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Spotting facial micro-expression from videos finds various potential applications in fields including clinical diagnosis and interrogation, meanwhile this task is still difficult due to the limited scale of training data. To solve this problem, this paper tries to formulate a new task called micro-expression generation and then presents a strong baseline which combines the first order motion model with facial prior knowledge. Given a target face, we intend to drive the face to generate micro-expression videos according to the motion patterns of source videos. Specifically, our new model involves three modules. First, we extract facial prior features from a region focusing module. Second, we estimate facial motion using key points and local affine transformations with a motion prediction module. Third, expression generation module is used to drive the target face to generate videos. We train our model on public CASME II, SAMM and SMIC datasets and then use the model to generate new micro-expression videos for evaluation. Our model achieves the first place in the Facial Micro-Expression Challenge 2021 (MEGC2021), where our superior performance is verified by three experts with Facial Action Coding System certification. Source code is provided in https://github.com/Necolizer/Facial-Prior-Based-FOMM., Comment: ACM Multimedia 2021

The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy.

The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy.

The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy.

The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

This paper presents a model based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. The supervisory control strategy seeks the minimum energy input to provide adequate cooling energy for buildings, taking into account the characteristics and interactions of central cooling water systems as well as the requirements and constraints of practical application. Simplified semi-physical chiller and cooling tower models are used to predict the system energy performance and environment quality as well as the system response to changes of control settings. A hybrid optimization technique, namely the PMES (performance map and exhaustive search) based method, is developed and utilized to seek optimal solutions to the optimization problem. The control performance and energy performance of this model based supervisory control strategy are evaluated on the central cooling water system of a high rise commercial office building by comparing with that of the model based supervisory control strategy using a genetic algorithm (GA) as the optimization tool, and the performance map based near optimal control strategy as well as other conventional control strategies for cooling water systems in terms of energy efficiency, control accuracy, computational cost etc. The results showed that this strategy is more energy efficient and computational cost effective than other methods for online practical application.

Hong Kong is a typical subtropical region with frequently high humidity in late spring and summer seasons. Plume from evaporative cooling towers, which service air-conditioning systems of civil buildings, has aroused public concerns since 2000 when the fresh water evaporative cooling towers were allowed to be used for high energy efficiency and environmental issues. This paper presents the evaluation of the plume potential and its effect on the sizing of the plume abatement system in a large commercial office building in Hong Kong for practical application. This evaluation was conducted based on a dynamic simulation platform using the typical meteorological year of Hong Kong since the occurrence of the plume heavily depends on the state conditions of the exhaust air from cooling towers and the ambient air, while the state condition of the exhaust air is determined by the total building cooling load and the control strategies of cooling towers employed mainly for improving energy efficiency. The results show that the control strategies have a significant effect on the plume potential and further affect the system design and sizing of the plume abatement system.

This paper presents a model-based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. Simplified chiller and cooling tower models are developed and used to predict the system energy performance, environment quality as well as the system response to the changes of control settings. A novel and simple optimization technique, named as PMES method, is developed and used to seek the optimal control settings under the given working conditions. The performance of both simplified models is validated using the field measurement data and/or the factory performance test data while the performance of this model-based supervisory control strategy is evaluated by comparing with that of near optimal control strategies and other conventional control strategies for cooling water systems through simulations. The implementation issues of the supervisory control strategy for practical applications are also presented.

This paper presents a model-based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. Simplified chiller and cooling tower models are developed and used to predict the system energy performance, environment quality as well as the system response to the changes of control settings. A novel and simple optimization technique, named as PMES method, is developed and used to seek the optimal control settings under the given working conditions. The performance of both simplified models is validated using the field measurement data and/or the factory performance test data while the performance of this model-based supervisory control strategy is evaluated by comparing with that of near optimal control strategies and other conventional control strategies for cooling water systems through simulations. The implementation issues of the supervisory control strategy for practical applications are also presented.

This paper presents a model-based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. Simplified chiller and cooling tower models are developed and used to predict the system energy performance, environment quality as well as the system response to the changes of control settings. A novel and simple optimization technique, named as PMES method, is developed and used to seek the optimal control settings under the given working conditions. The performance of both simplified models is validated using the field measurement data and/or the factory performance test data while the performance of this model-based supervisory control strategy is evaluated by comparing with that of near optimal control strategies and other conventional control strategies for cooling water systems through simulations. The implementation issues of the supervisory control strategy for practical applications are also presented.

This paper presents a model-based supervisory control strategy for online control of building central cooling water systems to enhance their energy efficiency. Simplified chiller and cooling tower models are developed and used to predict the system energy performance, environment quality as well as the system response to the changes of control settings. A novel and simple optimization technique, named as PMES method, is developed and used to seek the optimal control settings under the given working conditions. The performance of both simplified models is validated using the field measurement data and/or the factory performance test data while the performance of this model-based supervisory control strategy is evaluated by comparing with that of near optimal control strategies and other conventional control strategies for cooling water systems through simulations. The implementation issues of the supervisory control strategy for practical applications are also presented.

