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Current industrial carbon emissions studies are usually using some converted macro area statistics data, however, this kind of large scale carbon emissions calculation applied to regional scale can cause error.
Data Source and methods The relevant data is supplied by the “Shenzhen Statistical Yearbook 2012” and the enterprise data from the Economy Science Department of Pingdi sub-district office.
Since lacking of the directly data of monitor, most of the current measure research are based on the estimation of energy consumption.
Since there is no directly monitoring data, most of domestic research takes on the estimation of indirect conversion in China now.
Limited by the relatively more parameters and less statistical energy data of the second method, we applied the third method.

ORNL has been developing models and data to predict powder densification.
As example, two data sets (press data and press and sinter data) of two powder types (Armstrong and HDH) are shown in Figures 2 (a) and (b).
These data sets illustrate the need for improved understanding of consolidation mechanics and mechanisms.
For trucks, the case for weight reduction is different.
There is a paucity of this data and experience where Ti PM is concerned.

This is in agreement with XRD data on the presence of both Cu2+ and monovalent Cu+ ions in structure.
Temperature-programmed reaction CO In Fig. 5a the TPR-CO profiles with TCD and MS data obtained from the CZP-700 sample after TPO pre-treatment is shown.
According to MS data, CO2 evaluation occurred in a narrow temperature range of 100–170 oC with maximum at 122oC (Fig. 5b, m/z 44).
XRD data indicated formation of copper-zirconium phosphates such as CuZr4P6O24, Cu1.25Zr1.75P3O11.75, and CuZr2P3O12.
Agrawal, Synthesis and X-ray data of M(TiCr)P3O12, Cu(I)Ti2P3O12 and Cu(I)1+2xZr2-xCu(II)xP3O12-x, J.

Despite this reduction, high temperature oxidation alone is not useful to achieve low density of interface traps at the SiO2/4H-SiC interface.
Fig. 3 shows such a graph calculated from the data in Fig. 1.
Even when comparing the data collected with accumulation bias applied at low temperature the 1240o C shows a lower total trap density.
In that work the reduction was coupled to a reduction of residual carbon at the interface measured by XPS.
Conclusion The results suggests that high temperature oxidation alone is not useful to achieve low density of interface traps at the SiO2/4H-SiC interface, even though some reduction is seen with increasing temperature.

The minimum input and maximum output method based on DEA(Data Envelopment Analysis) is proposed, the mathematical model of validity evaluation of eco-economic region of Poyang Lake is set up and programmed by MATLAB.
Their inputs and outputs data are taken from Jiangxi statistical yearbook of China.
Due to the relative rarely research on eco-efficiency of Poyang Lake in the past, the statistical data of eco-economic indexes of Poyang Lake is not perfect, and some ecological indexes data are still not being recorded.
Among those indexes, the reduction ratio of energy consumption of industrial enterprises above designated size is the largest.
(Ed.), Measuring Efficiency: An Assessment of Data Envelopment Analysis.

The data were stored and analyzed, where we observed the influence of temperature in both systems, validating the mathematical modeling.
The collected data were entered into the spreadsheet software Microsoft Office Excel 2003®, to generate tables and graphs to optimize the analysis.
Comparison Between Simulations and Testing In order to graphically compare the results of mathematical models for some generated graphs and data obtained during the tests, was created in MATLAB ® 5.3 code, simulating the same graph, the theoretical data based on mathematical models and practical data collected during the tests.
There is a marked reduction in the amount of Δtt.
There was a clear reduction of power output compared to the data collected in a measurement which is a function of temperature increase of the system.

Overall Maintenance Time reduction by optimizing the distance of Service center in manufacturing unit through Single Facility Location Planning Manish Vishwakarma, V.K.Khare Department of Mechanical Engineering, Maulana Azad National Institute of Technology Bhopal M.P (INDIA) email : manish_v11@rediffmail.com Keywords : New Single facility location, Maintenance time reduction, Distance Optimization.
• Squared Euclidean distance d(X, pi ) = (x − ai )2 +(y − bi )2 • Euclidean distance d(X, pi ) = √(x − ai )2 +(y − bi )2 Rectilinear Facility Location Problem – We use the following notation: X= (x, y) location of the new facility P= (ai , bi) location of existing machines, i=1,2,3 ………..m Wi "weight" associated with maintenance hours and distance between Existing facility & machine i=1,2,3…….m In a rectilinear model, the distances are measured by the sum of the absolute difference in their coordinates, that is, SINGLE –FACILITY MINISUM LOCATION PROBLEM The minisum location problem is formulated as follows: Since above Equation is written in such a way that terms involving x are separate from terms involving y, the optimum values of x and y can be obtained independently. [13] LIST OF CRITICAL MACHINE AND DATA COLLECTION All data is been collected from SCR block (block no-4) BHEL, Bhopal.
The data is been collected is 1 year record of maintenance.
DATA FOR CALCULATIONS Machine no.
· (59.5, 52.5), (59.5, 70), (77,70) (77,52.5) As observed from past data an average maintenance personals make 2 trips per hour between maintenance department (existing facility center) and machines.

In addition, direct reduction processes, SDR (Sumitomo Dust Reduction) process, SPM (Sumitomo Pre-reduction Method) process, and INMETCO process [2] were employed to treat various types of residues such as sludges and dusts.
Table 1 gives the data of sludges supplied by a Chinese industry.
Table 2 gives the data of EAF dusts supplied by a Chinese steelmaking.
Reduction behaviors.
However, Cr2O3 need relatively higher reduction temperature

In this paper, firstly, a tidal flow and pollutant transport numerical model based on Delft 3D-FLOW was established and verified by measured data to simulate and analyze phosphate distribution in Caofeidian sea area.
Based on the model calibration from measured data, the horizontal viscosity coefficient of 10m2/s and the Manning coefficient range of 0.013~0.016, according to the bed sediment particle size distribution, are used in this numerical model.
The verification of tidal flow model is carried through by three times measured data, including neap tide in spring season (2008.5.13~2008.5.15), neap tide in summer season (2008.7.11~2008.7.13) and spring tide in summer season (2008.7.16~2008.7.18) at tide station of Caofeidian and Jingtang Port for tidal level verification and at stations #1~ #6 for tidal current verification.
Fig.3 shows that simulated flow velocity and direction match that of measured data well in velocity magnitude and phase at a representative observation station #2.
The phosphate allowed discharge amount, present discharge amount, needed reduction amount and reduction rate for eight river outlets are shown in Table 1.

According to the relevant historical and predicted data, the paper examines the process of Carbon Emission Trend of energy consumption in Beijing.
The interpolation algorithm principle Interpolation algorithm is widely used in mathematics ，from a discrete set of data for some value.
So it is more suitable for predicting the annual statistical data.
Can be seen in Fig. 2, the forecasting data of 2013-2020, Beijing carbon emissions data declined slightly in 2019 compared with 2018.In 1996-2012, there is declinedyear,suchas1996-1996.Lagrange interpolation algorithm, therefore, relatively correct prediction of the development of Beijing's carbon emissions.
Summary In energy conservation and emissions reduction and low carbon development road conditions, the author predict the carbon emissions in 2013-2020 data of Beijing on the basis of historical data through Matlab Lagrange interpolation algorithm by programming in the carbon emissions.