles were summarized. The characteristics of synthesis were discussed with a classification such as modified polyol synthesis, modified hydrothermal synthesis, solvothermal synthesis, and the others, focussing on effects of capping agents, reductants, and pH. Information on the oxidation of synthesized copper nanoparticles were additionally commented.

• 한국정밀공학회지
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• 제33권4호
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• pp.247-255
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• 2016

Sheet metal-forming processes such as stamping, deep drawing, bending, shearing, hydroforming, hydromechanical deep drawing, rubber forming, and incremental forming have been widely used in the automotive, aircraft, and ship-building industries. With the expansion of the automotive industry, research on these processes has been remarkably developed in Korea since the 1980s. Here, we review the history of this research as well as recent trends in sheet metal-forming processes. This overview focuses specifically on the results of research in Korea and on the works of Professor D.Y. Yang, in honor of his retirement.

• 한국신뢰성학회지:신뢰성응용연구
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• 제15권1호
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• pp.33-43
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• 2015

The importance of reliability engineering has increased in recent years. Many studies have been carried out into reliability in a variety of research domains, largely focused on industrial engineering, mechanical engineering, electronics engineering, materials engineering and statistical science. However, most of these studies were carried out without collaboration between different areas of study. Here, we analyze research papers and patents regarding reliability that were published during the past five years, and describe core trends in the development of reliability technology from a multidisciplinary perspective.

• 과학과기술
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• 4호통권407호
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• pp.32-35
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• 2003

세계 지식산업 인력 대이동/ 전화위복 맞은 NASA/ 캐나다 대학원 장학금 크게 증액/ 2015년까지 암 이긴다/ 국제 핵 융합로 유치에 열 올려/ 미국 ITER에 다시 참여/ 도마에 오른 대 정부 기술자문/ 해부학 교육에 적신호

• 한국정밀공학회지
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• 제30권12호
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• pp.1227-1235
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• 2013

Ceramic materials are classified by oxide, nitride and carbide material and have high brittleness, strength and hardness. Ceramic materials are strong in compression but weak in shearing and tension. This review paper has focused on technology trends and mechanism analysis of ceramics removal machining. The ceramic materials have superior mechanical, physical and chemical properties, but it is very hard to machining and the use of ceramics has been limited because of high strength and brittleness. In this paper, technology trends of ceramic removal-machining was introduced for types of machining technology, abrasive machining, cutting process, laser machining and so on.

• 한국산업정보학회논문지
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• 제23권2호
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• pp.63-73
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• 2018

학계나 연구소에서는 연구동향이나 과학기술동향을 파악하고 예측하기 위해 전문가들의 판단에 의존하는 정성적인 방법을 주로 활용하여 왔다. 이 기법은 많은 시간과 비용이 드는 단점이 있기에 본 논문에서는 키워드 네트워크 분석을 활용하여 과학기술 동향을 예측하였다. 이를 위해 미국 특허 중 AI(Artificial Intelligence) 특허 초록 13,618개를 대상으로 키워드 네트워크 분석을 활용하여 분석 1기(2002.1.1. ~ 2006.12.31.), 분석 2기(2007.1.1. ~ 2011.12.31.), 분석 3기(2012.1.1. ~ 2016.12.31.)로 구분하여 분석하였다. 빈도 분석 결과, 분석 1기에서 3기로 시간이 경과할수록 AI 응용 분야의 방법에 관련된 핵심어들이 부각되었다. 키워드 네트워크 분석에서도 시간이 경과함에 따라 응용 분야의 방법에 관련된 핵심어와 다른 핵심어 간의 연계성이 높아졌다. 또한 분석 전체 기간 중 상승 및 하락 추세를 보인 연계 핵심어를 분석하면 응용 분야의 방법과 관리에 대한 연계성은 강화되는 반면에 기초 분야의 연계성은 약화되었다. 키워드 연결 중심성 분석에서도 기간이 경과할수록 응용 분야에 대한 중심성 수치가 높았다. 키워드 매개 중심성 분석에서 분석 3기는 응용 분야의 방법론 관련 핵심어가 가장 높은 매개 수치를 보였다. 이는 앞으로 응용 분야의 방법들이 AI 분야의 강력한 중개자 역할을 할 것으로 예상된다. 본 논문에서 제시한 기법은 지역혁신과 관련된 과제 발굴이나 사회문제 이슈의 시각화 등 지역혁신 분야에 활용되어 질 수 있을 것이다.