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ϕ2 = 45˚ ODF sections obtained by XRD for cold rolled and annealed sheet, (a) 66% cold rolling reduction, (b) 76% cold rolling reduction, (c) 86% cold rolling reduction.
Conventional rm (a) and ∆r (b) as a function of cold reduction ratio. 66 71 76 81 86 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 rm Cold reduction ratio (%) HACA HCA (a) 66 71 76 81 86 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 ∆∆∆∆r Cold reduction ratio (%) HACA HCA (b) Fig. 4.
Modified rm (a) and ∆r (b) as a function of cold reduction ratio.
But in case of HCA, the modified ∆r became higher after 76% cold rolling reduction.
Comparison of the experimental r-value data and the calculated values of r for the {554}<225> texture component.

Approach Lactate was assumed to be the dominant limiting substrate and the steady-state experimental data were used to determine the kinetic constants.
The steady-state data were analysed using the Chen and Hashimoto (Eq. 3), Contois (Eq. 4) and Monod (Eq. 5) kinetic expressions to determine the kinetic constants
Data from the experiment using 1.0 g l-1 feed sulphate were used to describe lactate utilisation under conditions where the biological sulphate reduction reaction and concomitant lactate oxidation reaction were dominant, in accordance with the stoichiometric analysis presented by Oyekola et al
Using these data, the relative growth rates of lactate oxidation and lactate fermentation were compared as a function of operating conditions.
Experimental data studying BSR kinetics on varying feed sulphate concentration in chemostat STRs, shown in Fig. 3, agree well with the simulation presented.

As a new data analysis theory dealing with fuzzy and uncertain information, it's main idea is to make out decisions or classification rules of the issue through Knowledge Reduction Method with the classification ability unchanged.
Evaluate the three landscape areas respectively, so as to evaluate the general situation of Liuli Expressway Landscape quality. 4.2 The Sources of Data The index of highway landscape quality evaluation system includes two parts: quantitative and qualitative.
Table of attribute characteristic value U r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 x1 3 2 1 4 3 3 3 1 2 1 2 3 x2 1 3 2 3 2 3 3 2 3 2 1 4 x3 2 3 1 2 3 2 2 3 1 3 2 2 U r13 r14 r15 r16 r17 r18 r19 r20 r21 r22 r23 r24 x1 2 3 3 4 4 4 2 2 2 2 3 2 x2 1 3 3 3 4 3 1 3 4 2 2 2 x3 3 3 2 3 3 4 3 2 3 3 2 1 (2) Index collection Reduction After data reduction of the above form, 15 evaluation indexes are eventually retained after screening: r1, r2, r4, r5, r7, r8, r9, r11, r12, r13, r16, r20, r21, r22, r23.
Data of information system after reduction are shown in table 5.
The attribute reduction of information system [J].

Date accepted: 06 July 2013] Keywords: Fe2O3 reduction; Metallurgical coke; End-of-life tyres; Extent of reduction; Carburisation.
An IR gas analyser (Advance Optima model ABB^® AO2020) attached to this system was used to monitor CO and CO2 gases produced by the reactions and the results were recorded in a data-logging computer.
Figure 11 Change in extent of reduction with time at 1500 °C From Figure 11, RT and the blends are able to reduce the iron oxide rapidly, attaining at least 80% reduction in less than 600 seconds; within this time the reduction by coke is about 67%.
In particular, H2 apart from being a faster reducing agent than both CO and solid carbon enhances the rate of reduction of iron oxides by CO [8,9] when it is added to a reduction system containing the latter.
Rajakumar, Gaseous reduction of wustite with H2, CO and H2-CO mixtures, Trans.

In the real fault prediction, the test data is redundant and incomplete, and Rough Set Theory can reduce the redundant information and extract the useful information.
The classical attribution reduction algorithm given by [4].
In which, the attribution reduction algorithm are as bellows: Input: decision table S=(U,A,V,f); Output: all the reduction REDC(D) of decision table.
The grey prediction model steps are as bellows: Step 1: x(0)(t) is accumulated generating to get ; Step 2: Calculate data matrix B and the data row Y; Step 3: Calculate a and b by ; Step 4: Establish model ; Step 5: Calculate prediction accumulated value ; Step 6: Calculate the prediction value ； Step 7: Calculate ,。
Firstly, the data is discretized because Rough Set Theory only can process the discretized data.

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.

From the measured data for aluminum experiments on Gleeble-1500, Yuhua Kang established a material model to simulate rolling process on aluminum alloys, and analyzed the reduction, rolling speed and contact heat transfer coefficientps influence on temperature differ ence acr oss the thickness of slabs and flow str ess curvature.
a b e d c Fig.2 Metal strain field of difference reduction.
Reduction: a-5%, b-10%, c-15%, d-20%, e-25% Research on strain field.
Such as 20% for pass reduction to make the plate core metal obtain enough plastic strain.
Such as 20% for pass reduction to make the plate core metal obtain enough plastic strain

Reformulating Input Data for Linear Regression of Demographic Data Xiaoheng Pan, Yangping Li∗, Huaqiang Yuan Dongguan University of Technology, China ∗Contact author.
Independent and identical distribution is a fundamental assumption often made in data sampling, but it is no longer valid for demographic data.
Neighborhood augmentation achieves the most significant MSE reduction on both datasets.
(f) plots MSE vs ρ on crime data.
Statistics for Spatial Data.

We are presenting a feature based mapping procedure applied on data reduction to the relevant information used for autonomous navigation.
This is why data reduction becomes an important factor excluding any possible shape dissimilarities of the mapped area.
The reduction of data becomes consistent when clustering points into linear segments.
(2) Until reaching the final map structure data reduction is done in two steps.
A scan matching method assumes that generated lines can be compared and matched together within the map manager similar to the way of the data reduction.

INTRODUCTION Orthogonal frequency-division multiplexing (OFDM) is a method of encoding digital data on multiple carrier frequencies and is a popular technique for transmission of signals over wireless channels.
OFDM offers numerous advantages such as high data rate, robust performance and better spectrum efficiency.
But these techniques achieve peak power reduction at the expense of transmitting signal power increase, bit error rate (BER) increase, data rate loss, computational complexity increase, and so on.
Oversampling the data in IFFT, increases the resolution of the OFDM symbol giving a closer approximation to the band limited signal after filtering.
In the proposed SD-ICF technique, the reduction in PAPR is of optimized value.