Energy consumption of HV AC systems in commercial buildings takes a great part of the total building energy consumption. Energy perIormance evaluation plays an important role in building energy efficiency improvement for existing buildings and new buildings. It is also the basis for the retrofitting measure evaluation for existing buildings and the control improvement evaluation of new buildings for building energy perIormance contracts. In this study, the energy perIormance evaluation of a super high-rising commercial office building in construction is presented. Alternative control strategies are proposed to improve the energy efficiency based on the current measurements of the original design as well as additional metering instroments as requested. These control strategies mainly involve optimal chiller sequencing control, cooling tower sequencing control, optimal water pressure differential set-point control, AHU supply air static pressure reset control and DCVbased fresh air control, etc. To assess the economic feasibility, the benchmark electricity consumption and the optimal electricity consumption using alternative controls strategies are estimated using dynamic simulations. The results show that the electricity savings using the alternative control strategies can cover the costs of an additional metering system and related software and hardware in about one year.

Energy consumption of HV AC systems in commercial buildings takes a great part of the total building energy consumption. Energy perIormance evaluation plays an important role in building energy efficiency improvement for existing buildings and new buildings. It is also the basis for the retrofitting measure evaluation for existing buildings and the control improvement evaluation of new buildings for building energy perIormance contracts. In this study, the energy perIormance evaluation of a super high-rising commercial office building in construction is presented. Alternative control strategies are proposed to improve the energy efficiency based on the current measurements of the original design as well as additional metering instroments as requested. These control strategies mainly involve optimal chiller sequencing control, cooling tower sequencing control, optimal water pressure differential set-point control, AHU supply air static pressure reset control and DCVbased fresh air control, etc. To assess the economic feasibility, the benchmark electricity consumption and the optimal electricity consumption using alternative controls strategies are estimated using dynamic simulations. The results show that the electricity savings using the alternative control strategies can cover the costs of an additional metering system and related software and hardware in about one year.

Energy consumption of HV AC systems in commercial buildings takes a great part of the total building energy consumption. Energy perIormance evaluation plays an important role in building energy efficiency improvement for existing buildings and new buildings. It is also the basis for the retrofitting measure evaluation for existing buildings and the control improvement evaluation of new buildings for building energy perIormance contracts. In this study, the energy perIormance evaluation of a super high-rising commercial office building in construction is presented. Alternative control strategies are proposed to improve the energy efficiency based on the current measurements of the original design as well as additional metering instroments as requested. These control strategies mainly involve optimal chiller sequencing control, cooling tower sequencing control, optimal water pressure differential set-point control, AHU supply air static pressure reset control and DCVbased fresh air control, etc. To assess the economic feasibility, the benchmark electricity consumption and the optimal electricity consumption using alternative controls strategies are estimated using dynamic simulations. The results show that the electricity savings using the alternative control strategies can cover the costs of an additional metering system and related software and hardware in about one year.

Energy consumption of HV AC systems in commercial buildings takes a great part of the total building energy consumption. Energy perIormance evaluation plays an important role in building energy efficiency improvement for existing buildings and new buildings. It is also the basis for the retrofitting measure evaluation for existing buildings and the control improvement evaluation of new buildings for building energy perIormance contracts. In this study, the energy perIormance evaluation of a super high-rising commercial office building in construction is presented. Alternative control strategies are proposed to improve the energy efficiency based on the current measurements of the original design as well as additional metering instroments as requested. These control strategies mainly involve optimal chiller sequencing control, cooling tower sequencing control, optimal water pressure differential set-point control, AHU supply air static pressure reset control and DCVbased fresh air control, etc. To assess the economic feasibility, the benchmark electricity consumption and the optimal electricity consumption using alternative controls strategies are estimated using dynamic simulations. The results show that the electricity savings using the alternative control strategies can cover the costs of an additional metering system and related software and hardware in about one year.

Summary: Poly(magnesium acrylate) and poly(zirconyl acrylate) have been formed by chelating the magnesium ion and the zirconyl ion onto poly(acrylic acid). The PAA is usually neutralized by addition of sodium hydroxide before the synthesis process. The structures and characterisitics of these polymers are studied by various analytical methods such as thermal analysis, elemental analysis, infrared spectroscopy, and mass spectroscopy. The formation of these polymers is verified and their structures are determined. In addition, a preliminary attempt was carried out to make an advanced structural ceramic from a mixture of poly(magnesium acrylate) and poly(zirconyl acrylate)., Thesis (M.S.)--Florida Atlantic University, 1997.