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Room temperature simulations of ID-VGS curves and comparisons with experimental data enable us to extract the energy dependent interface trap density of states profile for the 4H-SiC MOSFET [1].
This reduction in the occupied interface trap density causes an increase in the Coulomb mobility near the interface.
Interface trap density of states profile extracted by comparing room temperature IV simulations to experimental data.
Notice the increase in inversion charge density and reduction in occupied interface trap density with rise in temperature.
Comparison of simulated and experimentally measured IV data gives us an estimate for the interface trap density of states (Fig. 1) and for the surface roughness mobility parameters.

Deng Ju-long, it has been widely used owing to the advantages of less sample data, convenient operation, and high precision of short-term forecasting.
At present, many scholars have proposed a number of GM (1,1) model improved method [1] .But these models do not adequately consider the data anomalies for sequence data abnormal situations, there are many factors that will impact subsidence monitoring data sequence in real life.
When it is bound to be a great deviation, and impact prediction accuracy [2], if the original data sequence model is used to predicted.
For better use of grey model to forecast, sometimes the smoothness of the original data sequence should be improved.
(2) The method is the exponential function to simulate the generated data, the raw data obey a certain distribution, only exception applies to the deformation of the exponential trend changes [6], but it is difficult to consider sequence data on the transition in the trend line, if hopping sequence data (such as index deviation is too large even decreases) is abnormal on the trend line.

Superparamagnetic core/shell nanoparticles have been prepared successfully by the reduction of Au3+ onto the surface of superparamagnetic nanoparticles.
Here, we report a facile synthetic process of superparamagnetic Au shell nanoparticles by the reduction of Au3+ onto the surfaces of seed particles which 2nm THPC-Au nanoparticles attached onto superparamagnetic nanoparticles coated by (3-Aminopropyl) trimethoxysilane (APTMS).
A typical synthesis of superparamagnetic Au shell nanoparticles was carried out as follows: the former seed particles acted as the nucleation sites for the reduction of Au ions using formaldehyde solution as the reducing agent from solution onto the superparamagnetic surface until Au nanoshells were formed[12].
In Fig. 2(a), all the peaks were matched well with the standard JCPDS data of Fe3O4 (JCPDS file, No. 01-082-1533).
Conclusions Superparamagnetic Au-shell nanocomposite particles were synthesized via assembling 2nm Au nanoparticles on the superparamagnetic which actually leads to the growth of gold nanoshells by catalyzed reduction of HAuCl4 with weak reducing agent, as a means to modulate their optical response.

Table 1 Attenuation Coefficient And Attenuation Center frequency/Hz 125 250 500 1000 2000 4000 Sound absorption coefficient / 0.60 0.65 0.60 0.55 0.40 0.30 Attenuation coefficient / 1.0 1.1 1.0 0.86 0.55 0.39 Effective attenuation length/m 3.0 3.0 3.0 3.0 3.0 3.0 Noise reduction A/dB 20.0 22.0 20.0 17.2 11.0 7.8 Noise reduction B/dB 30.0 33.0 30.0 25.8 16.5 11.7 Ordinary Muffler Attenuation Characteristic. [1] Noise reduction: Ordinary silencing slice does not have a convex C, , center distance between slices is , fin pitch , in order to enhance the comparability, the two mufflers combination, effective attenuation length of 3000 mm, the total noise reduction is calculated from Eq.1 [4]: (1) Where △L is the noise reduction, dB(A); is the noise coefficient, dB(A); L is the effective attenuation length, m; d is the distance between slices, m.
Taking the combination of Fig.6 as a calculation case. [1] Noise Reduction: Raised point C is in the 0.25 length direction of the silencing plate, ,, center distance between slices is , fin pitch , two muffler combination, effective attenuation length is 3000 mm, the total noise reduction is calculated from Eq.1.
By comparing the calculation data of the above theory, special-shaped anechoic structure has the following advantages
The folded plate silencing structure can increase the amount of noise reduction, improve the aerodynamic forces performance.
The expansion silencing structure can increase the low frequency noise reduction by changing raised position and level, moving the main subtractive frequency, increasing the low-frequency components noise reduction.

