The research and innovations in the field of wearable auxiliary devices for visually impaired and blind people are playing a vital role towards improving their quality of life. However, in spite of the promising research outcomes, the existing wearable aids has several weaknesses such as more weight, limitations in the number of features and cost. The main objective of this manuscript is to provide the detailed design of a novel lightweight wearable aid with higher number of features for visually impaired and blind people. The proposed research aims to design a cognitive assistant that will guide the blind people for walking by detecting the environment around them. The framework include a Multi-Sensor Fused Navigation system comprises of a sensor-based, vision-based, and cognitive (intelligent/smart) application. The visual features for the design include obstacle detection, uneven surface detection, slope and downward steps detection, pothole detection and hallow object detection; location tracking, walking guide, image capturing and video recording. This prototype is named as Blind’s Apron based on its appearance. The invention focusses on parameters like reduction on size (quite handy) and light weight (comfortable to wear), higher number of detection features, and minimum user intervention (high end operations like switching on and off). All user interactions are friendly and affordable to everyone. The results obtained in this research lead to a high end technical intervention with ease of use. Finally, the performance of the proposed cognitive assistant is tested with a user study in real-time. The feedback and corresponding results establish the effective outcome of the proposed invention which is a light weight and feature enhanced device with easily understandable instructions.

This study focuses on the physicochemical and tribological properties of bio-lubricants and commercial lubricant blends dispersed with graphene nanoplatelets. In the processing of the bio lubricant, special care was taken to ensure that the physicochemical properties do not deteriorate too much when the bio lubricant is blended with commercial oil. Calophyllum inophyllum (Tamanu tree) seed oil was used to prepare a penta-erythritol (PE) ester. The PE ester was mixed with commercial SN motor oil at 10, 20, 30 & 40% v/v concentrations. The oil samples are tested on a four-ball wear tester to see how well they perform under wear, friction, and extreme pressure conditions. The optimum blend of PE ester – commercial SN motor oil for the best performance is found in the first phase. Later the optimum blend of commercial oil and bio-lubricant is dispersed with graphene nanoplatelets in 0.025%, 0.05%, 0.1%, 0.25%, 0.5% and 1% weight fractions. A blend ratio of 30% bio-lubricant in commercial oil dispersed with 0.05% graphene nanoplatelets dramatically reduces friction and wear. During the extreme pressure test, commercial oil, and bio-lubricant blends performed better in load-carrying capacity and welding force, indicating an improved load-wear index. These improved properties due to the dispersion of graphene nanoplatelets could facilitate the use of a higher blend percentage of bio lubricant. Analysis of the worn surfaces after the EP test showed that bio lubricant, additives, and graphene worked together in the blend of bio lubricant and commercial oil.

We present a highly effective algorithm for image dehazing that leverages the valuable information within the hazy image to guide the haze removal process. Our proposed algorithm begins by employing a neural network that has been trained to establish a mapping between hazy images and their corresponding clear versions. This network learns to identify the shared structural elements and patterns between hazy and clear images through the training process. To enhance the utilization of guidance information from the generated reference image, we introduce a progressive feature fusion module that combines the features extracted from the hazy image and the reference image. Our proposed algorithm is an effective solution for image dehazing, as it capitalizes on the guidance information in the hazy appearance. By combining the strengths of deep learning, progressive feature fusion, and end-to-end training, we achieve impressive results in restoring clear images from hazy counterparts. The practical applicability of our algorithm is further validated by its success on benchmark data sets and real-world SEM and TEM images.

Conventional Steel Cylinders used for LPG cylinder for domestic applications are not manufactured in a single joint but are welded. While composite cylinders are manufactured in a single joint, Composite components cannot be welded like the steel cylinder. Composite Cylinders are winded using Filament Winding technique. Compared to Steel Cylinders, Composite Cylinders are costlier. As composite cylinders are safer than steel cylinder, composite Cylinders due to a rubber lining inside, they are 100% leak proof. If mass production of composite cylinders are done then the cost may get reduced. This paper summarizes the design and analysis of the manufacturing of Liquid petroleum gas (LPG) Cylinder using Glass Fibre Reinforced Plastic (GFRP) material. The stresses along all the directions of the ply sequence are also calculated using Classical Lamination Theory (CLT). The fibre stresses along all the directional angles were found to be under the required stress limits. The Metallic boss Calculation & angle variation at dome is the key parameter and is carried out and determined the tip radius. Â