• 한국컴퓨터정보학회논문지
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• 제6권4호
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• pp.30-37
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• 2001

전통적 개발방법론에서는 요구분석단계에서 요구사항들이 한번 정리되면 이들은 개발이 완료될 때까지 변경이 없을 것으로 간주한다. 그러나 현실적으로는 개발기간 중 목표 시스템의 구체화, 정보기술의 발전, 적용환경의 변화 등으로 인하여 요구사항은 끊임없이 변화하게 된다. 본 논문에서는 개발방법론에서 미흡한 요구사항 관리를 개선하기 위하여 요구사항의 관리를 전체 개발 생명주기로 확대하고, 지속적으로 발생하는 요구사항의 변경을 효율적으로 관리할 수 있는 요구사항의 명세화 방안을 제시한다.

• 전자통신동향분석
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• 제36권4호
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• pp.145-153
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• 2021

Data imputation is a crucial issue in data analysis because quality data are highly correlated with the performance of AI models. Particularly, it is difficult to collect quality time-series data for uncertain situations (for example, electricity blackout, delays for network conditions). Thus, it is necessary to research effective methods of time-series data imputation. Many studies on time-series data imputation can be divided into 5 parts, including statistical based, matrix-based, regression-based, deep learning (RNN and GAN) based methodologies. This study reviews and organizes these methodologies. Recently, deep learning-based imputation methods are developed and show excellent performance. However, it is associated to some computational problems that make it difficult to use in real-time system. Thus, the direction of future work is to develop low computational but high-performance imputation methods for application in the real field.

• ETRI Journal
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• 제44권4호
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• pp.531-542
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• 2022

With the increasing demand for unlicensed spectrum, several regulators have been opening up the 6-GHz band for unlicensed use while ensuring compliance with the technical requirement to avoid harmful interference in the existing primary services (PSs). In this paper, we present two methodologies, a channel-based method and a frequency-based method, which are applicable to a frequency coordination system that calculates the permissible transmit power in the channels or frequencies available to a secondary service (SS). In addition, we have demonstrated that the available transmit power of an SS can be maximized by adjusting the power allocation of the assigned resource units under the condition that the channel of the SS is partially overlapped with that of the PS. Based on the analysis results, it is suggested that it would be better to utilize the two methods selectively according to the operating channel conditions of the PS and the SS.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 춘계학술발표대회
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• pp.369-372
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• 2021

Scheduling the movements of trains in the modern railway system is becoming essential and important. Swiss Federal Railway Company (SBB) and machine learning researchers began collaborating to make a simulation environment and held a Flatland challenge. In this paper, the methodologies of the winners of this competition are analyzed to achieve insight and research trends. This problem is similar to the Multi-Agent Path Finding (MAPF) and Vehicle Rescheduling Problem (VRSP). The potential of the attempted methods from the Flatland challenge to be applied to various transportation systems as well as railways is discussed.

• 한국농촌건축학회논문집
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• 제26권1호
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• pp.41-49
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• 2024

This study focuses on citizen-driven regional agenda and improvement projects, with a specific emphasis on the Yokohama Shimin Machi-bushin Project. The research aims to categorize the scope of citizens' thoughts and the objects for improvement, shedding light on the Analysis Methodologies of citizen-driven proposals for living environment improvement. It also highlights the diverse factors influencing citizens' perceptions of regional issues and the different approaches to addressing them. The paper discusses potential challenges and obstacles in implementing citizen-driven initiatives for community improvement and suggests ways to address them effectively. Overall, the study underscores the significance of citizen participation in community development and the need to understand their perspectives and thought processes in proposing and implementing community improvement initiatives.

• International Journal of Advanced Culture Technology
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• 제12권2호
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• pp.119-135
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• 2024

The research is centered on veteran educators in the field of early childhood education who possess more than 20 years of teaching experience and have been recognized with awards for their outstanding achievements. The selection of participants was based on specific criteria, such as the number of years of experience and recognition received from the Ministry of Education's Teaching Innovation Competition in Korea. Eight teachers who met the specified criteria were selected to participate in the study. A qualitative phenomenological research study was carried out using semi-structured interviews to gain insight into the experiences and perspectives of the participants. The study identified five main themes: cultivating interpersonal relationships, establishing interactive classroom settings, providing impactful educational methodologies, facilitating healthy habits and character education, and creating a supportive environment for teachers' well-being. The study seeks to improve comprehension of teaching methodologies and offer suggestions for professional development, teacher training, and educational policies.

