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In this work, we use the Callaway model [6] to calculate LTC and compare the results with experimental data reported by Wingert et al.[5].
Fig.1 displays theoretical results, where solid lines are present calculations and the dotes experimental data taken from Ref.[5].
Experimental data are from Ref.[5].
Experimental data are from Ref.[5].
Solid lines are calculated curves and the dotes are the experimental data taken from Ref.[5].

The extrusion reduction ratio for this case was only 15.4, equivalent to a true processing strain of 2.7.
With increasing extrusion temperature, the UTS data in average decrease from 313 to 298 MPa, and tensile elongation data increase from 19 to 32%.
In parallel, with increasing extrusion strain rate, the UTS data in average increase from 303 to 316 MPa, and tensile elongation data decrease from 24 to 18%.
And the UTS and elongation data are seen to appreciably decrease to ~260 MPa and increase to ~40%.
The latter data are compared with those obtained from the uniaxial tensile tests, as shown in Fig. 7.

Tensile properties for the test materials [Data taken from ref. 10].
a) ARS 400 b) DC01 [Data taken from ref. 10].
The compression plates were first pressed against each other and the force-displacement data was collected.  
According to this data, the elastic modulus of the test equipment was compensated away from the real test data.
The comparison between mechanical test data and simulation results.

In the process of the experiment, chose a city river as subjects, use the data of the river as sample data, use optical measurement method and traditional methods respectively perform experiment, and compare them.
Measure each data set use an interval of 1 °.
After data processing the finally obtained two-dimensional measurement range from -10 ° to 10 °.
Remote-sensing reflectance of turbid sediment-dominated waters.Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios[J].Applied Optics,2003,(15):2623-2634

The primary benefit of PLC is the reduction of costs in the realization of new communication networks.
Narrowband PLC offers low data rates and is typically used for home automation and metering purposes.
The whole system is divided into four main subsystems, electric control, monitoring, network publishing and data logging.
The data logging rail subsystem to keep the time and date is when a switch on or off.
This data can be used to flow/balance, determine the peak load time and use of electricity produced by itemized electricity charges.

In this work, we study the effect of preparation route on the fractal dimension of catalyst in the absence and presence of PVP as stabilizing agent from SAXS data.
The catalyst surface was illustrated according to SAXS, FESEM and TEM data.
XPS data can be interpreted qualitatively and quantitatively [4].
Reductions of RuCl3 in ethylene glycol were done in two ways, i.e. with presence of PVP and presence of catalyst support (Al2O3).
The solid were sealed in 1 mm-diameter quartz capillary cell with a wall thickness of 0.01 mm.Background correction of the SAXS data were previously performed before analysis.

Introduction Energy depletion and environment protection make the concept of energy-saving and emission-reduction increasingly draw shipbuilding engineers attention all over the world.
Moreover, resistance of restrained body in calm water and head waves are explored here on the condition of different wave length and amplitudes(short name as A below) Figure 1.3 Wave added resistance(A=0.025m) Figure1.4 Wave added resistance(A=0.046m) Table2 Comparison of computed data and experiment data.
Speed F=0.2 F=0.3 F=0.4 Computed still water resistance /N 3.16 9.088 16.656 Measured still water resistance /N 3.42 9.97 19.86 fractional error: -7.60% -8.85% -16.13% Table2 reveals that computed results are all less than experiment data .The fractional error is no more than 10%.When Fr=0.4 , the gap is less than 20%.This software is reliable for these results are all acceptable.
All computed results reach an agreement with former researches and experiment data.

Emission estimates The formulation is adapted to estimate the amount of CO2 emissions as follows: ε =Efullk - Eemptyk * loading weightloading capacity + Eemptyk (Eq. 1) The calculation of Efullk and Eemptyk for different vehicle loading capacity is based on the data provided by DEFRA [15].
Affected region estimates ArcGIS is a Geographic Information System (GIS) tool that allows us to create map and analyze spatial data, while the proposed project is composed of different data, such as census, roads, sub-district outline, and facility location.
Once these data are compiled into ArcGIS, both a geodatabase and an electronic map is generated.
For solution 6, 39.3% reduction in environmental impact leads to approximate savings of 0.03% in transportation cost.
[2] EEA, EEE Greenhouse Gas Data (2008). 2011

However, when we happy for the achievement, in front of the “strange phenomenon” in reality, we run into another confusion; front one side, people are trying to enhance and improve the earth observing technology and measuring technology in the hope of getting more and more remote sensing image data, besides a mass of earth observation data has been acquired or in processing.
Assume the offerable parallel computing nodes numbers are K, then separate the original image into K pieces with the same size by rows or columns, distribute K data blokes into K nodes separately with the data provided by MPICH, each node doing feature extraction respectively to each data block, and collect the features by the MPICH provided functions, finally achieve the resulting image by clustering in the main process.
Table1 records the experimental data, each of which is the average of three times.
Figure5 shows the Comparison of experimental data to the different number of nodes.
The procedure of parallel processing // Broadcast arguments MPI_Bcast(&height, 1, MPI_INT, mainprocessid, MPI_COMM_WORLD); MPI_Bcast(&width, 1, MPI_INT, mainprocessid, MPI_COMM_WORLD); // Send image data MPI_Scatter(imagedata, myheight*width, MPI_UNSIGNED_CHAR, data, myheight*width, MPI_UNSIGNED_CHAR, mainprocessid, MPI_COMM_WORLD); // Get Symbiosis and Get Statistical Features in each node GetSymbiosis(SimpleSysMatrix, data_in, WndSize, WndSize, 1, 1); GetStatisticalFeatures(Feature, data_in, WndSize, SimpleSysMatrix, tag); // Gather feature data MPI_Gather(Feature1, dimen * myheight*width/WndSize/WndSize, MPI_DOUBLE, recvfeature1, dimen * myheight*width/WndSize/WndSize, MPI_DOUBLE, mainprocessid, MPI_COMM_WORLD); // Cluster Cluster_KMeans(recvfeature, numprocs * myheight*width/WndSize/WndSize, dimen, result, classnumber); Figure 2.

The noise is nearly random and significant reductions in the detection limit are possible by averaging multiple observations in this model.
The data storage motherboard is the analog to digital converter and transmits the data to the next board.
Fig.2 In-situ detection instrument of nitrate Data processing The photoelectric diode array of the spectrophotometer collect 256 data between 195nm and 391nm, but the wavelength and the data do not meet the linear relationship.
The light source has a shutter which can be closed to estimate dark current, but this leads to the useful concentration data lost during the period between detections.
The equation (Eq. 2)for this particular SG smoothing is defined: (2) We got the samples of 10mol/l nitrate and collected the curve[Fig.3.] of the data.The figure[Fig.4.] below shows the smoothing results for the spectral signal, using a second order polynomial fit with 102 data points.