数据要素市场化的理论内涵、现实挑战和实践路径

数据要素是数字经济时代的全新生产要素,数据要素市场化在数字经济推进经济高质量发展中具有显著的战略意义.目前,全球对于数据要素的认识仍然处在积极探索中,正确把握数据要素市场化的新内涵、新特征、新要求、新挑战至关重要.在对数据要素市场化的理论内涵和重大意义进行系统阐述的基础上,通过数据要素市场化指数测度发现我国当前数据要素市场化起步晚、起步缓,面临数据产权确权难、数据价值评估难、数据交易流通难、数据保护监管难等挑战,从而从加快数据汇聚、推动数据流通、深化数据应用、强化数据安全等方面提出具有实践价值的解决路径.     

Long-term ultra-precision phase synchronization technique for locking the repetition rate of OFCs based on FLOM-PD

Long-term ultra-precision synchronization between optical frequency combs (OFCs) and microwave oscillators is important for various fields, including scientific observation, smart grid, positioning and navigation, etc. Here, a phase-locked loop system based on fiber loop optical-microwave phase detector (FLOM-PD) is proposed to realize the synchronization of the repetition rate of OFCs and rubidium atomic clocks. Firstly, the scheme and locking process of the system are elaborated, then the mathematical model of the system is established, and the feasibility of the scheme is proved by theoretical analysis and experimental verification. After synchronization, the instability of the system reaches 8.69×10-12 at 1 s and 2.94×10-13 at 1 000 s, indicating that the phase synchronization system can achieve ultra-precision and stability of OFCs repetition rate.     

基于拓扑链路识别的光网络流量数据合成算法

基于深度学习的光网络流量诊断与预测等场景中,由于保密等原因,光链路的流量数据采集和存储工作受限。针对数据量少而无法支撑深度学习的问题,文章提出了一种基于拓扑链路识别的光网络流量数据合成算法,其核心思想是在生成对抗网络框架下,联合基于光网络拓扑的条件生成模型和基于光网络流量的数据合成模型,以自监督的方式合成指定光链路的流量数据。仿真结果表明,所提算法合成的光网络流量数据在自相关系数指标上与真实数据接近且使得基于全连接神经网络的流量预测模型准确率达到95%以上。     

超宽带雷达人体行为感知研究进展

超宽带 (UWB) 雷达人体行为感知主要研究如何利用人体目标电磁散射回波对位置、行为、意图等进行判别,是光学感知手段的有益补充,应对无光照、地物遮挡、非视距等情况下的应用场合。该文将超宽带雷达人体行为感知研究方法分成基于空间位置和基于微动特征两类技术。在介绍这类技术基本原理的基础上,对比分析了国内外代表性工作的能力现状。最后对超宽带雷达人体行为感知领域的后续重点研究方向进行了展望。     

Theories of Social Media: Philosophical Foundations

Although many different views of social media coexist in the field of information systems (IS), such theories are usually not introduced in a consistent framework based on philosophical foundations. This paper introduces the dimensions of lifeworld and consideration of others. The concept of lifeworld includes Descartes’ rationality and Heidegger’s historicity, and consideration of others is based on instrumentalism and Heidegger’s “being-with.” These philosophical foundations elaborate a framework where different archetypal theories applied to social media may be compared: Goffman’s presentation of self, Bourdieu’s social capital, Sartre’s existential project, and Heidegger’s “shared-world.” While Goffman has become a frequent reference in social media, the three other references are innovative in IS research. The concepts of these four theories of social media are compared with empirical findings in IS literature. While some of these concepts match the empirical findings, some other concepts have not yet been investigated in the use of social media, suggesting future research directions.     

