Search results

Gray model GM (1, 1) is based on gray prediction, with some known data; it could quantify the abstract concept of system information, and then set them in a model, at last forecast part of the unknown data through the model optimization.
GM (1, 1) model is to process random variables as gray quantity, look for the law between data, make up for the lack of data processing methods.
Modeling process of gray prediction model is to accumulate the irregular raw data, to get the generated sequence which has strong regularity before modeling, then obtain reduction model through regressive model data, at last, the reduction model is a predictive model.
Then, we got .As, the series of was used as the data of GM (1, 1) for forecasting.
Conclusions According to the historical demand data, the paper established a reasonable gray prediction model through the preprocessing for raw data, and got predicted values which had high precision.

Test details and primary test data are given in Table 1.
Therefore, scattered data are obtained in Table 1.
Real distributed shape of a set of data can be judged using a so-called statistical parameter, coefficient of skewness, g, which is defined for a set of data xi as (1) where and are respectively average value and standard deviation of a set of x data with sampling size of ns.
For the present data, the g values of five properties are all greater than zero.
It indicates that EMV1 and E are not reasonable models for the present data.

A degree of electrode reaction, current density, electrode potential and interface resistance, etc were discussed with measured electrochemical data.
Among many key roles of electrodes and electrolyte, the efficiency and properties of DSSC are affected by the reduction rate at the counter electrode and the properties of counter electrode materials.
Here, we need materials with high electric conductivity and good catalytic effect for increasing reduction rate of tri-iodide.
In CV graphs, a peak in negative potential range corresponds to reduction reaction of I3 ion.

The results indicate that hot corrosive gas mainly causes the strength reduction because of the degradation of grain boundary region.
Data points are means and standard deviations of a minimum of five specimens.
Data points are the average value of 10 data.
Figure 6 plots the strength data as a function of holding time for hot corrosion tests, at 900oC in the mixed gas as indicated in Table 1.
The solid line is a fit to the data sets, indicating no change of the slope of dynamic fatigue after hot corrosion test.

Based on the rule-of-mixture, there was a very small difference in the experimental and calculated data.
The data of the experimental CTE (3rd segment) in the glass state is shown in Fig. 2.
The experimental data and the prediction from the rule of mixture are shown in Fig. 2.
The experimental data was significantly lower than those based on the rule of mixture.
Although the value based on Schapery’s lower limit is significantly lower than the experimental data, the value from Schapery’s upper limit is a relatively good prediction of the CTEs for ZrW2O8/Matrimid 5292 hybrid.

This essay is the subject of national eleventh five support schemes: The analysis of key technology on emission reduction and comprehension utilization of solid waste from large iron ore mine (Number:2008BAB32B14).
Introduction This essay is the subject of national eleventh five support schemes: The analysis of key technology on emission reduction and comprehension utilization of solid waste from large iron ore mine (Number:2008BAB32B14).
The size distribution data of iron tailings refer to Table 2 .
Table 6 The working performance of sprayed concrete with iron tailings Sample number Sprayed concrete slump (mm) Initial setting time (min) Rate of resilience (%) 1 70 26 <35 2 130 45 <10 3 115 44 <5 4 70 40 <5 5 95 20 <5 6 70 42 <10 The data in Table 6 indicates that value of sprayed concrete sample slump is less than 130mm and below standard 160 mm, the initial setting time range is in 20 to 45 minutes,the rate of resilience less than 40%.
Test data in Table 5 showed that the the performance of sprayed concrete with iron tailings was better than that of sprayed concrete with natural sand.

This leads to a reduction of the tool lifetime or to tool deformation.
This study deals with the investigation of possibilities for the reduction of tool wear.
Table 1 Data specification of the used workpiece materials The desired cog geometry corresponds to DIN 867 using a module of 1.5 which is conventionally used to manufacture a toothed rack.
Based on this data, tool paths were computed in a CAM system with respect to the results of the fundamental investigations [16, 17, 18].
The application of lubricants causes an additional reduction of the process forces.

Very high gravity ethanol fermentation technology exhibited promising industrial application for advantages including productivity improvement, polluted water output reduction and energy consumption saving.
Datas analysis indicated that the osmotic pressure was controlled strictly exhibited by high growth rate of yeast and high rate of ethanol formation comparing with other dosages, and 119.78 g/kg (15.07 %, v/v) ethanol equivalent to 90.16 % of theoretical yield was achieved in 64 hours.
Therefore, very high gravity (VHG) ethanol fermentation technology exhibited promising industrial applications for advantages including productivity improvement, polluted water output reduction and energy consumption saving, particularly for the downstream processes like distillation because of high ethanol concentration in the mash to be distilled and the waste distillage treatment by the energy-intensive multistage evaporation process as less waste distillage to be treated [5, 6, 7, 8].
Table 1 Fermentation parameters of five glucoamylase dosages adding Glucoamylase dosage [g/kg dry matter weight] 0.2 0.4 0.6 0.8 1.0 Residue available glucose concentration [g/kg] 3.2 2.1 3.7 4.6 43.1 Final cells count [108/g] 2.35 2.43 2.17 2.11 1.78 Final ethanol concentration[g/kg] 72.44 95.43 113.47 119.78 101.39 Yield [theoretical production %] 55.59 73.24 87.08 90.16 77.81 Productivity [g/kg.h] 0.91 1.19 1.42 1.48 1.27 Conclusion Fermentations parameter datas indicated 0.8 g/kg dry matter was the optimum glucoamylase adding for SSF using very high gravity liquefied sweet potato mash, under such condition, the osmotic pressure was controlled strictly under the high inhibition limitation level and saccharifying rate was always kept high enough for the substrate providing, and 119.78 g/kg (15.07 %, v/v) ethanol equivalent to 90.16 % of theoretical yield was achieved in 64 hours, average productivity calculated by final ethanol concentration was 1.48 g/kg.h.

We dealt with palmprint images data as high order tensors that can both preserve the spatial structure of palmprint image data and decrease the number of the parameters to be learnt [8].
Essentially a tensor can be considered to be a multi-dimensional or N-way array of data and as such is useful for the description of higher order quantities e.g. multivariate data.
Given a set of n data points 12[ , ,...., ]n X X X X = in 1 2n n R R⊗ .
Let T Y U XV= denote a random variable in the tensor subspace and suppose the data points have a zero mean.
The number in bracket is the dimension reduction.

Finally, three levels reduction gear was chosen to be the transmission system of the gripper driven system, the primary reduction is the Synchronous belt reductor, the second reduction is the gear reductor, and the third reduction is the rope redactor [9, 10].
The reduction ratio of rope gearing is the ratio of the two wheel diameters, so improving the ratio of the two wheel diameters can amplified transfer torque.
The data and the image are transmitted between the robot and the ground base station by a couple of wireless data modems, the tasks of the ground base station are the remote control and the state monitoring for the inspection robot, and the images are transmitted from the robot to the ground base station by a set of wireless image transmission device to display and store.