• 트랜스-
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• 제13권
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• pp.141-169
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• 2022

서사 텍스트에 대한 분석은 학술적으로나 실용적으로 중요하게 여겨져 왔으며 여러 관점과 방법으로 이루어져 왔다. 이 논문에서는 정보처리 관점에서의 전산적 서사 분석 방법론을 살펴보았다. 정보처리 관점에서 서사의 창작과 수용은 서사 텍스트에 의해 매개된 양방향적 코딩 과정이고, 서사 텍스트는 다층적으로 구조화된 코드라고 할 수 있다. 이 논문에서는 이런 관점을 공유하는 네 가지 방법론 - 캐릭터 네트워크 분석, 텍스트 마이닝과 감성 분석, 사건 구성의 연속성 분석, 서사 에이전트의 지식 분석 -을 사례와 함께 살펴보았다. 이를 통해 서사 분석에 있어 전산적 방법론의 메커니즘과 가능성을 확인하였다. 결론에서는 전산적 서사 분석의 의의와 부작용을 살펴보고, 인문학과 과학기술 통섭에 바탕한 인간-컴퓨터 협업 모델 설계의 필요성을 논의하였다. 이를 통해 미적으로 창의적이고, 윤리적으로 선하며, 정치적으로 진보적이고, 인지적으로 정교한 서사를 보다 효과적으로 만들어 나갈 수 있음을 주장하였다.

• 한국컴퓨터정보학회논문지
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• 제28권10호
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• pp.55-65
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• 2023

본 논문에서는 딥러닝 및 강화학습 연구에 대해 KeyBERT(Keyword extraction with Bidirectional Encoder Representations of Transformers) 알고리즘 기반의 토픽 추출 및 토픽 출현 빈도 분석으로 급변하는 딥러닝 관련 연구 동향 분석을 파악하고자 한다. 딥러닝 알고리즘과 강화학습에 대한 논문초록을 크롤링하여 전반기와 후반기로 나누고, 전처리를 진행한 후 KeyBERT를 사용해 토픽을 추출한다. 그 후 토픽 출현 빈도로 동향 변화에 대해 분석한다. 분석된 알고리즘 모두 전반기와 후반기에 대한 뚜렷한 동향 변화가 나타났으며, 전반기에 비해 후반기에 들어 어느 주제에 대한 연구가 활발한지 확인할 수 있었다. 이는 KeyBERT를 활용한 토픽 추출 후 출현 빈도 분석으로 연구 동향변화 분석이 가능함을 보였으며, 타 분야의 연구 동향 분석에도 활용 가능할 것으로 예상한다. 또한 딥러닝의 동향을 제공함으로써 향후 딥러닝의 발전 방향에 대한 통찰력을 제공하며, 최근 주목 받는 연구 주제를 알 수 있게 하여 연구 주제 및 방법 선정에 직접적인 도움을 준다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제10권4호
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• pp.292-299
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• 2010

With scaled technology, timing analysis of circuits becomes more and more difficult. In this paper, we review recently developed circuit simulation techniques created to deal with the cost issues of transistor-level simulations. Various techniques for fast SPICE simulations and Monte Carlo simulations are introduced. Moreover, process and aging variation issues are mentioned, along with promising methodologies.

• JSTS:Journal of Semiconductor Technology and Science
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• 제3권3호
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• pp.153-166
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• 2003

Failure analysis is fundamental to the design and development methodology of electrostatic discharge (ESD) devices and ESD robust circuits. The role of failure analysis (FA) in the models, methodology, band mechanisms evaluation for improving ESD robustness of semiconductor products in CMOS, silicon-on-insulator (SOI) and silicon germanium (SiGe) technologies will be reviewed.