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The relationship between the drag reduction efficiency and heat transfer reduction was analyzed.
The heat transfer reduction can reach up to 80~90%, which is greater than the drag reduction.
All the data were collected by data acquisition board and processed by computer.
The results calculated with (7) and the measured data are shown in Fig.5.
Apparently, the measured data of HTR due to drag reduction induced by polymer was greater than the calculation results according to the Gnielinski formula.

Formerly, the setting of the parameter of the strip in the above-mentioned five parts in the process of production in cold reduction mill of roll, we adopt the method of thinking and setting alone.
When i=0, ( is the number of transverse distribution in the coming strip ); B—the width of the strip; —the average backward pull in framework i of cold reduction mill of roll; —the average forward pull in framework i of cold reduction mill of roll.
Similarly, we can understand from the model of elastic deforming in roll-system, the number of the exit thickness distribution after framework 1-5 could indicate by Eq.2 : (2) In this formula: —the setting value of the depressing rate in framework i in cold reduction mill of roll; —the force of the bending and working roll in framework i in cold reduction mill of roll; —the distribution of the roll shape in the working and sustaining rolls in framework i in cold reduction mill of roll.
In the procedure of setting and calculation of the parameter of the strip, we adopt the data under the condition that we have the experimental findings about the camber and template of the coming strip.
The Table 1 show the setting data of the bending force of framework 1-5 after the combined setting technology of the parameter of the strip, and the setting result of the bending force in traditional way of optimization.

Linear and exponential curve fit of experimental data is performed respectively to describe the evolution of damage as well as the descent of ultrasonic velocity with respect to the loading history.
The reduction degree of ultrasonic velocities is calculated according to following equation.
But then it can be seen from this figure that the mix proportion has no visible effect on the relationship between the damage and the loading history, so two groups of data can be investigated together.
The rule of ultrasonic velocity reduction for concrete specimen experienced hydrostatic compression.
And that induce the reduction of strength and the descent of ultrasonic velocity.

Import tariffs equivalents calculation based on carbon tariffs The data used for this study is based on version 8 of GTAP-E (Global Trade Analysis Project- Energy) database.
The benchmark year of the data is 2007, which covers 129 countries/regions, and 57 sectors.
We adopt Walmsley’s recursive dynamic method to update the data in base year (2007) to 2020.
The updating processes for population, labor, capital and GDP data are carried out in three phases (2007-2010, 2010-2015 and 2015-2020) to reflect the endowment and economic development [8].
Thus, the impacts of carbon tariffs on global and China’s emission reduction are very limited.

The other is the operation model change, introduction of energy saving and emission reduction technology, and reduction of traditional IT sales costs.
All the software runs in the cloud computing data center.
Business data is also stored in the cloud data center.
The security of cloud computing data center has two main aspects: First, security issues of cloud computing data center environment itself.
Cloud Computing Data Service Availability Requirements.

Reflection upon Energy Saving and Emission Reduction in Colleges in the Context of Low-carbon City Construction HuHuiFen Zhejiang Shuren University, Capital construction department of logistics, Hangzhou , Zhejiang 310015 Keywords: low-carbon city colleges and universities energy saving and emission reduction current situation measures.
The resolutions for energy saving and emission reduction in colleges and universities Ever since the beginning of the year 2008, Zhejiang Shuren University has began the project of water balance test in order to promote energy saving and emission reduction in an all round way.
It turns out to be quite effective in eliminating purposeful waste phenomena and promoting rational use of water and electricity. 3.1 Strengthen publicity for the improvement of energy saving and emission reduction awareness in both teachers and students Energy saving and emission reduction require involvement of all the students and teaching staff.
All these will help create an enthusiastic atmosphere of energy saving and emission reduction to attract the involvement of teachers and students so that they can have a deeper understanding. 3.2 Improve and apply technologies for energy saving and emission reduction The accomplishment of effective energy saving and emission reduction requires much investment in improving related technologies.
What’s more important is to better management in water and electricity use and promote the supervision, data collection, verification and announcement of energy consumption, bringing into realization double management of both the current energy saving and the outcomes. 3.4 Invest more capitals into the project of energy saving and emission reduction Firstly, try to win national financial support by learning about various policies about energy saving and emission reduction, using these policies for good and making detailed plans to be delivered to the authority.

Minimum Noise Fraction was used for dimension reduction.
And then the RX algorithm and KRX algorithm was used to detect the data after dimensional reduction.
And it indicates a lattice in high-dimensional space if hyper spectral data is considered as a collection of multi-data.
There are tow main problems for entire anomaly detection: firstly the background is so complicated that would probably leads to over-anomaly detection, secondly the comparatively low level of objectives would leads to higher false alarm rate and lower detection and minimum noise fraction is used for dimension reduction of data aiming at the disadvantage of large number of data for hyper spectral images.
The spatial size of the data is of 100 × 100 pixels, containing 38 targets to be detected.

There are a few reports regarding microalgal photo-biocatalytic asymmetric reduction reactions.
The data are not given, because we have discussed before [8].
Fig. 2 Photo-biocatalytic asymmetric reduction of EAA by various microalgae.
Fig. 3 Photo-biocatalytic asymmetric reduction of ACP by various microalgae.
Fig. 4 Effect of culture time on the asymmetric reduction of EAA by microalgal photo-biocatalysis.

Time series on“cleaned data” In this section we briefly recall the main steps to the noise-reduction scheme proposed in [4].
A phase portrait of cleaned version is shown below (Fig. 3) where it can be compared with the original data.
Conclusion We apply the noise reduction scheme to numerical simulation data sets, some techniques from nonlinear dynamics are adopted to identify the different dynamics regimes of system behavior.
Nonlinear processing can lead to consistent and reliable noise reduction, this done, much more information can be extracted from the numerical simulation data.
Kantz, Noise in chaotic data: Diagnosis and treatment.

Through the general data packet service [1] transmission method to collect the hydraulic characteristic information can be transmitted to computer, and then faults diagnosis.
The main idea of ​​rough set theory is in the premise of maintaining the same classification ability, through knowledge reduction, decision making or classification to export issues rules and the reduction of which can be used for pre-processing on high-dimensional data to remove redundancy property, so as to achieve the purpose of dimensionality reduction in fault diagnosis, the use of rough set theory to specific monitoring and diagnostic data processing, diagnostic information can reduce redundancy, improve the diagnostic efficiency [2].
Forklift hydraulic system is characterized by relatively large parameters, not all selected; (3) Creating the relevant target data set (the original sample database), in other words, knowledge acquired data samples; (4) Data reduction, including attribute reduction, value reduction; (5) Mixing rule knowledge base generated.
Attribute reduction is equivalent to eliminate some unnecessary ranks from decision-marking table; attribute value reduction is eliminate some unnecessary attribute value from the table.
Decision-making table without any redundant information can be get by the manner of attribute reduction, value reduction, and shown as in table 4 ("*" indicates can not be considered).