Publications

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Applied statistical methods for identifying features of heart rate that are associated with nicotine vaping

Published in The American Journal of Drug and Alcohol Abuse, 2025

This paper introduces a series of statistical methods to analyze heart rate data and identify features associated with nicotine vaping.

Recommended citation: Zhao, P., Yang, J.J., & Buu, A. (2025). Applied statistical methods for identifying features of heart rate that are associated with nicotine vaping. The American Journal of Drug and Alcohol Abuse. https://doi.org/10.1080/00952990.2024.2441868 https://doi.org/10.1080/00952990.2024.2441868

Sparse Temporal Aware Capsule Network for Robust Speech Emotion Recognition

Published in Engineering Applications of Artificial Intelligence, 2025

This paper introduces a novel Sparse Temporal-Aware Capsule Network (STACN) architecture designed to enhance the accuracy and reliability of speech emotion recognition systems.

Recommended citation: Zhang, H., Huang, H., Zhao, P., & Yu, Z. (2025). Sparse Temporal Aware Capsule Network for Robust Speech Emotion Recognition. Engineering Applications of Artificial Intelligence. https://doi.org/10.1016/j.engappai.2025.110060

CENN: Capsule-Enhanced Neural Network with Innovative Metrics for Robust Speech Emotion Recognition

Published in Knowledge-Based Systems, 2024

This paper introduces a groundbreaking Capsule-enhanced neural network (CENN) that significantly advances the state of SER through a robust and reproducible deep learning framework.

Recommended citation: Huiyun Zhang, Heming Huang, Puyang Zhao, Xiaojun Zhu, Zhenbao Yu, CENN: Capsule-Enhanced Neural Network with Innovative Metrics for Robust Speech Emotion Recognition, Knowledge-Based Systems (2024). https://www.sciencedirect.com/science/article/pii/S095070512401133X

DiGAN Breakthrough: Advancing Diabetic Data Analysis with Innovative GAN-Based Imbalance Correction Techniques

Published in Computer Methods and Programs in Biomedicine Update, 2024

Breakthrough in Diabetes Data Analysis: DiGAN represents a breakthrough approach in the field of medical diagnostics, especially in diabetes classification.

Recommended citation: P. Zhao, X. Liu, Z. Yue et al., DiGAN Breakthrough: Advancing diabetic data analysis with innovative GAN-based imbalance correction techniques, Computer Methods and Programs in Biomedicine Update (2024), doi: https://doi.org/10.1016/j.cmpbup.2024.100152. https://doi.org/10.1016/j.cmpbup.2024.100152.

An Attention-based Long Short-Term Memory Framework for Detection of Bitcoin Scams

Published in 2022 International Conference on High Performance Big Data and Intelligent Systems (HDIS), 2022

A novel Attention-based Long Short-Term Memory (A-LSTM) method is proposed for the classiﬁcation problem to determine whether a transaction is involved in Ponzi schemes or other cyber scams, or is a non-scam transaction.

Recommended citation: Zhao, P., Tian, W., Xiao, L., Liu, X., & Wu, J. (2022, December). An Attention-based Long Short-Term Memory Framework for Detection of Bitcoin Scams. In 2022 International Conference on High Performance Big Data and Intelligent Systems (HDIS) (pp. 21-26). IEEE. https://arxiv.org/pdf/2210.14408.pdf

Research on Prediction of Solar Power Considering the Methods of Statistical and Machine Learning – Based on the Data of Australian Solar Power Market

Published in IOP conference, 2022

The results show that the regression model with correlated errors is better than the machine learning-based LSTM algorithm, which is based on the differential MSE performance, and can accurately predict solar power generation.

Recommended citation: Zhao, P., & Tian, W. (2022, June). Research on prediction of solar power considering the methods of statistical and machine learning–based on the data of Australian solar power market. In IOP Conference Series: Earth and Environmental Science (Vol. 1046, No. 1, p. 012006). IOP Publishing. https://iopscience.iop.org/article/10.1088/1755-1315/1046/1/012006/pdf