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assunpp@263.net,b1039716857@qq.com,cshayuzhang@163.com,d373752621@qq.com Keywords: Slurry pipeline transportation, Drag reduction technology, Micro-bubble drag reduction, Vibration drag reduction.
Introduction Slurry pipeline transportation has greatly advantages such as less investment, construction period shortly, less environmental pollution and ease of management,causing various aspects of attention.It has been used widely in many fields.With increasing depletion of energy and intensification environmental pollution,energy-saving and emission reduction have to be solved.Thus the research of drag reduction technology plays an increasingly important role.There appears a variety of drag reduction methods.For instance,soluble high molecular weight polymer,fiber material, spiral flow, changing pipe geometry,heating drag reduction and adjusting the size of particles etc.With the analysis of the theoretical knowledge and experimental data to be established,the above drag reduction technologies had been made great progress, but there are some disadvantages and some of the drag reduction technology apply in reality still for a long time.This article will discuss micro-bubble drag reduction
The Technology of Micro-bubble Drag Reduction The Development of Micro-bubble Drag Reduction Technology.
The Technology of Vibration Drag Reduction The Development of Vibration Drag Reduction.
Li: Review of Research on Drag Reduction.

., Huwei, Yunlin 63208, Taiwan ason.summer@msa.hinet.net, blochsieh@nfu.edu.tw Keywords: Electric vehicle, gear data, helical gear reducer, prototype manufacture Abstract.
Then, based on the involute theorem, the gear data of helical spur gear pairs we obtained.
Finally, according to the gear data, its corresponding engineering drawings were accomplished and its corresponding prototype was manufactured.
Tables 3 and 4 showed some important gear data of this two gear reducers.
According to the gear data, the corresponding engineering drawings were accomplished and their corresponding prototypes were manufactured.

Naive Scaler algorithm is used to discrete the risk index data, then an algorithm of attribute reduction based on mutual information entropy is used in decision table to reduce index and build risk index system optimal model.
Naïve Scaler algorithm array the data of decision table in ascending or descending order according to conditional attributes.
The risk index data table is shown in Table 2.
From the result of reduction, “backward purchase method and operate error”, “backward storage technology and operate error”, “backward goods of management technology and operate error”, “a deviation of information in data transfer” are the main factors on the risk index system of distribution obviously.
Conclusions For the distribution risk index of distribution of supply chain in retail enterprises is redundant and it is difficult to determine the decision rules through the complex index, this article provide a risk index reduction model from risk analysis to risk index data discretization ,then to risk index reduction.

Isothermal Carbothermic Reduction Effect of Temperature on the Reduction of Chromite.
The ores had different reduction rates and reached different extent of reduction.
No trace of Cr reduction was observed for SCO reduction in this temperature (Fig. 2a).
It was also noted that the following equation can be used to fit the data of the early stage of reduction up to a reduction time of 20 minutes: -ln (1 – X) = k . t (3) where equation (3) is the kinetic model for nucleation control (Tanaka, et al 1987).
It was also found that the extent of reduction increased with increasing temperature and reduction time.

When the data is evenly distributed, regular interval and regular frequency are commonly used.
When data distribution is very uneven, discretization easily leads to information loss, and affects the final classification accuracy.
Therefore we process the simplified data using SVM training and learning techniques and implement affective semantic mapping.
Discretize the data in decision table by K-means clustering method to four categories.
However, in the case of big data, a more reasonable affective semantic classification method needs further study in the future.

At that time, the COD reduction rate(full aperture) will be 11.2%, the Sulfur dioxide emission reduction rate will be 6.5%, the Ammonia emission rate (full aperture) will be 13%, the Nitrogen oxide emission reduction rate will be 9.5%.
Then from the 35 industrial categories, select the pillar industries in Dalian City, which are also the 7 large industries of energy consumption, and then collect the specific industry evaluation index data of Dalian city in 2011( see Table 1).
Table 1 Evaluation Index Data of the Industrial Sector of Dalian City in 2011 　 The Industrial Output Value in 2011 Industrial Output Value (10Billion yuan) consumption of raw coal (10milion tons) oil consumption (10milion tons) heat consump- tion power consumption (KWH) Petroleum processing, coking and nuclear fuel processing 1296.56 0.14 2485.68 374.70 18.66 Chemical raw materials and chemical-products manufactory 419.60 153.26 141.05 2451.36 14.06 Non-metallic mineral products industry 224.34 211.83 12.20 41.83 20.48 Ferrous metal smelting and rolling processing industry 463.70 47.40 2.57 94.36 12.06 General equipment manufactory 1193.11 11.84 4.15 165.21 29.60 Electricity, heat production and supply industry 107.85 1456.49 0.49 0 15.52 Agricultural and sideline products processing industry 802.43 21.12 5.12 290.19 163.97 Note: Data from the "Statistical Yearbook of Dalian City " in 2012 .
that the Dalian City’s energy-saving and emission reduction work reap preliminary fruit.
But there still have some industries with low efficiency in energy conservation and emission reduction, and the potential to further proceed energy-saving emission reduction.

