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Thermal reduction of phosphate ore dates back to the late 19th century when blast furnaces were used to carry the reduction with charcoal.
Analysis of thermodynamic equation in the reduction of phosphate ore by carbon The nominal chemical reaction in the reduction of phosphate ore by carbon [7] can be summarized as: (1) The equation of total gas (P2 and CO) pressure P versus reaction temperature T can be obtained by thermodynamic analysis as follows and the thermodynamic data is referred to the handbook [8]
When (C/P2O5)m is 5.0, the percent reduction is only 74.38%; when (C/P2O5)m is 8.0, the percent reduction is up to 98%, which is close to that of (C/P2O5)m 9.0.
Effect of flow rate of nitrogen gas on percent reduction.
Hu, in: Practical handbook of thermodynamic data of inorganic compounds 2nd edition, Metallurgical Industry Press, Beijing (2002), in press.

The base data of power plants are shown in table 1.
Tab.1 Base data of power plants Plant Net coal consumption rate/(g/kWh) auxiliary power ratio /% SO2 mg/m3 NOx mg/m3 EAF Net loss/% Water consumption t/h plant 1 340 6.2 390 380 0.90 6.7 800 plant 2 330 6.1 380 350 0.91 6.9 820 plant 3 310 7.2 61 310 0.92 7.1 200 plant 4 320 7.1 55 120 0.91 7.2 80 plant 5 303 7.5 65 250 0.90 7.3 350 The matrix of the original data B is: The B’ after standardized treatment is: The indexes of energy-saving and emission reduction and the comprehensive evaluation indexes are shown in table 2.
In order to compare the effect of energy-saving and emission reduction, the basic data of power plant 3, 4, 5 should be calculated.
Tab.3 Calculation data of power plants Plant Coal consumption t/h Flue gas/(m3/h) SO2 kg/h NOx kg/h Water consumption t/h Order Power plant 3 186 1116000 68 245.5 300 2 Power plant 4 192 1152000 57.6 138.2 80 1 Power plant 5 181.8 1090800 81.8 272.7 350 3 As is shown in table 3, although the coal consumption of power plant 5 is low, compared to power plant 4, the SO2 and NOx emission per hour is higher.
According to the comparison of the computational data, the proposed evaluation method of this paper can fully reflect the situation of energy-saving and emission reduction.

The effects of reduction temperature and reduction time on the removal rate of magnesium were investigated.
Therefore, the garnierite was treated by carbothermal reduction in vacuum in this paper, and the effects of reduction temperature and reduction time on the removal rate magnesium were studied.
The data of the first 120min was fitted by the least squares according to Fig. 3, and the reaction rate constant K and its correlation coefficient R2 at different temperatures are shown in Table 4.
By introducing the experimental data into the expression of the zero-order reaction kinetic model, the kinetic equation for the removal of magnesium by carbothermal reduction in vacuum from the garnierite can be obtained: 1-(1-α)1/3=(-22850.1/T+2.6296)t (3) Table 4 Reaction rate constant K and model correlation coefficient (R2) at different temperatures Model Number 1623K 1673K 1723K 1773K 1823K K(10-6) R2 K(10-6) R2 K(10-6) R2 K(10-6) R2 K(10-6) R2 D1 11.50 0.7678 14.00 0.7818 25.30 0.8006 36.00 0.9834 122.00 0.9899 D2 6.43 0.7502 7.95 0.7617 15.00 0.7725 22.60 0.9711 105.00 0.9826 D3 1.60 0.7320 2.01 0.7407 4.03 0.7424 6.43 0.9819 47.90 0.9125 D4 1.48 0.7441 1.84 0.7546 3.56 0.7623 5.46 0.9652 29.50 0.9661 D5 -2.62 0.7621 -3.21 0.7743 -5.93 0.7873 -8.70 0.9763 -39.20 0.9829 R1 13.70 0.9362 14.40 0.9276 20.90 0.9276 24.00 0.9843 75.30 0.9974 R2 43.70 0.9271 46.50 0.9167 69.60 0.9137 83.30 0.9872 348.00 0.9735 R3 33.00 0.9070 36.00 0.8929 57.50 0.8803 75.30 0.9832 643.00 0.8163
The effects of reduction temperature and reduction time on the removal rate of magnesium were investigated.

Experimental 2.1 Preparation of Mg-Sr Alloy by silicothermic vacuum reduction.
Data of time and pressure were recorded every 4 minutes during the total reduction process.
The fastest reduction rate was obtained at point C and the reduction was finished at point D.
Preparation of Mg-Sr Alloys Using Vacuum Reduction - a Thermodynamics Approach [J].
The practical thermodynamics data book of inorganic matter.

