Abstract The use of Convolutional Neural Networks (CNNs) as a feature learning method for
Human Activity Recognition (HAR) is becoming more and more common. Unlike …

The accurate severity classification of a bug report is an important aspect of bug fixing. The
bug reports are submitted into the bug tracking system with high speed, and owing to this …

Recently, excellent performance has been achieved in Acoustic Scene Classification (ASC)
by using Convolutional Neural Networks (CNNs) and Mel spectrogram feature …

Purpose A vast body of literature has documented the negative consequences of stress on
employee performance and well-being. These deleterious effects are particularly …

Everyday objects are becoming smart enough to directly connect to other nearby and remote
objects and systems. These objects increasingly interact with machine learning applications …

In acoustic event detection, the training data size of some acoustic events is often small and
imbalanced. To deal with this, this paper proposes generating the virtual training data …

It aims to apply the neural network algorithm to the mining of educational resource data and
provide new ideas for the intelligent development of teaching evaluation. The Apriori …

As relevance theory shows, the success of communication crucially depends on the right
contextual information being highly accessible at the right time. Thus it is not sufficient that …

As honey bees are extremely sensitive to a variety of chemicals and emit typical sound when
exposed to environmental chemical, the sound of beehive may be explored as signal to …

Noise negatively affects the complexity and performance of models built in classification
problems. The most common approach to mitigate its consequences is the usage of …