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Special joints are characterised by easy execution, treatments and machining reduction and a significant reduction of construction costs.
Results obtained indicate that experimental data for the specimens investigated and exposed to the test solution for the same time are almost overlapping.
Figure 5: PD tests comparison between AA6005A-T6 and Cold sprayed aluminium AC electrochemical tests carried out on bare AA6005A-T6 and cold sprayed pure aluminium, further support the DC data as shown in Figure 6 and figure 7, respectively.
The high stability of data observed at medium frequency further suggests the high stability of the deposited layer.
Comparing the results of EIS tests performed on bare and sprayed AA 6005A-T6, it is clear that the impedance modulus and the capacitance of the repaired specimen are higher than those exhibited by the AA 6005A-T6 by one order of magnitude supporting the DC data on the expected increase of service life.

For example, Shen Jing proposed the rough set attribute reduction model.
With the equipment at hand, we need to have true and accurate monitoring data to complete the supervision of enterprises, especially the seriously-polluted ones.
The collected data should be timely feedback to the local monitoring stations for processing.
Of course, to do real-time data collection and processing is not an easy thing.
However, we should try to understand that only by doing so can we get convincing data and take effective restrictions on the enterprises.

Methodology Data and Model specification.
Data sources were from BP Statistical Review of World Energy 2011 [12], Taiwan Tourism Bureau [13] and Taiwan Directorate-General of budget, Accounting and Statistics [1].
Energy consumption data are expressed in million tonnes of Oil Equivalent.
The analysis in this study utilized annual time series data for the period 1965-2010.
Since neither number of visitor nor visitor expenditure is associated with real GDP, the constraint in number of visitors may be considered as one of appropriate strategies for the reduction of energy consumption but not to harm the tourism development.

Introduction Telecommunications network fault diagnosis system when received the massive network the original events, the need for its reduction, and fault diagnosis will filter out unrelated events, for the purpose of reducing the number of alarms which will be processed in the process of fault diagnosis.
Even after the original events reduction, but still very large amount of alarm, nor are the root causes of failure, the need for further diagnosis of these alarms to determine the root cause of the alarm - fault.
Meanwhile, the paper also tests the reasoning part of the process and gets some intermediate data, and the number of actual failures have been confirmed by network maintenance staff.
All the data as shown in Table 2: Table 2 Efficiency of Results verification method Number of alarms Faults before verification Faults after verification Confirmed faults False faults 10000 39 31 27 4 According to the data in Table 2, we can see through the results verification step, a decrease of 8 false faults and reduce the false faults rate of 8/27 = 29.63%, faults accuracy was improved (27/31-27/39) = 17.87%.
Then according to the characteristics of telecommunications networks, to improve the performance of Bayesian reasoning networks, two improved methods are proposed on the Bayesian networks reasoning, that is narrow range method and pretreatment method, and tested in the current network obtained the experimental data verified the two improved methods to improve the performance of Bayesian reasoning is valid; the same time, The third improvement method, that is results verification method is also verified to improve the accuracy of the Bayesian network reasoning.

However, high optical accuracy and disturbance reduction are required to project high-coherence light.
Figure 5 shows data for a precision steel sphere with 10 mm diameter.
Figure 5(c) shows the data for the cross-sectional shape of the sphere.
The circles denote the experimental data.
However, the processing time will increase owing to the increase in the data for processing.

The quantitative analysis methods mainly include rigid body limit equilibrium method [1], strength reduction method based on FEM theory and strength reduction method based on finite difference theory and so on.
The specific steps are dividing the total variation square sum of the data into the sum for variation square sum of factors and random error square sum, then F-test is carried out, and the significance of factor effects can be obtained. 2 Calculation models of slope and verification for calculation method 2.1 Calculation models In this paper, the assessment question 1 (a) used in Australia slope stability analysis program in 1987 for ACADS is adopted as calculated slope model.
Table 4 Range analysis data of factors Factors level A（/（kg.m-3）） B（C/kP） C（/（°）） 1.026 0.990 0.917 1.007 1.008 1.007 0.990 1.025 1.098 （Range） 0.036 0.035 0.181 In the upper table, is the average value of test results for level 1. 3.3 Variance analysis In order to better study the degree of influence of various factors on the slope stability factor, variance analysis method is performed for the further analysis of slope stability calculation results under the combination of factors.
Table 5 Analysis data of variance Factors level tests number A （/（kg.m-3）） B （C/kP） C （/（°）） Safety factor 1 1 1 1 0.917 2 1 2 2 1.025 3 1 3 3 1.135 4 2 1 2 0.989 5 2 2 3 1.097 6 2 3 1 0.934 7 3 1 3 1.063 8 3 2 1 0.901 9 3 3 2 1.006 3.077 2.969 2.752 3.020 3.023 3.020 2.970 3.075 3.295 Deviations sum 0.00191 0.00187 0.04914 Contribution rate 3.61% 3.53% 92.86% It can be seen from Table 5 that, the deviation sum of the first and the third column are much small, so the results can be incorporated to error estimates, that is The sum of errors deviations The degree of freedom for errors the ratio of the factor C is showed as followed： Given significance level，，it can be obtained by checking the distribution critical values table of F ， For So the results of significance level are： Factor A（bulk density）………………………………………（not significant） Factor B（cohesion force）………………………………………（not significant） Factor C（internal friction angle）………………………（highly significant
Therefore, In the course of engineering survey, special attention must be put on the value of the geotechnical internal friction angle, ensuring that the data provided reflect the actual situation, thus ensuring that the numerical results can be more realistic evaluation of slope stability condition. 2) Variance analysis shows that, when the parameters have the same relative rate of change, the changes of internal friction angle have highly significant impact on slope stability factor, while the changes of bulk density and cohesion force have much lower significant impact on slope stability factor.