Fault detection based on TLLE TLLE cannot compare the projection data with the original data like PCA.
But after the projection, TLLE can keep the topological structure of the original data as well as the similarity of normal data and illed data.
Therefore, we can perform fault detection by computing the inter-class distance between the testing data and the training data[5][6].
After have been projected to the feature space, the distance between the testing data and training data can be computed.
Thus, we can get the similarity of the testing data and training data.

, i=1,2,…,n (1) Where xi is the historical data of oxygen consumption influencing factors as input data of the training sample set (Independent Variable) and yi is the historical data of oxygen consumption, which is output data of the training set (Dependent Variable).
Ultimately, the data from 29 qualified data were chosen.
Data preprocess.
To reduce the influence of large-value data on the computational speed of the model, it is necessary to preprocess the input data on normalization.
Actual data of production —○—SVM.

The obtained natural frequency data are compared with the natural frequencies of the body-in-white as well as the common excitation frequencies of the engine.
Finally, the optimal lightweight hood design is determined by comparing the modal frequency data to the typical excitation frequency ranges and the known natural frequencies of the BIW.
Table 3 lists the first 10 modes of the BIW on which the hood is attached; and Table 4 shows the weight reduction results of the four alternative designs.
Mode order 1 2 3 4 5 6 7 8 9 10 Frequency (Hz) 30.7 33.1 43.0 47.8 48.5 56.5 59.3 69.7 71.9 77.1 Table 4 Weight reduction data of four alternative designs.
Edwards, Causes of weight reduction effects of material substitution on constant stiffness components, Thin-Walled Structures, 42(4), (2004), pp. 613-637

An Optimal Model for Low-carbon Urban Agglomeration Based on Energy Structure Reduction under Uncertainty Lun Wang1, Zhao Sun2, Jingya Wen2, Zhuang Li2,3, Wenjin Zhao1,a, Yu Li2 1College of Environment and Resources, Jilin University, Changchun, 130012, China; 2Resources and Environmental Research Academy, North China Electric Power University, Beijing, 102206, China 3Changsha Environmental Protection College, Changsha, 410004, China azhaowj@jlu.edu.cn Keywords: optimal model, urban agglomeration, energy structure, uncertainty.
(20) (21) (22) (23) (24) (25) where: =percentage reduction of fossil energy i of urban agglomeration core area in planning late compared with the base period.
Based on emission reduction requirements about carbon intensity and energy intensity in 12th Five-Year Plan about the case of urban agglomeration and survey data, combined with the optimization model in this article, the net carbon emissions of the urban agglomeration area is [1.32, 1.55] (107t) in 2015 solved by LINGO software[5, 6].
Carbon intensity of the urban agglomeration "core area" in the case in 2015 reduces by [50.88, 54.11] (%) compare with those in 2010, it is higher than the national requirements which set greenhouse gas emissions in 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission and the proposed carbon intensity decreased by 18.00% requirements in 12th Five-Year Planning plan for the urban agglomeration in the case; and the optimization plan of energy consumption is also meet the emission reduction targets which in 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission and the urban agglomeration plan, it have down [51.24, 54.57] (%).

Drone data collection.
Strain data collection.
The V-Link-200 will then record and transmit data wirelessly via 2.4 GHz radio waves to the WSDA-2000 gateway which will submit data to the cloud for remote data monitoring [10].
The GW1100 records ambient temperature, humidity and atmospheric pressure and transmits the above data additionally to the wind speed and direction data to the cloud allowing for remote data monitoring. 2 metres Fig. 6.
Data analysis.

In this paper, the effects of EPS geofoam buffer on the reduction of thrust wall force are numerically studied to simulate three reduced-scale models of rigid walls using a large shaking table.
The use of the EPS geofoam as a compressible buffer yields obviously reduction of the lateral seismic thrust against retaining wall.
The test data showed that the peak lateral loads acting on the compressible model walls were reduced obviously of the value measured for the nominally identical structure but with no compressible inclusion.
Based on the results of direct shear box tests on specimens of the same sand material and data adopted by [4] and [6], the soil properties are summarized in Table 1.