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Traffic flow and time headway data are extensively used for this study.
Case Study Area and Data Description The data used for this study obtained from a study conducted in Denpasar, Bali [5].
Table 2 shows traffic flow data during 10 hours of observation period.
Following a previous method used in Thailand [3], flow rate and traffic composition classifications for 1-minute interval are established for this data.
The data therefore, is statistically fit to use in the analysis.

Water resources management requires making full use of water resource, but involved in various data of domestic, industrial, agricultural aspects and so on.
The calculation of water poverty index in Reclamation Area from 2000 to 2009.In order to eliminate the influence of the evaluation indexes dimension, firstly the sample data set {x (i, j)} needs to be made standardized treatment [6].
To keep consistent with change information of the evaluation indexes, standardized formula can be taken for: The bigger the x(i, j) is, the more optimal type index is : （4） The smaller the x(i, j) is, the more optimal type index is : （5） Where, r(i, j) is normalization data of the first i sample of the first j index, i=1~n，j=1~m;x(i, j) is the first j index first i of the samples the original data of the first i sample of the first j index; is maximum value of the first j index; is minimum value of the first j index.
To guarantee the WPI calculated value between 0~100, during the process of the specific calculation normalization data needs to be multiplied by 100.
Data Processing Methods and Application in Agriculture .Beijing: Science Press.2006,156 [7] Reclamation economic statistical year book.China Statistical Press. 2001,2006,2010Year .

Data (2019), DOI: 10.1021/acs.jced.9b00886 [8] Y.
Sum, Phase equilibrium data of methane hydrates in mixed brine solutions, J.
Data. 61 (2016) 3607–17
Linga, Hydrate phase equilibrium data of mixed methane-tetrahydrofuran hydrates in saline water, J.
Data 64(2) (2019) 632–39

The reduction of force in tail segment shouldn’t exceed 5 percent of Tmax , where Tmax is a nominal value which can be calculated through a formula in the Criterion 95.
Whether “flat” means that the continuous acquired force data should be all identical or they are allowed to wave in certain upper and lower boundaries, the explanation is not clear.
The final algorithms are as follows: (1) Preliminary data Preliminary data is a time series which consists of two elements—force and displacement acquired during press-fit process, the time series is symbolized by: where represents that the force value corresponding to displacement si is fi
(6) Judgment to the length of flat parts in the middle of the curve In middle segment, if exist a series of data x1(f1, s1), x2(f2, s2), x3(f3, s3) … xn-1(fn-1, sn-1), xn(fn, sn) , they meet the following two conditions: a) The maximum difference between any two forces is under 2.0kN, 2.0kN is a threshold value set according to the resolution ratio of print report; b) the length exceeds 2mm, that is sn - sa≥2mm, 2mm is a threshold value set according to the resolution ratio of print report, so this part is regarded as a flat line(symbolized by L1).
Program implementation The whole program mainly focuses on curve judgment, includes the functions of data processing, curve judgment and data query.

Technical data of the solar farm The solar farm has a capacity of 20 MW, which is mainlycomprised oftwo solar blocks, i.e.19 MW fixed installation block and 1 MW tracking system.
Results and Discussion 4.1 Normalized output energy profiles According to the data record, twoperiods’ data is lost due to themalfunctionsof main transformer, from 2012-1-1 to 2012-1-19, and from 2012-5-17 to 2012-6-17 respectively.
As a result, the measured data should be modified by an appropriate method..Fig. 2 shows themeasured normalized energy yield and modified data in 2012, and illustrates the relationship among monthly output, solar irradiance and temperature.
By comparative analysis of the original data, the characteristics can be described properly.
Lei Liangto provide us with long-term data acquisition.

Table 1 Primary data of hydraulic turbine generator unit about the southwest hydropower plant No.
According to the operation data of the power station records, in June 2010, working head is 62.12m, No.1 and No.2 units worked at full load, but the units all emerged vibration.
From the actual plant situation and the existing domestic data, taking the following methods can reduce or eliminate the channel vortices
In the day-to-day running of power plant, technical staffs should record all the vibration data, and define the vibration area of the unit.
Noise reduction in a low head francis turbine caused by runner inter-blade vortices[J].

Data from SGs were recorded, stored and evaluated using two acquisition systems: the wired BMCM system [2].
The system was controlled using NextView 4.2 data acquisition software [3].
Fig. 5 Compression strength reduction due to the presence of defects.
The FOBG and SG strain data coincide up to 45 kN where buckling of the panel initiated.
In the skin bays, the difference between FOBG and SG data occurred in consequence of buckling effect and sensors positioning in panels.