A Secure and Effective Energy-Aware Fixed-Point Quantization Scheme for Asynchronous Federated Learning

Asynchronous federated learning (AsynFL) can effectively mitigate the impact of heterogeneity of edge nodes on joint training while satisfying participant user privacy protection and data security. However, the frequent exchange of massive data can lead to excess communication overhead between edge and central nodes regardless of whether the federated learning (FL) algorithm uses synchronous or asynchronous aggregation. Therefore, there is an urgent need for a method that can simultaneously take into account device heterogeneity and edge node energy consumption reduction. This paper proposes a novel Fixed-point Asynchronous Federated Learning (FixedAsynFL) algorithm, which could mitigate the resource consumption caused by frequent data communication while alleviating the effect of device heterogeneity. FixedAsynFL uses fixed-point quantization to compress the local and global models in AsynFL. In order to balance energy consumption and learning accuracy, this paper proposed a quantization scale selection mechanism. This paper examines the mathematical relationship between the quantization scale and energy consumption of the computation/communication process in the FixedAsynFL. Based on considering the upper bound of quantization noise, this paper optimizes the quantization scale by minimizing communication and computation consumption. This paper performs pertinent experiments on the MNIST dataset with several edge nodes of different computing efficiency. The results show that the FixedAsynFL algorithm with an 8-bit quantization can significantly reduce the communication data size by 81.3% and save the computation energy in the training phase by 74.9% without significant loss of accuracy. According to the experimental results, we can see that the proposed AsynFixedFL algorithm can effectively solve the problem of device heterogeneity and energy consumption limitation of edge nodes.     

Container-Based Internet of Vehicles Edge Application Migration Mechanism

Internet of Vehicles (IoV) applications integrating with edge computing will significantly drive the growth of IoV. However, the contradiction between the high-speed mobility of vehicles, the delay sensitivity of corresponding IoV applications and the limited coverage and resource capacity of distributed edge servers will pose challenges to the service continuity and stability of IoV applications. IoV application migration is a promising solution that can be supported by application containerization, a technology forseamless cross-edge-server application migration without user perception. Therefore, this paper proposes the container-based IoV edge application migration mechanism, consisting of three parts. The first is the migration trigger determination algorithm for cross-border migration and service degradation migration, respectively, based on trajectory prediction and traffic awareness to improve the determination accuracy. The second is the migration target decision calculation model for minimizing the average migration time and maximizing the average service time to reduce migration times and improve the stability and adaptability of migration decisions. The third is the migration decision algorithm based on the improved artificial bee colony algorithm to avoid local optimal migration decisions. Simulation results show that the proposed migration mechanism can reduce migration times, reduce average migration time, improve average service time and enhance the stability and adaptability of IoV application services.     

Revisiting the security of secure direct communication based on ping-pong protocol[Quantum Inf. Process. 8, 347 (2009)]

A. Chamoli and C.M. Bhandari presented a secure direct communication based on ping-pong protocol[Quantum Inf. Process. 8, 347 (2009)]. M.Naseri analyzed its security and pointed out that in this protocol any dishonest party can obtain all the other one’s secret message with zero risk of being detected by using fake entangled particles (FEP attack) [M. Naseri, Quantum Inf. Process. online]. In this letter, we reexamine the protocol’s security and discover that except the FEP attack, using a special property of GHZ states, any one dishonest party can also take a special attack, i.e., double-CNOT(Controlled NOT) attack. Finally, a denial-of-service attack is also discussed.     

矿井煤仓三维计算机辅助设计

针对传统的矿井煤仓二维设计存在绘图复杂、抽象、易出错等问题,提出了一种矿井煤仓三维计算机辅助设计的方案;以恒源煤矿的-600煤仓和主井缓冲煤仓为例,详细介绍了煤仓三维计算机辅助设计及其动画演示的具体实现。该方案解决了复杂工程施工中设计者与施工人员的交流问题,为高质量、快速施工提供了基础保障。     

基于液滴指纹图的波形分析算法的改进

不同的液体在相同的夜滴分析系统中,光纤信号的强弱不同,电容信号的强弱即液滴体积不同,液滴指纹图的波峰波谷的高度、位置以及峰的形状不同,液滴指纹图的曲线长度和曲线下的面积不同;因此,对光电液滴指纹图进行波形分析,计算波形参数,可以实现特征提取并区分不同液体.针对波形分析算法在特征提取过程中存在的两个缺陷,即最值检测时可能错误识别波谷位置和邻域比较时产生大量等值数据集,提出了改进的波形分析算法;对改进前后的波形分析算法进行了分析比较,改进后的算法有效提高了波形参数的准确性.