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Proceedings Papers

A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency

Bharath Pidaparthi, Samy Missoum
Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A030, August 14–17, 2022
Paper No: DETC2022-90115
DOI: https://doi.org/10.1115/DETC2022-90115
View Paper titled, A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency
Click here to open pdf in another window PDF for A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency
Topics: Failure, Heat exchangers, Probability, Reliability, Support vector machines
Proceedings Papers

Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications

Sara Luciani, Stefano Feraco, Mario Silvagni, Angelo Bonfitto, Nicola Amati, Andrea Tonoli
Proc. ASME. IDETC-CIE2022, Volume 1: 24th International Conference on Advanced Vehicle Technologies (AVT), V001T01A014, August 14–17, 2022
Paper No: DETC2022-89454
DOI: https://doi.org/10.1115/DETC2022-89454
View Paper titled, Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications
Click here to open pdf in another window PDF for Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications
Topics: Artificial intelligence, Artificial neural networks, Lithium-ion batteries, Support vector machines
Proceedings Papers

A Constraint-Handling Technique for Parametric Optimization and Control Co-Design

Ying-Kuan Tsai, Richard J. Malak, Jr.
Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A009, August 14–17, 2022
Paper No: DETC2022-89957
DOI: https://doi.org/10.1115/DETC2022-89957
View Paper titled, A Constraint-Handling Technique for Parametric Optimization and Control Co-Design
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Topics: Design, Optimization, Genetic algorithms, Pendulums, Support vector machines, Algorithms, Control equipment, Control systems, Dynamics (Mechanics), Machine learning
Proceedings Papers

A Study of Machine Learning Framework for Enabling Early Defect Detection in Wire Arc Additive Manufacturing Processes

Nowrin Akter Surovi, Shaista Hussain, Gim Song Soh
Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A002, August 14–17, 2022
Paper No: DETC2022-89164
DOI: https://doi.org/10.1115/DETC2022-89164
View Paper titled, A Study of Machine Learning Framework for Enabling Early Defect Detection in Wire Arc Additive Manufacturing Processes
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Topics: Additive manufacturing, Flaw detection, Machine learning, Wire, Acoustics, Printing, Support vector machines, Pressure
Proceedings Papers

Gait Prediction and Mechanism Design for 1-DOF Lower Limb Rehabilitation Devices Based on Machine Learning

Wanbing Song, Yating Zhang, Zhaojie Ge, Ping Zhao
Proc. ASME. IDETC-CIE2021, Volume 8A: 45th Mechanisms and Robotics Conference (MR), V08AT08A045, August 17–19, 2021
Paper No: DETC2021-70009
DOI: https://doi.org/10.1115/DETC2021-70009
View Paper titled, Gait Prediction and Mechanism Design for 1-DOF Lower Limb Rehabilitation Devices Based on Machine Learning
Click here to open pdf in another window PDF for Gait Prediction and Mechanism Design for 1-DOF Lower Limb Rehabilitation Devices Based on Machine Learning
Topics: Design, Machine learning, Patient rehabilitation, Rehabilitation devices, Trajectories (Physics), Algorithms, Machinery, Shapes, Support vector machines, Trains
Proceedings Papers

Towards Transparent Motion Planning of Wearable Rehabilitation Exoskeletons via Model-Based Estimation

Jiamin Wang, David Blankenship, Oumar Barry
Proc. ASME. IDETC-CIE2021, Volume 9: 17th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC), V009T09A030, August 17–19, 2021
Paper No: DETC2021-70011
DOI: https://doi.org/10.1115/DETC2021-70011
View Paper titled, Towards Transparent Motion Planning of Wearable Rehabilitation Exoskeletons via Model-Based Estimation
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Topics: Exoskeleton devices, Path planning, Transparency, Algorithms, Delays, Optimization, Signals, Stress, Control equipment, Design
Proceedings Papers

Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage

Apeksha Lanjile, Mohamed Younis, Seung-Jun Kim, Soobum Lee
Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A017, August 18–21, 2019
Paper No: DETC2019-97553
DOI: https://doi.org/10.1115/DETC2019-97553
View Paper titled, Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage
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Topics: Leakage, Pipelines, Acoustics, Pipes, Sensors, Accelerometers, Corrosion, Cracking (Materials), Damage, Fluids
Proceedings Papers

