상호작용성, 소속감, 정보 수용자의 만족, 그리고 부정적 구전 감소 의지

김철호(Chulho Kim) 충남대학교 사회과학연구소 2013 사회과학연구 Vol.24 No.1

The purpose of this study is to examine the relationship among interactivity, sense of belonging(SOB), satisfaction, and the intention to reduce negative word-of-mouth(WOM) on e-learning. Interactivity was divided into subjective control(SC), perceived reciprocal communication(PRC), and perceived timeliness of response(PTR). Sense of belonging(SOB) was limited to the SOB on the institute he/she belongs to. Satisfaction was divided into satisfaction with the components of e-learning and satisfaction with self-directed study. As results, three components of interactivity were strongly related to the SOB. Within the components of interactivity, PRC shows a more significant relationship with satisfaction on the components of e-learning, whereas, SC was more related to satisfaction with self-directed study. It also indicates that SOB has an impact only on satisfaction with the components of e-learning. In the case of the impact of satisfaction, satisfaction with the self-directed study shows a relatively significant relationship with the intention of reducing negative WOM. This research has the following significance. First, as variablizing shared phenomena between communication and education with interdisciplinary perspectives, this research applies the changing paradigm of utilizing media pursuing interactivity into e-learning. Second, this research variablizes people’s SOB and scrutinizes the effect of people’s SOB, an important concept on educational environment and yet a complicated concept difficult to be applied into on-line based education empirically. Third, this research tries to find the effect of the relationship between satisfaction and self-directed study quantitatively. Fourth, this research variablizes the concept of negative WOM, a familiar concept to marketing and/or consumer behavior traditionally, applies it into e-learning, and tests it exploratively.

건축물 에너지 수요 예측을 위한 이종 공공 데이터 통합 방안 연구

김철호(Chulho Kim),김한주(Hanjoo Kim),변지욱(Jiwook Byun),고재현(Jaehyun Go),허연숙(Yeonsook Heo) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.6

This study investigated a method of integrating building energy-consumption public data such as MOLIT EAIS and KEPCO AMI to develop the probabilistic models to predict the electricity demand of non-residential buildings. The data set was created by integrating electricity data composed by consideration of time (24 hours) of 9 business types into 5 building types (i.e., education, office, hotel, culture, retail). Individual building energy data source alone provides partial information, and different data sources are at different temporal resolution. Therefore, there is a strong need to develop a framework to integrate various types of public data sets, and this data-integration framework will be essential to develop building energy forecasting models at high resolution levels.

건축물 에너지 수요 예측을 위한 이종 공공 데이터 통합 방안 연구

김철호(Chulho Kim),김한주(Hanjoo Kim),변지욱(Jiwook Byun),고재현(Jaehyun Go),허연숙(Yeonsook Heo) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.6

This study investigated a method of integrating building energy-consumption public data such as MOLIT EAIS and KEPCO AMI to develop the probabilistic models to predict the electricity demand of non-residential buildings. The data set was created by integrating electricity data composed by consideration of time (24 hours) of 9 business types into 5 building types (i.e., education, office, hotel, culture, retail). Individual building energy data source alone provides partial information, and different data sources are at different temporal resolution. Therefore, there is a strong need to develop a framework to integrate various types of public data sets, and this data-integration framework will be essential to develop building energy forecasting models at high resolution levels.

주거 커뮤니티 전력 수요 예측을 위한 단계별 확률적 통계 모델 개발

김철호(Kim, Chulho),변지욱(Byun, Jiwook),고재현(Go, Jaehyun),허연숙(Heo, Yeonsook) 대한건축학회 2021 대한건축학회논문집 Vol.37 No.7

This study developed a series of probabilistic statistical models for electricity demand prediction of residential communities. The series of probabilistic models were developed to reflect individual variations in the electricity demand depending on household characteristics and temporal variability in the pattern of hourly electricity use. We used the hourly electricity data, including plug-in and lighting energy use, from 23 households selected from the public data of the Korea Energy Agency. The prediction model consists of four models to capture variability in the electiricity demand at different indiviual and time scales. Models 1 and 2 are blinear regression models that predict the annual average electricity load depending on the household characteristics and variation in the daily electricity load, respectively. Models 3 and 4 are multivariate normal distribution probability density functions that generate average hourly electricity load profile and temporal variations from the average profile, respectively. The results demonstrarate that the series of probabilistic models sufficiently reflect actual individual and temporal variations.

교육 시설의 전력 수요 예측을 위한 클러스터링 기반 확률적 통계 모델 개발

김철호(Chulho Kim),김한주(Hanjoo Kim),변지욱(Jiwook Byun),고재현(Jaehyun Go),허연숙(Yeonsook Heo) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.6

This study developed the probabilistic models of the internal electricity load for educational buildings on the basis of the structured probabilistisic model framework developed in the previous study for residential buildings. In this process, heterogeneous public data sosurces (MOLIT EAIS and KEPCO AMI) were used, and differences in internal electricity load within education buildings were invetigated with using the clustering method. The cluster analysis revealed two distinctive load profiles, which may be due to different types of educational purposes: schools and private educational institutes. Within each cluster of buildings, individual-building variations of internal electricity load, as well as temporal variations of internal electricity load were quantified by the structured probabilistic models Statistical models 1 and 3 can represent individual variations in internal electricity load for each building, and statistical models 2 and 4 can reflect temporal variations in hourly internal electricity load patterns that change daily.