Make North Schisandra criterion and sample data as Normal-Weibull distribution to calculate similar.
Knowledge reduction method description Knowledge reduction method is based on rough set[3, 4].
Rough set methods can be applied as a component of hybrid solutions in machine learning and data mining.
Sample data y are normal distribution and standard data x are weibull distribution, the probability density function are , Where is mean of Sample data; is standard deviation of Sample data; is scale parameters; is shape parameters; .is location parameters.
After calculated, the fuzzy centre data of recommended samples are(0.06178±0.044, 0.04656±0.0102, 0.04456±0.0084); the fuzzy centre data of no-recommended samples are(0.093962±0.0757, 0.036608±0.0087, 0.024415±0.0068).

Implementation of Parallel Lanczos Method for Intrusion Detection with Cloud Technologies Bo Chen 1, a, YuleDeng 2, bandTiemingChen3, c 1Zhejiang University of Technology, Hangzhou China 2Zhejiang University of Technology, Hangzhou China 3Zhejiang University of Technology, Hangzhou China acb@zjut.edu.cn, brainerdun@live.cn, ctmchen@zjut.edu.cn Keywords:IntrusionDetection; Dimensionality Reduction; Cloud Computing Abstract.The aim of dimensionality reduction is to construct a low-dimensional representation of high dimensional input data in such a way, that important parts of the structure of the input data are preserved.This paper proposes to apply the dimensionality reduction to intrusion detection data based on the parallel Lanczos-SVD (PLSVD)with the cloud technologies.
The massive input data is stored on distribution files system, like HDFS.
Dimensionality reduction [2] is a preferablemethodto speed up intrusion detectionfor mass data.
For the PCA dimension reduction, usually only needs to take principal component accounted for over 85% of all principal components, and it is enough for get better data dimension reduction result.
Experimental detection rate and false alarm rate is shown in Table 1: Table1．The detectionrateandfalse positiverateunderthetwo conditions Dataset Normal data Intrusion data Detection rate（%） False alarm rate（%） IFCM PLSVD+IFCM FCM PLSVD+IFCM dataset 1 103510 2103 84.5 84.8 0.82 0.78 dataset 2 104120 2458 83.8 84.1 0.84 0.82 dataset 3 110250 2220 82.6 82.7 0.81 0.8 Average 105960 2260 83.6 83.9 0.82 0.8 From Table 1,we can gethigherdetection rateby using PLSVD dimension reduction algorithm data, compared to clustering directly from raw data,and maintaining a lowfalse detection rate at the same time.

Over the six data mining methods can be divided into two categories, namely direct and indirect data mining data mining.
Direct Data Mining.
Indirect Data Mining.
Rough set reduction is an important concept for data analysis.
Use reduction results, you can get a preliminary classification of fault data, the rules are diagnosed.

In addition, the pressure transducer is installed in the cylinder to monitor the pressure status while the segment is performing soft-reduction action, which could provide the necessary technical data for the normal execution of soft-reduction.
The manipulation board is used to adjust roll gap under the service mode, and to display the necessary data & important status messages.
The main control system is used to control the soft-reduction equipments, to modify the significant operating parameters, and to transfer data mutually between the L2 computer or the model computer.
The operator terminal is a industrial PC installed with InTouch or WinCC, which is used as a HMI to show the main frames, the trend curves, the alarm signals and the report forms, the other functions of which include collecting the process data, monitoring the running status, controlling the roll gap, choosing the control mode and showing the important parameters for soft-reduction.
Third, the CISDI_CCPS ONLINE (L2) was installed, the data transfer between which and instrument PLC & soft-reduction PLC was checked to be ok.

Some theories on the basis of data mining as follows: Data Reduction: In this theory, the basis of data mining is to simplify the data.
Data reduction in accuracy for speed to quickly get an approximate answer apply large database query.
Data reduction technologies include singular value decomposition, wavelet, regression, log-linear model, histograms, clustering, sampling and construction of the index tree.
For example, the pattern found in data reduction can be seen as a form or a data compression.
Data access layer is mainly related operations processing and data sources, and data source stores data the user wants to mining.

Abstract: The magneto-rheological (MR) vibration reduction control technology is studied and a design and implementation of an automobile MR vibration reduction control system based on ARM9 is given in this paper.
This system is able to achieve joint acquisition of multi-channel physical quantity of vibration and real-time control of MR damper, providing functions of online testing and acquisition of vibrating sensor signal and functions of management, storage, display and control the on-site collection data.
The controller based on ARM embedded processor, with CAN bus interface, high response speed and fine scalability, can realize transmitting the data acquired from field to the upper PC measurement and control platform through CAN bus, or receiving control information from the platform, or downloading the control algorithm, or communicating with other vehicle electronic devices in real time.
As for multiple-input multiple-output control system with PID control, fuzzy control or other control algorithms, control process contains a large amount of data processing.
Acquire vibration signal and control in real time and upload data and display vibration waveform on LCD screen; (2)Numerical display control: Acquire vibration signal and control in real time and upload data and display vibration number on LCD screen; (3)Control algorithm Setting: receive control algorithm from PC demand; (4)Communication parameter setup: receive PC command parameter, such as the communication rate,etc.