651 papers
This study develops a Random Forest-based machine learning framework using LTPP data to accurately predict the occurrence and severity of moisture damage in asphalt pavements, enabling transportation agencies to implement proactive, climate-resilient maintenance strategies.
This paper introduces PACT, an interpretable decentralized coordination mechanism for electric-vehicle charging that uses a single broadcast price signal to guarantee hard capacity constraints are never exceeded while significantly reducing costs and meeting deadlines compared to independent learning approaches.
This study validates a solar-powered hybrid system integrating Air Gap Membrane Distillation and PEM electrolysis, demonstrating its capability to simultaneously produce freshwater and green hydrogen while identifying key operational parameters that optimize performance for sustainable decentralized resource generation.
This paper proposes a low-cost adaptive smart sock prototype that utilizes minimal hardware and intelligent software to assess a user's current walking or running level and generate a progressive, personalized cardiorespiratory training program aligned with public health guidelines.
This paper presents a native Verilog RTL implementation of a high-performance FP64 quantum statevector simulator on an HBM-equipped FPGA that achieves perfect fidelity for up to 15 qubits by translating a validated HLS kernel into hand-written logic with specialized gate engines and an optimized HBM memory architecture, while also documenting a specific verification failure for 16 or more qubits.
This paper proposes an energy-efficient, event-driven structural health monitoring pipeline that combines a level-crossing spike encoder with a compact spiking neural network to localize damage in multi-story buildings, achieving near-baseline accuracy while significantly reducing energy consumption and data transmission rates through a tunable threshold mechanism.
This experimental study demonstrates that the geometric design of L-shaped Oscillating Water Column chambers critically determines their hydrodynamic-pneumatic coupling and overall energy conversion efficiency, revealing that stable, coherent motion is more vital for optimal power extraction than large oscillation amplitudes alone.
This paper presents an automated pipeline combining deep learning-based U-Net segmentation and RAFT dense optical flow to reconstruct high-fidelity hemodynamic velocity fields from standard abdominal aortic aneurysm cine-MRI, achieving Phase-Contrast MRI-level accuracy without specialized acquisition or manual intervention.
This study extends the validation of Pyramidal Lucas–Kanade optical flow for AAA cine-MRI by introducing a new synthetic phantom with closed-form ground truth to demonstrate that the method's optimal window size is motion-regime dependent, that it outperforms dense Farneback flow in noise robustness, and that it accurately recovers angular velocities matching real-patient data.
This paper proposes a self-executing smart contract architecture on permissioned distributed ledgers that automates and cryptographically verifies the settlement of Peruvian civil engineering public works, reducing certification cycles from months to minutes while maintaining full compliance with existing national procurement laws without requiring legislative reform.