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NO reduction efficiency depends strongly on the redox process of iron/iron oxides.
Fig 2 NO reduction efficiency by iron Fig 3 Durable reaction of NO reduction by CO/CH4 in simulated flue gas at 1050 ˚C A durable test of NO reduction by iron in N2 atmosphere was conducted at 800˚C since the NO reduction efficiency was almost 100% at 800˚C (refer to Fig 2).
This showed that CO was not good reductant for NO reduction by iron in durable application.
NO reduction quickly increased to over 98% as CH4 was fed.
NO is chemically reduced to N2 by iron according to the following reaction: Fe + NO®FexOy + N2 According to the thermodynamic calculations using data from the JANAF tables (1985), it is possible for metallic iron to be completely oxidized to Fe2O3 when NO volume fraction is less than 0.05% at 700-900 ˚C.

Design of the reusable data reduction tool Data set is a collection of data, is the object of data mining.
Data reduction tools can be called by data mining system can also be called by other cloud applications platform to access heterogeneous data.
The design of reusable data reduction tool.
The development and implements of data reduction tool on cloud computing platform.
Then test data set is to verify the effectiveness and efficiency of data reduction tool.

The soft-reduction segments with remote roll gap adjustment functions (the key devices for implementation of soft-reduction action).
The servo hydraulic control system with high control accuracy for soft-reduction (the hydraulic drive system for implementing action of soft-reduction).
The soft-reduction basic automatic control system with high efficiency in the implementation (The electrical control system for implementing action of soft-reduction).
The L2 model database has been debugged, we have confirmed the database structure and the variable set, we have also defined the relationship of data communications between L1 basic automation program and L2 process control model and improved the database functions to test and verify the normalcy and stability of L2 model database.
As Fig.1 shows, it is the macroscopic comparison of the JB45 and JB50 steel grade produced without soft-reduction and with soft-reduction, and the details lie in Table1.

Reduction of forming stage is the most effective approach for reduction of manufacturing cost and time of such multi-stage forming parts.
However, if there is not enough data in advance, the system can not provide the optimum process design.
Stage reduction by using numerical optimization Fig.1 shows the idea of stage reduction to obtain the optimum multi-stage process design.
   (7) Result and discussion Optimization and stage reduction.
Here the further stage reduction from 2-stage to 1-stage is discussed.

Based on the involute theorem, the gear data of helical spur gear pair is obtained.
According to the gear data, its corresponding engineering drawing is accomplished.
Based on the involute theorem, the gear data of helical spur gear pair is obtained.
Then, according to the gear data, its corresponding engineering drawing is accomplished.
According to the gear data, its corresponding engineering drawing is accomplished.

According to the statistical data, the disposal cost of excess sludge was very high and held the 25~65％ of the total operating cost in the STPs in the developed countries while the disposal facilities of sludge held the 60~70％ of the total construction cost [1].
Fig. 1 Schematic diagram of process for the reduction of activated sludge by ozone.
Hajsardar et al. [24] studied the reduction efficiency of sludge in a SBR process by the ozonation.
Table 1 The reduction efficiencies of excess sludge by the ozonation under the different conditions.
Choi, Ozonation of wastewater sludge for reduction and recycling, Water Sci.

At this point, nation-scale carbon related data are critical.
This paper introduced the acquisition of soil, vegetation and land use/land cover data at a large scale using remotely sensed data and the simulation of carbon sink/source by means of ecosystem models.
In the process of obtaining these data, remote sensing is an indispensable important mean.
These data are mainly come from remote sensing, land inventory, etc.
In these studies, remotely sensed data leveraged its strengths.

For the independent variable, according to the study of W.P.S.Dias et al.[2], the optimum models can be given by the raw data, and the non-dimensional ratios does not result in good models.
The discovery of a certain property allows us to describe the information of the universe, or to predict the unseen data in the future.
Alternatively, a property can be understood as a previously unknown pattern to be discovered by a data analysis task, for example, an association of attributes, a cluster of objects, a set of classification rules, a preference ordering of objects, or the similarities or differences among objects.
The theory of rough sets has been applied to data analysis, data mining and knowledge discovery.
Slowinski: Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory (Kluwer Academic Publishers. 1992) [5] Z.Pawlak: Rough Sets-Theoretical Aspects of Reasoning about Data (Kluwer Academic Publishers, Dordrecht. 1991)

The calculated roughness is close to the measured data.
The results from the FEM simulation will be compared with the experimental data that used the same rolling and profile parameters.
Fig. 8 shows a comparison of the simulated surface roughness with the experimental data.
It can be seen that the calculated results are Oxide scale Steel close to the experimental data.
The results of the simulation are compared with the experimental data to verify the effectiveness of the developed model for calculating the surface roughness transformation.

Previous studies of total factor productivity (TFP) mainly focus on time series data concerning economic aggregate.
Methodology and data Methodology.
Data.
The sources of capital stock data are based on the perpetual inventory method, proposed in Zhang et al (2007) [9].
The rest data come from “China Statistical Yearbook” and “China Energy Statistical Yearbook” from 1995 to 2008.