Academic Articles & Research Papers

Upper Limb Movement Prediction Based on Segmented sEMG Signals

Motion intent recognition research is one of the key challenges in achieving human-robot collaboration in rehabilitation robots. In the traditional method, intention recognition is performed based on the complete sEMG, however, due to the m...

Learning metal microstructural heterogeneity through spatial mapping of diffraction latent space features

Abstract To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal microstructures that surpasses the limitations of current physics-b...

Machine Learning‐Driven Biomaterials Evolution

Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been ham...

Life prediction model of feedback rod in electro-hydraulic servo valve

Abstract Metallic elastic elements serve as critical structural components in advanced electro mechanical assemblies, where cyclic loading induces progressive rigidity reduction. Within electro-hydraulic servo valves (EHSV), the feedback me...

Supply Capability Evaluation of Intelligent Manufacturing Enterprises Based on Improved BP Neural Network

With the rapid development of economy and information technology, traditional manufacturing industry is facing severe challenges. Enterprises need to rectify the traditional manufacturing industry and realize the transformation from traditi...

Machine Learning in Additive Manufacturing: A Review

Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning

At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by...

Machine learning in manufacturing: advantages, challenges, and applications

The nature of manufacturing systems faces ever more complex, dynamic and at times even chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an efficient manner, it is essential to utilize all means av...

Design, framework and benchmark of safety monitors for black-box classifiers

Abstract The last decade has seen a surging opportunity for developing autonomous systems (e.g., fully autonomous driving, computer-guided robotic surgery, mobile robots for inspections and surveillance, and manufacturing robots) to relieve...

Unlocking pseudocapacitors prolonged electrode fabrication via ultra-short laser pulses and machine learning

Summary: Pseudocapacitors outperform lithium-ion batteries in terms of charging rate and power density. However, their electrode manufacturing procedures are prolonged and environmentally unfriendly, posing a research challenge. To address ...

Fault-Resilient Manufacturing Scheduling with Deep Learning and Constraint Solvers

As edge computing environments become increasingly dynamic, the need for efficient job scheduling and proactive fault prevention is becoming paramount. In such environments, minimizing machine downtime and maintaining productivity are criti...

A Protein‐Centric Strategy Coupled with Match‐Between‐Run Glycoproteomics Enables Discovery of Robust Site‐Specific Glycan Biomarkers for Hepatocellular Carcinoma

ABSTRACT Dysregulated protein glycosylation is a hallmark of cancer, and systematic investigation of glycosylation patterns is crucial for identifying biomarkers. However, current glycoproteomic studies are constrained by the limited quanti...

Machine learning: Trends, perspectives, and prospects

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and a...

Artificial intelligence and professional roles

2017 promises to be the year that artificial intelligence (AI) moves out of film and fiction and into the workplace. While automation has become commonplace in retail and services, from the ubiquitous uptake of automatic tills to the growin...

Advances in ligand-targeted nanodelivery systems for leukemia therapy: from single- to dual-ligand strategies

Abstract Background Leukemia is a highly heterogeneous and aggressive hematological malignancy. Current therapeutic approaches (e.g. chemotherapy, radiotherapy, small-molecule targeted therapies, and hematopoietic stem cell transplantation,...

Applications of artificial intelligence in intelligent manufacturing: a review

Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of ‘Internet plus AI’, which is triggerin...

A Generalized Framework for Adopting Regression-Based Predictive Modeling in Manufacturing Environments

In this paper, the growing significance of data analysis in manufacturing environments is exemplified through a review of relevant literature and a generic framework to aid the ease of adoption of regression-based supervised learning in man...

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

AI-Driven Identification of Critical Dependencies in US-China Technology Supply Chains: Implications for Economic Security Policy

This research examines the critical dependencies within US-China technology supply chains through advanced artificial intelligence methodologies, addressing significant economic security implications in an era of strategic competition. The ...

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...