The effects of reduction temperature and reduction time on the removal rate of magnesium were investigated.
Therefore, the garnierite was treated by carbothermal reduction in vacuum in this paper, and the effects of reduction temperature and reduction time on the removal rate magnesium were studied.
The data of the first 120min was fitted by the least squares according to Fig. 3, and the reaction rate constant K and its correlation coefficient R2 at different temperatures are shown in Table 4.
By introducing the experimental data into the expression of the zero-order reaction kinetic model, the kinetic equation for the removal of magnesium by carbothermal reduction in vacuum from the garnierite can be obtained: 1-(1-α)1/3=(-22850.1/T+2.6296)t (3) Table 4 Reaction rate constant K and model correlation coefficient (R2) at different temperatures Model Number 1623K 1673K 1723K 1773K 1823K K(10-6) R2 K(10-6) R2 K(10-6) R2 K(10-6) R2 K(10-6) R2 D1 11.50 0.7678 14.00 0.7818 25.30 0.8006 36.00 0.9834 122.00 0.9899 D2 6.43 0.7502 7.95 0.7617 15.00 0.7725 22.60 0.9711 105.00 0.9826 D3 1.60 0.7320 2.01 0.7407 4.03 0.7424 6.43 0.9819 47.90 0.9125 D4 1.48 0.7441 1.84 0.7546 3.56 0.7623 5.46 0.9652 29.50 0.9661 D5 -2.62 0.7621 -3.21 0.7743 -5.93 0.7873 -8.70 0.9763 -39.20 0.9829 R1 13.70 0.9362 14.40 0.9276 20.90 0.9276 24.00 0.9843 75.30 0.9974 R2 43.70 0.9271 46.50 0.9167 69.60 0.9137 83.30 0.9872 348.00 0.9735 R3 33.00 0.9070 36.00 0.8929 57.50 0.8803 75.30 0.9832 643.00 0.8163
The effects of reduction temperature and reduction time on the removal rate of magnesium were investigated.

In addition, the pressure transducer is installed in the cylinder to monitor the pressure status while the segment is performing soft-reduction action, which could provide the necessary technical data for the normal execution of soft-reduction.
The manipulation board is used to adjust roll gap under the service mode, and to display the necessary data & important status messages.
The main control system is used to control the soft-reduction equipments, to modify the significant operating parameters, and to transfer data mutually between the L2 computer or the model computer.
The operator terminal is a industrial PC installed with InTouch or WinCC, which is used as a HMI to show the main frames, the trend curves, the alarm signals and the report forms, the other functions of which include collecting the process data, monitoring the running status, controlling the roll gap, choosing the control mode and showing the important parameters for soft-reduction.
Third, the CISDI_CCPS ONLINE (L2) was installed, the data transfer between which and instrument PLC & soft-reduction PLC was checked to be ok.

Implementation of Parallel Lanczos Method for Intrusion Detection with Cloud Technologies Bo Chen 1, a, YuleDeng 2, bandTiemingChen3, c 1Zhejiang University of Technology, Hangzhou China 2Zhejiang University of Technology, Hangzhou China 3Zhejiang University of Technology, Hangzhou China acb@zjut.edu.cn, brainerdun@live.cn, ctmchen@zjut.edu.cn Keywords:IntrusionDetection; Dimensionality Reduction; Cloud Computing Abstract.The aim of dimensionality reduction is to construct a low-dimensional representation of high dimensional input data in such a way, that important parts of the structure of the input data are preserved.This paper proposes to apply the dimensionality reduction to intrusion detection data based on the parallel Lanczos-SVD (PLSVD)with the cloud technologies.
The massive input data is stored on distribution files system, like HDFS.
Dimensionality reduction [2] is a preferablemethodto speed up intrusion detectionfor mass data.
For the PCA dimension reduction, usually only needs to take principal component accounted for over 85% of all principal components, and it is enough for get better data dimension reduction result.
Experimental detection rate and false alarm rate is shown in Table 1: Table1．The detectionrateandfalse positiverateunderthetwo conditions Dataset Normal data Intrusion data Detection rate（%） False alarm rate（%） IFCM PLSVD+IFCM FCM PLSVD+IFCM dataset 1 103510 2103 84.5 84.8 0.82 0.78 dataset 2 104120 2458 83.8 84.1 0.84 0.82 dataset 3 110250 2220 82.6 82.7 0.81 0.8 Average 105960 2260 83.6 83.9 0.82 0.8 From Table 1,we can gethigherdetection rateby using PLSVD dimension reduction algorithm data, compared to clustering directly from raw data,and maintaining a lowfalse detection rate at the same time.

Different paths contain different semantic information such as control dependence, data dependence and so on.
(3) Table 2 shows the mean percentage of test-suite reduction for our reduction strategy.
Program number of unreduced test-suite mean number of reduced test-suite mean percentage of test-suite reduction print_tokens 4129 2605 36.909% print_tokens2 4115 2156 47.606% replace 5542 3251 41.339% schedule 2650 2175 17.925% schedule2 2710 2278 15.941% tacas 1608 11 99.316% tot_info 1052 347 67.015% In order to further investigate the test-suite size reduction of each program, boxplot A boxplot is a standard statistical device for representing data sets.
The box’s height spans the central 50% of the data and its upper and lower ends mark the upper and lower quartiles.
Fig. 3 shows the percentage reduction for our reduction strategy.