A5063935011- Emotion and Mood Recognition
- Topic Modeling
- Advanced Data Compression Techniques
- Sentiment Analysis and Opinion Mining
- AI in Service Interactions
- Mental Health via Writing
- Data Stream Mining Techniques
- Industrial Vision Systems and Defect Detection
- EEG and Brain-Computer Interfaces
- IoT and Edge/Fog Computing
Universidade do Vale do Rio dos Sinos
2022
Mental disorders affect a large number of people worldwide. In response to the increasing affected by such illnesses, there has been an increased interest in use state-of-the-art technologies mitigate its effects. This paper presents Sequence Model for Stress Classification (MoStress), which is novel pipeline pre-processing physio-logical data collected from wearable devices and identifying stress sequences using recurrent neural network (RNN). Using WESAD dataset, RNN model achieved...
The present work proposes a neural network model capable of anticipating possible faults in semiconductor manufacturing plant by predicting non-linearity spikes sensor data.Early detection significant variation can be crucial for identifying machinery degradation or issues the process itself.We use as it is not affected regular changes and autocorrelation, thus avoiding false-positives caused demand presence control systems.The developed able to predict up 30min future with loss ≤...