Physicians and obstetricians should be vigilant so that they can swiftly identify co‐infections of malaria and dengue in pregnant women with COVID‐19.

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In recent days, a developed driver support system has been introduced to enhance driving, which is considered as the renowned one. In the Advanced Driver assistive systems, Lane departure detection plays an important role and it enhances the vehicle's active safe driving. Nowadays, a decent lane detection model that is on the basis of the computer vision methods, is introduced in many studies. From a stream of videos, the lane boundaries and its radius of curvatures and lane direction is detected. This video footage is recorded from a camera mounted on the top of a vehicle. Here, the lane detection model is proposed, which concentrates more on driving assistance. In this paper, a deep learning scheme is used for a lane detection model. Here, the adopted strategies possess two main components namely lane detection and image transformation. At first, the multiple lane images are obtained by the adopted technique and it transforms the image, and it aids in classifying the training. The Deep Convolution Neural Network (DCNN) classifier is considered to detect the lane from the bird's eye view image. An Enhanced Manta-Ray Foraging Optimization Algorithm (EMRFOA) is proposed to aid the DCNN classifier with the optimal weights in this paper. Finally, the developed model is analyzed with the conventional models in that the performance of the adopted model is higher than the conventional models.

Increasing digital technology has revolutionized the life of people. The banking system in today’s world is open to threats of fraud and cyber-attacks. Since todays banking system is built on centralized databases, it is easy for an attacker to penetrate in any such database which will easily compromise all the information and data of the customers of the bank. This vulnerability of today’s banking system can be reduced by re-building the banking systems on top of block chain technology, which will remove the centralized database architecture and decentralize the data over the block chain, thus reducing the threat of database being hacked. Since the transactions over the block chain technology is verified by each and every nodes of the chain, it will make the transactions more and more secure thus making the overall banking system faster and secure.