基于Streams的高可用数据库系统模型研究

在分析Oracle streams工作原理的基础上,指出了基于streams构建高可用数据库系统是可行的;并与Oracle提供的其他高可用方案相对比,Streams具有在性能、控制的灵活性、成本和维护等方面的优点.最后针对零数据丢失的企业需求,设计了Streams结合Dataguard的高可用数据库模型,并验证了该模型在提高系统可用性方面的作用.     

Land inputs of trace metals, major elements, particulate organic carbon and suspended solids to an industrial coastal bay of the NE Atlantic

Rivers, streams and municipal and industrial effluents flowing into the Ferrol Ria (NW Spain) were analyzed for dissolved and particulate trace elements (Cd, Cu, Pb, Zn), particulate major elements (Al, Fe, Si), particulate organic carbon and nitrogen (POC and PON), and total suspended solids. Trace metal clean techniques were applied. Mean annual fluxes of these components were calculated. Dissolved trace metal concentrations in the major freshwater inputs were found to be within typical values for uncontaminated rivers: Cd: 0.020-0.035 nM; Cu: 11.7-19.2 nM; Pb: 0.40-0.71 nM and Zn: 18-54 nM. Two sources of suspended particulate matter (SPM) were observed: (i) a detrital SPM, which becomes more important at high river discharges, with metal concentrations tending to lithogenic values; (ii) an organic- and metal-rich SPM, which becomes dominant at low discharges. Municipal and industrial effluents in the northern shore, despite of constitute a minor freshwater contribution to the bay, were responsible for more than 50% of total inputs of Cu, Cd, Pb, Zn, POC and PON. The fluxes of trace metals obtained for the Ferrol Ria are in the range of other inhabited world semi-enclosed embayments.     

Flow Structure at Different Stages in a Meander-Bend with Bendway Weirs

Streambank erosion is an important management issue, particularly for meandering rivers. Recently, bendway weirs have become popular control measures for bank erosion along small meandering streams in the agricultural Midwest. Although these structures have successfully mitigated bank erosion in some cases, there is evidence that the weirs do not always perform as anticipated. Scientific understanding of how bendway weirs influence flow dynamics, streambank erosion, and aquatic habitat is limited. Current design criteria are based primarily on expert judgment rather than a formalized technical design procedure. At field-scale studies, the present paper represents a first step toward an integrated geomorphological and engineering evaluation of the performance of bendway weirs in rivers. To accomplish this initial phase, three-dimensional (3D) velocity data were collected on Sugar Creek at Brookside Farm, Ill., and 3D numerical simulations for low-flow conditions were performed to validate the computational fluid dynamic model. Overall results show good agreement between measured and simulated data for streamwise velocities and turbulence kinetic energy. The model is less accurate at predicting the velocity and turbulence kinetic energy in the shear layer immediately downstream from the weir tips. Based on the validation for low-flow condition, 3D simulations were carried out for medium and high flows where the bendway weirs are completely submerged. These simulations indicate that 3D patterns of flow, especially flow near the outer bank, change dramatically with changes in flow stage. Flow patterns at high-flow condition indicate that bank retreat over the tops of weirs is associated with locally high-shear stresses, thus producing a “shelf” along the base of the outer bank as observed in the field.     

基于ANSYS平台的中厚板控冷过程的横向冷却曲线

针对中厚板控冷过程中均匀喷水时造成钢板变形的现象,提出了非均匀喷水的补偿方法,利用ANSYS大型有限元分析软件对钢板在多股集管冲击射流作用下的温度场分布进行了数值模拟,得到钢板横向冷却曲线,为控冷装置上集管的工艺设计提供了理论依据。     

The orchestration of Machine Learning frameworks with data streams and GPU acceleration in Kafka-ML: A deep-learning performance comparative

Machine Learning (ML) applications need large volumes of data to train their models so that they can make high-quality predictions. Given digital revolution enablers such as the Internet of Things (IoT) and the Industry 4.0, this information is generated in large quantities in terms of continuous data streams and not in terms of static datasets as it is the case with most AI (Artificial Intelligence) frameworks. Kafka-ML is a novel open-source framework that allows the complete management of ML/AI pipelines through data streams. In this article, we present new features for the Kafka-ML framework, such as the support for the well-known ML/AI framework PyTorch, as well as for GPU acceleration at different points along the pipeline. This pipeline will be described by taking a real Industry 4.0 use case in the Petrochemical Industry. Finally, a comprehensive evaluation with state-of-the-art deep learning models will be carried out to demonstrate the feasibility of the platform.     

