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Basic data cleaning and data validation function was developed to meet data quality demand referring to data integrality, data authenticity and data time effectiveness.
Thus, the meta data management module should record all data sources and compare the data from data warehouse with the data from source pages.
When the data are inconsistent, the system should update the data of the data warehouse.
Basic data cleaning and data validation function was developed to meet data quality demand referring to data integrality, data authenticity and data time effectiveness.
We are fully convinced that the application of these methods and data must lead to the reduction of family car’s LCC and actively enhance the level of design.

Therefore, numerical method is used for the research of the influence of six kinds of sun visors differenced by shapes or layouts on the aerodynamic drag reduction.
Moreover, compared to the original one, the CD values of each case have different degrees of reduction which illustrates that an appropriate shape and layout of a sun visor benefits the air drag reduction, the largest decline is 4.7%.
Introduction For resistance reduction case of a truck, many domestic and foreign scholars have had comprehensive and thorough studies.
Models and sun visor layouts The real data of a domestic mass-production heavy-duty truck is used as the computational model, which is simplified using modeling software CATIA and pre-processing software Hypermesh.
（a）Case 1 （b）Case 2 Fig.7 Streamlines along the side of cab in case 1 and 2 shown in the horizontal plane Z=1.55m Conclusions In this study, the coefficients CD of all the six modified cases have varying degrees of reduction compared with the original case, it can be judged that the sun visor is effective for reducing aerodynamic drag.

By using Rist operating line for the indirect reduction zone, as seen in Fig.2, direct reduction degree of the new process can be calculated, and thus indirect reduction degree can be obtained.
Fig.3 Algorithm for solving full oxygen blast furnace mathematical model Fig.2 Rist operating line for the indirect reduction Fig. 4 Influence of hearth-recycle gas quantity on theoretical combustion temperature Theoretical Analysis of Model Results Data Used in the Model.
In this study, data used in the model are derived from a real operating blast furnace in China.
Set (VRG-h, VRG-s ) as (380, 357) and (187, 550) m3/thm, respectively, and keep other data unchanged.
Table 7 Results derived from different VRG-h data value data value VRG-h 380 550 VRG-h 380 550 direct reduction degree 0.16 0.16 CO in top gas (v%) 50.6 50.6 blast volume (99.2% O2) (m3/thm) 207.7 207.7 CO2 in top gas (v%) 37.0 37.0 gas volume in hearth (m3/thm) 813.1 983.1 H2 in top gas (v%) 7.3 7.3 gas volume in belly (m3/thm) 890.7 1060.7 H2O in top gas (v%) 2.8 2.8 gas volume in lower shaft (m3/thm) 1247.7 1247.7 N2 in top gas (v%) 2.3 2.3 gas volume at top (m3/thm) 1285.8 1285.8 volume of output gas (m3/thm) 590.7 590.7 Conclusions (1) A new comprehensive mathematical model of full oxygen blast furnace with top recycle gas heated by gasifier is established.

Processing of the ECAP+CR sample consisted of ECAP of 4 passes, which was less than that showing the optimum microstructure for high strain rate superplasticity of UFG Al alloys (i.e. 8 passes), with route Bc and subsequent cold rolling (70% thickness reduction).
An analysis of the mechanical data revealed that deformation of the ECAP+CR sample was dominated by grain boundary sliding, but dislocation viscous glide was the main deformation mechanism for the ECAP sample.
The ECAP+CR process takes two main advantages: (a) reduction of the ECAP passage and (b) production of the UFG plates or sheets.
After ECAP, cold rolling with a total reduction of 70% was carried out with 0.2 mm reduction per rolling pass.
By contrast, except high strain rate region faster than 1×10-2 s-1, the mechanical data of the ECAP sample coalesced into a straight line with the slope of 0.33 (= m), indicative of operation of dislocation viscous glide.

The paper is dedicated to predict tension softening curve of concrete by using artificial neural networks (ANNs) based on experimental data of five different mixtures of concrete (including High Performance Concrete).
In order to evaluate the prediction accuracy, tension softening curve and other fracture parameters were predicted for each mix from the other four mixes and compared with the omitted data of the relevant mix.
The reduction easily exceeds 10 % and sometimes exceeds even 20 %, [1].
Then, a prediction was made for the omitted concrete and compared with the data of the original omitted concrete.
[13] StatSoft, Inc. (2004) STATISTICA (data analysis software system), www.statsoft.com.

Result and Discussion Beer’s Law equation was applied in this experiment to analyse the absorbance data obtained from UV-VIS spectrophotometer.
(1) Figure 1: Standard calibration curve The standard calibration curve using ammonium stock solution was prepared before undergoing the inhibition and data was recorded at 640 nm.
Meanwhile, urea solution with mixture of urease-guava leaves extract showed reduction in NH3 concentration release.
The reduction happened in small value with different around 0.1 mol/L and the releasing also was almost equal till the end of incubation time.
This small reduction might be because of the concentration of guava leaves extract that been used is slightly low.

Road condition data is a precursor for road monitoring and is collected on a periodic basis by road authorities to assist in transportation planning.
This ensures the compatibility and quality of data sets and make greater use of available road condition data for improved statistical reliability in data analysis [4].
Critical examination of the condition survey data in Botswana, showed that defects varies from road to road, thus the strategy adopted so as to analyze the condition data was to group the sections into different districts.
Conclusion This research experience has shown that it is essential to select a uniform and site specific data set of gravel road performance deterioration parameters and use consistent methods to collect and record gravel road condition survey data.
The data sets of 2008 were not use for the analysis because it was not available for all the roads evaluated.

When a catalyst supports this reaction they are usually referred to as selective catalytic reduction (SCR) processes, while the processes are known as selective on-catalytic reduction processes without catalyst used (SNCR). 1.
According to the results of the experimental data, Salimina obtained the branch coefficient a is 0.29 at least in the model.
The NH2 produced will react along with two paths: the reduction and oxidation.
The reduction reaction is mainly dependent on the self-sustaining reaction, i.e. the reaction (2-1).
Control of combusion generated nitrogen oxides by selective non-catalytic reduction[J].

Bacterial reduction of at least 88.5% against both, Staphylococcus aureus and Escherichia coli, has been obtained.
The samples were pressed on a diamond and the absorbance data was recorded over the range between 400 and 4000 cm-1 with a spectral resolution of 1 cm-1 and averaged over 64 scans.
According to literature data [15] the plasmon maxima at 395 nm and 405 nm match silver nanoparticles size of ~10 nm and 14 nm, respectively.
The values of microbial reduction of cotton fabrics loaded with Ag nanoparticles are given in Table 4.
From the data it is evident that the reduction of bacterial colonies was always at least 88.5% or higher against both S. aureus and E. coli.

It was decided to collect the data regarding the defects generated in the pump manufacturing process and analyze them using various tools being implemented.
To collect the data, analyze, find out the Root cause and the Rolled Throughput Yield (RTY).
Table 3 and 4 show the data of production collected in the enterprise based on which Fig. 1 Run Chart; Fig. 2 P-Chart; Fig. 3 Pareto Chart were plotted.
AND PLOTTING PARETO CHART Fig. 3 Pareto Chart Fig. 4 Cause and Effect Diagram TABLE 5: COLLECTION OF DATA AFTER IMPLEMENTATION MOTOR ASSEMBLY PROBLEM – Data After Implementation Type of Problem Date 10 11 12 14 15 17 18 19 20 21 22 24 25 26 27 28 SUM AVG % OF TOT PROD % OF TOT DEF.
The data of defects were collected after implementing the measures (Table. 5) and the percentage of rejection has come down from 18.5 to 3.079.