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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
Significance of Medium-Wave AM Radio Broadcasting for Enh...
Eiichi Shoji · 2023-06-24 · via eess.SP updates on arXiv.org

On the occasion of centenary anniversary of the Great Kanto Earthquake and commencement of radio broadcasting in Japan, this study reiterates the paramount importance of medium-wave (MW) AM broadcasting in safeguarding public safety and security. Utilizing the electromagnetic principles of MW, the author has earlier developed hoop-shaped radio (HOOPRA), which is a battery-free sustainable radio receiver. This study aims to determine the maximum achievable reception distance with HOOPRA for broadcasts from public stations, such as Nihon Hoso Kyokai (NHK) JOFG (927 kHz, 5 kW) in Fukui, and NHK JOAK (594 kHz, 300 kW), and JOAB (693 kHz, 500 kW), in the Kanto region. The significance of the findings in this study is that approximately 38 million individuals in the Kanto region, residing within an 80 km radius of JOAK or JOAB, can access broadcasts using only the energy of radio waves with HOOPRA. Additionally, ~0.4 million people in Fukui, within a 15 km radius of JOFG, can potentially be recipients of the broadcast. Given that most transmitting stations operate at 5 kW nationwide, HOOPRA can be effectively utilized within a 15 km radius of each station. Moreover, these outcomes validate the efficacy of HOOPRA as a radio receiver and provide valuable insights into the global potential applicability of MW AM radios. Furthermore, the current investigation underscores the need to reevaluate the significance of terrestrial MW broadcasting as a vital source of emergency information, especially in the event of anticipated natural disasters, such as the predicted Nankai Trough Earthquake.