1641 papers
This paper proposes and validates an automatic workpiece alignment system for CNC machining that utilizes Gray-code structured light scanning and 3D modeling to reconstruct workpiece geometry and determine coordinate offsets with high precision, thereby reducing reliance on skilled operators and minimizing human error.
This paper presents a reproducible, parametric modeling framework using Grasshopper and Python to generate three-dimensional airfoils with bio-inspired leading-edge tubercles and trailing-edge serrations, detailing the governing equations, source code, and workflow for aerodynamic optimization and CFD preparation.
This paper establishes a criterion for selecting between linear and bilinear Koopman models in MPPI control, demonstrating that bilinear lifts are structurally necessary for configuration-dependent input gains and serve as a robust default that outperforms linear counterparts on velocity-driven systems while maintaining efficiency for force-driven platforms.
This study employs a moisture-coupled reduced-order simulation framework to demonstrate that the three-story compact tower archetype in Old Sana'a offers superior thermal resilience and adaptive comfort compared to taller variants, identifying window-to-wall ratio as the primary overheating driver and advocating for reversible, heritage-sensitive interventions.
This paper presents a systematic literature review analyzing how IoT and Wireless Sensor Networks, integrated with advanced techniques like AI and edge computing, optimize energy conservation in smart cities while identifying current challenges and future research directions for sustainable development.
The paper proposes SAVER, an adaptive low-dose CT framework that dynamically selects projection angles based on real-time data variance and a stochastic scheduling scheme to maximize reconstruction fidelity and diagnostic quality while minimizing radiation exposure.
This study demonstrates that high-intensity ultrasonic treatment of molten AA-series aluminium alloys effectively removes dissolved hydrogen through acoustic cavitation, significantly reducing porosity and refining grain structure to achieve defect-free 6-micron foil production while eliminating the need for environmentally harmful degassing gases.
This study demonstrates that axial-dispersion models with specific boundary conditions (BC I and BC III) provide superior physical consistency and predictive accuracy for residence time distribution in multi-compartment wastewater reactors compared to the tanks-in-series model, though all reduced-order formulations fail to capture short-circuiting phenomena driven by local flow pathways.
This paper introduces MEMNet, a recurrent neural network that learns to map vehicle motion from planar to complex terrains using control inputs and terrain data, achieving high predictive accuracy for position and velocity across diverse synthetic terrain classes while highlighting altitude reconstruction as a current limitation.
This study demonstrates that optimizing injection rate, sand-to-fluid ratio, and cluster spacing for multi-cluster hydraulic fracturing in a soft, low-permeability coal seam using a surface L-shaped well significantly enhances fracture uniformity and gas drainage efficiency, as validated by simulations and field monitoring at Yongchun Coal Mine.