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In order to further understand the Agave americana var. marginata electrical signals in High Voltage Pulse Stimulation conditions, a new method is provided in this paper by using wavelet soft threshold noise reduction and the power spectrum analysis.
The laboratory temperature 29-30 ℃, humidity 62% -65% RH, the sampling frequency is 20Hz, the low-pass filter frequency 5Hz, measured data points is 4096.db7 with 7 layers of wavelet decomposition of the signal, the noise is calculated based on the signal strength, draw global threshold, then apply the global soft threshold for signal noise reduction.
After the noise reduction signal, estimate the power spectrum and analyze the variation of plants at different voltage electrical stimulation.
Conclusions Wavelet soft threshold noise reduction for inclusion in the plant electrical signal has played an important role in well eliminates noise and power spectrum analysis can clearly understand the plant electrical signal frequency components.

The CO emission purification efficiency data of the DOC+CDPF+SCR system shows in Fig.4 Fig.4 The purification efficiency of CO (DOC+CDPF+SCR) As is showed in Fig.4, the percentage of the CO purification efficiency is about 60% and it increases with the increase of the temperature.Also the purification efficiency is more than 50% in most working conditions.
The NOx emission purification efficiency data of the DOC+CDPF+SCR system shows in Fig.6 Fig.6 The purification efficiency of NOx (DOC+CDPF+SCR) The conversion efficiency of SCR exists from 30% to 80%,when the exhaust gas temperature is over 250℃，the NOx purification efficiency of the SCR system is more than 50%.
Fig.9 shows the data curve of the equilibrium temperature of CDPF.
Fig.9 The data curve of the equilibrium temperature of CDPF Conclusion The purification performance of the diesel exhausts four-effect catalytic purification system which consists of DOC, CDPF and SCR is tested through the methods given in this paper.
[2] “A kind of low temperature ammonia selective catalytic reduction of denitration catalyst preparation method”, Application number: 201010539716.0[P]

H2-TPR (Temperature-Programmed reduction) TPR used the GC method with a thermal conductivity detector.
The reduction mixture gases were purified using a 105 deoxidizer and silica gel; flow-rate of the mixture of H2 and N2 was 40ml/min.
In this work, the specific surface area of these carriers forα-Al2O3, cordierite andγ-Al2O3 ,respectively, was ～12m2/g, ～6m2/g,and ～140m2/g.Those data indicated that the surface area of α-Al2O3 was further twice as large as that of cordierite, so the activity of L-S-C-O/α-Al2O3 was better than that of L-S-C-O/cordierite.
Fig.2 The XRD patterns of samples Temperature-programmed Reduction The TPR profiles concerning pure carrier, pure active component and a few kinds of prepared catalysts were given in Fig.3, which showed that a few kinds of pure carrier had not any high reduction peaks suggesting the carrier was unable to be reduced at range of experiment temperature (under 700℃).
Then there was a small reduction peak of carrier γ-Al2O3 at 550℃, probably hydroxyl reduction peak.

A Computational Approach for the Assessment of Seismic Vulnerability based on the National Data Infrastructure Gabriela M.
The algorithm considers all the possible tests that can split the data set and selects a test that gives the best information gain.
In order to gather the entropy gain of all these binary tests efficiently, the training data set belonging to the node in consideration is sorted for the values of the continuous attribute and the entropy gains of the binary cut based on each distinct values are calculated in one scan of the sorted data.
These data correlated with data on the real earthquake accelorograms identified from the national seismic database have the basics for the decision tree induction algorithm.
M. (2006), Data Mining Methods for GIS Analysis of Seismic Vulnerability, Proceedings of the First International Conference on Software and Data Technologies, ICSOFT 2006, vol. 2, pp. 153-156, INSTICC Press, Portugal, 2006 [5] McGuire, R.

(1) Sediment reduction amount by ditch management measures.
Sediment reduction amount by ditch management measures is the sum of silt storage dam and reservoir, sediment reduction amount by reservoir is 37.52 million m3 in 1980s,if the sediment dry density as 1.4t/m3, the sediment reduction amount is 52.53 million ton, the sum of sediment reduction amount by reservoir and silt storage dam is 0.171 billion ton
(2) Sediment reduction amount by slope management measures.
The sediment reduction amount by ditch management measures is 0.171 billion ton, the sediment reduction amount by slope management measures is 92 million ton.
Based on the hydrological sediment data, under the condition that the rainfall reduced by 13% in 1980s, compared with the basis period, the sediment reduction amount had reduced to 0.65 billion ton, under the condition that the rainfall reduced by 15% in 1990s, the sediment reduction amount was 0.56 billion ton.

The stiffness reduction is caused by two phenomena.
But partially it could be highlighted by the data measured in Norway, which was published in [5]: Table 3: Determination of microfibril angle by small-angle X-ray scattering.
Fig. 6: Elastic modulus determined by nanoindentation.Using the data measured in Norway, they are presented in Table 3 and Fig. 6, the proposed formula of coeffred was validated.
It is seen, that presented formula matches the Norwegian data pretty well.
The reduction formula was derived introducing some assumptions.

Incorrect cooling, however, can lead to heat unbalance in the die casting tool, thus causing the destruction of casting quality, reduction of the lifetime of die casting tool and irreversible production-reduction.
Thermal data is given in tables.
For each calculation only 1 parameter was changed, for the others general workshop data were applied. 2.
Given and calculated data are presented in table 4.
In production these are the most varying parameters and this is why it is justified to continuously monitor them with data collection systems [5-6]. 4.

This article aims to carry out a study on defining an indicator to improve the energy efficiency of machine tools through the acquisition of energy data in real time.
No methodology has been found in the literature for developing indicators related to energy efficiency or for acquiring data related to it.
In summary, data about the process (status, number of parts, rpm…) are acquired from machine variables, whereas the energy variables are acquired from another element.
These elements are connected to an industrial PC, in this case the C6015 from Beckhoff, which is responsible for collecting the data and storing it in the cloud.
Thanks to this implementation, real time data about energy consumption and machine process can be acquired.

Subsequently, predictions of heat release rate, as well as NO and soot emissions are compared with experimental data.
Experimental data are available for these engines [1].
The predicted cylinder pressure trace falls in very good agreement with the experimental data.
Conclusions The software created meets the requirements (combustion modelling), i.e. to estimate the in-cylinder pressure with a 2-5 % error from the measured data.
Accurate data is need for the calibration of model constants.

Based on the measured data, the change of mechanical properties of cold-worked alloy AMg6 during the process of short duration heating was evaluated.
Based on the received measurement data the level of strength properties of the cold-worked AMg6 alloy articles during the process of long after deformation holds was predicted (Fig. 2).
Comparison of the results of the prediction of the yield strength with long-term exposure for products with a yield point of 294.3 MPa () and for a product with a yield strength of 304.1 MPa () with experimental data Analyzing obtained results it is possible to evaluate the influence of temperature and heating period on the intensity of strength properties level decrease of cold-worked alloy АМg6.
At 300°С hardening effect reduction (in resistance in rupture) by 50% is observed after 10 minute heating up.
One hour heating at 200°С leads to 50-% reduction of effect in yield point.