Human Activity Recognition Based on Frequency-Modulated Continuous Wave and DenseNet

With the development of wireless technology, Frequency-Modulated Continuous Wave (FMCW) radar has increased sensing capability and can be used to recognize human activity. These applications have gained wide-spread attention and become a hot research area. FMCW signals reflected by target activity can be collected, and human activity can be recognized based on the measurements. This paper focused on human activity recognition based on FMCW and DenseNet. We collected point clouds from FMCW and analyzed them to recognize human activity because different activities could lead to unique point cloud features. We built and trained the neural network to implement human activities using a FMCW signal. Firstly, this paper presented recent reviews about human activity recognition using wireless signals. Then, it introduced the basic concepts of FMCW radar and described the fundamental principles of the system using FMCW radar. We also provided the system framework, experiment scenario, and DenseNet neural network structure. Finally, we presented the experimental results and analyzed the accuracy of different neural network models. The system achieved recognition accuracy of 100 percent for five activities using the DenseNet. We concluded the paper by discussing the current issues and future research directions.

BODIPY荧光探针的合成及次氯酸检测的综合实验

有机实验和仪器分析实验是本科生阶段化学教学的重点内容,虽然现有的教学实验内容已十分丰富与完善,但缺少两者之间的融合以及与科研领域的联系。针对上述不足,我们将科学研究前沿和热点的荧光检测技术引入教学实践。实验通过对BODIPY (氟硼二吡咯)荧光染料结构的设计改良,合成一种具有快速响应、选择性高和灵敏度好的新型次氯酸荧光探针,对荧光探针结构进行表征,并测定荧光探针的荧光性质。通过对探针结构与荧光性质之间关系的研究,有助于加深学生荧光发光原理的理解。实验内容涵盖有机合成、产物仪器表征、光谱分析等方面,综合性强且易于学生操作。教学实践过程有助于培养学生的科学思维、理论与实践相结合的能力。