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Figure 1 reports the weight gain data over time.
(Full markers) experimental data; (open markers) data corrected with Cr-evaporation; (solid line) calculated values from kinetic model.
The parabolic rate constant obtained from the weight gain data is 9.42 ×10-14 g2cm-4s-1 and agrees with those calculated from literature data [6].
Calculated data.
Corrected data.

Experimental evaluations using scan data or noise data demonstrate the efficiency of the proposed method.
First a triangular mesh is created which reflects the basic topology of the final model and remains a preferred representation for surface data because of its ability to approximated complex shapes and visualization efficiency.
Given n data points, = 1,…,on a d-dimensional space,the multivariate kernel density estimate obtained with kernel functionand bandwidth h is
When the weight of the smallest edge is larger than a given threshold, this graph reduction ends.
(b) Pocket The noise contaminated in the data may come from measurement and form error.

The outcomes agree well with the in-situ observation data and the indoor experiment data, which verifies the feasibility of modeling the sinking process of open caissons using PFC and further studying their soil-structure interaction mechanisms from the microscopic prospect.
At present, the working conditions of open caissons are usually studied with semi-empirical theoretical analytical method, in-situ observation data analysis, indoor model test, and numerical simulation, and the sidewall pressure is important to open caisson design and is of interest to the geotechnical engineering community.
It can be seen that sidewall pressure firstly increases almost linearly, then fluctuates in a certain range of depth, after that it starts to decrease gradually with the reduction of sidewall elevation.
The above characteristics agree well with the in-site observation data [7-8].
(2) The variations of the side pressure of the PFC simulation agree well with the in situ observation data and indoor experiment data, which indicate that PFC can offer a new approach to further study the interaction mechanism between open caisson and soils from the microscopic prospect.

Study on the Extraction of the Water Bodies from Remote Sensing Image Using ENVI Software—Applied to the River Environmental Protection in Qinzhou Weirong QIN Qinzhou University, Qinzhou, Guangxi 535000, China Keywords: Maximum; Likelihood; Data Mining; Classification; Water Abstract.
Extracting the main water body of remote sensing image with the maximum likelihood algorithm of ENVI software based on Qinzhou's remote sensing images 2008 and 2011, and also analyzing the water body overview of Qinzhou Fig.1.Remote sensing image of Qinbeifang Fig.2.The combination of 543 wave bands of Qinzhou's remote sensing image in 2008: Purple-urban area of Qinzhou; Blue-drainage Fig.3.The latest remote sensing image by Google earth in 2003 Fig.4.A remote sensing image in 2008, which is a drainage remote sensing image classified with the maximum likelihood classification of ENVI software in recent years: blue-water body; red-urban area; green-others Fig.5.A remote sensing image of Qinzhou in 2011 Fig.6.A Qinzhou's drainage remote sensing image classified with the maximum likelihood classification of ENVI software in 2011: blue-water body; red-urban area; green-forest; yellow-others Fig.7.The remote sensing data of extracted water body in 2008 and 2011
Figure 5 and figure 6 are included in the processed data statistics after classified by ENVI software, and then the numerical values of blue water are compared (P5water is the pixels of the water body in figure 5, and p6water is the pixels of the water body in figure 6).
Reasons for the reduction of water bodies in Qinzhou Too fast increasing planting area of fast-growing eucalyptus The advantages of fast-growing eucalyptus include fast growth speed, and high economic benefit.

With the data obtained from these tests and in order to analyze the results obtained from the models, a methodology based on four points is proposed: First, the uncertainty of the dataset obtained from the DoE is analyzed in order to evaluate to which degree the experimental data define the problem.
Third, the accuracy of the generated models is checked using an additional — previously unused — set of data.
Finally, the best models obtained for each machine learning technique are tested and compared to actual data to assess the accuracy are the models.
Prior to generating the regression models, the data obtained from the DoE was normalized between 0 and 1 to improve the quality of these models.
Hall, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, Elsevier Inc, 2011.

