Kaveh Bastani - Publications
Affiliations: | 2016 | Virginia Polytechnic Institute and State University, Blacksburg, VA, United States |
Year | Citation | Score | |||
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2019 | Bastani K, Namavari H, Shaffer J. Latent Dirichlet Allocation (LDA) for Topic Modeling of the CFPB Consumer Complaints Expert Systems With Applications. 127: 256-271. DOI: 10.1016/J.Eswa.2019.03.001 | 0.32 | |||
2018 | Bastani K, Barazandeh B, Kong Z(. Fault Diagnosis in Multistation Assembly Systems Using Spatially Correlated Bayesian Learning Algorithm Journal of Manufacturing Science and Engineering-Transactions of the Asme. 140: 31003. DOI: 10.1115/1.4038184 | 0.322 | |||
2018 | Barazandeh B, Bastani K, Rafieisakhaei M, Kim S, Kong Z, Nussbaum MA. Robust Sparse Representation-Based Classification Using Online Sensor Data for Monitoring Manual Material Handling Tasks Ieee Transactions On Automation Science and Engineering. 15: 1573-1584. DOI: 10.1109/Tase.2017.2729583 | 0.597 | |||
2016 | Bastani K, Kim S, Kong ZJ, Nussbaum MA, Huang W. Online Classification and Sensor Selection Optimization With Applications to Human Material Handling Tasks Using Wearable Sensing Technologies Ieee Transactions On Human-Machine Systems. DOI: 10.1109/Thms.2016.2537747 | 0.593 | |||
2016 | Bastani K, Rao PK, Kong Z(. An online sparse estimation-based classification approach for real-time monitoring in advanced manufacturing processes from heterogeneous sensor data Iie Transactions (Institute of Industrial Engineers). 48: 579-598. DOI: 10.1080/0740817X.2015.1122254 | 0.612 | |||
2016 | Bastani K, Kong ZJ, Huang W, Zhou Y. Compressive sensing–based optimal sensor placement and fault diagnosis for multi-station assembly processes Iie Transactions (Institute of Industrial Engineers). 1-13. DOI: 10.1080/0740817X.2015.1096431 | 0.611 | |||
2013 | Bastani K, Kong Z, Huang W, Huo X, Zhou Y. Fault Diagnosis Using an Enhanced Relevance Vector Machine (RVM) for Partially Diagnosable Multistation Assembly Processes Ieee Transactions On Automation Science and Engineering. 10: 124-136. DOI: 10.1109/Tase.2012.2214383 | 0.534 | |||
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