Search results

An approach to the problem is to apply dimensionality reduction to the data for the object of classification and identification.
Learning the manifold underlying the fault data is important because the manifold reveals the intrinsic structure of the data and the essential relations in them.
In Section 4, experiments are performed on the benchmark data and real data sets to verify the effectiveness of the proposed method.
In Step 2, the local geometry in the neighborhood of each data point is characterized by the linear coefficients that best reconstruct the data point from its neighbors.
From the experimental results, it can be concluded that the proposed CSSLLE has an ability of extracting the most discriminating data with the best generalization among all the used dimensionality reduction methods.

In the first method the average of given data in the vicinity of the desired pixel is taken as the desired data.
In the second one replacing the data with the median of the surrounding data, and in the last one the average of the surrounding data with weighing according to the distance of the pixel is taken.
In surface shape measurement the phase data are needed and then reliability of the data increases if authentic phase data are chosen.
To determine a pixel value, the surrounding data are also collected and all nine data are sorted by intensity.
Dotted line is taken from data with laser microscope.

At the same time, it can also provide simulations under different policies, providing credible data for policy influence research.
Fig.3. shows the comparison of simulated data and statistics data of China from the year 2001 to 2009.
The statistical data is from the “China Statistical Yearbook” and the data of carbon emissions is based on literature data[11].
Verification of the model by comparing the simulation data and statistic data of China Future Scenario Analysis According to China’s carbon emission reduction target, the emission intensity of 2020 will be reduced by 40% to 45% compared to the emissions level of 2005.
Fig. 7 shows the simulation data of scenario 3.

The porous ceramic holds good potential as acoustic resistance and vibration reduction material during ultra-precision machining.
This is mainly dependent on two aspects, one is the manufacturing accuracy, the other is the vibration control and reduction on machine and its peripheral systems during the operation [2].
This paper probes into the acoustic properties of porous ceramic, which hold good potential as acoustic resistance and vibration reduction material on machine body, tool post, saddle, and so on.
The noise absorption and resistance properties are studied, and the calculation based on JCA model and the comparison between it and the reported data are presented.
The calculation results based on the above model are compared with the experimental data from literature [9], as shown in Fig. 3 and Fig. 4, which indicate the model conforms to the measurement well.

Given process history and time/temperature data from the annealing heat treatment, the model can predict the microstructure, average grain size and grain size distribution with high accuracy and the executing time is short which makes it suitable for in-line use.
At some interval in time, recrystallization takes place, and the model must handle the varied time/temperature in-data and the non-isothermal aspect of the annealing heat treatment.
The recrystallization and grain growth is calculated and the model uses time and temperature vectors provided through temperature measurements and data collections on-site for each sheet, during incremental upload.
The data was divided in three sets, training, validation and testing, and the training set consists of 80% of the samples.
Experimental data The modeling work has been focused on one material, the austenitic stainless steel 304L (EN 1.4301).

The experiments focused on monitoring the vibration signals using a vibration data acquisition system during turning operation.
It is apparent that a reduction of chatter amplitude will result in improved surface finish, tool life, machining accuracy, productivity, as well as reduction of operation.
Vibration data were measured using a Kistler (50 g) accelerometer connected at the bottom of cutting tool holder.
The data was collected using Dewtron signal analyzer and displayed using ‘DASY Lab’ software.
Subsequently, Fast Fourier Transform (FFT) transformed the vibration data to a function of frequency domain.

Send device processing the data collection equipment, assembly up and through the channel data sent out.
comEvCTS 3 Change of "Clear To Send" line. comEvDSR 4 "Data Set Ready" line of change.
With continuous data sent to and send way of connected PC, packets for fixed length.
Through the research of CDT data acquisition method design grid data acquisition software, against the traditional manual operation way, simple operation, easy to management, to power measurement data for statistical analysis, to realize the resource sharing, data sharing, meet the needs of enterprise cost accounting, to ensure the data security ,completeness, correctness, reflects the advance of the computer and network.
Ning, “Algorithm Analysis CDT Protocol Reduction Numerical,” Journal of Liaoning Institute of Technology, vol. 24, no. 4, pp. 29-31, 2004

Drug data preprocessing of data mining with constraints Data preprocessing.
In order to solve the problem of redundancy, use groups in the process of attribute reduction from the number of all the methods for elimination
Use some drugs attribute data tables for data analysis, the summary of the data processing includes the following steps: using drug data table to generate more data summary, only keep part of data information.
The drug after data preprocessing the data summary table, the table in the cluster analysis as a mining pharmaceutical data source, the target output data is clustering data summary table.
Experiments using (2) in the type k medoids clustering analysis method, using this method for drug data reduction and the actual noise processing, simulation of the effect is very obvious.

The ash reduction comparison of the step-by-step release flotation test with high intensity conditioning (HIC) or not, and the comparison of flotation test with HIC and adding depressant were made.
The results show that after cleaning stages the ash contents of flotation clean coal have some reduction while the clean coal yields decrease greatly.
The results show that step-by-step flotation with HIC method not only realizes the ash reduction but also keep better yields.
Comparing them with traditional process above, the yield grow 22.10 and 20.13 percentage points respectively, and the ash contents has a little reduction at the same time.
These data show that flotation with HIC will increase the yield of clean coal obviously.

This paper introduced TPM implementation in Shandong Lingong (SDLG) with two years of data collection and practice.
The company conducted equipment classification, production plan improvement, failure rate reduction, spare parts management and staff training practices based on MTTR, MTBF and OEE figures.
Data of breakdown and total up time were collected monthly to calculate MTTR and MTBF complying with the formula of Eq. 1 and Eq. 2.
Then our department will prepare all the excavator parts besides the traditional spare parts stock based on the marketing forcast. 3.3 Reduction of failure rate Two factors involved in reduction of failure rate.
Conclusion Data of MTTR, MTBF and OEE were collected and calculated monthly in SDLG, which then make the basement of plan adjustment.