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Rare earth Halide Reducing metal ∆H298 in Kcal per gram atom of halogen Ca Mg K Al NdCl3 -10.6 +8.0 -19.7 +29.0 NdF3 -8.4 +5.1 +2.1 +31.1 The data were computed by Quill.
Experimental Procedure In pyro-metallurgical reduction a well-blended mixture of neodymium fluoride, iodine and calcium metal chips is charged into a reduction chamber, which is lined with dry calcium fluoride powder.
Thermal Reduction or Pyro-Metallurgical Process.
Reduction of NdF3 to neodymium metal was carried out in a bomb sealed reactor.
Gray, The production of pure cerium metal by electrolytic and thermal reduction processes, Trans.

The classical metal-organic Frameworks CuBTC showed remarkable low temperature activity in selective catalytic reduction of NO with NH3 (NH3-SCR).
The nature of the active Cu species among CuBTC in NH3-SCR based on the activity data were characterized by TEM, XPS, XRD, EPR and IR.
In this paper, CuBTC was synthesized by hydrothermal method and used for selective catalytic reduction of NO with NH3.
The activity data was recorded when the catalytic reaction practically reached steady-state condition at each temperature.
Conclusions The CuBTC catalysts showed remarkable low temperature activity in selective catalytic reduction of NO with NH3.

Model Validations Test Computations of the averaged drag coefficients and Strouhal numbers for a single cylinder at Re=200 and Re=5.5X104 for three dimension are carried out and the results compared to the published data to validate the computational method.
The result shows that the tripping rod has a better control effect for force reduction at higher Re.
All this phenomenon relate to the drag force reduction.by C.H.Kuo.et.al[9] Fig. 3.
This optimum angular position was found to be 40° for Re=200 where the drag coefficient is reduced by 21%,while for Re=5.5´104 the optimum position is 30° and the drag coefficient is reduced by 36%.The effect of tripping rod for drag reduction is more effective at high Reynolds number is in good agreement with previous experiment data.
“Numerical study of Fluid Force Reduction on a Circular Cylinder Using Tripping Rods”.

There can be many reductions of.
So, means all the reductions of.
Intersection set of any reduction is a sole kernel.
Thus the minimum attribute reduction is obtained.
The implementation tool is the data mining software WEKA.

Based on a user-defined range of parameters (module, helix angle, etc.) the software presents a large number of possible solutions covering the full parameter space and presents a list with many data (geometry, safeties, characteristics as sliding, losses, price, transmission error) including a qualification of every solution based on required characteristics.
KISSsys windows of the Gearbox-Variant-Generator User Interface: Provides for input of required torque and speed Sizing: Includes the various sizing functions and functions for user data input Table of Variants: List of the different reducers, of which any solution can be selected Solutions: 3D display of main results for the 90 reducer variants calculated Optimization of a Compact Micro-Planetary-Gearbox The tool was used in a project for a Chinese company, producing small compact gear reducers with a high speed reduction.
The design data for one of the required gearbox was: Output speed 31 rpm and 16 Nm torque.
Therefore, the required total reduction is i = 160.
The design data for the gearbox was: Input speed 15 rpm and output power 3.2 MW.

Rough set theory has powerful data reduction capability, this paper rough set theory to model the stock time series data, reduction, rule extraction, study the ups and downs of the relationship between the stock price, the use of advanced data mining techniques to dig out price linkage between stock association rules, has a very important significance.
In these data, a large part of the data type of the sequence of the presentation time (time series).
Clearly, data mining is such a tool.
Rough Set Theory has a good effect in processing the large amount of data and eliminate redundant information, and it is widely used in data mining, data preprocessing (data reduction), rule generation.
In addition, time series data mining, too much energy focused on the prediction of future data trends.

The principle of the method was presented and then we compared the results obtained by the new method to the experimental data measured by Marla et.al [3] and Bresee and Ko [4].
Substitute the data of Fig. 4a into Eq. 2, the fiber diameter reduction distribution along the spinning line can be obtained.
Fig. 4b shows the fiber diameter reduction obtained by the geometry method.
However, our result fits the diameter reduction measured by Bresee and Ko very well.
(b) The diameter reduction calculated by the geometry method and the compared data from Marla et.al [3] and Bresee and Ko [4].

By using the data mining method to preprocess the communication data, we reduce the amount of data and shorten the data process time.
So the function of the data preprocess include removal of erroneous data and data conversion.
The aim of dimension reduction is to get rid of the attributes which have nothing effect with our data mining result and improve the speed of computation time.
In the process of dimension reduction, it is usually used attribute subset selection to get the proper subset for data mining.
The algorithm of minimal subset discovery is used to discover the optimal subset in the process of data dimension reduction.

Dependability of the relative sulphide oxidation rate from oxidation-reduction potential (versus Ag/AgCl).
Table 1 contains data on biocake mineralogy in the feed reactor 1/5 of BIO-1, where the potential was 600mV and in the feed reactor 1/2 of BIO-2, where the potential was 540mV.
These data confirm the impact of oxidation-reducing potential on the sulphide minerals oxidation rate.
Data in the table 1 fully comply with data on Fig.1.
These data clearly demonstrate the impact of oxidation-reduction potential on the oxidation rate of sulphide minerals.

Due to the possibility to collect a huge amount of production-relevant data [8], it is possible to use methods of data mining to obtain more insight into assembly processes and subsequently to identify top consumers and focus stations for example for energy saving projects.
This new data flow enables real-time tracking of energy consumption as well as long-term analysis and advanced data mining for e.g. quality improvements.
The data for the average and standard deviation of this program is shown in Table 2.
By using power measuring instruments, it is very important to generate a large number of data to confirm data accuracy, since power measurement has significant uncertainties.
This data mining approach aims to improve product and process quality.