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Chorus waves are intense electromagnetic emissions critical in modulating electron dynamics. In this study, we perform two‐dimensional particle‐in‐cell simulations to investigate self‐consistent wave‐particle interactions with oblique chorus waves. We first analyze the electron dynamics sampled from cyclotron and Landau resonances with waves, and then quantify the advection and diffusion coefficients through statistical studies. It is found that phase‐trapped cyclotron resonant electrons satisfy the second‐order resonance condition and gain energy from waves. While phase‐bunched cyclotron resonant electrons cannot remain in resonance for long periods. They transfer energy to waves and are scattered to smaller pitch angles. Landau resonant electrons are primarily energized by waves. For both types of resonances, advection coefficients are greater than diffusion coefficients when the wave amplitude is large. Our study highlights the important role of advection in electron dynamics modulation resulting from nonlinear wave‐particle interactions. Plain Language Summary: Wave‐particle interactions can modulate electron distributions through advection and diffusion. Previous studies focusing on advection and diffusion primarily relied on test particle simulations, which uses a simplified model of wave evolution. In this study, we perform self‐consistent simulations to investigate the wave‐particle interactions with chorus waves and quantify the advection and diffusion coefficients of resonant electrons. It is found that advection coefficients are greater than diffusion coefficients in both cyclotron and Landau resonances, indicating the significant role of nonlinear wave‐particle interactions. The quantification of advection and diffusion coefficients in a self‐consistent system is important for understanding and predicting the loss and energization processes in radiation belt electrons. This study complements previous diffusion models that regarded the evolution of electron dynamics in wave‐particle interactions as a slow diffusive process. Key Points: Electron advection and diffusion in wave‐particle interactions with chorus waves are investigated through self‐consistent simulationsThe second‐order time derivative of gyrophase angle is nearly zero for phase‐trapped electrons but is negative for phase‐bunched electronsThe advection and diffusion coefficients for cyclotron and Landau resonant electrons interacting with chorus waves are quantified [ABSTRACT FROM AUTHOR]

In order to further improve the effectiveness of homomorphic cryptography, we optimize Lauter et al. 's partial homomorphic cryptography scheme, and propose a new RLWE-based total homomorphic cryptography (FHE) scheme, which combines a series of existing techniques with the Chinese residual theory, and merges several “plaintext slots” into a ciphertext for homomorphic computation. The extended key transformation technology and modulo transformation technology are used to reduce the noise of ciphertext and enable it to carry out the next homomorphic operation. Compared with the original scheme, the security and effectiveness of the scheme were studied on the premise of ensuring CPA security, and the results showed that the performance of the scheme was improved by N times.

Relativistic electron precipitation (REP) into the Earth's atmosphere is one of the fundamental mechanisms causing radiation belt electron flux dropout. It is important to know the preferred regions of REP events and the interplanetary and magnetospheric conditions under which the events take place. In this study of the POES relativistic electron data during 1998–2017, we have examined all REP events from L = 3–10 using an automatic algorithm. The REP events preferentially occur in MLT = 17–03 at L = 4–6.5, where the precipitation fluxes also peak. The monthly average REP event number is correlated with both monthly average AE (auroral electrojet index) and Pd (solar wind ram pressure) indices, so we separately investigate the spatial dependences of the events on one index by restricting the other one to a low level. The occurrence rate of REP events increases with both the AE* and the Pd∗ ${P}_{d}^{\ast }$ indices (where AE* and Pd∗ ${P}_{d}^{\ast }$ are time‐modified from the AE and Pd indices). During large AE* but low Pd∗ ${P}_{d}^{\ast }$, the events occur mainly in the dusk sector (MLT = 17–22) near the plasmapause. For large Pd∗ ${P}_{d}^{\ast }$ but low AE* intervals, most of the events occur outside the plasmapause in the midnight sector (MLT = 23–03). Possible REP loss mechanisms are discussed based on our findings. Our study provides new insights into the distribution and dependences of REP in the Earth's magnetosphere. Key Points: With 20‐year POES data, we separately investigate the spatial dependences of REP events on substorm injection and solar wind ram pressureDuring periods of low Pd* ${P}_{d}^{\ast }$ but large AE*, REP events are preferentially observed in the dusk sector near the plasmapauseDuring periods of low AE* but large Pd* ${P}_{d}^{\ast }$, REP events occur preferentially in the midnight sector outside the plasmapause [ABSTRACT FROM AUTHOR]

For the shortcomings of an unstable clustering effect and low accuracy caused by the manual setting of the two parameters Eps and MinPts of the DBSCAN (density-based spatial clustering of applications with noise) algorithm, this paper proposes an adaptive determination method for DBSCAN algorithm parameters based on the K-dist graph, noted as X-DBSCAN. The algorithm uses the least squares polynomial curve fitting method to fit the curve in the K-dist graph to generate a list of candidate Eps parameters and uses the mathematical expectation method and noise reduction threshold to generate the corresponding MinPts parameter list. According to the clustering results of each group of parameters in the Eps and MinPts parameter lists, a stable range of cluster number changes is found, and the MinPts and Eps corresponding to the maximum K value in the stable range are selected as the optimal algorithm parameters. The optimality of this parameter was verified using silhouette coefficients. A variety of experiments were designed from multiple angles on the artificial dataset and the UCI real dataset. The experimental results show that the clustering accuracy of X-DBSCAN was 21.83% and 15.52% higher than that of DBSCAN on the artificial and real datasets, respectively. The X-DBSCAN algorithm was also superior to other algorithms through comprehensive evaluation and analysis of various clustering indicators. In addition, experiments on four synthetic Gaussian datasets of different dimensions showed that the average clustering indices of the proposed algorithm were above 0.999. The X-DBSCAN algorithm can select parameters adaptively in combination with the characteristics of the dataset; the clustering effect is better, and clustering process automation is realized. [ABSTRACT FROM AUTHOR]

Recently, the rapid development of deep learning has greatly improved the performance of image classification. However, a central problem in hyperspectral image (HSI) classification is spectral uncertainty, where spectral features alone cannot accurately and robustly identify a pixel point in a hyperspectral image. This paper presents a novel HSI classification network called MS-RPNet, i.e., multiscale superpixelwise RPNet, which combines superpixel-based S3-PCA with two-dimensional singular spectrum analysis (2D-SSA) based on the Random Patches Network (RPNet). The proposed frame can not only take advantage of the data-driven method, but can also apply S3-PCA to efficiently consider more global and local spectral knowledge at the super-pixel level. Meanwhile, 2D-SSA is used for noise removal and spatial feature extraction. Then, the final features are obtained by random patch convolution and other steps according to the cascade structure of RPNet. The layered extraction superimposes the different sparial information into multi-scale spatial features, which complements the features of various land covers. Finally, the final fusion features are classified by SVM to obtain the final classification results. The experimental results in several HSI datasets demonstrate the effectiveness and efficiency of MS-RPNet, which outperforms several current state-of-the-art methods. [ABSTRACT FROM AUTHOR]