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김태엽(Kim Taeyeop) 한국언어문학회 2006 한국언어문학 Vol.59 No.-
The primary purpose of this paper is to certify the reason that can’t set up low-level in korean honorific system. Most of investigators have setted up a contrast system of high-level and low-level in korean honorific system by this time. But we are on the assumption that can be setted up a contrast system of horizontal-level and high-level in korean honorific system.<BR> We shell certify four reasons that can’t set up low-level in korean honorific system. There are high-level forms and horizontal-level forms in 2, 3 personal pronoun of korean. It can be suppose for 2, 3 personal pronouns to the hearer of korean sentence. We can not set up low-level in korean honorific system because of be without low-level forms in 2, 3 personal pronoun of korean. The second there is not what is called the prefinal-ending of low-level function in korean. There are the prefinal-endings of high-level function such as ‘-si’, ‘-i-’, ‘-jap-’ in middle korean. But there be without the prefinal-ending of low-level function in middle korean and modern korean. Therefore we can not set up low-level in korean honorific system. The third there are not low-level but horizontal-level in embedded ending of indirect quotation sentence in korean. All of final-ending is be neutralized in embedded of indirect quotation sentence. The embedded final-endings of korean be neutralization in indirect quotation sentence are not low-level function but horizontal-level function nin korean honorific system. We can’t set up low-level in korean honorific system. The fourth we can to describe subject honorific system, object honorific system and hearer honorific system with consistent methods. Most of investigators have described high-level and horizontal-level in subject honorific system and object honorific system.<BR> After all we have to set up a contrast system of high-level and horizontal-level in korean honorific system with consistent descriptive methods.
COVID-19 팬데믹에 따른 스마트 호흡보호구의 필요성과 머신러닝 기법을 이용한 공기노출 예측/분류에 관한 연구
정화민(HwaMin Jeong),김태엽(TaeYeop Kim),박철우(ChulWoo Park) 한국산학기술학회 2023 한국산학기술학회논문지 Vol.24 No.4
COVID-19 팬데믹으로 인해 스마트 기술을 활용한 호흡 보호 장비의 수요가 증가하고 있다. 스마트 기술을 적용한 호흡 보호 장비는 사용자의 호흡을 보호하면서, 환경 오염물질을 제거하거나 감지하는 등 다양한 기능을 수행할 수 있고, 이러한 장비는 COVID-19 뿐만 아니라 다른 전염병 예방을 위해서도 유용하게 사용되고 있다. 본 연구는 COVID-19와 같은 감염병 대응에 더욱 효과적으로 사용될 수 있는 스마트 호흡보호구의 필요성과 스마트워치, IoT 기술, 머신러닝 기술 등의 접목도 꼭 필요하다고 주장한다. 또한, 머신러닝 기법의 의사결정트리와 SVM(Support Vector Machine)을 적용하여 국내 A사의 전면형 스마트 호흡보호구의 호흡데이터를 이용한 스마트 호흡보호구의 공기 노출을 예측하고 분류하는 예측모델을 구축하였다. 의사결정 트리는 97.24%의 분류 정확도를 달성했으며 서포터 벡터 머신은 96.24%의 정확도로 나타났다. 머신러닝 기법의 활용은 호흡기 감염병을 예방하기 위한 스마트 호흡 보호 장비의 호흡유출 감지 및 분류에 활용될 수 있어, 이를 활용한 스마트 호흡보호구를 더욱 발전시킴으로써 전 세계적인 전염병 문제를 해결하는 데 중요한 역할을 할 것으로 사료된다. Due to the COVID-19 pandemic, there is a growing demand for respiratory protective equipment that incorporates smart technology. Such equipment not only safeguards users breathing but offers various functions, including the removal or detection of environmental contaminants. This equipment is beneficial for preventing not only the spread of COVID-19 but other infectious diseases as well. This study emphasizes the necessity for smart respirators that can more effectively address the spread of infectious diseases like COVID-19, and contends that the integration of smartwatches, IoT technology, and machine learning is crucial. Furthermore, decision tree (DT) and support vector machine (SVM) models (both of them machine learning techniques) were employed to construct a model to predict and classify air processed through smart respirators by using data from Company As full-face smart respirators. The DT achieved a classification accuracy of 97.24%, while the SVM reached 96.24%. The application of machine learning techniques can facilitate detection and classification of leaks in smart respiratory protective equipment, thus helping to prevent the spread of infectious respiratory diseases. Consequently, further development of smart respirators using these techniques is anticipated to play a significant role in addressing global infectious disease issues.