A CNN-RF Hybrid Approach for Rice Paddy Fields Mapping in Indramayu Using Sentinel-1 and Sentinel-2 Data by Dodi Sudiana, Mia Rizkinia, Rahmat Arief, Tiara De Arifani, Anugrah Indah Lestari, Dony Kushardono, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo

“…Research findings in some districts of Indramayu show that the scheme combining Sentinel-1 features with GLCM (gray-level co-occurrence matrix) and Sentinel-2 features with selected bands provides the best results, with an overall accuracy of 98.23% and a Kappa coefficient of 0.96, using the CNN-RF method. …”
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Multi-Feature Driver Variable Fusion Downscaling TROPOMI Solar-Induced Chlorophyll Fluorescence Approach by Jinrui Fan, Xiaoping Lu, Guosheng Cai, Zhengfang Lou, Jing Wen

“…To address this, we leveraged MODIS data at a 1 km resolution, including bands b1, b2, b3, and b4, alongside indices such as the NDVI, EVI, NIRv, OSAVI, SAVI, LAI, FPAR, and LST, covering October 2018 to May 2020 for Shandong Province, China. …”
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Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud by Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao

“…Millimeter-wave (MmWave) channel characteristics are quite different from sub-6 GHz frequency bands. The major differences include higher path loss and sparser multipath components (MPCs), resulting in more significant time-varying characteristics in mmWave channels. …”
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Four weeks of slow-paced breathing: a longitudinal, randomized, placebo-controlled study of the autonomic nervous system by Nicolas Bourdillon, Arnaud Rochat, Vanessa Hoop, Grégoire P. Millet

“…Personalized SPB was determined as the breathing frequency that elicited the greatest possible RSA, i.e., the best synchronization between breathing and heart rate. …”
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