• 산업경영시스템학회지
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• 제46권spc호
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• pp.1-8
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• 2023

To investigate the national science and technology policy direction in the field of construction machinery, an analysis was conducted on projects selected as national research and development (R&D) initiatives by the government. Assuming that the project titles contain key keywords, text mining was employed to substantiate this assumption. Project information data spanning nine years from 2014 to 2022 was collected through the National Science & Technology Information Service (NTIS). To observe changes over time, the years were divided into three-year sections. To analyze research trends efficiently, keywords were categorized into groups: 'equipment,' 'smart,' and 'eco-friendly.' Based on the collected data, keyword frequency analysis, N-gram analysis, and topic modeling were performed. The research findings indicate that domestic government R&D in the construction machinery field primarily focuses on smart-related research and development. Specifically, investments in monitoring systems and autonomous operation technologies are increasing. This study holds significance in analyzing objective research trends through the utilization of big data analysis techniques and is expected to contribute to future research and development planning, strategic formulation, and project management.

• 한국산학기술학회논문지
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• 제21권12호
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• pp.107-114
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• 2020

기계, 디자인, 중공업 분야에서 많이 사용되어오던 역설계 기법이 최근 건설 산업분야에 BIM(Building Information Modeling) 기반 역설계 기법인 Scan-to-BIM 기술로 적극적으로 도입되기 시작하였으며, 그동안 비효율적인 부분들을 개선하기 위한 알고리즘, 시스템, 장비 등의 개발이 이루어지면서 기술의 확장성이 더욱 커지고 있다. 본 연구에서는 객관적인 자료에 근거한 특허 분석을 통하여 한국, 미국, 유럽, 일본의 Scan-to-BIM 관련 기술 동향을 파악하여 한국 Scan-to-BIM 기술의 올바른 방향을 모색하고자 한다. 건설 산업기술 특허분석관련 선행 연구 분석, Scan-to-BIM 기술에 대한 이론적 고찰과 관련 선행연구 고찰, WIPSON 특허검색시스템을 사용한 한국, 미국, 유럽, 일본 네 국가의 관련 기술에 대한 공개된 특허 문헌을 검색하여 정보를 수집, 검증과정 및 유효 특허 추출이 이루어졌으며, 도출된 유효 특허 데이터를 이용하여 특허출원 연도별 동향, 국가별 동향, 그리고 국제특허분류(IPC: International Patent Classification) 코드를 통한 기술별 동향, 상위 20위 주요출원인 및 출원 주체 종류, 패밀리 특허 동향 등을 분석하였다.

• 디지털융복합연구
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• 제15권2호
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• pp.165-172
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• 2017

본 논문에서는 전기자동차를 주제로 SCIE 및 SSCI 저널에 게재한 논문데이터를 활용한 시계열 분석과 국제특허분류(International patent classification, 이하 IPC) 별 특허 데이터를 활용한 시계열 분석과 노드엑셀을 활용한 네트워크 분석을 통해 2001년에서 2014년까지의 전기자동차의 기술 동향을 파악하고 특허와 논문 데이터의 상관관계 분석을 통하여 기술 동향을 분석하였다. 또한 예측기법 중 하나인 가중이동평균법으로 전기자동차의 유망 요소기술을 예측하였다. 본 연구의 결과 전기자동차 요소기술 중 배터리 기술이 유망한 기술로 나타났다.

• 기술혁신학회지
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• 제5권3호
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• pp.354-366
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• 2002

This study is a case study on the analysis of technological informations and patents in Electric Vehicle(EV). It first discusses technological trend, and second patents trends in comparison with major countries such as USA, Japan, Europe and Korea. Technological activities in EV are increasing year after year in the world. The focuses are concentrated in battery and recharging technology.

• 지식경영연구
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• 제14권1호
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• pp.121-132
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• 2013

In education, innovative ways of teaching and learning are always under development and keep being proposed with advanced concepts since the ancient times. Student-centered learning, problem-based learning and cooperative learning have been three major trends under development in secondary education research and practice more than a decade or so. Combined with advanced information and communication technologies, these trends will greatly transform the way we teach and learn in classroom environment and may change the classroom environment itself, into a more interactive and self-centered coaching type environment. In this study, a smart environment that utilizes advanced information technology devices and network is conceptualized, accommodating requirements contained and proposed in the recent trendy pedagogies. Pedagogical cases discussed in these trends are analyzed in detail, producing requirements for such a learning and coaching environment. These requirements are modeled using unified modeling language, leading to a proposal of a basic architecture for an information system supporting this environment.

