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Atomic CN reduction.
Fitting the measured data gives the values of m and A for a specific semiconductor.
High order CN reduction is considered for dipole-dipole interaction. 0 20 40 60 80 100 -100 -80 -60 -40 -20 0 (b) EB change (%) K BOLS W Mo 0 50 100 150 200 -4 -2 0 (a) Lattice strain (%) K Plate Dot Pr2O3/Si 0 10 20 30 40 50 -80 -60 -40 -20 0 (c) Tm suppression (%) K Plate, m = 1 Dot, m = 1 CdS Bi-01 Bi-02 Bi-03 Bi-04 Bi-05 0.0 0.1 0.2 0.3 0.4 0.6 0.8 1.0 1.2 (d) m = 4 P(x)/P(0) K -0.5 TiO2 HPR IHPR (BOLS) 0 20 40 60 80 100 -40 -30 -20 -10 0 (e) Tm suppression (%) K Plate, m = 1 Dot, m = 1 Fe3O4 0 2 4 6 8 10 12 14 0 50 100 150 200 (a) m=4.88,dot m=4.88,rod STS-data Data-1 Data-2 EG Expansion (%) K 0 2 4 6 8 0 10 20 30 40 50 m = 1, dot m = 1, plate Au/TiO2 Au/Octan Au/Pt Au/thiol (b) Au-4f shift (%) K 0.0 0.2 0.4 0.6 0 20 40 60 (c) 1/R (nm -1 ) Raman Accoustic Shift (cm -1 ) TiO2-a TiO2-b SnO2-a 0 20 40 60 -30 -20 -10 0 (d)
d) Raman optical frequency shift of CeO2,94 SnO2-1,95 SnO2-2,93 InP,96 and e) Dielectric suppression of nanosolid silicon with Data 1, 2, and 3;97 Data 4 and 5;98 and Data- 6.99 f) Temperature and size dependence of magnetization. 2 4 6 8 -80 -60 -40 -20 (e) Dielectric suppression (%) Data-1 Data-2 Data-3 Data-4 Data-5 Data-6 m=4.88,dot m=4.88,rod K 9 12 15 18 21 24 3.0 3.5 4.0 4.5 5.0 Pc (GPa) R (nm/10) CdSe (a) Figure 8 Theoretical reproduction of (a) Temperature dependence of the thermal expansion coefficient100 of AlN, 101 GaN102,103 and Si3N4.101 (b) Size and pressure dependence of the phase transition at room temperature of CdSe nanocrystals.104,105 (c) Pressure dependence of the Raman shift of the E1 and E2 modes of AlN.106,107 (d) Size
The literature data for atomic cohesive energy is from Kittel115 for comparison.

In this paper, based on multivariate statistical principal component analysis, we select characteristics of the signal, and use radio monitoring equipment mined measurement data to do some processing and analysis, which provided technical support to automatic modulation recognition of the radio signal.
Principal component analysis and Modulation Recognition Principal component analysis is a multivariate statistical methods which utlize ideological dimension reduction and make multiple indicators into several composite indicators on the premise of lossing very little information .
(6) On a number of sample data for each type signals , we can obtain its eigenvectors matrix according to above methods.
Experiment we conduct the relevent experiment by selecting data of five modulation of broadcast signals such as AM ,FM ,VSB ,SSB ,FSK ,where sample rate isMHZ,if frequency is=465MHZ; we take ten groups of data from the same class modulation broadcast signals,extract seven characteristic parameters of initial data by matlab.then conduct Principal Component Analysis by SAS starting with correlativematrix R,and obtain the principal components when accumulative contribution rate than 90%.
The experiment results are as follows: Table 1 Eigenvalues of Correlation Matrix Eigenvalue Difference Proportion Cumulative 1 3.73250912 1.76770925 0.5332 0.5332 2 1.96479987 1.07126818 0.2807 0.8139 3 0.89353169 0.56422843 0.1276 0.9415 According to Table 1, we see that cumulative contribution rate of the first three principal components have achieve 94.15%,so we take the,, as after dimension reduction characteristic parameters .where We take ,,as a modle to create classifier which used to classfiy the data of actual measurement,the results show that the three principal components to do pattern recognition of signals which have the correct rate more than 95%. 4.Conclusion This paper proposed a feature extraction methods which based on principal component analysis of

Therefore we also have to look at the reduction of vehicle weight and consequently at various strategies for lightweight construction.
The methodology for reaching targets and requirements like weight reduction, crash performance and cost targets will be explained.
Significant reductions in fuel consumption require implementation of lightweight design solutions in large-scale production.
This 3D data set was then reprocessed using the TOSCA topology optimisation software.
This would contribute to the reduction of consumption and CO2 in the automobile.

The present study focuses on a reduction of the HHV and a change of autogenous shrinkage of the high-strength mass concrete.
The reduction mechanism of the HHV can be divided into three methods.
Hence, the first method of the aforementioned reduction mechanism is inappropriate if applied to the experiment.
HHS and ASS were determined by regression analysis with a determination coefficient of over 0.95 from the datum points.
The datum point of ASS was the bend point.

