Biblio

This paper proposes a magnetic actuator using a partially magnetized FePt thick film as a permanent magnet and membrane material for bi-directional micropumps. The magnetized areas act as flux sources, while the magnetized and unmagnetized areas play a role of the membrane part. The mechanical and magnetic characterization results show FePt has a large tensile strength and a lower Young’s modulus than Si crystal, and a comparable remanence to NdFeB. A magnetic pattern transfer technique with a post thermal demagnetization is proposed and experimentally verified to magnetize the FePt partially. Using the proposed magnetic actuator with partially magnetized FePt film is beneficial to simplify the complicated structure and fabrication process of the bi-directional magnetic micropump besides other magnetic MEMS devices.

Teaching evaluation is an indispensable key link in the modern education model. Its purpose is to promote learners' cognitive and non-cognitive development, especially emotional development. However, today's education has increasingly neglected the emotional process of learners' learning. Therefore, a method of using machines to analyze the emotional changes of learners during learning has been proposed. At present, most of the existing emotion recognition algorithms use the extraction of two-dimensional facial features from images to perform emotion prediction. Through research, it is found that the recognition rate of 2D facial feature extraction is not optimal, so this paper proposes an effective the algorithm obtains a single two-dimensional image from the input end and constructs a three-dimensional face model from the output end, thereby using 3D facial information to estimate the continuous emotion of the dimensional space and applying this method to an online learning system. Experimental results show that the algorithm has strong robustness and recognition ability.