While some field data of construction cases revealed that, the lateral displacement of embankment is not always apart from axis of symmetry of embankment, which can close up to axis of symmetry of embankment too, but this phenomena has been neglected as error or unreasonable data, so rarely reported by article or report.
Meanwhile, the stability of embankment at different construction stages can be calculated with shear strength reduction FEM.
In this method the FOS of slope is defined as the shear strength reduction factor by which the origin shear strength parameters must be divided in order to bring the slope to the verge of failure [9].
(3) Inclinometer pipe should be vertically paved to hard layer without lateral displacement, and the work of recording test data is tedious, so error can be generated during this work.

By using a larger average particle size,compared with the use of concrete mixing with fine aggregate, the coarse sand concrete mixingcan be reducedabout 10% ofwater while a corresponding reduction in cement consumption, reduced heat of hydration of cement
In the absence of data which can measuredirectly, it can estimate the heat of hydration of cement [6].
The following calculation is the temperature of concrete surface: concrete virtual height by the formula (3): (3) In formula (3), λ is the thermal conductivity ofconcrete which in this project takes 2.33 w /m.k; k is the reduction factor for the calculation, takes 0.666; β is the insulation layer conductivity which refers withformula (4): (4) In formula (4),δ is the thickness of insulation material; λi is the conductivity of insulation materials, look up table to take it 0.14; βq is the air conductivity, take 23 w/m2.k.
The foundation slab of clinker reservoir which with mass concreteconstructs in mid-September, reference to the weather data of Nan Yang thatthe average of outdoor temperature is 25℃ in September later, so setting the security temperature of the concrete center is 50℃ which temperaturedown to requires about 20 days.
Measured data shows that the maximum temperature of the concrete center is 72.5℃ which appearsin point B.

The author of this paper analyzed a large number of documents and data about active coke desulfurization, and discussed the reasons why does this technology not be used widely on the basis of the economic analysis.
According to the activated coke FGD reaction mechanism, activated coke SO2 adsorption process occurs first, namely, adsorption on active sites, while the temperature rise helps the desorption process, leading to the SO2 reduction on the active sites, and ultimately affects the removal rate.
There will appear broken, particle size reduction in active coke FGD process.
Economic analysis of active coke FGD Here, take the 600 MW units in China as an example, analyzing the two technologies of active coke FGD and limestone-gypsum wet FGD for the total cost and the operation cost per year comparatively [7]: Assuming the content of coal sulfur as 1%, and the coal consumption as 250t/h, running hours cited the data 5000 h from the thermal power engineering quota design index of cost of calculation.
Table 1 Active coke FGD and wet FGD’s Chemical reaction and product yield calculation Input quantity SO2 Chemical reaction and calculation Output the coal consumption 250t/h the content of coal sulfur 1% the coal consumption×the content of coal sulfur 250t/h×1%=2.5t/h coal sulfur 2.5t/h coal sulfur 2.5t/h S + O2 = SO2 2.5 t/h × 80% × 64/32 = 4 t/h (Where S + O2 = SO2 is the reaction equation of sulfur and oxygen in the fired coal, 32 is molecular weight of S, 64 is molecular weight of SO2, 80% is the conversion rate of sulfur in coal combustion, refer to the actual statistic data 80%~ 85%) SO2 generating capacity 4t/h Input quantity wet FGD’s Chemical reaction and calculation Output SO2 generating capacity 4t/h The requirements of CaCO3 8t/h 1） SO2 + H2O → H2SO3 Absorption 2） CaCO3 + H2SO3 → CaSO3 + CO2 + H2O Neutralization 3） CaSO3 + 1/2 O2 → CaSO4 Oxidation 4） CaSO3 + 1/2 H2O → CaSO3•1/2H2O Crystal 5） CaSO4 + 2H2O → CaSO4 •2H2O Crystal 4 t/h × 95 % × 172/64 =

Although the strength of individual CNT shells is extremely high, weak shear interactions between adjacent shells and tubes leads to significant reductions in the effective strength of multi-walled carbon nanotubes and carbon nanotube bundles down to only a few GPa’s.
However, larger-scale defects such as Stone Wales defects cause phonon scattering over a wide range of frequencies, leading to a greater reduction in thermal conductivity [15].
The data are still fragmentary and subject to criticism.
However, available data clearly show that, under some conditions, nanotubes can cross membrane barriers, which suggests that, if raw materials reach the organs, they can induce harmful effects such as inflammatory and fibrotic reactions.
Although further research is required, the available data suggests that under certain conditions, especially those involving chronic exposure, carbon nanotubes can pose a serious risk to human health.