Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Articles by Mansor Ahmad
Total Records ( 2 ) for Mansor Ahmad
  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 on-site. 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 = 916-2.19 Red -2.30 Green -1.667 Blue. The correlation between the calculated Arsenic (V) and known Arsenic (V) concentration was high (R2 = 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.
  Soleha Mohamat Yusuff , Ong Keat Khim , Wan Mad Zin Wan Yunus , Jahwarhar Izuan Abdul Rashid , Anwar Fitrianto , Mansor Ahmad , Nor Azowa Ibrahim , Syed Mohd Shafiq Syed Ahmad and Chin Chuang Teoh
  Dewatered alum sludge from drinking water treatment plants was exploited as carbon dioxide (CO2) adsorbent in a fixed-bed (CO2)lumn system. In this study, the effects of 6 parameters including particle size of adsorbent, heat treatment of adsorbent, adsorbents dosage, adsorption temperature, flow rate of adsorbate and (CO2) ncentration on the fixed-bed adsorption of (CO2) were investigated using Response Surface Methodology 2 2 (RSM). The experimental data was successfully fitted with the regression model to identify the significant parameters and predict the optimum value parameters for maximizing (CO2) adsorption capacity. Analysis of 2 Variance (ANOVA) revealed that (CO2) ncentration was the most significant factor influenced the (CO2) adsorption capacity. The experimental data of (CO2) adsorption capacity were in a good agreement with the 2 predicted data from the regression model. The highest fixed-bed (CO2) adsorption capacity of 10.028 mmol.g 2 –1 (441.24 mg.g–1) was achieved using 1 g of 450-500 μm of 800°C thermally treated alum sludge at (CO2) ncentration of 8000 mg.L–1 with a flow rate of 90 mL.min–1 at 25°C. The results suggested that thermally treated alum sludge is a promising solid adsorbent for (CO2) capture.
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility