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𝛽is defined as the lateral stiffness reduction coefficient, e.g. .
The lateral stiffness reduction coefficient at collapse point C is denoted as, e.g. ; γ is the inter-storey drift angle, e.g. .
The relationship between the lateral stiffness reduction coefficient and the inter-storey drift angle is derived in reference [2], according to the experiment data, as follows: =1.0 （≤1/ 500） (1) =（1/ 500＜≤1/ 100） (2) =0.65-20（＞1/ 100） (3) The horizontal line, curve and slash can be represented by Eqs.(1), (2) and(3), respectively, shown in Fig.3.
Researches show that[7], if the stiffness reduction coefficient after yielding is greater than 0.2, the structure elastic-plastic seismic response should have good stability.

Without the reduction of the initial billet cross-section, the process is usually repeated 6 to 14 times and the billet is rotated between consecutive passes in order to obtain uniform strain.
(a) Billet (b) Product f0.7 4.23 f1 f1 3 Fig. 3 Schematic diagram of CWR (a) Knifing zone (c) Sizing zone Billet Workpiece Bottom wedge die Top wedge die a b (b) Forming zone Fig. 4 Key dimensions of workpiece (a) Schematic diagram of CWR system (c) Die assembly on the system Load cell Driver Workpiece Die Position sensor Controller Stroke and load control, and data acquisition unit (b) Developed CWR system Fig. 5 CWR system and die assembly Process Conditions.
The concave curvature radius of the end face on the rod increased with grain size reduction.
Moreover, the difference between the maximum and minimum values decreased with grain size reduction.
Clearly, the load increased with grain size reduction and the ECAE processed copper resulted in the largest value.

Reduction of finish rolling temperatures Tf (T2 and T3) brought in all wall thicknesses a relative refinement of the structure.
The strength properties quite slightly decrease with the increasing wall thickness of the simulated tube, plastic properties remained within the data scatter almost unchanged (see Fig. 3).
It is not possible to declare unequivocally that reduction of the finish rolling temperatures resulted in the obvious influencing of the yield strength or ductility, which is due to different grain sizes rather surprising.
Reduction of the finish rolling temperatures in laboratory conditions was manifested by certain refinement of the resulting grain, which, however, did not have any significant impact on the strength or plastic properties determined by the tensile test.
The only positive effect of reduction of the finish rolling temperatures in case of the investigated steel appeared to be a significant increase in notch toughness of the simulated tubes with a wall thickness of min. 20 mm.

The database collects data including battery SOC, battery voltage, discharging current, temperature…etc.
According to cloud data analysis, charging current 5C/10C/20C under rapid charging grid’s load monitoring is possible; the process of environmental development and hardware planning can train students to use hardware, firmware and software design platform for the skills development for future employment.
Introduction In Taiwan, there are hundreds of millions of oil-fueled vehicles and motorcycles, has caused a lot of environmental pollution and oil consumption, electric vehicles are expected to occupy a signicant portion of the automotive market share in the near future, the use of Li-ion(LiFePO4) battery as a vehicle motor power to replace the fuel, is the best choice of today's environmental issues; An electric vehicle has only an electric drive-train powered by Li-ion battery; in the past, motor vehicles is the inverter-driven with lead-acid batteries, in order to slim and light in weight, most of the current cell has replaced by Li-ion battery with its weight reduction, energy saving effect and high energy density; The cost and performance of the electric vehicle is primarily determined by the type of battery and its management system ; but when nearly one million electric vehicles on electric system, the load flow of charging current and large information of the battery will impacts
According to the cloud data, charging current under rapid charging grid’s load monitoring is possible [4]; the process of environmental development and hardware planning can train students to use hardware, firmware and software design platform for the skills development for future employment.

This paper compares calculated and measured energy use data (for space heating and cooling) pertaining to a hospital building in Austria.
Thereby, an effort was made to define model input assumptions (building construction, weather data, internal gains) based on actual circumstances in reality.
Monitored data, default settings, fault indications, and other related information are sent to the communication and control center [4].
Actual energy use data was provided by the building management.
Furthermore, heating degree days as per EC’s weather data are about 5% higher than the weather data used for the simulation.

