https://www.um.edu.mt/library/oar/handle/123456789/106376 Fri, 17 Jul 2026 14:49:52 GMT 2026-07-17T14:49:52Z https://www.um.edu.mt/library/oar/handle/123456789/129311 Title: A pilot study in energy harvesting to surrogate the power source for pacemakers Abstract: The natural pacemaker of the heart is located in a small region named the sinoatrial node. The electrical stimulus generated in the SA (Sinoatrial) node passes in sequence through different anatomical locations in the cardiac conduction system and causes the heart to beat. As a result of heart disease, the normal electrical conduction pathway can get interrupted subsequently leading to the heart beating in a pathological rhythm known as an arrythmia. There is no arguing that implantable cardiac pacemakers have drastically improved the quality of life of many patients suffering from arrythmias and are recognized as the gold standard when it comes to treating arrythmias. The form factor and conditions that are treated have come a long way from the very first implantable pacemaker manufactured in 1958. That being said, the long term operation of such devices remains an obstacle due to their limited battery life which is usually limited to 7-10 years for modern pacemakers, after which the patient must undergo surgery to remove the old pacemaker box and replace it with a new one. One possible way of extending the life of pacemakers is by harvesting power from the surrounding kinetic energy within the body via the use of energy harvesting devices. One such energy harvesting device of interest for biological applications are the Triboelectric Nanogenerators, commonly abbreviated to TENG, which use the phenomena of triboelectrification between two contacting surface to generate power. In this project, various TENG devices incorporating the contact surfaces of PDMS (Polydimethylsiloxane) and silver nanoparticles were successfully fabricated using different manufacturing processes. The performance of the devices were subsequently tested under uncontrolled and controlled testing methods. Under controlled testing, the best performing TENG device had a maximum power output of 6.60µW using a bradycardic testing frequency and 17.90µW using a tachycardic testing frequency. This was achieved by using the combination of 12µg/cm2 silver nanoparticle coating and using the PDMS film that was bonded to the PDMS substrate and that had no surface modification. Comparison of the RMS power obtained from this device with a commercial pacemaker and ICD (Implantable Cardiac Defibrillators) device on the market shows that a small percentage of the power needed to power such devices was extracted from the TENG devices. Taking a state of the art pacemaker indicated for single chamber pacing of bradycardia , the extracted RMS power of the TENG accounted for 0.35% and 0.30% of pacemaker’s power requirements in 100% inhibition mode, where the pacemaker is using its energy to solely sense, and 100% pacing mode, where the pacemaker is using all its energy to solely pace, respectively. Better results were obtained for the leadless pacemakers where the extracted RMS power of the TENG accounted for 8.14% and 3.94% of the device’s power requirements in 100 % pacing mode and 100 % inhibition mode respectively. Lastly, with regard to the ICD, the extracted RMS power of the TENG accounted for 1.221% and 1.079% of the ICD power requirements on 100% inhibition and 100% pacing mode respectively. Description: M.Sc.(Melit.) Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/129311 2023-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/129309 Title: Underground cycle lanes system : services design Abstract: In this dissertation, a methodology was developed to design a ventilation system for an underground tunnel to be used a cycle path. Temperature and humidity were calculated along the tunnel, considering the sensible and latent loads due to the cyclist metabolism, sensible loads due to the lighting equipment and water infiltration from the tunnel wall surface. Different ventilation layouts were used to calculate the energy consumption required to have good air quality along the tunnel. Operational cost for such ventilation layouts were calculated and a life cycle cost analysis for each layout was performed to select the most feasible layout with the highest net present value. It was concluded that the ventilation layout in a tunnel mainly depended on the outdoor environment and water infiltration. The use of different layouts operating seasonally resulted in the lowest yearly operational cost of €90,580.30 and lowest net present value after the lifetime of the ventilation system. An economic analysis including the cost for construction of the 2km tunnel, equipment costs, maintenance costs, external costs(benefits) and other expenses, with an initial capital cost €4,330,000, payback period would be just after 9 years. Therefore, such tunnels used as a cycle path would be a feasible solution in Malta. Carbon dioxide emissions would be reduced by more than 75%. Description: M.Sc.(Melit.) Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/129309 2023-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/129308 Title: A review and analysis of HVAC technologies in data centre configurations in Malta Abstract: Data centres are industrialised computing infrastructures which accommodate the requirements of servers that are responsible for data storage and data communication. These data centres are coupled with mechanical cooling which allows these servers to operate for twenty-four hours per day, seven days per week all year round. These cooling technologies have a large impact on the overall energy performance of these data centres. Furthermore, the cooling technologies present within data centres are responsible for ensuring that the data centre is operating at the optimum conditions. Any deviations from the operating conditions may be detrimental and may lead to system failure and consequent downtime. This can be detrimental for some businesses. In this dissertation, a study on the effects of data centre cooling technologies and the operating parameters has been carried out on three data centres in Malta. Temperature and humidity logging was carried out to analyse the data centres operating conditions in conjunction with the cooling system present within the data centre. Furthermore, an energy performance metric was then used to be able to compare energy performance efficiencies of these data centres. A comparative analysis of the cooling technologies and operating conditions was then related to the energy efficiency of the data centre and recommendations were done with the aim of potential improvements on the overall energy consumption. The results obtained reveal that the use of CRAC cooling in Malta is predominant and the most energy efficient data centre considered in this study made use of segregated cold and hot aisle cooling. Works carried out reveal the importance of the cooling strategy employed on the overall data centre efficiency. Additional investigation would be required to study the effects of the cooling strategy which varies with different ambient temperatures. Description: M.Sc.(Melit.) Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/129308 2023-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/124147 Title: Classification of neural disorders from fMRI data using machine learning Abstract: Attention Deficit/Hyperactivity Disorder (ADHD) is a neural disorder prevalent in 5-8% of children worldwide. The traditional procedure followed to diagnose children with this disorder is tedious and lacks homogeneity and objectivity. Based on the hypothesis that children with ADHD may have neuroanatomical and cognitive differences from neurotypical children, this study aimed at taking advantage of these differences to identify functional connectivity patterns unique to children with ADHD. Functional Magnetic Resonance Imaging (fMRI) is a neuroimaging technique used to analyse functional connectivity by obtaining brain scans over a period of time during which a subject must complete a simple task. An fMRI dataset was sourced, visualized and pre-processed. Three Machine Learning (ML) models were developed and trained on a subset of the pre-processed fMRI dataset. Their performance was then evaluated on an unseen testing set, to evaluate whether the models succeeded in accurately classifying children with ADHD and controls. The techniques used during the development included Principal-Component Analysis (PCA), grid searches and cross-validation. Three ML models were developed: Support Vector Machines (SVM), a Multi-Layer Perceptron (MLP) and a Long Short-Term Memory (LSTM) network. The results indicated that the models learned well and were able to generalize. When evaluated on unseen data, the model accuracies range between 60-70%. These results are in line with other studies reviewed in literature, and indicate acceptable performance from ML models trained on small datasets. Further developments can be made on this study to improve the results. These include testing on a larger dataset, looking into different parcellation atlases, and attempting alternative ML techniques such as transfer learning. Description: B.Eng. (Hons)(Melit.) Sun, 01 Jan 2023 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/124147 2023-01-01T00:00:00Z