Mekelle University Institutional Repository
Discover scholarly works, research outputs, and institutional publications.
The Mekelle University Institutional Repository is a digital collection of scholarly and research outputs created by the university's faculty, students, and researchers. This repository provides open access to a wide range of materials, including articles, theses, dissertations, conference papers, books, and more."
By making our research available, we aim to
- Increase the visibility and impact of research conducted at Mekelle University.
- Promote knowledge sharing and collaboration within the academic community.
- Preserve and disseminate valuable scholarly works for future generations
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- A central archive for Mekelle University’s institutional abstract books from academic and research conferences.
Recent Submissions
IMPACT OF DISTRIBUTED GENERATION ON PROTECTION DEVICE IN THE CONTEXT OF DISTRIBUTION NETWORK
(Mekelle University, 2025-12-15) Selemon Mesfin Gebreyowhans
The increasing integration of distributed generation (DG) into low voltage distribution networks has introduced significant protection performance challenges. Traditional non directional over current relays, designed for unidirectional power flow, often malfunction under DG operation due to changes in faults current magnitude, direction, and source contribution. This research investigates the impact of DG on relay performance and proposes effective mitigation strategy using coordinated and graded non directional relays. A 15kv radial distribution network with a total capacity of 24 MVA was modeled and simulated in DIgSILENTPowerFactory. A 6MW inverter based DG unit (solar PV and wind hybrid) was integrated at bus 47 to analyze its impact under various fault types (L-G, L-L, L-L-L) and locations. Three simulation scenarios were evaluated.1) based case (without DG), 2) DG integrated case, 3) mitigated case (with DG and 11 coordinated non directional relays).
The performance was assessed using key metrics: fault current, relay operating time, coordination time interval (CTI), selectivity, directional behavior, and unwanted/missed trips. Results indicated that DG integration changed fault current, reversed current direction, and led to protection blinding, sympathetic tripping, islanding risk and loss of selectivity. After applying the mitigation scheme with 11 graded relays, selectivity fully recovered, and no false trips and missed trips occurred. The mitigation thus demonstrated that DG induced issues can be eliminated using only non-direction relays, provided proper coordination and setting adjustments are made. Furthermore, a practical method for current transformer (CT) ratio selection was developed to ensure adequate sensitivity without saturation under DG fault conditions.
The key contribution of this research lies in showing that reliable DG integration can be achieved through analytical coordination and relay grading, avoiding the need for expensive directional or adaptive relays. The findings are highly relevant for distribution utilities in developing regions seeking low cost and technically viable protection solutions for networks with moderate DG penetration (<=25%).
Assessing the impact of urban-rural linkage in terms of local construction material flow: the case of Mekelle and surrounding areas
(Mekelle University, 2026-02-16) Haftay Tsegay Nere
Rapid urban expansion in Mekelle is driving the extraction of manufactured sand and gravel from surrounding rural areas, leading to increased bareland. This study examined the impacts of urban–rural linkages through construction material flows between Mekelle and nearby rural communities. A mixed quantitative and qualitative research design was applied. Used both primary and secondary data collected through different methods, including questionnaires. Random and purposive sampling methods involved 80 participants. The study was conducted at seven crusher sites in Hareko and Messebo tabias, purposively selected based on post-conflict functionality, proximity to Mekelle, and rural administrative locations. Also, three sand and gravel trading centers in Mekelle were selected based on their reliance on materials sourced from the study areas. The analysis adopted a cradle-to-gate system boundary within the broader cradle-to-grave framework due to data limitations. Results showed that annual production reached 86,680 m³ of manufactured sand and gravel, of which 15% generated as byproduct. The material flow chain supported 159 rural and urban residents through wage labor and trading activities. However, socio-environmental impacts were identified, including health risks, carbon emissions (2.23 kg C02 /t), and soil degradation. Although mitigation measures were agreed upon, weak regulatory enforcement prevented their full implementation, except for water spraying, which reduced dust emissions by 70% annually (492.41kg/year) but led to raised concerns over unsustainable water extraction. The study highlights policy gaps and recommends stronger regulatory enforcement to ensure sustainable resource management, alongside future research on why environmental policy in Ethiopia has weak in implementation.
