Future railway is expected to accommodate both train operation services and passenger broadband services. The millimeter wave (mmWave) communication is a promising technology in providing multi-gigabit data rates to onboard users. However, mmWave communications suffer from severe propagation attenuation and vulnerability to blockage, which can be very challenging in high-speed railway (HSR) scenarios. In this paper, we investigate efficient hybrid beamforming (HBF) design for train-to-ground communications. First, we develop a two-stage HBF algorithm in blockage-free scenarios. In the first stage, the minimum mean square error method is adopted for optimal hybrid beamformer design with low complexity and fast convergence; in the second stage, the orthogonal matching pursuit method is utilized to approximately recover the analog and digital beamformers. Second, in blocked scenarios, we design an anti-blockage scheme by adaptively invoking the proposed HBF algorithm, which can efficiently deal with random blockages. Extensive simulation results are presented to show the sum rate performance of the proposed algorithms under various configurations, including transmission power, velocity of the train, blockage probability, etc. It is demonstrated that the proposed anti-blockage algorithm can improve the effective rate by 20% in severely-blocked scenarios while maintaining low outage probability. Index Terms-High-speed railway, mmWave communications, hybrid beamforming, low complexity, anti-blockage. I. INTRODUCTION We have witnessed the rapid expansion of high-speed railway (HSR) transportation in the past decade, where railway communications are evolving at a fast pace to provide wireless broadband connections between roadside infrastructures and onboard travellers [2]. Innovation campaigns have been launched by railway operators, and the concept of "smart rail" is put forward by Shift2Rail [3]. Smart rail services are envisioned to deliver consistent quality experiences, supporting a variety of services including autonomous driving, train multimedia M. Gao, B. Ai, and Y. Niu are with the

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It is estimated that the waterway in North Passage would not be able to meet the demand of shipping development soon and it is necessary to open a new deep navigation channel with a depth of 10 m in North Channel in the near future. A pilot study on the regulation of North Channel was proposed by Yangtze Estuary Waterway Administration Bureau and Prof. Dano Roelvink from UNESCO-IHE. The idea of regulating the navigation channel in North Channel was raised based on an analysis of morphological processes in this area. Multiple regulation plans were proposed, amongst which a configuration to regulate the North Channel was suggested after a study on a numerical modelling of tidal flow and morphological processes. Some suggestions were put forward for future studies.

SummaryRegion of interest detection is a useful technique in video encoding. This work presents a model to distinguish region of interest area based on VP9 video codec. The model contains high motion, contrast, color sensitive areas which fits for human visual system. A hybrid detection algorithm, including Wavelet Transform and Context Modeling method, is proposed. The algorithm approximately reveals ROI details for the sake of pursuing computing time. In ROI‐based encoding, adjusting encoding parameters for region of interest (ROI) during the encoding procedure can bring turbulence in bits output, a rate control model is established in this work. We also design a rate control mechanism for ROI encoding mode both in CBR and VBR to maintain the output bit rate stable. The encoding parameter are set specifically in different ROI areas to improve both visual effects and PSNR. The proposed detection method and rate control mechanism work well in VP9 codec and contribute saving bits according to experimental results.

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