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Abstract
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"Polyamide-6 (PA6), acrylonitrile-butadiene-styrene (ABS) and their blends
are an important class of engineering thermoplastics that are widely used in
electronic and automotive industries. Many efforts have been taken to improve the
properties of both pure components and the blends. It was for this reason that the
dynamic mechanical and rheological properties of PA6/ABS blend systems
compatibilised by acrylonitrile-butadiene-styrene-maleic anhydride (ABS-g-MAH)
was studied. The compatibiliser levels were kept up to 5wt. % in the blends. Short
glass fibre (SGF) was used to improve the stiffness of the compatibilised blends and
the fibre contents were from 10 to 30 wt. %. Therefore, the reason behind blending
the PA6/ABS blends with short glass fibre was to balance the toughness and
stiffness. Both the blends and corresponding composites were compounded using a
counter-rotating twin screw extruder. Tensile, flexural and impact properties were
determined using the injection moulded test samples according to ASTM standards.
The mechanical properties of the blends and the composites were investigated in
both static and dynamic modes. Rheological properties were investigated using
rotational and capillary rheometer. In general, the mechanical strength either
dynamic (refer to dynamic mechanical properties) or static conditions improved by
incorporation of compatibiliser to the PA6/ABS blends. The incorporation of SGF
into the PA6/ABS blends enhanced the mechanical strength but reduced the
toughness of the composites. The rheological measurements confirmed the
interaction between the blend components with the incorporation of compatibiliser
has been improved. However, the compatibiliser has no favourable effect on the
mechanical properties of the composites although it has significant effect on the
blends of PA6/ABS. The compatibiliser increased the melt viscosity of the blends.
The SGF increased the rheological properties especially viscosity and flowability of
the composites. The optimum ratio of compatibiliser and SGF concentration were
determined using power law, n and consistency index, K analyses. From the analysis,
the optimum ratio obtained was 1.5 wt. % for 50/50 and 60/40 PA6/ABS blends and
3 wt. % for 70/30 PA6/ABS blends. The n values drastically decreased, when
concentration of the SGF was about 20 wt % indicating more pseudoplastic nature
for the composites and suggesting that, 20 wt % is the optimum SGF concentration." |
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Abstract
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"Implicit speech segmentation approach as in divergence algorithm is able to
avoid problems of training data dependent and phoneme boundary selection which
existed in explicit segmentation approach like Hidden Markov Model based methods.
Although the method could give high match but its drawback is high insertion rate
which reduces the segmentation quality. This work proposed a fusion between
divergence algorithm and back propagation neural network with new property based
on zero crossing rate to enhance speech segmentation via reducing the insertion in
divergence algorithm. The segmentation performance of divergence algorithm was
optimized via choosing the best combination of bias, threshold and auto regression
order parameters. The introduced signal property based on zero crossing rates are
applied on segmentation points resulted from divergence algorithm to detect obvious
false insertion points at unvoiced signal. The remaining insertions points at voiced
signal are then further detected using the back propagation neural network via signal
pattern classification between two segmentation points. The effects of different
operators in the fusion method were studied and the effectiveness and shortcoming of
the fusion were highlighted. The proposed method was tested on Malay connected
speech and results of segmentation performance were compared between divergence
algorithm, the introduced property based on crossing rate and the fusion with back
propagation neural network. It was discovered that the introduced property could
reduce insertion points up to 5% while maintaining 98% match rate as in divergence
algorithm while fusion method could reduce insertion rate more than 20% while
maintaining match rate at above 90%. Although not all insertion points were
detected, the study demonstrated the potential use of the fusion method for speech
segmentation improvement." |
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Abstract
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"Polyvinyl alcohol (PVOH) blends with cassava starch (CSS) is a
biodegradable polymer compound. This polymer compound is suitable to be used as
biodegradable material to reduce the accumulation of synthetic petroleum-based
polymer solid wastes. In this study, the fundamental blending characterizations of
PVOH-CSS were investigated by molecular modeling to unveil the hydrogen
bonding interactions among the blending components. In addition, infrared
spectroscopy (FT-IR), differential scanning calorimetry (DSC), and
thermogravimetric analysis (TGA) were conducted to support the molecular
modeling outcomes. The processability behaviour of the PVOH-glycerol-CSS
compounds (PGCS) such as specific heat capacity, pressure-volume-temperature,
and shear rate-viscosity were studied as well. These data were imported into
Moldflow software for injection moulding simulation based on a name tag article
design (NTA). Subsequently, the simulated outcomes were validated by actual
injection moulding process using statistical analysis. The fundamental blending
characterizations results showed that blending of PVOH and CSS are synergistically
compatible. However, the incorporation of glycerol has weakened the genuine
interactions between PVOH and CSS. Meanwhile, the processability study of PGCS
showed that 40 wt.% and 50 wt.% CSS compounds are favourable to be injection
moulded. Finally, the statistical outcomes have concluded that optimum processing
can help to produce NTA with low volumetric shrinkages at acceptable variabilities.
In conclusion, PVOH-CSS blend is a compatible polymer compound. It is also a high
potential injection moulding processable biodegradable starch-based polymer
compound. " |
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Abstract
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Share buyback has gained Prominence in all the leading capital markets. Since 1999 many companies in Bursa Malaysia has embraced this phenomena whole heartedly. The Asian financial crisis in 1997 has encouraged the adoption of this corporate management tool to shore up the sagging share prices and to improve the financial image and ratios. This study examines and substantiates with empirical evidence the signaling motivation of share repurchases.
The analyses and results provided here are based on observations of 187 companies for the years 1999 to 2006. A number of test including the t test, regression analysis, random number simulations and wavelet analysis were conducted. A dichotomous method was applied to record the changes in prices and risks before buyback at buyback and after share buyback, both for the wider buyback period and narrow buyback period. To examine the collective correlation and influence of Share buyback on share prices, twelve independent variables were included in the regression analysis. In addition, a stepwise regression analysis was done to determine the independent variables individual influence on the share price. Besides that to investigate the effects of the share repurchases on individual companies, the wavelet analysis was undertaken. To evaluate the predictability of share prices for companies undertaking the share buyback program, a Monte Carlo Simulation with random numbers was also done.
The results showed that the share price changes after share buyback was robust in the narrow buyback period but weak over the wider buyback period. Similarly, the changes in risks were in tandem and direction of the changes in the prices. Overall, the R2 were high and significant for all the regression models for every year with share price as the dependent variables. This may be due to the fact that for all the models the independent variables which were accounting ratios fit the model well. But for the share buyback, the accounting ratios did not explain a major part of the purchase consideration. There could be other independent variables which were external to the company that determined the major part of the share buyback phenomena.
The Earnings per share model indicated that purchase consideration is one of its determinants. But purchase considerations did not influence dividend payments. Random number simulation using six years data did not accurately predict share prices of companies that undertook the share buyback program. The Wavelet analysis showed the oscillations in share price wavelets of five different frequencies. The higher volume showed greater oscillations in the wavelets.
The influence of the share buyback on share prices was not consistent for the years studied. This makes it difficult for one to reach a conclusion. The opportunistic behaviour of market players may blunt and blur the results. However, the results are generally similar and support the major studies conducted on share buyback. |
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8. |
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Governance of Public Universities in Malaysia
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, 2009. University of Malaya
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9. |
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10. |
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Orientasi Moral di Kalangan Pelajar Tingkatan
Empat
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11. |
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12. |
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The Development of Islamic Banking in Yemen
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