Muni Repository (MR)
This repository contains open access publications of Muni University Library.
Objectives:
- To digitally collect, preserve and provide electronic access to scholarly works and research output of Muni University.
- Increase the visibility and impact of our research, making it easy for researchers, students, policymakers and journalists to reference, replicate, and re-use the work.
- Issue permanent, unique and trustworthy identifiers when creating URLs to access the resource without concern that the location of the resource may change.
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- Contact the library through email: libsupport@muni.ac.ug
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Recent Submissions
Real‐time road obstacle detection system to enhance road safety on African roads
(Wiley, 2026-06-19) Mutabarura, Pison; Muchuka, Nicasio Maguu; Segera, Davies Rene
Globally, there has been a 5% decline in road accident fatalities. Integrating advanced technologies into vehicles in developed regions like Europe has significantly reduced road accident fatalities in these regions. This has played a pivotal role in reducing global road accident fatalities. However, the African road accident-related fatalities have increased by 17%. Drivers' lack of sufficient technology to detect common African road obstacles is one of the leading causes of this increase in African road fatalities. These road accidents particularly affect the young and economically active population, impacting the continent's economic growth. Object detection models have effectively enhanced road safety in developed countries by detecting road obstacles. Unfortunately, these object detection models require substantial computational and memory resources, which limits their deployment on resource-constrained edge devices. A real-time road obstacle detection system is developed based on a YOLOv3 model in this study to address the rising accidents on African roads. The YOLOv3 model was trained on a custom dataset with African road-specific obstacles. The trained model was deployed on an NVIDIA Jetson Nano for real-world inference. The NVIDIA TensorRT half-precision optimization was utilized to accelerate the model inference speed and reduce the model's memory usage while retaining the model's accuracy on the deployment platform. Experimental results reveal that deploying the model in TensorRT format reduced the inference time by 66%, achieving 68.8 ms (approximately 14.5 FPS, which meets the real-time processing requirement for obstacle detection and collision warning systems), and the memory usage by 49.9% with a 0.35% drop in accuracy. The system offers an effective and cost-effective solution on affordable hardware to improve road safety across African roads.
First evidence of underground extractive tool use by chimpanzees in Kibale National Park, Uganda
(Springer Nature, 2026-05-25) Krief, Sabrina; Magaldi, Hugo; Katumba, Raymond; Kajobe, Robert; Dif, Julia; Poquin, Pierre; Bortolamiol, Sarah; Tibesigwa, John Justice; Chapman, Colin A.; Watts, David P.
Chimpanzee behavior, including tool use, varies widely among communities and populations. Tools made by chimpanzees for extracting products from the underground nests of stingless bees are among the most complex used by the species. They have rarely been described in East Africa and have never been observed in three chimpanzee communities in the Kibale National Park, Uganda—two at Ngogo and one at Kanyawara community—that have been studied for over 30 years. In the current study, we present the results of a 15-year study of a fourth community of chimpanzees ranging at Sebitoli, in the northern part of Kibale, and the insects they consume. We identified the stingless bees and carpenter bee species on which they feed. In addition, we collected the tools used by the Sebitoli chimpanzees. Of the 443 tools used in 152 episodes to extract products from insect nests, 332 were used by chimpanzees to explore or exploit underground or arboreal nests of Meliponula sp.. In addition, individuals sometimes left sticks vertically inserted into the entrances of underground bee nests. We discuss the implications for the transmission of the tool use behavior for subterranean extractive task within this social group, given that it appears to be absent in the other three Kibale Forest communities being studied. Our results highlight the importance of taking small-scale cultural variation into account in understanding chimpanzee behavioral repertoires as well as planning and implementing conservation strategies. We dedicate this article to the chimpanzee Hugo, who loved honey the most. He was slaughtered with machetes by poachers on April 3, 2026.
Integrating local plant-phenology knowledge into anticipating seasonal weather changes: evidence from smallholder farmers in Uganda’s Mount Elgon region (cross-sectional survey)
(Springer Nature, 2026-04-02) Naigaga, Hellen; Rukarwa, Runyararo Jolyn; Ssekandi, Joseph
Background
Indigenous communities have long relied on detailed empirical knowledge of natural phenomena to inform their daily lives and livelihoods. Adaptation to climate change among smallholder farmers is a critical step in achieving sustainable livelihoods. This study explored the potential of integrating indigenous ecological knowledge with scientific methods to improve weather forecasting in the Mt. Elgon region of Uganda.
