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Qualitative data analysis was conducted by comparing collected data against the approved procedures as well as maintenance manual and the result of the study revealed the occurrence of errors during inspection, cleaning/lubrication, training, troubleshooting and documentation tasks.
Two research assistants with strong background training in aircraft maintenance operations were used to collect data.
Data collection was nonintrusive, allowing maintenance personnel to focus on their work.
Data Analysis.
The collected data were analyzed using qualitative technique based on comparing the collected data against recommended practice as contained in the maintenance manual, maintenance procedure manual and approved best practices publications/documents on aviation safety.

The reduction characteristics of Co3O4/SiO2, promoted by SEA, were investigated by temperature programmed reduction (TPR).
Temperature programmed reduction (TPR).
Measured ζ-potential data as a function of the pH for SiO2 (Davisil 646) and Co3O4 with a 0.1M KCl background (curves represent fit to equilibrium model – see text) –SiO2 model, - -Co3O4 model Table 1. pKa and pKb values for SiO2 and Co3O4 determined from model fitting of ζ -potential measurements pKa1 pKb1 a Davisil 646, SiO2 13.8 6.9 30 Co3O4 1. 7.4 4.8 16 2. 3.8 10.1 10.5 1Ka=K2; Kb=K1Kw Figure 2.
The activation energy for the reduction of Co3O4 to CoO in the platinum promoted catalyst is reduced to 50 kJ/mol and for the reduction of CoO to Co0 found to be 38 kJ/mol.
This markedly decreased the reduction temperature for both stages of the reduction of Co3O4 evidenced by the TPR measurements.

Samples of 25% deformed (thickness reduction) material have been used for these studies.
For example, the spectrum curves for the mean lifetime of positron changes as a function of the sample deformation or annealing temperature; [1-5] the advantages of these methods for obtaining both qualitative and quantitative data on defect behavior are pointed out.
Figure 5 Resistivity as a function of annealing temperature Figure 6(a) Variation of Resistivity as a function of annealing time at 583K As shown in figure 1, the isochronal annealing data reveal two regions.
Samples of 2024 alloy were deformed to 25% thickness reduction, and then subjected to isothermal annealing.
From this figure, it is clear that the isochronal annealing data include two regions observed using the PAL technique.

Data preprocessing, namely discretization and data completation.
Data preprocessing, namely disperse and complete train samples and unclassified; Step2.
End For and output the class label ; Experiment In order to verify the validity of above algorithms, this experiment select four datasets from UCI data depository[7], respectively Zoo, Wine, Vote, Tic-tac-toe.
Intelligent Data Mining and Knowledge Discovery[M].Xian: Xian University of Electronic Science and Technology Press, 2006, pp.431-471
Data Mining Practical Machine Learning Tools and Techniques Second Edition [M].Beijing: China Machine Press, 2006, pp.98-189.

Through the analysis of pressure distribution on the cavity bottom and the noise spectrum monitored at front and rear walls respectively, noise suppression effects of mesh programs relative to the clean cavity and changes in the flow field are studied, the results show that the mesh inside the cavity has a better noise reduction effect.
The work in this paper provides an effective way for cavity noise reduction.
Therefore, noise reduction measures around the cavity have launched a lot of work internationally.
Noise measurement use LMS dynamic measurement system with 8-channel data acquisition front. the frequency range of PCB130 series of acoustic sensors is 10-15KHz.
The figure shows that the inside mesh can reduce front wall noise about 5dB, the low-frequency noise reduction of back wall is more prominent, the overall noise reduction can be 2-8dB, ie, the inside mesh has noise reduction effect on both low and high frequency and such good results should be attributed to the obstruction and combing effect on back flow inside the cavity.

The pesticide residues were calculated using the following formula: Pesticide residues = For all treatments, data from independent replicate trials were collected and the standard deviations were calculated[5].
Duncan’s multiple range test was used for analyzing all data and the significance was determined by one-way analysis of variance (SPSS 11.0 for Windows, SPSS Inc., Chicago, Ill., U.S.A.).
Significant differences between data were established at a significance level of P < 0.05.
Effects of CGW immersion time on the reduction of 2 pesticides residues on fresh spinach are reported in Figure.3.
The reductions of the pesticides on fresh spinach increased to 38.0% (phorate), 40.2% (chlorpyrifos) after10 min of immersion in CGW (20 mg/L).

First, data fusion technology caused data transmission delay.
Because of a great reduction in data redundancy, the sensor network after fusion has a smaller data size.
As we know, the cost of data transmission mainly depends on the data output of data fusion nodes.
In contrast, the cost of data fusion is mainly depends on the data input of data fusion nodes, Fig.1.
For data fusion, node failure means that the fusion data contains abnormal data, namely, the impulse noise.

Based on the daily precipitation data in Northeast China (NE China) from 1961 to 2010, six extreme precipitation indices (RX1day, Rx5day, R10mm, R20mm, R95T, and R99T) in NE China were calculated, and the temporal and spatial characteristics of extreme precipitation events were analyzed.
Based on the daily observational data of 100 stations in Northeast China (NE China), spatial and temporal variations of extreme precipitation in the last 50 years are analyzed in the present study.
Data and Methods Study Area.
Data.
The data were provided by the National Climatic Center (NCC) of the China Meteorological Administration (CMA).

Deformation twinning due to low SFE is observed even in the case of low reduction in thickness.
As the reduction increases, grains are refined by intersections of shear bands.
The reduction in thickness was 10 to 20% per each pass.
The maximum total reduction applied was 90%.
Single iteration clean-up of EBSD data was performed to reduce the point of zero solutions.

Rough set theory has the ability of data mining and is able to reduce redundant data.
Financial Crisis Prediction Based on Improved Neural Network The rough set theory can realize data mining and rule mining through data reduction, approximate classification and data relation reasoning.
It is very suitable for reduction of massive data.
The raw data are discretized by using above discretization rules.
So the raw data table is changed into the decision table.