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Introduction Dimensionality reduction is an efficient method to handle the complicated high dimensional data commonly met in our modern society and widely explored in data mining, machine learning, pattern recognition and etc.
locally linear embedding(lle) Given a data matrix ,where, represent the data points in the space.
Conclusion Dimension reduction is a very effective method to deal with high dimensional data and widely explored in pattern recognition, data mining, machine learning and etc.
LLE has been regarded as the classical non-linear dimension reduction algorithm because of this good performances on real data and artificial data.
Niyogi, Laplacian eigenmaps for dimensionality reduction and Laplacian eigenmaps for dimensionality reduction and data representation, Neural Computation 15 (2003) 1373-1396

Plenty of basic research, including spot investigation and data collection, was carried out in this paper.
Through extensive field research and data collection, the present paper identifies 18 types of typical energy saving technologies in cement sector, takes daily 5000 tons production line as the benchmark, makes quantitative analysis of the emission reduction potentials and costs in cement sector based on the marginal emission reduction cost estimates, and thus proposes policy recommendations for technical development.
This study combines emission reductions and economic benefits, which is the emission reduction cost mentioned above.
It embodies the relationship between the emission reductions achieved by each emission reduction measure and the costs needed in per ton of CO2 emission reduction.
Discussion on cement sector CO2 emission reduction in China.

Therefore, a rough calculation method about carbon emission reductions of separation collection was summarized here, with reference to the domestic and foreign empirical data of carbon emission reductions in the waste management.
Besides, carbon emissions by recycling are influenced by the reprocessing technology, the type of energy as an alternative, and the use of different basic data.
Moreover, the commonly used calculation methods of carbon emissions are based on the volatile data of each waste component, which is more often established by the study of waste in European and American.
Table 1 The composition of MSW in Guangxi in2010 [%] Composition Organic matter Inorganic matter Others Kitchen waste Waste paper Bamboo Fiber Plastics Rubber Glass Ceramics Metal Dust Mass percentage 46.6 5.2 1.3 9.8 0.9 1.9 0.2 30.9 3.2 Note: Data is from the "The second Five-Year Plan of waste disposal facilities construction in Guangxi".
Table 2 Adopted value of carbon emissions during the operation/process of waste treatment [kg CO2-eq.t–1] Operation type Collection/ transportation Landfill Biological treatment Recycling Within a distance of 20 km High organic waste Low organic waste Anaerobic digestion Waste paper Waste wood Waste plastics Waste glass Waste metal Unit carbon emission 20 675 -25 -132 -3125 -220 -528 -485 -9260 Note: The -related data about carbon emissions were derived from references [1~10].

Reduction Kinetics of Iron Ore Materials by Gases A.N.
In particular, recently at the Institute of Metallurgy of the Ural Branch of the Russian Academy of Sciences a balance logic-statistical model of the blast furnace process [1] has been used which is based on the use of material and thermal balances along with statistical data and the most significant regularities of heat exchange and balance conditions of iron oxides with a gas phase.
Calculation of non-uniformity of distribution of gas on top radius As the initial information the practical data about distributions 2CO and temperature of gas on radius of top are usually used.
In the mathematical model, there is the possibility of using any types of distributions as on practical data and by expert.
As the initial data the following are used: the furnace characteristics, composition and properties iron ore raw materials, limestone, coke, blasting parameters, factors of non-uniformity of the gas stream, coordinated with the profile of charge level (a site of an ore crest, its height).

