Journal of Computing and Information Science in Engineering: Recent submissions
Now showing items 101-120 of 1402
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Band-Limited Vibrotactile Noise Enhances Fingertip Haptic Sensation
(The American Society of Mechanical Engineers (ASME), 2024)This paper presents a method to enhance the haptic sensation of the fingertip by applying a vibrotactile noise to the wrist, an application of stochastic resonance. This sensation is known to improve when a sufficiently ... -
Diffusion Generative Model-Based Learning for Smart Layer-Wise Monitoring of Additive Manufacturing
(The American Society of Mechanical Engineers (ASME), 2024)Despite the rapid adoption of deep learning models in additive manufacturing (AM), significant quality assurance challenges continue to persist. This is further emphasized by the limited availability of sample objects for ... -
Helical Actuator–Driven Inchworm Robot Design and Prototype
(The American Society of Mechanical Engineers (ASME), 2024)Bio-inspired robots provide solutions in many applications. Robots that can traverse and transport materials through confined areas are useful in disaster response, mining, mapping, and tunneling. The proposed robot is an ... -
Toward Fatigue-Tolerant Design of Additively Manufactured Strut-Based Lattice Metamaterials
(The American Society of Mechanical Engineers (ASME), 2024)The advent of additive manufacturing (AM) has enabled the prototyping of periodic and non-periodic metamaterials (a.k.a. lattice or cellular structures) that could be deployed in a variety of engineering applications where ... -
Fairness- and Uncertainty-Aware Data Generation for Data-Driven Design Based on Active Learning
(The American Society of Mechanical Engineers (ASME), 2024)The design dataset is the backbone of data-driven design. Ideally, the dataset should be fairly distributed in both shape and property spaces to efficiently explore the underlying relationship. However, the classical ... -
Special Issue: Highlights of CIE 2023
(The American Society of Mechanical Engineers (ASME), 2024)This special issue contains a selection of 14 manuscripts (two technical briefs and 12 research papers) from the 43nd American Society of Mechanical Engineers (ASME) Computers and Information in Engineering (CIE) Conference ... -
Probing an Easy-to-Deploy Multi-Agent Manufacturing System Based on Agent Computing Node: Architecture, Implementation, and Case Study
(The American Society of Mechanical Engineers (ASME), 2024)Due to the widespread adoption of personalized customization services, the application contexts within discrete manufacturing workshops have become increasingly intricate, necessitating the modern industry to evolve toward ... -
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 ...