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Journal of Computing and Information Science in Engineering
EISSN: 1944-7078
ISSN: 1530-98270
Priority: 4
Publisher: American Society of Mechanical Engineers
Description: The Journal of Computing and Information Science in Engineering publishes archival research results and advanced technical applications More ...
Now showing items 921-930 of 1277
Poincaré Plot Features and Statistical Features From Current and Vibration Signals for Fault Severity Classification of Helical Gear Tooth Breaks
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Most of the approaches of feature extraction for data-driven rotating machinery fault diagnosis assume characteristics of periodicity and seasonality typically inherent to linear signals obtained from different sensors. ...
A Quantitative Insight Into the Role of Skip Connections in Deep Neural Networks of Low Complexity: A Case Study Directed at Fluid Flow Modeling
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Deep feed-forward networks, with high complexity, backpropagate the gradient of the loss function from final layers to earlier layers. As a consequence, the “gradient” may descend rapidly toward zero. This is known as the ...
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In recent years, identification of nonlinear dynamical systems from data has become increasingly popular. Sparse regression approaches, such as sparse identification of nonlinear dynamics (SINDy), fostered the development ...
Study of Electroencephalograph-Based Evaluation Method of Car Sound Quality
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Those methods that are applied to evaluate car sound quality by means of the scoring mode cannot guarantee the universality of results. Some studies have shown that the sound-induced change of electroencephalograph (EEG) ...
Reusing and Extending Standards-Based Unit Manufacturing Process Models for Characterizing Sustainability Performance
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Over the past two decades, numerous efforts have characterized manufacturing processes for sustainability performance. These efforts have been pursued primarily by manufacturing researchers in academic and governmental ...
Combining Uneliminated Algebraic Formulations With Sparse Linear Solvers to Increase the Speed and Accuracy of Homotopy Path Tracking for Kinematic Synthesis
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The method of kinematic synthesis requires finding the solution set of a system of polynomials. Parameter homotopy continuation is used to solve these systems and requires repeatedly solving systems of linear equations. ...
Physics Informed Synthetic Image Generation for Deep LearningBased Detection of Wrinkles and Folds
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Deep learningbased image segmentation methods have showcased tremendous potential in defect detection applications for several manufacturing processes. Currently, majority of deep learning research for defect detection ...
Upper Extremity Joint Torque Estimation Through an ElectromyographyDriven Model
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Cerebrovascular accidents like a stroke can affect the lower limb as well as upper extremity joints (i.e., shoulder, elbow, or wrist) and hinder the ability to produce necessary torque for activities of daily living. In ...
MetricBased MetaLearning for CrossDomain FewShot Identification of Welding Defect
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: With the development of deep learning and information technologies, intelligent welding systems have been further developed, which achieve satisfactory identification of defective welds. However, the lack of labeled samples ...
PhysicsConstrained Bayesian Neural Network for Bias and Variance Reduction
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: When neural networks are applied to solve complex engineering problems, the lack of training data can make the predictions of the surrogate inaccurate. Recently, physicsconstrained neural networks were introduced to integrate ...