This research pioneers the application of a diverse set of advanced machine learning and optimization methods, to predict the erodibility of lateritic soil treated with cement and nanostructured quarry fines, providing a groundbreaking, data-driven approach that enhances traditional erosion analysis techniques. Traditional experimental methods for erosion analysis are often complex and resource-intensive; therefore, this research focuses on developing predictive models using Python. To build the machine learning and optimization models, 121 data points were collected from existing literature. The dataset includes erodibility measurements of unsaturated lateritic soil treated with local cemen... More >

Pilgrimage tourism in India is a cultural and deeply spiritual journey, especially for elderly individuals who view it as a cherished life milestone. However, their mobility and accessibility needs are often under-addressed in policy and planning. This study examines inclusive mobility challenges faced by elderly pilgrims in Haridwar through qualitative and quantitative data from 225 participants, including interviews, group discussions, and field observations. Findings reveal physical, sensory, and cognitive barriers that restrict freedom, dignity, and spiritual fulfilment. Existing infrastructure and services, such as signage and pathways, are frequently inadequate. The research highlights... More >

There has been recorded differences between a train spulled by a locomotive and a train unit with all the bogies moving simultaneously. This study aims at the slip of wheel on a railway track under these different movements using finite element simulation on a ballasted railway track. The railway track was subjected to a loaded wheel moving at different speeds using two modes: translation-controlled (wagons pulled by locomotive) and rotation-controlled (simultaneously moving bogies) motion. The results were obtained in the form of track vibrations and wheel slip under moving loads at changing speeds and wheel-rail friction. It was concluded that the force transferred to the substructure does... More >

In this research paper, advanced artificial intelligence (AI) techniques have been applied in predicting the mechanical properties of black cotton soil (BCS) treated by the method of partial displacement of the soil. The materials of the displacement operation were fly ash (FA) and quarry dust (QD), which are both solid wastes derived from coal combustion in power plants and quarrying of stones for the production of aggregates. Previous activities show that BCS has never been treated by displacement of the soil sample but by the addition of these cementitious materials as wt % of the dry soil. The advanced AI techniques were the ANN, GP and the EPR, which executed forty data entries collecte... More >