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.%) alloy sheet under the conditions of 940~1000℃ and 5.5×10-5s-1~1.7×10-3s-1 were studied.
Summary 1.
References [1] J.W.
Metals. 20(s.1)(2010)s336-341
Bampton, Evolution of microstructure and superplastic deformation mechanism in super α2 Ti3Al base alloys, Acta Mater. 46(2)(1998)465-479

From a plot of 1/qe vs 1/Ce, the Q0 and b can be obtained from its slope and intercept.
The slope 1/n is a measure of the adsorption intensity.
Table 3 Kinetic parameters B2 (h-1) Di(cm-1/h) kf(cm/min) ks(cm·g/mL·min) kfav((h-1) H(mL/g) ksavH(h-1) Kf·av (h-1) Kf (cm/min) 1.276 3.231×10-4 16.6 1.78×10-4 29880 8729 2796.8 2557.4 1.42 Treatment of tannery wastewater.
References [1] Lee T., Lim H., Lee Y., Park J.
-W., Use of waste iron metal for removal of Cr(VI) from water, Chemosphere, 53 (2003) 479-485 [2] Alguacil F.

Figures of 0, 1, 2 and 3 respectively represent percentages of different elements, with the margin made up with copper and other ingredients unchanged. 4 groups of tests were carried out with the data shown below: Group 1: Design of carcass recipe conducted with the orthogonal table (in Table 1) Table 1 Test results of Group 1 1-Factors;2-Level;3-No.Range Factors Level No.
483.4 476.6 409.4 499.4 523.6 545.2 464.2 440.4 467 512.2 527 495.2 411 473.6 499.8 532.8 524.6 Range 72.8 135.8 86.6 121.8 Group 2: (test results shown in Table 2) Table 2 Test results of Group 2 1-Metal;2-Content;3-Temperature Metal Content Temperature Cu (%) Sn (%) Ni (%) Cr (%) HRB σ (Mpa) 710 84 8 6 2 50 519.5 710 82 8 8 2 56.6 479 780 83 6 8 3 58.1 551 710 79 8 10 3 67.9 493.7 780 82 10 6 2 59.4 555.6 Group 3: (Test results shown in Table 3) Table 3 Test results of Group 3 1-Elements;2-Level;3-No.
Table 5 shows only No.1 and No.5 had coordinated hardness and strength.
In the recipe of Group 1, we added Fe content of 10%, 15%, 20% and 25% respectively.
We carried out 1 group with the iron content the same iron as that of Group 1, and adjusted Sn:Ni:Cr into 8:10:2.

Fig. 1 shows the XRD spectra for TiO2 (as)/ZnO thin films.
The intensity of the thin films show TiO2 appear with anatase phase at typical peaks around 2θ = 25.3, which are attributed to the (1 0 1) plane matched with the JCPDS file (00-021-1272) and ZnO appear with zincite phase at 2θ = 31.8, 34.3, 36.3, 47.5, 56.6, 62.9, 66.4, 68, 69.1 which are attributed to the (1 0 0), (0 0 2), (1 0 1), (1 0 2), (1 1 0), (1 0 3), (2 0 0), (1 1 2) and (2 0 1) planes, respectively matched with the JCPDS file (00-036-1451).
Fig. 2(c) show the bilayer TiO2 (400oC)/ZnO calcined at 600 oC appear with anatase phase at 2θ = 25.3, 37.9, and 53.9 which are attributed to (1 0 1), (0 0 4), (1 0 5) planes.
References [1] J.
Sci. 351 (2015) 474-479 [5] L.J.

Table 1 Major physic-chemical properties of the unamended soil, the fly ash and steel slag Unit Test items Soil FA SS 1 pH 4.0 13 13 (mg kg-1) Available Si (Si) 90 4430 9790 Olsen P (P) 50 1020 989 Cd 10 0.41 < 0.01 Zn 329 83 25 Cu 479 39 14 Pb 946 37 16 (g kg-1) Ca 1.1 69 248 Mg 3.3 1.9 35 Fe 86 12 101 Al 60 2.6 5.5 Results and Discussion The Characteristics of the Soil and Amendments.
The concentrations of available Si were 4430 mg·kg-1 and 9790 mg·kg-1, and the available P concentrations were 1020 mg·kg-1 and 989 mg·kg-1 in FA and SS, respectively.
The Cd concentration was 14 ng·kg-1 in control, and the amount decreased by 77% and 50% in addition of 10 g·kg-1 FA and 1 g·kg-1 SS treatments, respectively.
The concentration of available Cd was lower than the detection limit (0.5 ng·kg-1) in the treatment of FA added at 60 g·kg-1, and the amount was only 0.65 ng·kg-1 in the treatment of SS added at 8 g·kg-1.
The Zn concentration was 5.5 mg·kg-1 in control, and the amount decreased by 72% and 63% in treatments with 10 g·kg-1 FA and 1 g·kg-1 SS, respectively.

