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POSCO’s ERP based environmental management system (POEMS: POSCO Environment Management System) enables the systematic management of environmental data.
The environmental data collected through the TMS at each plant is transmitted real-time to the local government and the Ministry of Environment, and employees with authority connected to the company environmental system can see the data individually.
Detailed action plans include web-based integration to improve user convenience in data usability and analysis, building family information sharing system, mobile-based Smartwork, and comprehensive health care system.
The water usage and discharge data for each plant is analyzed and diagnosed by specialists to identify areas to be improved, and used as basic data in improvement activities to reach optimal water efficiency.
The various efforts to reduce water usage is expected to bring 40,000 tons reduction daily.

For the increase of mapping data precision, besides using the odometer information of the car we integrated the SLAM technique.
Considering this we have chosen for our test platform two algorithms on which our Simulink models will be build up: Discrete Curve Evolution (DCE), for data reduction, and Iterative Closest Point (ICP), for a higher positioning accuracy.
A significant reduction of data has been observed, the reduction rate of points was at around 70%.The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of two and three-dimensional models when an initial estimate of the relative poses is known.
This data is then analyzed and interpreted according to a world coordinates system.
A relatively big amount of data is filtered and obstacle specific features are obtained.

Simulation results show that: the mechanism can reduce the amount of data transmission, reducing downtime and total migration time.
Because page written frequently is likely to be transmission, which will make total transmission data increase, migration time be effected, migration performance be reduced [5].
Low rate of dirty pages experimental operating system in the source domain free time; high dirty pages experiment in kernel compile time, migration memory size is 128MB, 256MB, 512MB and1024MB.Take the averages of the experimental results after several experiments, which are shown in table 2 and table 3.The data in the table respectively using Xen original algorithm and improved probability prediction algorithm in this page the experimental data.
Under the high rate of dirty pages of experimental environment, this article also tested and analyzed the total amount of transmitted data migration.
After several experiments, the data are averaged, the experimental results shown in table 4.

Finally, the depolarization current is measured during reheating of the sample at constant rate b by an electrometer connected to a computer for the data acquisition. 2.3.
This phenomenon can be explained by considering the reduction in free volume due to the structural relaxation of the material [13]; the aged sample has a smaller free volume as well as a lower enthalpy and potential energy than the unaged sample.
The diminution of the thermo-currents peak intensity and polarization Pmax can be attributed to the reduction of the free volume, which leaded to the decrease of the molecular mobility.
Consequently, a low activation entropy will be recorded, which resulted in a reduction of the activation enthalpy.
The reduction of α relaxation mode has been found by the optical technique (ATR): it was highlighted by a decrease in all absorption bands intensities due to the reduction of the free volume and molecular mobility during aging.

Elongation data presented by Higashi et al. [8,9] for AA5182 showed that the elongation to failure increased with increasing strain rate.
Figure 1 shows the measured room temperature stress-strain data for 1.6 mm AA5754-O for the range of strain rates considered.
The Hopkinson bar data lies above the quasi-static curve, indicating a positive rate sensitivity.
Similar data is plotted for 1.6 mm AA5182-O in Figure 2, but shows much less rate sensitivity.
Data is shown for quasistatic and high rate samples tested to fracture as well as for the interrupted samples shown in Figure 7.

Characteristic strength of fiber and yarn were determined from Weibull data distribution.
Table 3 shows the tensile strength data of composites.
Hence, the tensile test data were normalized to 37% fiber volume fraction.
The actual data and normalized strength of the composites were tabulated in Table 2.
Normalized composites strength data are also depicted in Fig.6.

I/O Port Data display Mainboard of industrial control Data collection board Sensor connection plate Upper computer Shore-based database Fig .1 Working principle of hardware system Sensor connection plate receives fuel consumption signal sending form the sensor on fuel consumption pipe, transmitting the information to the data acquisition board, and the data acquisition board converts analog quantity into digital and sent to the mainboard.
Based on monitoring terminal display of data and flow meter data using the recursive least square method for linear fitting, reduce the internal error because of the signal monitoring system. 3.1 Recursive least squares method calculation principle Assuming the original observation sequence is (t = 1, 2,).
Estimate parameter based on , and observe a new data and type it into the original sequence.
When experimenting, from the beginning of the 220 L/h, every time adding in 50 l/h, record 20 sets of data.
Then we use Wilcoxon symbols average rank test to process data.

The physical meaning of the data are studied and illustrated as well as its representation methods.
Experiments are conducted to verify the range finding accuracy of the sensor and the data visualization method is also introduced.
Coordinate System Conversion Distance data of each frame is constituted by 683 distance metric.
Use a ruler to determine the distance of the object from the sensor, data returned by the sensor is collected and saved.
Fast range-independent spherical subsampling of 3D laser scanner points and data reduction [J].

Original data of this paper were from the China Energy Statistical Yearbook 2008 and China Environmental Yearbook 2008.
Data Envelopment Analysis: the evolution of state of the art (1978~1995) [J].
Data Envelopment Analysis[M].
Some models for estimating technical and scale inefficiencies in Data Envelopment Analysis[J].
Data Envelopment Analysis[J].

*napassavong.o@chula.ac.th Keywords: Bending defect, Clamping distortion, Hard disk drive media, Six Sigma, Defect reduction, Design of Experiment Abstract.
First, disk failure results in temporary unavailability of data or even permanent data damage.
However, excessively high clamping force tended to cause disk distortion in the waviness form along the inner data zone .
Table 1 Project Charter Six Sigma Project Charter DEFECTIVE REDUCTION FROM BENDING DEFECTS ON HARD DISK DRIVE MEDIA Project Leader Champion Executive sponsor Master black belt Suthongchai S.
Pierce, “Six Sigma: concepts, tools, and application,” Industrial Management & Data System,vol. 105, pp. 491-505, 2005