Shi CHEN (D2), Department of Nuclear Engineering and Management, won “Best Poster Award” at The 39th Annual Meeting of the Institute of Nuclear Materials Management Japan Chapter(INMMJ).
<About awarded research>
An urgent lesson learned from Fukushima Daiichi accident is what can happen by natural disaster also can be made to happen by human design. The accident raised a fear that terrorists could cause a similar accident by acts of sabotage against nuclear facilities and it is noticeable that threats of nuclear terrorism for nuclear security is increased after the accident. Especially as a threat to nuclear facilities, insider sabotage is worthy of attention. We propose a vision-based Deep Neural Network (DNN) model for hand motion recognition and sabotage detection in response to the certain limitations of Physical Protection System (PPS) in nuclear facilities.
<Comments>
I would like to express my sincere gratitude to my supervisor Prof. Kazuyuki Demachi. His patience and kindness helped me to overcome the difficulties and develop my research ideas. I would also like to thank all of my laboratory colleges for insightful comments and incredibly helps.
For the future plan, I will continue my work on developing the insider sabotage detection system using deep learning to maintain the safety and security of nuclear facilities