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The data before repair include the environmental or operational influences, whereas the data after repair represent the current structural condition.
Introduction Structural health monitoring (SHM) is based on reference data, or training data, collected from the undamaged structure.
Therefore, the test data can also fall beyond the training data, making the estimation more inaccurate.
The training data consist of reference data before and after repair. 6.
This paper introduces a data-based technique to utilize the information from two or more structural conditions in the training data.

Thus a study using more recent data to analyze the energy consumption and major environmental emissions in urban passenger transport is crucial.
Methodology and Data The LEAP model.
However, the increase speed of total energy consumption have different degrees of reduction in the case of adopting different energy saving and emission reduction measures.
For nitrogen oxide emissions, the emission reduction effect of scenario 2 and 3 are almost the same.
Meanwhile the reduction effect of SO2 emission under scenario 3 is better than that under scenario 2.

In order to facilitate the use of the data in the scene recognition, we save the depth data and RGB data together.
Flowchart of Data reconstruction Figure 2.
After processing, the point cloud data is still very large, in order to accelerate the data processing speed, sampling process is needed, so that the final data is approximately the 1/5 of the total number of original data.
In order to ensure that the final extracting plane data are valid, before running the RANSAC algorithm, it is necessary to check whether the number of data points in each category is greater than the threshold value after clustering category data, that is to eliminate the noisy point class and small data sets.
Thanks to sampling and noisy reduction processing of the original data, there are many "holes" in this picture, e.g., screen of the computer shown in Figure 3(d)

Powdered chicken feathers–PCF (4% w/v) were added to the medium due its nutritional properties, its potential to be used as a solid supporting material to optimize bacterial growth (data not published) and also due to its previously reported arsenic biosorptive capacity [3].
The same feature was observed in this study (data not shown).
It was observed that the deleterious effects on bacterial growth caused by As(III) are less severe for those experimental flasks containing PCF (data not shown).
Reduction of chromate (CrO42-) by an enrichment consortium and an isolate of marine sulfate-reducing bacteria.
Sulfate reduction and copper precipitation by a Citrobacter sp. isolated from a miningarea.

Some forms of data reduction are essential to make optimal use of the data information.
The independent source matrix S, resulted from ICA, was used as input data to PCR 3.
An absorption matrix for calibration D was built up from these data.
The essence of the step is the pseudo-rank determination of the raw experimental data.
The method can obtain very selective information from unselective full-spectrum data.

However, some existing barriers have impeded the usage of data, such as inefficiency mode of data reporting and transmission, sluggishness of data collection and summarization, deficiency of data standardization and serious information asymmetry.
And the basic energy data acquisition systemcan provide data service for the analysis according to the demand of index management.
The real time energy data can be monitored, and the collected data can be replied to the info platform
Data processing and storage 4.1 Data processing The data cleaning, integration and load can be implemented automatically on the acquired data to maintain consistency and renewal.
Benghanem.Measurement of meteorological data based on wireless data acquisition system monitoring[J].Applied energy. 86(2009)2651-2660

In addition, very high strength steels can be cold rolled twice with very small reductions.
Rolling models are usually overestimating roll flattening in the case of small reductions.
Model describes the effect of reduction, strength of steel strip and roll radius.
Despite the uncertainty denoted by the error bars in data the phenomenon can be noticed.
Measured rolling force values from SSAB Hämeenlinna mill are plotted against reduction.

Threeteen test data were obtained from each sample.
Eight test data were obtained for each phase.
Table 3 Test micro-hardness values Structure Sampling size Test data Hi, i=1, 2, …, nh (KHN0.98) Average Value (HV10) Standard deviation (HV10) Cov 1 2 3 4 5 6 7 8 Ferrite 8 253.32 225.87 220.06 224.64 259.28 220.06 232.17 221.25 104.037 6.968 0.06697 Pearlite 8 277.83 292.17 334.84 266.41 285.04 312.82 267.36 343 133.334 13.282 0.09961 Macrostructure Check.
Reduction of area is up to 45 % which are much larger than those of conventional ferrous alloys.
Significant neck reduction was appeared before the specimen failure.

The simulated data are also shown (solid and dashed lines).
In order to compare as close as possible the experimental data with the simulated results a routine was developed [11] to evaluate the Raman shift based on a pre-calculated stress field by numerical or analytical models.
A morphological analysis by Secco d'Aragona etching confirms this reduction.
The data of the second row refer to the annealing at 10500 C. 1.
The data are obtained by SEM inspection after Secco etching.

Data sources and feasibility analysis A.
So high dimension data should be reduced.
Data is discretization, and data variables can express by a few control factors.
So the pattern classification of hypersonic inlet can reduced, and this is a standard pattern recognition problem, Manifold learning nonlinear dimension reduction method can be used to high dimensional data classification.
There is much noise by data set or the branch from abnormal data.