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In this paper, with the SPSS statistical software, we select the 10 listed companies as an analytical sample, 2012 listed company's annual report for the data source, use the factor analysis method to make evaluation the financial quality of the 10 listed companies.
Selection of evaluation index In view of the accessibility of the data, select the nine evaluation indexes from the quality of asset, the quality of the capital structure, the quality of profits and the quality of cash flow, construct electrical machinery and equipment manufacturing industry listed companies' financial quality evaluation index system.
Data (Table 1) is a collection of 10 listed companies financial data for the year 2012.
14.36 34.2809 0.53 18.1582 CHINA-KINWA HIGH TECHNOLOGY CO. 0.313 3.5947 61.0405 0.83 0.6509 0.26 16.1026 0.0045 -5.1834 ZHONGTIAN TECHNOLOGY 0.8231 3.113 39.4432 1.8008 1.2839 9.36 21.1815 0.598 8.7615 Factor analysis method suitability test Before the given sample index data for factor analysis, numerical input of 10 listed companies in various financial indicators KMO and Bartlett test in SPSS software.
Table 4 Rotated Component Matrix (a) Component 1 2 3 X1 .025 .841 .104 X2 .180 .172 .934 X3 -.855 .066 -.416 X4 .971 -.019 .204 X5 .946 .000 .309 X6 .084 .980 .059 X7 .462 .603 .605 X8 -.079 .922 .117 X9 .931 .200 -.220 Computing factor scores and rankings Through the SPSS statistical software, data processing, as shown in (Table 5), automatically generated Fac_1, Fac_2, and Fac_3 three factor score, the three factor score can instead of the 91.960% of the original data information.

In view of combustion process involves resources (including energy) utilization and reduction of CO2 emission, the related research mainly focuses on the following aspects [3,4]: · Analysis and modeling the energy and resource consumption of equipment, machinery and workstations in production facilities
The concrete data for the six Kyoto Protocol GHGs and their GWP factors can be drawn from IPCC[6].The amount of CFP can be calculated based on the activity data, emission factors of the use of energy, resources, and greenhouse gas emissions, formulated as follows: (1) where ECO2e is the total CO2-eq emissions ;Mi is the quantity of greenhouse gas i; GWPi is its Global Warming Potential ability of each greenhouse gas; EFi is the ith greenhouse gas emission; i = (CO2, CH4, N2O,…); is the activity data at the process step j.
It is well known that the available data (i.e. energy consumption and production data) of the production process is various and complicated for collection instantaneously.
Moreover, much precise data could be even useless due to the method approximations and the related foresight uncertainty.
Therefore, it is worth to concentrate on the measurable index of capacity of expression and evaluation for production data.

This method (NRMYSF) is used to reach a linear, more robust relationship along with smoothing data, generalization of data and construct of new characteristic thus more accurate prediction data are offered [14].
Prediction of stress-strain values need the reversion of data set using inverse factor, then difference error can be calculated.
Normalised data are shown in Fig. 4 showing all peak deviator stresses has become unity at the same axial stress.
The refinement method of NRMYSF enhances the prediction fit to actual data.
Using normalised axial strain analysis, the predicted deviator stresses align with the actual laboratory data.

The implications of these findings are significant, as practical data about the behavior of diminutive like TiO2 nanoparticles has been notably lacking.
All experiments were conducted in duplicate, and the data were averaged and plotted after a paired t-test was conducted at a 95% confidence interval.
Afterward, paired t-test analysis was conducted to obtain the data average.
An exponential decay can be observed from the averaged data in the case of no alum addition (Figure 3).
The study findings are noteworthy, as data consistent with practice has not been shown for TiO2 nanoparticles.

Introduction The achievements of ICA in the separation of speech signals, biomedical signal processing, financial data analysis, image denoising and the application of face recognition, are described in the literatur [2]-[4].
ICA of Mixed Vibration Signal For the array signals, the number of Signals are often more than the number of array elements.Therefore, the first thing is dimension reduction with the process of signal whitening.

According to the equal circuit of solar battery to establish simulation model, then collecting data of adjusting the size of the load resistance, When the Light changing, Fig. 2 is the curve of solar battery’s characteristic.
On the Constant temperature from the curve we know the Open circuit voltage with light from the reduction of decline, on the contrary the Short-circuit current and Maximum output power rise.

In view of the fact that most extensions are built on top of objects which are in use during the construction process the speed of construction process and reduction of negative impact upon the users of the building are fundamental requirement.
According to data from Passive House Center three quarters of passive and low-energy houses built in Czech are built as wooden houses.

Experience shows that the increase of Kn and reduction of τ n will make the system oscillation aggravate.
The two sets of data in the transfer machine can illustrate its feasibility.

System development life cycle and basic risk Phase Basic risk Feasibility Misunderstanding of nature, chance or technology as well as the profit and cost of the problem itself Analysis The lack of understanding to the details of solution researching the problem and opportunity Design Misinterpretation the plan drafted in the analysis phase, or wrongly, partly understanding question about information system design Implement Incomplete or uncompetitive work, or continuing errors happened in the analysis and design phase, inappropriate development tools or using these tools insufficiently Testing Inadequate test data, order or test plan Delivery Preparing for new system insufficiently The main risk level or type can cause different results in Table 1, which may be listed the results of risk in Table 2.
Buy/Promise Information system isolate Short of strategy of business objective Attend Business change Related losses Avoid changes Contingency planning Development Risk Assess and plan Violence and distrust Skill of project management Project management Staffs turnover Study and delay Staffs satisfaction Staff management Development tools Redo Budget and research Substitute Organization Risk Technical competence Quality reduction Human resources plan Outsourcing, recruit, train Technical platform Instability Technical perspective Match Technical life cycle Business advantage weaken Institutional infrastructure Delay and research Orders of information system risk management Information system risk management is a challenging work, because it requires preparing adequately in organization.

TG-DTA data of TEOS and photoresist mix.
[8] Yao-Yu Cao, Nobuyuki Takemasu, Takuo Tanaka, “3D Metallic Nanostructure fabrication by surfactant-Assisted Multipoton-Induced Reduction”, small 2009, 5, no. 10, 1144-1148.