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This led to a sharp reduction of dissolved Sn down to 1% on Si, down to 20% on Ge, and down to 40% on InP substrates.
According to the AFM data, Sample C has a flat surface consisting of the densely packed round-shaped particles with a diameter of up to 15 nm (Fig. 1 a).
The last is an artefact of data processing and it should be considered as zero.
Since the Si-Sn film has a p-type conductivity (it will be shown later, in the section with Hall data), in the case of the Al contact illumination a separation of the photo-generated carriers takes place at the Schottky junction under reverse bias.
The difference in the observed values (26 meV) can be explained by the Schottky effect of barrier reduction with the applied bias increasing [12].

Mass Concrete Test In the application of mass concrete to stadium, a strict data test should be made from concrete material selection, concrete configuration and transportation, concrete pouring, and concrete temperature control for ensuring the quality of the project, and also concrete is prepared and constructed according to the test data.
In the test, the cement dosage reduction test is gradually made by starting from 380 kg cement per cubic concrete, so as to find the effect change law of cement thermalization reaction on the temperature of concrete and then determine the best cement content.
In calculation, an item is the common-sense data that has been tested for many times.
Conclusion According to quality requirement, the mass concrete construction in stadium projects should refer to the test data analysis, and also all parts of the construction and especially the links of concrete temperature control measures should be adjusted.
The excellent data test for mass concrete can guide the project construction, so that the project better according with the actual conditions can be built.

The traditional approaches mainly focus on simplification and reduction of the terrain data executed on CPU, which usually result in a very high CPU loading and make it inefficient in real-time terrain rendering.
Terrain LOD algorithm based on GPU can process the batch of terrain data and it uses the terrain block as the basic unit instead of a single vertex or triangle in LOD simplify.
In the terrain rendering cluster triangulations form the data block which is the node of quad tree.
The configure of computer is Intel Core 2 Duo E8400 @3.0GHz CPU 2GBRAM NVIDIA GeForce9600GT GPU 512MBVRAM Windows 7.The high data of the representative Puget Sound is the test data of this algorithm.
We need to adjust different parameter to different terrain data.

Dynamic modelling was performed for a gearbox having the technical data as described in table 1, which was equipped with four pairs of gears (pinion & idler) having the same module, teeth number, tooth width and normal pressure angle, but with different helix angles: β= 9°, 11°, 13° and 15°. 
Technical data of the gearbox Main geometrical data of the gear Centre distance A= 125 [mm] Module mn= 4 [mm] Teeth number z1/ z2= 17/ 43 Tooth width b= 40 [mm] Normal pressure angle α0= 20 [°] Performance data Maximum power P= 2,5 [kW] Nominal input speed n1= 1.500 [rpm] Output torque Mt2= 38,5 [Nm] Geometrical data of the four pair s of gears Helix angle β 9° 11° 13° 15° Addendum modification coefficients x1/ x2 0,48452/ 0,47656 0,39876/ 0,34228 0,30296/ 0,18148 0,20311/ -0,00731 Reference diameters d1/ d2 68,85/ 174,14 69,27/ 175,22 69,79/ 176,52 70,40/ 178,07 Dynamic modelling of the gear transmission was started from the model described in Fig 1.
Based on the proposed mathematical model, using the SimulationX software, it has been performed a numerical simulation of the gearbox dynamics, simulation results being compared with data obtained experimentally.
Korka, Research on vibration reduction in operation of cylindrical gearboxes, Ph.D.

It does not directly control the operation of access controller, of which main purpose is to realize data forwarding and conversion between RS485 interface and TCP/IP communications protocol.
At the same time, the program communicate to access controller through RS485 bus, which record the data and time information collected from access controller.
Management center server is the management and control center, which can accomplish timing charge, power control, safety alarm, data management and document printing.
The data of different laboratories can be transmitted through the LAN.
The Mifare1 IC card with a only 32-bit card serial number, data communication encryption and bidirectional password verification can ensure the system’s safety preferably.

