基于组播和P2P的文件分发管理模块的设计与实现

本文对CNGI研究课题"组播与P2P相结合的文件分发系统"进行了简要介绍.通过对该系统文件管理模块的总体设计和详细设计,实现了基于IPv6组播与P2P技术的结合.该系统借助JxTA平台实现P2P的基本功能:节点搜索、节点资源搜索、节点间的通讯和文件的统一管理等,实现了尽量利用可靠的组播并利用P2P实现跨组播域的信息传输.最后通过对管理模块在不同环境下的测试数据进行分析,表明该设计思想的有效性.     

基于组织结构的纺织品各向异性建模方法

纺织面料的物理仿真将虚拟现实与纺织CAD相结合,是虚拟服装与试衣系统研究的一项关键技术,纺织品建模也是纺织品真实感模拟的基础及关键工作.在基于物理的粒子系统的基础上,提出各向异性的建模方式.根据织物面料的不同组织方式进行分析,对其进行经纬方向的分离建模.仿真过程分为初始过程的刚性物体模拟和接近平衡时的柔性物质模拟两大步骤.为了在产生逼真表现效果的同时兼顾计算复杂性,构模时引入多分辨率模型.     

高铁场景下联合天线与IOS单元选择的分布式IOS-SM传输方案

针对高铁场景下封闭车厢带来的高信号穿透损耗导致传输速率下降问题,提出一种分布式智能全表面（intelligent omni-surface,IOS）辅助空间调制（spatial modulation,SM）的传输方案。首先,采用SM技术保证索引信息部分不受穿透损耗的影响;然后,为了减小远距离IOS车窗的高路径损耗和功率损耗,根据最大化接收信噪比原则对分布式IOS遍历选择,激活最佳IOS车窗传输SM调制信息。最后,为了减小缺失直视路径增益对系统容量性能的影响,基于功率损耗模型,采用天线移除原则和排序选择方式,对接收天线和IOS单元进行动态选择激活。仿真结果表明,相比于传统中继转发和可重构智能超表面-空间调制（reconfigurable intelligence surface-SM,RIS-SM）方案,所提方案更适合高铁通信场景。并且在功率损耗模型下,联合天线与IOS单元选择的分布式IOS-SM方案仍能够保证系统高性能传输。     

Analysis on influencing factors of detecting chemical oxygen demand in water by ultraviolet absorption spectroscopy

Taking the standard solution and actual water samples as the research object, this paper studies the influence of various environmental factors (temperature, alkalinity (pH), inorganic salt ions and salinity) on the detection of chemical oxygen demand (COD) in water by ultra-violet (UV) spectrometry, analyzes the influence mechanism, and draws relevant conclusions. The results show that the UV absorbance of the COD standard solution and the actual river water samples varies very little with temperature. The value of pH has certain impact on both the standard solution and the actual water samples, but the pH values of the affected experimental samples are in different ranges. The effects of nitrogen salt ions (NO2- and NO3-) on the UV absorption spectra can be eliminated by intercepting the UV spectrum interval less affected for modeling. The influence of salinity values below 35‰ on the UV absorption spectrum of water is mainly concentrated in the spectral band of 200—250 nm, and the influence above 250 nm is very little. This paper provides a preliminary analysis and discussion on the influence mechanism and laws of various environmental factors in the detection of water quality parameters by UV spectrometry, which provides an experimental basis for selecting the optimal test conditions when establishing the COD prediction model.     

Application of quantum genetic algorithm in high noise laser image security

Aiming at the security problem of range gated laser imaging in high noise background, a range gated laser image encryption scheme based on the quantum genetic algorithm (QGA) is proposed. Due to the fuzziness of the laser image itself, the randomness and security of the key become more and more important in encryption. In this paper, the chaotic sequence is used as the parent chromosome of the QGA, and the random number satisfying the encryption algorithm is obtained by an iterative genetic algorithm. To further improve the security of laser images, some random pixels are stochastically inserted around the laser image before scrambling. These random pixels are scrambled together with the image. Finally, an adaptive diffusion method is designed to completely change the original statistical information of the image. Experimental simulation and performance analysis show that the scheme has high security.     