The results show that rolling reduction ratio has significant influences on C2S2 procedure.
Table 1 lists the geometry, materials and simulation data for the simulation.
Table 1 Data for the numerical simulation Geometry data Central distance of each pair rollers, (mm) 80 Initial work-piece thickness, (mm) 4 Initial work-piece width, (mm) 20 Rolling reduction ratios 5 %, 10 %, 20 % Bending channel thickness, (mm) 3.8, 3.6, 3.2 Output channel cross-section (mm2) 4×20 Die channel angle, (°) 92.7 Die outer corner angle, (°) 0 Materials data Young’s modulus, (Gpa) Work-piece (5052Al) Rollers and others (H13) Poisson’s ratio, 68.9 206 Thermal expansion, (˚C-1) 0.33 0.3 Thermal conductivity, (N s-1/˚C) 2.2E-5 1.4E-5 Heat capacity, (N mm-2/˚C) 180.2 32 Emissivity, 2.433 3.588 Simulation data 0.7 0.5 Roller angular velocity, (rad/s) 0.1 Time step, (s) 0.3 Initial temperature, (°C) 20 Environmental temperature, (°C) 20 Friction factor, 0.7 (rollers), 0.03 (others) 5052Al was used as the work-piece material that was hypothesized as a plastic body.
It is important to note that, contrasting with the rolling reduction ratio of 5 %, the rolling reduction ratio of 10 % produced only very slight reduction in restoration ratio, while the rolling reduction ratio of 20 % produced a far larger reduction in restoration ratio.
Contrasting with the at the rolling reduction ratio of 5 %, the at the rolling reduction ratio of 10 % and 20 % is respectively 8.16 % and 8.32 % less.

Reduction of GO by NaHTe.
These XPS data indicate that the oxygen-containing functional groups have been partially removed after reduction.
XPS of Te-GO2 Summary A mild and efficient reduction system by using NaHTe as reducing agent for reduction of graphene oxide is described.
This reduction was carried out at room temperature.
Cheng, The reduction of graphene oxide, Carbon 50(2012)3210-3228

The metal and slag in sponge iron obtained from reduction was melted and separated.
The sponge iron obtained from reduction was melted and separated.
At 950℃,1000℃, the reduction experiment was carried out respectively, so as to determine the time of complete direct reduction.
Results and discussions Results and discussions of direct reduction Data of direct reduction is shown in Table3 and Fig2, in which, weight loss is the weight difference between re-concentration minerals and sponge iron.
Data of direct reduction experiment Sample # Temperature/℃ Holding time /h Weight of sponge iron /g Weight loss w/g 1 950 1.0 284.14 56.86 2 950 2.0 269.23 71.77 3 950 3.0 264.05 76.95 4 950 4.0 263.99 77.01 5 1000 0.5 290.55 50.45 6 1000 1.0 278.96 62.04 7 1000 1.5 270.82 70.18 8 1000 2.0 270.91 70.09 Fig2.

“Energy saving and emission reduction” problem has drawn worldwide attention.
Most of these studies are based on the technology of energy saving and emission reduction in a certain machinery or industry, while studies concerning energy saving and emission reduction conditions of the whole society are few.
Modeling Optimization Model of Carbondioxide Emission Reduction.
The model to evaluate the optimal energy consumption structures is: (2) Results and Discussions Based on the relevant data of China [7], two optimization models can be solved.
Based on the data in Table 1, the carbondioxide emission reductions of each major sector are evaluated in Table 2.

The key parameters of soft reduction technology includes: total reduction, reduction position and reduction ratio, reduction rate for the designated areas.
On the premise of determination of position in soft reduction, we analyze the macrostructure test, central segregation index methods according to the measured data.
The relation between total rolling reduction and reduction ratio[7]: Total rolling reduction = (1) Where:— total rolling reduction/mm; —reduction ratio/mm·m-1; —length of soft reduction/m。
Reduction rate means the rolling reduction during unit time.
Reduction rate is an important parameter for devices of soft reduction.

Vorovskogo, 13-7, Chelyabinsk, 7454094, Russian Federation abilgenova@susu.ru, bgamovpa@susu.ru, croshchinve@susu.ru Keywords: solid-phase reduction, direct reduction, indirect reduction, anionic vacancy, cation, quantitative estimation.
The direct reduction of metals from a complex oxide with low iron content by solid carbon and indirect reduction by CO gas were studied in a vertical laboratory resistance furnace at 1300 °C for an hour reduction time.
Introduction The complexity of the process of metal reduction from solid oxides by carbon is associated with the fact that there is no a single reduction mechanism which could be valid for all cases of the metal reduction.
The data about the area of each reduced iron particle, the total number of iron particles, the average size and the area of the total metal was obtained as a result of processing of the panoramic optical images of surface of the samples’ sections, Table 1.
At the same temperature and time of reduction, the reduction by CO gas led to the reduction of the metal with total area 1373.33 - 1851.55 μm2 with average size of every particle 1.87-1.32 μm2.