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The analysis results indicated that with the increase of the depth of hinge joints, the transverse tensile stress, vertical shear stress and longitudinal tension stress were all showed regular distributions, and with the increase of the depth of hinge joints from 10cm to 26cm, the maximum reduction value of transverse tensile stress in hinge joints was 3.25MPa, the reduction range was 51.9%; the maximum reduction value of vertical shear stress was 1.06MPa, the reduction range was 77.9%; longitudinal compressive stress decreased gradually, and longitudinal tensile stress increased; the maximum reduction value of hinged plates deflection difference was 0.16mm, the reduction range was 36.4%; the transverse tensile stress of hinged plates’ bottom increased.
There was no definite provision of hinge joints depth in code, considering the thickness of plates were 30cm, the value range of hinge joints depth was 10cm~26cm, the data interval was 4cm, so there were 5 value of depth can adopted, the analysis of each depth including centre load and side load.
It was unnecessary to analysis all data of every hinge joints, the hinge joints of maximum stresses were enough.
For point 1, with the depth of hinge joints increased from 10cm to 26cm, the reduction values of stress were 0.74MPa, 0.63MPa, 0.43MPa and 0.26MPa respectively, this shown that with depth increasing, the impact of transverse stress on top of hinge joints by depth of hinge joint decreased gradually.
With the depth of hinge joints increased from 10cm to 26cm, the reduction value of transverse tensile stress was 3.25MPa, reducing range was 51.9%; the maximum reduction value of vertical shear stress was 1.06MPa, reducing range was 77.9%; the maximum reduction of deflection difference of slab was 0.16mm, reducing range was 36.4%.

The first stage is for the dimension reduction, where the high-dimensional spatio-temporal output data can be reduced to the low-dimensional time series data .
The second stage is for the dynamic modeling, where a low-order temporal model is identified using the time series data.
After measurement, a series time data of thermal crown are obtained from an aluminum company, as shown in Fig.1.
Thermal crown from measurement KL decomposition is implemented for the dimension reduction, where the high-dimensional spatio-temporal measured output data can be reduced to the low-dimensional time series data.
For the data shown in Fig.1, only 5 principal spatial structures are enough to capture the 99% of the system“energy”.

The vacuum of 10 Pa and temperature level of 1200°C were maintained in 4.5 hours for the MgO reduction.
Table 1 Weight data of input (briquettes) and output (products) materials for the early pilot tests and F contents analyzed in the products, % (weight percent) Test Briquette materials [kg] Products from test [kg] F content in products [wt%] No Dolime FeSi Fluorite Mg slag Mg ingot K and Na condensate Mg slag Mg ingot K and Na condensate 1 5.0 0.84 0.25 4.1 0.9 0.031 2.6 0.064 0.169 2 4.5 0.84 0.25 4.2 0.8 0.023 2.95 0.042 0.166 3 8.13 1.67 0.25 7.1 1.8 1.57 0.022 — 4 8.13 1.67 0.25 8.3 1.85 0.061 1.24 0.047 0.07 Table 2 Results of F balance calculated using the data in Table 1 for input and output materials of the early pilot tests Early pilot test 1 2 3 4 Input of F [g] In briquettes 115.7 115.7 115.7 115.7 Output of F [g] In Mg slag 106.6 123.9 111.47 102.92 In Mg ingot 0.58 0.34 0.4 0.87 In K and Na condensate 0.05 0.04 0.04 Total F-output 107.23 124.28 111.87 103.83 (F-output)/(F-input) [%] 92.68 107.42 96.69 89.74 (F in Mg slag)/(F-input) [%] 92.13 107.09 96.34 88.95
Table 2 lists results of F balance computed by using the data in Table 1.
These data are presented in Table 3 and used in Equation 1 to calculate recovery of F in Mg slag from F added in the charged briquettes.
The high rates of F recovery indicate little or no F compounds leaving the retorts during MgO reduction. 3.

Analysis for SCR Control System Based on ANN Guanqiang Ruan 1 2, a, Zhengdong Zhang 1,b and Qiang Wang 2,c 1 School of Energy and Power Engineering, University of Shanghai for Science and Technology, No.516 Jungong Road, Yangpu, Shanghai, 200093, China 2 School of Automotive Engineering, Shanghai Dianji University, No.88 Wenjing Road, Minhang, Shanghai, 200245, China aruangq@ sdju.edu.cn, busstzzd@126.com, cwangqiang@sdju.edu.cn Keywords: Artificial Neural Network (ANN), Selective Catalytic Reduction (SCR), Modeling, Experiment Abstract.
The data of urea injection is obtained from MAP, the many experiments with different revolutions and loads are necessary.
Introduction For modern diesel engine, selective catalytic reduction (SCR) control is based on MAP which is obtained from experiments with different engine running conditions.
Control Strategy for Emission Reduction with SCR. 2003 SAE International Truck and Bus Meeting and Exhibition (Boston, American, November 10-12, 2003). p.3362

Data mining in medical domain has gained great potential in discovering the hidden patterns from large data sets.
Classifying the raw medical data is a tedious task, because the data may have some missing or irrelevant data.
Discretization is an important step in data processing to convert the data into discrete intervals
“Effective dimension reduction methods for tumor classification using gene expression data”, Bioinformatics, vol.19, no.5, 563–70, 2003
Prather et al., “Medical data mining: knowledge discovery in a clinical data warehouse,” in Proc.

