Search results

Hierarchical Modeling makes the data dimensionality reduction and interpretation much easier by principal component analysis (PCA).
Metabolomics research generates a large number and complex samples data, the chemometric tools were proved to be powerful for metabonomic data analysis.
Hierarchical Modeling was generating to make the data dimensionality reduction, this method was investigated for data processing.
The data set contains 244 variables.
The data of all the groups was imported into the SIMCA-P 12.0.

In these methods worker intervention may be required, but it is minimized and the actions of the employee are supported with hardware and software solutions, that enable the reduction of the error rate of data acquisition and increase its speed.
Manual data acquisition Automation, robotics and mechanization allows a significant reduction in human participation in production process, but there are still processes that are not automated, mainly due to insufficient profitability.
Primary data sources.
Secondary data sources.
Secondary data sources can also create new data based on the raw data, that is necessary for control purposes.

This paper describes an investigation into the reversing process of H-beam using MARC software and compares the results with rolling data from the production line.
The influence of rolling reduction, the reduction rate between the web and flange are also discussed.
The rolling forces of all-passes obtained from the FEM analysis were compared with the forces recorded in the process data acquisition system (shown in Fig. 2).
The reduction rate between web and flange was adjusted by keeping the web reduction and changing the flange reduction.
For example, the theoretical rolling reduction is 7mm but the actual rolling reduction is 23.2mm.

The reduced T’-PCCO nanopowders were obtained by reduction annealing process at 700°C for 5 h under Ar gas atmosphere.
However, they did not concern the change of oxygen content due to reduction annealing process.
The Cu K-edge and Ce L3-edge XANES data in transmission mode were collected at room temperature.
The oxygen reduction causes a change in the oxidation state value which depends on the optimization of the reduction process.
After the reduction process, the oxidation state value slightly increases, but the value remains about +4.

Table 1 The property and composition of the heavy oil Item Data Viscosity [Pa·s, at 50˚C] 25.306 SARA Composition [%] Saturate hydrocarbon 31.9 Aromatic hydrocarbon 19.3 Resin 43.8 Asphaltene 5.0 Elemental Composition [wt%] C 81.2 H 13.7 O 1.26 S 0.28 N 0.95 Static experiment.
The ratio of viscosity reduction was calculated by the following equation: △η=（（η0-η）/η0）×100, where△η (%) is the ratio of viscosity reduction, η0 (mPa·s) is the oil viscosity before reaction, and η(mPa·s) is the oil viscosity after reaction.
It shows that the viscosity reduction rate was over 75% at 200˚C with the reaction time of 24 hs, and catalyst accounting for 0.3wt%.
Table 3 Experimental data of steam huff and puff cycle of steam huff and puff Without catalyst With catalyst cumulative oil production [ml] oil recovery [%] ∆η [%] cumulative oil production [ml] oil recovery [%] ∆η [%] first 2.42 3.70 47.7 5.55 8.50 76.3 second 1.53 2.35 43.7 2.81 4.30 87.6 third 1.12 1.71 38.3 2.07 3.17 84.7 fourth 0.67 1.03 35.5 0.81 1.24 81.3 fifth 0.42 0.64 32.4 0.40 0.61 74.4 total 9.43 17.82 Composition changes of the oil samples after reaction.
The laboratory experiment shows that the viscosity reduction ratio of heavy oil is over 75% at 200℃, 24 hs, 0.3 % catalyst solution.

Data mining is a class of in-depth data analysis[4].
Data mining is in-depth analysis of financial data.
Data management includes the following: (1) data selection.
Search all the financial analysis of object-related internal and external data, according to the purpose of financial analysis and choose the data for data mining. (2) Data reduction.
Data reduction is in the discovery task and understanding to the content data itself, based on search depends on the data found target characteristics of a useful to reduce the data size, Conger data as much as possible the original appearance of the data possible on the premises. (3) Data conversion.

In these approaches, data analysis is a key issue.
Materials Description of the relevant data sets.
Data set 1.
Data set 2.
Calculations with simulated data.

Effects of Mechanical Activation during the Synthesis of Tungsten Carbide Powders by Carbothermic Reduction of Tungsten Oxide J.
The as-milled powder underwent a rapid reduction reaction at about 150°C lower than the un-milled powder.
The reduction sequence to WC was illustrated to differ for the two powders.
The as-milled powder underwent a rapid reduction reaction at 150°C lower than un-milled one.
Phase identification was done using MDI Jade 5.0 software (Materials Data Inc., United States).

Selective catalytic reduction of NO by hydrocarbons (HC-SCR) was extensively investigated as a potential way to remove NOx from oxygen-rich exhausts[1,2].
As reported in the Ref[14], complete combustion of C3H6 was the main reaction during the reduction of NO at higher temperature.
Considered comprehensively, more active sites are presented for the reduction of NO on the AgZr/Al catalyst.
Fig. 2 NO-TPD profiles of different catalysts Table 2 NO-TPD data of catalysts Sample Initial temperature (oC) Summit temperature (oC) Peak area(mV·S) AgZr/Al 100 325 617 198 426 728 17843 4894 4963 AgLa/Al 88 / 660 181(shoulder peak) / 751 24505 / 2718 AgFe/ Al 82 275 677 148 425 751 11380 4413 2241 AgCe/Al 90 306 660 178 447 751 15608 3639 8253 O2-TPD Fig. 3 O2-TPD profiles of various catalysts Table 3 O2-TPD data of catalysts Sample Initial temperature(oC) Summit temperature(oC) Peak area(mV·S) AgZr/Al 110 552 273 750 20671 10469 AgLa/Al 125 571 319 750 17787 7620 AgFe/Al 130 588 325 750 19091 11085 AgCe/Al 118 591 312 750 17041 7658 O 2-TPD measurements were employed to investigate O2 adsorption of the samples, and the results are shown in Figure 3 and Table 3.
This indicates adding ZrO2 increases the amount of crystal lattice O, which favors the high activity of NO reduction [20].

author Keywords: Non-thermal plasma, Dielectric barrier, NO reduction, Emission controls, Catalyst.
Selective catalytic reduction (SCR) [4] and selective non-catalytic reduction (SNCR) [5], use ammonia (NH3) or urea as a reagent to reduce NOx via Eg. 1 - 3.
Experimental Setup and Methodology DBD-NTP setup The experimental setup is depicted in Fig. 1 which consists of simulated gas system, gas heater chamber, NTP reactor, catalyst reactor, gas analyser, and data acquisition system.
In this case, a selective non-catalytic reduction (SNCR) reaction is induced using DBD-NTP system.
YU et al., “Cold Plasma-Assisted Selective Catalytic Reduction of NO over B2O3/γ-Al2O3,” Chinese J.