| A comparative study on machine learning algorithms for smart manufacturing: tool wear prediction using random forests D Wu, C Jennings, J Terpenny, RX Gao, S Kumara Journal of Manufacturing Science and Engineering 139 (7), 071018, 2017 | 604 | 2017 |
| Cloud-based machine learning for predictive analytics: Tool wear prediction in milling D Wu, C Jennings, J Terpenny, S Kumara 2016 IEEE International Conference on Big Data (Big Data), 2062-2069, 2016 | 95 | 2016 |
| Forecasting Obsolescence Risk and Product Life Cycle With Machine Learning C Jennings, D Wu, J Terpenny IEEE Transactions on Components, Packaging and Manufacturing Technology 6 (9 …, 2016 | 80 | 2016 |
| Cloud-based parallel machine learning for tool wear prediction D Wu, C Jennings, J Terpenny, S Kumara, RX Gao Journal of manufacturing science and engineering 140 (4), 041005, 2018 | 70 | 2018 |
| Data-Driven Prognostics Using Random Forests: Prediction of Tool Wear D Wu, C Jennings, J Terpenny, R Gao, S Kumara Proceedings of the ASME 2017 International Manufacturing Science and …, 2017 | 29 | 2017 |
| Early-time Ultraviolet Spectroscopy and Optical Follow-up Observations of the Type IIP Supernova 2021yja SS Vasylyev, AV Filippenko, C Vogl, TG Brink, PJ Brown, T de Jaeger, ... The Astrophysical Journal 934 (2), 134, 2022 | 14 | 2022 |
| Photometric and spectroscopic analysis of the Type II SN 2020jfo with a short plateau B Ailawadhi, R Dastidar, K Misra, R Roy, D Hiramatsu, DA Howell, ... Monthly Notices of the Royal Astronomical Society 519 (1), 248-270, 2023 | 12 | 2023 |
| The Lick Observatory Supernova Search follow-up program: photometry data release of 70 SESNe WK Zheng, BE Stahl, T De Jaeger, AV Filippenko, SQ Wang, WP Gan, ... Monthly Notices of the Royal Astronomical Society 512 (3), 3195-3214, 2022 | 11 | 2022 |
| Cloud-based parallel machine learning for prognostics and health management: a tool wear prediction case study D Wu, C Jennings, J Terpenny, S Kumara, R Gao Journal of Manufacturing Science and Engineering 140 (4), 2017 | 7 | 2017 |
| Forecasting obsolescence risk using machine learning C Jennings, D Wu, J Terpenny International Manufacturing Science and Engineering Conference 49903 …, 2016 | 7 | 2016 |
| Taxonomy of Factors for Lifetime Buy C Jennings, J Terpenny Industrial and Systems Engineering Research Conference, 2015 | 6 | 2015 |
| Cloud-based machine learning for predic-tive analytics: prediction of tool wear D Wu, C Jennings, J Terpenny, S Kumara Proceedings of 2016 IEEE international conference on big data, 2016 | 5 | 2016 |
| Clustering Design Structure Matrices: A Comparison of Methods Using Minimum Description Length A Kulkarni, C Jennings, M Hoffman, E Blanco, JP Terpenny, TW Simpson IISE Conference 2018: Orlando, Florida, 2018 | 4 | 2018 |
| Receiver operating characteristic analysis for forecasting obsolescence risk C Jennings, D Wu, J Terpenny IIE Annual Conference. Proceedings, 722-727, 2017 | 3 | 2017 |
| PIPS, an advanced platform for period detection in time series – I. Fourier-likelihood periodogram and application to RR Lyrae stars YS Murakami, C Jennings, AM Hoffman, AB Savel, J Sunseri, R Baer-Way, ... Monthly Notices of the Royal Astronomical Society 514 (3), 4489-4505, 2022 | 2 | 2022 |
| A low-mass helium star progenitor model for the Type Ibn SN 2020nxt Q Wangq, A Goel, L Dessart, OD Fox, M Shahbandeh, S Rest, A Rest, ... Monthly Notices of the Royal Astronomical Society, stae1038, 2024 | | 2024 |
| The Hubble Space Telescope Survey of M31 Satellite Galaxies. III. Calibrating the Horizontal Branch as an Age Indicator for Nearby Galaxies C Jennings, A Savino, D Weisz, N Kallivayalil, A Cole, M Collins, ... arXiv preprint arXiv:2311.16397, 2023 | | 2023 |
| PIPS: Period detection and Identification Pipeline Suite YS Murakami, C Jennings, AM Hoffman, J Sunseri, R Baer-Way, BE Stahl, ... Astrophysics Source Code Library, ascl: 2108.019, 2021 | | 2021 |
| New Four-Band Photometry of RR Lyrae Stars in M3 C Jennings, R Baer-Way, J Sunseri, Y Murakami, N Girish, W Zheng, ... American Astronomical Society Meeting Abstracts 53 (6), 314.03, 2021 | | 2021 |
| Forecasting Technical and Functional Obsolescence for Improved Business Processes C Jennings The Pennsylvania State University, 2018 | | 2018 |
Janis TerpennyGeorge Mason UniversityVerified email at gmu.edu
