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Unfortunately, accounting and modeling of environmental impact and energy content of products (including latent energy in raw materials) are routinely influenced by politics and and manipulation of data and are difficult to reconcile.
However, regardless of the model used, a reduction in energy usage leads to a reduction in costs as well as reduced environmental strain.
They evaluated the effects of batch processing, reduction in the numbers of machines in production, automatic shutdown of idling machines, etc., and estimated energy savings.
Table 2 summarizes the energy needed to produce materials, and presents the data by mass and by volume.
Energy reduction within a process is fairly small, although the energy lost in defects is very high.

The detachment of anodic oxide layer was performed either by step reduction of the applied voltage up to 0 V or chemical dissolution in 0.1 M CuCl + 20% w/w HCl solution at 5 °C.
The identification was performed according to the ICCD available data.
In fact, the pore density increases from 6.2 1012 to 25 10 12 pores/m 2 and the average pore diameter decrease from 230 to 130 nm by decreasing the applied potential from 160 to 80 V, as confirmed by the data reported in table 2 and Fig. 7, relating to the growth of porous films in 0.4 M H3PO4.
The method consists in a voltage reduction sequence in small steps until the zeroing of the circulating current (see Fig.11a).
For metals which have oxidation states higher than the ones present in the solution (such us cerium), possible cathodic oxidation of Ce(III) to CeO2 into the porous structure can arise from the reduction of oxygen gas dissolved into the solution, to hydrogen peroxide via a two-electrons pathway according to the reactions [25, 26]: O2 + 2H2O +2e- Æ H2O2 + 2 OH 2 Ce3+ + 2OH- + H2O2 Æ 2Ce(OH)22+ 2Ce(OH)2 2+ + 4 OH Æ 2 CeO2 + 2H2O corresponding to the following overall cathodic process: 2 Ce 3+ + 4 OH + O2 +2e- Æ 2 CeO2 + 2H2O which is operating during the electrodeposition presumably in parallel with the nitrates reduction leading to the direct Ce(OH)3 precipitation.

The coefficient of friction was evaluated considering frictional and normal load data.
Using height loss data, the wear rates were evaluated in terms of volumetric wear loss per unit sliding distance.
This reduction in density is due to the low density of carbon fibre rods as compared to Aluminium alloy matrix material.
As a result, aluminum-based metal matrix composite (MMC) was discovered to be the greatest option for weight reduction.
Remarkable 13.28 % reduction in density of synthesized composite material as compared to cast aluminium 6061 alloys.

Using MATLAB nonlinear least squares method to fit stress-bulk density data, and obtain the coefficients of the equation with 95 % confidence bounds.
The mass of the press roller was 500 N, which was in the range of the above-mentioned data.
The results indicated that higher HDR attributed to larger adhesion reduction as compared with conventional roller.
Additionally, No. 9 (the number of 18) was 21.4 % reduction in rolling resistance.
All the biomimetic rollers have obvious effects on adhesion reduction of soil.

Experimental data represent always a various scatter of results (e.g. [5]) and in this way the impreciseness (uncertainty) of the experimentally measured value that in our approach is treated as a fuzzy number.
With the use of the above-mentioned construction it is possible to build the Fuzzy Knowledge Base or probabilities for the given set of experimental data.
Representations of the Fuzzy Sets The representation of the data “integer less than 10” is the definition of the characteristic function ΠA in the following way:
The use of fuzzy sets to formally represent vague data is often done in an intuitive way because in many applications there is no model that provides a clear interpretation of the membership degrees, although we want or we try to base on various experimental data.
The values of four experimental data lie almost exactly between upper and lower bounds.

The data acquisition setup collected information regarding the air temperature, humidity, and carbon dioxide concentration, in the three group rooms, and the gym.
Data was collected from the sensors using an Arduino YUN based data logger, locally stored, and forwarded to a web service of our own central monitoring service via UMTS (see [6] for more details on the general monitoring strategy and configuration).
The temperature data shows significant higher room temperatures in the summer time.
The recorded data from the regular occupied hours was used to calculate the cumulative distributions (see Fig. 11) for the summer and winter periods.
However, the data from the winter period diverges from that, and shows values above 1000 ppm for approximately 40% of the time.

