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Introduction Incineration is witness a rapid increase for treatment of Municipal Solid Waste (MSW) due to weight reduction and energy reuse [1].
Such a pre-treatment is necessary for reduction of leaching toxicity of the hazardous fly ash.
In addition, they also elaborated the leaching data for selected heavy metals (Cr, Cu, Pb and Zn) obtained from sequential monolith leach tests with a pseudo-diffusional leaching model in order to identify the release mechanisms of such heavy metals and to predict the long-term leaching behavior of cement mortars.

The dsPACE hardware was employed to data acquisition from coil and make switching signals to the circuit.
In frequency domain there were almost 15dB reduction from uncontrolled beam structure.
In frequency domain self sensing method showed nearly a 15dB reduction in the vibration of the first mode of cantilever.

The slow-speed of saw blade shaft is selected and the average of the recorded data is taken as a final result.
This study provides a theoretical basis for the design of blade noise reduction, it also provides a basis for the selection of circular saw application.
Research on noise of circular saw blade: Characteristics of vibration and noise reduction technology [J].

· Persistent Event logging: no loss of data after power down · Event Logging History: better analysis of errors and event dependences · Fully automatic installation algorithm for both profiles: self-adjusting of profile relevant Hardware construct design The EDCS consists of one printed circuit board with integrated: input filter/ burst and surge protection, power supply, microprocessor system[3], serial (RS422) and discrete interface, 3-phase inverter power output, as shown in Fig.1.
Frequency inverter power plat design The inverter power plat consists of an ESD protection circuit, surge current reduction, an EMC reduction circuit , an uncontrolled full bridge rectifier, the DC Link (buffer capacitor), the 3 phase inverter and current/voltage sensors.

Fig.1 The dam cross section design The design of discharge and velocity of a debris flow is in accordance with 20 years rainfall (P = 5%) standards, the specific data are shown in Tab.2.
(5) In the formula: -the uplift pressure ( kPa ); H1-the dam upstream water depth(m); H2-the dam downstream water depth (m); B –the base width ( m ); K-the reduction coefficient of permeability ,0.8.
Tab.4 The overall impact of debris flow calculation （t/m3） (m/s2) (m/s) sinα (kPa) 1.648 9.8 14.85 0.87 1.33 429.1 (7) In the formula: -the impact force of debris flow; -the reduction coefficient of kinetic energy, 0.3; -the stone movement speed; W -stone quality; -the angle of debris flow impact force between the dam stress surface; -the rock elastic deformation coefficient, .

However, the algorithm in determining the fuzzy density value, the use of a priori training data is static information, that is, after the end of the training to each individual SVM classifier training accuracy of each individual to give that support vector machine classifier important degree of fuzzy density values, its individual support vector machine classifier of the corresponding fuzzy density values ​​are the same for all of the test sample is fixed, a static fuzzy density of areas.
(1) Table 1 shows the AFSAMICBag, the literature [6] algorithm and the proposed adaptive fuzzy integral algorithm of support vector machine ensemble comparison of classification performance can be seen: Tab.1 Comparison of classification precision（%） Data collection AFSAMICBag algorithm In [6] Algorithm OLCP LCCP vehicle 89.71 89.46 89.77 89.82 waveform 92.97 93.31 94.55 93.69 tic 88.56 88.45 88.75 88.93 diabetes 79.87 80.58 80.74 80.87 heart 85.83 85.31 85.69 85.65 sonar 91.49 91.48 91.98 92.25 A. defined in two ways OLCP and LCCP adaptive fuzzy integral on the support vector machine ensemble classification performance in all data sets were higher than those in [6] based on the static fuzzy integral algorithm of support vector machine ensemble, This shows, according to the individual support vector machine classifier treated samples measured classification performance of the local adaptive fuzzy definition of a more accurate description of the density of each individual support
Fig.1 Comparison of relative bias among three ensemble algorithms It can be seen: A. two methods based on fuzzy integral support vector machine ensemble algorithms have a certain level of bias and variance reduction, which reduces the magnitude of difference is greater than the other side than on the magnitude of bias reduction; Conclusions This paper analyzes the integration of the three metric learning algorithm layers the advantages and disadvantages, studies show, in which the integration based on fuzzy integral learning algorithm to obtain the integrated approach than the Bayesian inference theory of integration methods and evidence better classification results.
Of the standard UCI data sets and StatLog test results can be seen, the proposed algorithm to further improve the integration of test performance.
The deviation from the expected error variance decomposition point of view come, although the bias reduction algorithm is not very obvious, but can effectively reduce the variance.

