Electrical Electronics and ICT Faculty
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Item Energy Efficiency Optimization Techniques For 5g Ultra Dense Wireless Networks Using Massive Mimo(2026) Zinabu NegashWith the fast development of wireless communication systems, lowering energy utilization in these systems has resulted in an essential requirement for network operators. In the context of 5G wireless networks, the concept of energy efficiency (EE) has been recognized as an important performance measure. Optimizing the network design will result in considerable savings in terms of total power consumption, especially with the incorporation of massive MIMO (multiple input multiple output) technology.Item Design Double Layer Aerial With Lens For Millimeter Wave Image Detection Systems(2026) Ehtinat AmisaluThere has been significant interest in millimeter-wave systems used in detection of concealed images. security, medical and industrial fields because of their ability to detect concealed items with. minimal penetration loss. Current antenna designs, i.e. single-layer patch antennas. Slot designs, and APSAs have low gain, small bandwidth, low directivity, and are generally low gain. restrained detection range, and hence less image resolution and fidelity. To overcome these challenges, this work is a patch antenna of circular form on the double-layer with an inbuilt lens, optimized at 24.411 GHz - the best millimeter-wave radio frequency to use in imaging. The High Frequency Structure Simulator (HFSS) was used to develop and simulate design. utilizing multi-layer layouts and lenses in order to increase radiation effectiveness and beam. focusing. Performance tests were taken to be of importance with regard to gain, directivity, and reflection. coefficient (S11), voltage standing wave ratio (VSWR) and bandwidth which were subsequently correlated.Item Performance Comparison of Temperature Profile Control of Clay Kiln for Ethiopian Pottery Industry(2026) Nahome NigussiePottery production plays an important cultural and economic role in Ethiopia; however, traditional clay kilns are commonly operated using manual temperature control methods that lead to inconsistent firing conditions, poor product quality, and high energy consumption. Maintaining an accurate temperature profile during the firing process is critical for achieving proper clay vitrification, minimizing defects, and improving overall production efficiency. This study focuses on the modeling, design, and performance comparison of temperature profile control strategies for an electric clay kiln used in the Ethiopian pottery industry. A dynamic mathematical model of the electric clay kiln was developed based on energy balance principles, incorporating heat transfer through conduction, convection, and radiation, as well as thermal inertia and time delay effects. Using this model, three control strategies Proportional Integral Derivative (PID), Fuzzy Logic Control (FLC), and Model Predictive Control (MPC) were designed and implemented in MATLAB/Simulink.Item Developing An Ai Integration Framework In Tvet Curriculum: The Case Of Aatpc(2026) Zerihun Basazin YehualaAI is increasingly transforming the education sector by enhancing personalized learning, automating, administrative task in teaching and learning process. However, the use of AI in TVET in Ethiopia is still in its initial stage with low infrastructure, low digital literacy among teachers and lack of a structured implementation strategy. This research attempts to fill these gaps by developing a contextualized framework for integration of AI into TVET curriculum using the case study of AATPC. The research use a mixed-methods research design. Focus groups and interviews were used to gather data from TVET instructors, administrators, curriculum developer. We also collected using questionnaire from students and instructors. Thematic analysis and descriptive statistics were used to analyze the data. The data was analyzed using thematic analysis and descriptive statistics. A total of 72 questionnaires were distributed. Out of these 69 were returned while 3 were not returned. Among the returned questionnaires 2 were excluded due to incomplete or invalid responses. Therefore, 67 valid questionnaires (93%) were considered valid for analysis. Validity and reliability tests were conducted to assess coverage of the topic, with a Cronbach’s alpha coefficient of 0.988.Item Design and Performance Enhancement of Massive MIMO PIFA Arrays for 5G Wireless Communication Systems(2026) Mesfin BerhanuThe rapid deployment of fifth-generation (5G) wireless communication systems has increased the demand for small-size, high-gain, and high-directivity antennas that can operate efficiently at millimeter wave frequencies. This thesis presents the design, simulation, and performance of single and massive MIMO Planar Inverted-F Antenna (PIFA) configurations with a resonant frequency of 28 GHz by using High Frequency Structural Simulator (ANSYS HFSS) software. Starting from a single PIFA element, the work systematically explores 1x2, 4x4, and 4x5 PIFA MIMO arrays in order to quantify the effect of array scaling on impedance matching, bandwidth, gain, directivity, and radiation behavior.Item Classification Of Goat And Sheep Skin Diseases Using Deep Learning Approaches(2026) Hiluf Nuguse GideyAnimal farm has played one of critical roles in the socio economic wellbeing of most developing countries, Ethiopia being one of them as sheep and goats play major role in providing food security, generate incomes and export income. Nevertheless, there are a number of skin diseases, which have a severe impact on the quality, and yields of animal products. In the rural set ups, they are not handled well because of the inaccessibility of veterinary clinics and shortage of expertise in the field. In this paper, an enhanced method