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Introduction Association rules mining aims to find interesting association or correlation in large quantities of data between itemsets.
It is an important subject in data mining, and it has been widely researched in recent years [1].
For mass and some important information which loss of measured data, rough set theory can complete the dimensionality reduction, incomplete information feature extraction [4].
There is no general theoretical solution to find the optimal number of clusters for a given data set.
Summary of Data Mining Technology Based on Association Rules [J].

Moreover, the reduction is the percentage of reducing the thickness of the strip.
The experimental data has been arranged in the best way to analyze the effect of each processing parameter individually.
To analyze the reduction effect on the surface roughness, the values of surface roughness (Ra) have been plotted against the reduction values as shown in Fig. 3.
Fig. 3 Effect of reduction on surface roughness By analyzing the trends in Fig. 3, it can be noted the obvious linear decrease of the surface roughness found as a result of increasing the reduction.
It is known as explained above the effect of reduction which is in summary with increasing the reduction the surface roughness decreases.

Data and Monitoring Sites.
Hydraulic geometry parameters were measured to provide the input data for model segmentation.
The model was first calibrated with the measured hydraulic characteristics and water quality data collected on April 29, 2008.
The data obtained from July 26, 2008 were then utilized to verify the model using the calibrated model coefficients.
In general, the model results of spatial DO, BOD5 (CBOD5), NH3-N, and TP match the field data reasonably well (not shown).

From AFM data we could measure the kinetics of cluster growth on the surface.
The reduction of the silver during diffusion of hydrogen into the glass was accompanied by growth of silver clusters, both in the bulk and on the surface.
If Ns is the surface cluster density and the average cluster radius R, one can write (assuming a hemispherical cluster shape) 2 2 πR N dR j dt s sAg= Ω , and after integrating Eqs. 5 and 6, determine that the total volume of clusters per unit surface grows with time as V t D N D N d t D Nl t t s Ag Ag H H Ag Ag ( ) ( ) / = = 0 0 0 0 2 0 3 1 2 Ω Ω (15) Eq. 7 allows the estimation of DAg0 from the experimental data Vs(t), if the dependence l(t) is known.
Summary As it follows from experimental data on optical extinction and our analysis, the propagation rate of the layer filled by nanoclusters as well as the kinetics of cluster growth in the bulk of glass are independent of the silver diffusion coefficient DAg0 and defined by the hydrogen diffusion coefficient DH.
The coefficient DH can be estimated from data on optical density of the glass as a function of annealing time, whereas the coefficient DAg0 - from the kinetics of surface clustering.

The results of isothermal compression with friction show that both an acceleration of the process and a reduction of damage are possible using the suggested control strategy.
The use of TiAl alloys with a density of approx. 3.9 g / cm3 pursues the goal of replacing the heavy nickel-based superalloys currently used in the high-temperature range, thus achieving a drastic weight reduction.
The constitutive equations relating the flow stress with temperature, strain rate and strain are calibrated from the data of the hot compression tests.
The problem can be stated as follows: (7) The problem is hence to minimize the process time t1, which is necessary to form the specimen to a height reduction of Dh, while keeping the damage variable D smaller than a critical value and recrystallization above 95% at the outer radius of the workpiece, given by the domain W.
McQueen, New formula for calculating flow curves from high temperature constitutive data for 300 austenitic steels, J.

Data integration is a function of MIAS, allowing the reduction in the amount of data and information noise because of differences in the information needs of control systems and management support systems [1].
Analysis – the level of data sources.
Choice and creation of data sources.
The process of data integration can be divided into two phases – the pre-processing (basic data manipulation, such as formal verification of correctness, analog-to-digital conversion, digitization and reduction) and aggregation of information.
Data archiving in MIAS.

Arc-shaping of magnets for reduction of cogging torque inpermanent-magnet synchronous generators Chao-Yuan Cheng1,a,Chun-Yu Hsiao2,b, Shu-Wei Chung1,c, Chun-Pin Chiang1,d, Zai-Wei Chin1, e 1Department of Electrical Engineering, St.
Ansoft’s Maxwell and RMxprt were employed for data analysis.
When the thickness of the magnets exceeds a given limited, variations in cogging torque reach saturation levels at which point further reduction does not lead to observable improvements.
Thus, a reduction in cogging torque leads to a reduction in motor efficiency.
Shen, “Cogging torque reduction in permanent magnet flux-switching machines by rotor teeth axial pairing,” IET Electric Power Applications, vol. 4, pp. 500-506, 2010

Table.2 shows the specifications of the temperature data recorder and Type T thermocouples installed (Fig.4) to measure the indoor air and the roof surface temperatures.
The data were recorded every 5 minutes for 120 minutes in both the reference and passive cool system models.
Data logger and Thermocouple specifications Type Type T, exposed type, PTFE insulated Model TC-08 Sensitivity 40 µV/°C, 1oC over the range -200oC to 400oC Channels Eight Tip diameter 1.5 mm Range of measurement –270 to +1820 °C Tip temperature –75°C to +350 °C Resolution 0.025oC (a) Data logger (b) Type T thermocouple Fig.4 Instruments for measuring the temperature Results and Discussions Type T thermocouples fixed in the middle of the symmetrical test models were used to measure room air temperature.
These sensors are connected to the temperature data logger and temperatures were recorded with a computer assisted system continuously for 120 minutes.
Regardless, the aluminium reflector - evaporator passive cool system stayed stable all the time with a marginal fluctuation in temperature and the data after 60 and 120 minutes were 21.64oC and 21.2oC respectively.

To understand the phase purity and crystal structure, XRD of samples before and after reduction have been studied.
Before reduction, as-synthesized α-Fe2O3nanoeggs are single rhombohedral phase and match well with the standard magnetic diffraction data α-Fe2O3.
After chemical reduction at high temperature, the phase is converted to cubic inverse spinal phase Fe3O4.
We can see that the phase before and after reduction are purity and no other impurities are appeared.
Fig. 2 XRD profiles of as-synthesized a-Fe2O3nanoeggs and after chemical reduction to Fe3O4nanoeggs.

Finally, do simulation examples with line loss rate data of a city using the software.
The software is designed modularly, and divided into five modules: data input, data viewing, analysis and forecasting, results showing and usage management.
Users can choose importing excel sheet or manually inputting data according to themselves.
After finishing importing or inputting data, the collation of data and statistics can be seen, which include historical data table name, fields, and a variety of charts displayed in the window.
The software is based on the characteristics of the raw data of the grid line loss rate.