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Introduction The theory of rough sets [1], proposed by Poland mathematician Pawlak in 1982, is a mathematical method to deal with insufficient and incomplete data.
It is a set-theory-based technique to handle data, that is, through the known information to approximately describe the uncertainty concept [2, 3].
Reduction of Multi-covering Information System and Consistent Decision System Reduction of multi-covering information system.
Then we study the reduction of this case.
Pawlak, Rough sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, boston,1991

The data indicate that both cultures are able to reduce soluble iron(III) by oxidation of sulfur compounds under anaerobic conditions.
A significant pH drop from 1.8 to ~1.2 indicated oxidation of sulfur compounds to sulfuric acid in all the tested assays (data not shown).
Table 1 summarizes the data for pressure effects on growth and iron(III) reduction by the enrichment culture TK65.
When the pressure increased from 1 bar to 100 bar, cell growth was inhibited by 27 up to 39% as indicated by direct cell counts and qPCR data.
Iron(II) ions (mM) Cell count (/mL) Gene copy number (/mL) S0, 1 bar 27 1×109 5×109 S0, 100 bar 20 8×108 3×109 Summary The data show that mesophilic and thermophilic acidophiles are able to reduce soluble iron(III) by oxidation of sulfur compounds under anaerobic conditions at 100 bar.

Key Words: Mg-Sr alloys; Thermodynamics; Vacuum reduction 1.
In the melt-leaching-reduction process, the driving force kinetics for Sr reduction are very low at the reaction temperatures normally used[2].
Thermodynamics Analysis of MgO and SrO Co-reduction 3.1 Method of Gibbs Free Energy Evaluation and Establishment of Oxygen Potential Diagram All the thermodynamics data for Sr compounds and reactions involved in this paper were calculated using a Gibbs free energy function method using original data taken from the Ye-Hu thermodynamics data book.[6] The mathematical model for the evaluation of the Standard Gibbs Free Energy is ΔG Θ =A+BT (1) The oxygen potential diagram of Sr, Mg, Si and Al is plotted in Fig. 4.
The data indicates the following: (1) Tc decreases as pv decreases
H.: The practical thermodynamics data book of inorganic matter.

Knowledge reduction is one of the most important contributions of rough set theory to machine learning, pattern recognition and data mining.
So, quicker methodologies for attribute reduction are better for huge data processing.
Experiment Results In the first experiment, the uci KDDCUP99 data set is used. 10%, 20%, 30%, …, and 100% records of the KDDCUP99 data set are selected to create a testing data set each time respectively.
Half (50%) of the entire data set was split as and used as the training data set, while the remaining 50% was used as the testing data set.
This attribute reduction algorithm can process huge data sets efficiently.

From the ring-disc data and other kinetic parameters it has been assumed that the oxygen reduction occurs by dissociative chemisorption at low overpotentials.
Id data used for these plots were corrected from mass transfer interference using the procedure described by Gojkovic et al
Plots of Id/Ir vs. ω-1/2 obtained from the experimental data of the present study for the LBM catalyst at various electrode potentials have been drawn (Fig. 4).
But in view of the present RRDE data in which one observes that the end product depends on the applied potential, it has been assumed that the HO2 ion maintains an adsorption-desorption equilibrium and this equilibrium constant may be dependent on the potential of the electrode.
Suggested model for O2 reduction in KOH solution.

Some attributes of data lose in the course of data collection due to the abnormal work of the terminals.
The incompleteness of data brings tremendous difficulties to data fusion and data mining, impeding the development of computer application, especially the Internet of Things.
After getting attribute reduction, the paper improves the method for filling incomplete data based on similarity to fill the important attribute of the incomplete data.
Conclusion With rapid development of the Internet of Things, a large number of collected data are incomplete, which brings difficult to data mining and data fusion and a serious impediment to the application of the Internet of Things data.
Study on data reduction algorithm based on rough set[J]. 2011,23(7):405-413

Noise reduction.
The noise reduction and ventilation cooling is contradictory each other for urban indoor substation.
The measurement data of before and after renovation demonstrated that this renovation on noise reduction and ventilation cooling has a visible effect in meeting the national standard for noise level of the substation surrounding as well as in improving the cooling effect significantly.
It can be also seen from the comparison data before and after renovation in Table 4, the installation of indoor sound-absorbing wall can reduce indoor noise about 5-6 dB, the soundproof walls and the air intake silencer can reduce the nose about 16-17 dB of noise, which meet the predict requirements for noise reduction.
The measurement data of before and after renovation demonstrated that this renovation on noise reduction and ventilation cooling has a visible effect in meeting the national standard for noise level of the substation surrounding, as well as in improving the cooling effect significantly.

(RLB2) 12) Protection of the financial and personal data of customers.
(ETM3) Sample Design and Data Collection Data were collected using self-administered questionnaires according to service quality scale from the college students (167 of 175 copies are valid).
Factor analysis is a technique for data reduction.
It offers mathematical tools to discover patterns hidden in data.
Information-preserving hybrid data reduction based on fuzzy-rough techniques.

The method can be divided into 4 parts: dimension reduction, data segmentation, feature extraction, and feature cluster.
Methodology The cluster analysis model based on RSF is composed of 4 parts: dimension reduction, data segmentation, feature extraction, feature cluster.
Step1 Dimension Reduction In general, there are only several dimensions of the high-dimensional data are important to the underlying information.
Step2 Data Segmentation The second step is to segment the data set after dimension reduction.
Step2 After data dimension reduction, we execute the data segmentation to the 701×601×2 data set with the improved high-dimension RSF model based on level set formulation.

Finite Element Data Reduction Based Energy Release Rate for Delamination Tests S.
This is shown through two relevant aspects in delamination toughness measuring, say: data reduction and Iso-G delamination front design.
Many experimental data reductions are based on beam theories and thus assumes straight delamination front during propagation, which is not true when investigating laminates with general anisotropy.
Data Reduction Based Energy Release Rate Experimental Approaches.
This last expression (3) can be used as data reduction scheme more efficiently in delamination toughness measuring.