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The data is presented for two stress ratios, R = 0.1 and 0.7.
Unfortunately, data was not generated on the as-welded at R = 0.7.
Examining first the R = 0.1 data, the friction stir welding induced a residual tensile stress, increasing the crack growth rate at a given ∆K over the baseline data.
Examining the R = 0.7 data shows a similar trend as the R = 0.1 data set.
The three layer laser shock peening applied to friction stir welded specimens resulted in a substantial reduction in fatigue crack growth rate compared to the as-welded data.

According to the data, in general, increasing the time of treatment of sulphurised PE in the thallium salt solution may lead to a faster rate of sorption and larger amounts of thallium.
For more accurate composition data the thallium sulfide layers were studied by X-ray photoelectron spectroscopy.
The XPS analysis data shows that the composition of TlxSy layers formed under different conditions is very similar.
The XPS analysis data gives only approximate x and y values in the TlxSy layers obtained.
The data shows that the overall composition of the layers obtained is very close to TlS.

This work includes thermodynamic calculations of the furnace atmosphere dew points that satisfy these oxidation / reduction criteria.
Therefore, the belt is exposed to cyclic oxidation and reduction within the furnace.
The reduction in tensile strength and elongation between 35 and 49 weeks in service was statistically significant for both belts.
The oxidation-reduction curves were calculated using FactSage™ software [12].
Berger, “Control of Nitrogen Absorption and Surface Oxidation of Austenitic Stainless Steels in H2-N2 Atmospheres”, 1983, Air Products Technical Data, Air Products and Chemicals, Inc., Allentown, PA

Nevertheless, great attention is needed in the data analysis in order to ascertain reliable results.
In order to compensate the effect of signal reduction in data, the results where normalized by taking the ratio of peak area for a characteristic line to the area for a spectral window of 50-60 nm.
Each data is the mean value of the integrated intensity by applying 10 laser pulses, while error bars depict the standard deviation of mean value.
Thus the data is the result of an average of 10 laser pulses and the error is the standard deviation.
This is shown in Fig. 6, where the data of Table 1 are presented in the form of a bar diagram.

To take advantage of binocular vision system to get for the data of the log examining, to measure the depth of the system information is the most important.
Get the parallax values experimental data by measured are shown as table 1.
The data of the calculated depth value is shown in table 2.
Experimental data is shown in table 3.
Fig.7 Fold line of experimental data Fig.8 Fitting line of experimental data The two lines of figure 7 and figure 8 directly show that the bigger of camera focal length, the smaller of the best baseline distance of the binocular vision system that is consist of the camera.

Aiming at studying the effect of climate change on water resources, 25 years collected secondary data of both climatic and hydro-meteorological stations were used and Statistical analysis was performed using ORIGIN PRO 8.0 Software.
Fig. 1 Map of Lake Kivu Data Collection and Analysis This study was done based on 25 years collected secondary data of both climatic and hydro-meteorological representative stations.
Fig. 2 Trends in temperature and precipitation anomalies in (a) and (b) respectively from 1980- 2004 Note: Anomalies are obtained by subtracting the long-term mean temperature and precipitation data from observed data.
Wiley, Chichester, p. 248 (1996) [6] Courtenay Cabot Venton: Disaster Risk Reduction and Climate Change Adaptation Environmental Resources Management, London (2007) [7] WWF-World Wide Fund for Nature (formerly World Wildlife Fund): Climate Change Impacts on East Africa: A Review of the Scientific Literature.

The measured data shows that the photovoltaic conversion efficiency and open circuit voltage of DSSC are significantly improved by more than 38.8% and 5.8% under the stimulated AM 1.5 sunlight by using the biased operation mode compared to the conventional operation mode without an external bias applied.
The measured data show that the increased photoelectric conversion efficiency by 38.8% can be achieved in a DSSC module with an aperture area of 10mm×10mm by applying a 1.5V external bias.
Based on the measured data, the net output voltage of DSSC (Vx) can be extracted from the equivalent circuit as shown in Fig. 2.
According to the measured data, The I-V characteristics of DSSC is optimized distinctly under the novel biased operation mode which causes the improvements of photoelectric conversion efficiency and open circuit voltage of DSSC by 38.8% and 5.8% respectively.
(dark reaction) (4) It should be noted that the 5.8% increase of the open circuit voltage has also been got from the measured data.

is the input data
is the input data
(6) : the target value for neuron corresponding to input data on the output layer.First, input the input-output pair into the neural network.
We extract historical data of the aforesaid input parameters of 14 days during 2012/7/3 to 2012/7/30 as the training samples of artificial neural network.
It is observed in Figure 4 that the forecast model trained by using the historical data of the 14 days as training samples has good effect.

The trained and the predicted transmission are compared with the experimental data.
A new predicted data at 10% H2 concentration has been introduced using proposed ANN model.
The experimental data coincides with the proposed ANN model (line is the ANN model and symbol is experimental data).
The result of ANN model showed a good agreement with the experimental data.
The predicted values of the transmission variation with the wavelength at 10% hydrogen concentration The ANN model not only simulated the data but also predicted the data using the above examined model.

Construction and Functions of EMS Conventional EMS system is divided into 3 parts according to its functions: Data Acquisition Layer, Data Logic Layer and Data Presentation Layer.
Data Acquisition Layer.
Data Logic Layer.
Data Logic Layer is the core of EMS, whose functions include the organization, storage and analysis etc. of the data.
Data Presentation Layer.