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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.

Increasing O2 concentration can also improve the catalytic reduction efficiency.
It is clearly seen from both figures that once the engine is switched to DF-PCCI mode, CO emissions are substantially higher and OEM DOC is ineffective while exhaust temperatures from each combustion modes are very similar (data are not shown here but the reader can find more details in [8]).
Ranges of each parameters employing in DOE are chosen based on data from NEDC.
However, if exhaust temperature is up to 250oC, CO reduction efficiency can reach up to 100 % (case12-15) as well.
Reduction efficiency significantly improves after exhaust temperature is up to 250oC.

The paper analyzes the fuel-switching project for district heating and main pollutant reductions, emission reductions of atmospheric particulate matter are calculated by materials accounting method.
The economic, environmental and social benefits are also calculated according to pollutant reductions.
In this paper, reductions of the pollutant emissions have been calculated and the co-benefits have been analyzed.
Reference to the literature [4,5] get the data of the residential layer burning wet de-dusting boilers as Table2 : Table 2 Data of the layer burning boiler Combustion mode The dust of the coal The bottom ash in the total ash Proportion of particulate matter in the flue gas Removal efficiency Layer burning boiler 0.084 0.85 0.80 0.13 0.07 0.99 0.90 0.50 This project only consider the residential heating boilers, so A is the coal consumption, is 44.72t.
Suppose this project only use one control technology, so , and , from calculations, all the particulate matter emissions can be obtained from Table 3: Table 3 Result of three kinds of particulate matter emissions Particulate Matter 0.0126 [t/t] 1.008 1.638 4.41 [t] 450.78 732.51 1972.15 The emission reductions of particulate matter: Natural gas as clean energy, regarded as no particulate emissions after burning, so the emission reductions of TSP is 3155.44t, the emission reductions of PM10 is 2704.66t, and the emission reductions of PM2.5 is 1972.15t.

According to the engineering geological and geophysical data, field outcrop on UDL Archeozoic Fuping group put a shop group (Ar3f ) biotite plagioclase gneiss, from top to bottom has weathered, strong weathering, weathering in three kinds of soil properties.
The toe of slope changes first; with the strength reduction, slope displacement develops gradually, eventually leading to the failure.
Extracte every reduction coefficient F, using software z-soil to calculate, we can achieve the distribution of plastic zone of the slope to observe the plastic zone’ development.
With the strength reduction factor F increasing gradually, plastic zone located at the toe of the increases gradually, and slowly extent to the top.
When the reduction coefficient F=1.0, plastic zone is produced at the slope toe.

Currently accepted definition of data mining is that: knowledge acquisition is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns in data [9].
It can be used as the data source for configuration rules.
(7) Reduction of the rules, then add the rules into fuzzy rules library.
(2) The characteristics of simulation data are discussed, so that we could deal with the simulation data with the algorithm of fuzzy rough set
Kamath, in: An Introduction to Scientific Data Mining, edtied by Institute for Pure&Appl.

As 2 waste-water treatment stations operation results have shown, during the passed 6 years, annual sludge reduction ratios (per tons product) reach 43.64% and 50.29% respectively, realizing 105.6 thousands tons of sludge reduction effect and 68.04 millions CNY economic benefits.
The results show that sludge pellet reduction, reduction swelling index, compressive strength and leaching toxicity to meet the requirements, but its softening melting property is poor.
Therefore, the sludge pellet and sinter ore, lump ore are mixed by the ratio of 10:85:5, and its softening melting property is 1508 ℃ with the melting interval is 111 ℃, the maximum differential pressure is 3103Pa, meeting the requirements of blast furnace. 3)Sludge amount reduction effect During Sept., 2010~Feb,2014, sludge amount reduction technical transformation project have been carried out with 57,576 tons sludge reduction achievement(based on the basic data that per ton steel produces 50.18 kg mixed sludge, theoretical sludge amount is 114,487 tons,while actual sludge amount is 56,911 tons), reduction ratio reaches 50.29%,and annual sludge reduces 16,450 tons.
Based on the basic data that per ton steel produces 17.49 kg mixed sludge, during Sept., 2011~Feb,2014, theoretical sludge amount is 93,594 tons,while actual sludge amount is 60,503 tons, sludge reduction ratio reaches 35.36%,and annual sludge reduces 13,000 tons. 2)Recovery of waste sulfuric acid : During Sept., 2011~ Feb,2014, 5224 m3 waste sulfuric acid has been taken out from wastewater to produce polymeric ferric sulfate (water purifying agent), obtaining multiple benefits, such as wastewater neutralization agent saving, sludge amount reduction, acid raw material purchase cost saving,etc. multiple benefits. 4.
During the passed 6 years(A Plant, 2.5 years; B Plant, 3.5 years), annual sludge reduction ratios (per tons product) reach 43.64% and 50.29% respectively, realizing 105.6 thousands tons of sludge amount reduction and 68.04 millions CNY economic benefits.

