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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Multi-instrument analysis of L-band amplitude scintillati...
Abdollah Masoud Darya, Muhammad Mubasshir Shaikh, Grzegorz Nykie · 2024-05-23 · via eess.SP updates on arXiv.org

This study investigates the spatial and temporal characteristics of L1 amplitude scintillation-causing ionospheric irregularities over the Eastern Arabian Peninsula during the ascending phase of solar cycle 25 (years 2020--2023). The temporal occurrences of weak and strong scintillation were separated by sunset, with weak scintillation observed predominantly pre-sunset during the winter solstice and strong scintillation observed mainly post-sunset during the autumnal equinox. Strong scintillation was much more pronounced in 2023 compared to the other three years, indicating a strong influence of solar activity. Spatially, weak-scintillation-causing irregularities exhibited a wide distribution in azimuth and elevation, while strong-scintillation-causing irregularities were concentrated southwards. The combined analysis of S4 and rate of total electron content index (ROTI) suggested that small-scale ionospheric irregularities were present in both pre- and post-sunset periods, while large-scale irregularities were only seen during the post-sunset period. Furthermore, the presence of southward traveling ionospheric disturbances (TIDs) during the 2023 autumnal equinox was confirmed with the total electron content anomaly ($Δ\text{TEC}$), while the Ionospheric Bubble Index (IBI) provided by the Swarm mission was unable to confirm the presence of equatorial plasma bubbles during the same period. Observations from the FORMOSAT-7/COSMIC-2 mission indicated that strong-scintillation-causing irregularities were more prevalent under the F2-layer peak, while the weak-scintillation-causing irregularities were mostly observed at the E-layer, F2-layer, and above the F2-layer.