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Haniff, using shape data to inspect defects on a glue process [8].
Din [9], in his research on data quality for offshore pipeline assessment, discussed noise and data lost during acquisition and transfer.
By understanding ‘what data to be extracted’, proper tools are used.
After the data extraction process is done, the image data is processed to obtain the value for the corrosion analysis.
The challenges are uncontrolled inspection environment, quality of the image and validation of proposed inspection data with the present inspection data.

Instead, data driven methods use previously collected training data from the structure as a reference for deducing impact locations [2,10–14].
However, the downside is that data driven methods are only accurate for the scope of training data given and thus will suffer from reduced accuracy for impact conditions outside of the given training data condition [2,12].
Inclusion of all possible impact variations in the training data is not practical due to the large amount of training data that would amount to.
Data processing and analysis was done using MathWorks MATLAB R2018a software.
This means that it is possible to accurately predict the impact location of various impact cases without having to incorporate them in the training case, leading to a large reduction in required training data and increased feasibility for ANN use in real life conditions.

events to get timely and accurate information on the disaster, provide the scientific and accurate basis for disaster reduction and relief work[2][3].
Camera with Rotary filter system can be synchronized access to four bands of data, according to the actual need to replace the filter, get more spectral information.
In order to ensure the measured data can reflect the reflection characteristics of the test area features, in the whole test area according to various typical terrain, multi-point measurement of statistical average method is adopted to get reflectance values.
According to the needs, select three typical vegetation, water body, bare soil underlying surface type data processing, the result is shown in the figure 2.
In selecting several typical ground typical objects within the reflectivity image (such as water, vegetation, bare soil) as the sample data, statistical average reflectance.

Theoretical Model and Data Sources Input-output local closed model.
Data sources.
The decomposition results and data analysis The influence factors analysis of water consumption change at structure level.
In addition, the water strength decreases, the structure of production and final demand structure changes, lead to a reduction in water consumption.
A Regression Model Based on the Compositional Data of Beijing’s Water Consumed Structure and Industrial Structure[J].Systems Engineering,2008, 26(4):67- 71.

The statistical parameters are based on the available literature, test data and survey results.
In this study, only the first three are considered, the load models are based on the available statistical data, surveys, inspection reports, and analytical simulations.
Table.3 The statistics of the resistance model of suspenders for the example bridge Random variable Distribution nominal value Bias factor Coefficient of variation Normal 1570MPa 1 0.05 Normal 5mm 1 0.05 (2) The resistance model of arch ribs The resistance model of arch ribs of the bridge is calculated using[11] (2) where is the design value of carrying capacity, is reduction coefficient of carrying capacity from slenderness ratio, is reduction coefficient of carrying capacity from eccentricity ratio, and is the design value of carrying capacity of each axial compression short column
From equation (2) to (5), Xu Fuyou[12] gives the resistance model of arch ribs, (6) where and are variables and mean value of which reduction coefficient of carrying capacity is derived from influence of slenderness ratio and eccentricity ration respectively, and are variables and mean value of steel resistance respectively, and and are variables and mean value of which resistance uncertainty from concrete restrained by steel tubular is considered respectively.
The load and resistance parameters are treated as random variables, and the statistical parameters are taken from the available literature, test data and survey results.

According to the analysis of the landslide monitoring data, it is revealed that the amount of the cumulative displacement of the landslide depends on the monitoring cycle.
The correlation study mainly got qualitative relation through analyzing statistical data.
The period of collecting landslide displacement monitoring data is fifteen days to thirty days.
The period of collecting data was increased from 30 days to 60,180, 360 days, and the different ST(T is the period of collecting data T days) in one year were got.
When the monitoring period is Tn+1, it is that a value is increased between two monitoring data based on the period Tn.

Concerning the standard mass, the addition of 4 and 8% has provoked a reduction of viscosity, while the addition of 15% resulted in a rise of viscosity.
Concerning the standard mass, the addition of 4 and 8% has provoked a reduction of viscosity, while the addition of 15% resulted in a rise of viscosity.
Table 1 indicates the chemical analysis data of the standard mass and of the three formulations.
The viscosity range ideal for glasses conformation [10], regarding the standard of adding 4% of albite, has provoked a small reduction of viscosity, which became more expressive with the addition of 8%, especially when in high temperatures.
Concerning the standard, the addition of 4 and 8% of albite has provoked a reduction of viscosity, while the addition of 15% resulted in a raise of viscosity.

European directive on energy performance of buildings (2010) and related national technical rules force reduction of energy consumption of both new and reconstructed buildings due to the so-called passive standard.
The paper demonstrates a possibility of compromise between complicated multi-physical models and nonexpensive thermal evaluations of buildings, as well as some optimization procedures in building design leading to energy reduction.
Some realistic initial and boundary conditions, due to available climatic data, are needed to be joined to Eq. 1, with respect to Eq. 2, too.
The extremely simplified (but non-realistic) model problem introduces only one domain Ω and its boundary ¶Ω where the environmental temperature τ*, as well as the gray body radiation flux g(τ,τ*) by the generalized Stefan-Boltzmann law, introduced in [13], p. 534; this approach takes into account the actual position of Sun on the sky, expected weather conditions, etc., coming from (sufficiently detailed) environmental data, as discussed in [8], [10] and [16].
Reduction of energy ε in (1), hidden in (2), too, to the thermal one may obstruct the detailed analysis of heat transfer in buildings, as well as other simplifications in remaining terms.

The second one is to investigate the performance of solar absorption system arrangement using parabolic trough collector at different ambient conditions following Indonesian weather data.
For the simulation, Indonesian weather data was applied which include solar radiation, insolation, ambient temperature, humidity, main temperature and ground reflectance.
Properties tax in Indonesia was 0.1% assumed without annual increase based on data that there was no change of the tax since 1985 [2] and without any discounts or subsidy from Indonesian government.
A reduction of 37% of CO2 emissions would be achieved.
[12] G.L.Morrison, Sudjito, Solar radiation data for Indonesia, Journal of solar energy science and engineering 49 (1992) 65-76

(28) Rc is volumetric current densities produced in cathode TPB due to O2 reduction by Butler - Volmer equations:
(29) is reference exchange current densities for O2 reduction at the reference concentrations and hc is cathode activation overpotenetials defined as:
, (A m-2) [14] 400 Reaction order for H2 oxidation, [14] 0.5 Reaction order for O2 reduction, [14] 0.5 Model Validation This work validated the results with an available experimental data by Barnett et al. [15].
For a conventional thin film SOFC, the optimal thickness of the electrode particles in a SOFC film for both anode and cathode sides should be 1370 nm with the optimal radius of cylindrical shaped particles of 4.34 nm.The model analysis shows the cell performance strongly depends on the electrode microstructure.The model-predicted results are validated with the experimental data found in the literature.
A good agreement is obtained between the predicted values and the measured data.