Word Sequence Prediction Model for the Tigrigna Language Using a Deep Learning Approach
(Mekelle University, 2026-01-22) Yibralem Hagos Mekonnen
This research explores the development of a word sequence prediction model for the Tigrigna language using deep learning techniques, specifically Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU). Tigrigna, primarily spoken in Eritrea and Ethiopia, faces significant challenges in natural language processing (NLP) due to the scarcity of comprehensive computational resources and annotated corpora. This study addresses the urgent need for effective NLP tools tailored to Tigrigna, focusing on the fundamental task of word sequence prediction, which underpins various applications such as machine translation and text generation. Despite the limited dataset of 10,000 sentences compiled from diverse sources, the models were evaluated for their ability to predict and generate coherent word sequences. Results indicate that while LSTM and GRU models demonstrated potential in capturing Tigrigna’s unique linguistic characteristics, they faced issues with overfitting and underfitting, particularly influenced by the choice of embeddings Word2Vec and Keras Embedding. The findings highlight the necessity for improved regularization techniques and the importance of data augmentation to enhance model generalization. This research contributes to the nascent field of Tigrigna NLP by demonstrating the applicability of deep learning models in resource-scarce languages. The outcomes suggest pathways for future advancements in Tigrigna language technology, emphasizing the potential for enhanced predictive text applications and deeper insights into Tigrigna's grammatical structures. Ultimately, this work lays a foundation for further developments in Tigrigna NLP, advocating for increased investment in linguistic resources and innovative modeling techniques to support the digital representation of the Tigrigna language.
DEVELOPMENT OF A TEXT-BASED, AMHARIC-LANGUAGE CHATBOT FOR MATERNAL HEALTH CONSULTATION USING SUPERVISED MACHINE LEARNING
(Mekelle University, 2026-01-26) BIRTUKAN NGATU
Maternal health continues to be a critical concern in Ethiopia, where language barriers and limited access to healthcare information contribute to high rates of preventable pregnancy complications. Motivated by the need to improve maternal outcomes through accessible and culturally appropriate solutions, this study introduces an Amharic-based pregnancy chatbot. The chatbot is designed to provide expecting mothers with personalized, trustworthy, and timely maternal health guidance throughout their pregnancy journey. Using natural language processing (NLP), the chatbot interacts with users in Amharic, addressing common concerns and delivering information on prenatal care, nutrition, warning signs, emotional well-being, childbirth, and postpartum care. The methodology involves integrating the chatbot with local health resources and deploying it via mobile platforms to ensure 24/7 conversational support. The developed chatbot achieved approximately 100% training accuracy and 75% test accuracy in intent classification using an ensemble model averaging approach. Beyond technical validation, this study establishes a comprehensive theoretical framework grounded in the Technology Acceptance Model (TAM) and Nielsen's Usability Heuristics to evaluate usability, acceptance, and user satisfaction. This framework addresses the critical gap between technical functionality and real-world adoption, providing a methodological foundation for future empirical validation with target users in Ethiopia's maternal healthcare context.
AUTOMATED SELENIUM TESTING FOR THE QUALITY ASSURANCE OF MEKELLE UNIVERSITY WEB SITE
(Mekelle University, 2026-01-28) Berihu Gidey Gebremeskel
Websites serve as critical platforms for administrative, academic, and communication functions in higher education institutions. However, many institutional websites in Ethiopia, including that of Mekelle University, face persistent challenges such as outdated content, inconsistent navigation, broken links, and poor mobile responsiveness. Manual quality assurance is labor intensive, error prone, and insufficient to ensure consistent performance across diverse devices and user interactions. To address these limitations, this study develops an automated testing framework using Python and Selenium WebDriver to systematically evaluate the functionality, usability, responsiveness, and content accuracy of the Mekelle University website. The design and execution of nine test cases (TC001–TC009) addressed navigation, form validation, authentication, content verification, responsive design, homepage content verification, and link validation. The results show that the navigational components (TC001–TC003) are generally reliable and offer consistent access to the main sections of the website. However, the failure of form validation testing (TC004) revealed a significant flaw in data entry operations. This failure resulted from a combination of automation-related problems, such as uneven HTML structure and unstable element locators, and website-side issues, such as missing elements and unresponsive buttons. This mixed outcome demonstrates that while Selenium works effectively with well-structured underlying web components, interacting with poorly developed or dynamically loaded form elements reduces its ease of use. Content verification (TC006) exposed discrepancies in page titles and footer components, while authentication testing (TC005) confirmed that the website currently lacks a login feature for authenticated access. Homepage content verification (TC008) further identified accessibility issues, particularly the absence of a working mobile navigation menu. Responsive design testing (TC007) showed generally acceptable behavior across devices, and link validation testing (TC009) revealed that 5 out of 53 hyperlinks failed (9.4%), indicating broken links that undermine reliability and user trust. Overall, the study demonstrates that Selenium-based automated testing is effective in detecting usability issues, content inconsistencies, and functional flaws across large portions of the website. At the same time, the mixed results from TC004 highlight an important limitation: Selenium’s accuracy and ease of use depend heavily on the quality and consistency of a website’s underlying HTML structure. Thus, the findings emphasize both the value of automated testing and the need for improved web development standards and continuous quality assurance practices to enhance the reliability, accessibility, and overall user experience of Ethiopian higher education websites.