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Empirical analysis a) Sample data selection This paper chooses China's total energy consumption (in million of tons of standard coal) and carbon dioxide emissions (in thousand of tons) data from 1978 to 2010 as the sample data.
The raw data of energy consumption is from Year 2010 Edition of China Statistical Yearbook while the 1978-2008 data of CO2 emissions is from the World Bank database2 and the 2008-2010 CO2 emissions from Wikipedia3.
In the simple total average method, all the data of the past are equally used.
The moving average rule does not take into account longer-term data, and the weighted moving average method gives more weight to the near-term data.
This paper finds that the Holt-Winter non-seasonal model better fit the original data by comparison.

Ground movements, horizontal + vertical motion components Skewed Curvature Shifts Changes in length Reduction Elongation Elongation Reduction vertical motion components horizontal motion components mining seam part area full surface Fracture angle β Limiting angle γ Reduction trough Skewed.
In the opposite case, the pressure leads to a reduction in the area of ​​foundation soil under the building.
Here, the remaining small to large voids are filled by fine material, leading to a volume reduction.
A distinction is made between uniform and non-uniform reductions.
Schematic structure of the building lifting plant load distribution element control box with measuring device tobe lifted part remote control (electrical) hydr. lift double acting pump data cable stack of wood lining plates more –way - ventil load bearing underground lift fugue forerun Design of a the lifting system reverse running System representation computer control Fig. 8.

Numerical Study As one of the most important input data for the analysis of distributed energy system, the technical information for both electricity and heat generation are assumed according to the investigation on previous studies, and is shown in Table 1 [4-5].
The emissions reduction cost increases from 2.3 Yen/kg-CO2 to 5.8 Yen/kg-CO2, when the CO2 emissions are reduced to half of current value.
On the other hand, from the viewpoint of reduction cost, unless the CO2 emissions are reduced to less than about 35% of current value, the system has a negative reduction cost.
However, as the total emissions are reduced by a half, the reduction cost increases to as high as 8 Yen/kg-CO2.
In addition, natural gas shares a small part of the total energy consumption as the reduction ratio is over 30%.

Then, the real-time data is input to the computer by AD card (Fig. 4). 4.Results and dicussion In order to establish equation of instantaneous speed ratio, a multi-condition simulation has been used according to detailed description by table 1.
The standardized regression coefficient of Forming angle, Spreading angle, Diameter of workpiece, void and reduction is 0.105, -0.184, -0.931, -0.144, -0.015.
So, the equation of knifing and stretching stage is: Where y is the instantaneous speed ratio, x1 is forming angle, x3 is diameter of workpiece, x4 is void x5 is reduction andεis constant.
The standardized regression coefficient of Forming angle, diameter of workpiece, void and reduction is -0.013, -0.877, -0.300, 0.267.
This shows that the diameter of workpiece significantly affect the instantaneous speed ratio, followed by the void and reduction.

No reduction effect was observed at 0.1% vanillin on all Candida species.
Table 2 presents the percentage reduction of candidal adhesion to obturator resin.
No reduction effect was observed at 0.1% vanillin on all Candida species.
Percentage reduction of candidal adhesion to obturator PMMA resin.
Data from this study revealed the reduction effect of vanillin on candidal adhesion after incorporation into obturator PMMA resin.

As can be seen from the above equation EEOI is a comprehensive data, the calculation parameters include the ship's own data and ship operation data in two parts.
The ship’s own data is mainly about fuel consumption, such as: all kinds of fuel consumption, CO2 emission factor of fuel; ship operation data is the amount of cargo loading, voyage and other information.
After getting the variance of each cross-section sample collection, draw each characteristic wave height cross-section sets variance curve shown in Figure 3 access to data: According to EEOI curve obtained from each characteristic wave height simulation, as the wave height increases, EEOI curves converge slower.
Fig. 3 The curve of the cross sectional samples variance This phenomenon is due to the fact that the perturbation model is the random wave force, but the overall random wave force data has a certain statistical properties.
This paper is also an example to a 2000nm voyage, Given the relation curve between the engine speed reduction and EEOI changes.

The results of optimization show that the 28% reduction was achieved in hydrogen production of north section and this is 35.7% for south section of refinery.
Also adding the new hydrogen recovery unit in hydrogen network will cause 20% reduction in total costs of north and 31.2% in south sections.
Fonseca et al. employed the linear programming model to optimize hydrogen network refinery which leaded to a 30% reduction in hydrogen utility usage [6].
Also the cost data for cost calculations, the optimization results and cost estimations are shown in table 1.
The cost data and optimization results North Section North Section Existing Network Optimized Network Existing Network Optimized Network Total Annual Cost [M$] 64.72 51.31 40.36 27.32 Operating Cost [M$/Yr] 64.72 43.18 39.75 24.29 Hydrogen Cost [M$/Yr] 56.67 40.77 32.55 20.90 Electricity Cost [M$/Yr] 0.70 0.73 39.75 24.29 Fuel Cost [M$/Yr] 7.35 1.68 6.80 2.97 Piping Cost [M$] 0.0000 9.4600 0.0000 0.0078 PSA Cost [M$] 0.00 6.77 0.00 6.06 Hydrogen Flow[lbm/hr] 7072.28 5087.52 4062.30 2608.74 Cost Calculations Data Hydrogen cost for hydrogen plant = 850 $/ton; Electricity cost = 0.08 $/kWh; Fuel costs = 2.5 $/MMBtu; Annual operating hours = 8200 hr/year; References [1] M.I.

The data in normal state are utilized to build an observer with two radial basis function (RBF) neural networks.
It can be seen from the above literatures that data-driven method have widely used in many field.
When a test data is inputted, the observer will estimate the values of normal output signals.
Fist, input the test data into one RBF neural network observer which is trained already to generate the residual.
So what data can be obtained is the control signal and the feedback of transmission mechanism when simulating.

The basic data of the CFST are shown in table 1.
Table3 the comparison of the reduction factor’ measured values and fitting values separation ratio reduction factor’measured values reduction factor’fitting values errors 0 0.98 0.99 1.0% 0.68 0.86 0.87 1. 2% 1.9 0.79 0.78 1.3% 3.47 0.76 0.76 0 6.3 0.73 0.73 0 10.76 0.69 0.68 1.4% Fig3 curve of ultimate load capacity Fig4 curve of ultimate load capacity reduction factor –separation ratio –separation ratio The influence of eccentricity ratio: As shown in table2, the ultimate carrying capacity of the concrete-filled steel tubes after separation has some connection with eccentricity ratio.
When the eccentricity increases from 20mm to 60mm, the load reduction often keeps at 14%.
(3) The relationship of ultimate load capacity reduction factor and separation ratio can be described by functional relationship formula
(4)When separation height is 4mm(separation ratio is 0.68%),and eccentricity increasing from 20mm to 60mm , the load reduction often keeps at 14%, indicating that the load reduction due to core concrete separation doesn’t change in pace with the increase of the eccentricity ratio.

Also, a new noise reduction based on data visualization technology is proposed.
By observing the change amplitude of heart sound signal and the analog value of the acquired data, the content of noise in heart sound was analyzed.
This is the data necessary in medical examination.
The addition of the device effectively increases the protection of the signal source data.
The experimental data shows that the shunt device can produce the high and low harmonic under the joint action of AC voltage and DC voltage.