Τμήμα Ηλεκτρολ. Μηχαν. και Τεχνολ. Υπολογιστών (ΜΔΕ)
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- ItemOpen AccessSmart grid management on distributed generation systems with RES and storage units(2023-03-01)The rapid integration of renewables into the daily production schedule has greatly increased the complexity of today’s contemporary power systems. These sources suffer significantly from variability in terms of production due to their large dependance on ambient conditions. As the main purpose of a power system is to ceaselessly supply the demand, in a supervised manner, renewables are usually installed in systems in ways that facilitate cooperation between them and conventional power sources. These systems are known as microgrids and they combine distinct renewables and conventional power sources to either supply local demand or inject power to the grid. The introduction of such complex systems has also led to the need of proper control algorithms that can accommodate their performance. The general notion of a microgrid is not a novel term, but had been first introduced in the late 1950s. Nevertheless, the conventional control systems that have been developed, mainly dismiss dynamic response and unfortunately these assumptions may lead to a system failure due to unaccounted parameters. In this frame, researchers mainly focused on model-based analysis and development of model-based control algorithms, that regulate these contemporary power systems dynamically, while only making mild assumptions that do not significantly restrict the operation bounds of the final system. Furthermore, the results of the control design are also exploited to appropriately select system parameters that can facilitate its operation and improve the response of the applied control scheme. The proportional and integral controllers constitute the main blueprint of these controllers and have been repeatedly proven to be quite efficient when regulating power systems, but without proper analysis, they may fail to control more complex installations such as those of the microgrids. Thus, a proper stability analysis is important when applying any type of control scheme that aims to regulate specific states of a larger system. Even though PI-based control schemes are usually able to achieve the control design goals, they unfortunately suffer from lack of adaptation and when they are applied in more complex systems, where strict transfer functions cannot be derived, it is almost impossible to control parameters such as overshoots, oscillations or even settling time. Solution to this problem is provided with the introduction of Artificial intelligence. More specifically, intelligent controllers such as neuro-fuzzy techniques and Neural Networks are able to adapt their output in a way that minimizes specific cost functions. Unfortunately, though, they lack vital stability foundations and that’s the main reason why researchers have not yet introduced effective AI-based control schemes. In this frame, main purpose of this thesis is to design, control and implement a novel microgrid that combines distinct renewable power sources that are regulated by an elaborate energy storage system. The microgrid consists a Permanent Magnet Synchronous Generator-based wind-turbine and a PV panel farm. The microgrid operates in two unique modes known as grid-following and grid-forming. In the former, the microgrid control design goal is to inject set amounts of active power to the grid, while the power sources are regulated to operate in maximum power point mode. In grid forming mode, the microgrid’s sole purpose is to supply local loads under nominal voltage and frequency conditions, whereas the power sources proportionally share the load power through a novel droop technique. Details on the modeling and design of the interface of the power system that provides the ability to control and interconnect the renewable power sources are also provided. Furthermore, based on the equivalent average model, a rigorous control system is developed that is based on the highly-efficient cascaded-PI scheme and relies on the time separation principle. Finally, to prove the efficiency of AI-based controllers, suitable Neural Networks were properly trained, under various circumstances, to improve the transient response of the conventional control technique. Hence, simulation results pertaining the response of the microgrid that took place on Matlab’s Simulink virtual environment, are provided for both the cascaded-PI scheme-based system and the Neural network one, to facilitate their comparison, where it is found that the later significantly, improves the system transient response and therefore the potential of AI-control algorithms on power system applications is established.
- ItemOpen AccessCurrent insight into kidney fibrosis and the role of EGFR as a potential therapeutic target(2023-02-17)The epidermal growth factor receptor (EGFR) is a member of the ErbB/HER family of receptors and its expression can be detected in almost every tissue of the human body. EGFR is a receptor tyrosine kinase with 11 known ligands. Over the years, researchers have conducted numerous experiments to determine the structure and the receptor’s potential implications in human physiology and pathophysiology. Renal fibrosis is the final common manifestation of a wide variety of chronic kidney diseases such as diabetic and obstructive nephropathy. Chronic kidney disease carries significant impact for the patients’ lives and its management poses a challenge for the physicians and the healthcare systems globally, especially due to its high prevalence. Τhis thesis presents a description of the normal ECM, the fibrotic process and its major mediators. Hereupon and based on the current literature, researchers argue that sustained or dysregulated activation of EGFR leads to renal fibrosis via the following mechanisms: a) activation and increased expression of TGF-β1, b) arrest of epithelial cells in the G2/M phase of cell cycle, and c) excessive production of cytokines and chemokines. Furthermore, the role of two EGFR ligands, amphiregulin and heparin-binding EGF, in the fibrotic process is explained. EGFR could be used as a therapeutic target for the treatment of chronic kidney disease. Nevertheless, extensive research has yet to be conducted to elucidate the exact molecular pathways implicated in EGFR activation. The aim of the thesis is to lay emphasis on the structural and functional complexity of the kidney and to explain the most prominent information about EGFR along with its role in chronic kidney disease. It also aims to highlight the absence of clinical trials that test specific anti EGFR agents as potential therapeutic agents for renal fibrosis. The interdisciplinary approach that was followed is essential for every scientist who wishes to dive into research and address elaborate clinical challenges.
