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AVIoT: web-based interactive authoring and visualization of indoor internet of things
Yuna Jeong,Hyuntae Joo,Gyeonghwan Hong,Dongkun Shin,Sungkil Lee IEEE 2015 IEEE TRANSACTIONS ON CONSUMER ELECTRONICS - Vol.61 No.3
<P>Internet of things recently emerges as a common platform and service for consumer electronics. This paper presents an interactive framework of visualizing and authoring IoT in indoor environments such as home or small office. Building blocks of the framework are virtual sensors and actuators that abstract physical things and their virtual behaviors on top of their physical networks. Their behaviors are abstracted and programmed through visual authoring tools on the web, which allows a casual consumer to easily monitor and define their behaviors even without knowing the underlying physical connections. The user study performed to assess the usability of the visual authoring showed that the visual authoring is easy to use, understandable, and also preferred to typical text-based script programming.</P>
김근영(Geunyoung Kim),주현태(Hyuntae Joo),김희재(HeeJae Kim) 한국산학기술학회 2018 한국산학기술학회논문지 Vol.19 No.2
대설 재난은 한국에서 태풍 및 호우 다음으로 두 번째로 많은 자연 재해라고 할 수 있다. 대설 재난으로 인한 2005년에서 2014년 사이의 연 평균 경제 피해액은 약 80억원이다. 심각한 경제적 피해에도 불구하고 한국에서 대설 재난에 대한 경제 효과 연구는 거의 없다. 본 연구의 목적은 다중 회귀모형을 이용하여, 대설 재난의 경제적 피해액과 강설량, 강설일, 인구밀도, 비도시지역 비율 및 수도권 더미 변수 등 간의 연관성을 확인하는 것이다. 2005년부터 2014년 사이의 대설 재난 피해액 관련 데이터는 행정안전부 (국민안전처)에서 발행하는 자연 재해 연보를 이용하였으며, 강설량 및 강설일과 같은 날씨 관련 데이터는 기상청에서 수집하였다. 인구와 비도시 관련 데이터는 지자체 통계 데이터를 사용하였다. 연구 결과 강설일, 강설량, 비 도시면적 비율 등이 대설 재난 피해에 영향을 주는 것으로 나타났다. 본 연구의 결과는 한국의 대설 재난관리 정책에 적용될 수 있다. Heavy snowfall disasters are the third most serious natural disasters, after typhoon and heavy rainfall disasters, in terms of economic disaster damage in South Korea. The average annual economic damage of heavy snowfall disasters was approximately eighty-eight billion won during the period of 2005- 2014. In spite of significant economic damage, there have been few economic studies regarding heavy snowfall disasters in South Korea. The objective of this research is to identify the association between economic damage of heavy snowfall disasters and damage effect factors of snowfall amounts, snowfall days, population densities, and non-urban area ratios using a regression analysis model. Economic damage data sets of heavy snowfall disasters during the period of 2005- 2014 were obtained from the Natural Disaster Yearbook published by the Ministry of Public Safety and Security. Weather-related data sets, such as snowfall amounts and snowfall days were collected from the Korea Meteorological Administration. Demographic and urban data sets, including population densities and non-urban area ratios, were provided by the Local Government Yearbook. Outcomes of this study can assist with heavy snowfall disaster management policies of South Korea.
PRIME KNOTS WITH ARC INDEX 12 UP TO 16 CROSSINGS
Jin, Gyo Taek,Kim, Hyuntae,Lee, Seungwoo,Myung, Hun Joo Korean Mathematical Society 2021 대한수학회지 Vol.58 No.4
We obtain the list of prime knots with arc index 12 up to 16 crossings and their minimal grid diagrams. This is a continuation of the works [5] and [8] in which Cromwell matrices were generated to obtain minimal grid diagrams of all prime knots up to arc index 11. We provide minimal grid diagrams of the prime alternating knots with arc index 12. They are the 10 crossing prime alternating knots. The full list of 19,513 prime knots of arc index 12 up to 16 crossings and their minimal grid diagrams can be found in the arXiv [6].
임미화 ( Lim Mihwa ),주현태 ( Joo Hyuntae ),이창무 ( Lee Changmoo ) 한국부동산분석학회 2016 不動産學硏究 Vol.22 No.3
Previous studies have used households` permanent income to estimate long-term housing demand, as in the Mankiw and Weil Model(1989). However, in Mankiw and Weil(1989), the long-term effects of income varying with time were not taken into account. In the current study, by contrast, the fact that income depends on changes in economic growth has been reflected in household characteristics when estimating permanent income. This study analyzes the effect of income variables using the GDP scenario, which compares the effect that permanent as well as economic growth-dependent income can have on long-term housing demand estimates. The results show that the elasticity of permanent income was similar (0.46) to that of previous studies (0.453-0.488), while per capita GDP and per household GDP displayed greater elasticity than that of permanent income. In addition, upon comparing estimates of per household demand with the number of households by KOSIS, the error between variables was not differentiable over short to mid-term horizons. On the other hand, the error of per capita GDP and per household GDP was less than that of permanent income for long-term estimates of over 20 years. This study highlights the importance of carefully selecting income-related variables when estimating long-term housing demand.
김근영(Kim, Geunyoung),주현태(Joo, Hyuntae),김희재(Kim, Heejae) 한국방재학회 2017 한국방재학회논문집 Vol.17 No.4
대설 재난은 태풍․호우를 포함한 풍수해 다음으로 경제적 피해가 높은 자연재난이다. 전 지구적인 기후변화로 겨울철 북극진동주기가 불규칙해지면서 우리나라에서 대규모 대설 재난 피해의 위험성은 더욱 높아지고 있다. 그러나 대설 재난으로 인한 재산피해를 대상으로 하는 기존의 연구는 미흡한 실정이다. 본 연구는 누적 강설량, 누적 강설일 등 대설 재난 요인변수, 사회경제변수, 대설 재난 피해액에 상당한 부분을 차지하는 농 ․ 축산 관련변수 등 대설 재난 피해액의 영향요인들과 대설 재난 피해액간 관계성을 파악하여 대설 재난으로 인한 경제적 피해를 추정하는 모형을 개발하는 것을 목적으로 한다. 본 연구에서는 단계별 회귀분석 모형 개발절차를 통해 4개의 유효한 회귀분석모형을 개발하였으며 대설 재난 피해액에 영향을 미치는 6개의 요인을 파악하였다. 본 연구의 결과는 설해위험지역 선정, 비닐하우스 ․ 축사 등 농축산 시설기준 개선, 대설 재난 대응방안 수립, 대설 재난 복구예산 추정 등 다양한 대설 재난 정책 수립에 활용될 수 있을 것으로 판단된다. Heavy snowfall disasters are the natural disasters with high economic effects after typhoon and heavy rainfall disasters. The economic effect risk of massive heavy snowfall disasters is growing in South Korea caused by the irregular cycle of arctic oscillation during the winter season due to the global climate change. However, there has been lack of research for economic effects by heavy snowfall disasters. The objective of this research is to develop the economic effect estimation model for heavy snowfall disasters by identifying the association between economic effects of the disasters and their effect factors, including cause factors of heavy snowfall disaster such as cumulated snowfall amount, cumulated snowfall days, socioeconomic factors, and agricultural and livestock factors. This esearch developed four relative regression models by the regression model development procedure, and identified six effective factors for snowfall economic damage. Results of this research are used for various heavy snowfall disaster management policies.