No abstract

This work aims at enhancing the thermal conductivity of base fluids (water and methanol) through successive washing of polymers from the surface of polyvinylpyrollidone (PVP)-stabilized copper (Cu) nanoparticles. Cu nanofluids were successfully synthesized and characterized using transmission electron microscope and UV-vis spectrophotometer. Thermal conductivity of freshly prepared Cu nanofluid shows~10% enhancements. The poor enhancement in thermal conductivity is due to the presence of thick polymer coating on the surface of nanoparticles. A new technique has been developed to erode the polymers from the nanoparticle surface by repeated washing and redispersion. After one-time washing and redispersion, the thermal conductivity of nanofluid has been increased to 0.732 W/mK (~22% enhancements). Greater enhancement (~30.34%) has been achieved after three times continuous washing and redispersion. Finally, the experimental values of thermal conductivity were compared and validated against the existing Maxwell effective model.

This paper presents a three dimensional hybrid filter to remove random valued impulse noise from colour video sequences. The switching median technique is utilized to protect noise free isolated pixels from filtering so as to avoid blurring of frames. The restoration of noisy pixels is done by brightness information obtained from median filtering and chromaticity information is obtained from vector directional filtering. This hybrid filter is applied in three dimensional sliding window where spatial as well as temporal information about neighbourhood is available for restoration of frame under consideration. Only noise free pixels of three dimensional sliding window are used for restoration of frame under consideration. Simulation results show that the proposed three dimensional hybrid filter yields superior performance in comparison to other filtering methods

The rapid worldwide spread of the COVID-19 disease has resulted in a global pandemic. Wearing the face mask correctly is extremely crucial for infectious disease control, but the effectiveness of facemasks has been diminished, mostly due to improper wearing. This project is a cost-effective warning system to the people for wearing the masks by using the ESP32-CAM and Arduino. This model can be applied to safeguard public places or private businesses during the pandemic. It will help in ensuring that the mask-wearing policy is followed and the concerned authorities are notified so that they can take appropriate actions and prevent the further spread of COVID-19.