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Gold nanoparticles were prepared by NaBH4 reduction method, and homogeneous SiO2 were coated on gold nanoparticles and assembled into densely-packed 3-dimensional arrays by the layer-by-layer self-assembly (LBL) technique.
Introduction Metal nanocrystallites embedded in transparent matrix exhibit novel linear and nonlinear optical properties due to local field enhancement near the surface plasmon resonance (SPR) of the metal, are essential for light-controlled phase and refractive index modulation for future applications in various fields such as optical telecommunications, data storage, optical computing and information processing [1].
Gold colloids were prepared by NaBH4 reduction method [7]. 1mL 1%wt HAuCl4 aqueous solution, 2 mL 38.8 mM sodium citrate aqueous solution and 1 mL 0.75% NaBH4 aqueous solution were added into 90 mL water at room temperature.
A change in absorption coefficient with the pump-pulse intensity I is expressed by Iβα=∆ (1) 0 10000 20000 30000 � (cm-1 ) 8layer 6layer 3layer Au�SiO2 acid reduction p=0.047 2.26eV 2.30eV 2.35eV 2.0 2.5 3.0 -2000 0 2000 8layer 6layer 3layer �� (cm-1) Photon Energy (eV) Delay Time:0.1ps pump:3.12 eV power:10.6 GW/cm 2 0 5 10 15 -3000 -2000 -1000 0 2.26eV 8layer � � (cm -1 ) pump power I (GW/cm 2 ) � obs =(-2.5 r 0.9) ˜ 10 2 (cm/GW) Au � SiO 2 acid reduction pump:3.12eV Im � (3) =(-8.7 r 3.3) ˜ 10 -11 (esu) Im � (3) / � =(-3.2 r 1.2) ˜ 10 -15 (esu � cm) p=0.047 Fig. 3.

The method of single minute exchange aims at reduction of setup and adjustment times.
According to [1] there are several methods that support the assembly cost reduction.
· Reduction of screws and other items that make the assembly process time consuming.
· Reduction of number of tools needed for assembly.
Ho, “5-S Practice: a New Tool For Industrial Management”, Industrial Management & Data Systems, vol.98/2, 1998, pp.55-62

The theoretical predictions are in good agreement with the experimental data.
The effect of section dimensions on temperature reduction is significant both for the section core and for the steel out surface.
It can be found that the influence of steel ratio on steel tube and section core temperature reduction is less.
The theoretical predictions in this paper are in good agreement with the experimental data
(3) The increase in section dimension results in a temperature reduction within the section, whereas the reduction in temperature within a three hour fire time becomes less significant when C exceeds a certain range

Foreword Enter the "12th Five-Year", the nitrogen oxide emissions for the first time by the state as a binding target, the industrial total nitrogen oxides emissions reduction of 15% in 2010 based on 2015, a 12% reduction in the cement industry [1].In China, the nitrogen oxide emissions in the cement industry has become the third major emitters.Following the thermal power generation, automobile exhaust emissions.
State Environmental Protection Department made it clear that the cement companies to advance the nitrogen oxides emission reduction, construction of environment-friendly green cement companies.
According to the requirements of the national environmental policy, Tangxian Jidong Cement Co., Ltd. in Hebei Province, the first to start a cement production line experimental work of reducing nitrogen oxide emissions, flue gas denitrification engineering SNCR (selective non-catalytic reduction) denitration process.
Flue online monitoring system.At the exit of the decomposition furnace, flue gas line monitoring system for online monitoring of pollutants in flue gas denitrification treatment ingredients, and the data is fed back to the control system.Based on the feedback signal line detection of NOx ammonia, the control system automatically adjusts the amount of ammonia by injection system and compressed air flow.
Table 3 Monitoring data summary table Coal consumption t/h Feeding amount t/h Flue gas volumeNm3/h Processing before NOX concentration mg/Nm3 After treatment NOx concentration mg/Nm3 Denitrification efficiency% The amount of ammonia slip mg/Nm3 32.35 390 423853 721.1 196.0 72.82% 0.86 Economic and environmental benefit analysis Economic Benefit Analysis.The running costs is project materials and power consumption, including ammonia, compressed air, demineralized water and electricity consumption.

In the proposed method, and can be directly obtained from the measured data using the parameter identification technique, for instance, the ERA [19] technique (for free vibration response) and the NExT [20]-ERA technique (for response under ambient excitation).
General description Description of damage cases 1 2 Single damage case k8: 20% reduction of stiffness k17: 20% reduction of stiffness 3 4 Multiple-damage cases k5 and k9: 20% reduction of stiffness k4, k7 and k16: 20% reduction of stiffness Single Damage Cases.
Chung, A study on crack detection using eigenfrequency test data, Computers & Structures. 77(3) (2000) 327-342
Pappa, An eigensystem realization algorithm for modal parameter identification and model reduction, Journal of Guidance, Control, and Dynamics. 8(5) (1985) 620-627

All of the data was then sent to a data acquisition computer for analysis.
This could be attributed to more reduction in grinding forces under cryogenic cooling at higher depth of cut.
The measurement results show that the profile longitudinal parameter values, such as Ry, Rq, Ra and Rz reduction of about 30%-50% in comparation with the oil-based coolant.
The effects could be attributed not only effective temperature control but also to a desirable reduction in grinding forces.
A reduction of about 30%~ 50% of the longitudinal parameter values could be realized by the application of the liquid nitrogen grinding the nickel based superalloy

It is showed that the binding energy shift to higher with the thickness reduction from the Al 2p, N 1s, In 3d5/2 spectra.
It is clear that both Al-N and Al-O peaks shift toward higher binding energy in Al 2p spectra with the reduction in the thickness of In0.13Al0.87N layer from sample A to C.
It can be concluded that thin In0.13Al0.87N epilayer is more seriously oxidated after exposed to air from the XPS data and the native oxide induce upward surface band bending.
There is more native oxide in the thin sample than the thick from the XPS data.

The DAT warm-mix asphalt has poor water stability and low-temperature stability but good high-temperature stability than the hot mix asphalt when the indoor mixing and molding temperature has 20°C reduction.
In addition, each reduction of 10°C, about 0.9kg carbon dioxide emission per ton can be cancelled in the asphalt mixture production process [4].
Conclusions Though the analysis of the contrast experimental data of asphalt and asphalt mixture, some conclusion can be made: a.
The warm mix agent DAT has a little negative effect on the moisture sensitivity and low temperature stability but the data can meet the requirement.

Li et al. put forward the pipeline of data and data mining in IDS.
Step 3: Classifying the data after dimension reduction by SVM.
Dimension reduction reduces the complexity of data and the running time of the classification algorithm.
The idea of the method is that original data sets are divided into K groups, each group acts as a training data set, and the rest acts as test data set separately, then the number of model is K.
We extract 2000 records as training data set and other 2000 records as test data set.

Some of the advantages of TWB are weight reduction, saving in fuel consumption, cost reduction and best quality, etc.
A material of DQSK grade was selected for tensile test on experiment, engineering strain/stress data was converted to true stress and strain.
Derivation of ANN sample data In order to get the ANN sample data, 18 group simulations were conducted.
Architecture of ANN model for TWB tensile test Results and analysis From the available data sets in Table 5, 18 data sets were used to train the ANN model and two data sets were used to verify the accuracy of ANN model.
Simulation of ANN model using with 18 data sets compare with FEM simulation trail result data are shown in Fig. 4 and Fig. 5 respectively.