Kabale University Digital Repository (KAB-DR)
KAB-DR preserves research output from the Kabale University community
Communities in KAB-DR
Select a community to browse its collections.
- The collections in this Community are comprised of Indigenous Knowledge emanating from communities in the neighborhoods of Kabale University. These are communities in the great Kigezi Region.
- This community holds students (Graduates) dissertation and Thesis, Staff field reports, Students (undergraduate) study reports
- The community includes research article publications in journals both local and international, conference papers in proceedings and reports, abstracts and reviews by Kabale University Staff and Students
- This community archives publications by individual University Staff and Students, Faculty and Departmental Publications (i.e. University Journal, Newsletters, University official publications etc.), groups and Association operating in the University (i.e. Convocation and Staff and Students Association}
Recent Submissions
Prevalence of Bovine Fasciolosis,Financial Losses and Risk Factors Associated with the Disease in Lira and Gulu Districts, Northern Uganda
(John Wiley & Sons Ltd., 2025) Ogwal, Anthony; Okello, Daniel Micheal; Aliro, Tony; Owiny, David Okello; Ndyomugyenyi, Elly Kurobuza
Bovine fasciolosis (BF) is a parasitic disease of cattle that causes significant economic impacts to cattle farmers. The physical loses include weight loss, drop in productivity, liver condemnation and mortalities. Tis study assessed the prevalence, financial losses and risk factors associated with the disease in Lira and Gulu Districts, northern Uganda. A cross-sectional study of 720 slaughter cattle from the abattoirs was conducted by macroscopic examination of the animals and carcasses during routine slaughter. In the farms, 120 rectal faecal samples were taken to a laboratory for Fasciola egg detection by simple microscopy, while risk factors were assessed by administering a questionnaire to farm owners. Prevalence of BF was highest (38%) within cattle in the age group of 1–3years and lowest (18%) in those over 5years. The overall BF prevalence was 48% and 26% by postmortem examination and coprology, respectively. The cattle body condition had a significant association (p<0.01) with prevalence of BF, in which emaciated cattle were most affected (59%), while fat ones had the least prevalence (15%). The annual financial loss due to BF infection was USD 89,099. The major risk factors associated with the disease at the farm level were communal grazing in swampy areas (82%) and watering cattle in swamps (71%). Farms where the source of drinking water was swamp water had higher chances (p<0.05) of their cattle having BF. An integrated approach using routine deworming programs, improvement of cattle management practices and control of snail intermediate hosts is recommended to effectively control the spread of BF.
Deep Learning Techniques in DICOM Files Classification: A Systematic Review
(BON VIEW PUBLISHING PTE.LTD., 2025) Mabirizi, Vicent; Kawuma, Simon; Natumanya, Deborah; Wasswa, William
The digital imaging and communications in medicine (DICOM) format is a widely adopted standard for storing medical imaging data, integrating both image and metadata critical for clinical diagnostics. However, its complexity poses challenges for deep learning applications, particularly in extracting and processing this dual-layered data. This review analyzes 23 peer-reviewed studies published between 2014 and 2024, sourced from PubMed, Google Scholar, PLOS, Science Direct, and IEEE databases. Guided by Arksey and O’Malley’s scoping methodology, the review reveals that existing deep learning techniques typically rely on converting DICOM images into simpler formats like JPEG, TIF, or PNG for classification, a process that often results in metadata loss and reduced classification accuracy. Frameworks such as MONAI, NVIDIA Clare, SimpleITK, and OpenCV facilitate direct DICOM processing but face limitations, including overfitting, challenges with data heterogeneity, and inefficiencies in handling large datasets. This review emphasizes the urgent need for developing a robust convolutional neural network architecture capable of directly processing DICOM data to preserve metadata integrity and enhance predictive performance, paving way for more reliable and scalable medical imaging solutions.
Adoption of sustainable agricultural intensification practices: assessing the role of institutional and socio economic factors amongst smallholder farmers.
