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Keywords: deep learning
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Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A027, August 17–19, 2021
Paper No: DETC2021-69058
... forecasting model selection intersection waiting time deep learning Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August 17-19, 2021, Virtual, Online DETC2021-69058 SHORT-TERM VEHICLE VELOCITY...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 5: 26th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A029, August 17–19, 2021
Paper No: DETC2021-71403
..., two categories of Machine Learning (ML) and Deep Learning (DL) techniques are used to classify consumer electronics. ML models include Naïve Bayes with Bernoulli, Gaussian, Multinomial distributions, and Support Vector Machine (SVM) algorithms with four kernels of Linear, Radial Basis Function (RBF...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 6: 33rd International Conference on Design Theory and Methodology (DTM), V006T06A051, August 17–19, 2021
Paper No: DETC2021-72406
... design performance, and identifying design actions identification. design thinking design embedding design cognition deep learning Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August...
Topics: Design
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 8A: 45th Mechanisms and Robotics Conference (MR), V08AT08A037, August 17–19, 2021
Paper No: DETC2021-71629
... associated with inherently uncertain inputs and constraints. deep generative models path synthesis planar mechanisms machine learning deep learning variational autoencoder latent space Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A016, August 17–19, 2021
Paper No: DETC2021-70596
... digital simulation of team-based multidisciplinary design, where the actions of individual team members are simulated using deep learning models trained on historical human design trends. The main benefit of this work is to simulate design session events and interactions without human participants...
Topics: Design, Teams
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A034, August 17–19, 2021
Paper No: DETC2021-72149
... learning (ML) for user experience β-VAE deep learning t-SNE Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August 17-19, 2021, Virtual, Online DETC2021-72149 SKETCH-BASED MECHANISM SIMULATION...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A022, August 17–19, 2021
Paper No: DETC2021-68237
... positioning error using the CNN, the joint 1 current is a feature. This indicates that the vibration current in joint 1 is a factor in the X-axis positioning error. industrial robot positioning accuracy deep learning convolutional neural network Proceedings of the ASME 2021 International Design...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 10: 44th Mechanisms and Robotics Conference (MR), V010T10A031, August 17–19, 2020
Paper No: DETC2020-22679
... deep generative models path synthesis planar linkage synthesis machine learning (ML) for user experience ML for managing uncertainties ML for computational creativity deep learning Abstract Abstract This paper brings together computer vision, mechanism synthesis, and machine...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A005, August 17–19, 2020
Paper No: DETC2020-22399
.... The effectiveness of this approach is demonstrated by training a GAN on designs intended to be manufacturable on a 3-axis computer numerically controlled (CNC) milling machine. Keywords: Topology optimization, design for manufacturability, deep learning, manufacturing constraints, generative adversarial networks 1...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 9: 15th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, V009T12A026, August 18–21, 2019
Paper No: DETC2019-97011
... Abstract The mushroom cultivation is an important smart agriculture in Taiwan. This study uses the deep learning object detection method to inspect the cap flaws or positional imperfection in the automatic production of the mushroom PP-bag packaging. This study uses the UR robotic arm...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A011, August 18–21, 2019
Paper No: DETC2019-98472
... Abstract The demand for fast and accurate structural analysis is becoming increasingly more prevalent with the advance of generative design and topology optimization technologies. As one step toward accelerating structural analysis, this work explores a deep learning based approach...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A029, August 18–21, 2019
Paper No: DETC2019-97625
..., and heuristics, which are important to the development of new algorithms embedded with human intelligence to augment computational design. In this paper, we develop a deep learning based approach to model and predict designers’ sequential decisions in a system design context. The core of this approach...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A040, August 18–21, 2019
Paper No: DETC2019-98415
..., that have been researched using ML. Furthermore, this report discusses the benefits of ML for AM, as well as existing hurdles currently limiting applications. additive manufacturing machine learning deep learning data analytics algorithm survey review A REVIEW OF MACHINE LEARNING APPLICATIONS...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 5A: 43rd Mechanisms and Robotics Conference, V05AT07A029, August 18–21, 2019
Paper No: DETC2019-98193
... a single position of a given motion can change the topology and dimensions of the synthesized mechanisms drastically. Thus, the synthesis becomes a blind iterative process of maneuvering precision positions in the hope of finding good solutions. In this paper, we present a deep-learning based framework...