Papers by Muhammad Ismail
Water Air and Soil Pollution, 2010
The gamma spectrometric analysis of soil and essential foodstuffs, e.g., wheat, millet, potato, l... more The gamma spectrometric analysis of soil and essential foodstuffs, e.g., wheat, millet, potato, lentils and cauliflower, which form the main component of the daily diet of the local public, was carried out using high purity germanium (HpGe) detector coupled with a computer based high-resolution multi-channel analyzer. The activity concentration in soil samples for 226Ra, 232Th and 40K ranged from 30.0 Bq kg−1 to 81.2 Bq kg−1, 31.4 Bq kg−1 to 78.25 Bq kg−1 and 308.8 Bq kg−1 to 2177.6 Bq kg−1, with mean values of 56.2, 58.5 and 851.9 Bq kg−1, respectively. The average activity measured for 226Ra, 232Th and 40K in soil samples was found higher than the world average. The major radionuclide found in the food items studied was 40K, while 226Ra, 232Th and 137Cs were detected in very nominal amounts. The results clearly indicate that these radionuclides have no health hazard to human beings, as they are well below the annual limit of intake (ALI) for these radionuclides. The transfer factors of these radionuclides from soil to food were also studied. The mean transfer factors of 40K, 226Ra, 232Th and 137Cs from soil to food were estimated to be about 0.17, 0.07, 0.16 and 0.23, respectively. An artificial radionuclide, 137Cs, was also present in detectable amount in all samples. The internal and external hazard indices were measured and had mean values of 0.70 and 0.55, respectively. Absorbed dose rates and effective dose have been determined in the present study. Concentration of trace metals, such as Cr, Pb, Ni and Zn, was also determined in the soil samples. The concentrations of radionuclides and trace metals found in these samples during the present study were nominal and do not pose any potential health hazard to the general public.
a b s t r a c t a r t i c l e i n f o This paper presents a new approach to automatic pipe inspec... more a b s t r a c t a r t i c l e i n f o This paper presents a new approach to automatic pipe inspection using pixel-based segmentation of colour images by support vector machine (SVM) coupled with morphological analysis of the principal connected component of the segmented image. The pixel-based segmentation method has been tested using RGB, HSB, Gabor and local window feature sets and is seen to work best with the HSB feature set. The morphological analysis allows the principal connected component of the segmented image to be decomposed into the pipe flow line region, the pipe joints and adjoining defects. Generalisations of the morphological operations of erosion and dilation are defined and some simple properties of them are derived. A fuzzy approach to pipe connection detection is also described.
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Papers by Muhammad Ismail