ID	原文	译文
4833	HMDB51 和 UCF101 数据集上的实验结果表明，所提时空压缩激励残差乘法网络能够有效提升动作识别性能。	The experimental results onthe HMDB51 and UCF101 datasets show that the proposed spatio temporal squeeze-and-excitation residual multiplier networks can effectively improve the performance of action recognition.
4834	针对互联网面临的内容大数据趋势显著、内容语义标识缺乏和内容安全态势严峻等内容治理挑战，提出了一种支持内容大数据智能治理的双结构互联网，以现有互联网体系结构作为主结构，以基于辐射−复制范型的播存网络作为次结构。	For the current Internet architecture is suffering many challenges of cyber content governance, including big data trends of cyber contents, lack of semantic identification, and the severe situation of content security. In seeking to address these challenges, a dual-architecture Internet which integrated the current Internet architecture with a comple-mentary secondary broadcast-storage network architecture characterized as the combination of broadcast transmissionand ubiquitous storage was proposed.
4835	介绍了双结构互联网的体系结构设计原则、核心理念和内容智能治理实现机制，尤其对统一内容标签 UCL 国家标准与富语义矢量编码、热门内容汇聚与 UCL 安全能级模型、UCL 知识空间与内容汇聚研讨厅等内容智能治理关键技术进行了详细阐述。	The design principles and core concepts of the dual-architecture Internet and its in-telligent realization mechanism of cyber content governance were introduced, and especially, the national standard ofuniform content label (UCL) and UCL-based rich semantic vector coding of contents, the gathering of popular contentsthe UCL-oriented security energy level model, the UCL knowledge space and content clustering hall for workshop of me-ta-synthetic engineering were detailed.
4836	最后，通过研发双结构互联网内容智能治理原型系统，对双结构互联网及其内容智能治理能力进行了验证。	Consequently, a prototype of dual-architecture Internet supporting intelligent gover-nance of cyber contents was developed to verify the design principles and core concepts of the dual-architecture Internet andits capability for intelligent governance of cyber contents.
4837	双结构互联网为破解内容大数据治理难题提供了网络体系结构层面的创新解决思路。	The dual-architecture Internet proposed can provide a brand-newapproach to solve the problem of cyber content governance from the high-level perspective of network architecture.
4838	针对超密集网络的室内场景，提出了一种基于干扰图的自适应干扰协调方法。	An interference graph based adaptive interference coordination method was proposed for indoor scenario ofultra dense network (UDN).
4839	该方法以最大化系统吞吐量为目标，首先将系统中的干扰关系建模为干扰图，并利用迭代着色算法确定各小小区基站的可用资源；	The algorithm aimed at maximizing system throughput. Firstly, the interference relationship in the system was modeled as an interference graph, and the iterative coloring algorithm was used to determine the avail-able resources of each small cell base station (SBS).
4840	然后，由小小区基站采用优化吞吐量的资源分配算法将资源分配给各用户。	Thereafter, the SBS allocated resources to each user by using athroughput optimizing resource allocation algorithm.
4841	所提方法能够根据网络拓扑结构及信道条件自适应地选择资源分配策略，从而降低系统内干扰。	The method could adaptively select a resource allocation strategyaccording to the network topology and channel conditions, thereby mitigating interference in the system.
4842	仿真结果表明，相比于现有方法，所提方法通过较小的额外信令开销，在明显提升吞吐量性能的同时有效地降低了系统中断概率。	The simulation results show that compared with the existing methods, the proposed method effectively reduces the system outage proba-bility while significantly improving the throughput performance through a small additional signaling overhead.