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Data presented here were obtained at an engine speed of 1500, 2000, 2500 and 3000 rpm. the dynamometer unit loads was held fixed at 0% and 50% thus covering the typical and middle load range of the combustion regime.
Measurements vehicle performance data comprised power (kW), flywheel torque (Nm) together with the exhaust emissions observation.
Further analysis and presentation of these data is based on average of these 3 cycles.
As seen in Fig.5, the blended palm oil fuels under all engine speed conditions depicts the reduction of exhaust emissions.
However, there is little influence of oxygenated fuel on emission reduction at the range of biodiesel between 5 to 15vol%. 2.

A dimension reduction through principal component analysis of the feature data of all groups was performed.
This paper expands on previous work using Principal component analysis (PCA) of feature data [1,2].
PCA is a method used to simplify high order data sets to lower dimensions to allow a simple analysis.
It is performed by taking a rotation of the data around two orthogonal vectors which describe the largest amount of variance in the data.
The result of the PCA showing the greatest variance in the data is shown in Fig. 5 (The plot has negative axis as standard-normalised mean subtracted data is used).

During the tests, data on the load and deflection of the specimen was acquired for one cycle in every 100.
The resulting output data was analysed to investigate any stiffness degradation during the fatigue life.
A more appropriate and useful function to represent the data would be continuous in nature.
The correlation between the experimental data and the function used to fit the data is very good with an R2 value also equal to 0.95, validating the use of the Weibull function to describe the as-determined fatigue life of the hybrid joint
(Experimental Data) unfailed (0%-25%UCSnom) Fig. 3 Fatigue life data showing correlation with Weibull function Residual Strength Residual strength (RS) tests allow the evaluation of remaining strength in a structure after a given life cycle.

It is also a critical component of the fuel cell technology, where platinum acts as the most effective electrocatalyst for the oxygen reduction reaction and fuel (including hydrogen, methanol, ethanol, and formic acid) oxidation reaction [5].
Many studies on the methods for the preparation of platinum nanoparticles were reported, such as controlled chemical reduction [7, 8], electrochemical synthesis [9], irradiation method [10], and thermal decomposition process [11, 12].
The peak positions are in good agreement with those for platinum powder obtained from the International Center of Diffraction Data card (ICDD, formerly JCPDS, 04-0802).
The peaks at 71.0 eV and 74.3 eV, which was corrected with reference to C1s (284.6 eV), corresponding to the binding energy of Pt7/24f and Pt5/24f are in good agreement with the data observed for Pt [13].

Simultaneously, the green target will appear and data collection began.
Data recorded will represent the performance of motor skill before training.
Data Analysis.
This involved removing the repeated data and interpolating the data by 1000 equidistant along the target line.
Further analysis with bigger subject population is required to verify the experimental data.

Load vs. displacement data from the tensile test was collected by a digital data collection system.
Elongation data was measured by an attached extensometer.
The data was directly downloaded into a spreadsheet.
All of the data was stored in digital format.
The affected data is represented with open symbols.

After running it for some time, vibration data in the vertical axis is acquired for a period of 200 secs.
These features are extracted from the data using Matlab.
Then these data are grouped based on the engaged gear and their respective speed in rpm.
Bayesian networks are a family probabilistic graphical data.
This simplifies the representation of P(A/B) and the problem of estimating it from the training data.

The experimental obtained data were statistical processed by the method of regression analysis.
The number of tools is possible to lower by standardization and unification of the working surfaces, what enables better manipulation with the tools and the reduction of the claims for informative system.
This enables better manipulation with the tools and the reduction of the claims for informative system.

The swelling data was obtained as follow.
The noticeable change is the pH reduction over time when vulcanized temperature is at 60 oC.
The swell ratio and viscosity data in Fig. 1 and 2 are replotted at curing temperatures between 45-60 oC and is shown in Fig. 3.
The viscosity data shows a promising potential to predict the degree of vulcanization in this moderate-to-fully vulcanized condition where there is a rapid change in viscosity value
The viscosity data exhibit a very responsive change to the degree of vulcanization particularly in the moderate-to-fully vulcanized condition which can be further exploited as an on-site industrial measurement.

A maximum reduction in cross-sectional area of 50% was achieved for the AISI 1018 stainless steel with a draw velocity of 12.7mm/min.
Alexander and Turner’s [15] dieless drawing machine achieved reductions in cross-sectional area of approximately 75% while Kobatake et al. [16] invented a continuous dieless drawing machine, and achieved successful draws at velocities of up to 4m/min for a 0.4%C steel with a 32% reduction in crosssectional area.
The extension pin of the load-cell was kept away from the specimen and the heater by incorporating a long bar, the top of which was the new datum for the pin.
The Qmat software provided the stress-strain data required.
(b) 0 5 10 15 20 25 30 600 650 690 710 Temperature Strain [%] AISI 01 HT AISI 01 The data recorded in Fig. 6(a), will be useful in the labview front-end parameter control of the dieless drawing machine.