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As the automobile-bodies point cloud had the traits of large geometric dimension, huge data and rigor reverse precision, the improved iterative closet point algorithm (ICP) is put forward.
It basically consists in finding the correct alignment between two or more sets of data, based on their intrinsic properties, and plays an important role in today’s computer vision.
Starting from an initial rough alignment of the data, the ICP processes iteratively.
The main advantage of the k-D tree is that it permits to use multi-feature data and to compute the real closest point.
So, it is the emphasis of future work that how to speed up the ICP algorithm by three methods: reduction of the number of iterations, reduction of the number of data points and acceleration of the closest points search.

Several techniques for addressing this issue via indirect coupling of phase data with CALPHAD software have been developed [3,4].
Both the data structure used and the method of parameterization of the thermodynamic liquidus are analyzed.
The literature on data reduction for quaternary systems is scarce.
Therefore, the existing database of the quaternary Al-Si-Mg-Fe system was modeled and analyzed to gain a thorough understanding of data reduction as applied to this type of system.
The regression model is run using Matlab 7.0 and the COST2 thermodynamic database was used as a data source.

The Kansei Engineering is applied to the drum washing machine aided by a variety of engineering mean.Semantic differential(SD) is applied to extract the kansei tags.Multivariate statistical analysis method is also used for data mining.The data of design elements is processed by principal component analysis(PCA)and SPSS.
In order to ensure the rationalization of perceptual information to be stable and reliable , multivariate statistical analysis,PCA and SPSS software have been used in the data analysis process.
All selected product samples comprise a set X, where n is defined as the total number of selected product samples and k is the number of paticipants,as shown in eq.1 As the emotional evaluation varies from person to person, the raw data is filtered by examining the discreteness of the data which includes the calculation of average values as eq.2 and standard deviation test as eq.3.
PCA and SPSS are also discussed as the assistant date mining tool.The data of design elements is processed by PCA which is used to bulid the relationship between the user and product.
[9]Huiwen Wang,Rong Guan,Junjie Wu.CIPCA:Complete-Information-based Principal Component Analysis for interval-valued data[J].

Shuttle Radar Topography Mission (SRTM) terrain data is used in simulations to investigate the performance of RRBPF.
Inertial Navigation System (INS) is often regarded as the primary navigation data source.
SRTM terrain data with the resolution of 90m used in the simulations is obtained from the International Scientific Data Service Platform [9].
The terrain data covers the area of Sichuan Province.
With the bilinear interpolation technology, we get the elevation of any position within the range of terrain data.

At the same time, growing concerns regarding global climate change are pushing companies and governments to addressing carbon emissions reductions.
The data is for U.S., however, the data is quite similar to the Western countries.
Underlying these product and process innovations are materials and materials processing developments that enable performance breakthroughs and radical cost reduction.
The Panel identified several areas where MSE breakthroughs could be the key enabler for high impact energy efficiency and carbon reduction solutions.
However, this approach also holds promise to yield significant energy and carbon emissions reductions in many parts of the energy sector.

In some cases, empirical data and the experience based design procedure can be combined with Finite Element Method (FEM) based analysis to reduce time and cost.
The methodology for process sequence design combines experience based empirical data obtained through previous designs, design rules and numerical simulations including plastic deformation and friction.
The design predictions, made by using empirical data and FEM, were compared with experimental data.
For the given reduction and initial blank diameter (49.53 mm), the punch diameter is 28.98 mm.
The experimental data was obtained for the strains up to 0.53.

(a)5% area reduction ; (b)50% area reduction.
While the billet rotates and moving along the major axis continuously ，reduction extent increases and plastic deformation in it accumulates and develops successively.
The distributions of the effective strain on the cross-section of the billet , in the 5% area reduction and 50% area reduction, are shown in Fig.5.
In this charm, the data of maximum effective strain is 0.795, but that in center zone is 0.765.
A wide range of rolling conditions were considered by varying the billet diameter, friction coefficient and the cross-sectional area reduction.

Research data of flow local properties.
Measurements (fig.3, b) correspond to the data of A.Wegmann, P.
This information also corresponds to the experimental data [5].
On the figure 6 there are represented the data of distribution of wall friction over the pipeline and reduction of wall friction relative to high-viscosity core due to formation of water ring.
The data describe the behavior of friction factor at the condition of steady turbulent flow (D=5,6mm.

Data can also be used by future professionals responsible for the management and maintenance of the future building.
Advantages of BIM: The main advantage of BIM is accurate geometric representations of parts of buildings in an integrated data environment.
· Controllable life cycle costs and environmental data – The environment is more predictable and the life cycle costs are more understandable
Some software solutions allow for remote data access using cloud computing and enable thus to handle flexibly information and data from any remote computer or device that supports this service.
[6] FREEMAN S., Data rich modeling tools may translate into dynamic new facility management capabilities.

., LTD, China a 310177194@qq.com, b liusanmingxyx@163.com, c lvyonghai86@126.com d zouyang@shanghai-electric.com, e 644526998@qq.com Keywords: Safety evaluation；Multi-scale；Noise reduction； Hilbert transformation；Fault diagnosis Abstract.
In the process of fault diagnosis method based on multi-scale wavelet decomposition reconstruction and the Hilbert transformation, firstly, the wavelet noise reduction approach was used to filter out the noise of the vibration signals.
Fig.5 high-frequency reconstruction figure was gotten through using Multi-scale wavelet decomposition on pure vibration signals after wavelet noise reduction.
Engel, and WGui, Survey of the application of basic data-driven and model-based methods in process monitoring and fault diagnosis, in The 18th World Congress The International Federation of Automatic Control.
Wind turbine condition monitoring based on SCADA data using normal behavior models.