Predicting temporal centrality in Opportunistic Mobile Social Networks based on social behavior of people

Predicting the centrality of nodes is a significant problem for different applications in Opportunistic Mobile Social Networks (OMSNs). However, when calculating such metrics, current studies focused on analyzing static networks that do not change over time or using aggregated contact information over a period of time. Furthermore, the centrality measured in the past is not verified whether it is useful as a predictor for the future. In this paper, in order to capture the dynamic behavior of people, we focus on predicting nodes’ future centrality (importance) from the temporal perspective using real mobility traces in OMSNs. Three important centrality metrics, namely betweenness, closeness, and degree centrality, are considered. Through real trace-driven simulations, we find that nodes’ future centrality is highly predictable due to natural social behavior of people. Then, based on the observations in the simulation, we design several reasonable prediction methods to predict nodes’ future temporal centrality. Finally, extensive real trace-driven simulations are conducted to evaluate the performance of our proposed methods. The results show that the Recent Weighted Average Method performs best in the MIT Reality trace, and the recent Uniform Average Method performs best in the Infocom 06 trace. Furthermore, we also evaluate the impact of parameters m and w on the performance of the proposed methods and find proper values of different parameters for each proposed method at the same time.     

Viscosity-difference-induced asymmetric selective focusing for large stroke particle separation

We developed a new approach for particle separation by introducing viscosity difference of the sheath flows to form an asymmetric focusing of sample particle flow. This approach relies on the high-velocity gradient in the asymmetric focusing of the particle flow to generate a lift force, which plays a dominated role in the particle separation. The larger particles migrate away from the original streamline to the side of the higher relative velocity, while the smaller particles remain close to the streamline. Under high-viscosity (glycerol–water solution) and low-viscosity (PBS) sheath flows, a significant large stroke separation between the smaller (1.0 μm) and larger (9.9 μm) particles was achieved in a sample microfluidic device. We demonstrate that the flow rate and the viscosity difference of the sheath flows have an impact on the interval distance of the particle separation that affects the collected purity and on the focusing distribution of the smaller particles that affects the collected concentration. The interval distance of 293 μm (relative to the channel width: 0.281) and the focusing distribution of 112 μm (relative to the channel width: 0.107) were obtained in the 1042-μm-width separation area of the device. This separation method proposed in our work can potentially be applied to biological and medical applications due to the wide interval distance and the narrow focusing distribution of the particle separation, by easy manufacturing in a simple device.     

Novel prototyping method for microfluidic devices based on thermoplastic polyurethane microcapillary film

Thermoplastic polyurethane microcapillary film (TPU-MCF), as a novel extruded product, inherently contains an array of circular micron-sized capillaries embedded inside the polymer matrix. With the aid of simple laser cutting and conventional sealing technologies, a rapid prototyping method for microfluidic devices is proposed based on the ready-made microstructure of MCFs. Two functionalized microfluidic devices: serpentine micromixer and multi-droplet generator, are rapidly fabricated to demonstrate the advantages and potential of employing this new method. The whole proof-of-concept fabrication process can be completed in 8–10 min in a simple way; each procedure is repeatable with stable performance control of microfluidic devices; and the material cost can be as low as $0.01 for each device. The TPU-MCF and this novel method are expected to provide a new perspective and alternative in microfluidic community with particular requirements.     

基于案例分析金字塔模型的主动运维案例体系建设

针对传统运维案例在经验共享和处置效率方面的不足及运维领域同类事件重复发生概率高、处置差异大的情况,提出一种案例分析金字塔模型,使用基于向量化解析和知识分层提取的素材库构建方法,实现由生产运维操作标准库、生产运行异常事件库到案例素材库再到案例教学库的自动生成转变,并以金字塔模型为基础,通过引入改进的趋势预测分析方法、案例推理"5R"模型和"4S"案例教学模式完善预警预测、辅助决策、案例教学相关应用,建立主动运维案例体系。实践结果表明,通过整个体系的推行,改变了企业信息系统运维被动应付的局面,同类事件占比逐年降低,事件响应时间和处置时间明显缩短,运维服务质量大幅提升。     

“智能控制”研究性课程建设探讨

“智能控制”研究性课程旨在将教师的科研成果分层次、分块地融入到原有课程知识体系之中,通过采用探究式、讨论式、专题式、成果展示式等多种教学方式,将智能控制研究领域最新的成果有效地转化为教学资源。课程建设过程中注重学生的实践与动手,围绕“理论、实验、课题项目”进行一体化设计,提升了课程内涵,提高了学生学习智能控制的兴趣,提高了学生研究问题的能力和创新意识,为学生后续实际工程实践打下坚实的基础。     

树形网络中的副本更新策略及算法

树形网络中的副本放置和更新是网络通讯中值得研究的重要问题之一。面对网络中数据访问需求的动态变化,好的副本放置和更新策略可以在保证服务质量的前提下有效减少网络运行及副本更新成本。针对此问题提出了两种贪心的动态副本更新策略,最大重用策略和请求覆盖策略。通过算法复杂度分析和仿真实验可以看出,所提出的两种算法的最坏时间复杂度为O(nlog n),远低于现有的使用动态规划求最优解的最坏时间复杂度O(n5),而网络运行及副本更新成本与最优解相差不超过11%。在极大地缩短了运算时间的同时,保持了尽可能低的网络运行及副本更新成本。     

基于校园一卡通数据的学生消费及学习行为分析

校园一卡通系统通过对各种信息、资源的有效集成、整合和优化,能够实现学校对信息的有效配置和充分利用。采用数据挖掘技术针对学生校园消费、学习活动的管理分析方面进行深入研究,首先,通过数据预处理技术提取相关特征。然后,采用K-means聚类算法针对学生消费行为进行消费习惯聚类分析,并采用决策树算法评估聚类结果;再采用Apriori关联规则算法针对学生学习行为进行学习行为关联度分析,所得结果用于高校学生工作人员分门别类的进行学生管理。     

AM186EM处理器的地址空间优化及应用

本文介绍了一种基于 AM186 EM 处理器的地址空间优化应用,当系统需要处理器支持的最大容量内存时, FLASH 和外围存储器(例如双口 RAM等)可以共用处理器的UCS选通信号,从而实现 FLASH 和外围存储器共用尽可能大的地址空间。同样,当系统需要最大容量的FLASH 时,内存 RAM和外围存储器可以共用处理器的LCS选通信号,从而实现 RAM和外围存储器共用尽可能大的地址空间。     

Efficient link scheduling with joint power control and successive interference cancellation in wireless networks无线网络中联合功率控制和串行干扰消除的高效链路调度算法

Existing works have addressed the interference mitigation by any two of the three approaches: link scheduling, power control, and successive interference cancellation (SIC). In this paper, we integrate the above approaches to further improve the spectral efficiency of the wireless networks and consider the max-min fairness to guarantee the transmission demand of the worst-case link. We formulate the link scheduling with joint power control and SIC (PCSIC) problem as a mixed-integer non-linear programming (MINLP), which has been proven to be NP-complete. Consequently, we propose an iterative algorithm to tackle the problem by decomposing it into a series of linear subproblems, and then the analysis shows that the algorithm has high complexity in the worst case. In order to reduce the computational complexity, we have further devised a two-stage algorithm with polynomial-time complexity. Numerical results show the performance improvements of our proposed algorithms in terms of the network throughput and power consumption compared with the link scheduling scheme only with SIC.