A truncation parameteris introduced to control the reduction of points with low weight value from the mesh.
The Improved PMF Algorithm and Its Implementation Process Considering to the influence of initial error on PMF algorithm, we give an improved terrain aided navigation system: through echo sounders to obtain a large of real-time submarine depth data, so it can search in a large range.
The performance index is mean square difference (MSD) algorithm, defined as: (1) Where is the real-time measurement depth data,is the storage data in digital map, is the length of data sequences real-time measured .
(2) the current depth data of the underwater vehicle is obtained by sensors, namely real-time map
(3) take output position from INS as the search center, determine the size of search area and then get the corresponding data from digital map as the reference map

Fig. 3 Hardness profile data of nitrided layers in smooth and rough samples.
In Fig. 8, the fatigue data for all nitrided specimens (smooth and rough) are plotted together.
Discussion Let us now distinguish between the fatigues data of rough and smooth nitrided samples which is performed in Fig. 9.
It could be achieved when distinguishing locations of the crack nucleation related to individual fatigue data as shown in Fig. 8.
(ii) The common S-N curve for all nitrided specimens was located well above both the S-N curves of virgin specimens but exhibited a rather high scatter of data.

Technical data of AAC panels - Producer: Ytong Property Units AAC Block Size mm 600 X 200 X (75 to 300) Size Tolerance mm +/- 5mm in length +/- 3mm in width & height Compressive Strength N/mm2 Min 4.0 Normal Dry (Oven Dry) Density Kg/m3 551 to 650 Thermal Conductivity "K" W/m-k Max 0.24 Drying Shrinkage % Max 0.05% Fire Resistance Hrs. 2 to 6 (Depending on thickness) Sound Reduction Index Db 45 for 200 mm thick wall It has been noted that during the exposure to fire, the overall appearance of the material has not changed.
Technical data of fireproof wood panels - Producer: S.C.
Technical data of insulation panels - Producer: NMC Sa Belgium Thermal transmission coefficient Nominal thicknesses (mm) Ktotal (kcal/m2.h, 0C) Ktotal (W/m2. 0C) 40 0.44 0.52 Weight Thickness (mm) Kg/ml Kg/m2 40 11.2 10.2 Acoustic insulation Frequency Hz Insulation dB 125 25 250 27.5 500 29 1000 29.5 2000 31 4000 365 Two supports/One span Thickness (mm) Load (daN/m2) 40 60 80 100 120 150 3.10 2.90 2.70 2.50 2.20 Three supports/Two spans 40 3.40 3.20 3.00 2.80 2.5 In the first 10s of fire exposure, the material starts to deform; after another 10 seconds, the material starts to melt and burn with flame, generating a highly toxic smoke.
Technical data of expanded polystyrene panels - Producer Arco TECHNICAL DATA SHEET Unit Value Method of determination Name EPS ARCO EPS 80 GRAPHITE Thermal conductivity standard value W/mK 0.032 EN 12667 Thermal conductivity calculation value W/mK 0.036 Tensile strength kPa ≥150 EN 1607 Bending strength kPa ≥115 EN 12089 Water absorption trough total immersion % ≤5% EN 12087 Dimensional stability in specified temperature and moisture condition % 1% EN 1604 Dimensional stability in laboratory condition % ≤2% EN 1603 Thickness mm ± 1mm EN 823 Length mm ± 2mm EN 822 Width mm ± 1mm EN 822 Flatness mm ± 3mm EN 825 Perpendicularity mm ± 1mm/1000mm EN 824 Compression strength at 10% deformation (stand.)
Technical data of plasterboard panels - Producer Saint Gobain Plate type DF 13 – 2.60 (12 mm thick) Fire reaction class according to SR EN 13501-1: A2-s1, d0 (B0 SR EN 520 Coefficient of resistance to water vapour diffusion μ Dry Wet SR EN ISO 10456 10 4 Thermal conductivity λ (W/(m·K) 0.23 SR EN ISO 10456 Sizes of contraction and dilation At 1% variation of air humidity (mm/m) At 10 Kelvin temperature variation (mm/m) 0.005 – 0.008 0.013 – 0.02 Gross density (kg/m3) ≥ 800 DIN 18180 Gross density (kg/m2) Plate thickness 12.5 mm DIN 18180 ≥ 10 Compressive strength at compression fc, 90, k (N/m2) ≥ 5.5 DIN 1052 The characteristic resistance at bending fm, k (N/m2) Parallel to fibre direction Perpendicular to the direction of the fibres DIN 1052 ≥ 6.5 ≥ 2.0 Elasticity mode E medium Emean (N/m2) Parallel to fibre direction Perpendicular to the direction of the fibres DIN 1052 ≥ 2800 ≥ 2200 Burst breaking load (N) Parallel to fibre direction Perpendicular to the direction of the fibres SR