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Pseudo-second-order models fitted the experimental data well and kinetic parameters, rate constants, equilibrium sorption capacity and related correlation coefficients at various temperatures were calculated and discussed.
Current technologies utilized for the removal of heavy metals from water include chemical precipitation[4], ion exchange[5], flotation[6], electrochemical reduction[7], and membrane separation [8].
The adsorption isotherm data were further analyzed in terms of the Langmuir isotherm model.
Various parameters are calculated from Langmuir isotherm models and in all cases, high regression coefficient values of R2 > 0.99 were obtained, suggesting that Langmuir isotherms fitted well for the experimental data[16].
Shen, J Chem Eng Data Vol. 56(2011), p.444 [10] I.

Managerial decision-making process being environmentally friendly is based on experimental data.
This conclusion is supported by analytical data, which indicate that car wash wastewater is a significant source of environmental pollution due to the diversity and high concentration of pollutants contained in it.
Complex indicators are calculated by integrating heterogeneous data that comprehensively characterize the analyzed process.
Table 1 shows the initial data for calculating the prevented damage from the discharge of detergent solutions after car washing into surface water bodies.
This leads to a targeted reduction of environmental costs by enterprises.

Secondly, in different areas out of net the change regularity of extrapolation error is further discussed with types of data in different length baselines.
Therefore, in this paper based on the traditional interpolation model, from the characteristic of mathematical model and example data, the extrapolation accuracy in different areas outside the net will be analyzed in detail.
We select simultaneous observation data of nearly 20 minutes (sampling rate is 1 sec) from these reference stations, and then use GPS processing software with high precision to calculate the double-differential integer ambiguity of every baseline.
During the observation period the extrapolation accuracy is decreasing as the reduction of the satellite’s altitude angle.
According to the analysis from error propagation law and example data it shows that for the CIM, the extrapolation accuracy is decreasing with the increase of the distance away from the net, however, it can be reached within 5 cm in the areas that not more than 40km to the net external.

The OA-based model building procedure can be summarized in the following steps: (i) Collect data to train and verify the models.
To obtain good modeling results, a large quantity of data is advantageous and the observations should cover a sampling space as wide as possible.
The modeling design of experiments reveals that an accurate relationships for dsx, dsz, and esy prediction can be achieved using a three layers ANN model and shows that all models fitted the training and validation data relatively well as indicated by the MSE values.
For the sake of comparison, all the MSE values were calculated using normalized data.
Hunter: Statistics for experimenters - An introduction to design, data analysis, and model building, John Wiley & Sons (1978).

The redial stiffness of the bearings was found according to bearing specifications presented in Table 2, by using the following experiential formula [4]: (8) Where CA is empirical data defined based on the experimental results.
In design optimization, the DOE can be used to fit the simulated response data to mathematical equations.
A grid of data arguments of minimum density through the multivariable design planetary is often used instead.
The predicted three candidates’ points are summarized in Table 4 by comparing to its original data.
It can be seen that when minimizes the structural weigh Mw the FONF has been increased as result of inertia forces effects reduction.

From the design point of view, fatigue properties of welded structure such as fatigue crack growth data (da/dN) should be determined accurately so that design life of welded structures can be correctly estimated.
Table 1 Tensile test data of welded joints Property Welding process Base Metal GTAW EBW FSW Yield Strength, [MPa] 390 220 265 305 Ultimate Tensile Strength [MPa] 470 242 304 342 Elongation [%] 15 8.8 10.4 12.2 Reduction in Area [%] 10.5 6.2 7.5 8.6 Weld efficiency[ %] - 51 64 72 Table 2 Fatigue test data of welded joints Welding process Fatigue strength (at 2x106 cycles) [MPa] Un notched Notched Base Metal 200 110 GTAW 110 50 EBW 150 55 FSW 180 80 Table 3 Fatigue crack growth test data of welded joints Welding process Crack growth exponent, m Intercept C 10-8 ∆Kth [MPa.m½] ∆Kcr [MPa.m½] Base Metal 2.85 2.44 4 30 GTAW 4.10 3.40 2.3 10 EBW 3.76 3.98 2.5 12 FSW 3.57 1.68 3 20 Fig. 4 Effect of tool rotation speed and tool travel speed on FCG rate of FS welded joint.
a b Fig. 5 Fatigue crack propagation data of 2024-T3 starting from different distances to plate joint line (PJL), (a) perpendicular to the PJL, (b) parallel to PJL.
The results indicate a significant reduction in fatigue crack growth rates using laser peening compared to shot peening and native welded specimens, Fig. 10.
Although a substantial data is available for effect of different treatments on mechanical properties in friction stir welded aluminum 2xxx alloys, a great deal of research is still necessary to evaluate the effects exerted by the post weld treatments on the fatigue crack growth phenomena of the joints.

l Automatic acquisition and storage of data.
l Security administration of data & system.
Massive data can be used for common prediction due to the wide range of Logistics.
The user can either input add, cancel, refresh and search for data available in data base with the aid of data base management system, or process data by system user interface then save data operation simultaneously in data base while reentering is necessary if there is no relevant data for new project.
LMIS has not only reduced data processing workload of system user but also guaranteed the uniformity of data used for prediction by pre-processing and analyzing original data assisted by data mining technology.

MMX technology adds eight 64-bit registers (MM0-MM7) of 57 new instructions in the processor, a plurality of 8/16/32 bit integer data integration into a 64-bit data.
IF input intermediate frequency sampling data, the local carrier and local pseudo-code, are 8 bit quantitative data.
Therefore, this article USES the method is that before the eight multiplication, the extension of the 8 bits of data into 16 the sign bit, concrete is before 8 bits of data to add 8 0 or 1, the same as the data of the sign bit, as shown in table 1.Data expanded, although the wasted storage space, but guarantee the application and multiplication of 16 multiplication instructions after only low 16-bit result does not overflow.
Table 1 8-bit signed extended to 16 High 8 Low 8 With the same sign sample data After expansion in Table 1, the multiplication of inputs A, B are into 16 data, MMX registers 64, each register can be loaded into the four sampled data; sampled data bit actual calculation of the number of CNT.
Because 16-bit 32-bit multiplication result, only keep a low 16 results also removes unwanted high 16 data.

In order to minimise the average error over all data points for an nth order approximation, the method of least squares is used to obtain the values of Ai.
Figure 2.- Mechanical properties stainless steel AISI 316L a) Bending test data used to obtain the stress-strain curve. b) AISI 316L stress-strain curve.
The relaxation will produce strain data, which can be used by the CCM to determine the acting residual stress field.
The numerical data obtained will facilitate the experimental procedure for the induction of residual stress fields and the application to the CCM.
Significant data has been obtained for the experimental procedure of the CCM and the proper manner to establish its application.

To determine the process efficiency of the filter device, a multiparameter water quality analyzer and a data transmission system were established, which showed the efficient process even at a large distance, as well as the good operational status of the filter device.
The following results were obtained: 1) The pelletized fibrous filter in a high-rate filtering device was shown to be very effective in removing TSS due to its irregular internal structure. 2) The efficiency of the filtering device was 7.16 and 97.9% for TSS, 11.5 and 53.1% for CODMn, 21.7% for T-N, and 31.6% for T-P. 3) The increase in the amount of the influent to be processed in a high-rate filtering device is proportional to the reduction of the process efficiency.