An Influence Maximization Algorithm Based on Improved K-Shell in Temporal Social Networks

Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving the K-shell method. Then, in the local scope, the calculation method of comprehensive degree is proposed to weigh the influence of nodes. Finally, the node with the highest comprehensive degree in each core layer is selected as the seed. However, the seed selection strategy of KT can easily lose some influential nodes. Thus, by optimizing the seed selection strategy, this paper proposes an efficient heuristic algorithm called improved K-shell in temporal social networks for influence maximization (KTIM). According to the hierarchical distribution of cores, the algorithm adds nodes near the central core to the candidate seed set. It then searches for seeds in the candidate seed set according to the comprehensive degree. Experiments show that KTIM is close to the best performing improved method for influence maximization of temporal graph (IMIT) algorithm in terms of effectiveness, but runs at least an order of magnitude faster than it. Therefore, considering the effectiveness and efficiency simultaneously in temporal social networks, the KTIM algorithm works better than other baseline algorithms.     

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.     

Composition-Controllable Syntheses and Property Modulations from 2D Ferromagnetic Fe5Se8 to Metallic Fe3Se4 Nanosheets

Exploring new-type 2D magnetic materials with high magnetic transition temperature and robust air stability has attracted wide attention for developing innovative spintronic devices. Recently, intercalation of native metal atoms into the van der Waals gaps of 2D layered transition metal dichalcogenides (TMDs) has been developed to form 2D non-layered magnetic TMDs, while only succeeded in limited systems (e.g., Cr₂S₃, Cr₅Te₈). Herein, composition-controllable syntheses of 2D non-layered iron selenide nanosheets (25% Fe-intercalated triclinic Fe₅Se₈ and 50% Fe-intercalated monoclinic Fe₃Se₄) are firstly reported, via a robust chemical vapor deposition strategy. Specifically, the 2D Fe₅Se₈ exhibits intrinsic room-temperature ferromagnetic property, which is explained by the change of electron spin states from layered 1T'-FeSe₂ to non-layered Fe-intercalated Fe₅Se₈ based on density functional theory calculations. In contrast, the ultrathin Fe₃Se₄ presents novel metallic features comparable with that of metallic TMDs. This work hereby sheds light on the composition-controllable synthesis and fundamental property exploration of 2D self-intercalation induced novel TMDs compounds, by propelling their application explorations in nanoelectronics and spintronics-related fields.     

对话框设计在机械 CAD 系统的应用

介绍了在ＡｕｔｏＣＡＤＲ１２．０下进行对话框设计的一些方法。包括参数化设计、数据检索以及主要的构件类型,并列举了有关例子。     

多目标群体决策的区间层次分析法研究

基于专家个体判断矩阵,应用数理统计及误差理论,探讨了综合判断矩阵的建立途径,给出了用区间层次分析法求解多目标群体决策问题的算法与步骤,最后以算例说明该方法的实用性及有效性。     

基于模糊神经网络及证据推理的数据融合系统

在研究战术弹道导弹电子对抗条件下作战仿真运用问题时,我们成功地将模糊神经网络与证据推理相结合,弥补了传统多传感器数据融合系统未考虑外界环境因素影响的缺陷,提高了数据融合系统的抗干扰能力,最后简单介绍了仿真系统软件的实现流程。这是作战仿真方法研究及实现的新途径。     

Study of the diffusion of Al–Li alloys subjected to an electric field

An experimental investigation of the homogenization treatment of 2091 Al–Li alloy in the presence of an electric field, has revealed the phenomena of reduced volume fraction, small size, spherical shape and random distribution of second-phase particles, which bring about an increase in ductility. The results show that the dissolution of second-phase particles is promoted by means of the vacancy mechanism, because of the larger diffusion coefficient of solute atoms than the vacancy–solute complexes at the beginning of the homogenization treatment. By increasing the homogenization time and applying an electric field, the diffusion coefficient of vacancy-solute complexes is raised, whereas that of solute atoms is reduced, because of the decreased potential energy of the second phase at grain boundaries. Therefore, the non-equilibrium segregation of magnesium and copper elements is generated near the surface of the ingot by a complex mechanism. An experimental study of the solution treatment under an electric field, revealed that the lithium non-equilibrium segregation is induced at grain boundaries responsible for the precipitates. © 1998 Chapman & Hall     

Design and fabrication of a diffractive phase element for wavelength demultiplexing and spatial focusing simultaneously

The design of a diffractive phase element (DPE) that simultaneously implements wavelength demultiplexing and focusing is carried out on the basis of the general theory of amplitude-phase retrieval. The designed DPE is fabricated with optical contact lithography. Three masks are needed to produce the surface-relief structure of the DPE with eight quantized levels in depths. Experiments demonstrate that the designed DPE can successfully implement both the functions of demultiplexing three different-wavelength beams and focusing each component at a predesignated position simultaneously. Experimental measurements are in good agreement with the results of numerical simulations.     

Molecular dynamics simulation on flow behavior of nanofluids between flat plates under shear flow condition

Molecular dynamic model of nanofluid between flat plates under shear flow conditions was built. The nanofluid model consisted of 12 spherical copper nanoparticles with each particle diameter of 4 nm and argon atoms as base liquid. The Lennard–Jones (LJ) potential function was adopted to deal with the interactions between atoms. Thus, the motion states of nanoparticles during the process of flowing were obtained and the flow behaviors of nanofluid between flat plates at different moments could be analyzed. The simulation results showed that an absorption layer of argon atoms existed surrounding each nanoparticle and would accompany with the particle to move. The absorption layer contributed little to the flow of nanoparticles but much to the heat transferring in nanofluids. Another phenomenon observed during shear flowing process was that the nanoparticles would vibrate and rotate besides main flowing with liquid argon and these micro-motions could strengthen partial flowing in nanofluids.     

车载无线电台同址干扰测试与分析

同址干扰是车载、舰载、机载无线电通信中面临的一个重要问题,针对同址干扰对复杂通信系统的影响提出了一种有效的测试和分析方法;首先对车载电台的各种天线进行了耦合度测试,从实验和仿真两方面阐述了同址干扰的严重程度,为进一步定量分析同址干扰的影响,构建了有线测试平台;在需求分析基础上,详细介绍了平台的组成,并以短波、超短波电台为对象,通过大量现场实验,深入分析了误码率,同址工作电台的频率间隔和功率之间的相互关系;研究表明,同址干扰的定量分析是设计车载通信系统,合理分配电台工作参数的关键环节。