基于双向流固耦合弹性环式挤压油膜阻尼器建模及动力学特性研究

利用数值方法建立了弹性环式挤压油膜阻尼器(ERSFD)的流固耦合模型,分别利用有限元方法以及有限体积法建立了弹性环和内外油膜的CFD数值模型,并进一步利用分时迭代的弱耦合方法实现了油膜以及弹性环控制方程的耦合求解,获得了内油膜的压力分布特性及弹性环的变形,并进一步识别了油膜和弹性环的动力学特性系数;研究了涡动频率、凸台数目、凸台高度、凸台宽度以及弹性环厚度对阻尼器动力学特性系数的影响。结果表明,弹性环的凸台高度对ERSFD油膜动力学特性系数的影响最为明显,ERSFD油膜阻尼与涡动频率无关。     

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。     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

The significant promotion of g-C3N4 on Pt/CNS catalyst for the electrocatalytic oxidation of methanol

This article reported a series of g–C₃N₄–CNS (g-C₃N₄ and carbon nanosheets) composite carriers formed by the hydrothermal method, and then the ethylene glycol reduction method was used to anchor Pt nanoparticles on the g–C₃N₄–CNS carrier to form the Pt/g–C₃N₄–CNS catalysts. The electrochemical test for the electrocatalytic oxidation of methanol (MOR) shown that the Pt/20%g–C₃N₄–CNS catalyst has the best catalytic performance and stability. These Pt/g–C₃N₄–CNS catalysts were analyzed by TEM, XRD, XPS, and BET characterization. It is discovered that the amount of g-C₃N₄ greatly influenced the structure and chemical properties of Pt/CNS precursor. As the content of g-C₃N₄ increases, the content of pyridine nitrogen and pyrrole nitrogen also increases, and N species can enhance the interaction between Pt nanoparticles and CNS, promote Pt dispersion, and increase the specific surface area of the catalyst. Similarly, an excessive addition of g-C₃N₄ will cause a sharp decline in the conductivity of the catalyst, and then led to the decline of MOR activity.     

WSN低功耗低时延路径式协同计算方法

针对云计算应用于无线传感器网络(Wireless Sensor Network,WSN)时延敏感型业务时存在的高传输时延问题,提出了一种WSN低功耗低时延路径式协同计算方法。该方法基于一种云雾网络架构开展研究,该架构利用汇聚节点组成雾计算层;在数据传输过程中基于雾计算层的计算能力分步骤完成任务计算,降低任务处理时延;由于汇聚节点计算能力较弱,时延降低将导致能耗增加,WSN工作寿命减短,为此提出能耗约束下的任务映射策略,并利用离散二进制粒子群优化(Binary Particle Swarm Optimization,BPSO)算法解决能耗约束下的时延优化问题。仿真结果表明,在相同的能耗约束下,对比其他算法,基于BPSO算法得出的映射方案能有效降低业务处理时延,满足时延敏感型业务的需求。     

矿产资源节约集约利用驱动因素研究

矿产资源属于耗竭性资源,基于其稀缺性和不可再生性,从国家资源安全战略考虑,通过节约集约利用缓解资源短缺问题是一种有效的途径。本文以矿产资源节约集约利用为研究目标,从政策驱动和技术驱动角度,研究了规划、税收、监管、标准、资源禀赋条件、采矿技术、选矿技术等驱动因素的驱动机理,以及与矿产资源利用的关系,分析了各驱动因素的现行政策和存在的问题。研究表明,各驱动因素促进矿产资源节约集约利用的过程是相互的、复杂的,在多因素的共同作用下,驱动因素之间的协同能力是实现目标的关键,协同程度越高,矿产资源节约集约利用的成效越好。     

ChronoCorrelator: Enriching Events with Time Series

Event sequences and time series are widely recorded in many application domains; examples are stock market prices, electronic health records, server operation and performance logs. Common goals for recording are monitoring, root cause analysis and predictive analytics. Current analysis methods generally focus on the exploration of either event sequences or time series. However, deeper insights are gained by combining both. We present a visual analytics approach where users can explore both time series and event data simultaneously, combining visualization, automated methods and human interaction. We enable users to iteratively refine the visualization. Correlations between event sequences and time series can be found by means of an interactive algorithm, which also computes the presence of monotonic effects. We illustrate the effectiveness of our method by applying it to real world and synthetic data sets.     

基于压缩感知的移动群智感知任务分发机制

针对移动群智感知任务中区域全覆盖感知成本过高问题，提出基于压缩感知的移动群智感知任务分发（CS-TD）机制。首先提出了感知任务整体成本模型，该模型综合考虑了参与感知任务的节点个数、节点的感知次数与数据上传次数；然后基于成本模型，分析感知节点的日常移动轨迹，结合压缩感知数据采集技术，提出了一种基于感知节点轨迹的压缩感知采样方法；其次通过区域全覆盖最少节点（RCLN）算法，选出最佳节点集合，对节点进行任务分配，利用压缩感知技术恢复节点数据；最后在多次感知任务的迭代中对感知节点的可信程度进行评定，保证任务方案的最优性。对CS-TD分发模型进行多次实验验证，与已有的CrowdTasker算法相比，CS-TD算法平均成本降低了30%以上。CS-TD模型能有效降低感知节点的消耗，能在全覆盖感知任务中降低整体感知成本。     

Why stop after 20 minutes? Breaks and target prevalence in a 60-minute X-ray baggage screening task

Current EU regulation restricts continuously reviewing X-ray images of passenger baggage to 20-min duration as a precautionary measure to prevent performance decrements in airport security officers (screeners). However, this 20-min limit is not based on clear empirical evidence on how well screeners can sustain their performance over time. Our study tested screeners in a 60-min simulated X-ray cabin baggage screening task. One group took 10-min breaks after 20 min of screening; the other group worked without breaks. We found no decrease in performance over 60 min in either group. Breaks did not affect performance, but they did reduce the amount of subjective distress. By varying target prevalence, we found that d_a with a slope of about 0.6 is a more valid measure of detection performance than d'. Target prevalence caused a criterion shift. Our results provide a basis for conducting field studies of prolonged screening durations, and open the discussion on whether more flexible break policies and work schedules should be considered.