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Articles by Mohammad Mokhtari
Total Records ( 2 ) for Mohammad Mokhtari
  Mohammad Mokhtari , Mazlan Abd Ghaffar , Gires Usup and Zaidi Che Cob
  Fiddler crabs burrow creates oxic-anoxic interfaces on the burrow walls. Accordingly burrow walls represent the transitions site between oxic and anoxic condition where the sediment properties varied significantly across it. In this study the burrows of three species of fiddler crabs including Uca rosea, Uca forcipata and Uca pardussumieri were sampled at three depth layers. Sediment properties of burrow walls including; temperature, redox potential, pH, density, porosity, water content, organic content, chlorophyll content and solid phase iron pools were measured to determine the magnitude of burrow effects on mangrove sediments. The results indicated that U. paradussumieri effectively reduced the sediment porosity of surrounding sediments down to 45%. Oxidized layer was more extended around U. paradussumieri burrows. Burrow walls of U. forcipata and U. paradussumieri contain higher water content than ambient sediment and burrows of U. rosea efficiently decreased the organic content of sediment. The PCA biplots indicated that the burrow walls of the all three species of fiddler crabs at 3 and 8 cm depth were correlated with oxidized iron. Ambient sediments of U. forcipata habitat were correlated with reduced iron and organic content. At 20 cm depth, burrow walls of U. paradussumieri were highly correlated with water content, while ambient sediment was correlated with reduced iron. The results of this study revealed that the thickness of oxidized layer varied according to sediment depth and burrow volume. Consequently the burrow effect varied significantly among different species of fiddler crabs as results of different habitat characteristics, sediment types and crab size.
  Christine Baronian , Mohammad Ali Riahi , Caro Lucas and Mohammad Mokhtari
  In this study, different synthetic earth models have been developed for providing as accurate as possible mapping between inputs and outputs. The input parameters were seismic travel times fed to input layer of ANN and the output parameters were interval velocity and structural dip fed to output layer of ANN. After training the so structured ANN the generalization ability of ANN can create desirable outputs for new input patterns. As dipping layered structures has more occurrences in nature and in subsurface of earth (like anticline shapes of hydrocarbon traps), therefore obtaining an accurate initial velocity model for dipping structures as well as dip values of each layer is an important part of later seismic imaging procedures especially in areas with little or no initial geological information available.
 
 
 
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