ABSTRACT
Energy consumption in the home increases recently due to the extremely hot or cold weather. Because of COVID 19, many people stay in the home and energy consumption in the home is increasing very much. Moreover, many homes are using new electric home appliances such as dishwasher or washer dryer which consumes much electric energy for a long duration. To reduce electric energy consumption and use energy more efficiently, the usage pattern of the home appliance should be analyzed. In the paper, we propose a pattern analysis method of the home appliance using Boosting technique. Boosting method is a sort of ensemble machine learning algorithm and is based on the decision tree. The correlation between home appliance usage can be analyzed with the result of feature importance in boosting algorithm. To verify the method, we analyzed the electric usage record in the UK with boosting algorithm. © 2022 IEEE.
ABSTRACT
Evoker is a narrative-based facial expression game. Due to the COVID-19 pandemic, adolescents should be wearing masks in their daily lives. However, wearing masks disturbs emotional interaction through facial expressions, which is a critical component in emotional development. Therefore, a negative impact on adolescent emotional development is predicted. To solve this problem, we design a narrative-based game Evoker that uses real-time facial expression recognition. In this game, players are asked to identify an emotion from narrative contexts in missions, and make a facial expression appropriate for the context to clear the challenges. Our game provides an opportunity to practice reading emotional contexts and expressing appropriate emotions, which has a high potential for promoting emotional development of adolescents. © 2022 Owner/Author.