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.     

Use of heat-moisture treated maize starch to modify the properties of wheat flour and the quality of noodles

Waxy, normal and high-amylose maize starches were subjected to heat-moisture treatment (HMT) and then added to wheat flour (WF) in different ratios (1%, 5% and 10%). The properties of blends and their cooked noodles were studied to investigate the effects of HMT starches. The incorporation of HMT starch in WF led to an increase in swelling power, peak viscosity and breakdown and to a decrease in setback, thus inhibiting retrogradation, hence enhancing resultant noodle softness. Compared to the same addition ratio of native starch to WF, HMT starch led to higher tensile strength and extensibility in resultant noodles. WF with added HMT starch had higher resistant starch than with native starch. This study showed that addition of HMT maize starch has potential to bring nutritional benefits. However, it is necessary to select the proper blending ratio and amylose content of starch to add, in consideration of its effect on noodle quality.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Low-temperature synthesis of SiC nanowires with Ni catalyst

SiC nano wires were fabricated on the silicon substrate dipped with a layer of Ni catalyst at 900 ℃ by gas pressure annealing processing. The morphologies and crystal structures were determined by scanning electron microscopy(SEM), transmission electron microscopy(TEM)and X-ray diffraction(XRD). The results show that the assynthesized nanowires are β-SiC single crystalline with diameter range of 50-100 nm, and length of tens of micron by directly annealing at 900 ℃. The SiC nano wires grow along the [111] direction with highly uniform morphology. And the possible growth mechanism of SiC nano wires is proposed.The present work provides an efficient strategy for the production of high-quality SiC nano wires.     

气藏型储气库注气期试井分析探讨

针对气藏型储气库注采井注采过程中储层物性参数影响因素不明确、注采能力不对称的问题。基于相国寺储气库井下连续油管试井测试结果,提出储气库注气期“温降效应”、“变表皮效应”的概念,分析了储气库注采过程中温降效应、变表皮效应以及储层应力敏感对注采的影响。通过气藏型储气库注气期试井分析技术,研究各因素在试井曲线上的响应特征以及对试井解释参数的影响。结果表明:①相对于采气期试井测试,注气期测试得到的储层物性参数具有同样的参考价值;②储气库温降效应对于试井解释结果的影响可忽略不计,而在不同注采运行周期内,变表皮效应以及应力敏感效应影响差异较大;③编制储气库注采运行方案时应充分考虑变表皮效应与应力敏感的影响,在不同注采运行周期内开展试井测试获取准确的储层参数值。研究成果为储气库试井测试与解释提供了重要的研究依据和理论指导。     

Fabrication and characterizations of Cr3+-doped ZnGa2O4 transparent ceramics with persistent luminescence

0.5 at.% Cr:ZnGa₂O₄ precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa₂O₄ powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa₂O₄ ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa₂O₄ ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa₂O₄ ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa₂O₄ transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m² after 30 min, which is far superior to that of Cr:ZnGa₂O₄ persistent luminescence powders.     

30Cr13不锈钢冶炼过程夹杂物控制技术

  针对30Cr13生产过程中存在的轧材非金属夹杂物合格率偏低仅85%左右的问题，通过对30Cr13不锈钢精炼过程钢中非金属夹杂物存在形态进行分析，并结合现有精炼工艺制度，在实验室研究的基础上制定了不锈钢精炼过程非金属夹杂物控制方案。工业应用后，精炼结束钢中大于5 μm的非金属夹杂物总数、形状以及尺寸等参数均得到了有效改善，钢水洁净度大大提高。