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A study on vessel applicable indoor environment monitoring system
최기도,권오찬,주양익 한국마린엔지니어링학회 2021 한국마린엔지니어링학회지 Vol.45 No.6
Recently, interest in indoor fine dust and indoor environment improvement has been increasing. Compared to land transpor-tation, ships have a more restricted indoor environment owing to stability and space constraints. Due to the nature of the activities, such as, eating and moving on board a ship, if the indoor environment is polluted, exposure to that pollution can occur for a long time. Therefore, in this study, a vessel-applicable indoor environment monitoring system is developed that measures the indoor environmen-tal values and communicates with the server using Wi-Fi. Further, to improve the reliability of the implemented system, an algorithm for removing the outliers in the data is proposed.
최기도(崔基度) 서울대 사회보장법연구회 2020 사회보장법연구 Vol.9 No.1
문재인 대통령이 2018년 3월 제안한 대한민국헌법 개정안은 국회 본회의에서 의결정족수 미달로 사실상 폐기되었다. 그러나 해당 헌법개정안의 제안은 1987년 제9차 헌법 개정 이후 처음 이루어진 것으로서 현행 헌법의 지속가능성에 대한 의문을 공식화하였을 뿐 아니라, 앞으로 언제든지 개헌 논의가 이루어질 수 있음을 시사한다. 사회보장에 관한 헌법 규정의 개정은 사회보장을 둘러싼 헌법현실과 헌법규범의 괴리에 대한 반성적 고찰을 토대로 우리 사회에서 이루어지고 있는 사회보장에 관한 헌법 규정의 개정 논의, 다른 나라의 입헌례, 그리고 사회보장에 관한 헌법 규정의 개정 연혁을 종합적으로 고려하여 이루어진다. 그 중 사회보장에 관한 헌법 규정의 도입 배경·이유에 대한 고찰은 규정에 대한 이해를 깊이 있게 하고, 개정 과정에서의 문제점을 확인할 수 있도록 하여 사회보장에 관한 헌법 규정의 개정 방향에 대하여 중요한 시사점을 줄 수 있을 것이다. 본 글에서는 사회보장에 관한 헌법 규정의 개정 배경을 당시의 자료 등을 통하여 구체적으로 살펴봄으로써 사회보장에 관한 헌법 규정에 대한 개정 과정의 한계를 밝히고 개정 방향에 대한 시사점을 찾는다. 사회보장에 관한 헌법 규정의 개정 연혁에 대한 고찰이 향후 개정 과정에서 반면교사가 될 수 있기를 기대한다. The proposed revision to the Constitution of the Republic of Korea proposed by President Moon Jae-In in March 2018 was virtually abolished due to insufficient legislative meetings at the National Assembly. However, the proposed constitutional revision was first proposed after the ninth constitutional revision in 1987, and it not only formalized the question of the sustainability of the current constitution, but also suggests that discussions on the revision can be made at any time in the future. The revision of the constitutional rules on social security is based on a reflection on the disparity between the reality surrounding social security and the constitutional rules, discussions on the revision of the constitutional rules on social security in our society, comparative study of constitutional rules of other countries, and the consideration of the revision history of the constitutional rules on social security. Among them, in-depth consideration of the reason and background of the introduction and revision of the constitutional rules on social security deepens understanding of the regulations and identifies problems in the revision process. It may give some implications for directions for revision. This article clarifies the limitations of the revision process and suggests directions for revision by examining the background of the revision of the constitutional rules on social security through the constitutional data of the time. It is hoped that review of the revision history of the constitutional rules on social security will become a lesson in the future.
정성범,서홍일,최기도,서동환 한국마린엔지니어링학회 2023 한국마린엔지니어링학회지 Vol.47 No.3
Recently, radar-based human activity recognition (HAR) technology has been actively studied in the field of artificial intel-ligence by applying radar datasets to deep learning (DL) models to automatically learn and classification. This is one of the important applications in the field of activity recognition and can be used in various fields, such as exercise tracking, smart homes, self-driving cars, and health status monitoring, by recognizing human daily activity patterns. However, DL models are complex and have significant computational costs and numerous parameters to process and classify high-dimensional radar datasets. Therefore, their implementation on commercial mobile devices is limited by their computational complexity. Therefore, in this study, we propose a lightweight HAR DL model using Self-Attention technology to solve the complexity and computational costs of these DL models. Experimental results demonstrate that this model can maintain its performance while reducing the number of parameters required. In the future, these light-weight models will not only be usable on mobile devices but will also require lower computing power and memory capacity; therefore, they are expected to be used in various fields as time series-based DL models.