An optimal test method for paint is proposed; additionally, the Field and Laboratory Emission Cell （FLEC） method used in Europe is applied as a substitute for the 20 L small chamber method. The emission factors of t...An optimal test method for paint is proposed; additionally, the Field and Laboratory Emission Cell （FLEC） method used in Europe is applied as a substitute for the 20 L small chamber method. The emission factors of total volatile organic compounds （TVOC） and formaldehyde from oil-based paint, emulsion paint, and water-dispersion paint with a coating weight of 300 g/m2, cured for 24/48 hours, were measured using the 20 L small chamber method. The emission rate of TVOC and formaldehyde from all paints began to stabilize after approximately 7 days after 24/48 hours of curing even though Korean standards stipulate that paint should be measured and analyzed after the third day of application. The emission factor of TVOC and formaldehyde from oil-based, emulsion, and water-dispersion paints were also measured using the FLEC method. There was good correlation between the 20 L small chamber method and the FLEC method for oil-based, emulsion, and water-dispersion paint emissions. With the FLEC method, using paints prepared under identical conditions, the emission rate was stable 24 hours after installation of samples because the air flow rate of FLEC is much higher than that of a 20 L small chamber, and the relative cell volume of FLEC is much smaller than that of a 20 L small chamber.展开更多
The application of phase change materials(PCMs)in building envelopes can help promote energy efficiency due to its high heat capacity.Our study aimed to provide energy and economic insights for deploying PCM to buildi...The application of phase change materials(PCMs)in building envelopes can help promote energy efficiency due to its high heat capacity.Our study aimed to provide energy and economic insights for deploying PCM to buildings in eight different regions of East Asia through a series of energy and economic analysis using computer modelling and simulations.The static payback period(SPP)and dynamic payback(DPP)methods were used to evaluate the economic feasibility of applying a PCM at different melting phase temperatures(20℃,23℃,25℃,27℃ and 29℃).Results show that the proper choice of a PCM melting temperature is a key factor to improve the performance of the PCM applied to buildings.A melting phase temperature of 29℃ achieved the highest economic feasibility in Seoul,Tokyo;Pyongyang;Beijing;and Ulaanbaatar and a melting temperature of 23℃ in Hong Kong had the highest economic feasibility.Overall,the combined economic and energy analysis presented in this study can play an important role in improving the energy and economic feasibility of PCM in buildings.展开更多
As crop harvesting becomes more difficult in environments affected by climate change,the application of artificial intelligence technology to crop management through accurate yield prediction is receiving worldwide at...As crop harvesting becomes more difficult in environments affected by climate change,the application of artificial intelligence technology to crop management through accurate yield prediction is receiving worldwide attention.This study proposes a convolutional neural network(CNN)-based transfer learning framework to increase the productivity and improve the economic feasibility of cherry tomatoes(solanum lycopersicum)in South Korea.You-Only-Look-Once 10 Nano(YOLOv10n)is adopted as a CNN-based algorithm.The source model for transfer learning is trained using cherry tomato imagery from the Tomato Plantfactory Dataset,while the target model is trained based on field survey data collected by the National Institute of Horticultural&Herbal Science,Rural Development Administration,Korea.In that process,an image segmentation technique is developed to improve the prediction accuracy,which reduces the root-mean-square deviation of the existing YOLOv10n from 32.3 to 19.8,a 38.7% reduction.Also,the devised economic feasibility analysis method finds the cost of producing cherry tomatoes in South Korea to be 11.12 USD/m^(2),while the maximum revenue can reach 22.44 USD/m^(2).As a result,the proposed transfer learning framework helps general farms where it is difficult to collect big data to use machine learning techniques to predict crop or vegetable production.展开更多
基金Supported by the National Research Foundation of Korea (NRF) by the Korea Government (MEST) (No. 2011-0001031)
文摘An optimal test method for paint is proposed; additionally, the Field and Laboratory Emission Cell （FLEC） method used in Europe is applied as a substitute for the 20 L small chamber method. The emission factors of total volatile organic compounds （TVOC） and formaldehyde from oil-based paint, emulsion paint, and water-dispersion paint with a coating weight of 300 g/m2, cured for 24/48 hours, were measured using the 20 L small chamber method. The emission rate of TVOC and formaldehyde from all paints began to stabilize after approximately 7 days after 24/48 hours of curing even though Korean standards stipulate that paint should be measured and analyzed after the third day of application. The emission factor of TVOC and formaldehyde from oil-based, emulsion, and water-dispersion paints were also measured using the FLEC method. There was good correlation between the 20 L small chamber method and the FLEC method for oil-based, emulsion, and water-dispersion paint emissions. With the FLEC method, using paints prepared under identical conditions, the emission rate was stable 24 hours after installation of samples because the air flow rate of FLEC is much higher than that of a 20 L small chamber, and the relative cell volume of FLEC is much smaller than that of a 20 L small chamber.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science ICT and Future Planning(NRF-2017R1D1A1A09000639)financially supported by Korea Ministry of Environment(MOE)as“Graduate School specialized in Climate Change.”。
文摘The application of phase change materials(PCMs)in building envelopes can help promote energy efficiency due to its high heat capacity.Our study aimed to provide energy and economic insights for deploying PCM to buildings in eight different regions of East Asia through a series of energy and economic analysis using computer modelling and simulations.The static payback period(SPP)and dynamic payback(DPP)methods were used to evaluate the economic feasibility of applying a PCM at different melting phase temperatures(20℃,23℃,25℃,27℃ and 29℃).Results show that the proper choice of a PCM melting temperature is a key factor to improve the performance of the PCM applied to buildings.A melting phase temperature of 29℃ achieved the highest economic feasibility in Seoul,Tokyo;Pyongyang;Beijing;and Ulaanbaatar and a melting temperature of 23℃ in Hong Kong had the highest economic feasibility.Overall,the combined economic and energy analysis presented in this study can play an important role in improving the energy and economic feasibility of PCM in buildings.
基金supported by a Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(Grant No.RS-2023-00239448)the support of the Korea International Cooperation Agency(KOICA).
文摘As crop harvesting becomes more difficult in environments affected by climate change,the application of artificial intelligence technology to crop management through accurate yield prediction is receiving worldwide attention.This study proposes a convolutional neural network(CNN)-based transfer learning framework to increase the productivity and improve the economic feasibility of cherry tomatoes(solanum lycopersicum)in South Korea.You-Only-Look-Once 10 Nano(YOLOv10n)is adopted as a CNN-based algorithm.The source model for transfer learning is trained using cherry tomato imagery from the Tomato Plantfactory Dataset,while the target model is trained based on field survey data collected by the National Institute of Horticultural&Herbal Science,Rural Development Administration,Korea.In that process,an image segmentation technique is developed to improve the prediction accuracy,which reduces the root-mean-square deviation of the existing YOLOv10n from 32.3 to 19.8,a 38.7% reduction.Also,the devised economic feasibility analysis method finds the cost of producing cherry tomatoes in South Korea to be 11.12 USD/m^(2),while the maximum revenue can reach 22.44 USD/m^(2).As a result,the proposed transfer learning framework helps general farms where it is difficult to collect big data to use machine learning techniques to predict crop or vegetable production.