3D printing system: an innovation for small-scale manufacturing in home settings? – early adopters of 3D printing systems in China

This study investigates Chinese consumers’ adoption of the innovative 3D printing systems for small-scale manufacturing in home settings. Empirical studies were conducted in a survey with 256 participants. The number of significant determinants that affect an individual’s decision to adopt 3D printing systems has been identified by applying a model that integrates the Technology Acceptance Model and Innovation Diffusion Theory. A number of moderation effects of demographic variables (e.g. gender, design background) on the association between motivational variables and participants’ adoption have also been analysed with factor analysis, structural equation modelling and hierarchical regression. Our results shed some light on the characteristics of early adopters of home 3D printing systems in China. This study contributes to the early understanding of Chinese consumers’ adoption of innovative 3D printing systems.     

酒石酸还原Cu(Ⅱ)制备多种形貌Cu_2O晶体及形成机理

以CuSO_4·5H_2O为原料,KOH为添加剂,酒石酸为还原剂,在水热条件下通过调整相关的实验参数,制备了一系列不同形态的Cu_2O微-纳米晶体及三维十字形枝晶。采用XRD、SEM等手段对不同形态的Cu_2O晶体进行了表征,探讨了不同因素变化对Cu_2O晶体形态的影响。分析认为,晶体生长过程控制了晶体的具体形貌和大小,Cu_2O晶体显露的单形晶面随晶体生长条件的变化而不同。在低温、弱碱性、高浓度溶液中有利于形成八面体形态的Cu_2O晶体,而菱形十二面体单形晶面在高温、强碱性、低浓度溶液中形成的晶体中显露的面积有所增大。     

Engineering 3D Ru/Graphene Aerogel Using Metal–Organic Frameworks: Capture and Highly Efficient Catalytic CO Oxidation at Room Temperature

Noble metals (Au, Pt, and Ru) loaded into carbon supports show excellent performance for CO oxidation. Herein, a tunable metal–organic framework (MOF) coating is applied to a macroscopic 3D Ru/graphene aerogel (Ru/GA) composite, using a facial step‐by‐step method. The open macroporous structure of the Ru/GA provides pathways for the access and diffusion of reactant and product molecules. The resulting HK (HKUST‐1)‐containing MOF composite exhibits good performance for CO adsorption. It can simultaneously adsorb and oxidize CO, which improves the reaction rate. In this work, the catalytic efficiency of the resulting catalyst is higher than that (≈48.4%) of the Ru/GA. These findings provide a simple method for increasing the instantaneous concentration of reactants around the catalyst, which in turn increases the reaction rate. The catalytic performances of composites subjected to different pretreatment conditions are also investigated. Hopefully, this finding may provide a feasible direction for the effective management of the diverse environment issues.     

基于数据挖掘方法的风力涡轮机状态监测技术研究

目前风力涡轮机的故障模式预测成为了风力发电站发展的重要任务;提出了一种基于数据挖掘算法的涡轮机故障状态预测方法;这种方法包括3个主要的步骤:涡轮机状态抽象,算法训练,状态预测;首先利用先验知识将涡轮机的初始状态进行分类,选择建立预测模型的参数;为了降低计算难度,采用数据挖掘算法进行模型参数的选择;最终采用发电机转速、变速箱速度、温度枢纽、叶片螺距角这些参数进行预测模型的建立;建立预测模型的过程分为3个阶段:预测任意故障;预测系统的特殊故障;确定未知故障;通过对各种数据挖掘算法基于大量风力涡轮机数据的性能分析,选择了性能最优的随机森林算法模型;这种模型的预测准确率能够达到98%;同时还能够预测训练数据没有包含的故障类型;通过在实际风力涡轮机数据的验证,表明了这种模型的稳健性。