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By using the reduction procedure, various mechanical quantities can be calculated more simply, as compared to the traditional methods.
These quantities represent basic data for the dynamic, vibration and structural analysis of mechanical systems with complex motions, such as various industrial robots [8].
Reduction of a homogeneous elliptical plate to a discrete system of material points In paper [5], two elementary bodies were analyzed: triangle and parallelogram.
Homogeneous elliptical plate Application In order to highlight the benefits of the reduction method proposed above, an application is studied.
Orăşanu, Reduction of the conical and pyramidal bodies to the lower order bodies, The XXth SISOM, Ed.

Variable precision rough set(VPRS) model and formal concept analysis are studied in this paper, include algorithm of reduction attribute and extraction rule.
Step 2: If FL needs to be reduced, then using a rule reduction algorithm to reduce FL. 3.
But the traditional recommendation systems have some shortcomings, such as data sparsity and digging out the potential demand.
The primary content of this dissertation is to apply formal concept analysis technology to obtain all connotative concepts and hierarchy of them automatically from the designated data, which is not under the influence of developer.
The primary content of this dissertation is to apply rough concept lattices technology to obtain all connotative concepts and hierarchy of them automatically from the designated data, which is not under the influence of developer.

Aluminum Reduction Cell’s Fault Monitoring Based on LS-SVM Shuping WANG1, Yajing SONG1, Hui WANG2 1Shandong Water Polytechnic, Rizhao Shandong 276826, China 2Shandong Taikai Transformer Co.
Fault feature extraction of characteristic vector (1)Aluminum electrolysis fault feature analysis Through the comparison of electrolytic tank under normal and fault data, and groove resistance spectrum analysis, we found that in normal electrolysis aluminium,liquid undulation, or low electrolyte containing anode block and an anode long bud under four different conditions, the frequency and amplitude of the position groove resistance are different, with 5 minutes for a cycle of cell data analysis, can be shown in Table 1 different slot status characteristics in frequency domain.
The frequency band energy accounts for the percentage of total energy and total energy spectrum, this algorithm for support vector machine, sampled data generalization is important, considering all kinds of electrolytic cell situation difference degree, in order to avoid wide input range than the range of small input quantity occupies the superiority, so here on the the total energy spectrum are normalized
(2) Logarithmic transformation, is given as follows (3) Inverse cotangent function conversion formula In the experiment, firstly use inverse cotangent function conversion makes the total energy spectrum is normalized, and then the diagnostic sample was divided into training samples and test samples, all kinds of condition number of samples are shown in table 2: Table 2 Selection of Samples condition normal anode tsuga lower polar distance fluctuations in liquid aluminum training samples 60 45 25 25 test samples 20 20 15 20 Different state of the training data as shown in table 3: Table3 Some Sample Data Total energy A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 Category 240 3876 844 577 518 639 677 105 209 151 617 1787 1 3076 300 776 4986 2508 869 51 59 34 20 130 268 2 170 2516 874 494 250 1132 787 894 498 155 659 1741 1 2047 629 443 6564 1550 104 85 116 36 67 149 257 2 227 4044 1637 416 299 556 102 149 313 84 752 1648 1 3210 2785 227 375 4028 266 76 1317 399 75 129 321 3 3134 1409 419
532 4006 424 239 2284 276 62 137 213 3 2395 598 206 144 58 26 36 17 26 12 99 8779 4 1553 966 138 77 51 16 19 17 19 19 338 8340 4 Notes：All the above data The test used in the fault diagnosis of the number of samples is not particularly much, here using leave-one-out cross validation method to evaluate the generalization performance of classifier.

Under current situation, with high labor cost and energy cost having an impact on production cost, the need for cost reduction in the industry is extremely of concern.
This research demonstrates application of the lean supply chain for cost reduction in the industry.
Methodology Four main steps are involved in this research: First, a study on the current state of the rubber glove supply chain using data collected in southern Thailand - logistics cost is classified in this step; Second, identification of NVA activities with the purpose of reducing the wastes in the supply chain, NVA activities with higher logistics cost are chosen for further analysis; Third, analysis of the causes of NVA operations and investigation of countermeasures against them; Fourth and final, proposal of practical guidelines to reduce those wastes. 3.
Based on data collected in this study, VSM of rubber glove supply chain is developed in Figure 3.
On the total cost, inventory reduction in the supply chain should be focused on the rubber glove industry.

After determination the times of spectrum analysis data as shown table 1.
From table 1 the times of spectrum analysis data, each monitoring point was above the national minimum standard of noise.
Noise value of the main suction cabinet and times frequency spectrum analysis measurement data as shown tables 2 and 3.
Therefore, after the noise reduction transformation, the noise value of the main suction cabinet is reduction of 9.5dB.
Therefore, after the noise reduction transformation, the noise value of the main suction cabinet is reduction of 9.5dB.

