1710 papers
This study demonstrates that an immersive telepresence experience can be achieved using less-than-ideal, accessible hardware by integrating standard VR equipment with a robot to create a virtual environment that mimics real-world constraints, as validated by a user study categorizing the solution's effectiveness across five key areas.
This study demonstrates that incorporating 12% fly ash optimally enhances the shear strength of both cohesive and cohesionless soils through distinct mechanisms of densification and pozzolanic cementation, while a proposed quadratic regression model effectively predicts this optimum dosage for sustainable geotechnical applications.
This study presents a machine learning framework that leverages near-surface observational networks to simultaneously correct ERA5 hub-height wind speeds and predict wind shear exponents, significantly improving accuracy and temporal variability across large spatial domains without requiring direct hub-height measurements.
This PRISMA 2020-compliant systematic review of 729 records identifies critical security and privacy gaps in EEG-based BCI systems, particularly the near-total absence of blockchain-based provenance, and proposes a "NeuroChain" reference architecture to address these vulnerabilities through hash-anchored data integrity, differential privacy, and patient-controlled consent.
This study presents a fully coupled transient wellbore–fracture model validated by field data that reveals tripping speed as the dominant factor driving pressure drops and fracture closure in deep gas reservoirs, thereby providing a quantitative framework for optimizing drilling protocols to mitigate lost circulation risks.
This paper presents a fully automated multi-robot system that utilizes up to six robots and a graphical user interface to significantly improve the efficiency and speed of illuminance measurements in construction sites compared to traditional manual methods.
This paper proposes an improved conditional Generative Adversarial Network (cGAN) that leverages high-fidelity CFD data to rapidly and accurately predict complex flow fields around unseen geometries, achieving a 79.14% accuracy improvement over baseline models while significantly reducing computational costs.
This paper proposes an intelligent chatter identification method for thin-walled parts finishing milling that combines second-order generalized synchrosqueezing transform for signal reconstruction with natural visibility graph-based multiscale dispersion entropy for feature extraction, achieving high recognition accuracy through a crayfish optimization algorithm-optimized support vector machine.
This study demonstrates that rotary ultrasonic vibration-assisted grinding (RUVAG) significantly improves the surface integrity and reduces material removal defects of Zr-based bulk metallic glasses compared to conventional grinding by introducing intermittent contact that mitigates stress concentration and lowers surface roughness by approximately 21%.
This study proposes and validates a novel wire-renewal EDM milling electrode that overcomes traditional electrode wear limitations to fabricate high-accuracy microlens array molds on tungsten carbide through optimized rotationally averaged annular discharge.