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가솔린기관에서 운전조건 따른 바이오에탄올 연료의 연소 및 배기배출물 특성
윤승현(Seunghyun Yoon),하성용(Sungyong Ha) 한국자동차공학회 2014 한국자동차공학회 부문종합 학술대회 Vol.2014 No.5
The combustion and exhaust emission characteristics in a spark ignition engine (SI engine) with variation of the bioethanol-gasoline blending ratio and the excess air-fuel ratio were investigated in this research. To investigate the influence of the excess air ratio and ethanol blends, the combustion characteristics such as the cylinder pressure, rate of heat release(ROHR), and fuel consumption rate were analyzed. In addition, the reduction effects of exhaust emissions such as carbon monoxide (CO), unburned hydrocarbon (HC), and oxides of nitrogen (NOx) were compared with those of gasoline fuel under the various excess-air ratios. The results showed that the peak combustion pressures and the ROHR of bioethanol fuel cases were slightly higher than those of gasoline fuel at all test ranges. As compared with gasoline fuel (G100) at each given excess air ratio, BSFC of bio-ethanol was increased. The CO, HC, NOx emissions of bio-ethanol fuel were lower than those of gasoline fuel under overall experimental conditions.
윤승현(Seunghyun Yoon),임은희(Eunhee Rhim),김덕호(Deokho Kim) 한국정보과학회 2015 정보과학회 컴퓨팅의 실제 논문지 Vol.21 No.2
Question Answering (QA) 서비스는 사용자의 자연어 질의에 대응하는 정확한 답변을 제공하는 시스템이다. 본 연구는 특정 도메인에 관련한 사용자들의 질문에 대해 QA 서비스가 자동으로 대응하는 방법에 관한 연구이다. 이를 수행하기 위하여 사용자의 자연어 질문을 이해하고, 정형 데이터 및 비정형 데이터로부터 사용자 질문에 적합한 답변을 도출하여 제공하는 방법을 제시한다. 실험 결과 top 1 accuracy 68%, top 5 accuracy 77% 결과를 얻었다. 또한 본 논문은 QA 시스템 내부 모듈이 전체 accuracy 에 미치는 영향에 대해서도 기술하였다. Question Answering (QA) services can provide exact answers to user questions written in natural language form. This research focuses on how to build a QA system for a specific domain area. Online and offline QA system architecture of targeted domain such as domain detection, question analysis, reasoning, information retrieval, filtering, answer extraction, re-ranking, and answer generation, as well as data preparation are presented herein. Test results with an official Frequently Asked Question (FAQ) set showed 68% accuracy of the top 1 and 77% accuracy of the top 5. The contribution of each part such as question analysis system, document search engine, knowledge graph engine and re-ranking module for achieving the final answer are also presented.