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Articles by M.R. Othman
Total Records ( 3 ) for M.R. Othman
  M.R. Othman , Z. Helwani and Martunus

Fractal permeability model for bi-dispersed porous media is developed based on the fractal characteristics of pores in the membrane. The fractal permeability model is found to be a function of the tortuosity fractal dimension, pore area fractal dimension, sizes of particles and clusters, micro-porosity inside clusters, and the effective porosity of a medium. The pore area fractal dimension and the tortuosity fractal dimension of the porous membranes are determined by the box counting method. To verify the validity of the model, the predicted permeability were compared with the experimental data utilizing H2 gas permeating through porous Pd-alumina, silicalite-1 and B-ZSM-5, and O2 across perovskite-alumina membranes form the past effort.

  M.L. Othman , I. Aris , S.M. Abdullah , M.L. Ali and M.R. Othman
  In this study rough-set-based data mining strategy was formulated to discover distance relay decision algorithm from its resident event report. This derived algorithm, aptly known as relay CD-prediction rules, can later be used as a knowledge base in support of a protection system analysis expert system to predict, validate or even diagnose future unknown relay events. Nowadays protection engineers are suffering from very complex implementations of protection system analysis due to massive quantities of data coming from diverse points of intelligent electronic devices. In helping the protection engineers deal with this overwhelming data, this study relied merely on digital protective relay’s recorded event report because, among other intelligent electronic devices, digital protective relay sufficiently provided virtually most attributes needed for data mining process in knowledge discovery in database. The method of discovering the distance relay decision algorithm essentially involved formulating rough set discernibility matrix and function from relay event report, finding reducts of pertinent attributes using genetic algorithm and finally generating relay prediction rules. The classification accuracy and the area under the ROC curve measurements provided an acceptable evaluation of the fact that the discovered relay decision algorithm.
  N.M. Hanif , M.T. Latif and M.R. Othman
  In this study, the dust (total) at exterior surfaces of windows and street dust (<63 μm) in the vicinity of both busy and quiet streets were sampled in order to determine the concentration of anionic and cationic surfactants, as well as anions (sulfate, nitrate and chloride) to indicate its possible sources. The sampling locations were Bandar Baru Bangi, Bandar Kajang and Seremban, which were selected due to the traffic density in those areas. Samples obtained were analyzed by caolorimetric methods using Methylene Blue Active Substances (MBAS) for anionic surfactants and Disulphine Blue Active Substances (DBAS) for cationic surfactants. The results obtained indicate that the concentration of surfactants was higher in busy areas for both windows and street dust in comparison to quiet areas; although, the difference noted was insignificant (p>0.05). Such that, it is suggested that combustion in car engines is mostly likely to be the source of surfactants in both areas. Additionally, the positive correlation recorded between surfactant and nitrate concentration (R2nitrate = 0.51) added further support to surfactants mainly being produced as a result of vehicular emissions. On the other hand, the insignificant correlation between both surfactants in street dust and on windows in busy areas suggests that the presence of surfactants originated from different sources.
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