Ali et al. [6] presented a new system which can be appropriate for rating tunnel sites to evaluate the potential of groundwater inflow according to the preliminary site investigation data based on the fuzzy Delphi AHP method.
On the basis of the relevant data, the permeability coefficients of the lining is 1.03×10-4 m/d, and that of the surrounding rock is 0.54 m/d.
According to the exploration data, the water head (h) of the model is 60m.
According to the Fig. 7, with the reduction of h, Q decreased sharply at the beginning, and then, the reduction trend gets inconspicuous.
(3) Based on the Fig. 7, with the reduction of ground water level, the seepage discharge decreased sharply at the beginning, and then, the reduction trend gets inconspicuous.

Keywords: Carbon dioxide; Solidification; Kinetics; Thermodynamics; Reduction emission.
The data are listed in Table 1. ③ Air ② CO2 ①NH3∙H2O (NH4)2SO4, CaCO3 or Mg(OH)2 and other less inorganic species.
Results and Discussion 3.1 Optimization of process That the two sets of data listed in Table 1 from an open and a closed system experiments, respectively, show that carbon dioxide reacts with calcium sulfate and ammonia to produce calcium Table 1 Data obtained from open system and closed system Partial pressure (MPa) 0.025a 0.05a 0.075a 0.025b 0.05b 0.075b CaSO4/g 86.13a 86.43a 86.13a 86.07b 86.02b 86.11b H2O/mL 150 150 150 150 150 150 NH3·H2O (35%)/mL 38 38 38 38 38 38 Reaction time/min 8a 6a 5a 6b 5b 4b CO2 volume/L 31.2a 40.2a 52.0a 11.2b 11.2b 11.2b CO2 gas solidification (%) 36% 28% 22% 100% 100% 100% a: open system data; b: for closed system data.
The data are recorded and listed in Table 2, respectively.
Data Vol. 51 (5) (2006) , p. 1788

Relationship between Correlation Distance and Sample Spacing In order to analyze the effect of sampling space of data on the calculation correlation distance, the data is collected of 10 static cone penetration holes from some a construction field of high-rise building in Taiyuan in China.
The relationship is described in figure 2 between correlation distance and different sampling space of data.
At present the sampling space of exploration data is generally between 1m and 2m and sometime is even larger, which makes us not to find the real correlation distance because of littler data and larger sampling space.
So we can obtain reliable calculated result of correlation distance when sampling space of data is equal to correlation distance on the whole.
According to exploration datum, the vertical and horizontal correlation distances of typical stratum are analyzed in statistics based on a large amount of investigation data and the representative values of correlation distance of local area are obtained, which can be seen in Table 2 and Table 3.

Although rhodium is very similar to platinum in chemical sense, by comparing these data with the ones published elsewhere [11], one may see that there is a considerable difference between rhodium and platinum deposits obtained in the same potentiodynamic way: while platinum builds microspheres imbedded randomly in the TiO2 layer [11], rhodium tends to spread over the whole surface of titanium support, in the form of a layer.
Along the potential axis, the region of hydrogen adsorption/desorption is clearly separated from the region of oxide formation/reduction, the transition potential being 0.0 V vs.
With a scan rate of 150 mV s -1, the current of oxide formation and reduction is between 12 and -12 mA cm-2, for a smooth Rh foil [17].
As a consequence of high surface roughness, the currents of hydrogen underpotential deposition are comparable to diffusion current of oxygen reduction in an oxygen-saturated solution.
Voltammograms in the region of O2 reduction, on Rh/TiO2 electrode in oxygen saturated 0.1 M NaOH solution, at rotation rate 5 cps (closed curve labeled by double arrows) and 10 cps.

Over 50 percent of CO2 emissions come from coal-fired power in the power sector[3], implementation of the energy-saving and emission-reduction policy in power sector has an important significance to the whole society’s energy saving and emission reduction.
Model for calculating pollution reduction and its value after power generation exchange The reduction of the kth kind of pollutant from power generation: (3) The value of the kth kind of pollutant’s reduction from power generation: (4) The total value of various pollutants’ reduction from power generation: (5) In the formula: is the emission reduction of kth kind of pollutant after power generation exchange, is the add-value brought by the kth kind of pollutant’s reduction after power generation exchange, is the total value of various pollutants’ reduction from power generation, is kth kind of pollutant’s emission coefficient of per unit of coal consumption, is the price of kth kind of pollutant of power purchasing side, is the price of kth kind of pollutant of power supply side.
Basic data This paper collected basic power generation information about area A and area B to start the case analysis; details as shown in table 1.
According the data above, we can see a significant benefit for inter-regional power generation exchange.
In order to deal with this situation, the energy-saving and emission-reduction measures are necessary to be applied in the power industry.