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Jeju World Peace Island Korean Peninsula Cruise: Planting the seeds of the Jeju King
Cherry Grant McCall 세계환경사회거버넌스학회 2022 World Environment and Island Studies Vol.12 No.2
The proposal in this paper outlines an idea for a Korean Peninsula focused Peace Cruise starting from Jeju World Peace Island and going up the eastern coast of the peninsula , taking in a port or two in Japan (such as Fukuoka) to accommodate potential Korean-descended passengers there and ending at Wonsan, where a grove of Jeju King Cherry (Prunus Yedoensis var. Nudiflora) trees could be planted progressively as a welcome avenue for those on the peace cruise ship. This grove of Jeju King Cherry trees will grow each time a Jeju World Peace Island Peninsula Cruise arrives. Wonsan has been a holiday place for the DPRK for some time and with the permission of that country could become a limited and controlled international destination for Peace and, perhaps, other cruise tours. There are precedents internationally for special zones to be declared for specific activities. Such places frequently become economic development zones for the host country. After successful itineraries have been shown, the Jeju World Peace Island ship could extend its cruise north to ports on the Kamchatka Peninsula and west to Chinese ports interested in the concept
체리(Cherry Ling Yieng Siang),신지원(Gee Won Shin),김용민(Yong min Kim),윤명환(Myung Hwan Yun) 한국HCI학회 2018 한국HCI학회 학술대회 Vol.2018 No.1
The aim of this study is to build human activity recognition (HAR) model using deep neural network (DNN) and investigate the influence that affects misclassification. As wearable devices become widespread and used in various applications such as health care and sports, people are interested in HAR. Therefore, it is important to improve classification performance in HAR. We implemented a DNN based HAR model through open smartphone sensor data set and t-Distributed Stochastic Neighbor Embedding was used to visualize extracted features. The performance of the DNN model was excellent except for one activity. Through the visualization of the extracted features, we were able to identify the cause of the performance degradation. Similar extracted features between activities are the cause of performance degradation. The DNN model can recognize human activity using smart phone sensor data and be used for health care, sports, fall detection and so on.