https://ir.kdu.ac.lk/handle/345/6714 2026-04-21T16:47:51Z https://ir.kdu.ac.lk/handle/345/6890 Gripper-enhanced fabric cut piece sorting system based on defects Hewavitharana, DC; Wickramathunga, LTUD; Rajapaksha, TNN; Pallemulla, PSH; Piyumini, HDI Sri Lanka’s garment industry is crucial, contributing significantly to the country’s export market. However, current fabric handling methods in Sri Lankan companies are primarily reliant on manual labour, creating a compelling potential for research and development in the field of automated fabric handling. Fabrics present distinct challenges due to their dynamic and static character, needing novel solutions to overcome these limitations. Furthermore, human fabric problem detection achieves just 60% accuracy, emphasizing the importance of automation in this vital sector. Significant benefits can be obtained by automating these processes in textile manufacturers. The fundamental goal of this project is to design and build an innovative system capable of automatically separating and classifying cloth cut pieces based on the presence of defects. Our suggested device includes a cylindrical manipulator outfitted with cutting-edge pinch-like grippers designed exclusively for effective ply separation. To improve defect detection accuracy, we use a custom-trained Convolutional Neural Network (CNN) with a validation accuracy of 80%. We have also created a simple platform for remote control and real-time monitoring of the entire system by using IoT technology. This complete project not only meets the critical demand for fabric handling automation, but it also has the potential to change the garment manufacturing process in Sri Lanka. 2023-09-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/6889 Water treatment efficiency of aerator and roughing filter in treating groundwater : A case study in mullaitivu of Sri Lanka Sutharsan, ME; Anoja, N The paper describes an investigation into the efficiency of the water treatment process used in the Mullaitivu well field in Sri Lanka. The well field experiences significant groundwater extraction, approximately 1,440,000 liters per day, due to developments and resettlements in the area over the past decade. However, the groundwater quality does not meet the standards set in SLS 614: 2013 on a few occasions. The treatment process includes a fountain-type aerator with four drops with varying heights and vertical-flow roughing filters. The water then passes through four medial filter layers in the roughing filters, each with different particle size and layer thickness. To assess the effectiveness of the treatment process, water samples were collected at regular intervals of 6 hours during 72 hours of continuous operation. The samples were taken before and after aeration and after passing through the roughing filters. The selected water quality parameters tested in the study were turbidity, color, total iron, and manganese. The results showed that the treatment process significantly removed color and total iron from the raw water with removal efficiencies of 84% and 88% respectively. Additionally, the treated water’s turbidity was well below the threshold limit of 2 NTU in 100% of the treated samples, the treated manganese level was below the limit of 0.1 mg/l, and the treated total iron level was below the limit of 0.3 mg/l specified in SLS 614:2013 for drinking water. Based on the findings, the paper recommends including pre-chlorination in the treatment process to enhance oxidation and increase the total iron and manganese removal efficiency. 2023-09-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/6888 Thermography and thermal sensors as a breast cancer early diagnostic technique: A review Perera, MKPSSA; Karunaratne, MPA; Wijesinghe, WPLK; Perera, NMA Breast cancer is a widespread and devastating disease with significant global morbidity and mortality. Early detection plays a crucial role in improving outcomes and survival rates. However, current breast cancer screening methods, such as mammography, ultra sound, and magnetic resonance imaging, have limitations, including false-positive and false-negative results, high costs and radiation exposure. This literature review examines the potential of thermography and thermal sensors as a non-invasive and radiation-free screening technique for breast cancer detection. Increased metabolic activity around tumor cells leads to temperature asymmetry and alterations in blood flow, which can be detected through thermographic techniques. Research studies have shown promising results, demonstrating high sensitivity and specificity in detecting breast cancer using thermography. Recent developments in breast cancer screening involve the use of surface thermal sensors, such as flexible antennas integrated into wearable bras and thermal sensor arrays. While these advancements show potential, they require further validation and improvements. Thermography and thermal sensors hold promise as a non-invasive, radiation-free, and potentially cost-effective screening method for breast cancer detec tion and technological advancements are necessary to overcome current limitations to establish its efficacy as a standalone or complementary screening tool. 2023-09-01T00:00:00Z https://ir.kdu.ac.lk/handle/345/6887 Software defined radio based drone detection using machine learning algorithm Bandaranayake, WMH; Gunathilaka, HHC In this new era, misuse of drones and harmful acts that can be done using drones make it hard to detect and classify drones effectively due to the larger bandwidth and real-time processing. The purpose of this research is to find a better machine-learning algorithm to detect and classify the emitting signals from a drone or a remote controller. We built multiple classification models and trained them over the dataset we obtained using Software Defined Radio (SDR) and drone remote controller. We have compared the performances of all these models and logged their results in terms of prediction accuracies. Based on the accuracy results, K-Nearest Neighbor classifier has given the highest accuracy among all other models. 2023-09-01T00:00:00Z