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The information techniques being used in product innovation include PDM (product data management), CAD (Computer Aided Design) or data mining et al. [9].
But most data set comes from a certain business, knowledge acquired from which is only reflected a part of affairs, most of the product innovation is based on incomplete data.
Intelligent Knowledge (IK) for Innovation 3.1 Creation Process of IK As mentioned above, there are many data sources in the information age from which data mining discovered lots of knowledge.
Primary knowledge is knowledge from data mining but only a part of a given knowledge meets interest of human beings.
Han and Kamber, M., Data Mining: Concepts and Techniques (2nd.ed), Morgan Kaufmann, 2006 [13] C.Y.

The process data is used for clustering analysis to acquire the state in advance.
The simulator for the Tennessee Eastman process is used to generate normal and fault data.
We select 100 process data from the normal data and the first two fault data respectively, as the original data.
The blast furnace is a huge chemical reactor where reduction reactions take place.
The data comes from three steel grades, including 81, 138, 200 samples respectively.

Although with the accumulation of technical data concerning the developed materials and structural elements obtained from the research programs, they are not systematically used in large scale in civil construction.
Baseline data, implementation records and progress reports are necessary to monitor and evaluate the achievement of the project’s objective.
% of effective cost reduction in implemented housing using NOCMAT.
It should reveal the effective changes observed by government action and relative advantages of the innovation to the users, improvements in warranty, reduction in complaints, new norms created or adopted for constructions, reduction of construction deficit.
It should present the economic and social advantages pointing out changes in local culture, increased applications for constructions, pollution reduction, waste reduction, number of inhabitants benefited by the project implementation, increased Human Development Index by NOCMAT utilization, improved dissemination of technical information.

In terms of nano-particle addition, its influence on the mechanical properties are not notable; enhancement of the elastic modulus, yield stress and tensile strength are negligible, and there is a small reduction in ductility.
A, B, C and D in Fig. 3a) were drawn along the gauge section of the specimen and a high-speed camera operating at 100,000 frames/second was utilized to capture visual data on the specimen deformation.
With respect to nano-particle addition, for strain rates in the range of 0.0012-1000s-1, its effects on the Young’s modulus, yield stress and tensile strength are negligible; there is actually a small reduction in ductility.
However, considering that the experimental data for tests on the nanocomposite at 1600s-1 is limited, this observation remains to be substantiated by further tests.
The addition of nano-particles results in little influence on the mechanical properties of the alloy; enhancement of the Young’s modulus, yield stress and tensile strength is negligible, while there is a small reduction in ductility.

At 500°C, the cermets showed a small reduction in their mechanical performance.
Results and Discussion For the analysis of the mechanical results, some data on the Capirona and Capinuri precursor woods must be considered such as the basic density they present and their maximum resistance to compression in a direction parallel to the fiber.
Physical and mechanical data of interest of the study woods.
Both materials show a reduction in their maximum compressive strength, reaching values of approximately 594 MPa for the Capinuri cermet and 363 MPa for the Capirona cermet.
Furthermore, the reduction of stiffness is observed in the elastic zone, as well as a transition in the failure mode going from a brittle behavior at room temperature to a more ductile response, revealed with an initial linear stretch followed by an increase in resistance.

In fact, the theoretical basis of the defect detection methods discussed in this article is that bars local stiffness reduction appears because of the crack and thereby causes curvature mode shapes mutation.
Table1 Local equivalent elastic modulus of cracks with different depths Crack depth/mm 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 E/MPa 2.1e5 2.0e5 1.7e5 1.4e5 1.1e5 7.8e4 5.5e4 3.6e4 2.2e4 7.8e3 3.1e2 In order to achieve the quantitative relationship between different cracks depths and stiffness (elastic modulus), we need to carry on the data fitting to obtain their mathematical expressions.
The computational formula of is as following: (1) Where, , is respectively test or calculated data and fitted data of the ith node; is arithmetic average ofor.
Fig.5 Relationship between the crack with different depths and elastic modulus Carry on the linear, quadratic and biquadrate fitting to the data of table 1, we can obtain the relationship between the cracks with different depths and local elastic modulus on the premise that the crack width is 1 mm as shown in figure 5.
New techniques for order reduction and damage detection in structural and rotor dynamic systems [D].2010

Cell morphology was assessed by fluorescent staining with hypericin and viability test was performed by the MTT dye reduction assay.
Such data support infrared data and are arguments in the explanation of induction of bioactivity.
According to data of table 2 the following scale for corrosion rates was supposed: natural passive TiAlNb < chemical bioactive TiAlNb < electrochemical bioactive TiAlNb.
From the open circuit potential in time data (fig. 5) at very short time of immersion of electrode in artificial saliva (5000 min), the results present a better stability of electrochemical deposition samples in comparison with the untreated and chemical deposition samples.
The viability test performed by the MTT dye reduction assay Conclusion Bioactivation method is directly related to surface stability and to in vitro compatibility. 1.

Data were shown as arithmetic mean ± standard deviation (M ± SD).
These data did not obey a normal distribution law (by the Kolmogorov-Smirnov criterion).
Results and Discussion According to data of myocardial perfusion scintigraphy with 99mTs-MIBI and metabolic scintigraphy with 123I- BMIPP, the average size of perfusion and metabolic defects in patients with DCM did not exceed 10%.
In the delayed scan, there was a significant reduction in the size of the metabolic defect and an increase in perfusion-metabolic mismatch.
Our data are consistent with the studies of the Japanese authors [12] who showed that the presence of negative perfusion-metabolic mismatch detected using positron emission tomography with fluorodeoxyglucose and SPECT with 201Tl, defines a positive response to CRT.

We can read and operation of the training sample data and sample data to predict two types of data through the program.
Then we divide these teachers data into two parts, data about 2/3 as the training set, the remaining data of 1/3 as a set of prediction samples to be evaluated.
Before model training and prediction, first, the sample data sets need to be pretreated, in addition to converting vector data of teacher evaluation, but also normalizing these data.
SVM can generate model files through the training sample data.
In actual prediction and evaluation of the data does not need to know the number of classes predicted data.

Data Processing of the Logistics System The early processing on the data of the internal resources of the database is mainly to ensure the operation efficiency of logistics system and prevent the data errors from hindering the operation of the system.
And a comprehensive data mining can help acquire more reliable information.
Through the data processing, conditions can be created for the data mining.
Relevance Principle in the Data Mining The application of the data correlation method in the data mining derived from the "relevance principle", which relies on all kinds of the correlation factors in the half-structural data source.
Discussion on the Algorithm of the Association Rules of Data Mining [J].