(Taylor & Francis Group., 2025) Kule, Enos Katya; Agole, David; Obia, Alfred; Okello, Daniel Micheal; Odongo, Walter
Sustainable agricultural intensification practices (SAIPs) are highly recommended for smallholder farmers due to their positive impact on farm production and productivity. However, farmers remain reluctant to adopt SAIPs resulting in low agricultural productivity in Uganda. This study assessed the institutional and socio-economic factors affecting the adoption and adoption intensity of SAIPs amongst smallholder maize farmers in Eastern Uganda. Primary data were collected from 320 maize farmers in Kamuli and Jinja districts using a pretested questionnaire. The binomial logistic and generalized Poisson regression models were used to compute the predictor variables of adoption and adoption intensity of SAIPs respectively. Results showed that improved maize varieties, conservation tillage, legume intercrop, integrated soil fertility management (ISFM), and integrated pest management (IPM) were adopted by 58, 36, 44, 52, and 56% of the farmers. Institutional factors i.e., group membership, access to all-weather roads, credit, and extension information were the significant predictors of
the adoption and the adoption intensity of SAIPs. Socio-economic factors i.e., market-oriented farming influenced both the adoption and adoption intensity of SAIPs, age of family head, family labour use, household size, and dependence ratio, only positively influenced the adoption intensity of adoption of SAIPs. The policy implications of this study include the need to strengthen agricultural extension institutions and streamline extension information disseminated to farmers to enhance the adoption of SAIPs. Farmers should be advised to utilize cheap credit services such as village savings and loan associations to facilitate the adoption of SAIPs.
Impediments to the Development of Kiswahili in the Education Sector in Uganda
(Journal of the Institute of Kiswahili Studies, 2024) Agume, Innocent; Ogechi, Nathan Oyori; Majariwa, David
This study explores the challenges facing the growth of the Kiswahili language in the Ugandan education system. Despite noticeable efforts by the government, the development of Kiswahili through the education system still faces various obstacles. Data was collected from policymakers, coordinators, and language policy implementers, who were purposively selected. Data was analysed using a qualitative approach. Based on a thematic analysis of data, it was established that the growth and development of the Kiswahili language in Uganda, through the education system is still low. This is due to a lack of political will, the absence of effective strategies for implementing language policy regarding Kiswahili, the non-deployment of available Kiswahili teachers, and the inadequacy of materials and resources for teaching and learning Kiswahili. Similarly, ethnolinguistic rivalries have derailed efforts towards Kiswahili development in the education sector. Suggested practical strategies to address these challenges include: strong political will, adequate supply of Kiswahili teaching materials, as well as recruitment and deployment of more Kiswahili teachers. Additionally, tackling negative attitudes and conducting further research on language perceptions will enhance its acceptance and development. These findings are important for policymakers in guiding the formulation of necessary policies that will impact Kiswahili teaching and usage in Uganda.
A state-of-the-art review on the modeling and probabilistic approaches to analysis of power systems integrated with distributed energy resources.
(Ain Shams Engineering Journal, 2024) Wanjoli, Paul; Abbasya, Nabil H.; Moustafa, Mohamed M. Zakaria
Modern power systems are shifting toward decarbonization and incorporation of distributed energy resources (DERs) to replace fossil fuel generators. Although promising, DERs introduce uncertainty because of their intermittent nature. This study provides a comprehensive survey of current approaches for modeling system uncertainties and methods of analysis, particularly in the context of static voltage stability studies within modern power systems. Emphasis is placed on evaluating various models applied to different system random variables (RVs), focusing on their suitability for those particular RVs. Additionally, the study examines the characteristics and frameworks of prominent probabilistic methods (PM), evaluates their efficacy, and discusses static voltage stability analysis approaches, emphasizing solution structures and appropriate applications. It concludes by thoroughly reviewing both numerical and analytical PM methods and offering insights into their strengths and limitations. The provided comprehensive survey reveals that, considering system uncertainties, voltage stability studies have gained the most share, followed by small-signal stability studies, whereas the frequency stability studies have gained the least share.