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To optimize the reduction technology, kinetic model of SSI reduction was established.
The main objectives of this study are: (1) to establish the kinetic model of SSI reduced by hydrogen on the basement of unreacted core model, (2) to analyze the restrictive key through calculating effective diffusion coefficient De and chemical reaction rate constant k according to the reducing data, and (3) to provide basement for optimization of reduction technology.
Reduction of SSI Spherical Sponge Iron (SSI) with 1~5 mm diameter was prepared through the process of palletizing, roasting and direct reduction by H2.
Thus the oxidative pellets reduction, with higher intension and ferric oxide content was ferric oxides reduction.
To optimize the reduction technology, kinetic model of SSI reduction was established on the basement of unreacted core model in this paper.

The Study of Synchronous Reduction-carbonization of V2O3, Cr2O3 and W-Co Composite Oxides in Fluidization Nanyan GONG，Yafei OUYANG Diamond Road, Zhuzhou, Hunan, P.R.China GONGNY@126.COM , OUYANGYAFEI123@126.COM Key words: VC,Cr3C2, Fluidization, Reduction-carbonization Abstract.
Theory Analysis Thermodynamics calculation of synchronous reduction-carbonization of vanadium.
Thermodynamics computing of synchronous reduction-carbonization chromium.
The chemical compositions of composite powder are shown in Table.3 after reduction-carbonization of composite oxide in fluidized bed.
Practical manual with thermodynamics data on mineral.

Data mining analyze the great amount data of CRM to make reactions in electronic commerce.
It is a platform based on C/S mode, which contains data pretreatment, the building of data warehouse, data mining and management of the content of E-mail.
Data pretreatment is to clean the data, to do the integration and transformation, and to do data reduction.
After data pretreatment, data is stored in data warehouse for data mining.
Data mining: For the data source provided by data warehouse, we build the mathematical model, train the data and finally get the rules for the website platform according to the target of the system and the paper.

The data obtained when the experimental samples breached, in which the intense influence of the aggressive medium was carried out during Δt=10 days didn’t show any significant changes.
The obtained data at break of the experimental samples, in which the intense influence of the aggressive medium was carried out during Δt=30 days, determined the decrease in the strength of the welds, prone to forced corrosion, in relation to the usual ones by 5-8%.
The obtained data at break of the experimental samples, in which the intense influence of the aggressive medium was carried out during Δt=100 days, determined the decrease in the strength of the welds, prone to forced corrosion, in relation to the usual ones by 10-15%.
Experiment data for welds
Experimental data for reinforcing rods

To date no experimental data is available about the dynamic temperature profile for refinery sludge gasification in an updraft gasifier.
In order to measure the temperature profile inside the gasifier and classify the gasification reactions zones, five type-K thermocouples connected to data logger (USB TC-08) and the readings of the temperature are logged in the computer.
In gasification, reduction reaction is the prefered.
Combustion is also important as it sustain the endothermic reduction reaction.
Obrenberger, “Updraft- Fixed Bed gasification of Softwood Bellets: Mathematical Modelling and Comparison with experimental data,” in European biomass Conference and Exhibition, 2009, no.

However, no literature data concerning the process of obtaining cobalt nanoparticles with the use of surfactants have yet been found.
Results and discussion The experimental data have stated that the process of Co(OH)2 reduction in nonisothermal conditions was developing in three stages (Fig. 1): I – removal of adsorbed moisture; II – elimination of structured water with Co3O4 compound, proved by the X-ray phase analysis data; III – reduction of oxide to metallic cobalt.
According to the X-ray phase analysis data, all metallic samples consisted of the phase α-Co (table).
According to BET data, nanopowder surface was increasing in “CPCl - EDTANa2 -PEG - SLS” surfactants, achieving its maximum value for the sample obtained from hydroxide precipitated in an anionogenic surfactant solution.\ The results obtained by the electron-microscopic analysis correlate with the specific surface analysis data (table).
Phase composition and dispersity of obtained cobalt nanopowders Surfactant-containing aqueous solution for obtaining Co(OH)2 (surfactant concentration – 0.1 wt.%) Phase composition X-ray data S, [m2/g] BET data Average particles size dav, [nm] BET data SEM data No surfactants α-Co 4.5 148 123 EDTANa2 5.0 134 94 SLS 9.5 70 55 CPCl 3.7 183 116 PEG 6.0 112 98 We have conducted a microscopic examination of the metallic cobalt samples obtained from the Co(OH)2 precipitated with the usage of different surfactants (Fig. 3).

