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Selective catalytic reduction (SCR) is a well-proven method to reduce NO emission.
Phase changes were identified by using X-ray powder diffraction technique performed on a Panalytical X’Pert PRO XRD diffractometer and the patterns were compared with JCPDS reference data.
The patterns were compared with IR Correlation Chart of Molecular Vibration reference data for some functional groups identification.
Low-temperature selective catalytic reduction of NOx with NH3 over metal oxide and zeolite catalysts—A review.
MnOx-CeO2 mixed oxides prepared by co-precipitation for selective catalytic reduction of NO with NH3 at low temperatures.

In the same figures also the uniform and fracture strain and the reduction in cross-sectional area are depicted.
For each of these trends, a visual trend line is included to help distinguish the data sets.
The strain-rate dependence on ductility can be described by the reduction of cross-sectional area in necked region observed after fracture.
These data can contribute to the improvement of the current understanding of the non linear behaviour of materials by taking into account the effect of the rate of loading and in the knowledge of the materials response to dynamic loadings.
A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures.

Neural network can greatly help the library management system, especially in data analyzing function.
Introduction Data mining is a kind of new technique that discovers and extracts the information hidden in large database or data warehouse, it can make automatic analysis and inductive inference to the data in data warehouse, and find the latent pattern; or create association and establish new business model to help the leader make correct decisions.
Data mining research and practice indicate that knowledge is hidden in the innumerable data accumulated day by day, yet it can’t be discovered only by complex algorithm and inference.
The technique of artificial intelligence, especially the combination of neural network and data mining points out a new way for the research of data mining theories and methods [1].
So for the university library value comprehensive factors as well as the different units of the survey data are relatively into evaluation index dimensionless data, and the establishment of university library evaluation index factor related equation coefficient matrix[4,5].

The unfrozen water content reduction of No.3 sample was the slowest, because it had the lowest water content and the least frost-heave and thawed amount.
(5)When the temperature of the sample met the test requirement, the NMR test was started and the test data were collected.
Fig.2 Changes of magnetization vector From NMR test data, the relationship of unfrozen water content and frozen temperature was obtained for 4 kinds of Mohe permafrost samples, as shown in Fig.3, Fig.4, Fig.5 and Fig.6.
In Fig.5 and Fig.6, under the condition of similar initial water content and density, the reduction rate of unfrozen water content of No.3 sample was lower than that of No.4 sample with the same amount of frozen temperature reduction.
Compared to the relationship in Fig.3, Fig.4 and Fig.6, the unfrozen water content reduction of No.3 sample was the slowest, because it had the lowest water content and the least frost-heave and thawed amount.

Analysis of Field Test Results By integration analysis of monitoring data of typical section, curves of horizontal and vertical displacement with time were drawn, shown in Fig.1.
By integration analysis of monitoring data of typical inclinometer hole, deep displacement curves with depth were drawn, shown in Fig.2.
When strength reduction factor is smaller, lateral deformation has less increment; and when strength reduction factor is larger, lateral deformation has larger increment.
Lateral deformation increases with increasing reduction factor.
When strength reduction factor is smaller, lateral deformation has less increment; and when strength reduction factor is larger, lateral deformation has larger increment

A retrospective study of obese patients after bariatric surgery with two years' follow-up data was conducted.
All data were analyzed by using multivariate adaptive regression splines.
Data mining in medicine can deal with this problem.
Firstly, MARS constructs a very large number of basis functions which are chosen to overfit the data initially.
Coupling with any arbitrary shape for the functions and interactions, and by using the above-mentioned two-stage model building procedure, MARS is capable of reliably tracking the very complex data structures usually hidden in high-dimensional data [7].

Tension plays a very important role in the reduction of the rolling force.
Tension can significantly reduce the rolling force, and then increase the maximum thickness reduction.
With this actual data, resistance-to-deformation is calculated by matching the measured rolling force.
2.104 11.43 76.30 72.38 0.037 3.020 8 0.62 1735.9 2.104 1.878 10.74 78.43 64.59 -0.037 3.274 Experimental actual data and regression results for the stainless steel 304 and the TRIP steel are depicted in Fig. 3 and Fig. 4, respectively.
The experimental data, such as roll gap, rolling force and roll speed, are measured and the resistance-to-deformation model is regressed.

Reduction of giga-cycle corrosion fatigue strength was 12.5%.
On the contrast reduction of giga-cycle corrosion fatigue strength of austenitic stainless steel was small[5,6].
These data for SUS329J3L can be seen above the best fit lines for austenitic stainless steels.
The reduction rate of giga-cycle corrosion fatigue strength was 12.5%.
It can be concluded that the corrosion fatigue strength reduction was due to corrosion pit formation at corrosion fatigue crack initiation site.

Currently, these roll bite peaks are approximated with Heat Transfer Coefficients ‘HTC’ macroscopically tuned on measured mill data.
DESIGN OF THE TEMPERATURE SENSOR AND DATA ACQUISITION SYSTEM (simulation analysis) An industrial hot rolling condition has been considered in the following simulation analysis: last roll revolution after 56 coils rolling on the 4th stand of a 6-stands finishing mill has been used for the following calculations: entry/exit thickness: 5.15/3.35 mm, roll speed = 7 m/s, entry strip temperature: 896°C, roll water cooling applied at entry and exit of the stand.
In agreement with previous simulation results, temperature signals during rolling have been stored using a 3.6 kHz data acquisition system.
Table 1: Pilot hot rolling test results Fig.6: Temperature signal for test n°10 Fig. 6 shows that the typical noise level on measured temperature signal is ~ +/- 0.5°C, which is a bit lower (though of same order) than the +/-1°C noise level used in simulations of the paragraph ‘design of the temperature sensor and data acquisition system’ of this paper.
a) 0.73 m/s – test n°10 b) 0.35 m/s – test n°11 Fig.11: Rolling speed influence on heat transfers –tests n°10&11 - strip reduction = 40% reduction.

Experimental Design and Data Acquisition As introduced, an experiment has been conducted under a humid tropical climate.
All of these probes are connected to a data logger (CR3000), directly or through a multiplexer (AM25T).
Figure 2: Synoptic of the data acquisition.
But, this is not the only phenomenon that is able to lead to a heat gain reduction.
The data manipulation allows to get the VCP resistance Rvcp=0.302±0.016 m².K.W-1, then the substrate (lava-rock) and vegetation (Zosya Tenuifolia) layer conductivities: λsub=0.319±0.017 W.m-1.K-1 and λveg= 0.775±0.046 W.m-1.K-1.