基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。     

负径向电场对带电粒子俘获率影响的数值模拟

本文采用数值方法求解Grad-Shafranov方程反演EAST典型长脉冲放电实验(炮号33068)的平衡位形和磁场分布，进而结合粒子在托卡马克电磁场中的运动方程，模拟氘离子在负径向电场存在时的运动轨迹，并统计不同负径向电场下的氘离子俘获率。结果表明：随负径向电场的增大，氘离子轨迹由扩张通行轨迹向外翻香蕉轨迹再向内翻香蕉轨迹，最后向压缩通行轨迹演变；氘离子俘获率随负径向电场的增大而减小，氘离子初始速度越小，其变化越大。     

On the capacity of the state‐dependent interference relay channel

This paper considers the state‐dependent interference relay channel (SIRC) in which one of the two users may operate as a secondary user and the relay has a noncausal access to the signals from both users. For discrete memoryless SIRC, we first establish the achievable rate region by carefully merging Han‐Kobayashi rate splitting encoding technique, superposition encoding, and Gelfand‐Pinsker encoding technique. Then, based on the achievable rate region that we derive, the capacity of the SIRC is established in many different scenarios including (a) the weak interference regime, (b) the strong interference regime, and (c) the very strong interference regime. This means that our capacity results contain all available known results in the literature. Next, the achievable rate region and the associated capacity results are also evaluated in the case of additive Gaussian noise. Additionally, many numerical examples are investigated to show the value of our theoretical derivations.     

面向电信承载网的监控系统设计与实现

面对电信承载网连接的日益增长的海量终端设备，运营商需要结合网络拓扑对终端设备产生的数据进行高效的汇聚统计、异常分析、故障定位处理等操作。针对已有系统存在的操作困难、分析效率低等问题，设计与实现了一个面向电信承载网的高效监控系统，提供实时与离线数据分析和多维可视化分析的能力。对网管、认证、终端等系统及设备采集的数据进行结构化存储，对采集的数据进行拓扑相关性和时间序列方法分析，根据分析结果实现基于动态阈值控制的异常实时告警、定位等操作，并提供多维度可视化分析对网络状态进行实时监控。实际应用结果表明，该系统性能优异，具有良好交互性，能较好地满足承载网运维人员业务分析需求。     

Components and Development in Big Data System: A Survey

With the growth of distributed computing systems, the modern Big Data analysis platform products often have diversified characteristics. It is hard for users to make decisions when they are in early contact with Big Data platforms. In this paper, we discussed the design principles and research directions of modern Big Data platforms by presenting research in modern Big Data products. We provided a detailed review and comparison of several state-of-the-art frameworks and concluded into a typical structure with five horizontal and one vertical. According to this structure, this paper presents the components and modern optimization technologies developed for Big Data, which helps to choose the most suitable components and architecture from various Big Data technologies based on requirements.     

Chaos-Based transmitted-reference ultra-wideband communications

Transmitted-reference (TR) ultra-wideband (UWB) communication systems have gained increasing popularity for the usage in the low data rate application, due to its non-coherent receiver structure. In conventional TR system, non-coherency at the receiver is achieved by sending reference pulses prior to the data-bearing pulses. Then, at the receiver side, reference pulses are used as template signals for correlation with data-bearing pulses. Therefore, the orthogonality between reference and data pulses is obtained in time division multiple access (TDMA) fashion. However, the implementation of a wideband delay line is very difficult in the current low power integrated circuits. In this paper, a TR method called Chaos-Based TR (CB-TR) is proposed. In the proposed method, chaotic sequences are used to separate the reference and data pulses. Such approach exploits the benefits of chaotic signals, such as non-periodicity, easy-to-generate, impulse-like autocorrelation value and low cross-correlation value. Furthermore, in order to decrease the influence of some negative properties of conventional chaotic maps, a modified chaotic generator (MCS) is proposed. Simulation results over the IEEE 802.15.4a channel model show comparable bit error rate performance to other TR methods.     

基于分支定界法的相控阵雷达事件调度算法

为解决相控阵雷达事件调度问题中调度成功率、时间偏移率与算法时效性三者之间的矛盾，本文提出一种基于分支定界法的调度算法；该算法首先在现有调度结果上调取所有可执行事件，即获得若干"节点"，多步递推后由多"层"节点形成若干条备选"分支"，扩大解空间范围，提高算法性能；然后通过"删减"操作删减掉收益较低分支，将解空间控制在一适当范围内，减小搜索盲目性，降低算法计算量.仿真实验表明，与基于综合优先级算法的调度结果相比，利用本文算法调度时调度成功率提升了52%；与基于时间指针算法的调度结果相比，本身算法时间偏移率降低了61%；与基于遗传算法的调度结果相比，本文算法调度耗时仅为前者1~2%.     

Insight into selective oxidation of dual-phase steel after annealing in pure H2 atmosphere at different heating rates and temperatures

In this paper, the oxidation behaviors of DP980 advanced high strength steel (AHSS) are studied during annealing in a hydrogen atmosphere with different temperatures and heating rates. It is revealed that with the increase in holding time, the different heating rates affecting the surface oxide precipitation on the strip surface will be weakened. Mass transfer of Mn in heating, soaking, and cooling stages has been considered to illustrate the effect of heating rate on the oxide morphology of steel. And then, the Wagner model and aluminothermic reaction kinetics were performed to discuss the transition from external to internal and maximum reduction diameter of MnO oxidation.     

浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。