ECM-OPCC: Efficient Context Model for Octree-based Point Cloud Compression

Recently, deep learning methods have shown promising results in point cloud compression. For octree-based point cloud compression, previous works show that the information of ancestor nodes and sibling nodes are equally important for predicting current node. However, those works either adopt insufficient context or bring intolerable decoding complexity (e.g. >600s). To address this problem, we propose a sufficient yet efficient context model and design an efficient deep learning codec for point clouds. Specifically, we first propose a window-constrained multi-group coding strategy to exploit the autoregressive context while maintaining decoding efficiency. Then, we propose a dual transformer architecture to utilize the dependency of current node on its ancestors and siblings. We also propose a random-masking pre-train method to enhance our model. Experimental results show that our approach achieves state-of-the-art performance for both lossy and lossless point cloud compression. Moreover, our multi-group coding strategy saves 98% decoding time compared with previous octree-based compression method

A Local Signal based Inter-area Damping Controller via Dynamic State Estimation Approach

To suppress inter-area oscillations and enhance small-signal stability of power systems, wide-area damping controllers (WADC) have been used by utilising wide-area signals with high observabilities to inter-area modes. However, the requirement of the wide-area signal makes communication systems involved in the control loops of the power systems and therefore, the damping performance of the conventional WADC suffers from time-delay, data dropout and cyber-attacks. This paper proposes a local signal based inter-area damping controller (LSIADC) to suppress inter-area oscillation without using wide-area signals. The LSIADC extracts a signal with high observability to the inter-area mode from the local signal by dynamic state estimation (DSE) technique and the control signal is obtained by adding a proper phase shift to the extracted signal. The simulation results show that the proposed controller can effectively suppress inter-area oscillation using the local signal only