Among them, greenhouse gas emission of coal-fired power generation sector is the main link in coal-energy chain and aslo the focus of regulation and emissino reduction.
The data shows that, at the end of 2010, the total capacity of the national power generation equipment achieved 966.413 million kilowatts, among them, thermal power 704,144,400 kilowatts, accounting for 72.86% of the total installed capacity.
Carbon emissions measurement model of coal-fired power generation （4） Formula (4): is standard coal consumption of a unit of electricity; is the carbon equivalent emissions coefficient of the k-th greenhouse gas of a unit tce by power generation; Unit: —g/kWh, —gCO2 eq / tce Basic data of the measurement （1）Standard coal consumption (g/kWh):343.63g/kWh （2）tce CO2 emission coefficient(t/tce):2.4567tCO2/tce （3）tce NOx emission coefficient(t/tce):0.01567tNOx/tce （4）Quality conversion coefficient between the raw coal and standard coal: 0.7143 （5）Some greenhouse gas default GWP values by IPCC ​​shown in Table 1 Table 1 Part of the greenhouse gas preset GWP value of IPCC the chemical formula of the greenhouse gas GWP value CO2 CH4 N2O 1 23 296 Source: IPCC Third Assessment Report (2001) Calculation and analysis of measurement inventory Carbon emission coefficient measurement inventory in the coal production .The greenhouse gas emission
According to the data of China Coal Research Institute in recent years, energy consumption indicators of China's raw coal mined estimates were made: power consumption mining tons of coal 36KWh; raw coal consumed mining tons of coal 30kg.
The data shows that the diesel locomotive proportion of China's railway transport in 2009 is 57.3%, diesel locomotive tons km fuel consumption of 24.6kg / (Wan t • km); the electric locomotive was 42.7%, electric locomotive Wan ton-km power consumption was 111.8kWh / (Wan t • km).

More importantly, the correlation data sequences of chaos has low frequency power spectrum as shown in Fig.1.b.
The method are as follows.First, construct new correlation data sequence(eq.4) by Using sample data (eq.2).
Fig.4 is wavelet packet decomposition energy of new data sequence (eq.4) ,it shows that the power of new data sequence locates in low frequency packet.
Fig6 show the spectrum of new hybrid data sequence, the new harmonic(30hz and 33hz) can not be estimated.
[5] Tim Sauer, “ A noise reduction method for signals from nonlinear systems ”,Physical D, vol 58(1992), pp.193

Then the collected data were sent into the server in real time.
Fig. 4 LabVIEW application software realization diagram Data acquisition.
The system connects the data acquisition by differential mode.
Meanwhile, the bottom functions of DAQmx are applied to program the data acquisition program (see Fig. 5), which acts as the bridge between data acquisition card and LabVIEW application software.
Fig. 5 The data acquisition program Fig. 6 The realization of wavelet denoising Analysis and calculation.

Analysis of initial data On the first work stage actual WEM model and its price forming were studied.
With a view to specification of actual consumption schedule of eligible customers XML 80020 AIMSCEM model data, transferred from market players per May, July and December, was processed.
Average daily consumption diagrams for each month, included in sample, were plotted for this data, and minimum consumption was determined.
This data was also used for accuracy analysis of declared maximum scheduled consumption and its deviations from actual values.
On the base of this data calculation of EE and capacity cost for end consumer for the following cases of optimization were performed: without DGU; with DGU operating in basic mode; with DGU operating in mode of peak loads leveling.

For the numerical simulation the results are perfectly symmetrical because it has been simulated a quarter of model while, the experimental data are not perfectly symmetrical because of particular experimental cell condition.
Numerical-experimental TPR comparison for all curves In Fig. 15 is shown the comparison between the global tendency line for all experimental data and numerical simulation.
Global tendency line for MOD1 Analyzing Fig. 15 it is possible to evaluate a good correlation between the global tendency of the experimental data and the numerical results is evident, especially for low R2 values which are for higher drawing heights and then more critical conditions.
Numerical-experimental thickness values comparison for MOD1, along X-X, Y-Y and A-A section where the experimental data have been measured As it can be appreciated, thanks to the reported data, (Fig. 16) there is a uniform thickness distribution and a good agreement between numerical and experimental values with a discordance of about 4%.
From the reported data it can be assumed a good correlation and a very good repetitiveness.