Meanwhile, the power grid enterprises energy-saving diagnosis work and energy-saving emission reduction work of demand side management are prospected.
In August 31, 2011, the State Council of China promulgated the “Twelfth Five Year Plan of Integrated Energy-saving and Emission Reduction Work Program”, which produced a definite “Twelfth Five Year Plan” energy-saving and emission reduction major requirement and target.
The field detection points mainly include power quality monitoring points, conventional electronic parameter monitoring points, and heat monitoring points of 3 types of points, and the test item, detection time, detection method, and detection instrument accuracy are respectively stipulated in detail, for those reports of abnormal operation, outmoded production equipment, or the equipment which have energy-saving technology transformation potential founded in previous finish of forms, and the system implements special field measurement operation data collection work, etc.
This part mainly includes two parts: the rational use of energy settings and energy-saving amount calculation in each industry, the data of evaluation analysis, which is mainly from the collected materials and field testing, then is counted based on the standard “Energy Saving Amount Audit Guide of Energy-saving Project”.
While the count of light energy consuming is based on the data from real time monitoring or the electricity bill from power supply department.

Data preparation.
Data preparation is broadly divided into three steps : data integration, data selection, data transformation.
While also cleaning data, including noise data, such as missing data and abnormal data processing.
Data selection.
Data reduction and transformation.

Nanjing Jiangsu China 210000 a E-mail:hh4166@sian.com b E-mail:tq19880626@yahoo.com.cn Key words: Yunnan; carbon emission; low carbon economy; influence factors Abstract:The paper uses a large amount of data uncertainty analysis of a the Yunnan "12th Five-Year" period of low-carbon development, pointed out that economic development, eliminate backward production capacity, energy consumption and energy saving will be contradictions, and the main problem of the reality of low-carbon development in Yunnan.
According to the GDP and carbon emissions data from 2005 to 2010 in Yunnan province, using the method of regression analysis, analysis the relationship between the carbon emissions and GDP in Yunnan province , and to predict the " 12th Five-Year Plan" GDP carbon emissions and its trend.
estimates Years GDP (billion) Carbon emissions (tons) Carbon emission intensity (tons / million) 2005 3461.73 11033.71 3.19 2006 3988.14 12633.91 3.17 2007 4772.52 13714.67 2.87 2008 5692.12 13813.07 2.43 2009 6169.75 15267.3 2.47 2010 7224.18 16183.33 2.24 2011 8750.95 18217.09 2.08 2012 9808.36 19546.89 1.99 2013 10993.53 21037.36 1.91 2014 12321.92 22707.95 1.84 2015 13810.82 24580.39 1.78 Energy-saving emission reduction target to calculate in the period of " Twelfth Five-Year Plan" in Yunnan Using the regression model, on the basis of data in " 2011 in Yunnan statistical yearbook ", put the GDP gross, the unit GDP energy consumption reduction rate and energy consumption of 2010 in Yunnan to the formula, obtained energy saving and emission reduction predictive value during "Twelfth Five Years Plan" ( see Table 4 ).
Table 4 Yunnan Province during the "12th Five-Year" energy-saving emission reduction estimates Index In 2010 In 2015 GDP（One hundred million yuan） 7224.18 13810.
The uncertainty about the lack of long-term mechanism of energy-saving emission reduction “Eleven five”period, China's energy saving and emission reduction for pollutant discharge standard uncertainty, especially to ensure energy-saving emission reduction economic policy flaw, caused the " 12th Five-Year Plan" energy-saving emission reduction difficult.

According to the low efficiency of vegetable leaf image data mining problems, proposed an improved algorithm based on Apriori algorithm to get greatly related groups.
(1).experimental environment: server: P42．0GHz, 4G memory, SQL Server2000; ; client: P4 3.9 GHz, 2G memory (2). the experimental data pretreatment: choose 563 slice of cucumber downy mildew blade using photoshop tools separation, a total of 2457 pieces of disease spot, disease spot image connected data of image region, Obtain the original data, the following table 1 Table 1 Cucumber leaf disease spot image characteristics disease spot Area A Color C Brightness B Location P Premeter G gray median H Shape R 0001 1.16 brown 70 central 1.23 146 elongatd 0002 1.24 Green 78 edge 1.17 161 triangle 0003 0.05 light 100 central 1.41 123 circular 0004 0.55 light green 91 edge 4.65 128 triangle (3), using the improved Apriori algorithm support degree or more than 30% of the maximum correlation set {ACHR}, showed that degree of victims has nothing to do with brightness, location, but relates with area of shape, color, grayscale average, significantly
But for image data preprocessing, how scientific dynamic partitioning discrete interval, and not to divide the discrete artificial fixed interval is thin, is not conducive to dig up rules, so using coarse intensive algorithm to conclude mining rules, make the mining results more scientific.
The concept of data mining, and technology [M].
Large data set based on rough sets and genetic algorithm of data mining application research [D].