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The sampling data were off-line analyzed and processed.
Its general objectives are (1) data reduction and (2) interpretation.
The k principal components can then replace the initial p variables, and the original data set consisting of n measurements on k principal components. 　
Data Disposal and Analysis of characteristic information.
Based on the principal component analysis, the data in Table 1 are processed.

Test data Test of ice storage process starts at 19:00 on August 19, 2010 and ends at 3:30on August 20, 2010, the total time of thermal storage is 8 hours (ice storage time is 7.5 hours).
Detection data in ice storage process shown in table 2.The total ice storage capacity is 18513 kWh, the total power consumption during ice storage is 6268.4kWh.
Detection data in ice discharge process is shown in table3.
The data can be used to comparing the economy of cold source
(4) The test can provide reference data for compared to ice storage air-conditioning system and traditional air-conditioning system and especially for the optimum design and economic operation of other ice storage systems in Yangzhou. 

This method can make new data to add to the specific position of the board simply.
If one data of bit boards is 1, Boolean condition of the data is true.
If one data of bit boards is 0, Boolean condition of the data is false.
This representation can improve the efficiency of reading and storing data, and judge the connection and threat of the stones in evaluating conveniently.
But there is more to iterative deepening than just a reduction of storage space.

Skeletal tracking is to produce X, Y, Z data to determine these skeleton points.
The Kinect manages to provide the depth data of each node (Z value), but it can't use, this looks very waste.
In the coordinate space, the depth data is needed in.
That is to say, the depth value is smaller, and the bigger images, namely the figure is closer to Kinect, the skeletal data is more.
Skeletal tracking engine can recognize up to 20 joint point data.

Assume x(t) (t =1, 2, …, N) is a set of stationary random sample data, then, the following equation can be created
The end effect may cause divergence on data ends of the local mean function line and the local envelope function line and finally lead to serious distortion of decomposition results.
In addition, the singular value of a matrix also has such characteristics as scale invariance, rotational invariance and dimensionality reduction and compression [5].
The sampling frequency is 2048Hz and the rotation rate is 6000 rpm. 10 sets of data are extracted randomly from such 4 types of data respectively to be sample data and the remaining data are used as test data.
The local mean decomposition and its application to EEG perception data.

First, establish a comprehensive evaluation index system, then list indicator data matrix X.
Processing the raw data into the naturalization analyze data which is a mean of 0 and variance of 1, the original data matrix X is then converted to standardized covariance matrix S.
Substitute the original data of each unit into the equation to calculate the value of comprehensive evaluation, then analyze and compare them.
b) The raw data was made standardized by using SPSS software through the process of Analyze-Descriptive Statistics-Descriptive, standardized result is shown in the matrix below.
c) Call SPSS software through the process of Analyze-Data Reduction-Factor to calculate the Covariance matrix which is Correlation coefficient matrix.

As a case study, we select 30 provinces of mainland China except for Tibet considering the availability of data.
Detailed data for energy consumption come from National Bureau of Energy Statistics of China (2010), while the data for GDP, forest area and, population are from China Statistical Yearbook 2010.
Lacking of sufficient data on the environmental capacity, the forest area is used instead.
However, we modeled the two-stage optimization only based on data of year 2009 considering the simplicity for calculating.
This is worth exploring although it may produce new problems such like allocation criteria, data processing, etc. in the future research.

We collected data using an HOBO humidity and temperature data logger, solarimeters, heat flux sensors, and thermocouples.
As shown by the data (Table 1), the heat flux of the top surface of the concrete coated with UU500 was higher than that of bare concrete by 20 W/m2.
For this reason, we used the temperature and heat flux data of the top surface at 360 minutes (Table 3) to estimate the radiative cooling coefficient Ex.
First item of experimental data after turning off lamps Specimen Irradiated heat Top-surface temperature Top-surface heat flux (W/m2) (°C) (W/m2) Bare concrete 0 68.42 -104.2 Concrete with UU500 coating 60.7 -74.9 The experimental data obtained after the lamps were turned off show that the heat flux through the top surfaces was negative, which means that in the absence of a solar radiation, the two specimens began to continuously give out heat.
Integration of thermal insulation coating and moving-air-cavity in a cool roof system for attic temperature reduction.

The Data Selection and Processing.
The iron and steel enterprises statistical data is from 2003 to 2012.
In model estimation, in order to facilitate the calculation data, the explanatory variables are unit conversion.
The other selected data are from statistical yearbook of the National Bureau of statistics and Chinese statistical yearbook on science and technology, to ensure the authenticity of data.
Analysis and Countermeasures of the Empirical Results Data Analysis.

PCA is intended to reduce the huge amount of acquired data and to describe it by as few factors as possible.
According to the data from the spectrometer, a linear least-squares fit was used to retrieve the urban area trace-gas concentrations.
The factors are orthogonal, i.e. they are independent so that a part of the information of the data set is represented by only one factor.
The factors are calculated for the whole data set.
Principal component analysis is performed to the detect data of trace gases.