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Intelligent transport systems must be developed due to the rising use of vehicles, particularly cars. In the field of computer vision, the identification of a vehicle's license plate (LP) has been crucial. Various methods and algorithms have been used for the detection process. It becomes challenging to find similar images, nevertheless, because the features of these plates change depending on the characters' color, font, and language. The research proposes a robust deep-learning framework based on feature extraction using convolutional neural networks and localization using an improved approach integrating bilateral filtering and Canny edge detection. Further, a CNN architecture is used to extract features from images and classify the presence of license plates in unseen vehicles. If present, the stage is followed by recognition of numbers written on the plates. An extensive experimental investigation is performed on Stanford Cars, Car Licence Plate Detection dataset, and Indian Licence Plates Dataset. The attained simulation outcome ensures a superior performance over existing techniques in a significant way. [ABSTRACT FROM AUTHOR]

Rapid industrialization and technological advancement have increased the release of toxic effluents into the water thus decreasing clean water sources day by day. Engineered materials and membrane filtration techniques have emerged as a reliable solution for wastewater treatment. Carbon-based nanomaterials are playing a major role due to their effective adsorbing capacity led by high surface area and porosity. Carbon nanotubes, Graphene and Graphene oxide and natural carbon-based materials were reviewed for the treatment of wastewater. The focused nanomaterials proved the future materials for wastewater treatment in terms of sustainability, availability, high surface area, catalytic activity, environment-friendly, ease of modification, non-toxicity, exceptional structural feature, adsorption selectivity with high strength and many more proves its novelty in the domain of wastewater treatment. This piece of work is a step towards the recent development in greener and sustainable carbon-based nanomaterials with the prospects of technologies that gives enhanced efficiency thus enabling large-scale production for wastewater treatment. [ABSTRACT FROM AUTHOR]

Plants are considered excellent resources for the generation of greener biomaterials. Plant extract are renewable in nature. Various metabolites present in plant extract are normally used in redox reaction for the formation of eco-friendly nano-particles. It is also considered as the main factory for the green synthesis of metal nano-particles. The plant-based nano-particles is very necessary for absolute harmony connection between plant science and nanotechnology. Ashwagandha is the non-toxic herb which used to treat a range of conditions and its life changing benefits runs over a long time. Its numerous medicinal values make this plant so popular. It is a stress buster which works for all "SUPERHERB". This super herb rejuvenates our body and brain from the inside out. Present review depicts the variety of assistance of Ashwagandha plant with or without nanoparticles, from the past to the present time of corona. [ABSTRACT FROM AUTHOR]

Brief Background There are differences in the understanding and knowledge about HIV/hepatitis in healthcare professionals and the primary aim of the current survey is to evaluate about the knowledge on Hepatitis B, Hepatitis C, and HIV among dental professionals and paramedical staffs and correlate the level of awareness to the attitude they behold toward the disease. Materials and Methods Asymptomatic patients aged between 18-40 years who can understand and are willing to follow all study procedures are included in the study and a structured questionnaire was administered through convenience sampling to dental professionals, paramedical staffs and dental students of all departments in Swami devi Dayal dental college and hospital, Panchkula. The results of questionnaires were calculated and analyzed via the software SPSS version 26.0. Results Results of the current study revealed that dental professionals, paramedical staffs and dental students of all departments in Swami Devi Dayal dental college and hospital, Panchkula had showed positive response towards the questionnaire survey conducted to know the rate of awareness of hepatitis B, hepatitis C, and HIV diseases. Summary and Conclusions A solid education and awareness of the preventative measures used in response to a needle stick injury can help healthcare personnel avoid many bloodborne diseases by preventing needle sticks. Therefore, it is essential that medical workers are informed of Hepatitis B, C, and HIV in order to prevent potentially fatal situations. [ABSTRACT FROM AUTHOR]

Audio classification in smart devices is complex in comparison to image or text classification and recognition as it requires to clean the audio or pre‐process it before extracting its features and thus the accuracy heavily depends upon the pre‐processing of the audio. In this paper, we have used an envelope function having a specific threshold that removes the useless part of the audio which cannot be used to differentiate one audio from another by the smart device. Further, pre‐processed sounds from different musical instruments are subjected to feature extraction and classification using deep convolutional neural networks and Recurrent Neural Networks. It is observed that our proposed approach is suitable for audio classification for smart devices, with results at par with state‐of‐the‐art techniques. [ABSTRACT FROM AUTHOR]