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Electrical data is analyzed and deviations in the ΔV signal are compared with defectivity observed by the optical surface detection system with UV-PL capability.
Reliable statistical data of the relationship between decreasing voltage and defect classification show good detection of triangles and several other defects in the epitaxial layers.
The data is collected on 25 wafers of 200 [mm] 4H-SiC with n-type SiC epitaxial layers.
Logarithmic distribution of defectivity with overlapping voltage leakage sites, see Tab. 1 for corresponding data.
The data from QUAD and UV-PL do not correspond one to one and UV-PL gives more detections.

Area detectors were used for all measurements, which together with the high photon flux enabled fast data acquisition.
Data analysis.
However, only three of the strain coefficients were solved in the average grain studies since the sample was not rotated, while all six coefficients were determined from the individual grain data.
Figure 3: The residual stress state after cold rolling reduction.
From our data it looks like there is a difference in behavior among the grains when plastic yielding has started.

The aim of this work was to optimize the growth and sulfate reduction capacity of mixed bacterial cultures.
This phenomenon was observed for sample growing in lactate medium, pH 5.5 after a 48h incubation period thus confirming previously reported data [6].
Maximum sulfate reduction was observed during the first 120h.
However, it is possible to affirm that LG1 consortia have some metal tolerant SRB which are being identified (data not shown).
However, when growing with ethanol as organic carbon source a sulfate reduction of about 50% was achieved.

The results showed that the predicted data agreed well with the experimental stress-strain curves.
There have been many studies working on constitutive equation but the accuracy of the calculated data varied widely [3-6].
The data obtained from the tests were used to calculate the true stress-strain data.
The R-squares between fitted and experimental data are above 0.96.
The Figure 4a-d show the distinction between the calculated data and experimental data from the different tests at different temperatures and strain rates.

The final direct to DDS simulation results and the overall DDS platform oscilloscope experimental data, verify the correctness of the design of DDS with the two data.
Shown in Figure 1, its main parts: the phase accumulator (to produce the output waveform phase angle data), relative to digital converter, (above the phase data is converted to the instantaneous output amplitude data), and digital-to-analog converter (DAC) (the magnitude of data into a sampled analog data points)[5].
It contains two ROM as sine wave table ROM and square wave table ROM. data width of the two ROM are 14 bits, and the data depth is 214, the data of the wave table ROM was Provided by Memory Initialization File. .
ROM data is a 14-bit signed number, amplitude keyword is also a 14-bit signed number,。
Last retain the previous 14 bit as output result. when it was Outputed, because the digital representation of the symbolic, you can flip the highest sign bit, unified data raised to above zero and expressed as an unsigned data.

The scaled El Centro 1940 earthquake data is used as input excitation.
In order to evaluate the performance of the newly developed TMD, dynamic tests are performed by employing scaled El Centro 1940 earthquake data [8].
Input excitations: (a) original El Centro 1940 earthquake data, (b) scaled data for 20 sec and (c) scaled data for 25 sec Herein the scaled El Centro 1940 is employed due to the existing laboratory setup.
The input excitation such as El Centro data remains same as experimental tests input (see Fig. 6) for the simulations.
Along with the full-time history, a zoomed view of 0-5 sec are also provided for better visualization of the data.

For the strong ability of qualitative analysis, the Rough Sets has already been used successfully in many fields such as machine learning, fault diagnosis, decision analysis, process control, pattern recognition, data mining and so on.
By the way, because of the pool intuitiveness of many concepts and operations of the theory, it normally isn’t easy to understand their essence; 2) many concepts of the Rough Sets is defined and used under the hypothesis of complete information system while in the real life it’s more often to face with incomplete information systems because of the error of measurement, the limitation of data understanding or knowledge acquisition, or some other reasons.
But like the Find-S algorithm, the Candidate Reduction algorithm is also sensitive to noise.
Song[11] proposed a redundant information reduction method in 2009, it improves the speed of reducing redundant attributes through automatically clustering based on ranked data subtraction.
Beijing: Engineering Industry Publishing House (2003) [2] Shuopin Wen, Shengyong Qiao, et al., Data and rules extracting in incomplete decision table based on decision tree, Computer applications, 23(11) (2003) 17-22 [3] Changsong Sun, Xiguo Dong, Jianpei Zhang, Algorithm based on rough set and decision tree to gain minimal classing rule set, Journal of Harbin Engineering University, 23(5) (2002) 87-91 [4] Jing Yang, Hao Wang, Xue-Gang Hu, et al.

GC data was used to calculate conversion, selectivities and Anderson-Schultz-Flory (ASF) parameter for [4, 20].
Obviously there is a difficulty in showing the promoter effect on the conversion which will be explained when discussing the selectivity data.
FTS reactor runs data Catalyst CO conv.% α S% CO2 S% C1-5 Fe/rGO 95.4 0.30 37.9 62.1 Fe-K/rGO 96.2 0.27 34.8 38.0 Fe-Mn/rGO 82.6 0.29 37.3 44.6 The selectivity of the C1-5 range showed promising trends.
From Fig. 3(a) which shows C1-5 detailed selectivity data, it is clear that promoters severely decreased the CH4 selectivity which started at a high of about 37% Fe catalyst and fell to a low of about 20 % with Fe-K and Fe-Mn.
For complete reduction to α-Fe0, higher temperatures or more reduction time is required.

The peak profile analysis data and the self-consistent predictions of texture evolution showed a good agreement with the experimental deformation texture evolution.
Other advantages are the “easier” sample preparation routine, relative short time required by the “state of the art” equipments to render results and the fact that the data obtained is statistically averaged over the area/volume irradiated.
The rw1 data files generated by the Philips software were converted into raw archives, recognizable by PopLA [6), using PC-Texture 3.0.
The profile data acquisition was done using a solid-state position-sensitive ultra-fast detector (X’Celerator, Panalytical).
The initial texture, corresponding to the As-received material, consisted of a file with a set of grains orientations extracted from the SOD file (sample orientation distribution) obtained from the X-ray data for pole figure measurement using the routine PoPla (Preferred orientation package Los Alamos).

Before performing pre-feasibility studies using RET Screen, the analyst should have enough technical and financial information about the proposed project, such as meteorological information in the location of the project, technical data of the power station component as well as the project's cost constitution.
Meteorological data can be gathered from the NASA Surface meteorology.
The product cost data can be collected from their products supplier.
The PV case in china The PV power plants analyzed in this paper is located in the city of Hami, at the centre of the autonomous region of XingJiang in china, Wurmqi is the nearest weather data location.
Solar resource input parameters Nearest location for weather data Urumqi Latitude of project location 42.9 °N PV array tracking mode Fixed Slope of PV array 36.0° Azimuth of PV array 0.0° Application type On grid Table 3.