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The reduction in the saturation drain-source current is correlated to both simultaneous degradation of the channel mobility and an increase in the threshold voltage shift.
The solid lines are fits to data using Eq. 3.
The value of A = 0.80 and B = 8.12×1012 cm-2 gives an excellent fit to the measured data.
The reduction in the channel mobility and an increase in the threshold voltage shift are due to the increase in the Coulomb scattering centers.
The channel mobility was found to recover to 83% of its pre-radiation value and simultaneously a reduction in the interface trap density.

An increase in crystalline content results in a reduction in dissolution enhancement.
Data will be presented demonstrating the reduction in dissolution performance as the level of drug loading and crystallinity increases.
Drug dissolution enhancement Due to the reduction in crystalline drug content and increased drug surface area, enhanced drug dissolution was observed in the first 30 minutes for the majority of drug-silica systems studied by our group.
While differential scanning calorimetry and standard powder X-ray diffraction analysis are useful to determine a reduction in drug crystallinity, these techniques need to be supported by ancillary techniques such as solid state NMR and pair-wise distribution function analysis of X-ray and neutron diffraction data.

In order to obtain data concerning twinning deformation one set of samples were processed by cold-rolling, with a thickness reduction of 10%.
In figure 3 one can observe that twinning deformation occurred in a large number of grains even at 10% thickness reduction.
Only crystal orientation data contained in the selected area (see Fig. 5b) was used in order to obtain Inverse Pole Figure (IPF) and Pole Figure (PF) of parent grain – twin system.
Fig. 6 shows the distribution of rolling direction (RD), transverse direction (TD) and normal direction (ND) in respect to reference frame of the crystal, in the case of Ti-31.7Nb-6.21Zr-1.4Fe alloy cold-rolled with a 10% thickness reduction.
(hkl)[uvw] 332 113 332 113 332 113 332 113 233 311 232 311 233 311 233 311 323 131 323 131 323 131 323 131 Schmid Factor (SF) -0.122 -0.141 0.295 0.200 0.305 0.052 0.305 0.012 -0.451 -0.108 -0.016 -0.392 Conclusions The main results can be summarized as follows: (1) at 10% thickness reduction twins are observed in a large number of grains; (2) for all observed twins a CSL close to 50.47° is observed, indicating a {332}<113> twinning system; (3) computed SF’s suggest that the primary activated twinning variant is 323131 (SF = -0.451); a possible secondary twinning variant being 323131 (SF = - 0.392).

The results demonstrate that sufficient CTAB amount is important in order to obtain AuNRs and the reduction rate of Au ions was dependent on the AA concentration.
The reduction rate of Au ions was dependent on the AA concentration.
Low concentration of AA caused slower reduction kinetic, hence allows slow diffusion of Au ions on the Au seeds particles surface.
However, excess AA caused forced reduction, resulted in the decrease of AuNRs aspect ratio.
Filled dots represent the experimental data and straight line is calculated data.

The evaluation of technological properties of quartzites was done by comparing the curves of relative weight loss with industrial technological data of the ferrosilicon smelting process.
The results in the form of curves of relative loss of mass during heating of samples were compared with technological data from the ferrosilicon furnaces.
The study was conducted in thermobalance Thermogravimat Sartorius 4304 series, in which was modernized and upgraded the recording system and processing of measured data.
The relative weight loss of sample with quartzite Bukowa Góra after 360 min as a function of the flow rate of argon, VAr Summary The usefulness of thermo-gravimetric studies to assess the technological properties of quartzites was determined by comparing the weight loss curves with technological data from the FeSi75 ferrosilicon smelting process.
This is confirmed by data on technical and economic indicators of consumption of raw materials and energy.

This study proposes to use mathematic geometric equations to compose the programming language via which point data are obtained and processed by Solid Works to complete the construction of the model.
Di Francesco and Marin[1] have studied the external gear with asymmetric teeth, and analyzed the reduction of size and weight.
Research Propose This study proposes to use mathematic geometric equations to compose the programming language via which point data are obtained and processed by Solid Works to complete the construction of the model.
The point data are then converted into Solid Works for 3D modeling.
Structural analysis of asymmetrical teeth: reduction of size and weight, Gear Technology,14(5),47-51

The calculated results show good agreement with the experimental data.
Applying the perturbation procedure similar to that in Refs. [12,13], the perturbation formulas of g factor and hyperfine structure constant for an octahedral 5d5 cluster can be expressed as: g = 2 (1 + 2kp)/3, A = P (κ/3 – 8Np /7) (1) Here kp and Np are the orbital reduction factor and the normalization factor for the π component, characteristic of covalency of the system.
From the cluster approach [14], the orbital reduction factors kp and ks can be determined by considering the ligand orbital contributions: kp = Np (1 + lpp2/2), ks = (Np Ns)1/2 [1- lpp (lps + lss w)/2] (2) Here w denotes the integral , where R is the reference impurity-ligand bond length.
Then the orbital reduction factors kπ » 0.857 and kσ » 0.461 are calculated from Eq. (2).
When the ligand orbital contributions were neglected, the theoretical results (Calc. a) are in poor agreement with the experimental data, especially the g factor and hyperfine structure constant are smaller than the observed values.

But the dimension of Gabor wavelet is usually high, an effective dimension reduction process is need to be considered.
Section Four briefly describe the adopted the approach of dimensionality reduction.
Fig. 5 Gabor filters Dimensionality reduction Because each image is 128 × 128 dimensions after pre-processing, the dimension of extracted features is 128 × 128 × 5 × 6.
The procedure of DCT transform is shown in Fig. 6: Fig. 6 The procedure of DCT From Fig.6, we can easily find that the top left corner data includes most of information of the original image.
To get the top left corner and put these datas into a vector, zigzag algorithm is used in the paper. 2DPCA is also employed to reduce dimension for comparison with DCT.

The Database of Facilities Asset Management Application in the Disaster Reduction – Case Study of Ching Yun Building in Ching Yun University Ruei-Hung Shiu1, a, Po-Hsun Sung2,b, Jyh-Dong Lin2,c, Hao-Hsien Chen3,d and Li-Rung Jeng1,a 1No.229, Jianxing Road, Zhongli City, Taoyuan County, Taiwan, R.O.C. 2No.300, Zhongda Road, Zhongli City, Taoyuan County, Taiwan R.O.C. 3Department of Civil Engineering, National Ilan University, Taiwan, R.O.C.
Asset management system demands data such as the goals set in the opening, the list of assets to create and manage systems, and performance indicators and final set of program planning and evaluation, etc.
To assess management platform is vulnerable or not, and improve the risk assessment about the software and hardware. [4] First, the study combines the business information systems and related inventory data of Ching Yun University.
Second, the important meetings of competent department confirm the priority order aim on the important system or data analysis.
Center, "Disaster risk management and vulnerability reduction: protecting the poor," 2001

The results then were compared with the experimental UEWS data to achieve the closest fit.
Through the model developed, suggests that they are closely conformed to the UEWS experimental data.
Whilst pure axial loading, which presumably more prone to transverse stiffness reduction by matrix cracking showed the closest fit to experimental data at αE2/αG = 6.0, which is the highest of the previous two modelling results.
The results from the model for all stress ratios showed a good agreement with the experimental data.
On the contrary, modeling for pure hoop loading (1:0) showed a reduction in the ratio between αE2 and αG from 1.0 to 0.625 to achieve the closest agreement to experimental data.