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Zulkafli A.H.,Universiti Sains Malaysia | Hamzah A.H.,University Sultan Zainal AbidinTerengganu | Bakar N.A.,University Sultan Zainal AbidinTerengganu
Advanced Science Letters | Year: 2015

This paper presents evidence on the role of board governance in influencing financing policy of listed companies in Malaysia. As most of board’s studies directed towards understanding the influence of its structure on firm’s performance, this study is intended to measure its relationship with corporate financial policies in a country with a highly concentrated ownership structure; Malaysia. This study employs board size, board independent and board remuneration as board governance proxy while debt ratio is used to represent financing policy of a firm. It is found that board remuneration is the only significant board governance variable in explaining financing policy of public listed companies in Malaysia. © 2015 American Scientific Publishers. All rights reserved. Source


Ibrahim A.,University Sultan Zainal AbidinTerengganu | Juahir H.,University Sultan Zainal AbidinTerengganu | Toriman M.E.,University Sultan Zainal AbidinTerengganu | Mustapha A.,Kano University of Science and Technology | And 2 more authors.
Malaysian Journal of Analytical Sciences | Year: 2015

Multivariate Statistical techniques including cluster analysis, discriminant analysis, and principal component analysis/factor analysis were applied to investigate the spatial variation and pollution sources in the Terengganu river basin during 5 years of monitoring 13 water quality parameters at thirteen different stations. Cluster analysis (CA) classified 13 stations into 2 clusters low polluted (LP) and moderate polluted (MP) based on similar water quality characteristics. Discriminant analysis (DA) rendered significant data reduction with 4 parameters (pH, NH 3-NL, PO4 and EC) and correct assignation of 95.80%. The PCA/FA applied to the data sets, yielded in five latent factors accounting 72.42% of the total variance in the water quality data. The obtained varifactors indicate that parameters in charge for water quality variations are mainly related to domestic waste, industrial, runoff and agricultural (anthropogenic activities). Therefore, multivariate techniques are important in environmental management. © 2015, Malaysian Society of Analytical Sciences. All rights reserved. Source


Mamat A.R.,University Sultan Zainal AbidinTerengganu | Abd Rawi N.,University Sultan Zainal AbidinTerengganu | Awang M.I.,University Sultan Zainal AbidinTerengganu | Kadir M.F.A.,University Sultan Zainal AbidinTerengganu | Abd Rahman M.N.,University Sultan Zainal AbidinTerengganu
International Journal of Advances in Soft Computing and its Applications | Year: 2015

Content based image retrieval (CBIR) has become one of the most active research areas in the past few years. Many indexing techniques are based on global feature distributions. However, these global distributions have limited discriminating power because they are unable to capture local image information. In this paper, the new proposed method based on local image to classify the Interest Region (IR) and Non Interest Region (NIR) of images. To develop this, the integration of clustering and user intervention was applied. Clustering process is obtaining several regions, meanwhile to ascertain the location of the center of images through user intervention. Several experiments are conducted using different weight (ω, γ) of IR and NIR. Subsequently average color moment is extracted from this region (IR and NIR) in CIE Lab color model. To investigate the performance, new distance is proposed based on Euclidean distance. Experimental results show the proposed method more efficient in image retrieval. Source

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