NUST Institutions Library Catalogue Search for 'an:"125951"'

Railway Track Fault Detection using AI /

By Haroon ,Muhammad . . 72p. ; , Railway infrastructure is critical for the safe and efficient transportation of goods and people. However, defects in rail tracks can lead to severe accidents, resulting in significant human and financial losses. This thesis presents the development of an end-to-end railway track defect detection system utilizing advanced deep learning techniques. The proposed system is designed to detect various defects, including rail surface anomalies and component defects such as missing fasteners, bolts, and fishplates. The approach combines a supervised YOLOv8x Segment Model and a self-supervised U-Net model. The YOLOv8x-segment model, trained on a curated dataset, achieved a mean Average Precision (mAP) of 94% and demonstrated its capability for real-time detection with high frames per second of 30 FPS. To overcome the issue of scarcity of labeled rail surface defects dataset, the U-Net model was pre-trained on normal rail images and fine-tuned using a subset of Rail Surface Defect Dataset (RSDDs), resulting in significant improvements in defect segmentation accuracy. The system demonstrated strong performance across various metrics and datasets, providing a reliable tool for enhancing railway safety through automated defect detection. Future work includes expanding detection capabilities to include sleepers and ballast and real-time implementation with live video feeds. 30cm..

Place Hold on Railway Track Fault Detection using AI /

Virtual Reality Headset based Control and Navigation of Drone /

By Mehran Javed ,Muhammad . . 77p. ; 30cm..

Place Hold on Virtual Reality Headset based Control and Navigation of Drone /

Bidirectional Language Agnostic Framework for Sign Language Production and Recognition /

By Ahmed ,Mateen . . 69p. ; 30cm..

Place Hold on Bidirectional Language Agnostic Framework for Sign Language Production and Recognition /

Thermo-Economic Evaluation of an Organic Rankine Cycle powered Vapor Compression chiller for cooling air conditioning of SMME. /

By Talha, Muhammad . . 97P. , The worldwide need for energy as well as environmental challenges have promoted the creation of sustainable power solutions. Various working fluid combinations are utilized for an Organic Rankine Cycle powered Vapor Compression Cycle (ORC-VCC) to deliver cooling applications. The selection of an appropriate working fluid significantly impacts system performance, efficiency, and environmental impact. In this study we evaluates possible working fluids to optimize the ORC-VCC system. Firstly, the Artificial Neural Network (ANN) derived models for exergy destruction (𝐸𝑑𝑡𝑜𝑡), and the heat exchanger total heat transfer capacity (𝑈𝐴𝑡𝑜𝑡). Later on, the multi-objective optimization was conducted using the acquired models for 𝐸𝑑𝑡𝑜𝑡 and 𝑈𝐴𝑡𝑜𝑡 using the Genetic Algorithm (GA) followed by Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).The optimization result showcase Decane ORC- R600a VCC as the optimal choice for ORC-VCC system, resulting in values of 𝐸𝑑𝑡𝑜𝑡 and 𝑈𝐴𝑡𝑜𝑡 resulting in value of 24.50 kW and 6.71 kW/K, respectively. From the extended analysis and optimization, the cooling capacity was found to be 41.8 kW. Meanwhile, the total cost per unit was estimated to be approximately $78710 and the payback period is 9.7 years. The research data shows how viable it is to implement biogas-driven ORC-VCC systems when providing air conditioning capabilities. 30CM.

Place Hold on Thermo-Economic Evaluation of an Organic Rankine Cycle powered Vapor Compression chiller for cooling air conditioning of SMME. /

Experimental Research on solar still technology, a promising solution for water purification in developing countries /

By Malik, Nawaf Mehmood . . 86p. , Water scarcity is a major problem, which the world is facing at the present moment. Most of the earth’s water is saline, comprising about 97 %. Solar still is a very economical and easy method for water desalination. This experimental research was conducted to enhance the output of square pyramid type solar still incorporating PCM (paraffin wax) and Fresnel lenses concentrating sunlight on bricks placed in basin area. Effect of hot water circulation in PCM was also observed on solar still distillate output enhancement. Experiments were conducted at different water depth levels (i.e., 1, 2, 3 and 4 cm) in Islamabad, Pakistan. Nocturnal output was observed to increase by using Fresnel lenses. Solar still output was observed to increase from 1 cm to 3cm in nocturnal hours and then started to decrease. When Fresnel lens was used, maximum distillate output in autumn and spring season was 0.9 L and 1.68 L at 1 cm water depth. Maximum distillate in simple experimental cases (without Fresnel lens utilization) was also at 1cm water depth. In autumn season it was 0.85 L and in spring 1.55 L. Circulation of hot water in PCM chamber increased both daytime and nocturnal output of solar still significantly 30cm.

Place Hold on Experimental Research on solar still technology, a promising solution for water purification in developing countries /