- ItemOpen AccessPhysical breast phantoms for X-ray imaging employing 3D printing techniques(2023)Cancer is one of the most severe diseases, and many studies have been conducted to investigate possible treatments for it. Cancer is characterized by abnormal cell growth and the ability to invade tissues and distant organs. Breast cancer is the leading cause of cancer death in women worldwide and the risk factors may vary according to several conditions. Menarche and the menstrual cycle, childbearing, menopause, diet, and exercise are some of these factors. The female breast is composed of adipose, glandular, and soft tissues and lymph nodes which create the lymphatic route, which is the main route for breast cancer metastasis. Breast cancer has always been studied by the scientific world and combined with the constant evolution of technology, important tools have been developed in order to detect and diagnose cancerous tumors. Conventional mammography and digital breast tomosynthesis are specialized medical imaging devices that display these abnormal masses of tissue. Three-dimensional printing is another excellent example of the evolution in the biomedical field, providing several applications. Physical breast phantoms are one of them. Physical breast phantoms are physical models of the breast developed by ‘mimicking’ materials to assess the image quality of the breast. This project mainly focuses on the study of the appropriate materials, suitable for the development of physical breast phantoms for breast X-ray imaging. Six thermoplastic materials were investigated and printed by employing the fused deposition modeling technique of 3D printing and two photopolymer resins by employing the stereolithography technique of 3D printing. 3D cubes made of ABS, PLA, PLA_Pro, Nylon, CPE, PET_G, Clear, and Purple were printed for optimal breast tissue imaging based on their attenuation coefficient (μ) and phase contrast. The X-ray exposure took place at Freiburg University Hospital and have been studied back at University of Patras.
- ItemOpen AccessDevelopment of virtual reality (VR) graphical user interface for learning the human body(2023-02-10)In this thesis we created a virtual environment for the users and a graphical user interface. Based on this environment a user can see the different parts of the human body. The circulatory system, the muscles, the nervous system, and the rest of the elements that make up the human body will be able to advance the user. The users have full control over what they see. Using virtual reality (VR) the users can see the human body unfold before them. They can rotate, grab, zoom and examine the parts of the human body in detail. After the creation of the app an evaluation was performed. During this evaluation the factors that affect the presence in virtual environments were measured. Also, an SUS questionnaire was used to measure the system usability. In total, 21 participants took place in the evaluation and filled the questionnaire. They results are interested and showed that, users who had previous virtual experiences performed better in our virtual environment. Our app is placed in a good place in the system usability scale through the SUS questionnaire. After the evaluation and the results, we performed some changes in the app to make users have a better experience.
- ItemOpen AccessModeling of the pathway of multiciliated cells' differentiation(2022-11-10)Multiciliogenesis constitutes an important biological process in which progenitor cells differentiate into multiciliated cells (MCCs). These cells are located in various biological systems, performing important biological functions such as: ensuring the circulation of cerebrospinal fluid in CNS (Central Nervous System), removing extraneous pollutants from the respiratory tract, transporting gametic cells during fertilization and many others. The aim of this diploma thesis is to study multiciliogenesis at the level of protein interactions. We examine whether our designed mathematical model is capable enough of describing the behavior of the proteins we have chosen as key factors of this biological phenomenon. More specifically, our mathematical model consists of ordinary differential equations (ODEs), each one expresses the rate of change in the concentration of one of the regulatory proteins: Geminin, Lynkeas, McIdas. For the parameter estimation of the model, we use experimental data and a calculated estimator as a comparison measurement. The results of the simulations we run, show that the designed for Geminin equation verifies with great precision qualitatively and quantitatively its behavior, as it is presented on the experimental data. On the other hand, the designed system of Lynkeas/McIdas equations, while qualitatively seems to follow the behavior seen in the experimental data, failed to quantitatively describe the experimental data. In this work, we decide to examine the simplest form of this mathematical model, where in the system of Lynkeas/McIdas equations, we integrate the negative effect of McIdas to Lynkeas in the simplest form. More complex forms of equations may describe more precisely the behavior of these proteins in the biological phenomenon under study.