认知双向中继网络在κ-μ衰落信道下的中断性能分析

针对认知双向中继网络在进行数据传输时面临的复杂无线信道场景问题,采用广义κ-μ分布构建认知双向中继网络中的视距和非视距无线传输信道,推导次网络在κ-μ衰落信道下的统一中断概率,并分析次网络在多种单一和混合衰落信道情况下的中断性能。仿真结果表明,无线信道的衰落程度对次网络的中断概率影响显著,依据衰落信道类型合理设置网络参数将有助于提升次网络中断性能。     

Predicting the mechanical properties of Cu–Al2O3 nanocomposites using machine learning and finite element simulation of indentation experiments

Micromechanics model, finite element (FE) simulation of microindentation and machine learning were deployed to predict the mechanical properties of Cu–Al₂O₃ nanocomposites. The micromechanical model was developed based on the rule of mixture and grain and grain boundary sizes evolution to predict the elastic modulus of the produced nanocomposites. Then, a FE model was developed to simulate the microindentation test. The input for the FE model was the elastic modulus that was computed using the micromechanics model and wide range of yield and tangent stresses values. Finally, the output load-displacement response from the FE model, the elastic modulus, the yield and tangent strengths used for the FE simulations, and the residual indentation depth were used to train the machine learning model (Random vector functional link network) for the prediction of the yield and tangent stresses of the produced nanocomposites. Cu–Al₂O₃ nanocomposites with different Al₂O₃ concentration were manufactured using insitu chemical method to validate the proposed model. After training the model, the microindentation experimental load-displacement curve for Cu–Al₂O₃ nanocomposites was fed to the machine learning model and the mechanical properties were obtained. The obtained mechanical properties were in very good agreement with the experimental ones achieving 0.99 coefficient of determination R2 for the yield strength.     

基于云网PoP的弹性边缘网络设计思路探讨

移动边缘云是公司“云+5G”双引擎战略的最佳契合点,边缘网络是发挥移动云“大云”产品和5G网络融合优势,实现云网统筹、构建运营商“连接+计算”核心能力的关键。运营商传统接入网存在云网割裂、分段入云和组网复杂等突出问题,难以适应边缘业务敏捷交付要求。本文通过深入分析边缘云业务特征和技术架构,对标业界主流云商建设实践,研究基于云网PoP网的边缘网络建设思路,创新性提出云网一体化规划设计和建设交付流程变革,基于云网POP统一网络和业务锚点,构建Overlay和Underlay融合双层加速网络架构,探索Spine-leaf化的新型城域接入网实现L3下沉和弹性扩容等方法,实现“云+网+应用”一体化敏捷交付的边缘网络能力。     

Multiple material domain‐based computational tools for ease assessment of modal parameter in photonic crystal fibers

We report here the development of two computational tools PCFPS (Photonic Crystal Fiber Parameter Study) and PCFPA (Photonic Crystal Fiber Parameter Analysis), equipped with graphical user interface (GUI) for modeling of photonic crystal fiber. The tools are based on different structural parameters, and they provide characteristic analysis of the modal parameters from the structural parameters. The main feature of PCFPS is that it enables the user to find out the values of each defining modal parameter that has an immense contribution towards the manufacture of photonic crystal fiber. Additionally, PCFPA allows the user to observe the variation in the modal parameters with respect to the changes in structural parameters (such as d, Λ, d/Λ, and λ/>Λ). Besides their ease of use, these two schemes have high computational precision and adaptability, giving a novel platform to optical engineers to modulate the microstructured fibers according to their requirement.     

基于K-means和SOM的水下传感器数据采集方法

随着海洋资源勘探和海洋污染物监控工作的开展，水文数据的监测和采集等已经成为重要的研究方向。其中，水下无线传感器网络在水文数据采集过程中起着举足轻重的作用。本文研究的是水下无线传感器二维监测网络模型中，传感器节点数据采集的问题，其设计方法是通过自组织映射（Self-organizing mapping，SOM）对传感器节点进行路径最优化处理，结合优化的路径图形和K-means算法找到路径内部聚合点，利用聚合点和传感器的节点得到传感器通信半径内的数据采集点，最后通过SOM得到水下机器人（Autonomous underwater vehicle，AUV）到各个数据采集点采集数据的最优路径。经过实验验证，在水下1 200 m×1 750 m范围内布置52个传感器节点的情景下，数据采集点相比于传感器节点路径规划采用相同的采集顺序得到的路径优化了6.7%；对数据采集点重新进行自组织路径规划得到的路径比传感器结点路径的最优解提高了12.2%。增加传感器节点的数量，其结果也大致相同，因此采用该方法可以提高水下机器人采集数据的效率。     

电商平台产品共同购买网络的影响因素研究

共同购买网络的推荐系统应用越加广泛，仅基于网络内生结构变量研究其共同购买链接的经济意义已有局限，故加入网络口碑这一外生变量，进行更全面的分析。采用了社会网络方法中指数随机图模型进行建模，主要围绕产品销售量、产品入度、差评率和评论数4个方面因素，探究其对共同购买网络中共同购买链接形成的影响。结果显示，销售量、产品入度和评论数对共同购买链接形成的影响呈正比关系，而差评率则会显著地降低产品共同购买的几率。该指数随机图构建出的共同购买网络为在线电商平台管理网络口碑和推荐系统优化设计提供有益参考。     

Computerized morphometry analysis of epithelial fimbriae nuclear symmetry in BRCA carriers may identify patients at risk for developing ovarian cancer

Serous ovarian tumors may originate in epithelial cells of the fallopian tubes. Computerized morphometry was able to find significant alterations in the fallopian tube epithelium of healthy BRCA carriers. The purpose of this study was to identify a subgroup of BRCA carriers that may be at risk of developing serous ovarian cancer by evaluation of the epithelial nuclear symmetry in the fallopian tubes. Four groups of patients were analyzed; healthy patients, ovarian cancer patients, BRCA carriers, and BRCA noncarriers. All fallopian tubes appeared normal by H&E examination. The ImageProPlus software was used to assess the nuclear symmetry of 65 fimbriae epithelium cells and an artificial neural network algorithm aided in detecting a subpopulation among fimbriae of healthy BRCA carriers at risk for ovarian cancer. Significant differences were found between healthy patients and ovarian cancer patients, and between BRCA carriers and noncarriers. The algorithm was able to accurately predict BRCA carriers with associated ovarian cancer based on fallopian tube nuclear symmetry characteristics. These results reinforce the hypothesis that fimbriae epithelial cells of BRCA carriers may undergo early-stage changes that could predict the risk of progression toward malignancy.     

Effect of ball-milling parameters on the rheological properties of mold powder slurry

In this study, mold powder slurries with high solid loading and low viscosity were prepared during the ball-milling process for improving the homogeneity and mechanical properties of granules after spray-drying. The effect of ball-milling parameters, such as solid loading, binder/dispersant content, and ball-milling time, on the flowability, dispersibility, stability, and rheological behavior of mold powder slurries was systematically investigated by rheology observation and sedimentation tests. As these parameters varied, the slurry exhibited the shear-thinning behavior of a non-Newtonian fluid with a shear rate range of 0–50 s^?1, which was adequately described by the Herschel-Bulkley model. The optimal parameters that optimized the flowability, dispersibility, and stability of the slurry, along with its rheological behavior, were chosen as follows: solid loading, 60 wt%; modified sodium carboxymethyl cellulose binder content, 1.0 wt%; sodium tripolyphosphate dispersant content, 0.5 wt%; ball-milling time, 60 min.