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According to the driving data collected by the data acquisition system, we studied the charge performance and fuel saving situation of EVs.
The technical indexes of EV used in the test can be seen in Table.1 Table.1 The technical indexes of EV Vehicle Index EV Whole Car L*W*H (mm) 3,120*1,680*1,505 Equipment Quality（kg) 1,080 Battery Type Li-ion battery Total Voltage（V) 277.5 Capacity（kWh) 12 Motor Model 2KM Rated Voltage（V) 270 Rated Power（kW) 35 Under ECE Driving Cycle Driving Range（km） 85 Fully Charged Time（h） 4 1.2 Study parameters Using the on-board equipment of data collection to collect the study parameters such as vehicle speed, SOC (sate of charge) and electric consumption of EV, the fuel consumption of CV, engine speed, ambient temperature, driving distance, electric consumption of air-conditioning and so on.
The complex electric consumption of 100-kilometer of EV was 12.3kWh/100km by calculating the test data.
Based on the mixed-use of EVs and CVs, we define the fuel-saving efficiency of EV as the reduction of the amount of gasoline (or the percent of the fuel reduction).
Fig.2 shows the distribution of the utilization rate of EV, where the columnar part is the categorization of the average daily driving distance data of EVs and CVs and the dashed line is the utilization rate of EVs.

This thesis makes a comprehensive use of the counter, [5]the commands for data conversion,[6] the timer [7]and the coherence check [5] of the PMC, which is the PLC in the FANUC system, to convert the external signals into G43 signals according to the requirements.
Figure 1 Digital Conversion Process from Current Values of the Counter into Working Mode Signals The main process of converting the current value of the counter into the working mode signal is shown in Figure 1 above: Pre-program a data conversion list by the data conversion function.
Table 2 Digital Conversion Examples from Current Values of the Counter into Working Mode Signals Data List No.
(Current Value of C2) Data Found in the List (K10) G43.2～G43.0 G43.5 G43.7 0 (00000000) 12 (00001100) 01100 1 (00000001) 4 (00000100) 00100 2 (00000010) 0 (00000000) 00000 3 (00000011) 16 (00010000) 10000 4 (00000100) 20 (00010100) 10100 5 (00000101) 6 (00000110) 00110 6 (00000110) 21 (00010101) 10101 3.
By practical verification on the numerical control machine, the program in this thesis is proved to be reliable, convenient, and it has a positive effect on the improvement of stability, the reduction of errors and costs for the manufacturers of the machine as well as of the system.

Traditional operation management technology had not contented the requirement of nowadays, which has enormous information flows and all-round data reduction and analysis.
BIM has super accuracy data analysis and 3D space location, which will be forceful weapon to solve operation problems.
It is hardly to get accurate statistical data of building and equipment energy consumption.
BIM could comprehend the level of building energy consumption in the round, accumulate relevant data of all equipments in building, analyze energy consumption and optimize the energy conservation of building operation, so that promote the building achieve the minimum energy consumption in even running.
It could manage and control indoor air conditioning system, lighting system, fire-extinguishing system, and other energy consumption systems automatically, after forming statistical data report.

Before the experiment, the hot-wire probe should be calibrated in advance to ensure that the voltage read by the Data Acquisition System in accordance with the imposed speed.
Three data were recorded from a set of test data that is stored for the period 1 minute.
Data were separated into three different parts, at the beginning section (Sample 1), the middle section (Sample 2) and the last section (Sample 3), within the interval of 0.03 seconds and each taken from the original data to show the stability and repeatability of the pulsed jet.
Calculation shows that the percentages of cavity volume reduction of model 2 and 3 compared to the model 1 are 40 % and 56 % respectively.
However, the reduction in the thickness of the cavity has a limit which does not exceed the amplitude of oscillation of the piezoelectric used.

In order to clearly show the changes of information, the 10 representative events from 25 incidents are selected, and data collections are completed with 3 days as a data unit.
The size of the data cannot be obtained from the real life.
We are unable to seek the pattern of the specific expression of discrete data for the analysis of the model, so this article use NetLogo simulation tool for the simulation model.
The network's basic data are as follows: total number of nodes is 10000, an average degree is 14.85, maximum degree is 334, clustering coefficient is 0.0838189.
The rate of reduction increases first and then decreases.

Block-diagram of the device The device consists of an optical transmitter and receiver part for collecting and processing data.
Mounting the sensor with adhesive tape led to a significant reduction of the reading changes.
It is clear from the graph, that the result is the reduction in oxygen saturation.

Therefore, amorphous transformer noise reduction is imperative.
Compared to the conventional noise reduction technology, there are several characteristics for ANC technology as follow: good effectiveness at reducing low frequent noise signals; lightweight control system with little bulk; designing and adjusting the characteristics of control system based on the characteristics of noise[4].
Initialization configuration of DSP chips is done in order to read and operate data.

In the above formula the following constants were adjusted from experimental data [9,10]: w0=400, Dw=13.70, Da, Da=7.50 and umax=4.56 mm/min corresponds to the maximum value of the boundary migration rate.
a b c d Fig. 1. a) Rolling texture of aluminium (reduction 60%, max. intensity: 18), b) calculated compromise function S(g); max. intensity: 0.67, c) predicted recrystallization texture; max. intensity: 11; texture components marked: cube (), S (), rotated Goss (), d) experimental recrystallization texture of aluminium annealed at 5200; max. intensity: 70 (after [4]).
The starting rolling texture of aluminium (60% rolling reduction) is shown in Fig. 1a, while the compromise function, S(g), calculated on the basis of the deformation texture, is shown in Fig. 1b.

Analysing Reliability Aspects of HVAC Systems- A case Rajiv Kumar Sharma, Chandan Parbhot, Sidhant Thakur, Vivek Thakur Department of Mechanical Engineering National Institute of Technology, Hamirpur, H.P India – 177 005 Keywords: FMEA, HVAC units, failure data, reliability assessment Abstract.
Liberopoulos and Tsarouhas [6] presented a statistical analysis of failure data of an automated pizza production line.
The analysis includes identification of failures, computation of statistics of the failure data, parameters of the theoretical distributions that best fit the data, and investigations on the existence of autocorrelations and cross correlations in the failure data.
Illustrative Case Six months data (July 2010-December 2010) of different HVAC failures is collected and the time between failures have been calculated for each pair of successive failures occurring in the six main identified system failure categories.
[3] Sharma, R. (2005), “Reduction of process defects in chrome-plated cylinder liners in WDM diesel locomotives using TQM tools”, Industrial Engineering Journal, Vol. 34 No. 3, pp. 17-21

Results First data set.
Second data set.
The second data set is a clutter scene including buildings, plants, flags, etc.
Third data set.
We use the third data set to estimate the RMS error between final point pairs.