基于相推法的空间光载射频链路绝对延时测量

空间光载射频链路利用空间光链路实现射频信号的传输。由于采用大气信道传输光载射频信号,链路绝对延时受到大气湍流和温度等因素影响,产生延时抖动。本文采用相推法对1 km空间光载射频链路的绝对延时进行了高精度测量,测量结果与理论模型吻合,测量精度优于0.1 ps。该测量方法采用电光调制和射频鉴相实现了链路绝对延时测量,与光载射频链路具有良好的技术兼容性,同时较高的测量精度可以满足构建稳定光载射频传输链路的要求。

Threat Assessment Method Based on Intuitionistic Fuzzy Similarity Measurement Reasoning with Orientation

The aim of this paper is to propose a threat assessment method based on intuitionistic fuzzy measurement reasoning with orientaion to deal with the shortcomings of the method proposed in [Ying-Jie Lei et al., Journal of Electronics and Information Technology 29(9)(2007)2077-2081] and [Dong-Feng Chen et al., Procedia Engineering 29(5)(2012)3302-3306] the ignorance of the influence of the intuitionistic index's orientation on the membership functions in the reasoning, which caused partial information loss in reasoning process. Therefore, we present a 3D expression of intuitionistic fuzzy similarity measurement, make an analysis of the constraints for intuitionistic fuzzy similarity measurement, and redefine the intuitionistic fuzzy similarity measurement. Moreover, in view of the threat assessment problem, we give the system variables of attribute function and assessment index, set up the reasoning system based on intuitionistic fuzzy similarity measurement with orientation, and design the reasoning rules, reasoning algorithms and fuzzy-resolving algorithms. Finally, through the threat assessment, some typical examples are cited to verify the validity and superiority of the method.

An Alternative-Service Recommending Algorithm Based on Semantic Similarity

With the development of the Internet of Things(Io T), people's lives have become increasingly convenient. It is desirable for smart home(SH) systems to integrate and leverage the enormous information available from IoT. Information can be analyzed to learn user intentions and automatically provide the appropriate services. However, existing service recommendation models typically do not consider the services that are unavailable in a user's living environment. In order to address this problem, we propose a series of semantic models for SH devices. These semantic models can be used to infer user intentions. Based on the models, we proposed a service recommendation probability model and an alternative-service recommending algorithm. The algorithm is devoted to providing appropriate alternative services when the desired service is unavailable. The algorithm has been implemented and achieves accuracy higher than traditional Hidden Markov Model(HMM). The maximum accuracy achieved is 68.3%.

WWW COLLABORATIVE RECOMMENDATION BASED ON RELIABILITY

Collaborative filtering recommender systems often suffer from the 'Matchmaker' problem, which comes from the false assumption that users are counted only based on their similarity, and high similarity means good advisers. In order to find good advisers for every user, a matchmaker's reliability mode based on the algorithm deriving from Hits is constructed, and it is applied in the proposed World Wide Web (WWW) collaborative recommendation system. Comparative experimental results also show that our approach obviously improves the substantial performance.

METHOD FOR QUICKLY INFERRING THE MECHANISMS OF LARGE-SCALE COMPLEX NETWORKS BASED ON THE CENSUS OF SUBGRAPH CONCENTRATIONS

A Mechanism-Inferring method of networks exploited from machine learning theory caneffectively evaluate the predicting performance of a network model.The existing method for inferringnetwork mechanisms based on a census of subgraph numbers has some drawbacks,especially the needfor a runtime increasing strongly with network size and network density.In this paper,an improvedmethod has been proposed by introducing a census algorithm of subgraph concentrations.Networkmechanism can be quickly inferred by the new method even though the network has large scale andhigh density.Therefore,the application perspective of mechanism-inferring method has been extendedinto the wider fields of large-scale complex networks.By applying the new method to a case of proteininteraction network,the authors obtain the same inferring result as the existing method,which approvesthe effectiveness of the method.

Influence of phase shift drift and splitting ratio on 80 GHz optical mm-wave generation

For the scheme of 80 GHz optical millimeter-wave(mm-wave) generation using two cascaded Mach-Zehnder modulators(MZMs),an exact analytical solution for the optical mm-wave affected by phase shift drift and splitting ratio is derived with the method of expanding Bessel series.The results show that for the carrier and the fourth-order sideband,the influence caused by phase shift drift is dominant,while the first-order,the second-order and the third-order sidebands are influenced by both phase shift drift and splitting ratio.It follows that the undesired sideband suppression ratio is at least 35.9 dB when the splitting ratio deviation is 0.001,and the phase shift drift is 1o.The performance of the system is perfect if the accuracy is achieved.

Precise determination of the α → α+β phase transformation temperature of Zr-1.0Sn-0.3Nb-0.3Fe alloy

In this investigation,differential scanning calorimetry(DSC) and metallographic experiments were performed to study α→α +β phase transformation temperature in a Zr-1.0Sn-0.3Nb-0.3Fe alloy.The deconvolution and extrapolation methods to determine the α→α+β phase transformation temperature in DSC experiment were appropriate for the Zr alloy.Moreover,precise determination of α→α+β phase transformation temperature was carried out by back-scattered electron imaging(BSEI) and electron back-scattered diffraction(EBSD) characterization techniques.The α→α+β phase transformation temperature of the Zr-1.0Sn-0.3Nb-0.3 Fe alloy was determined to be 765-770°C.

Measuring Nonlinear Dependence Between Time Series Based on Correlation Dimension

In this paper, it is proved that the correlation dimension estimate of a nonlinear dynamical system with its multivariate observation series is the same as that with its univariate observation series. Based on this result, an inference method is presented, and the Nonlinear Dependence Coefficient is defined. This method is designed for testing nonlinear dependence between time series, and can be used in economic analysis and forecasting. Numerical results show the method is effective.