1663 papers
This paper presents the first demonstration of a quaternion optical computing chip (QOCC) that leverages wavelength-division multiplexing to physically map non-Abelian Hamilton products onto a photonic circuit, enabling highly parallel, low-error, and energy-efficient processing of high-dimensional data for applications like 3D point cloud analysis and color image recognition.
This diagnostic study of all Grade-A public secondary schools in Adamawa State, Nigeria, reveals that penetrating dampness (47.8%) and rising dampness (39.6%) are the predominant forms of building deterioration caused primarily by wind-driven rain ingress and roofing defects, with significant variation across educational zones but no difference between urban and semi-urban settings.
This study proposes a safety-resilience evaluation framework for tower-crane construction that integrates a cloud model with an intuitionistic fuzzy Bayesian network to assess system robustness under uncertainty, identifying key improvement factors through a case study application.
This study demonstrates that machine-learning prospectivity maps for karst bauxite in Kazakhstan, which appear highly accurate under random cross-validation, reveal significantly lower but more realistic performance when evaluated through spatially honest validation schemes that account for clustered mineral systems and extrapolation risks.
This study experimentally quantifies substantial vibration-induced power losses in cycling on simulated cobblestones, revealing that these losses increase quadratically with speed and tyre pressure while being mitigated by an off-the-saddle posture, thereby highlighting their critical impact on overall cycling efficiency.
This study demonstrates that applying the Particle Swarm Optimisation algorithm to an aerobic biological treatment process successfully achieves simultaneous nitrification and denitrification, identifying temperature and aeration period as the principal drivers for minimizing nitrate accumulation.
This paper presents a rigorously validated, trigger-based variable-fidelity co-simulation scheduler for reinforcement learning in power electronic systems that achieves significant training speedups through three critical corrections to power-flow approximation, Jacobian caching, and error-bound calibration, while transparently reporting its specific accuracy-speed trade-offs against periodic switching baselines.
This study employs an enhanced numerical approach to reveal how in-situ stress conditions govern the deformation modes, failure patterns, and energy evolution of roadway surrounding rock, providing critical insights for optimizing support design in sustainable deep underground mining.
This paper presents a comprehensive set of temperature-dependent analytical formulas for the thermophysical and mechanical properties of SS316L, Ti-6Al-4V, and Inconel 718 alloys, derived from over 100 experimental datasets and designed to enhance the accuracy of simulations for laser powder bed fusion and directed energy deposition processes.
This paper proposes a high-precision, hardware-independent 3D temperature field reconstruction algorithm for tunnel faces that fuses multi-view point clouds and infrared images through a novel virtual-depth-view guided PnP registration and noise-suppressed thermal mapping, achieving sub-degree accuracy and robust performance in challenging underground environments.