Hi, I am Ahmad Zia Ul-Saufie Mohamad Japeri, My LiveDNA is 60.6594
 
   
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Dr. Ahmad Zia Ul-Saufie Mohamad Japeri
 
Highest Degree: Ph.D. in Air Quality from Universiti Sains Malaysia, Malaysia
 
Institute: Universiti Teknologi Mara, Malaysia
 
Area of Interest: Mathematics
  •   Statistical Modeling
  •   Environmental Modeling
  •   Regression
  •   Hybrid Models
 
URL: http://livedna.org/60.6594
 
My SELECTED Publications
1:   Abdul Hamid, H., A.S. Yahaya, N.A. Ramli and A.Z. Ul-Saufie, 2012. Moment or probability weihted moments: The suitable method in PM10 concentration modelling by using three-parameter weilbull distribution. Proceeding of the 3rd International Conference on Human Habitat and Environment in the Malay World, June 19-20, 2012, Puri Pujangga, Universiti Kebangsaan Malaysia, Bangi, pp: 243-248.
2:   Abdul Hamid, H., A.S. Yahaya, N.A. Ramli and A.Z. Ul-Saufie, 2012. Performance of parameter estimator for the two-parameter and three-parameter gamma distribution in PM10 data modeling. Int. J. Eng. Technol. 2: 637-643.
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3:   Abdul Hamid, H., A.S. Yahaya, N.A. Ramli and A.Z. Ul-Saufie, 2013. Finding the best statistical distribution model in PM10 concentration modeling by using lognormal distribution. J. Applied Sci., 13: 294-300.
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4:   Abu Bakar, A.A., K.A. Muhd Ali, N.A.A. Tarmizi, A.Z. Ul-Saufie and J.A. Tammy, 2016. Potential of using bladderwort as a biosorbent to remove zinc in wastewater. AIP Conf. Proc., Vol. 1774. 10.1063/1.4965079.
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5:   Ahmat, H., A.S. Yahaya, N.A. Ramli, A. Zia ul-Saufie and H.A. Hamid, 2015. Analysis of PM10 using extreme value theory. ESTEEM Acad. J., 11: 135-143.
6:   Elbayoumi, M., N.A. Ramli, N.F.F.M. Yusof, A.S.B. Yahaya, W. Al Madhoun and A. Zia Ul-Saufie, 2014. Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings. Atmos. Environ., 94: 11-21.
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7:   Mohammed, N.I., N.A. Ramli, A.S. Yahya, N.A. Ghazali and A.Z. Ul-Saufie, 2011. Relationship between AOTX indices and crops response towards ozone concentration in Malaysia. Int. J. Applied Sci. Technol., 1: 36-44.
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8:   Muhamad, M., A. Zia Ul-Saufie and S.M. Deni, 2015. Three days ahead prediction of daily 12 hour ozone (O3) concentrations for urban area in Malaysia. J. Environ. Sci. Technol., 8: 102-112.
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9:   Ul-Saufie, A.Z., A.S. Yahaya and N.A. Ramli, 2011. Improving multiple linear regression model using principal component analysis for predicting PM10 concentration in Seberang Prai, Pulau Pinang. Int. J. Environ. Sci., 2: 403-410.
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10:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli and H. Abdul Hamid, 2011. Comparison between multiple linear regression and feed forward back propagation neural network models for predicting PM10 concentration level based on gaseous and meteorological parameters. Int. J. Sci. Technol., 1: 42-49.
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11:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli and H. Abdul Hamid, 2012. Future PM10 concentration prediction using quantile regression models. Proceeding of the 2nd International Conference on Environmental and Agriculture Engineering, June 29-30, 2012, Jeju Island, South Korea, pp: 445-453.
12:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli and H. Abdul Hamid, 2012. Robust regression models for predicting PM10 concentration in an industrial area. Int. J. Eng. Technol., 2: 364-370.
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13:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli and H. Abdul Hamid, 2012. The application of principal component analysis to determine the factors that contribute to PM10 concentrations at an industrial area. Proceeding of the 3rd International Conference on Human Habitat and Environment in the Malay World, June 19-20, 2012, Puri Pujangga, Universiti Kebangsaan Malaysia, Bangi, pp: 227-232.
14:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli and H.A. Hamid, 2012. Performance of multiple linear regression model for long-term PM10 concentration prediction based on gaseous and meteorological parameters. J. Applied Sci., 12: 1488-1494.
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15:   Ul-Saufie, A.Z., A.S. Yahaya, N.A. Ramli, N. Rosaida and H.A. Hamid, 2013. Future daily PM10 concentrations prediction by combining regression models and feedforward backpropagation models with Principle Component Analysis (PCA). Atmos. Environ., 77: 621-630.
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16:   Umar, N., M. Japeri, A.Z. Ul-Saufie, S.B. Mahlan and M. Shamsuddin, 2015. Effects of air pollution on human health: Perspective of university students. Esteem Acad. J., 11: 144-149.
17:   Yaakob, Y., A.Z. Ul-Saufie, F. Idrus and M.D. Ibrahim, 2016. The development of thermosiphon heat exchanger for solar ponds heat extraction. AIP Conf. Proc., Vol. 1774. 10.1063/1.4965111.
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18:   Yahaya, A.S., N.A. Ramli, A.Z. Ul-Saufie, H. Abdul Hamid, H. Ahmat and Z.A. Mohtar, 2013. Predicting CO concentrations levels using probability distributions. Int. J. Eng. Technol., 3: 900-905.
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19:   Yusoff, W.M.B.W., M.B. Fikri, H.B. Muhammad and A.Z. Ul-Saufie, 2014. A case study on the impact of smart accounting on business students at a Malaysian polytechnic. IOSR J. Bus. Manage., 16: 24-28.
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20:   Zawawi, M.H., L.Z. Yuan, N.I. Mohammad, A.Z. Al-Saufie, M.Z. Ramli and N.A. Rosli, 2016. 24 and 12 hours Exceedances prediction of particulate matter 10 Using extreme value distribution: A case study in Kuala Lumpur City centre. J. Sci. Res. Dev., 3: 106-111.
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21:   Zia Ul-Saufie, A., A.S. Yahaya, N.A. Ramli and H.A. Hamid, 2015. PM10 concentrations short term prediction using feedforward backpropagation and general regression neural network in a sub-urban area. J. Environ. Sci. Technol., 8: 59-73.
22:   Zia Ul-Saufie, A., M.H. Lee and S. Salleh, 2008. Simulation of routing probability in ad-hoc networks. Esteem J., 2: 39-49.