不同细颗粒含量甲烷水合物沉积物三轴剪切试验研究

海域试开采区域含水合物沉积物的粒度分析结果表明水合物沉积物骨架由粗、细颗粒混合构成,通过开展多组低温、高压三轴排水剪切试验研究细颗粒含量和密度对含甲烷水合物沉积物和无水合物沉积物的强度和变形特性的影响。试验结果表明,含水合物沉积物抗剪强度及剪胀性都随细粒含量提高而显著增强。这是由于细颗粒含量增加改变了颗粒间水合物的样貌和分布特征,形成了由水合物包裹着粗颗粒-细颗粒的团簇状集合体。然而,细颗粒含量对无水合物沉积物的强度和变形特性的影响却表现出相反趋势。另外,含水合物沉积物的剪胀关系可以使用修正剑桥模型中的剪胀关系式进行描述。结果表明,剪胀关系的拟合曲线依赖于水合物饱和度的大小。通过对比研究发现,天然水合物和实验室合成水合物试样在较高饱和度时的峰值摩擦角大小及其伴随水合物饱和度的增长趋势存在差异,这种差异主要来源于水合物在沉积物骨架颗粒孔隙中不同的赋存模式及分布特征。     

Mixture ratio modeling of dynamic systems

Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled-data dependence. The extracted knowledge ultimately serves to a decision-making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black-box modeling deals with “universal” approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high-dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto-regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data-independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential.     

杭州湾南岸滩涂沉积物中HCHs与DDTs污染特征分析

摘 要：目的 了解六六六（hexachlorocyclohexanes,HCHs）与滴滴涕(dichloro diphenyl trichloroethanes,DDTs)在杭州湾南岸滩涂沉积物中的污染现状。方法 于2018年4月，采集杭州湾南岸地区4个采样点不同深度（0~80 cm）滩涂沉积物，利用气相色谱-串联质谱法（gas chromatography tandem mass spectrometry, GC-MS/MS）测定了该区域中HCHs与DDTs的含量，对其分布规律进行分析，使用共识沉积物质量基准法对其生态学风险进行了评估。结果 所有样品中均检出，HCHs与DDTs含量分别为4.20~6.24 μg/kg与3.37~4.73 μg/kg，主要以β-HCH、δ-HCH以及DDE为主，其污染主要来源于历史性工业品，整体污染处于较低水平；20.3%的沉积物样品中DDEs含量以及28.1%的样品DDTs总量介于阈值效应浓度(threshold concentration, TECs) 和可能效应浓度(probable effect concentration, PECs)之间。结论 杭州湾南岸沉积物中HCHs与DDTs的污染处于较低水平，具有较小的生态学风险。     

Container-based cluster orchestration systems: A taxonomy and future directions

Containers, enabling lightweight environment and performance isolation, fast and flexible deployment, and fine-grained resource sharing, have gained popularity in better application management and deployment in addition to hardware virtualization. They are being widely used by organizations to deploy their increasingly diverse workloads derived from modern-day applications such as web services, big data, and internet of things in either proprietary clusters or private and public cloud data centers. This has led to the emergence of container orchestration platforms, which are designed to manage the deployment of containerized applications in large-scale clusters. These systems are capable of running hundreds of thousands of jobs across thousands of machines. To do so efficiently, they must address several important challenges including scalability, fault tolerance and availability, efficient resource utilization, and request throughput maximization among others. This paper studies these management systems and proposes a taxonomy that identifies different mechanisms that can be used to meet the aforementioned challenges. The proposed classification is then applied to various state-of-the-art systems leading to the identification of open research challenges and gaps in the literature intended as future directions for researchers.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

The impacts of cattle access points on deposited sediment levels in headwater streams in Ireland

Cattle access to streams has been linked globally with degradation of stream water quality, driven largely by bank erosion and resultant instream, fine sediment deposition. The majority of evidence on such effects is however based in arid and semiarid regions of the United States and Australia, with few studies relating to cool temperate climates such as Northwest Europe. In this study, “Quorer” resuspendable sediment samples were taken from riffle geomorphic units upstream (control) and at two points downstream (pressure and recovery) of cattle access points in headwater streams in agricultural catchments in Ireland to assess levels of deposited stream sediment. Samples were taken in April/May (2016) prior to the grazing season and in October (2016) at the end of the grazing season. Sites in good‐high ecological status catchments and less than good ecological status catchments were included in the study. Higher levels of sediment were found downstream of cattle access points in both good‐high status and less than good status catchments; however, the impacts of access points were spatially confined to, in most cases, the area immediately downstream of the point of access. There was a strong correlation between deposited sediment mass and organic matter (OM) mass, with levels of OM increasing linearly with deposited sediment mass. Levels of measured sediment were negatively correlated with riparian habitat health (measured using a qualitative habitat assessment). The results of this study highlight the need for measures to prevent cattle access to headwater streams where access points can be many in order to manage local habitat quality and downstream water quality issues.     

论煤矿地质测量工作在安全生产中的作用

煤矿开采是在地层中进行的,不可避免地受到地质条件的影响。很多煤矿灾害的发生与地质构造有关,因此了解煤矿开采中的地质构造十分有必要。为了了解煤层的地质构造,必须对煤矿地质条件进行测量。分析了煤矿地质测量对安全生产的作用,并提出了一些措施来提升煤矿地质测量的有效性,可以为煤矿地质测量工作人员提供一定的参考。     

5G基站供配电勘察设计思路的调整分析

针对5G基站设备相对于以往2G/3G/4G设备的变化,面向一线勘察设计人员,阐述5G基站在供配电需求方面功耗增大、供电方式多样化、供配电改造工作量和难度加大等相应变化,归纳相应的勘察前期准备工作要点,分析在实际工作中可能面临的外市电引入改造、供电方式选择的多样性、新型锂电池应用等重点、难点,介绍理想的5G供配电模式及发展方向,最后提出5G基站供配电勘察设计工作思路调整的建议。     

Effects of risks on the performance of business process outsourcing projects: The moderating roles of knowledge management capabilities

Although business process outsourcing (BPO) can reduce cost and enhance the competitiveness of firms, the implementation of BPO projects is unsatisfactory. By integrating knowledge management capability theory and risk-based view, we develop a model of how different types of BPO risks affect project satisfaction and how knowledge management capability changes the influences of BPO risks. A survey of 121 BPO projects was conducted among BPO client department manager and project manager through a pairwise design. Empirical evidence reveals that social system, technical system, and project management risks negatively affect BPO project satisfaction. However, cultural, technological, and structural levels of knowledge management capabilities weaken the negative risk effects of social system, technical system, and project management, respectively. Different types of risks and knowledge management capabilities should be matched to achieve effective risk management.     

基于流数据聚类算法的电力大数据异常检测

针对电力大数据流的异常检测问题,该文将流数据聚类算法与电力大数据相结合,针对现有流数据聚类算法不易存储全部数据、断电数据易丢失等问题,以及流数据聚类算法对于离线阶段聚类算法实时应答的要求,从数据的完整性、安全性以及流数据聚类算法的低时间复杂度的角度出发,对CluStream流数据聚类算法进行改进,提出流式K-means聚类算法。对在线阶段,使用Redis集群进行流数据的缓冲,并设计节点时间衰减策略,增大心跳消息中有效消息所占比例;对离线阶段聚类算法进行优化,使用最佳距离法确定初始聚类中心,减少迭代次数;最后,使用所提出的流式K-means聚类算法进行用户用电异常行为检测,实验结果表明,该算法能够很好的发现用户用电异常行为。