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Dimension reduction is an important issue to understand microarray data.
In this study, we proposed a efficient approach for dimensionality reduction of microarray data.
Our method allows to apply the manifold learning algorithm to analyses dimensionality reduction of microarray data.
Rules of data dimensional reduction This paper applied the intra-category and inter-category distances as the assessment criteria to evaluate the effects of dimensional reduction and to quantitatively compare the data dimensional reduction effects of linear method and manifold learning method.
Our results indicate that Manifold learning is a suitable dimension reduction method for the microarray data.

This motivates us to survey power reduction techniques in cloud data centers.
In the following sections we will investigate power reduction techniques in data centers from different aspects.
Network Power Reduction in Data Centers Data center networks interconnect a large number of servers containing a lot of switches, routers and high-speed communication links.
Conclusions In this paper we give a survey of power reduction techniques in cloud data centers.
Power-reduction techniques for data-center storage systems[J].

This paper studies the application of rough set method in data mining, mainly on the application of attribute reduction algorithm based on rough set in the data mining rules extraction stage.
Rough set in data mining is often used for reduction of knowledge, and thus for the rule extraction.
In this paper, the traditional attribute reduction algorithm based on rough sets is studied and improved, and for large data sets of data mining, a new attribute reduction algorithm is proposed.
General process of data mining Research and improvement of the attribute reduction algorithm The application of rough set in data mining is mainly manifested in through attribute reduction to reduce the data size, make it convenient for extracting rules and improve the efficiency of data mining.
In data mining rough set is often used for the attribute reduction and rule extraction in data preprocessing phase and attribute reduction is one of the core research contents of rough set theory.

However, the data itself has noise, heterogeneity and other issues; it does not provide data reduction service on cloud computing platform.
The design and implementation of reusable data reduction tool The design of reusable data reduction tool.
Reusable data reduction tool can be called by data mining system, also be called by other applications running on this platforms to access to heterogeneous data.
Relationship between inner modules of data reduction too Layered data structure based on reuse.
Then test data set is to verify the effectiveness and efficiency of data reduction tool.

The two curves were similar, which proves that the normalization data reduction technique can be adopted in the static test.
The J-R curves were obtained from the dynamic test by the normalization data reduction technique and were compared to those of the static test results.
Then, the J-R curves were obtained using the unloading compliance method and the normalization data reduction technique.
These curves were then compared to determine the applicability of the normalization data reduction technique in obtaining the J-R curve.
Though ASTM suggests that the normalization data reduction technique be applied for crack extension within 4mm or 15% of the initial ligament, the obtained J-R curves by the normalization data reduction technique were similar to those by the unloading compliance method, even at the crack extension over 4mm or 15% of the initial ligament.

Meteorological Data Mining Based on Rough Set Attributes Reduction and Decision Tree Xiaoling Li1, a, Xu Wang2,b 1 Department of Information Technology, Hainan Medical College, Haikou, Hainan, China 2Hainan Meteorological Service, Haikou, Hainan, China 2Dongfang Meteorological Service, Dongfang, Hainan, China a53225922@qq.com, b37216526@qq.com Keywords: meteorological data mining, decision tree, attributes reduction, rough set Abstract.
The analysis of meteorological data based on data mining technique is a research hotspot currently.
Weather forecasting requires timely and accurate meteorological as the basis of data prediction, and the data changes with the time.
Applications 3.1 Data Preprocessing Table 1 shows the decision making table after discretization of data of one automatic station.
Meteorological data resources are abundant and precious.

Summary of Data Reduction based on cloud environment Shu-li Huang College of Information Engineering, Jiangxi University of Technology, Nanchang 330098, China Keywords: attribute reduction; cloud computing; distributed database Abstract: In today's era of big data, how to quickly find the data they need is a difficult thing from the mass of information, in order to achieve this goal, cloud computing to data mining technology provides a new direction, this article on how cloud environment attribute Reduction using data mining techniques are described.
Reduction theory for these kind of little change in the amount of data and the data is not fruitful, but for those who handle incremental data or mass data often have significant limitations.
To accommodate this massive amount of data or data, LIU Zong-tian proposed incremental reduction algorithm based on rough set; Wang Jue put forward based on the difference between a distributed matrix reduction algorithm;.
Dynamic Reduction traditional attribute reduction by developed and therefore restricted the traditional attribute reduction ideas, which are designed to adapt to a strong reduction of generalization and dynamic data.
With the further development of the information society, in the face of vast amounts of data every day, this data is still rapid growth, so the mass of the incremental data for data reduction, from efficient to obtain useful information , is a developing trend of the data reduction.

The Research on Data Acquisition Subsystem for Aluminum Reduction Cells under Reconstruction Mei Liu1, a, Qinwei Li1, b 1College of Computer Science and Information, Guizhou University,Huaxi,550025,Guiyang, China aliumei0217@163.com, bqwli@gzu.edu.cn Keywords: Aluminum reduction cells under reconstruction, Data acquisition, Memory mapped file, MODBUS Abstract: In this paper, a data acquisition subsystem for aluminum reduction cells under reconstruction is designed on memory mapped file and MODBUS, has realized the sampling procedure and the main control program of real-time data transmission through the memory mapped file, has realized the MODBUS communication between the sampling procedure and the prestage using MSComm control, the system can work stably at present.
Data acquisition subsystem Fig.1 shows that the design of the basic structure of the data acquisition subsystem.
Fig.1 Data acquisition subsystem Data acquisition This system used MSComm control to realize the communication of MODBUS between sampling procedure and the prestage, data gathered was received in OnComm of MSComm, the input mode for 1,port parameter for 9600 baud,8 data,1 stop, no parity checking.
This system needed to connect 24 set of each bus bar’s voltage and temperature of aluminum reduction cells under reconstruction, voltage of upstream and downstream and aluminum reduction cells under reconstruction, the sampling data was called for digital filter once every 200ms.
Data|data|data|......

Research on Data Mining Algorithm Based on Rough Set Yang Yongbin Chongqing Technology and Business University yangbin0715@sina.com Keywords: data mining; rough set; attribute reduction Abstract.Through in-depth study on the existing rough set and data mining technologies, for the shortcomings of the existing data mining algorithms based on rough set, this paper presents an improved algorithm.
Fig.1 Data mining processes The data mining model based on rough set is generally divided into four modules: data preparation, attribute reduction, rule generation and decision support.
Attribute reduction uses attribute reduction algorithm to deal with the original tables, then the data amount will be substantially decreased and the reduction data sheet will be output, to respectively process according to whether the simplified decision knowledge table is compatible.
Improvement of data mining algorithm based on rough set Analysis of data mining algorithm based on rough set.
Data Mining concepts and Techniques [M].

Another data reduction algorithm based on threedimensional grids was proposed by Lee [3].
Wang presented a data reduction method based on the straightness of curves [4].
In [7] and [8] chord-angle deviation criterion is applied to data reduction.
Finally, a bidirectional slicing based data reduction method is presented.
The Proposed Data Reduction Method.