Framework of the EWS of RVR Early warning is a major element of risk reduction.
Descriptive statistics and inferential statistics will be employed for data analyses.
For the data collected by questionnaire survey, T-test and MANOVA will be applied to discover the critical RVR indicators that would significantly affect RV, and correlations of these indicators will be calculated.
c) Case study and Data mining A certain amount of PPP cases will be collected around the world, and organized into a case base so that searches through the case base can be done efficiently and accurately.
After the case base structured, Data mining is used because it is good at mining incomplete data for knowledge discovery of case base.

The test load is applied step by step according to the design load by the loading system, and data such as gravel top settlement, pile stress, gravel pressure data etc are recorded by measurement system to calculate compression modulus, resilient modulus of the gravel bed, and to evaluate the impact of various factors on mechanical properties of the gravel bed.
Table 1 Test gravel gradations Sieve size(mm) Percent of pass(dry weight) Sieve size(mm) Percent of pass(dry weight) B1 B2 B3 B4 B5 B1 B2 B3 B4 B5 90 97 97 26.5 21 3 94 0 75 97 97 19 2 0 73 0 63 100 91 79 16 1 55 53 100 96 76 57 9.5 22 37.5 86 77 2 8 4.75 10 31.5 37 31 0 100 0 2.36 6 Test data of different gravel gradations are shown in Table 2.
Table 2 Test data of different gravel gradations Gravel gradation B1 B2 B3 B4 B5 Secant modulus of compression [MPa] 6.8 8.55 5.51 3.88 7.05 Modulus of resilience[MPa] 278.2 91.6 95.3 91.3 83.7 Maximum size dm [mm] 53 63 100 31.5 125 Effective particle size d10 [mm] 22 27.5 50 4.75 32 Control particle size d60 [mm] 34.5 35 52 17 54 Non-uniform coefficient Cu 1.57 1.27 1.04 3.58 1.69 Curvature coefficient Cc 1.11 1.03 1 1.64 1.02 Porosity (%) 45 49 47 48 41.6 Effects of groove size on gravel mechanical properties.
Load-settlement curve of different groove size is shown in Fig.4, Test data of different groove size is shown in Table 3.
Table 3 Test data of different groove size Working conditions non- groove Width 0.8m Width 1m Secant modulus of compression[MPa] 14.82 7.82 6.70 Settlement[mm] 39.65 68.38 83.22 Unloading resilience [mm] 3.56 0.47 0.3 Fig.4 L-S curve of different groove size The non-groove gravel show higher compressive modulus, and V-groove equals to a reduction of gravel lateral confining pressure, which lead to a nearly 50% ~ 55% decrease of compression modulus.

Methodology The electricity consumption data was collected from Building Energy Management system BEMS)/data logger recorders installed at SERT Smart Grid.
Data recordings is for every minute’s usage of electricity consumption for every floor in different buildings which is authenticated data with high accuracy.
Data is preprocessed for each hour and every day of the week.
The data is preprocessed to extract useful data for hourly consumption of every day of the week.
Fig.3 (A) Relative Variation b/w Mean Consumption of data and model (B) Relative Variation b/w Standard deviation of data and model.

The ICATS software was carried out to capture the Frequency Response Functions (FRFs) data at each load step.
On the other hand, using measured FRFs may have certain advantages over using modal data.
Second, the FRFs can provide much more information about damage in a desired frequency range than modal data extracted from a very limited number of FRF data around resonance [4].
The rest problem was most likely affected by bad FRF data capturing.
De Roeck, Structural damage identification using modal data.

Department of Defense design guidelines for conventionally constructed steel stud walls use acceptability criteria that are much more conservative than wood stud walls due to the lack of data available.
Composite behavior between the veneers and the steel studs has not been considered to be a valid assumption; the laboratory test data presented in this paper indicate the apparent effect of veneers.
Objectives Building from previous research, a main objective of the current study is to create an analytical methodology—validated against test data—that can accurately predict response limit states for various types of steel stud wall assemblies.
Nonetheless, data collected from load tree tests show that the overall response of the system is more greatly affected by the presence of sheathing than by the strength of the sheathing materials used.
Also, test data have shown that sheathing has a substantial effect on the resistance of steel stud wall systems, suggesting that current design methods may require modification to allow for composite wall behavior consideration.