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Test Data Processing and Analysis To verify the performance of the propose method in this paper for impulsive noise, GPS measurement data in an aircraft test is used to process.
The time domain wave of the data is shown in Fig.3.
From Fig.3 can see the data is interfered with impulsive noise.
Fig.3 The measurement data Fig.4 De-noising by SVD combined with WNN From the data processing result, it can see that, the de-noising by SVD combined with wavelet neural network (WNN) can eliminate the impulsive in the measurement data effectively.
For the GPS measurement data processing, this method is effective to obtain satisfaction results.

In this study, data form previous maintenance works or activities were collected from both companies.
The data were then analyzed.
Data Collections and Research Methodology The data collection was started by gathering all the information from the breakdowns and maintenance records.
The similar data were also collected from the Ladang Sabah Palm Oil Mill machineries maintenance or breakdown records.
The collected data were then analyzed.

From UV-Vis spectroscopy we observe that the absorbance of rGO decreased as increasing the reduction temperature because the higher reduction temperature yields a high degree of rGO defect.
One of the molecules that can be used as reduction agent is hydrazine [12], in which the temperature FOR the reduction takes place is becoming one of the important parameters to obtain reduced graphene oxide with high quality.
By using UV-Vis absorbances data, we could calculate optical constant (refractive index real and imaginary part) of rGO by using a number of Maxwell equation and Kramers-Kronig relation.
Then we have compared the calculation result with other data which have done by other people with other methods.
Increasing the reduction temperature will decrease the CO bonding in rGO plane [15].

This overview outlines the reduction of quantitative texture data for the use in industrial settings.
Three different levels of data reduction applied in the daily operations will be discussed.
With such data at hand it is possible to assess the performance of a product in a customer process for example involving plastic deformation.
For process control at the pilot or plant scale quantitative texture data either need further reduction to enable texture analysis as a useful tool at the operator level.
An important aspect frequently overlooked when comparing mechanical properties to texture data are through-thickness texture gradients.

The conclusions provide theoretical reference for the further study of aerodynamic drag reduction of complex underground.
In this paper, studies are focused on a real SUV vehicle model, and the drag reduction research on complex underbody was conducted to provide certain theoretical reference to the research on SUV drag reduction.
Firstly, point cloud data of the model were achieved with ATOS scanning and then reverse processed to obtain the full-scale geometric model, which is shown in Figure 1 and figure 2.
The difference between an average of the seven sets of test data and calculation results was only 1.1%, which verified the accuracy of numerical simulation results.
Flow rate increasing and lift force reducing led to the reduction of the induced drag caused by lift force, which was the root cause of the reduce of aerodynamic drag.

This sink node comprehensively checks and compares data and also ensure its secure transmission of data.
While in sensor network, as an important part of the network energy consumption, the way communication reduction how to reduce redundant data and reduce the transmission energy consumption and of research today in the scientific community has become one hot spot in the course of data transmission.
The main purpose of data aggregation is to reduce redundant data transmission and guarantee data transmission and resist t a variety of malicious attacks and thus improve its overall safety and timely resolve for the convergence data loss issues to t reduce communication overhead.
Once it receives the base station data message about the requirement, take periodic data collection.
Wireless sensor networks data aggregation scheme not only reduce the data accuracy and increase redundant data to gradually increase the aggregation efficiency.

Then with statistical data, the change of CO2 emissions of industrial sectors can be attributed into the four factors just as the Eq.3: (3) where Δ is the difference between the current year and the reference which is the last year in this paper.
The energy consumption of industrial sectors is statistical data in China Energy Statistical Yearbook from 1990 to 2010.
The gross industrial output value (GIOV) of 39 industrial trades is statistical data in China Industry Economy Statistical Yearbook from 1990 to 2010 corrected as the latest values and calculated in Chinese Yuan at 2005 constant price.
The energy consumption of industrial trades is statistical data from 1990 to 2010 from China Energy Statistical Yearbook and corrected as the latest values.
The indirect CO2 emissions of per unit power and heat are calculated based on the data from energy balance sheet in China Energy Statistical Yearbook.

Energy consumption data of industrial field and industrial added value data of Dongying City are mainly from the Statistical Yearbook of Shandong Province [3] and the Statistical Yearbook of Dongying City [4].
Energy consumption data of transportation field and data of vehicle numbers of different types are mainly from Dongying Bureau of Communications.
Energy consumption data of construction field and building area data of buildings of different types are mainly from the Civil Building Census Data Assembly of Dongying City [5] and the Rural Construction Statistical Yearbook of Shandong Province.
Data of baseline emission factors for regional power grids are from the Department of Climate Change of the National Development and Reform Commission.
Only carbon emission in road transportation is measured due to the limitation of data.

Introduction Alkali weight-reduction wastewater is from Alkali weight-reduction process which is designed to give the poly (ethylene terephthalate) (PET) textile a silky property, as well as to improve the dyeing capability.
Alkali weight-reduction wastewater discharged from the PET textile weight-reduction process of some plant was prepared.
A series of alkali weight-reduction wastewater samples are adjusted to various pHs with hydrochloric.
That is responsible for reduction of the recovery rate.
Ash content transmittance Recovery rate Purity (ppm) (%) (%) (%) A 510 85.2 93.6 96.7 B 2170 67.3 99.9 90.9 According to above data, it can be deduced that purifying mother liquid by coagulation-sedimentation is effective on improving the quality of recovered TA.

Thus, another promising opportunity is a use of graphene oxide with a consequent reduction.
(a) (b) Fig. 4 (a) The influence of hole-extracting GO layer and its reduction on dark and light Cole-Cole diagrams (in log-log scale) and (b) a typical equivalent circuit for BHJ OSC determined from IS spectra (data modeling), where Cg is the geometric capacitance, Cn is the chemical capacitance, Rs is the series resistance, Rt is the resistance due to the accumulation of the charge carriers at the interface and Rrec is the resistance due to the recombination of charge carriers Table 2 Data modeling parameters and calculated values of the time constants (Rs ≈ 82 Ω, Cg ≈ 1.0 nF) Structure of OSC Cn (nF) Rt (Ω) Rrec (Ω) td (ms) tn (ms) Reference dark 1.64 240 1 130 000 0.39 1853.2 Reference light 1.85 210 1 700 0.39 3.1 GO dark 1.52 215 65 000 0.33 98.8 GO light 1.55 250 1 600 0.39 2.5 rGO_UV dark 1.66 240 24 000 0.40 39.8 rGO_UV light 1.87 205 1 400 0.38 2.6 rGO_Th dark 2.21 175 15 000 0.39 33.2 rGO_Th light 2.17 180
5 000 0.39 10.9 rGO_Ch dark 2.78 160 550 0.44 1.5 rGO_Ch light 2.29 200 250 0.46 0.6 In this regard, the results from DC measurements were confirmed by AC measurements, i.e. by IS data analysis.
The diffusion and recombination processes in prepared BHJ OSC were discussed and data modelling enabled us to determine both the diffusion and recombination time constants.
Cheng, The reduction of graphene oxide, Carbon 50 (2012) 3210-3228