of deep learning approach provided to identify and classify skin diseases in sheep and goats with deep learning. The system automation CNN architectures mean that features are automatically trained by skin images by which skin diseases can be classified and classified to either bacteria and virus, parasite or healthy. The evaluated and tested model underwent testing and evaluation on the standard measures, which include accuracy, precision, recall and F1-score. The data employed in this thesis is 2341 images of data. The training dataset classified as 80% (1873 images), 10% (234 images) and 10% (234 images) in training, validation and test performance respectively.Item Optimal ANFIS Based Automatic Generation Control for Steam Power Plant(2026) G/hiwet G/mariam G/slassieThe growing complexity, nonlinear characteristics, and continuous load variations in modern power systems require advanced control techniques to ensure reliable operation and maintain frequency stability. Automatic Generation Control (AGC) plays a crucial role in balancing power generation with load demand and in maintaining system frequency within acceptable limits. Although conventional controllers such as PID and FLC have been widely used in AGC applications, their performance often decreases under nonlinear operating conditions and load disturbances. This can result in higher overshoot, longer settling time, and reduced robustness. This thesis proposes an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based AGC scheme for a steam power plant. The proposed approach integrates the learning capability of neural networks with the reasoning ability of fuzzy logic for effectively handle system nonlinearities and uncertainties. A detailed mathematical model of single-area steam power plant, including the governor, turbine, and generator-load dynamics, is developed and implemented in the MATLAB/Simulink. The performance of the proposed controller evaluated under both steady-state conditions and different load disturbance scenarios, including load addition and load rejection. The results compared with those obtained PID and FLC controllers.Item Design and Performance Optimization of Titanium Dioxide Coated Nanostructured Optical Fibers for 5G Wireless Communication Systems(2026) Birhanu GetinetThe 5G wireless communication systems demands optical fibers that can carry large amounts of data with low delay and stable performance, however, conventional optical fibers have limitations in their materials and structural design. Therefore, improving the performance of optical fibers has become an important area of research. This study examines the use of titanium dioxide (TiO₂)-coated nanostructured optical fibers to enhance fiber performance for 5G applications. Titanium dioxide was used for its high refractive index, good chemical stability and low optical loss. The coating was applied to photonic crystal fibers and tapered nanostructured fibers to improve light confinement, reduce signal loss and control dispersion. The behavior of the proposed fiber structures is analyzed through numerical simulations based on the Finite Element Method (FEM) and the Beam Propagation Method (BPM), and changes in coating thickness and fiber geometry are studied to understand their effect on key parameters such as transmission efficiency, bandwidth, bit error rate (BER) and receiver sensitivity. The findings show that applying a TiO₂ coating significantly improve fiber performance through reducing optical loss by up to 30%, and improving bandwidth and signal stability. In addition, the study indicates that these fiber designs can be introduced into existing 5G network system without major modifications. The study found that TiO₂-coated nanostructured optical fibers provide a practical and effective approach for supporting future high-speed wireless communication networks.Item Predictive Analytics of Industry Skills Gaps: Using Machine Learning – In Case of Tilahun Yigzaw TVET College(2026) Azmach BerheAlthough Technical and Vocational Education and Training (TVET) have gained increasing significance, many graduates remain unable to secure employment due to a persistent mismatch between the skills they acquire and the requirements of the labor market. This issue continues to contribute to high levels of unemployment among trainees. Within this context, this study attempts to analyze Tilahun Yigzaw TVET College in Tigray, Ethiopia. The research concludes that predictive analytics have the potential to enhance data-driven decision-making in TVET institutions by identifying critical factors influencing the skills gap and facilitating the alignment of training programs with industry demands.Item Design and Applications Of Massive Mimo Antenna With Metasurface For 5g Wireless Communications System(2026) Abinet OcheThe increasing demands for network expansion require Multiple-Input Multiple-Output (MIMO) technology which needs Multiple-Input Multiple-Output (MIMO) technology that can deploy extensive antenna systems. The study investigated the complete characteristics of a large MIMO antenna together with its adaptable Meta surface which supports innovative 5G wireless communication technology. The proposed design uses Meta materials to achieve electromagnetic control which solves three major problems such as mutual coupling, bandwidth constraints, and ineffective beam formation that affect standard MIMO systems. A trapezoidal patch antenna array was developed and optimized to function in the sub-6 GHz frequency range specifically at 3.5 GHz which serves as a vital 5G access network frequency. The Meta surface augmented design achieves significant performance improvements over traditional patch arrays in three key areas design delivers notable gains in isolation, directivity, and gain, which full wave simulations demonstrate through comprehensive testing.