지역정체성 기반 지역축제의 브랜드화를 위한 Z세대의 기대가치 연구

김철호(Chulho Kim) 한국문화융합학회 2023 문화와 융합 Vol.45 No.10

본 연구의 목적은, 지역 축제 참여자의 기대가치를 타당성 있게 확인하여 지역정체성 기반 축제의 차별화된 지역브랜드화에 도움이 되도록 이론적 토대를 제시하고 실무적 적용 필요성을 환기하는데 있다. Z 세대를 대상으로 한 정성적·정량적 조사가 실시되었다. 연구에 적용된 지역축제의 범위는 지역의 정체성과 쉽게 연계될 수 있는, 역사적 명소, 유적, 유물, 인물 관련 축제로 설정하였다. 연구 결과, Z세대의 지역 정체성 기반 축제에 대한 기대가치는 8개의 관점과 이에 따른 16개의 기대가치로 범주화 되었다. 이는 지역축제가 지역 정체성에 기반을 두고 차별화 된 브랜드로서 지속성 있게 포지셔닝 되기 위해서는 도출된 다양한 관점들을 고려하여 타겟층의 현재적·잠재적 기대가치에 부응해야 함의 제시하고있다. 나아가 이렇게 확인된 유목과 요인들을 바탕으로 통합적이면서도 타겟 지향적인 축제의 기획, 집행 및 성과관리를 추구해야 함을 보여준다. The purpose of this study is to validly check the value expectation of regional festival participants to suggest a theoretical foundation and raise the need for practical application to help differentiation of regional brandification of festivals based on regional identity. Quantitative and qualitative surveys were conducted on Generation Z. The scope of regional festivals for this research was set to festivals that can easily be correlated to historical landmarks, historical sites, artifacts, and people. Research results show that the value expectation of Generation Z on festivals based on regional identity could be categorized into 8 perspectives and 16 value expectations. This suggests that in order for regional festivals to be based on regional identity and position themselves as differentiated brands in the long term, they must meet current and potential value expectations of the target groups by considering various perspectives. Furthermore, it shows that integrated and target-oriented festival planning, execution, and performance management must be pursued based on the identified classifications and factors.

블로바이가스 오일분리장치에 관한 연구

김철호(Chulho Kim),박윤철(Yeunchul Park) 한국자동차공학회 2010 한국자동차공학회 학술대회 및 전시회 Vol.2010 No.11

This research aims to develop parts for advanced fuel/oil filtering re-circulation applicable to this kind of regulation proof engines. These parts can play a role of converting traditional air emission type crankcase into recovery type crankcase so that the engine can deal with environmental regulations, which do not allow minimal amount of toxic gas discharge. The results showed that oil separation efficiency of the cyclone type CCV(Crankcase Ventilation)system was higher than one of baffle type both in CFD program

브랜드 웹툰에 대한 2030세대의 기대가치 연구

김철호(Chulho Kim) 한국문화융합학회 2023 문화와 융합 Vol.45 No.7

주거 커뮤니티 급탕 수요 예측을 위한 확률적 통계 모델 개발

김철호(Kim, Chulho),변지욱(Byun, Jiwook),고재현(Go, Jaehyun),허연숙(Heo, Yeonsook) 대한건축학회 2021 대한건축학회 학술발표대회 논문집 Vol.41 No.2

This study developed a series of probabilistic statistical models for domestic hot water demand prediction in residential communities. The series of probabilistic models were developed to reflect individual variation in the domestic hot water demand depending on household characteristics and temporal variability in the pattern of hourly domestic hot water use in a systematic manner. We used the hourly domestic hot water data from 15 households selected from the public data of the Korea Energy Agency. Models 1 and 2 are based on linear regression models to predict the annual average domestic hot water load depending on the household characteristics and variation in the daily domestic hot water load, respectively. Models 3 and 4 are based on the multivariate normal distribution and beta distribution probability density function to generate hourly domestic hot water load profiles reflecting temporal variation. As a result of applying probabilistic domestic hot water load profiles, individual and temporal variations were reflected.

건축물 에너지 수요 예측을 위한 이종 공공 데이터 통합 방안 연구

김철호(Chulho Kim),김한주(Hanjoo Kim),변지욱(Jiwook Byun),고재현(Jaehyun Go),허연숙(Yeonsook Heo) 대한설비공학회 2022 대한설비공학회 학술발표대회논문집 Vol.2022 No.6

This study investigated a method of integrating building energy-consumption public data such as MOLIT EAIS and KEPCO AMI to develop the probabilistic models to predict the electricity demand of non-residential buildings. The data set was created by integrating electricity data composed by consideration of time (24 hours) of 9 business types into 5 building types (i.e., education, office, hotel, culture, retail). Individual building energy data source alone provides partial information, and different data sources are at different temporal resolution. Therefore, there is a strong need to develop a framework to integrate various types of public data sets, and this data-integration framework will be essential to develop building energy forecasting models at high resolution levels.