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However the systematic data on the influence of the process parameters (e.g., ratio of rolls velocity mismatch, reduction per pass, friction and diameter of rolls), and the shear strain rate required to achieve a significant grain refinement in asymmetric rolling are lacking.
However the works and projects known to the authors of this paper lack the integrated data on influence of asymmetric rolling parameters (e.g., mismatch ratio of the roll velocities, reduction per pass, friction and diameter of rolls) on the shear strain values and their distribution through the sheet thickness.
Pure aluminum DIN-Al-99.7 from DEFORM-2D data base was chosen as a material for simulation.
The initial data varied within the following ranges: 1) friction coefficient on the contact with the top and bottom rolls μ = 0.08…0.32; 2) work roll radius R = 50…200 mm; 3) mismatch factor of roll velocities Kv = 1.00…3.33 (Eq. 8); 4) reduction per pass ε = 30…70%.
Influence of reduction per pass Very high values of the shear strain can be achieved by means of combination of significant reduction (ε ≥ 50%) and velocities mismatch with (Kv ≥ 2.00).

Basing on the testing data of an ambulance, a multi-input and single-output linear system model is established employing the partial coherence analysis method.
Partial testing points and data acquisition and processing equipments are shown in Figure 2.
Fig.3 A weighted SPL spectrum within frequency range of 20~300Hz Generally, the overall sound pressure of one field point will reduce accompany with the reduction of major response peaks.
Topology Optimization Design for Noise Reduction in a Truck Cab Interior[J].
[8] Bai, S., Xu, X.X., Ren, X.D., et al.Analysis of Interior Noise in a Cab and Noise Reduction with Damping[J].Noise and Vibration control, 2012,32(3):139-142.

It understands knowledge as data partition.
Data Discretization Rough set can only analyze and process the discrete data.
So need to standardize the attribute data and convert it to dimensionless data.
Then disperse the continuous data.
Attribute Data Discretization and Attribute Reduction Disperse the data in table 1 with the method of equidistance, and reduce sample data which have the same decision rules.

Along with reduction of transit performance deploys the company in recent time significantly more energy effective power units for transit of natural gas.
The advantage of remote transition of data lies in data transfer from distant facilities in real time, observation of machine operation and it evaluation. [3] One of the most important features of on-line monitoring is recording of all operation states that means start, turn off or change of rotating regime.
Automated measurement system (AMS) and it technical measurement devices, technical equipment designed for data processing, data evaluation and information means must accomplish operation characteristics according to state-of-art of continual measurement technology, record the processed results and data in digital form, assure the alerting of its failure states and drop-outs and assure recording of at least 72 hours of operating data.
Following relations are used in these calculations: NOx (mgm3)=(NOppm+NO2ppm)∙2,0527 (4) CO (mgm3)=COppm∙1,2497 (5) NOxr (mgm3)=NOx (mg/m3)∙20,95-O2ref/20,95-O2mer (6) COr(mgm3)=CO (mg/m3)∙20,95-O2ref/20,95-O2mer (7) O2 ref - oxygen reference[ 15% ] O2 mer - measured oxygen The most essential condition of automated monitoring system operation is regular check and calibration to assure confidence of measured data.
The particular turbine power reduction in this alternative is realized by automated system, using feedback of mechanical power and NOx concentration in combustion gases, controlled by automated monitoring system.

It follows from the obtained data that the hot working with the following accelerate cooling under industrial conditions does not develop a tendency toward corrosion cracking in 3% agueous NaCl solution.
This is confirmed by experimental data for the effect of steel chemical composition and heat-treatment schedules on its tendency toward ICC.
With an increase in dislocation density a tendency is observed toward a reduction in corrosion rate (Table 2).
In contrast to data obtained in [9] for a similar steel given TMP, the grain size and overall amount of carbide phase in this case has almost no effect on ICC.
It follows from data in Table 2 that steel TMP-worked under industrial conditions practically does not develop a tendency toward corrosion cracking in 3% aqueous NaCl solution.

