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The overall carbothermic reduction to be studied is reaction (1).
Reaction (6) is reportedly difficult to happen[4], so it is hard to obtain the high active [Ti] during the process of the reduction reaction.
The first stage of the reaction is found to be the reduction of ilmenite forming elemental iron and TiO2 or other titanium oxides.
Conclusions This research has found that steel-bonded cemented carbide GT35 composites can be fabricated by carbothermic reduction of ilmenite.
Hu: Handbook of Data for Practical Inorganics Thermomechanics (2 nd ed) (Metallurgical Industry Press, Beijing 2002)

Multivariate statistical analysis explains the huge and complicated current situation of the original data efficiently, concisely, and explicitly.
It simplifies the original data into representative factors, or bases on the similarity between data to cluster and identify clustering outcome.
This implies that high accuracy can be obtained when discriminant and cluster analyses are applied for data evaluation.
This study provided a novel thought of applying statistical diagnosis approach on anatomizing groundwater monitoring data.
Before subjecting to data processing, data selection and data standardization were the essential steps of data pre-processing.

DATA PROCESSING BASED ON ROUGH SET Rough set theory was brought out by Z• Pawlak in Poland 1982.
Rosetta is useful experiment platform and application software for data mining based on Rough Set Theory.
Our questionnaire relating to various factors, and we make the following data processing: Step1.
Screening and processing data: Screening a total of 1128 valid samples applied to this study.
It is reflected by the data in this paper, and Martijn Brons has carried out in-depth study of this area [17].

The results for different datum precedence are summarized in this paper.
The functional tolerancing is now widely accepted by industry for contributing to a reduction of manufacturing costs while improving product quality [2].
However, the researches on the influences of datum precedence are still few.
If the datum precedence is plane | cylinder, the tolerance specifications for each part are specified with ISO tolerance language, as shown in Fig. 5.
While the datum precedence is changed, the final result is .

The process LCA-based water footprint method was applied using primary production data, with both volumetric and stress-weighted results reported.
Also, possible mitigation interventions for product supply chain water use impact reduction were raised on the basis of water footprint accounting.
Primary data were collected directly from the producer and supply chain stakeholders, which made this study different from other water footprint studies at product category level.
The authors have exercised complete freedom in designing the project, collecting and interpreting data and the decision to publish the results.
Ltd. for their active engagement in providing supply chain information during data collection process.

Apparent Enthalpies of Activation for Oxygen Reduction at Pt3Co Electrode in Alkaline Solution M.
Vra�ar 2� 1Institute of Chemistry, Technology and Metallurgy, Department of Electrochemistry, Belgrade, Serbia and Montenegro 2Faculty of Technology and Metallurgy, University of Belgrade, Belgrade, Serbia and Montenegro Keywords: Enthalpy of Activation, Oxygen Reduction, Pt-Co Alloy, Reaction Mechanism ABSTRACT Oxygen reduction (OR) at a Pt3Co alloy electrode has been examined in alkaline solutions of different pH’s in the temperature range from 274 to 313 K.
INTRODUCTION The oxygen reduction reaction is of most importance in electrochemical energy conversion devices such as fuel cells and metal-air batteries, as well as in corrosion and in several industrial processes.
In Fig. 2, the values of Tafel slopes, obtained from E - log j data in the high cd region, in solutions of different pH’s, are plotted against T.
Analysis of the experimental data All the quantities on the right side of Eq. 11 are either known (El and Eh) or can be determined experimentally ( � � lEa,H , � � hEa,H and ( � F/T)[d ET / d (1/T)]).

Clustering analysis of high-dimensional data is one of the challenging issues in data mining.
Characteristics and Difficulties of High-dimensional Data Characteristics of High-dimensional Data.
(1) data sparsity: Due to the growth of data dimension, sparsity is data objects’ inherent characteristic in space distribution.
(4) effective dimension reduction methods: High-dimensional data clustering has an important characteristic, local feature selection that makes it different form traditional clustering.
Learning High-dimensional Data.

Taken overall, the data suggest potential for the use of PLA in treating common wine faults, particularly ‘ladybug taint’, which is caused by elevated levels of IPMP.
Only data for IPMP and IBMP are reported here.
Measurement of lactic acid in the treated wines showed no change compared to control (data not shown), suggesting there was no degradation of PLA into its component lactic acid monomers.
Data represent the mean values of replicate treatments and measurements +/- SD.
Discussion and Summary This preliminary data demonstrates the capacity of PLA to decrease levels of these important taint compounds in red wine.

Based on improved linear regression filter method presented by Iwatani and wind tunnel test data, the program simulated 3-D time history of fluctuating wind pressure of Fuzhou Strait International Conference and Exhibition Center considering spatial correlation of wind loads, which is consistent with the object power spectrum .The simulation result is used in nodes of the structure to analyze response of wind-induced vibration.
Analytical results show it has the maximum displacement response in 0° wind direction .Due to the installation of TMD, node displacement response of roof truss is reduced from 44.14mm to 33.16mm, with best reduction 26.67%.
Fig. 1 Effect Diagram of FSCEC 3-D Fluctuating Wind Load Simulation Method Considering Spatial Correlation In the paper, improved linear regression filter method presented by Iwatani[6-8] is applied With the Davenport spectrum as object power spectrum and wind tunnel test data supplied by Hunan University, it is to simulate six cases of time history of fluctuating wind pressure of FSCEC under 0°, 45°, 90°, 135°, 270°and315°wind direction such as W00, W45, W90,W135,W270,W315.
Based on improved linear regression filter method presented by Iwatani and wind tunnel test data, the program simulated 3-D time history of fluctuating wind pressure of FSCEC considering spatial correlation of wind loads, which is consistent with the object power spectrum. 2.
Due to the installation of TMD, node displacement response of roof truss is reduced from 44.14mm to 33.16mm, with best reduction 26.67%.

The rough set theory is widely applied in data fusion, fuzzy recognition, artificial intelligence[6].
Software system for intelligent data processing and discovering based on the fuzzy-rough sets theory.
Rough sets-theoretical aspects of reasoning about data.
Rough sets intelligent data analysis [J].
Decision table reduction based on conditional information entropy.