In this paper, an adaptive approach of bilateral filtering is introduced for the despeckling of medical ultrasound images. The range parameter is estimated from intensity homogeneity measurements. For each pixel, the measurements are carried out utilizing its local neighbors considering different directions. The range parameter is then estimated from the variance of the most homogeneous blocks and thus, automatically gets adapted according to the variations of the speckle noise. Experiments performed on synthetically-speckled images reveal that the proposed method outperforms several recently introduced despeckling techniques in terms of the signal-to-noise ratio and structural similarity index with a better preservation of image structures. It is shown that the proposed method improves the visual quality of ultrasound images by removing mostly noise while retaining the diagnostically important image details.

As power density keeps increasing tremendously in emerging VLSI nanotechnology, the sensing and monitoring of die temperature is vital, implying the need for high performance materials compatible with current CMOS technology. Graphene is a promising material for sensor applications due to its planar geometry and high electrical and thermal conductivity. In this work, we have explored the feasibility of a thin oxide graphene field effect transistor (G-FET) as a temperature sensor. The resistivity of the device has been calculated using the semi-classical transport equations considering the scattering mechanisms by substrate polar phonons and intrinsic phonons. The generated self-heating in graphene-silicon dioxide interface, silicon dioxide layer and back-gated silicon wafer has been also considered to extract the saturation velocity of graphene at high electric field and high temperature. We have found that the resistivity of G-FET is highly sensitive to high ambient temperature variation. The calculated temperature coefficient of resistance (TCR) of G-FET at high temperatures (~600 o C) is three times higher than room temperature exhibiting the highly sensitive resistance to high temperature variation. The resistance shows third order dependence on the ambient temperature in the range of 0 to 600 o C and the TCR at high temperatures has been demonstrated a high dependence on the drain-source voltage ranging from to for the voltage spanning from 5V to 1V while that of low temperature is relatively unalterable.

In this work, we have studied Joule heating in carbon nanotube based very large scale integration (VLSI) interconnects and incorporated Joule heating influenced scattering in our previously developed current transport model. The theoretical model explains breakdown in carbon nanotube resistance which limits the current density. We have also studied scattering parameters of carbon nanotube (CNT) interconnects and compared with the earlier work. For 1 µm length single-wall carbon nanotube, 3 dB frequency in S12 parameter reduces to ~120 GHz from 1 THz considering Joule heating. It has been found that bias voltage has little effect on scattering parameters, while length has very strong effect on scattering parameters.

Recent studies have shown superior thermal transport of graphene on copper as a potential candidate for the next generation interconnects. Using density function theory (DFT) we have studied the current transport of graphene/copper (G/Cu) hybrid-nano wire interconnect system and compared electrical characteristics with other two dimensional counterparts along with graphene. From the first principle calculation, band structure and density of states have been calculated. Using Landauer-Buttiker (LB) formalism, electrical transport is calculated. We explained why G/Cu hybrid interconnect shows more conductivity than graphene only interconnects with the help of phase space argument. As graphene on copper system has more available density of states near the Fermi level it offers more states than graphene for conduction.

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