Brief introduction of ROSETTA ROSETTA is toolkit software for analyzing tabular data within the framework of rough set theory, which is developed by Norwegian University of Science & Technology (Department of Computer and Information Science) and Warsaw University of Poland (Institute of Mathematics) to cooperate, namely, A Rough Set Toolkit for Analysis of Data.
ROSETTA is designed to support the overall data mining and knowledge discovery process: From initial browsing and preprocessing of the data, via computation of minimal attribute sets and generation of if-then rules or descriptive patterns, to validation and analysis of the induced rules or patterns.
It provides a variety of data preprocessing functions, such as decision table completion, decision table discretization and so on, but also common reduction and rule extraction algorithm within rough set [4], so its support the whole process of rules from the data pretreatment to the prediction and analysis.
The system provides the main function of a data acquisition and output, data preprocessing (decision table completion, discrete), computing (reduction), and other functions.
ROSETTA Discretization Method At present, the data obtained from the experiment mostly are continuous values, but in rough set theory, data reduction is based on discrete data table basis, therefore, for the continuous attributes discretization of real-valued attributes of decision table is a pivotal step in the pretreatment of data.

Experimental Study on Unsupported Nano-MoS2 Catalyst for Deep Desulfurization Fuel Oil Yuqin ZHU School of Chemistry & Chemical Engineering, Xian Shiyou University, Xian, China zhuyq@xsyu.edu.cn Keywords: Unsupported MoS2 Catalyst; Hydrotreating Desulfurization; Hydrothermal Reduction.
Five kinds of unsupported MoS2 hydrodesulfurization catalysts and the precursor of MoS2 catalyst, nano-sized MoO3, were synthesized by a novel hydrothermal reduction method.
Experimental materials and preparation methods Experimental materials By analysis and comparison，the hydrothermal reduction is used to prepare MoO3, the precursor of MoS2 catalyst, and the MoS2 catalyst is synthesized by the hydrothermal deoxidization.
Preparation methods Hydrothermal reduction for the preparation of MoO3 The mixture of sodium molybdate and hydrochloric acid in certain proportion was put into the inner of a reactor and it was heated from the ambient temperature to 150℃ at an appropriate speed.
Handbook of thermochemical data for compounds & aqueous species.

After determination the times of spectrum analysis data as shown table 1.
From table 1 the times of spectrum analysis data, each monitoring point was above the national minimum standard of noise.
Noise value of the main suction cabinet and times frequency spectrum analysis measurement data as shown tables 2 and 3.
Therefore, after the noise reduction transformation, the noise value of the main suction cabinet is reduction of 9.5dB.
Therefore, after the noise reduction transformation, the noise value of the main suction cabinet is reduction of 9.5dB.

But, there is the redundant in the fault data, which influence the clustering effect.
Rough Set attribution reduction algorithm can process the redundant data, and need not any prior knowledge [2].
In the paper, one condition entropy attribution reduction algorithm is chosen to reduce the fault data, and fuzzy equal relationship clustering is applied to get the fault diagnosis results, finally the examples is test the validity.
Application example and analysis On the base of the original fault data, Rough Set attribution reduction algorithm is applied to get the reduced decision table and reduced condition attribution value, and then original fault data of the reduced decision table is substituted to the fuzzy equal relationship clustering, and the fault mode is divided.
Table 1 The original fault data No.

The results of mathematical treatment of experimental data of fluorination of oxides of neodymium and iron have shown that the minimal error under linearization is given by the equation of the contractive surface.
This results in more complete reduction of fluorides, especially that of oxides, as well as better elimination of reduction smelting products.
The occurrence of moisture and volatile impurities (HF, F2, CO2) in iron and REM fluorides in the lining materials results in reduction of metal fall into ingots, quality loss and abrupt increase of pressure in the reactor during the process of reduction smelting.
If the content of the impurities mentioned is greater than 0.15%, fluorides can’t be used for reduction.
Investigation of the stage of magnet production One part of the ingots of reduction smelting alloys was used to produce magnet samples.