Dynamic Adaptive Streaming over HTTP (DASH) has been widely adopted to deal with such user diversity as network conditions and device capabilities. In DASH systems, the computation-intensive transcoding is the key technology to enable video rate adaptation, and cloud has become a preferred solution for massive video transcoding. Yet the cloud-based solution has the following two drawbacks. First, a video stream now has multiple versions after transcoding, which increases the network traffic traversing the core network. Second, the transcoding strategy is normally fixed and thus is not flexible to adapt to the dynamic change of viewers. Considering that mobile users, who normally experience dynamic network conditions from time to time, have occupied a very large portion of the total users, adaptive wireless transcoding is of great importance.

To achieve deep insights into the polarization switching kinetics in ferroelectric $\text{Hf}0.5\text{Zr}0.5\mathrm{O}_{2}$ (HZO), the intrinsic switching characteristics are measured accurately by using a novel pulse sequence to eliminate the charge trapping, polarization unsaturation and imprint effects. By NLS fittings, the average switching time and the concentration of pinning sites are extracted, with main focus on their dependences on the external electric field, the electrode size $l$ and the temperature $T$ . Although the average switching time shows weak dependence on $T,$ , it decreases sharply with $l$ scaling and sub-ns switching behavior is predicted at $l\leq 3.89\mu \mathrm{m}$ . More importantly, our observations intensely imply that a transition happens from NLS to KAI model when $T$ is below 161K or $l$ is approaching the grain size (10~30nm). This surprised but reasonable transition indicates that, as scaling the ferroelectric memory size or for operations under cryogenic temperatures, HZO ferroelectrics can switch much faster and more uniform.

Kinetic energy of DFIG-based wind turbines (WTs) can be released to provide frequency support for power systems, as the DFIG has a wide admissible range of rotor speed. In this paper, an adaptive frequency support (AFS) based speed control is proposed for DFIG-based WTs. In the case of grid frequency drop, the proposed control scheme can directly regulate the WT's rotor speed and release the kinetic energy for frequency support. Moreover, the rotor speed can be limited within the admissible range. Control design for the proposed scheme is elaborately presented. In addition, to analyze the WT's dynamic behavior, model reduction for the WT system is conducted, wherein the proposed control scheme is applied. The derived reduced-order model not only precisely replicates the dynamics of the full-order WT system, but also greatly relieves computation burden and thus enables simulations of large-scale wind farms. Based on the reduced-order model, a two-area test system, which contains three hundred DFIG-based WTs in three wind farms, is simulated. It's shown that the proposed control scheme can fully utilize the stored kinetic energy of large-scale wind farms for frequency support, which reduces frequency fluctuations greatly and thus improve the frequency stability of power systems.