Urban Drone Navigation: Autoencoder Learning Fusion for Aerodynamics

Drones are vital for urban emergency search and rescue (SAR) due to the challenges of navigating dynamic environments with obstacles like buildings and wind. This paper presents a method that combines multi-objective reinforcement learning (MORL) with a convolutional autoencoder to improve drone navigation in urban SAR. The approach uses MORL to achieve multiple goals and the autoencoder for cost-effective wind simulations. By utilizing imagery data of urban layouts, the drone can autonomously make navigation decisions, optimize paths, and counteract wind effects without traditional sensors. Tested on a New York City model, this method enhances drone SAR operations in complex urban settings.Comment: 47 page

Sit-to-Stand and Stand-to-Sit Alterations in the Mild-to-Moderate Knee Osteoarthritis for Elderly Women

Purpose: The aim of this study was to examine biomechanics alterations during sit-to-stand and stand-to-sit in elderly female with mild-to-moderate knee osteoarthritis (OA) compared with health control (CG). Methods: Participants of knee OA (n=37) and CG (n=19) recruited from three communities in Shanghai. Participants performed sit-to-stand and stand-to-sit. Kinematic and kinetic data were collected. The main variables of interest were maximum ankle, knee and hip joint angle and joint moments in sagittal and frontal planes. The criteria measures were analyzed using two factors analysis of variance (ANOVA). Results: Main effects of group (p = .001) and group X limb interactions (p = .009) were observed for the sit-to-stand. Only group main effects (p = .002) was observed during stand-to-sit. Knee OA participants exhibited significantly less maximum ankle dorsiflexion angle (sit-to-stand, OA: 15.1±5.3, CG: 17.7±4.8; stand-to-sit, OA: 13.2±6.3, CG: 15.8±5.2 degrees) and greater ankle abduction/adduction moment (sit-to-stand, OA: 0.085±0.045, CG: 0.056±0.030; stand-to-sit, OA: 0.085±0.045, CG: 0.060±0.029 Nm/kg) during both tasks compared with CG. In addition, knee OA participants showed a significant greater maximum hip extension angle (OA: 68.45±7.69, CG: 65.35±9.37 degrees) during sit-to-stand and maximum ankle dorsiflexion moment (OA: 0.34±0.085, CG: 0.28 ±0.083 Nm/kg) during stand-to-sit compared with CG. Otherwise, the maximum knee extension angle (OA: 73.87±6.80, CG: 76.75±6.43 degrees) of knee OA participants showed a significant lower than CG during stand-to-sit. And also, significant group X limb interaction was observed in the maximum knee extension moment (OA: Involved: 0.60±0.17, Uninvolved: 0.58±0.15; CG: Left: 0.60±0.17, Right: 0.71±0.16 Nm/kg) during sit-to-stand. Conclusions: Knee OA participants show less ankle dorsiflexion angle and greater ankle abduction / adduction moment than the CG during both tasks. Therefore, knee pain or knee joint degeneration may induce freezing ankle range of motion and greater joint loading

Q-Band MMW Transmission Enabled by Joint Probabilistic Shaping and Precoding With MZM-Based OCS Modulation

In this letter, we propose a novel and straightforward scheme for Q-band (33–50 GHz) millimeter-wave signal generation enabled by a Mach-Zehnder modulator (MZM)-based joint algorithm, which combines probabilistic shaping (PS) and precoding technology, to enhance the anti-interference ability of the transmission system. Based on the proposed scheme, we experimentally demonstrate the generation and transmission of 1.4-Gbaud 46-GHz PS-16-quadrature-amplitude-modulation (PS-16QAM) vector signals, showcasing improved bit-error-ratio (BER) in both standard single-mode fiber (SSMF) and wireless transmission cases. The proposed scheme exhibits a clear advantage in terms of nonlinear interference suppression and satisfies the hard-decision forward-error-correction (HD-FEC) threshold with a BER of 3.8 × 10−3 in radio-over-fiber (RoF) systems