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멀티 에이전트 협력 플랫폼으로서의 가상발전소 적용을 위한 HCI 기반 EMS 알고리즘 및 UI 설계 연구
강동주(Dong-Joo Kang),최옥규(Ock-Gyu Choe),주다영(Da Young Ju) 한국HCI학회 2024 한국HCI학회 학술대회 Vol.2024 No.1
중앙집중적으로 계획 및 운영 되던 전력산업은 재생 에너지 및 분산에너지원(DER)의 보급으로 탈중앙화 되고 있으며, 사물인터넷 및 인공지능의 확산으로 무인화와 자동화가 가속화되고 있다. 다양한 분산자원과 에너지 프로슈머들이 ICT 기술로 상호 연계되어 단일 플랫폼에서 에너지 생산과 소비 활동이 유기적으로 협력하는 형태가 가상발전소이다. 여기에는 AI 기반의 사물이나 시스템, 전력시스템을 관리하는 사람 등이 포괄적으로 포함된다. 가상발전소는 사람과 컴퓨터가 상호작용하는 HCI 기반의 다자간 협력 플랫폼으로, 본 논문에서는 이러한 상호작용이 효율적으로 기능할 수 있는 가상발전소의 사용자 인터페이스에 대한 실증 연구 사례를 공유한다.
인구의 서울 쏠림과 지방 쇠퇴의 원인 및 해결방안 : 감성분석을 중심으로
정수빈 ( Su-been Jeong ),김재원 ( Jae-won Kim ),박서윤 ( Seo-yun Park ),곽인상 ( In-sang Kwak ),주다영 ( Da-young Joo ) 한국감성과학회 2023 한국감성과학회 춘계학술대회 Vol.2023 No.-
South Korea, which has developed around Seoul, has gradually widened the gap between Seoul and the provinces. This caused overcrowding in Seoul and the decline of the provinces, and emerged as a national problem along with a decrease in population. This study studies the causes and solutions of the population's concentration in Seoul and local decline: focusing on big data and emotional analysis. Previous studies derive solutions through statistical-based numerical surveys. However, statistical-based surveys estimate the results by investigating based on what has already happened. Induction methods that infer results based on statistical facts have high accuracy, but there are emotional areas that cannot be investigated only by statistical techniques. In particular, people's perceptions of social problems and psychological factors for individual factors can be seen as emotional areas. To this end, emotional analysis and big data analysis, which were not well used in previous studies, were used. Through emotional analysis, people's interest and public opinion are analyzed to infer the cause of the problem, and big data is used to provide a basis for the inference results. In the case of the subject of this study, upper factors such as medical care, transportation, and culture and various lower factors are intertwined. Behind these factors lies the psychological elements of positivity and denial. Through emotional analysis, the relationship between these keywords is analyzed and the psychology of the public hidden therein is grasped. In particular, since psychology has a strong subjective tendency, there is a limit to investigating it only with statistical techniques and refining it to meaningful values that can be used for reasoning results. Therefore, problem analysis using emotional analysis techniques is necessary. Emotional analysis technology is a technology that extracts positive, negative, and neutral emotions from natural language data such as text and sentences, and text data is used for this. This study used these emotional analysis technologies to analyze positive and negative factors about Seoul's population growth and local population decline, which are considered the main causes, and to identify the characteristics and problems of each region.Through this, we would like to suggest ways to help policy alternatives to solve the problem of leaning toward Seoul and local decline.