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The paper make a analysis of coal enterprises' inputs and outputs on the green mining, establishment of evaluation system of green mining, using the data envelopment analysis(DEA), to establish the model of coal enterprise's green mining of efficiency evaluation, and application in practice.
Based on the analysis of the input and output data, DEA can get each DMU efficiency quantitative index and DMU grading sort, determine the effective DMU, and point out non-effective reason and degree of other DMUs.
In addition, in order to ensure the data authority and reliability, in the data collection process, the coal enterprises related data is references
In order to meet the requirement of the model and exactly reflect green mining efficiency of the coal enterprise , from the two aspects of literature research and data availability , this paper use the index used to analyze the input and output index of green mining of coal enterprise .
Specific data as is shown in table 1.

Introduction It is extremely desirable to acquire high-quality data from vibration tests for many areas of applications.
The effect of noisy data on the success of many applications in vibration engineering has been an important subject of research.
Pickrel [1] focused on the assessment of the quality of the data and used the singular value decomposition (SVD) technique to estimate the effects of frequency band, number of measurement locations and signal-to-noise ratio in measured response data.
Reference [1] Pickrel C.R., in: Estimating the rank of measured response data using SVD and principal response functions [C].
[12] Tufts D. and Shah A., in: Estimation of a signal waveform from noisy data using low-rank approximation to a data matrix [J].

Therefore the noise reduction of echo signal is an important step about the detection of the leaving time.
In view of the above problems, a noise reduction algorithm based on the minimum statistics noise estimation [4] is presented in this paper.
Composing of the test system The test system consists of an infrared launcher, a special radar, a power-supply and a data acquisition instrument.
The test sustem After putting the test device in the correct positions, when the first projectile fires, the emerging flame launch the infrared detecting instrument, data acquisition instrument begins to collect data of radar echo.
When the projectile enters the radar beam, a data acquisition instrument can collect data of the projectile echo until the end of the experiment.

GeoChip data pre-processing.
Raw data obtained using ImaGene were uploaded to our lab’s microarray data manager (http://ieg.ou.edu/microarray/) and pre-processed using the data analysis with the following major steps: (i) Spots flagged as poor-quality by ImaGene 6.1 and with a signal to noise ratio [SNR, SNR = (Signal Intensity-Background) / Standard deviation of background] less than 2.0 were removed.
Preprocessed GeoChip data were used for further statistical analysis [6,9].
In total 13 elements were detected in two AMDs (data not shown), which included S, Ca, Mg, Fe, Al, Mn, Na, Si, K, Cu, P, Zn and Ni.
There are a total of 134nif genes for nitrogen fixation, 285 genes (ureC and gdh) for ammonification, 31 nasA genes for assimilatory nitrate/nitrite reduction, 330 genes (amoA, amoB and hao) for nitrification, and 289 genes (narG, nirS, nirK, narB, norB and nosZ) for denitrification across four samples (data not shown).

The network data was obtained and modeled on NEPLAN software for simulation and technical evaluation of the networks.
The study concluded that a further reduction in technical losses was achieved with an increase in system efficiency.
The data for the purpose and analysis is taken from [15]. 2.
R ∝ L A or R = ρL A (4) Where R is the resistance of the conductor, L is the length of the conductor, A is the area of the conductor, ρ is a constant depending on the nature of the material of the conductor and is known as its specific resistance or resistivity The load data and line data for modelling the Ajilosun 38-Bus distribution network is shown in Table 1 and 2.
The line parameters used for the extension of aggregated load points in the simulation model is given in Table 3, and the transformer reactance data used in the modelling is given in Table 4.

Data cycles are the life blood of a development effort.
Figure 2: Effective Cycle Time Targeting Take for example, the data in figure 2.
HOW TO LOOK AT CYCLE TIME Yield department: Everyone is engaged in defect reduction: Inline defect data can also be backward looking.
Defect data is immediately fed back to those who can impact defect performance.
In-line data is fed back to the tool owner as quickly as it is collected.

The measurement time for each curve of infiltration capacity is about 100 minutes, the time interval of measurement is about 1-5 minutes, and the data number of each curve is about 30.
Thus, the total data number of measurement is about 720.
Based on these data, the infiltration capacity curves corresponding to different initial soil moisture content conditions for the three test grasslands are drawn and shown in Fig.1-3, where Fig.1 is for grassland A, Fig.2 is for grassland B and Fig.3 is for grassland C.
However, some data points having similar moisture content values occur abnormal, for instance, the initial infiltration capacity corresponding to the initial soil moisture content of 27.20% is larger than that corresponding to the value of 27.17% for grassland B.
Possible runoff reduction caused by infiltrating of LID-type road greenbelt.

Based on the characteristics of RDF data, we propose to compress RDF data.
RDF data storage, to RDF data compression, the longer URI prefix mapping table stored in the prefix.
We use LUBM generator provided data sets of different size, size of the data shown in Fig.5.
Jena and RS_Opti over 500M memory overflow data when the result cannot be obtained, and the methods used herein 500M of data on the data shown in Table 1 These experiments show that the proposed algorithm can better handle the large-scale data, the complexity of data for small queries better algorithm optimization.
Optimize SPARQL by combining semantic reduction and selectivity estimation[J].

The reduction of tin ions according to [11] is a reversible diffusion-controlled process.
Polyanionic complexes and complexes with choline chloride reduction the most suitable form of linearization was the use of √τ↔1 / i coordinates, which corresponds to the reduction from the coating layer.
Based on a comparison of the data obtained, we propose a scheme of the process, including as the current density increases, the tin ions reduction directly from the electrolyte (1, Figure 3), the trichlorostanite complexes transition to the polyanionic coating layer (2, Fig. 3), followed by reduction (3 Fig. 3), the polyanionic layer conversion into a mixed one, with the participation of the choline cation (4, Figure 3), followed by restoration (5, Fig. 3): Fig. 3 Scheme of the process of reduction of tin ions from an ionic liquid At stage 5, at current densities of 20-30 mA/cm2, the electrocrystallization formed crystallites encapsulation conditions are created, which is a necessary condition for forming highly disperse metallic powders.
The tin ions reduction mechanism from a choline chloride based ionic liquid depends on the current density and includes: the trichlorostanite complexes reduction at current densities up to 5 mA/cm2; reduction from a polyanionic adsorbed layer at current densities of 5-12 mA/cm2 and reduction from a mixed layer including polyanions bound and by electrolyte ions at current densities exceeding 12 mA/cm2. 2.
The reduction rate from the polyanionic layer is less than the its growth rate, the reduction and growth rate for the mixed layer are comparable.

Overall noise reduction result is difficult to meet the expected goal.
In this paper, a full-scale diesel engine model was established, and the model is calibrated with the experiment data.
With this model, the noise and vibration reduction were analyzed.
Fig.1 Thermodynamics and acoustics model of single cylinder diesel engine In order to simulate the actual working state accurately, the diesel engine numerical model is calibrated with the experimental data.
The model is calibrated with experimental data.