Data was analyzed by using Spss data processing software, and the correlation coefficient matrix between the feeling of wearing Introduction As the knitted fabric has good elasticity and extensibility, the kinds of fabric has been used for more and more types of tight and sports garment.
Physiological data were measured including height, thigh, waist and hip circumferences, knee circumference.
The physiological data are shown in table 2.
After the wearing state, according to table 3, tester assessed the clothing pressure comfort and other related feeling in the range of values within 1-5, and the corresponding records were made by the experimenter in the wearing pressure comfort subjective assessment questionnaire calculated subjective evaluation data of each wearer, and a total of 80 group wearing sensation value were achieved. data was analyzed by using Spss data processing software, and the correlation coefficient matrix between the feeling of wearing sstretch pants were obtained.
Results and discussion After the subjective evaluation experiment ended, we The correlation coefficient is a quantity to show how close the relationship is between two experimental data, usually represented by the letter R.

To illustrate differences and similarities, some characteristic data are shown in table I.
The data might be too rough an approach, but they indicate some clear hint that there is not much room for luxury in case of the PV manufacturing processes.
The data are a rough indicator for strict constraints in the PV cleaning processes.
A significant reduction of the initial Fe and Cu contamination seems to be possible.
Some data indicate that these levels may be in the range of 10 ppb to some 10 ppb.

The COE data are in the range of 12.43 x 10-6 - 14.35 x 10-6 °C-1 which is consistent with another soft silicate glass [11].
All samples were also analyzed by IR spectroscopy and the data were analyzed according to the previous literatures [12-13].
The quantity of Cu+ and Cu2+ in the glass sample can be calculated using the empirical edge shift (data from Table 3) as shown in Eq.1 and Eq.2 [15]: % of Cu+ = (1) % of Cu2+ = (2) While the average oxidation state of copper ion in the glass matrix can be determined as follows: Copper oxidation state = + (3) From the calculations, valence state of Cu according to the edge energy shift position for each glass sample was obtained as data in Table 4.
Table 4 Calculated valence state of Cu according to the edge energy shift positions Sample ∆E of sample (eV) ∆E of Cu2+ and Cu+ (eV) Cu oxidation state %Cu+ %Cu2+ Cu(1) 1.28 3.63 1.35 64.74 35.26 Cu(2) 1.19 3.63 1.33 67.22 32.78 Cu(3) 0.99 3.63 1.27 72.73 27.27 Cu(4) 0.98 3.63 1.27 73.00 27.00 The appearance of Cu+ in Cu(1) might come from the oxide in the melt causing the reduction of Cu2+ to Cu+ in Cu(1) as presented in Eq. 4 [16]. 4Cu2+ + 2O2- 4Cu+ + O2 (4) While in the case of Cu(2), Cu(3) and Cu(4), the reduction by oxide as in Eq. 4 and by aluminum as in Eq. 5 might occur. 3Cu2+ + Al 3Cu+ + Al3+ (5) However aluminum can be reacted with oxygen from the air or in the melt as in Eq. 6 [17]. 4Al + 3O2 2Al2O3 (6)
Newville, ATHENA, ARTEMIS, HEPHAESTUS: data analysis for X-ray absorption spectroscopy using IFEFFIT, J.

There is not enough data about the chip formation during the machining of composite materials produced by powder extrusion method.
First, the friction angle β is found by substituting the experimental data for the cutting force () and the axial force () in Eq. 2.
Consequently, the experimental cutting forces data and the cutting forces that are calculated according to Merchant and Lee-Shafer models are compared with each other. 3-1-1.
This means that the data of these models compared with the experimental data are underestimated.
Third reason for reduction of cutting forces can be the thermal softening of the aluminum matrix, which occurs with increasing cutting temperature.

Experimental data (points) are compared to the theoretical MH model (dashes) and to the quenched MH model (solid lines).
Experimental data (points) are compared to the theoretical MH model (dashes) and to the proposed model (solid lines).
Surface diffusivity coefficient of crystal silicon (100) obtained from the rapid thermal annealing (RTA) experiment compared with literature data [4,6,9-11].
It shows an excellent agreement with most of the literature data obtained from the measurements of the transformation of the shape of periodic superficial silicon structures.
Their experimental data are obtained on the structures with high aspect ratio (high local curvature) where MH approximation could give significant errors (see numerical analysis of the limits of MH approximation in [10]).