Methods
A cross-sectional survey design was employed involving 384 respondents. Data were collected using structured questionnaires to examine perceptions of climate change, local weather pattern changes, and the use of plant phenological indicators for anticipating weather changes. Descriptive statistics was used to summarize responses, and comparative analysis was conducted to assess convergence between local forecasts and meteorological records. A Pearson correlation test was used to assess the relationship between local weather forecasts and formal meteorological information. A chi-square test of independence was used to examine how demographic factors influence farmers’ knowledge and use of phenological indicators.
Results
Respondents demonstrated extensive knowledge of local weather patterns and perceived declining reliability of rainy seasons in the region. 88% of respondents demonstrated familiarity with plant species used for anticipating weather changes. Local ecological knowledge-based reporting identified distinct rainy and dry months, with January identified as the driest month (98.7%) and April as the rainiest (87%), which converged with the meteorological weather forecast in the region. Plant phenology is a reliable predictor of seasonal weather changes, particularly among tree species such as Cordia africana and Erythrina abyssinica. Leaf shedding indicates impending dry seasons, while new foliage signals the onset of rainfall. Cordia africana and Erythrina abyssinica exhibit a high frequency of usage in weather prediction. The influence of plant phenology on farming activities was evident, with planting time being the most affected decision.
Conclusion
Plant phenology is a reliable, locally validated predictor of seasonal weather changes in the Mt. Elgon region. Integrating local knowledge with scientific approaches enhances the accuracy and resilience of weather forecasting in rural farming systems.
Managing Uganda's biodiversity amid climate and societal change
(John Wiley & Sons, 2026-04-10) Omeja, Patrick A.; Golooba, Martin; Opito, Emmanuel A.; Tumwesigye, Charles; Chapman, Colin A.
Uganda is home to remarkable biodiversity, supports diverse ecosystems ranging from glacier-topped mountains, tropical rain forests, to semi-arid systems, has a well-established and effective protected areas system, and benefits substantially from nature tourism. However, Uganda will face significant challenges if it is to maintain these riches. For example, the country's population is growing rapidly and is expected to surpass 100 million by 2050, more than 80% of households depend directly on natural resources for their livelihoods, and agricultural land has expanded by about 1% per year. Furthermore, Uganda is one of the world's most climate-vulnerable countries, and flooding and droughts are predicted to become much more common. Such changes will increase demands on natural resources, including those in protected areas. Uganda's government is aware of these challenges and has become a regional leader in environmental policy by taking a proactive approach. However, Uganda is struggling to educate its citizens and build the capacity for effective protection. Here we evaluate Uganda's conservation status and the threats to biodiversity from societal and climate change. We consider the current capacity and institutional infrastructure available to conserve the country's biodiversity, focusing on training and research, policy implementation and capacity in the field. Despite major challenges, clear pathways to a bright future are available.
Modeling aflatoxin risk dynamics in Uganda’s groundnut value chain: A System dynamics decision support approach
(PT. Teknologi Futuristik Indonesia, 2026-06-15) Nansukusa, Yudaya; Asikuru, Salama; Kalyankolo, Umaru; Nafuna, Ritah
Aflatoxin contamination remains a persistent threat to food safety, public health, and trade in Uganda’s groundnut value chain, where a large share of household and market samples exceed national and international safety limits. Despite sustained investment in awareness campaigns, improved storage, and biocontrol products, contamination remains high and unevenly controlled, in part because interventions are typically evaluated in isolation and are rarely supported by dynamic tools that capture the feedback, delays, and trade-offs linking climate, farmer behaviour, institutional support, and markets. This study develops and analyses a System Dynamics (SD) decision-support model of aflatoxin risk in the groundnut value chain, framed within an Information Systems view of simulation-based decision support. Causal loop diagrams constructed in Vensim PLE and a stock-and-flow model implemented in STELLA Architect represent the reinforcing and balancing feedback structures governing contamination, including the “Shifting the Burden” archetype. Scenario simulations and a one-at-a-time sensitivity analysis show that symptomatic measures such as awareness campaigns deliver only temporary relief, whereas post-harvest practice quality emerges as the highest-leverage parameter; a realistic mixed-policy scenario that combines moderate investment across practices, awareness, and storage technology drives contamination below regulatory thresholds within the simulated horizon. These findings indicate that durable mitigation in low-resource settings depends on sustained structural investment rather than reactive fixes, and they demonstrate how SD modelling can guide adaptive, evidence-based food-safety policy.