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Research Methodology Based on the data, [5,7] studied steel fiber-reinforced concrete based on a matrix of self-compacting cement-sand solution (table 1).
It is known, however, that with an increase in the content of different fibers, the degree of size reduction either decreases or increases.
The influence on the change in the mass, size and density of the quantity and type of fiber is not unambiguous, does not fully correspond to the theoretical provisions considered in the work and requires further research, at least on the basis of a comprehensive analysis of the data. 6.
In further investigations, the authors will conduct analysis of the data obtained in order to establish such dependencies.
Ivanenko, Results of verification of the model of fiber concrete structure developed for analytical determination of its thermal and radiation changes based on experimental data of shrinkage during hardening, Internet-journal "science of SCIENCE" That. 8, 4 (2016). http://naukovedenie.ru/PDF/43TVN416.pdf.

Electronic data were processed with the surface explorer document (SED) software kit.
From this data it is visible, as the membrane, and NWs have the uniform geometrical sizes.
Figure 2 presents the results of TGA data for Ni NWs/PAA in air.
TGA data for PAA membrane in air.
Shaped lines designated positions of diffraction lines of reference powder Ni of the database of the International Center for diffraction data (JCPDS).

Ground reaction force at anterior posterior direction was calculated from force platform (9286A, KISTLER, JAPAN) data.
Data Analysis.
Data at the first cycle of each perturbation need to be eliminated for next calculation to avoid movement bias due to introduction of perturbation.
Experiment data were compared with simulation data obtained based on eq. (2) which was developed by using Simulink.
Elimination of first cycle data (dash line) to avoid movement bias and passive movement.

Each of the rule sets produced are then evaluated on the original training data and on the test data.
The basic Genetic Algorithm Experiments Dataset In this research, 3 data sets from The UCI repository[16] and Bankruptcy Data [17] were evaluated.
Summary of data sets Data set Name Number of records Number of attributes Number of class +1 Number of class -1 Australian Credit 690 14 307 383 German Credit 1000 24 300 700 Bankruptcy Data 240 30 128 112 Accuracy calculation The performance of the proposed approach is analyzed using the accuracy of the classifier.
The technique generated random data called Bootstrap [19].
Due to ensemble techniques, there is a reduction of the bias problem that arises from the collection of data used in learning including the fixed set of parameters.

(2) negotiate with suppliers, and arranging factory visits, establishment of supplier data
(6) establish procurement operations as required by the order data
(7) to understand market trends, collecting exact data such as market supply and demand prices to cost analysis
Powerful print feature can print purchasing documents at any time, data export function, conveniently transfer purchasing documents to Excel data format and Word data format, is easy to adjust and modify format according to its own needs at any time. 5.2 Fair and transparent for procurement Administrators, with permissions, from the procurement planning to procurement contracts, purchases, returns, purchases, payments, purchase orders, can comprehensively follow these series of work, which can effectively monitor procurement process, thereby ensuring the impartiality of procurement. 5.3 Full-process purchase cost control Whole process cost control purposes could be realized due to the features that purchase software themselves have.
Existing problems and suggested solutions Despite there are many benefits by use of procurement software to make purchase management for project, but the software itself can only ensure the accuracy of input data and results, and is not a panacea, successful implementation of the procurement depends on the experience of procurement officers to judge.

Introduction In the data analysis, often need to deal with the massive data set.
These data sets contain some redundant or even irrelevant features.
Method of Data Grouping.
Experimental Result and Analysis Experimental Sample Data Sets.
It was only slightly lower on the data sets of Soybean-large and Zoo on, but higher on the other data sets.

Therefore the target of a dressing process improvement must be a substantial reduction of the speed ratio.
Q = 310 l/min cool gear data: m = 4.5 mm; z = 24 n αn 0 a = 20°; = 0° d = 118 mm; x = 0.7 β dressing data: dressing roller D300 n = -1500 min v = var.
Q = 310 l/min cool grinding data: v = 30 m/s a = 0.25 mm c e v = 110 mm/min ft gear data: m = 4.5 mm; z = 24 n αn 0 a = 20°; = 0° d = 118 mm; x = 0.7 β dressing data: dressing roller D300 n = -1500 min v = var.; q = var.
A reduction of the dressing roller speed reduces substantially the relative speed between the grinding worm and the dressing roller itself on the contact surface.
Q = 310 l/min cool grinding data: v = 30 m/s a = 0.25 mm c e v = 110 mm/min ft gear data: m = 4.5 mm; z = 24 n αn 0 a = 20°; = 0° d = 118 mm; x = 0.7 β dressing data: dressing roller D300 v = 1.1 m/s a = 10 µm; q = 10 cd ed d n = var.; q = var.

The data from production hot mill are analyzed in conjunction with the results of laboratory high temperature mechanical simulations.
Mill data indicate that Al suppresses the effects of microalloying on softening of austenite.
Head end data averaged over several bars.
Fig. 5 gives the hot strip mill head end rolling force data for the same two steels.
Conclusions Mill data analysis indicates that Al suppresses the effects of microalloying on softening of austenite.

Evaluation of CD Fluctuation on QC Monitor Chuan-Yu Yen1, Mu-Chien Luo1, Kuo-Bin Huang1 and Ting-Chun Wang1 1 Taiwan Semiconductor Manufacturing Company, Hsin-Chu, Taiwan Keywords: CDSEM, Caro’s Strip, Polymer Residue, Dry Etch Introduction The continually increasing complexity of IC integration drives the reduction of device dimensions.
However the basic QC monitor results showed the CD data was more unstable on the patterned monitor wafer requiring additional tool tuning that was not required on the device wafer.
Additionally, Figure 4 indicates the marathon test result (>25 times) was more stable than the previous monitor data (variation > 3nm).

A discordant outlier in a data set is an observation that is surprisingly different from the rest of the data and therefore is believed to be generated by an alternate mechanism to the other data.
Outliers in Univariate Data.
Transmissibility function for the unfaulted data.
Test Set-up and Data Capture.
Lewis: Outliers in statistical data, 3 rd ed.