《动力学、监测与诊断学报》3篇文章入选 “首届科技期刊高质量发展大会100篇精品论文”

    为推动期刊深度融合，拓展编辑国际视野，促进科技期刊高质量发展，由重庆市科学技术协会等主办，重庆市科学技术期刊编辑学会承办的“首届科技期刊高质量发展大会”于2023年10月18日至20日在重庆召开，并发布“首届科技期刊高质量发展大会100篇精品论文”。

    大会收到共计262篇论文。经过资格审查、学科分类，由学科专家从论文学术价值、创新价值、应用价值、社会效益和经济效益4个维度对每篇文章进行综合评分，得出了初评结果。10月8日召开终评会，评审专家团评出了100篇精品论文。由重庆中德未来工厂研究院、重庆理工大学共同创办的《动力学、监测与诊断学报》（Journal of Dynamics, Monitoring and Diagnostics）共有3篇论文入选！

Title: 

Residual Convolution Long Short-Term Memory Network for Machines Remaining Useful Life Prediction and Uncertainty Quantification

Authors: 

Wenting Wang, Yaguo Lei, Tao Yan, Naipeng Li, Asoke Nandi

How to Cite:  

Wang, W., Y. Lei, T. Yan, N. Li, and A. Nandi. “Residual Convolution Long Short-Term Memory Network for Machines Remaining Useful Life Prediction and Uncertainty Quantification”. Journal of Dynamics, Monitoring and Diagnostics, vol. 1, no. 1, Dec. 2021, pp. 2-8, doi:10.37965/jdmd.v2i2.43.

Title: 

Short-Time Fourier Transform Using Odd Symmetric Window Function

Authors: 

Miaofen Li, Youmin Liu, Shaodan Zhi, Tianyang Wang, Fulei Chu

How to Cite:  

Li, M., Y. Liu, S. Zhi, T. Wang, and F. Chu. “Short-Time Fourier Transform Using Odd Symmetric Window Function”. Journal of Dynamics, Monitoring and Diagnostics, vol. 1, no. 1, Dec. 2021, pp. 37-45, doi:10.37965/jdmd.v2i2.39.

Title: 

A Modified Generative Adversarial Network for Fault Diagnosis in High-Speed Train Components with Imbalanced and Heterogeneous Monitoring Data

Authors: 

Chong Wang, Jie Liu, Enrico Zio

How to Cite:  

Wang, C., J. Liu, and E. Zio. “A Modified Generative Adversarial Network for Fault Diagnosis in High-Speed Train Components With Imbalanced and Heterogeneous Monitoring Data”. Journal of Dynamics, Monitoring and Diagnostics, Apr. 2022, pp. 84-92, doi:10.37965/jdmd.2022.68.