Fig. 1 Experimental set up for end milling Kistler Rotating Cutting Force Dynamometer was used for measuring cutting forces.
Type Coding of Level Cutting Forces (N) x1 x2 x3 Cutting speed, m/min Axial Depth of cut, mm Feed, mm/tooth 1 Factorial 1 1 -1 410 2 Factorial 1 -1 1 605 3 Factorial -1 1 1 889 4 Factorial -1 -1 -1 342 5 Centre 0 0 0 500 6 Centre 0 0 0 503 7 Centre 0 0 0 503 8 Centre 0 0 0 502 9 Centre 0 0 0 503 10 Axial -1.414 0 0 515 11 Axial 1.414 0 0 450 12 Axial 0 -1.414 0 415 13 Axial 0 1.414 0 652 14 Axial 0 0 -1.414 325 15 Axial 0 0 1.414 905 In the experiment, small central composite design was used to develop the tangential cutting force model.
Table 4 ANOVA for second order CCD model Source Sum of Squares DF Mean Square F Value Prob > F Block 6.75E-05 1 6.75E-05 Model 1.196514 8 0.149564 15826.31 < 0.0001 Significant x1 0.019437 1 0.019437 2056.719 < 0.0001 x2 0.102046 1 0.102046 10798.14 < 0.0001 x3 0.5244 1 0.5244 55490.01 < 0.0001 x12 0.002589 1 0.002589 273.9307 < 0.0001 X22 0.003045 1 0.003045 322.1804 < 0.0001 x32 0.012612 1 0.012612 1334.583 < 0.0001 x1 x2 0.001351 1 0.001351 142.9317 < 0.0001 x2 x3 0.00066 1 0.00066 69.86719 0.0004 Residual 4.73E-05 5 9.45E-06 Lack of Fit 2.02E-05 1 2.02E-05 2.991322 0.1588 Non-significant Pure Error 2.7E-05 4 6.76E-06 Cor Total 1.196629 14 The quadratic CCD model shows that feed has the most significant effect on tangential cutting force, followed by axial depth of cut and cutting speed.
References [1] X.P.
Tools Manuf. 31 (4) (1991) 471–479

Total 400 group 9d (8d IMF component C1 ~ C8 and 1d surplus R) normalized energy as a sample characteristic vectors show in fig.1
Table 2 SVM binary classification and recognition results of bearing normal and fault kernel function category c g training sample test sample erroneous judgement classification accuracy linear kernel 1 1 200 group 9d 200 group 9d 0 group 100% polynomial kernel 1 1 200 group 9d 200 group 9d 0 group 100% RBF kernel 1 1 200 group 9d 200 group 9d 18 groups 91.0% Sigmoid kernel 1 1 200 group 9d 200 group 9d 50 groups 75.0% Compared high dimension large sample in table 2 with low dimensional small sample in table 1,SVM based on linear kernel function and polynomial kernel function is the same results.The classification accuracy using RBF kernel function and Sigmoid nuclear the function slightly less at low dimensional small sample.But there is no obvious difference at low dimensional small sample compared to high dimensional large sample.It shows that combination improved EEMD with SVM can realize the low dimensional small sample of correct fault diagnosis.
References [1] Hwi Li,Xiaofeng Liu and Lin Bo.
Advances in Adaptive Data Analysis，Vol.1(2009),p1-41 [5] Meijun Zhang,Sichen Han,Chuang Wang and Shuguang Li.
Journal of Advanced Materials Research.Vol. 479-481(2012) , p1180-1185 [6] Zhang Meijun ,Chen Hao , Cao Qin and Chuang Wang .

In Fig. 1.
References [1] N.
Contr., Vol. 107 (1985) No. 1, pp.1-24
IEEE/RSJ International Workshop on Intelligent Robots and Systems (Tsukuba, Japan, September 4-6, 1989). pp. 479-485
Vol.1, pp.186-191

For discussion, we assume that the pixel gray scale values have been normalized in the interval [0,1], r = 0 means black, r = 1 means white in the gray level coordinates.
Any one of the r-value within the interval [0,1] transforms by transformation function (5) T (r) meets two conditions: (1) single-valued monotonically increasing function; (2) 0 ≤ T (r) ≤ 1.The order of the gray level from black to white is kept in condition (1) and the condition (2) ensures that the mapping transformation pixel gray value within the allowable range.
References [1] Yue Z Q, Morin I.
Canadian Journal of civil Engineering, 1996, 23: 479~489
Cement& Concrete Research,1999, 29:1 403~1 401

When m-NpSB was spread on the pure water surface, a phase transition was clearly observed at 12.9 mN·m-1 or 0.56 nm2·molecule-1.
On the other hand, the extrapolating area of Cu-m-NpSB isotherm was 0.30 nm2·molecule-1 while that of the ligand on the 1.0 mmol∙L-1 Cu(Ac)2 surface was 0.35 nm2·molecule-1.
Fig. 1.
References [1] G.L.
Liu: Thin Solid Films Vol. 479 (2005), p. 269