Electrical structure and its implication across the lower- and upper-crustal settings of South India

Measurements of a large scale MMA experiment covering both the granulite and greenstone terrains of Archeans in the southern part of India is re-visited and re-analyzed. The induced field variations contain the signatures of crustal and subcrustal electrical conductivities, although substantially distorted by the sea-land interfaces and cenozoic sediments. However, through a selection of some reconnaissance profiles and temporal variations, an attempt is made to deduce whether: (1) significant differences exist between the electrical structures of the high and low grade complexes (i.e., if the electrical conductivity of the lower crust is due to minerological composition or is intrinsic to the positioning at depths greater than 15 km); (2) the probable seaward extension of the continental crust and its transition to oceanic type may also contribute (through intracrustal DC-like telluric sheets) to the induction field in addition to or rather than the sharply localized zones; (3) the observed parameters are indicative of a formal anisotropy and/or undulations in the deep crust; and (4) the postulate of relatively hotter Indian shield is reflected particularly with regard to differential metamorphism. In the last case, the crust-mantle coupling in this region - unlike other similar areas - seems to be markedly affected by the evolution of Ne-plate velocity field

Investigating the impact of image content on the energy efficiency of hardware-accelerated digital spatial filters

Battery-operated low-power portable computing devices are becoming an inseparable part of human daily life. One of the major goals is to achieve the longest battery life in such a device. Additionally, the need for performance in processing multimedia content is ever increasing. Processing image and video content consume more power than other applications. A widely used approach to improving energy efficiency is to implement the computationally intensive functions as digital hardware accelerators. Spatial filtering is one of the most commonly used methods of digital image processing. As per the Fourier theory, an image can be considered as a two-dimensional signal that is composed of spatially extended two-dimensional sinusoidal patterns called gratings. Spatial frequency theory states that sinusoidal gratings can be characterised by its spatial frequency, phase, amplitude, and orientation. This article presents results from our investigation into assessing the impact of these characteristics of a digital image on the energy efficiency of hardware-accelerated spatial filters employed to process the same image. Two greyscale images each of size 128 × 128 pixels comprising two-dimensional sinusoidal gratings at maximum spatial frequency of 64 cycles per image orientated at 0° and 90°, respectively, were processed in a hardware implemented Gaussian smoothing filter. The energy efficiency of the filter was compared with the baseline energy efficiency of processing a featureless plain black image. The results show that energy efficiency of the filter drops to 12.5% when the gratings are orientated at 0° whilst rises to 72.38% at 90°