Journal of Computing and Information Science in Engineering: Recent submissions
Now showing items 241-260 of 1402
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LongRange RiskAware Path Planning for Autonomous Ships in Complex and Dynamic Environments
(The American Society of Mechanical Engineers (ASME), 2023)Path planning and collision avoidance are common problems for researchers in vehicle and robotics engineering design. In the case of autonomous ships, the navigation is guided by the regulations for preventing collisions ... -
Hybrid MultiScale Convolutional Long ShortTerm Memory Network for Remaining Useful Life Prediction and Offset Analysis
(The American Society of Mechanical Engineers (ASME), 2023)Prognostic and health management (PHM) has become increasingly popular due to the requirement of improved maintenance techniques in the industry. Remaining useful life (RUL) estimation is an important parameter through ... -
Internal Leakage Detection in Hydraulic Pump Using ModelAgnostic Feature Ranking and Ensemble Classifiers
(The American Society of Mechanical Engineers (ASME), 2023)Hydraulic pumps are key drivers of fluid powerbased machines and demand high reliability during operation. Internal leakage is a key performance deteriorating fault that reduces pump’s efficiency and limits its predictability ... -
Reinforcement Learning for Efficient Design Space Exploration With Variable Fidelity Analysis Models
(The American Society of Mechanical Engineers (ASME), 2023)Reinforcement learning algorithms can autonomously learn to search a design space for highperformance solutions. However, modern engineering often entails the use of computationally intensive simulation, which can lead to ... -
Generative Transformers for Design Concept Generation
(The American Society of Mechanical Engineers (ASME), 2023)Generating novel and useful concepts is essential during the early design stage to explore a large variety of design opportunities, which usually requires advanced design thinking ability and a wide range of knowledge from ... -
Intelligent Detection and Classification of Surface Defects on ColdRolled Galvanized Steel Strips Using a DataDriven Faulty Model With Attention Mechanism
(The American Society of Mechanical Engineers (ASME), 2022)In the production of coldrolled galvanized steel strips used for stamping car body parts, the insitu and realtime defect detection is crucial for quality control, in which various types of defects inevitably occur. It is ... -
A New MultiObjective Genetic Algorithm for Assembly Line Balancing
(The American Society of Mechanical Engineers (ASME), 2022)The aim of this work is to enable a step towards a selfadapting digital toolset for manufacturing planning focusing on minimally constrained assembly line balancing. The approach includes the simultaneous definition of the ... -
A Bayesian Hierarchical Model for Extracting Individuals’ TheoryBased Causal Knowledge
(The American Society of Mechanical Engineers (ASME), 2022)Extracting an individual’s scientific knowledge is essential for improving educational assessment and understanding cognitive tasks in engineering activities such as reasoning and decisionmaking. However, knowledge extraction ... -
DataDriven Sensor Selection for Signal Estimation of Vertical Wheel Forces in Vehicles
(The American Society of Mechanical Engineers (ASME), 2022)Sensor selection is one of the key factors that dictate the performance of estimating vertical wheel forces in vehicle durability design. To select K most relevant sensors among S candidate ones that best fit the response ... -
An Efficient IsoScallop Toolpath Planning Strategy Using VoxelBased Computer Aided Design Model
(The American Society of Mechanical Engineers (ASME), 2022)The primary objective of an efficient computer numerical control (CNC) finishing toolpath strategy is to reduce the machining time and maintain desired surface finish (scallop). Among traditional toolpath planning strategies, ... -
Multifidelity PhysicsConstrained Neural Networks With Minimax Architecture
(The American Society of Mechanical Engineers (ASME), 2022)Data sparsity is still the main challenge to apply machine learning models to solve complex scientific and engineering problems. The root cause is the “curse of dimensionality” in training these models. Training algorithms ... -
Effects of Elastoplasticity, Damage, and Environmental Exposure on the Behavior of Adhesive StepLap Joints
(The American Society of Mechanical Engineers (ASME), 2022)The presence of damage in the adhesive material as well as combined environmental excitation in multimaterial adhesive steplap joints (ASLJs) often encountered in aircraft industries are frequently neglected. Historically, ... -
Physics Informed Synthetic Image Generation for Deep LearningBased Detection of Wrinkles and Folds
(The American Society of Mechanical Engineers (ASME), 2022)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 ... -
MetricBased MetaLearning for CrossDomain FewShot Identification of Welding Defect
(The American Society of Mechanical Engineers (ASME), 2022)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 ... -
Upper Extremity Joint Torque Estimation Through an ElectromyographyDriven Model
(The American Society of Mechanical Engineers (ASME), 2022)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 ... -
PhysicsConstrained Bayesian Neural Network for Bias and Variance Reduction
(The American Society of Mechanical Engineers (ASME), 2022)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 ... -
Monotonic Gaussian Process for PhysicsConstrained Machine Learning With Materials Science Applications
(The American Society of Mechanical Engineers (ASME), 2022)Physicsconstrained machine learning is emerging as an important topic in the field of machine learning for physics. One of the most significant advantages of incorporating physics constraints into machine learning methods ... -
Spatial Transform Depthwise OverParameterized Convolution Recurrent Neural Network for License Plate Recognition in Complex Environment
(The American Society of Mechanical Engineers (ASME), 2022)Automatic license plate recognition (ALPR) system has been widely used in intelligent transportation and other fields. However, in complex environments such as vehicle sound source localization, poor illumination, or bad ... -
Acceleration of a PhysicsBased Machine Learning Approach for Modeling and Quantifying ModelForm Uncertainties and Performing Model Updating
(The American Society of Mechanical Engineers (ASME), 2022)The nonparametric probabilistic method (NPM) for modeling and quantifying modelform uncertainties is a physicsbased, computationally tractable, machine learning method for performing uncertainty quantification and model ... -
A MultiFidelity Approach for Reliability Assessment Based on the Probability of Classification Inconsistency
(The American Society of Mechanical Engineers (ASME), 2022)Most multifidelity schemes for optimization or reliability assessment rely on regression surrogates, such as Gaussian processes. Contrary to these approaches, we propose a classificationbased multifidelity scheme for ...