• 전자통신동향분석
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• 제38권4호
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• pp.47-57
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• 2023

The competition for technological supremacy is unfolding in the high-tech field, and quantum computing can be determinant for economic and security ripple effects. The United States and China, leaders in quantum computing, have developed this field through adequate policies. The United States has fostered quantum computing through government policies and competition among private companies, while China has secured world-class technology through large-scale government investment and attracting foreign talent. In quantum computing, securing talented people is essential to guarantee independent technology development regarding academic attributes and security. We analyze quantum computing policies in the United States and China on a timeline and determine their policy trends. In addition, the policies for securing talent in these countries are reviewed, and the policy effects are compared based on literature analysis. Through the analysis of policy cases between the United States and China, bilateral policy implications for Korea are delineated.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.361-368
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• 2022

This study seeks to determine the research trend of late adolescents by utilizing big data. Also, seek for research trends related to activity participation, treatment, and mediation to provide academic implications. For this process, gathered 1.000 academic papers and used TF-IDF analysis method, and the topic modeling based on co-occurrence word network analysis method LDA (Latent Dirichlet Allocation) to analyze. In conclusion this study conducted analysis of activity participation, treatment, and mediation of late adolescents by TF-IDF analysis method, co-occurrence word network analysis method, and topic modeling analysis based on LDA(Latent Dirichlet Allocation). The results were proposed through visualization, and carries significance as this study analyzed activity, treatment, mediation factors of late adolescents, and provides new analysis methods to figure out the basic materials of activity participation trends, treatment, and mediation of late adolescents.

• 전자통신동향분석
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• 제36권6호
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• pp.55-66
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• 2021

The air traffic industry, one of Korea's major industries, has recently experienced increased demand from overseas air passengers, launched a low-cost airline, and increased special freight transportation capacity. These initiatives have had a positive impact on air traffic (for example, profitability); however, air traffic management has become more complex, which has increased the incidence of aviation accidents and created safety hazards. There is an increasing need to collect and analyze aviation data that can proactively respond to aviation accidents. Concatenation of collected aviation data as big data and the development of artificial intelligence technology are gradually expanding aviation safety event analysis from conventional statistical analysis to machine learning-based analysis. This paper surveys the trends of flight safety event analysis to derive aviation safety risk factors by looking at the types and characteristics of aviation data that can be used to predict accidents related to safety in aviation operations.

• Journal of Information Science Theory and Practice
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• 제10권spc호
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• pp.112-122
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• 2022

Food security and its sovereignty have become among the most important key issues due to changes in the international situation. Regarding these issues, many countries now give attention to smart agriculture, which would increase production efficiency through a data-based system. The Korean government also has attempted to promote smart agriculture by 1) implementing the agri-food ICT (information and communications technology) policy, and 2) increasing the R&D budget by more than double in recent years. However, its endeavors only centered on large-scale farms which a number of domestic farmers rarely utilized in their farming. To promote smart agriculture more effectively, we diagnosed the government R&D trends of smart agriculture based on NTIS (National Science and Technology Information Service) data. We identified the research trends for each R&D period by analyzing three pieces of information: the regional information, research actor, and topic. Based on these findings, we could suggest systematic R&D directions and implications.

• 한국IT서비스학회지
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• 제13권4호
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• pp.275-287
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• 2014

Recently, the volume of unstructured text data generated by various social media has been increasing rapidly; consequently, the use of text mining to support decision-making has also been growing. In particular, academia and industry are paying significant attention to topic analysis in order to discover the main issues from a large volume of text documents. Topic analysis can be regarded as static analysis because it analyzes a snapshot of the distribution of various issues. In contrast, some recent studies have attempted to perform dynamic issue tracking, which analyzes and traces issue trends during a predefined period. However, most traditional issue tracking methods have a common limitation : when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. Additionally, traditional issue tracking methods do not concentrate on the transition of individuals' interests from certain issues to others, although the methods can illustrate macro-level issue trends. In this paper, we propose an individual interests tracking methodology to overcome the two limitations of traditional issue tracking methods. Our main goal is not to track macro-level issue trends but to analyze trends of individual interests flow. Further, our methodology has extensible characteristics because it analyzes only newly added documents when the period of analysis is extended. In this paper, we also analyze the results of applying our methodology to news articles and their access logs.