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DeepFake detection has become an attractive research topic with tremendous growth of interests recently. However, existing DeepFake detection studies spare no effort to improve accuracy or Area Under Curve metric, regardless of computing costs. In this work, the tradeoff between result accuracy and computing resources is taken into consideration. A facial sparse optical flow method is proposed to extract spatio-temporal features representing facial expression incoherence, which helps to distinguish fake videos and real videos. The features fed into a light CNN model are highly compact and low-dimensional. The proposed method has an amazing small amount of parameters with high training speed and low usage of GPU memory. The low resource requirement makes it possible to port to embedded development platform.

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Accurately determining the atmospheric boundary layer height (ABLH) is needed when one is addressing the air quality-related issues in highly urbanized areas, as well as when one is investigating issues that are related to the emission and transport of dust aerosols over the source region. In this study, we propose a new ABLH retrieval method, which is named ADEILP (ABLH that is determined by polarization lidar); it is based on the short-term polarized lidar observation that took place during the intensive field campaign in July 2021 in Tazhong, the hinterland of Taklimakan Desert. Furthermore, we conducted comparisons between the ABLH that was identified using a radiosonde (ABLHsonde), the ABLH that was identified by ERA5 (ABLHERA5) and the ABHL that was identified by ADELIP (ABLHADELIP), and we discussed the implications of the dust events. The ADELIP method boasts remarkable advancements in two parts: (1) the lidar volume linear depolarization ratio (VLDR) that represented the aerosol type was adopted, which is very effective in distinguishing between the different types of boundary layers (e.g., mixing layer and residual layer); (2) the idea of breaking up the entire layer into sub-layers was applied on the basis of the continues wavelet transform (CWT) method, which is favorable when one is considering the effect of fine stratification in an aerosol layer. By combining the appropriate height limitations, these factors ensured that there was good robustness of the ADELIP method, thereby enabling it to deal with complex boundary layer structures. The comparisons revealed that ABLHADELIP shows good consistency with ABLHsonde and ABLHERA5 for non-dust events. Nevertheless, the ADELIP method overestimated the stable boundary layer and underestimated the heights of the mixing layer. The dust events seem to be a possible reason for the great difference between ABLHERA5 and ABLHsonde. Thus, it is worth suggesting that the influence that is caused by the differences of the vertical profile in the ERA5 product should be carefully considered when the issues on dust events are involved. Overall, these findings support the climatological analysis of the atmosphere boundary layer and the vertical distribution characteristics of aerosols over typical climatic zones.

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