アクセスランキング(PKV)
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Mechanical Engineering
Discover highly accessed papers in this field.
Top Paper
Jubilee Review: The 65 Years of the ASME Machine Design Award (1958–2023)
| 順位 | タイトル | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 著者 | 雑誌 | 巻 | 号 | ページ | 年 | PKVアクセス数 | |||
| 731 | SNIFF: Reverse Engineering of Neural Networks With Fault Attacks | ||||||||
| Jakub Breier, Dirmanto Jap, Xiaolu Hou, Shivam Bhasin, Yang Liu | IEEE Transactions on Reliability | 71 | 4 | 1527–1539 | 2022 | 9.75 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 732 | The Detection of Rolling-Element Bearing Faults in Non-stationary Quasi-Parallel Machinery Using Residual Analysis Augmented by Neural Networks | ||||||||
| Dustin Helm, Markus Timusk | International Journal of Prognostics and Health Management | 12 | 2 | 2915–None | 2021 | 9.75 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 733 | Prognostics and Health Management for Maintenance Practitioners - Review, Implementation and Tools Evaluation | ||||||||
| Vepa Atamuradov, Kamal Medjaher, Pierre Dersin, Benjamin Lamoureux, Noureddine Zerhouni | International Journal of Prognostics and Health Management | 8 | 3 | 2667–None | 2017 | 9.75 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 734 | Online Prediction and Improvement of Reliability for Service Oriented Systems | ||||||||
| Zuohua Ding, Ting Xu, Tiantian Ye, Yuan Zhou | IEEE Transactions on Reliability | 65 | 3 | 1133–1148 | 2016 | 9.75 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 735 | Automated Bug Report Field Reassignment and Refinement Prediction | ||||||||
| Xin Xia, David Lo, Emad Shihab, Xinyu Wang | IEEE Transactions on Reliability | 65 | 3 | 1094–1113 | 2016 | 9.75 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 736 | Enhancing Digit Recognition for Luminous Images in Edge Computing Through Transfer Learning With Robustness and Fault Tolerance | ||||||||
| Tse-Chuan Hsu, Yao-Hong Tsai, William Cheng-Chung Chu | IEEE Transactions on Reliability | 74 | 2 | 2529–2537 | 2025 | 9.73 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 737 | A Multi-Output Deep Learning Model for Fault Diagnosis Based on Time-Series Data | ||||||||
| Ahmed Al-Ajeli, Eman S. Alshamery | International Journal of Prognostics and Health Management | 15 | 1 | 3829–None | 2024 | 9.73 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 738 | Enhanced Method for Localization of Partial Discharges in Oil-Filled Transformers Using Acoustic Emission Signals | ||||||||
| Yasutomo Otake; Kunihiko Tajiri | International Journal of Prognostics and Health Management | 15 | 3 | 3852–None | 2024 | 9.73 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 739 | Early Fault Detection in Particle Accelerator Power Electronics Using Ensemble Learning | ||||||||
| Majdi I. Radaideh, Chris Pappas, Mark Wezensky, Pradeep Ramuhalli, Sarah Cousineau | International Journal of Prognostics and Health Management | 14 | 1 | 3419–None | 2023 | 9.73 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||
| 740 | Predicting the Evolution of Controlled Systems Modeled by Finite Markov Processes | ||||||||
| Shuo Li, Matteo Pozzi | IEEE Transactions on Reliability | 71 | 1 | 28–46 | 2022 | 9.73 | |||
| 平均評価: / 5 ( 件のレビュー) | |||||||||