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The obtained isotherm data are regressed by a new isotherm model.
Data acquisition and reduction are performed by Quantachrome HydroWin software.
It also illustrates the data regression by the new model of Equation 1.
The present data are displayed with 5% error bar.
The present data are displayed with 5% error bar.

Introduction Data quantization is one of the preprocessing techniques used frequently in data mining, machine learning and knowledge discovery [1].
Formally, given a data set .
Step one: Compute the level of consistency according to [3]; Implementation of PCA and MLE on input data; Normalize each continuous dimension to [0,1]; Mean-centralize each dimension and compute covariance matrix of data set X; Projected data set Perform PCA algorithm with the ID on the input data set.
A summary of data sets can be found in Table 2.
This can be attributed to information loss owing to dimension reduction and the weak correlation structure in ‘Glass’.

Low field data at 6 MV/cm suggest a lifetime of half a year.
Data measured at 375 °C is also plotted for comparison.
Our data measured at 375 °C is plotted for comparison.
Singh et al. projected a reduction by 1.5× based on the reduction of band offset.
This is where the data get confusing.

The operator could aquire the test data by the electronic load and work station operation software in the industrial computer.
Two 3-way switching valves were used to screen the water-bubbler when anode reduction of the NiO to Ni was carried out.
The operator could aquire the test data by the electronic load and work station operation software in the industrial computer (Fig.3).
Fig. 2 Process flow diagram of the SOFC single cell test device Fig. 3 Framework of system data acquision Fig. 4 Key test structure in sample room The size of SOFC single cell for testing was 5×5.8cm2 with an active area of 4×4cm2.
The reduction of NiO anode was performed under mixed flow stream of 0.1SLM H2 and 0.4SLM N2 for more than 5 h.

The R*-Tree is used to index the spatial data of the network.
Additionally, the new data are different from the historical data, for the new one is given higher weight than that of the old one.
The efficiency of the structure also results from the possible reduction of dimensionality of the trajectory data to be indexed
The efficiency of the structure also results from the possible reduction of dimensionality of the trajectory data to be indexed.
Change tolerant indexing for constantly evolving data.

This suggests faster reduction rate.
Parallel reactions, e.g. hydrogen generation, also compete with metal reduction for the amount of reductant.
In the present system, the main oxidation reaction is the oxidation of hydrazine: N2H4 + 4OH- à N2 + 4H2O + 4e- (1) On the other hand, the primary reduction reactions are Cu deposition and H2 generation: Cu(II) + 2e- à Cu (2) 2H2O + 2e- à H2 + 2OH- (3) where Cu(II) represents all possible Cu species since there is an insufficient thermodynamic data to calculate the redox potential Cu oxyanions and hydroxyanions.
This indicates faster reduction at lower concentrations of gelatin.
As a result, less Cu(II) ions are available for reduction.

The catalytic activity in the hydrogen oxidation and oxygen reduction reactions was measured using IPC Pro MF potentiostat (Russia).
Sizes of Pt and Pd nanoparticles with AF-9-6 and AOT according to AFM data Surfactant NPs d, nm ω = 1.5 ω = 5 ω = 8 АОТ Pt 2.6-3.4 4.5-6.8 6.2-9.0 Pd 5.0-6.5 7.9-9.1 9.3-10.7 AF-9-6 Pt 2.2-2.8 3.0-4.2 5.5-6.7 Pd 4.4-5.5 5.7-6.9 6.8-8.2 From the analysis of the data in Table 1, it can be seen that the minimum particle size is characteristic of systems synthesized with nonionic surfactant – AF-9-6.
Table 2 shows data on the comparison of the sizes of Pt and Pd nanoparticles obtained with nonionic (AF-9-6) and anionic surfactants (AOT) in the composition of Pt/Nf and Pd/Nf metal polymers.
According to SEM data, the average size of palladium and platinum nanoparticles varies from 3 to 9 nm (Table. 2) for ω from 1.5 to 8, which is consistent with the data obtained by atomic force microscopy and the smallest particle size is characteristic of samples formed with AF-9-6 and ω = 1.5.
Size distribution of Pt and Pd nanoparticles on the Nafion according to SEM data.

Based on data of shake table tests, regression analysis by least squares method is adopted to analyze the natural frequency and the damping ratio of a new isolation layer.
Shaking table test is the best method of simulated earthquake and reflects seismic reduction effect of the device directly.
Experimental data and calculation methods are needed to obtain the parameters.
In engineering practice and scientific experiments, experimental data need to be fitted into the empirical formula to reflect the relationship between variables.
Based on the experimental data, regression analysis by least squares method is adopted to analyze the natural frequency and the damping ratio of a new isolation layer.

Fig.1 The free suspension way of the machine The experiment equipments include several ICP type acceleration sensors, one force sensor, one vibration exciter, one power amplifier, LMS modal analysis experiment data acquisition front and the computer data processing software LMS Test.lab Spectral Testing.
Fig.2 The principle of the test system Data analysis and experimental results.
This paper uses the PolyMAX algorithm in the LMS software to analysis the modal data, the first three order natural frequencies and damping ratio of the sewing machine are shown in table 1.
The sewing machine is running from the operating speed of 500r/min to 4000r/min, read the vibration data of the standard point for per additional 100r/min, and 41 accelerating response data is carried out.
Industrial sewing machine vibration and noise reduction technology[D].

The reduction in radius.
Consequently, the 360 of data of reduction in radius can be obtained whenever the calculation of a whole revolution (360 steps) of workpiece has been finished.
Repeating this cycle for five same workpieces and measuring their roundness with a roundness measurement instrument give five data of roundness.
The average value of the five data is then regarded as the roundness under the given geometrical arrangement.
After resetting the geometrical arrangement and performing the same grinding and measuring process as above described, other data of roundness are obtained for the corresponded conditions.