Human Computer Interface Using Electroencephalography for Driver Behavior Classification

Vamsi K. Manchala, Alvaro V. Clara, Susheelkumar C. Subramanian, Sangram Redkar, Thomas Sugar
Proc. ASME. IDETC-CIE2019, Volume 3: 21st International Conference on Advanced Vehicle Technologies; 16th International Conference on Design Education, V003T01A014, August 18–21, 2019
Paper No: DETC2019-97540
DOI: https://doi.org/10.1115/DETC2019-97540
View Paper titled, Human Computer Interface Using Electroencephalography for Driver Behavior Classification
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Topics: Electroencephalography, User interfaces, Vehicles, Artificial neural networks, Machine learning, Support vector machines, Brain, Computers
Proceedings Papers

Predicting Multi-Disciplinary Design Performance Utilizing Automated Topic Discovery

Zachary Ball, Kemper Lewis
Proc. ASME. IDETC-CIE2019, Volume 7: 31st International Conference on Design Theory and Methodology, V007T06A053, August 18–21, 2019
Paper No: DETC2019-97189
DOI: https://doi.org/10.1115/DETC2019-97189
View Paper titled, Predicting Multi-Disciplinary Design Performance Utilizing Automated Topic Discovery
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Topics: Design, Algorithms, Engineering design, Collaboration, Competencies, Engineering design processes, Engineering disciplines, Students, Support vector machines, Teams
Proceedings Papers

Dimensional Prediction for FDM Machines Using Artificial Neural Network and Support Vector Regression

Jiaqi Lyu, Souran Manoochehri
Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A033, August 18–21, 2019
Paper No: DETC2019-97963
DOI: https://doi.org/10.1115/DETC2019-97963
View Paper titled, Dimensional Prediction for FDM Machines Using Artificial Neural Network and Support Vector Regression
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Topics: Artificial neural networks, Machinery, Modeling, Support vector machines
Proceedings Papers

Comparing Machine Learning Regression Techniques for Transmission-Related Storm Outages

Caitlyn E. Clark, Bryony DuPont
Proc. ASME. IDETC-CIE2018, Volume 2A: 44th Design Automation Conference, V02AT03A024, August 26–29, 2018
Paper No: DETC2018-85127
DOI: https://doi.org/10.1115/DETC2018-85127
View Paper titled, Comparing Machine Learning Regression Techniques for Transmission-Related Storm Outages
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Topics: Machine learning, Storms, Polynomials, Cost benefit analysis, Probability, Risk, Shorelines, Support vector machines
Proceedings Papers

Short-Term Load Forecasting With Different Aggregation Strategies

Cong Feng, Jie Zhang
Proc. ASME. IDETC-CIE2018, Volume 2A: 44th Design Automation Conference, V02AT03A019, August 26–29, 2018
Paper No: DETC2018-86084
DOI: https://doi.org/10.1115/DETC2018-86084
View Paper titled, Short-Term Load Forecasting With Different Aggregation Strategies
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Topics: Load forecasting, Stress, Algorithms, Artificial neural networks, Machine learning, Machinery, Power systems (Machinery), Robustness, Structures, Support vector machines
Proceedings Papers

High Degree of Freedom Hand Pose Tracking Using Limited Strain Sensing and Optical Training

Wentai Zhang, Jonelle Z. Yu, Fangcheng Zhu, Yifang Zhu, Nurcan Gecer Ulu, Batuhan Arisoy, Levent Burak Kara
Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A019, August 26–29, 2018
Paper No: DETC2018-85870
DOI: https://doi.org/10.1115/DETC2018-85870
View Paper titled, High Degree of Freedom Hand Pose Tracking Using Limited Strain Sensing and Optical Training
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Topics: Artificial neural networks, Control equipment, Degrees of freedom, Feedforward control, Manufacturing, Optimization, Sensors, Strain gages, Strain sensors, Support vector machines
Proceedings Papers

