Authors: Bai Hua Wang, Xiang Guo, Zhi Yu Hu, Li Ping Kong, Bao Guo Zhang
Abstract: In this study, the image definition of animal fibers captured by Axioskop 2 MOT PLUS differential interference contrast (DIC) light microscope using 1-bromonaphthalene, diethylene glycol, n-decyl alcohol, and ethylene glycol monomethyl ether as embedding medium, respectively, is compared with the image definition obtained using paraffin wax, the reference embedding medium. The effects of the four kinds of embedding media on the image definition of camel cashmere, yak cashmere, wool, and cashmere are also analyzed. Results show that topographical feature, scale structure, and pigmentation are better visualized when n-decyl alcohol is used as embedding medium compared to when the other kinds of embedding media are used. This meets the requirement of computer image analysis method for the identification of camel cashmereand yak cashmere fibers. Furthermore, the image definition of wool and cashmere is clearly improved when n-decyl alcohol is used as the embedding medium compared to when paraffin wax is used in the same condition.
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Authors: Cheng An Tao, Jian Fang Wang, Yin Long, Ya Nan Lv, Guang Tao Li
Abstract: Scattering spheres-embedding three-dimensional ordered macroporous (3DOM) titania(TiO2) was fabricated, by the route of colloidal spheres self-assembly, infiltration and template removal. The procedures of 3DOM structure preparation were characterized by transmission electron microscope (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD). The silica@PMMA core-shell spheres were prepared and self-assembled into colloidal crystal template. Solid material was deposited in the colloidal crystal template by spin-coating of titania nanoparticle dispersions. Subsequently, the samples were heated to 400 °C to form anatase TiO2 and to remove the polymer of template, which resulted in macroporous structure with a silica sphere in each lattice pore. The conventional TiO2 film, 3DOM TiO2 photoanodes were also fabricated. It was found that SiO2-embedding 3DOM photoanode has the higher photocurrent efficiency than both of TiO2 film and 3DOM, because there are scattering spheres in its lattice pores which enhance the light scattering and improve the light harvest of the dye.
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Authors: Predescu Cristian, Vasile Eugeniu, Predescu Andra Mihaela, Sohaciu Mirela Gabriela, Berbecaru Andrei Constantin
Abstract: The paper presents the results of the investigations made on cast pieces consisting of aluminium with Si and Mg mixed metals, in order to establish the nature of the embeddings and the causes that led to their appearance.
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Authors: Ying Ying Su, Fei Ma, Hai Yan Zhang, Zhi Qiang Liao, Peng Jun
Abstract: The forecasting precision of short-term wind speed is not high for its chaos and time-varying. Aimed at the problem, the novel data space is reconstructed with the best embedding dimension and time delay according to the phase space reconstruction. On the basis, neural network (NN) is used as the modeling tool with the novel sample data. Meanwhile, the structure of NN is confirmed compared with the others on the precision. In the end, the model of short-term wind speed is able to be obtained. The results show that the method is available and the Mean absolute error (MAE) is decreased to 16.2% for 2 hours.
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Authors: Zheng Qiang Li, Peng Nie, Shu Guo Zhao
Abstract: Aiming at the nonlinear characteristics of the tool wear Acoustic Emission signal, tool wear state identification method is proposed based on local linear embedding and vector machine supported. The local linear embedding algorithm makes high dimensional information down to low dimension feature space through commutation, and thus to compress the data for highlighting signal features. This algorithm well compensates for the weakness of linear dimension reduction failing to find datasets nonlinear structure. In this paper, acoustic emission signal is firstly made by phase space reconstruction. Using local linear embedding method, the high dimension space mapping data points are reflected into low-dimensional space corresponding data points, then extracting tool wear state characteristics, and using vector machine supported classifier to identify classification of the tool wear conditions. Experimental results show that this method is used for the exact recognition of the tool wear state, and has widespread tendency.
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