Adopting Japanese evaluation train derailment safety C limit value (that is, derailment coefficient=1.2, wheel load reduction ratio=0.67, lateral wheel-rail force=78kN) as the standards to evaluate the train running safety on rail-bridge during earthquakes.
When the earthquake intensity increased from 0.05g to 0.2g, the vehicle speed limit decrease from 265 km/h down to 23 km/h, a decline of 91.3%; (3) Derailment coefficient, wheel load reduction ratio and the lateral wheel-rail forces are all likely to become the vehicle derailment critical state control parameters, which also reflects the randomness of vehicle derailment.
Fig.3 Comparison between interpolation curves and simulation ones From Figure 3, one can see that the interpolation data curves are consistent with the simulation data curves.
This indicates that the Lagrange interpolation data meet the accuracy requirements of numerical interpolation.
Fig.4 Comparison of interpolation data ​​and specification values From Figure 4, it can be seen that the ground motions have greater influence on trains passing by the simply supported rail-bridge during earthquakes.

., S1 with mgb = 1 and mtj = 1/64) analogously a reduction in the number of grains together with an increase in the grain size can be observed as shown in Figure 2a.
Plotting the mean edge length of each grain versus its relative size, we observe a wide scattering of the data (Fig. 3b).
The data of vs. x for all grains with a certain number of faces s show a strict linear relationship.
The data of all grains with the same s are plotted in Fig. 3b with the same symbols labelled by s.
A reduction of the mobility of triple lines and quadruple points leads again to a reduction of the velocity of growth, where with decreasing mobility the simulated curves become linear over a long range of time.

Previously, studies were conducted in which was justified the choice of the chemical composition of the experimental alloy [20-25], computer models were developed, the modes of hot rolling of model ingots on a laboratory mill of DUO 330 are calculated and tested, and also received data on mechanical characteristics and structure of metal.
After that, temperature, speed and time modes of rolling were introduced, according to the parameters of the industrial process, and with the help of the DEFORM-3D software complex, an array of data was obtained on rolling passes, which included: - the dimensions of rolled products depending on the single reduction; - the temperature of the metal; - forces and moments of rolling.
The authors of this paper showed that when hot-rolled of ingots, the values of the Cockcroft-Latam criterion are the fastest approaching the maximum value at the edge of the rolling stock with a total reduction of more than 70%, which indicates the possibility of forming and further development of microcracks in this section of the slab.
Analysis of data on the metal forming, temperature and velocity parameters of rolling, as well as stress-strain state of the metal obtained in the simulation is described in detail in [20].
The data of experimental studies of the structure and properties of cast, deformed and annealed semi-finished products from the experimental aluminum alloy P-1580 make it possible to recommend the developed technology for industrial development, since the level of mechanical properties of these semi-finished products with a minimum content in the scandium alloy is comparatively high and comparable to high-alloy aluminum alloys such as 01570.

The result showed that: the reduction of energy intensity in the past decades was attributed to the improvement of industries’ energy efficiency, especially the improvement of secondary industries’ energy efficiency.
Based on analysis on dynamic characteristics of energy intensity in three industries of Anhui province from 1995 to 2009, decompositions of energy intensity’s dynamic change was investigated proceed year by year, by the Laspeyres model. 1 Research Method and Data Source 1.1 Disaggregation Model Disaggregation model is one brand-new and mature analysis approach based on input-output techniques.
(7) 1.2 Data Source Using the data of statistic books, GDP , triple industrial value and energy consumption from 1996 to 2009 were collected in Anhui.
Then, according to the given data, energy strength our industrial structure in different phases were calculated. 2 Variational Trend of Energy Strength in Anhui Table 1 shows the variation of energy strength of our industrial structure from 1995 to 2009.