This paper analyzes the status quo of study of rubber asphalt overlay noise reduction and mechanism.
Cao Weidong and Ge Jianmin equal to study the skeleton dense noise reduction road in 2006.
Field testing of road noise In this noise test, we selected freeway A and highway B and secondary roads C that before and after asphalt overlay as a total of four a field data.
Chart 3 Cement road noise to detect normal chart of secondary road C From Chart 2, we can conclude that on the secondary roads cement concrete pavement, noise data collected basically meet the normal distribution.
Chart 4 Rubber asphalt road noise detection normal chart of secondary road C Noise data was detected from the Cement Concrete Pavement thin layer of rubber asphalt pavement after paving 5cm.

Research on the Orthogonal Test of Tunnel Supporting Parameters Based on the Finite Element Strength Reduction Method Pengli He Luoyang Institute of Science and Technology Luoyang Hena 471023 China hepengli2003@126.com Key words: orthogonal test; strength reduction finite element; safety factor; numerical simulation; support parameters Abstract: In this thesis, considering the double-hole parallel tunnel engineering with super-small interval, the optimization of designed supporting parameters are studied by the strength reduction finite element method.
Strength reduction orthogonal test method of finite element Finite element strength reduction [1-2] is through the strength reduction to analyze the structure stability, until the structure to achieve critical state so far, this time the reduction coefficient is safety coefficient required by the structure.
The tunnel overall safety coefficient can be got by finite element strength reduction computation under each of the supporting conditions.
But the comparability between the test data will be found if they are fit together.
Based on the finite element strength reduction of double holes parallel tunnel construction simulation and parameters optimization design [D], 2005, (in Chinese) [6] Rongheng Sun.

Mn/Ba/Al2O3 indicated high activity of NO oxidation and NOx storage in the oxidation-storage reaction and certain reduction activity in the storage-reduction reaction.
Table 1 Catalyst formulations Catalyst Pt loading/% Ba loading/% Mn loading/% Mn/Ba/Al2O3 — 15.0 5.0 Pt/Ba/Al2O3 1.0 15.0 — Mn/Ba/Al2O3-Pt/Ba/Al2O3 0.5 15.0 5.0 Mn/Ba/Al2O3+Pt/Ba/Al2O3 0.5 15.0 5.0 2.2 NO Oxidation-storage The NO oxidation-storage activity data were obtained using a conventional fixed-bed flow reactor at atmospheric pressure.
The storage-reduction reaction performed 2 h, namely 10 cycles.
NOx storage-reduction catalysts for gasoline engines.
NOx storage-reduction over combined catalyst Mn/Ba/Al2O3-Pt/Ba/Al2O3.

The required input data are rolling speed, roll radius, furnace temperature, initial and final height of the specimen, and specimen width.
Experimental Data used in validating the new hot rolling simulation was obtained through preliminary metallographic, hot torsion tests, and hot rolling experiments performed on the as-received wrought AISI316 (with Nb, V and Ti inclusions) in the temperature range (600-1200) OC and strain rate range of (3.6X10-3 - 1.4) s-1.
Program Validation The hot rolling experiment performed on AISI316 provided a data base for assessment of the validity of the simulated model.
Fig.2: Effect of Reduction on Yield Stress distribution at Low and High Strain Rates 50 100 150 200 250 300 350 0 0.94 1.94 2.94 3.94 4.94 5.94 6.94 7.96 8.96 9.96 10.96 11.96 12.96 13.96 14.96 15.96 Specimen Height, mm Yield Stress for Load Calculation H37, Strain Rate = 0.08, Reduction = 6.27% H39, Strain Rate = 0.08, Reduction = 14.54% H41, Strain Rate = 0.09, Reduction = 19.35% H43, Strain Rate = 0.09, Reduction = 22.77% H38, Strain Rate = 1.00, Reduction = 6.67% H40, Strain Rate = 1.17, Reduction = 15.21% H42, Strain Rate = 1.28, Reduction = 20.15% H44, Strain Rate = 1.37, Reduction = 24.43% Fig. 3, revealed a uniform pattern of rolling load distribution with specimen through-thickness from the rolling surfaces.
Also, the ratio of experimental to estimated roll load and torque were higher at lower reduction than at higher reduction.