The characteristics of medical data make large differences between medical data mining and conventional data mining [1].
A Preprocessing for the Massive Data in Hepatopathy Information System Data preprocessing is an important step which usually takes about 70% of the time in the process of a complete data mining [3].
The characteristics of medical data such as privacy, diversity, integrity, redundancy and timeliness make large differences from conventional data mining [4].
Preprocessing of massive data in liver disease patient information system includes as follow: Fig. 1 Data mining and aided diagnosis system of hepatopathy 1) Anonymization and identity transformation: Due to medical information involves the patient privacy issues, besides the need of the general data preprocessing, medical data also requires special data processing such as name-anonymization and identity-transformation for patient records, thus separates the relationship between patients and patient records. 2) Medical Text standard: The explanation that medical experts do for images, signals or other clinical data in medical text information is usually nonstandard, so it is necessary to standardize the text data [5].
C The Classification Algorithm for Medical Image Data We research a new classification method that based on the combination of rough set and SLIQ decision tree, which combine the two methods’ advantages, namely using rough set data reduction, remove the redundant attributes and decision tree method is then used to generate the classification rules effectively.

Qiang Xu, et al. systemically analyzed and researched variation of cumulative displacement, deformation rate and acceleration of landslide from the beginning of deformation to instability failure relying on a large number of monitoring data of landslide deformation, and found that variation of acceleration was completely different from cumulative displacement and deformation rate.
By integration analysis of monitoring data of typical section, curves of horizontal and vertical displacement with time were drawn, shown in Figure 1.
By integration analysis of monitoring data of typical inclinometer hole, deep displacement curves with depth were drawn, shown in Figure 2.
Fig.5 Changing curves of lateral deformation with reduction factor Figure 5 shows that lateral deformation increases with increasing reduction factor.
Lateral deformation has smaller increment with smaller strength reduction factor, and has a larger increment with larger strength reduction factor

We believe that for said of the images data, then the three attributes must also are had as following: (1) Sparsity: only less expressed coefficients can be used, and the recovery of the high-quality for the data of the brain MRI images can be obtained
(2) Retention of the characteristics: image features, such as edges, etc., in the representation of the MRI brain image data, which can be preserved
(3) Separability: the ability is had the useful information of the brain MRI image with the noise data to distinguish.
(a) (b), =35.8385 (c), =36.8765 Figure 2(a) is Original image of brain MRI medical of the noisy; Figure 2 (b) is the images of the noise reduction by the redundant DCT dictionary; Figure 2 (b) is the images of the noise reduction by the adaptive dictionary.
The noise images for the global dictionary learning Summarize From the above results, the algorithm of the noise reduction of the adaptive dictionary learning is extremely effective algorithms of the noise reduction.

Other than this, noise/vibration can also be caused by nonparallel armature and the interaction between the armature shaft and bearing.[1,2] Title of Publication (to be inserted by the publisher) After analyzing the data of a durability test relating to brush noise in DC motors (Table 1), it can be seen that the element that has the biggest influence is the roundness of the commutator (Fig. 1).
According to the test data, the roundness deteriorated as the DC motor ran and this increased the brush noise.
There was a noise reduction of 1.3 dB(A) for the 3 inner points Title of Publication (to be inserted by the publisher) and a noise reduction of 3.5 dB(A) for the 4 outer points.
(1) After the durability test, it can be concluded that the interaction between the brush and the commutator has the biggest influence on the brush noise of a DC motor through a noise test data.
(3) Vibration also had a reduction effect.

From the analysis of microstructure, it is thought that the HIC contribute dominantly to the reduction in the fatigue life in the strain rate range from 0.04 to 0.4 %/s and the metal dissolution is mainly responsible for the reduction in the fatigue life at the strain rate of 0.008 %/s.
Although the LCF data of various LASs in high temperature water have been produced up to recently, the data of SA508 Gr.1a LAS used as piping material in Korean nuclear power plant is insufficient.
In this regard, the LCF tests were carried out to produce the fatigue life data of SA508 Gr.1a LAS used in Korean nuclear power plant.
For comparison, the ASME design fatigue curves and the fatigue life data in air are also shown in Figure 1 [8].
From the analysis of microstructure, it is thought that the HIC contribute dominantly to the reduction in the fatigue life in the strain rate range from 0.04 to 0.4 %/s and the metal dissolution is mainly responsible for the reduction in the fatigue life at the strain rate of 0.008 %/s.