适于数据流组合分类的直推学习方法

在进行组合决策时,已有的组合分类方法需要对多个组合分类器均有效的公共已知标签训练样本。为了解决在没有已知标签样本的情况下数据流组合分类决策问题,提出一种基于约束学习的数据流组合分类器的融合策略。在判定测试样本上的决策时,根据直推学习理论设计满足每一个局部分类器约束度量的方法,保证了约束的可行性,解决了分布式分类聚集时最大熵的直推扩展问题。测试数据集上的实验证明,与已有的直推学习方法相比,此方法可以获得更好的决策精度,可以应用于数据流组合分类的融合。     

小口径喷嘴冲击射流噪声锯齿特性及机理研究

测量了3毫米口径轴对称收缩喷嘴射流冲击大平板产生的噪声随冲击距离变化的特性。发现远场噪声随冲击距离的变化呈锯齿状，射流上游的噪声频谱上有粗缓、跨较宽频带的尖峰。根据不同唇厚喷嘴的实验对比，判断这些现象跟反馈有关，称为反馈噪声，而且正是反馈噪声与湍流噪声的相互作用，导致这种锯齿现象和射流上游的宽频尖峰。     

K-DDoS-SDN: A distributed DDoS attacks detection approach for protecting SDN environment

Software-defined networking (SDN) is an advanced networking paradigm that decouples forwarding control logic from the data plane. Therefore, it provides a loosely-coupled architecture between the control and data plane. This separation provides flexibility in the SDN environment for addressing any transformations. Further, it delivers a centralized way of managing networks due to control logic embedded in the SDN controller. However, this advanced networking paradigm has been facing several security issues, such as topology spoofing, exhausting bandwidth, flow table updating, and distributed denial of service (DDoS) attacks. A DDoS attack is one of the most powerful menaces to the SDN environment. Further, the central data controller of SDN becomes the primary target of DDoS attacks. In this article, we propose a Kafka-based distributed DDoS attacks detection approach for protecting the SDN environment named K-DDoS-SDN. The K-DDoS-SDN consists of two modules: (i) Network traffic classification (NTClassification) module and (ii) Network traffic storage (NTStorage) module. The NTClassification module is the detection approach designed using scalable H2O ML techniques in a distributed manner and deployed an efficient model on the two-nodes Kafka Streams cluster to classify incoming network traces in real-time. The NTStorage module collects raw packets, network flows, and 21 essential attributes and then systematically stores them in the HDFS to re-train existing models. The proposed K-DDoS-SDN designed and evaluated using the recent and publically available CICDDoS2019 dataset. The average classification accuracy of the proposed distributed K-DDoS-SDN for classifying network traces into legitimate and one of the most popular attacks, such as DDoS_UDP is 99.22%. Further, the outcomes demonstrate that proposed distributed K-DDoS-SDN classifies traffic traces into five categories with at least 81% classification accuracy.     

凝胶汽油双股撞击式雾化速度场实验研究

为研究凝胶剂含量、撞击角以及喷射压力等参数对凝胶汽油双股撞击式雾化速度场的影响,实验室制备了凝胶剂含量分别为4%和5%的QNJ-4、QNJ-5凝胶汽油样品。利用旋转式流变仪分别对QNJ-4、QNJ-5凝胶汽油的表观粘度进行了测量,并拟合了反映其表观粘度变化的幂率公式。采用粒子图像速度仪测量了撞击角θ分别为60°、75°、90°、105°和120°,喷射压力p为0.5 MPa、 0.75 MPa、1.0 MPa和1.25 MPa条件下双股撞击式雾化流场的速度分布。结果表明：凝胶剂含量越高,反映凝胶汽油表观粘度变化的幂率公式中,粘度系数k越大,流动指数n越小;凝胶剂含量越高,凝胶汽油撞击雾化后的液滴速度越小;在撞击点下游,中心轴线上的液滴速度v_l沿轴线呈总体下降的趋势,但由于撞击点产生的不稳定波的作用,液滴速度v_l会出现波动;随着撞击角的不断增大,凝胶液滴的核心速度v_c不断减小,但在撞击角为105°会出现暂时增大;随着喷射压力的增大,凝胶汽油雾化后的核心速度v_c不断增大,但增大幅度越来越小。     

Effect of the milling process on quality characteristics of rye flour

BACKGROUND: Most of rye flour is obtained by a gradual reduction system using roller flour mills, which generate different flour streams. The study of the different flour streams composition is necessary since it determines the flour quality and the flour uses. Four break streams and nine reduction streams were analysed for moisture, ash, starch, protein, damaged starch, falling number, amylose/amylopectin ratio, β‐glucans and colour. Mixing and pasting properties were also determined with a doughLAB and a Rapid Visco Analyser respectively. RESULTS: As the milling process advanced, moisture and starch content decreased but protein, ash, β‐glucans and damaged starch increased. The differences in composition are probably related to the effect of the roller mills and the increase in the contamination with bran. The absorption, development time, and pasting viscosity increased as the milling proceeded, in detriment of the peak time. The β‐glucan content was positively correlated to absorption, mixing tolerance index and pasting viscosity, and negatively correlated to peak time. CONCLUSION: Differences in composition, above all, in bran, showed different mixing and pasting properties in rye streams. The most different streams corresponded to the last streams in the break process, in the sizings and in the middlings. Copyright © 2008 Society of Chemical Industry