The [Formula: see text]-delayed particle emission from the exotic nucleus [Formula: see text]Si has been studied using a detection system with silicon array and clover-type high-purity germanium (HPGe) detectors. The [Formula: see text]-delayed charged-particle spectrum and [Formula: see text]-ray spectrum were identified. The half-life of [Formula: see text]Si has been determined. A new [Formula: see text]-delayed proton branch with an energy of 3811[Formula: see text]keV was observed. The [Formula: see text]-delayed two-proton emission was confirmed.
Synthetic aperture radar (SAR) imaging can penetrate rain, snow, fog, and mist, providing an effective precipitation detector under a wide range of atmospheric conditions. This powerful technique operates under any weather conditions and can detect environmental changes or help in the evaluation of natural disasters. Multi-temporal change detection is important for monitoring disasters, but commonly applied wavelet transforms are not ideal for capturing change information. This paper presents a new multi-directional change detection (MDCD) method designed to improve the change detection accuracy using multiple SAR images. This method employs double-density dual-tree complex wavelet transforms (DDDT-CWT) theory, which allows the capture of multi-directional information. The MDCD method can provide information for 16 directions at any decomposed scale, which allows for change detection in multiple SAR images collected over time. We used the MDCD algorithm method to analyse SAR images from actual natural disasters and successfully identified environmental changes over time using SAR images.
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