Feasibility study on combined heat and power with different distributed generation technologies for various commercial buildings Yingjun Ruan1,a Qingrong Liu 2,b and Weiguo Zhou1,c 1 No.1239, Siping Road, Shanghai, 200092, China 2 No.2103, Pingliang Road, Shanghai, 200090, China asnail2418@sina.com, bliuqingrong@shiep.edu.cn, ctjweiguo@tongji.edu.cn Keywords: Combined heat and power, Distributed generation technologies, Heat-to-Power ratio, Energy saving ratio, CO2 reduction ratio Abstract.
And their primary energy utilization efficiency, energy saving ratio and CO2 reduction ratio have evaluated and compared respectively.
And according to the data available [5], the daily, hourly and monthly percentage can be gained.
Fig.7 CO2 reduction ratios for various buildings Environmental impact is an important factor cannot be neglected in any project and the CO2 emissions are calculated and CO2 reduction ratio is defined as follows: (5) Where, : CO2 reduction ratio of CHP system; : CO2 emissions of the conventional energy supply system, kg; : CO2 emissions of the CHP system, kg; : Unit of CO2 emissions per cube meter natural gas; it equals to 2.37kg/m3; : Unit of CO2 emission for per kWh electricity; it equals to 0.38kg/kWh; : Consumption amount of natural gas in the conventional energy supply system, m3; : Consumption amount of natural gas in the CHP system, m3; : Utility electric power used in the conventional energy supply system, kWh; : Utility electric power used in the CHP system, kWh; According to the equation 5 and energy consumptions of the various buildings, CO2 reduction ratios were calculated and shown in Fig.7.
This shows that hotels had the highest CO2 reduction ratio with 29.7%, followed by apartments with 25.1%, hospitals with 21.7%, educational facilities with 18.2%, offices with 16 % and commercial buildings with only 10%.

The results proved that predictions based on our mathematical model were agreed with the experimental data comparatively.
The burr volume reduction ΔV within process time Δt can be expressed as follows:
Therefore, the volume of metal removal capacity from the workpiece calculated by Eq. 2 is larger than the actual burr volume reduction.
In M-ECD process, the deburring time t increase considerably when the processing current is less than 0.1A, and the reduction in deburring time is not evident while the probabilities of discharge and short circuit will increase when the processing current is more than 0.4 A.
(2) The rate of burr height reduction is initially high and it reduces gradually with processing time.

From TEM images, the average particle size is about 40 nm and all XRD diffraction peaks of phosphor powders were consistent to JCPDS data of YAG.
One major advantage is the reduction of internal scattering, it will lead to a higher efficiency in display and lighting applications[6-9].
Refer to JCPDS (Joint Committee on Powder Diffraction Spectrum) data, all diffraction peaks of synthesized powders are consistent with YAG JCPDS.
In Fig. 4, copper signal was also found in EDS data, it resulted from the copper support when the EDS measurement was carried out.
Furthermore, EDS data can ensure the composition of phosphors synthesized in our work be pure YAG:Ce without any impurity.

It can accurately describe the rule of the whole deformation process through numerical calculation to simulate the deformation process of steel and then modify it by using the key point data of the production process[3-8].
Contrast of macro and center reduction ratio during slab rolling under uniform temperature Macro-reduction ratio 5% 15% 25% 40% Center reduction ratio 0.03% 1% 7% 15% Figuer 4.
Curve of temperature range between surface and center during temperature waiting under air cooling for 400mm thick slab a. 15% reduction ratio b. 40% reduction ratio Figuer 6.
Center deformation is hard to occur when reduction ratio is less than 15%.
Improvement of center deformation can be gained by the increased reduction ratio or bigger accumulated reduction ratio.

Isothermal compression of Ti-6Al-4V-0.1B alloy was carried out at deformation temperature of 850-980 ºC, strain rate of 0.01-1s-1, and maximum height reduction of 60% with Gleeb1500D simulator.
Isothermal compression was performed to 60% of maximum height reduction at each combination of deformation temperature and strain rates.
Fig.1 Equiaxed microstructure of Ti-6Al-4V-0.1B rolling bar The load-stroke data were converted to stress-strain curves and the flow stress was obtained as a function of deformation temperature, strain rate and strain.
The activation energy of deformation was calculated by the experimental data.
　　　　　 　　 (5) Apply the value of flow stress, strain rate and α to Eq.4, the curves were drawn by the data of ln-ln(sinh(ασ)) , ln(sinh(ασ))-1/T and linear fit is obtained at Fig.5.

The data and information in the system are transfered using wireless transmission technology.
The data information of carpooling for them is imported by a summary keyboard.
Considering the actual application, this part of the circuit just need to send the data to the electronic screen, so the data reception pins of MCU don`t be used.
Display subroutine scans to turn out the dot matrix data by line, which has set stored by group, and then lighting LED line-by-line.
Afterwards, data sent out to the second column, the third column and so on.