

Articles
by
Abdul Ghapor Hussin 
Total Records (
2 ) for
Abdul Ghapor Hussin 





Leong Jin Hoong
,
Ong Keat Khim
,
Wan Md Zin Wan Yunus
,
Anwar Fitrianto
,
Teoh Chin Chuang
,
Abdul Ghapor Hussin
,
Mansor Ahmad
and
Siti Aminah Mohd Noor


Colorimetric method is one of the common methods used for the environmental monitoring of Arsenic onsite. However, the results that are mainly based on interpretation of the operator are less accurate and reliable. This study describes a more reliable approach to determine Arsenic (V) concentrations whereby an image processing technique is incorporated into a colorimetric method. In this approach, Arsenic (V) concentrations are quantitatively determined by digitized the color formed by the reaction of arsine gas generated from the ion with silver ion impregnated on the filter study. Multiple regression analysis is used to develop a mathematical model to analyze Arsenic (V) concentration by Minitab software. Validation of the developed mathematical model is performed by evaluating the model with the data from the Arsenic (V) standard solutions. The developed mathematical model to determine Arsenic (V) concentration is: Arsenic (V) concentration = 9162.19 Red 2.30 Green 1.667 Blue. The correlation between the calculated Arsenic (V) and known Arsenic (V) concentration was high (R^{2} = 0.9997). The results also revealed that relative bias (0.2 to 3.8%) and relative standard deviation (0.2 to 2.7%) of calculated Arsenic (V) concentrations are low. The accuracy of the Arsenic (V) concentration estimation by the model is between 96 to 99%. It can be concluded that the developed mathematical model is able to estimate the Arsenic (V) concentration accurately and precisely. 




Habshah Midi
,
Ehab A. Mahmood
,
Abdul Ghapor Hussin
and
Jayanthi Arasan


Mean direction is a good measure to estimate circular location parameter in univariate circular data.
However, it is bias and cause misleading when the circular data has some outliers, especially with increasing
ratio of outliers. Trimmed mean is one of robust method to estimate location parameter. Therefore in this study,
it is focused to find a robust formula for trimming the circular data. This proposed method is compared with
mean direction, median direction and M estimator for clean and contaminated data. Results of simulation study
and real data prove that trimmed mean direction is very successful and the best among them. 





