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Bias Reduction in Kernel Estimation of the Density Function of Cotton Fiber Length Yuheng SU a Guangsong YAN b (Henan Institute of Engineering, Henan, Zhengzhou, 450007, P.
According to Lin and Yan’s work, the kernel function is chosen as: （2） Due to the data tested be grouped, the kernel estimation function is revised as: （3） Where ,k is the group number, is the length of the i-th group, and .
Mixed Distribution Model Suppose that a population A is consists of the data from K different populations, and the distribution functions of these populations are,the probability of an arbitrary data in population A is taken from the i-th population is Pi, then the distribution function of A can be expressed as: （4） This expression is called mixed distribution function, accordingly, the probability density function is: （5） Where fi is the density function of the i-th population[8].

Instrumentation is composed of sensory device and data acquisition systems.
Figure 2 sensor layout of the intelligent monitoring system Real-Time Monitoring System The real-time monitoring system consists of data acquisition system (DAQ) and remote data transmission and control system.
Distributed data acquisition System [2] is adopted for acquiring data from the onsite point distributed sensors, storing or transmitting these acquired data.
The relayed and digitized signal data in the distributed data acquisition systems are then sent to a remote computer in maintenance office using fiber optic multiplexer or aiding by the Internet.
Advanced Digital Signal Processing and Noise Reduction [M].

This was used for a priori simulations to compare with experiment, and also for analysis of experimental data, as expressions for SIF in homogeneous materials are inappropriate for use with graded materials.
Fig. 2: Results for homogeneous composites: (a) Variation of Young's modulus and crack initiation toughness with composition, with EMA predictions for Young's modulus and an exponential fit to toughness data.
For analysis of experimental data, the measured crack path coordinates and load values were used, along with assumed spatial property variation, to calculate stress intensity factors and fracture toughness.
In this case, the crack traversed a large portion of the gradient so a series of sudden reductions in toughness were observed, corresponding to the crack moving from one step to the next.
The R-curve effects diminished with increasing epoxy content, so that the reductions in resistance at interfaces led to an overall reduction in the total fatigue resistance.

GNPs Colloid is prepared according to the Frens method from the reduction of HAuCl4 by sodium citrate [20].
And the lifetime data are listed on the rightmost column of Table 2.
Experimental data in Table 2 shows that lifetime of the membrane grows with the increasing lecithin concentration.
Particularly, the lifetime of the lipid membrane with a cyclohexane concentration of 100% significantly deviates from the other data, indicating the poor stability of the formed lipid membrane.
Because of which, the reduction of [Fe(CN)6]3- is much easier than the oxidation of [Fe(CN)6]4-.

On application of CKD, additional reductions in plasticity were observed.
Figure 2 Plasticity Index of contaminated and treated specimens as a function of chemical concentration Compaction characteristics: The compaction characteristics data of the contaminated test specimens and treated test specimens are reported in Figures 3 and 4.
The dry unit weight of soil specimens was slightly lowered on contamination notwithstanding the reductions in plasticity of the soil, which is expected to bring about higher dry unit weight as well as strength properties.
The influence of the degree of contamination on hydraulic conductivity of lateritic soil is illustrated by the data shown in Figure 5.
Figure 6 reports the UCS data for test specimens contaminated separately with the three solvents at 2.5, 5, 7.5 and 10% concentration.

Because of the higher reactive temperatures, the faster rates of VSS degradation can be gotten in a short time, which reach a lower level of effluent TSS concentration and a good effect of reduction.
The mixing operation for reduction of the strains was very an important factor related to stirring the fermented liquid matrix, DO, and the thermophilic bacteria.
The experiment results in Figure 3 show that the oxidation-reduction potential (ORP) in the ATAD system was not a proper state of DO in early batch tests under anaerobic condition.
According to the data in Table 2, the regression curve could be drawn through Figure 4 for influent TSS concentration of 17.28 g / L.
(7) The comparison of calculated data by equation (7) with the values of experimental data are shown in Table 2.

Fluorite is often mixed together with the two materials in a range of 2-3% to catalyze the MgO reduction.
It has been reported that for 1 ton of Mg metal produced from the MgO reduction 6-8 tons of the Mg slag were generated [3, 4].
Fig. 3 plots the related data and indicates a direct relation between the two, while the distribution of Fe3+ ions is less than 50%.
Our present and early studies [5-7] demonstrate that most of the fluorite could stay in the Mg slag after catalyzing the MgO reduction inside retorts.
Conditions of MgO reduction should thus be improved to minimize amounts of fluorite used as the reducing catalyzer.

The input data for network are the value of current and voltage of the VRFB stack when charging or discharging.
The network can classify the capacity loss degree into three levels: sufficient, moderate and insufficient according to these input data.
Unlike the mechanism models mentioned above, this neural network model only requires the external data of the VRFB system which can be easily measured rather than the data concerning the internal change of the cell.
The data of current, voltage and electrolyte temperature etc. are recorded every one second.
The network is trained by the previews data (X, C) using Matlab newpnn function.

Nevertheless, detailed experimental data for the pop-in in silicon were not given.
The experimental data are shown in figure 1 and fitted by equation [16] 128/1 8 2/1 2 1 2 0 ... cc c c hChChChCA ++++= (1) where hc is the contact depth, A is the nominal contact area and Ci (i = 1, …, 8) are constants.
The calculated results are presented in figure 2 together with the experimentally measured data.
With the experimentally determined area function of the indenter tip, the mechanical properties of silicon can be accurately calculated from the load-displacement data.
Spain: Crystal data for high-pressure phases of silicon.

Then how technological progress will act on economic structure changing and energy intensity reduction?
The estimation method is from 2006 IPCC national greenhouse gas inventories, and the data resource is China energy balance table from 2002 to 2009.
Thus compared with the reduction of energy intensity, energy-saving related technological progress can have greater effects for the reduction of carbon dioxide emissions per unit of GDP.
Then such reduction of carbon dioxide emissions per unit of GDP by energy-saving is still too low to reach the target which Chinese government has undertaken for dealing with global climate change.
Only through promoting energy-saving related technological progress, effective reduction of energy intensity can be implemented in the process of urbanization in China.