A Multi-Objective Robust Optimization Approach Under Interval Uncertainty Based on Kriging and Support Vector Machine

Tingli Xie, Ping Jiang, Qi Zhou, Leshi Shu, Yang Yang
Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A036, August 26–29, 2018
Paper No: DETC2018-86237
DOI: https://doi.org/10.1115/DETC2018-86237
View Paper titled, A Multi-Objective Robust Optimization Approach Under Interval Uncertainty Based on Kriging and Support Vector Machine
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Topics: Optimization, Support vector machines, Uncertainty, Design, Engineering design, Engineering simulation, Simulation, Vehicles
Proceedings Papers

Automatic Postprocessing of Topology Optimization Solutions by Using Support Vector Machines

Niclas Strömberg
Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A001, August 26–29, 2018
Paper No: DETC2018-85051
DOI: https://doi.org/10.1115/DETC2018-85051
View Paper titled, Automatic Postprocessing of Topology Optimization Solutions by Using Support Vector Machines
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Topics: Optimization, Support vector machines, Topology, Computer-aided design, Density, Computer software, Design, Engineers, Filters, Modeling
Proceedings Papers

From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback

Christian E. Lopez, Conrad S. Tucker
Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A039, August 6–9, 2017
Paper No: DETC2017-67340
DOI: https://doi.org/10.1115/DETC2017-67340
View Paper titled, From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback
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Topics: Feedback, Mining, Machine learning, Support vector machines, Workshops (Work spaces)
Proceedings Papers

3D Machined Surface Topography Forecasting With Space-Time Multioutput Support Vector Regression Using High Definition Metrology

Yiping Shao, Shichang Du, Lifeng Xi
Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A069, August 6–9, 2017
Paper No: DETC2017-67155
DOI: https://doi.org/10.1115/DETC2017-67155
View Paper titled, 3D Machined Surface Topography Forecasting With Space-Time Multioutput Support Vector Regression Using High Definition Metrology
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Topics: Metrology, Spacetime, Support vector machines, Engine cylinders, Manufacturing, Milling
Proceedings Papers

Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques

Achyuth Kothuru, Sai Prasad Nooka, Patricia Iglesias Victoria, Rui Liu
Proc. ASME. IDETC-CIE2017, Volume 10: 2017 ASME International Power Transmission and Gearing Conference, V010T11A030, August 6–9, 2017
Paper No: DETC2017-68067
DOI: https://doi.org/10.1115/DETC2017-68067
View Paper titled, Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques
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Topics: Gears, Machine learning, Milling, Signals, Wear, Cutting, Cutting tools, Machining, Support vector machines, Algorithms
Proceedings Papers

Automated Municipal Solid Waste Sorting for Recycling Using a Mobile Manipulator

Sathish Gundupalli Paulraj, Subrata Hait, Atul Thakur
Proc. ASME. IDETC-CIE2016, Volume 5A: 40th Mechanisms and Robotics Conference, V05AT07A045, August 21–24, 2016
Paper No: DETC2016-59842
DOI: https://doi.org/10.1115/DETC2016-59842
View Paper titled, Automated Municipal Solid Waste Sorting for Recycling Using a Mobile Manipulator
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Topics: Manipulators, Municipal solid wastes, Recycling, Algorithms, Doors, Robotics, Support vector machines, Aluminum, Developing nations, Imaging
Proceedings Papers

Wind Turbine Blade Damage Detection Using Various Machine Learning Algorithms

Taylor Regan, Rukiye Canturk, Elizabeth Slavkovsky, Christopher Niezrecki, Murat Inalpolat
Proc. ASME. IDETC-CIE2016, Volume 8: 28th Conference on Mechanical Vibration and Noise, V008T10A040, August 21–24, 2016
Paper No: DETC2016-59686
DOI: https://doi.org/10.1115/DETC2016-59686
View Paper titled, Wind Turbine Blade Damage Detection Using Various Machine Learning Algorithms
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Topics: Algorithms, Blades, Damage, Machine learning, Wind turbines, Acoustics, Cavities, Composite materials, Microphones, Support vector machines