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In the smelting reduction stage, the reaction temperature was set at 1550℃.
The composition of (Cr2O3) and reduction rate of Chromium are shown in Table 3 and Table 4.
This means after 34 min’s reduction, all of the Nickel had been recovered into iron-bath, and the reduction rate is nearly 100%.
The data confirmed all of the dephosphorizer got the advantageous effect on the dephosphorization process.
[3] Bauer K H: Recycling of iron and steel works wastes using the Inmetco direct reduction process [J].

The research studies the influence of soft reduction of a slab on the inner structure of a billet.
Soft reduction of the slabs was carried out in the 12 and 13 segments of the secondary cooling zone.
Change in the content of phosphorus and niobium in thickness of slabs cast with soft reduction () and without reduction (): the position of the upper freeze line (------) at the time of the start (1) and the end (2) of the soft reduction application The figure shows two vertical dotted lines characterizing the position of the upper freeze line inside the work piece at the beginning and the end of the soft reduction.
These data were obtained by calculation using the dependence of the square root.
Data on the maximum value of zonal chemical inhomogeneity degree of tube metal impurities, cast with soft reduction , and without external impact These data allow concluding that the maximum value of the degree of zonal inhomogeneity of most impurities is higher in the cobbled metal than in the metal without external influence.

The quantitative data of phases are summarized in table 1.
The quantitative data of phases by Mössbauer spectroscopy.
The quantitative data of phases, 1:12 average hyperfine fields for NdFe11Ti, NdFe10.5Mo1.5 and NdFe10.75Mo1.25 as-prepared.
The processing parameters, quantitative data of phases and magnetic properties of samples are summarized in table 4.
(see TC data in tables 4 and 5).

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.

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.

They can not yield a simple yet effective mapping function for the new coming test data sets.
Classification performance on Iris data set.
The following two real-world data sets are all from the UCI machine learning repository [11].
Influence of data normalization mode.
The proposed MML has nothing to do with specific data.

Study on the Lining Erosion of Deep Reduction Electric Arc Furnace in Smelting Metallized Pellets Process Produced by Vanadium Titanium Magnetite Qi Jianling1, a 1 PanGang Group Research Institute Co., Ltd. , State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization, Panzhihua 617000, Sichuan, china ) aqijianchou123@126.com Key words：deep reduction electric arc furnace；refractory; erosion Abstract.The erosion of the lining refractory of the deep reduction electric arc furnace is introduced, and the erosion appears in the process of smelting metallized pelltes produced by vanadium titanium magnetite.
Introduction A pilot plant was constructed in PanGang in 2009 which applied Rotary Hearth Furnace (RHF) and deep reduction Electric Arc Furnace (EAF) to deal with vanadium titanium magnetite.
Fig.1 Analysis of lining erosion mechanism Arc erosion of the deep reduction electric arc furnace (EAF) The electrode diameter of the EAF is 2200mm and the distance between outer edge of electrode and the lining is only 550mm.
However, the charges of the deep reduction EAF are the metalized pellets, and in order to improve the TiO2 content in the slag, it does not adjust the basic of the slag and the value of CaO/SiO2 is just around 0.2～0.3.
Handbook of chart data about steelmaking[M].

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.

J.W.Park et al [16] who used coal-based direct reduction process to research the direct reduction of iron in the hot mill sludge.
The carbon (50.47%) was the main active reagent in the direct reduction process.
Effect of reduction time on the iron recovery of lead slag was shown in Fig. 5.
Fig. 6 Effect of reducing agent ratio on iron recovery The recovery of iron in lead slag is mainly achieved by reduction reaction, which includes direct reduction and indirect reduction with coal as reductant.
Fig. 7 Effect of CaO ratio on iron recovery From data shown in Fig. 3, the values of Eq. (4) and Eq. (5) are always less than that of Eq. (1)and Eq. (2), indicating the increasing possibility of reduction Fe2SiO4 and Fe2AlO4 to metallic iron after adding CaO into the mixture.

Gene expression data usually have only a dozen or a few dozens of samples, but hundreds or even more than a million feature variables, if we classify the data directly, often fail to get good results, so for such a large data, dimensionality reduction becomes a key to the success of gene data classification.
High-dimensional data reduction method Data dimensionality reduction has played a more and more important role in research recent years.
Map high-dimensional data to low-dimensional space, and low-dimensional data can reflect the information in the original high-dimensional data, this is called data dimensionality reduction[2].
PCA is short for principal component analysis, it is a linear method which compresses data through the covariance matrix of the data, integrate the original data to extract the comprehensive variables which reflect the information of the original data best, comprehensive variables extracted are called principle component, the principle component is usually a linear combination of the original data[3].
In this study, the first 38 group of samples as the training data, the latter group of 34 samples as the test data, using two methods for testing, one is the non-linear Laplacian Eigenmaps dimensionality reduction combined with SVM (linear kernel function) classification, the other method is the linear dimensionality reduction PCA dimensionality reduction combined with SVM (linear kernel function) classification.