• Journal of Internet Computing and Services
• /
• v.21 no.6
• /
• pp.133-139
• /
• 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
• /
• v.29 no.2
• /
• pp.361-374
• /
• 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.

• The Science & Technology
• /
• no.6 s.445
• /
• pp.32-34
• /
• 2006

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

• Electronics and Telecommunications Trends
• /
• v.33 no.1
• /
• pp.1-10
• /
• 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.

• Journal of the Microelectronics and Packaging Society
• /
• v.20 no.3
• /
• pp.11-18
• /
• 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.

• Journal of the Korean Society for Precision Engineering
• /
• v.33 no.4
• /
• pp.247-255
• /
• 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.

• Journal of Applied Reliability
• /
• v.15 no.1
• /
• pp.33-43
• /
• 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.

• The Science & Technology
• /
• no.4 s.407
• /
• pp.32-35
• /
• 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

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.12
• /
• pp.1227-1235
• /
• 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.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.2
• /
• pp.63-73
• /
• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.