A New Approach for Border Detection of the Dumluca (Turkey) Iron Ore Area: Wavelet Cellular Neural Networks

Anomaly analysis is used for various geophysics applications such as determination of geophysical structure's location and border detections. Besides the classical geophysical techniques, artificial intelligence based image processing algorithms have been found attractive for geophysical anomaly analysis. Recently, cellular neural networks (CNN) have been applied to geophysical data and satisfactory results are reported. CNN provides fast and parallel computational capability for geophysical image processing applications due to its filtering structure. The behavior of CNN is defined by two template matrices that are adjusted by a properly supervised learning algorithm. After training stage for geophysical data, Bouguer anomaly maps can be processed and analyzed sequentially. In this paper, CNN learning and processing capability have been improved, combining Wavelet functions and backpropagation learning algorithms. The new architecture is denoted as Wavelet-Cellular Neural networks (Wave-CNN) and it is employed to analyze Bouguer anomaly maps which are important to extract useful information in geophysics. At first, Wave-CNN performance is tested on synthetic geophysical data, which are created by a computer environment. Then, Bouguer anomaly maps of the Dumluca iron ore field have been analyzed and results are reported in comparison to real drilling results.     

Seismic vulnerability assessment in the new urban area of Diriyah Governorate,Riyadh, Saudi Arabia

Nine seismic refraction profiles were conducted and processed to study the near-surface sediments in the new urban area of Diriyah. The 2D geoseismic models illustrate two layers: a surface layer of soft sediments and weathered to hard limestone bedrock. Moreover, microtremor measurements were performed at 38 sites for 40 min using three-component seismographs and processed to assess the peak spectral amplitude and the corresponding fundamental resonance frequency. The seismic vulnerability index at each measurement site was estimated. These results correlate well with the geotechnical borehole data. The north-western zone is highly vulnerable due to the great thickness of the soft sediments.     

Seismic design factors for RC special moment resisting frames in Dubai, UAE

This study investigates the seismic design factors for three reinforced concrete (RC) framed buildings with 4, 16 and 32-stories in Dubai, UAE utilizing nonlinear analysis. The buildings are designed according to the response spectrum procedure defined in the 2009 International Building Code (IBC’09). Two ensembles of ground motion records with 10% and 2% probability of exceedance in 50 years (10/50 and 2/50, respectively) are used. The nonlinear dynamic responses to the earthquake records are computed using IDARC-2D. Key seismic design parameters are evaluated; namely, response modification factor (R), deflection amplification factor (Cd), system overstrength factor (Ωo), and response modification factor for ductility (Rd) in addition to inelastic interstory drift. The evaluated seismic design factors are found to significantly depend on the considered ground motion (10/50 versus 2/50). Consequently, resolution to the controversy of Dubai seismicity is urged. The seismic design factors for the 2/50 records show an increase over their counterparts for the 10/50 records in the range of 200%-400%, except for the Ωo factor, which shows a mere 30% increase. Based on the observed trends, period-dependent R and Cd factors are recommended if consistent collapse probability (or collapse prevention performance) in moment frames with varying heights is to be expected.     

An application of three-dimensional electrical resistivity imaging for the detection of an underground waste-water system

A 3D electrical resistivity imaging survey is presented in this paper. The objective was to investigate an underground wastewater system at the University of Malaya, Malaysia. Apparent resistivity data were collected along ten parallel lines using a Wenner-Schlumberger configuration; electrode cables were oriented in the x-direction with 3 m spacing. Roll-along measurements using a line spacing of 3 m were carried out covering a grid of 20 × 10 electrodes. All data sets were merged into a single data file in order to perform a 3D inversion. Two different 3D least squares algorithms, based on the robust inversion method and the smoothness-constrained technique, were used for the inversion of the apparent resistivity data. Both the horizontal and vertical extents of the anomalous zones found by inversion are displayed. The results indicate the superiority of the robust inversion method over the smoothness-constrained technique at this site. The results are in sufficient accordance with previously known information about the investigation area. The results show that 3D electrical resistivity imaging surveys, in combination with an appropriate 3D inversion method, can be highly useful for engineering and archaeological investigations as well as for environmental applications.     

Young magmatism in Afghanistan as the consequence of the neocene-quaternary tectonic movements

A considerable portion of the territory of Afghanistan, having structures of the Mediterranean folded belt, has been subjected to a general tectonomagmatic activization over the Miocene through to the present, resulting in different (predominantly oscillating) tectonic movements, intrusive magmatism, terrestrial volcanism, mineral occurrences, and springs of carbonated and nitrous thermal water.Three types of young magmatism and volcanism products have been recognized in Afghanistan:

1. (1) Miocene alkaline granite intrusions, described as the Share—Arman Complex, resulted from the early orogenic stage of the Late Alpine geosynclinal troughs development and were restricted to transversal uplifts, in both the geosynclinal structures and on their extension, in the surrounding median masses. These transversal uplifts also play the role of mineralization-controlling structures.

2. (2) Late orogenic—Early Quaternary volcanics (the Dash-i-Nawar Complex) cropping out by the periphery of median masses and at the marginal uplifts of the Late Alpine folded area and also restricted to the transversal uplifts with the confined fault zones to them.

3. (3) Alkaline carbonatitic (the Khanneshin Complex) and trachybasaltic (the SarLogh Complex) Early—Middle Quaternary volcanics in the inner parts of the Central Afghanistan Median Mass and in the southeastern segment of the Turan Plateau.

Areas with products of Middle Quaternary volcanism are restricted to knot areas of the major subcrustal faults which are currently active.     

The use of watershed geomorphic data in flash flood susceptibility zoning: a case study of the Karnaphuli and Sangu river basins of Bangladesh

Natural Hazards - The occurrence of heavy rainfall in the south-eastern hilly region of Bangladesh makes this area highly susceptible to recurrent flash flooding. As the region is the commercial...     

NARX neural network approach for the monthly prediction of groundwater levels in Sylhet Sadar,Bangladesh

Groundwater is important for managing the water supply in agricultural countries like Bangladesh. Therefore, the ability to predict the changes of groundwater level is necessary for jointly planning the uses of groundwater resources. In this study, a new nonlinear autoregressive with exogenous inputs(NARX) network has been applied to simulate monthly groundwater levels in a well of Sylhet Sadar at a local scale. The Levenberg-Marquardt(LM) and Bayesian Regularization(BR) algorithms were used to train the NARX network, and the results were compared to determine the best architecture for predicting monthly groundwater levels over time. The comparison between LM and BR showed that NARX-BR has advantages over predicting monthly levels based on the Mean Squared Error(MSE), coefficient of determination(R~2), and Nash-Sutcliffe coefficient of efficiency(NSE). The results show that BR is the most accurate method for predicting groundwater levels with an error of ± 0.35 m. This method is applied to the management of irrigation water source, which provides important information for the prediction of local groundwater fluctuation at local level during a short period.