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How to manage energy consumption appropriately and energy saving and emission reduction are becoming crucial issue of the problem.
Research on energy consumption, conservation and emission reduction system of Beijing 1.3 Factor analysis of the system First, comparative analysis of raw coal consumption intensity has been made and shown in Figure 3.
A: Structure share B: Efficiency share On the basis of the analysis theory it could be found out that the raw coal consumption intensity analysis result is like the data shown in Table 1.
Table 1 Energy intensity of Beijing Year Structure share Primary Industry Secondary Industry Tertiary Industry 2006 -0.9336 0.0434 -0.6256 -0.3514 2007 -0.2675 -0.034 -0.4108 0.1773 2008 0.1738 0.0139 0.2541 -0.0942 2009 0.1582 0.014 0.2277 -0.0835 2010 -0.1491 -0.0198 -0.2097 0.0804 Year Efficiency share Primary Industry Secondary Industry Tertiary Industry 2006 1.9336 -0.086 0.0222 1.9974 2007 1.2675 -0.005 0.3278 0.9447 2008 0.8262 0.0075 0.4608 0.3579 2009 0.8418 0.0123 0.4653 0.3642 2010 1.1491 -0.0212 -0.6413 1.8116 Seeing from the data from Table 1, structure share reflects unreasonable industrial structure.
The data is normalized by using Min-max method.

The collected vibration signal can be used for data mining as well as obtaining fault rule based on the rough set theory.
Vibration data mining based on Rough Set theory 60 vibration signal of the rotor experimental platform sample data were analyzed, and the normalized energy as condition attributes, using fault types as decision attribute to form fault diagnosis data tables.
So we chose 80% of the data as training samples, 16 samples of each fault samples, and take the remaining 20% of the data as a test sample.
Data partition is obtained according to the above method(Table 3).
The table 4 shows that the reduction produces 37 diagnosis rules. 

Formal concept analysis and rough set theory provide two different methods for data analysis and knowledge processing.
For an initial data sets described by formal context, look for absolute necessary attribute sets by applying rough set theory.
Introduction Rough set theory put forward by Pawlak is a new mathematical method in the domain of intelligence data analysis and data mining.
As the powerful tool of data analysis and knowledge process, concept lattice has already applied widely in the domain of knowledge engineering, data mining, information retrieval, software engineering, etc[5～6].
Data sets are described by formal context exactly.

Four distinct classes of pure metal catalysts have been identified for CO2 reduction[10].
The standard potentials for CO2 reduction can be calculated from the thermodynamic data, and is shown as follows[14]: Nevertheless, CO2 reduction does not take place easily, and the actual electrolysis potentials for CO2 reduction are much more negative in most cases than the standard potentials.
They used silver cathode as the catalyst for the reduction of CO2 to CO.
Anodic half-reaction provides the protons for CO2 reduction at the cathode.
Armstrong, Reduction Potential of the CO2·- Radical Anion in Aqueous Solutions, J.

Noise mixed in the recorded seismic signals often affects the data analysis result.
In addition, the higher sampling frequency of seismic record, resulted in massive monitoring data, the application of split-based FFT algorithms to do spectral analysis of the data, reduce computation and improve the speed of data analysis than base 2FFT and base 4FFT, thereby improving the timeliness of the seismic monitoring system.
A Wavelet Packet Decomposition Technique Principle In the field acquisition of seismic data it was inevitable to contain some regular or irregular interference noise, which would have a significant impact on the geological data interpretation.
Fig4 and Fig5 were data of two channels and the denoising datas.
Fig4 Data processing of channel one Fig5 Data processing of channel two Acknowledgment This work was supported by Team funded projects of the Central Universities basic research expenses and special funds innovative projects (ZY20120101) References [1] RenXueping,Ma Wensheng, XiaoLongsong.

This reaction utilizes a high-temperature reduction using the weakly reducing hydroxyl groups of a solvent such as ethylene glycol.
Reference patterns were from 2002 PDF-2 release from the International Center for Diffraction Data ~ICDD, Newtown Square, PA, USA.
The reduction rate of Cr (VI) concentration by the two iron nanoparticle samples, respectively, was measured over time.
The free and immobilized on resin iron particles were then compared in terms of Cr (VI) reduction rate.
Figure 7a shows the kinetic data during the reduction of Cr (VI) by iron nanoparticle immobilized on CMC substrate at room temperature whereas Figure 7b shows the kinetic data resulted from free the iron nanoparticle sample.

Generally, pyrolusite can be treated by roast reduction-leaching and direct reductive leaching in acid medium [1].
On the other hand, roasting reduction in N2 is similar with that in the conventional roasters.
After the roasting reduction had been completed, the roasted product was cooled to room temperature in inert gas.
Compared with data in the literature, the roasting temperature of bagasse is much lower than that of coal [1].
These gasses provide a reductive atmosphere which promotes pyrolusite reduction.

In recent years, a variety of manifold-based learning dimensionality reduction techniques have been proposed, which attempt to project the original data into a lower dimensional feature space by preserving the local neighborhood structure.
But, when the data is distributed in a nonlinear way, LDA may fail to discover essential data structures.
LPP can preserve the intrinsic geometry of data and yield an explicit linear mapping suitable for training and testing samples.
In order construct the objective function using labeled and unlabeled data, we give total-scatter matrix and the local scatter matrix , respectively.
As a result, OSMFA is more effective and efficient in face recognition.Experiments on face data show that the proposed algorithm has more discriminative power in comparison with SDA, MFA and ODLPP.

However, for these ideals as the above, the testing data on surface structure of composite materials need to manage and analyze in some elementary, in other words, that are the testing data of mathematical or statistical models on the surface structures.
More concretely, due to the data being excessively complex, the data must be in a great extent contracted and purified to satisfy many applying objects.
Furthermore，it was indeed pointed that the effects of these data reduction modes are vary valid and significant especially in the updating age that composite material systems link closely with information network and large data, however, it is pity in some extent that there are few references on these topics at present.
At last, it should be pointed in data analysis for this paper that the element model, the picking indicator and the simulation on data are very important.
Journal of Data Acquisition & Processing, 2005,20(1): 34~39

Introduction of Shear Strength Reduction Technique The shear strength reduction technique (SSRT) is an effective way to compute the factor of safety (FOS) for slopes by numerical method.
This method has been referred to as the ‘shear strength reduction technique’ [5].
Increase the shear strength reduction factor Ftrial gradually with 0.01 increments.
Table 2 Data for stability analysis of Xietan landslide in natural state Ftrial Horizontal displacement of KP [cm] Incremental percent of the horizontal displacement [%] Difference of the incremental percent [%] 1.10 0.186 - - 1.11 0.328 76 - 1.12 0.499 52 -24 1.13 0.722 45 -7 1.14 0.984 36 -9 1.15 1.348 37 1 1.16 1.815 35 -2 1.17 2.418 33 -2 1.18 3.457 43 10 Stability Analysis of the Landslide in Long-term Reservoir Water Level Conditions.
Table 3 has indicated the data for landslide stability analysis in long-term water level conditions.