Journal of Computing and Information Science in Engineering: Recent submissions
Now showing items 241-260 of 1535
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Reviewer’s Recognition
(The American Society of Mechanical Engineers (ASME), 2024)The Editor and Editorial Board of the Journal of Computing and Information Science in Engineering would like to thank all of the reviewers for volunteering their expertise and time reviewing manuscripts in 2023. Serving ... -
Special Issue: Extended Reality in Design and Manufacturing
(The American Society of Mechanical Engineers (ASME), 2024)Extended Reality (XR) is a collective term that contains Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and everything in between. VR is an immersive technology that allows users to interact within a ... -
AnnotateXR: An Extended Reality Workflow for Automating Data Annotation to Support Computer Vision Applications
(The American Society of Mechanical Engineers (ASME), 2024)Computer vision (CV) algorithms require large annotated datasets that are often labor-intensive and expensive to create. We propose AnnotateXR, an extended reality (XR) workflow to collect various high-fidelity data and ... -
Unsupervised Anomaly Detection via Nonlinear Manifold Learning
(The American Society of Mechanical Engineers (ASME), 2024)Anomalies are samples that significantly deviate from the rest of the data and their detection plays a major role in building machine learning models that can be reliably used in applications such as data-driven design and ... -
Stress Representations for Tensor Basis Neural Networks: Alternative Formulations to Finger–Rivlin–Ericksen
(The American Society of Mechanical Engineers (ASME), 2024)Data-driven constitutive modeling frameworks based on neural networks and classical representation theorems have recently gained considerable attention due to their ability to easily incorporate constitutive constraints ... -
Stochastic Defect Localization for Cooperative Additive Manufacturing Using Gaussian Mixture Maps
(The American Society of Mechanical Engineers (ASME), 2024)Robotic additive manufacturing (RAM) offers significant improvements in maximum build volume compared to conventional bounded designs (e.g., gantry) by leveraging high degrees-of-freedom machines and multi-robot cooperation. ... -
Machine-Learning Metacomputing for Materials Science Data
(The American Society of Mechanical Engineers (ASME), 2024)Materials science requires the collection and analysis of great quantities of data. These data almost invariably require various post-acquisition computation to remove noise, classify observations, fit parametric models, ... -
Physics-Informed Fully Convolutional Networks for Forward Prediction of Temperature Field and Inverse Estimation of Thermal Diffusivity
(The American Society of Mechanical Engineers (ASME), 2024)Physics-informed neural networks (PINNs) are a novel approach to solving partial differential equations (PDEs) through deep learning. They offer a unified manner for solving forward and inverse problems, which is beneficial ... -
Multi-Fidelity Physics-Informed Generative Adversarial Network for Solving Partial Differential Equations
(The American Society of Mechanical Engineers (ASME), 2024)We propose a novel method for solving partial differential equations using multi-fidelity physics-informed generative adversarial networks. Our approach incorporates physics supervision into the adversarial optimization ... -
A Physics-Informed General Convolutional Network for the Computational Modeling of Materials With Damage
(The American Society of Mechanical Engineers (ASME), 2024)Despite their effectiveness in modeling complex phenomena, the adoption of machine learning (ML) methods in computational mechanics has been hindered by the lack of availability of training datasets, limitations on the ... -
Probabilistic Printability Maps for Laser Powder Bed Fusion Via Functional Calibration and Uncertainty Propagation
(The American Society of Mechanical Engineers (ASME), 2024)In this work, we develop an efficient computational framework for process space exploration in laser powder bed fusion (LPBF) based additive manufacturing technology. This framework aims to find suitable processing conditions ... -
What to Consider at the Development of Educational Programs and Courses About Next-Generation Cyber-Physical Systems?
(The American Society of Mechanical Engineers (ASME), 2024)We live in an age in which new things are emerging faster than their deep understanding. This statement, in particular, applies to doing research and educating university students concerning next-generation cyber-physical ... -
Data Privacy Preserving for Centralized Robotic Fault Diagnosis With Modified Dataset Distillation
(The American Society of Mechanical Engineers (ASME), 2024)Industrial robots generate monitoring data rich in sensitive information, often making enterprises reluctant to share, which impedes the use of data in fault diagnosis modeling. Dataset distillation (DD) is an effective ... -
Multi-Unmanned Aerial Vehicle-Assisted Flood Navigation of Waterborne Vehicles Using Deep Reinforcement Learning
(The American Society of Mechanical Engineers (ASME), 2024)During disasters, such as floods, it is crucial to get real-time ground information for planning rescue and response operations. With the advent of technology, unmanned aerial vehicles (UAVs) are being deployed for real-time ... -
Engineering-Guided Deep Learning of Melt-Pool Dynamics for Additive Manufacturing Quality Monitoring
(The American Society of Mechanical Engineers (ASME), 2024)Additive manufacturing (AM) fabricates three-dimensional parts via layer-by-layer deposition and solidification of materials. Due to the complexity of this process, advanced sensing is increasingly employed to facilitate ... -
Risk-Based Design Optimization via Scenario Generation and Genetic Programming Under Hybrid Uncertainties
(The American Society of Mechanical Engineers (ASME), 2024)The design of complex systems often requires the incorporation of uncertainty optimization strategies to mitigate system failures resulting from multiple uncertainties during actual operation. Risk-based design optimization, ... -
Digital Twins and Civil Engineering Phases: Reorienting Adoption Strategies
(The American Society of Mechanical Engineers (ASME), 2024)Digital twin (DT) technology has received immense attention over the years due to the promises it presents to various stakeholders in science and engineering. As a result, different thematic areas of DT have been explored. ... -
JCISE Editorial Board—Year 2023
(The American Society of Mechanical Engineers (ASME), 2023)The Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to scientific computing methods (e.g., modeling, simulation, representation, and algorithm) and computational tools (e.g., ... -
Sensor Data Protection Through Integration of Blockchain and Camouflaged Encryption in Cyber-Physical Manufacturing Systems
(The American Society of Mechanical Engineers (ASME), 2024)The advancement of sensing technology enables efficient data collection from manufacturing systems for monitoring and control. Furthermore, with the rapid development of the Internet of Things (IoT) and information ... -
Taxonomy-Driven Graph-Theoretic Framework for Manufacturing Cybersecurity Risk Modeling and Assessment
(The American Society of Mechanical Engineers (ASME), 2024)Identifying, analyzing, and evaluating cybersecurity risks are essential to devise effective decision-making strategies to secure critical manufacturing against potential cyberattacks. However, a manufacturing-specific ...