Study on the acoustic emission frequency of salicylic acid crystal growth based on beam vibration.

This study aims to investigate the relationship between the grain size of salicylic acid crystals and the frequency of acoustic emission signalsduring the crystallization of salicylic acid. During the crystallization process of salicylic acid, an acoustic emission system was utilized to monitor the emitted sound signals. Based on the beam vibration theory, a lateral vibration model of the crystals was constructed to study the correlation between acoustic emission signals and crystal grain size.

Understanding Convolutional Neural Networks From Excitations.

Saliency maps have proven to be a highly efficacious approach for explicating the decisions of convolutional neural networks (CNNs). However, extant methodologies predominantly rely on gradients, which constrain their ability to explicate complex models. Furthermore, such approaches are not fully adept at leveraging negative gradient information to improve interpretive veracity.

A Little Truth Injection But a Big Reward: Label Aggregation With Graph Neural Networks.

Various correlations hidden in crowdsourcing annotation tasks bring opportunities to further improve the accuracy of label aggregation. However, these relationships are usually extremely difficult to be modeled. Most existing methods can merely make use of one or two correlations.