Because of the complexity of the power load, if considering just a single factor of a change in the trend is unable to accurately describe the actual change law[1].Electric power production is proportional to the social and economic development to a great extent,power load will increase as the growth of the economy.For small sample data variation is not obvious, the grey forecasting method is usually used.It is a kind of trend extrapolation method which is suited to use in the small sample data prediction[2].But this method ignores the relationship between influencing factors and load, in the practical applications, it often cannot achieve good prediction results.Partial Least Square(PLS) can explain the linear relationship between impact factor and load well.
Finally the data of prediction model take subtraction,which conduct as the data of the predicted.
Therefore, can be represented as again (17) Standardize inverse reduction process to the type, regressing equations for reduction of y to x: (18) In the type, is the regression coefficient of yon .
Simulation using Matlab, to the region in December 2009 - January 2011 - the actual social and economic data and the quantity sold as historical data, with improved grey prediction models to predict their the value of the variable to 2012 months with partial least squares regression fitting out months quantity sold and each variable linear relation, finally get 2012 months forecast electricity, and the prediction results compared with the actual quantity sold, and the prediction precision.
Research on ANN Power Load Forecasting Based on United Data Mining Technology[J].Transactions of China Electrotechnical Society,2004,19(9):62-68

The data in the official website of “China Statistical Yearbook -2012” show that the GDP has reached to 47.28816 trillion Yuan in year 2011, of which the construction industry has been up to 3.19427 trillion Yuan, accounting for 6.76 percent of the annual GDP; The total energy consumption of the society is 3,249,391,500 tons of standard coal, including 62.263 million tons of standard coal consumed in the construction industry.
The feedback loop showing: the increase in new traded land area will increase the new construction area of land, so as to reduce the stock of land area, reduction of the stock of land area makes available land area reduced, thereby reducing the annual land transfer area, the land vacant area decreases, eventually leading to the reduction of new traded land area.
Through data analysis on the "China Real Estate Statistics Yearbook", "China fixed asset investment Statistics Yearbook", "Shandong Province Statistical Yearbook", “Qingdao Statistical Yearbook” etc., integration of the information published by the local housing management departments as well as urban planning departments and Land Resource Bureau, simulation predicted through VENSIM software on three basic situation of Qingdao green building, the demand for green building, green building supply and price simulation results (shown in Table 1) are obtained.
Through repeated export of the indicators, and to be compared with the corresponding history data, eventually control relative error of all variables within a range of 5%, which shows the simulation results of the model described herein is sufficient to make it through inspection.
Table 1 Green Building simulation results of Qingdao Year Influencing factors Supply (10,000m2) Demand (10,000m2) Price (Yuan) 2008 117.1 98.3 6627 2009 168.8 136.5 7483 2010 266.6 206.1 9356 2011 279.4 246.4 10878 2012 261.8 290.6 10420 2013 310.4 320.3 11202 2014 327.6 312.1 11405 2015 423.2 364.4 11809 Analysis of Simulation Results Simulation data was plotted as the curve shown in Fig. 7 and Fig. 8, which shows the analysis on trend of influence factors.

The particle size data also was used to calculate the specific surface.
The data is normalized to the individual compressive strength of the mortar produced with standard cement CEM I).
The finer the slag is, the closer the curve comes to the data of the standard CEM I system.
Bringing all comminution data together, it can be stated that the specific surface of the slag system determines the mechanical properties of the final mortar system (Fig. 5).
Bringing together the data sets of different processing machines and concepts, they all follow the breaking law of the slag system.

For compositions with a dispersion of fewer than 200 microns and 200 ... 500 microns the reduction of horizontal deformations was 20 and 17 %, respectively.
It will contribute to the reduction of shrinkage deformations and obtaining a composite with high-performance properties.
In this case, the approximation of the results of the experimental data shows a linearly increasing nature of the change both in the flexural and compressive strength.
To analyze the obtained experimental data, we will carry out a factor analysis to identify the patterns of influence of the parameters of the structure on its quality.
For the obtained experimental and calculated data, correlation dependences for crystals of hydration products were constructed: "strength - dislocation density" (Fig. 5).