In recent years fluids containing suspension of nanometer sized particles have been an active area of research due to their enhanced thermo physical properties over the base fluids like water, oil etc. Nanofluids possess immense potential applications to improve heat transfer and energy efficient in several areas including automobile, micro electronics, nuclear, space and power generation. Nowadays most of the researchers are trying to use the nanofluids in automobile for various applications such as coolant, fuel additives, lubricant, shock absorber and refrigerant. The goal of this paper is to create the awareness on the promise of nanofluids and the impact it will have on the future automotive industry. This paper also presents a comprehensive data of nanofluids application in automobile for various aspects.

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In spite of having low Compressive and flexural strength, No-fines concrete has properties capable of being used as rigid pavement for low traffic volume roads. Along with the mix proportions and water content to have sufficient bond between the aggregate particles, it is critical to determine what happens to the water once it penetrates the pavement surface. Different combinations of Cement, GGBS, water and Course aggregate with different maximum size and gradation were adopted for trial mixes to arrive at M20 grade concrete.M20 grade concrete is achieved with a w/c ratio of 0.36, Coarse aggregate of nominal size 20 mm passed and 10 mm retained ,cement is partly replaced with 30% of GGBS and with a cement to Course aggregate ratio of 1:4. Its compressive strength were observed to be 20.4 kN/m3.A perforated pipe can be provided at center of the pavement above sub-base such that it collects the water stored in concrete and drains it to the required treatment plant or a recharge pit.

One of the most difficult challenges of multimedia transmission during the last two decades has been the retrieval of degraded or missing regions of images and videos while maintaining satisfactory perceptual accuracy. The objective is to retrieve lost data by using the similarity between frames. Usually, error concealment (EC) schemes depend on replacing incorrect data with data that are identical to the initial. This is possible because video contains a high degree of self-similarity. This research focuses on applying an EC approach in transform-domain video sequences. To conduct EC on films, they must first be translated to frames and then transformed using one of the available transformations into frequency-domain images. Using successive frames, it is possible to recover lost or incorrect data from images. Intra-coded frames (I-frames) may be used to recreate lost knowledge in predictive (P-frames) and bidirectional predictive frames (B-frames). I-frame knowledge that has been lost may be restored using previous intra-coded frames. The use of wavelet error concealment generated more precise results than the other techniques. In this study, it was discovered that covering faults in the density sector with wavelets produces more reliable results than the other techniques.

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Digital image processing is currently used in various fields of research. One of them is in the field of medicine. In fact, experienced radiologists have difficulty distinguishing the cancerous portions of the blood vessels in the lung or detecting fine nodules that suggest lung cancer on X-ray images. Previous studies have shown that doctors and radiologists fail to detect cancerous patches in 30% of positive cases. Implementation of CAD system to classify and detect parts of cancer has been developed, but the results obtained from this implementation are that there are still many errors in the classification results. Therefore, this study will develop android app image technique to perform the classification process of lung cancer. With this research, it is hoped that the developed algorithm can help doctors and radiologists to detect cancer in a short time with more accuracy. Finally, after 20 iterations, a percentage of 90.65% was attained for the test results' performance in classifying 10 X-ray pictures.

The thermal and mechanical effects of human tissues and physics that governs biological processes has been developed by applying fundamental engineering principles in the investigation of numerous heat and mass transfer applications in biology and medicine. An incompressible magnetohydrodynamic nanofluid flow passing over a stretched surface along with the effect of viscous dissipation is analyzed numerically. In order to create a nonlinear transformed model in terms of ordinary differential equations, suitable similarity transformations are used and solved by employing a Mathematica algorithm. Furthermore, a minimal case comparison standard has been provided to validate the current methodology. The machine learning method is built through very important parameters. Simulations and machine learning approaches could work together to reveal new and fortunate prospects in computational science and engineering problems. The performance of the parameters in terms of heat and mass transfer is presented with an aid of graph to demonstrate the applicability of the current model.