School-wide publications

Permanent URI for this collectionhttps://dspace.njala.edu.sl/handle/20.500.144402/182

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Start date: 2025

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Now showing 1 - 10 of 24
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    User-Centric Evaluation and Optimization of Resource Allocation in Edge Computing Environments
    (2025) Koroma, Mohamed
    The proliferation of mobile applications with intensive computational demands has necessitated the adoption of edge computing to reduce latency and energy consumption. However, edge servers face challenges such as limited resources, dynamic wireless conditions, and inefficient task offloading strategies, particularly in multiuser environments.
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    Turning Resources into Results: Accelerating Capacity Building in Digital Learning at Njala University
    (2025-02-18) Dumbuya, Emmanuel
    Njala University is actively integrating digital learning solutions to enhance educational outcomes. This paper examines strategies for transforming available resources into measurable results through capacity-building efforts. Utilizing a mixed-methods approach—including policy analysis, stakeholder interviews, and institutional data review—this paper identify key factors contributing to successful digital capacity building. The findings suggest that strategic resource allocation, collaborative partnerships, and targeted professional development initiatives are critical for sustainable digital transformation in higher education. It discusses implications for digital learning at Njala University and proposes a framework to guide similar institutions.
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    Technological Advancements of Energy Storage Systems Technologies in Africa: A Review
    (Scientific Research Publishing, 2025) Koroma, Mohamed
    The global energy landscape is transforming to tackle climate change, improve energy security, and meet growing energy demands. Energy storage technologies are vital for incorporating “renewable energy”, stabilizing electrical network, and advancing electrification. This review paper provides a comprehensive analysis of the technological advancements in energy storage systems (ESS) and their applicability in Africa. The study highlights the potential of ESS to address Africa’s energy challenges, including grid instability, rural electrification, and renewable energy integration. The paper critically evaluates various ESS technologies, such as lithium-ion batteries, pumped hydro storage, and flywheels, and assesses their economic, environmental, and technical feasibility in different African regions. The findings suggest that tailored ESS solutions, supported by innovative financing models and regional-specific policies, are essential for sustainable energy transitions in Africa. The paper concludes with recommendations for policymakers, researchers, and industry stakeholders to accelerate the adoption of ESS technologies across the continent.
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    Quantum computing in financial security: A risk management framework for systemically important financial institutions
    (GSC Online Press, 2025-01-30) Jhessim, Eric
    This research explores the application of quantum computing in enhancing financial system security, focusing on developing a robust risk management framework for systemically important banks in Sierra Leone. By evaluating 2 leading banks in the country, this study identifies key vulnerabilities, assesses potential quantum computing solutions, and provides a blueprint for safeguarding financial systems in the quantum era. Through implementation of the proposed framework, participating institutions demonstrated significant improvements in threat detection, encryption strength, and risk mitigation, with quantum-enhanced systems showing 99.8% accuracy in detecting sophisticated financial fraud attempts while reducing false positives by 90% compared to traditional systems. The implementation resulted in a 60% reduction in security incident response time and a 75% improvement in encryption strength against potential quantum attacks. These advancements provide crucial protection for financial infrastructure while ensuring regulatory compliance and operational resilience.
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    Insights into breast cancer: A simple machine learning method for early disease detection
    (GSC Online Press, 2025-01-22) Sowah, Anthony
    Breast cancer remains a significant global health challenge, where accurate prediction plays a vital role in early diagnosis and effective treatment, ultimately saving lives. This study evaluates the performance of three machine learning models; Support Vector Machine (SVM), Random Forest Classifier, and XGBoost for breast cancer prediction. Using the Wisconsin Breast Cancer Dataset, the models were assessed based on their accuracy. The experimental results demonstrated that SVM outperformed the other models, while both XGBoost and the Random Forest Classifier achieved just slightly lower accuracies. This research underscores the potential of machine learning models in enhancing breast cancer prediction and highlights their importance in advancing early detection and treatment strategies.
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    Incorporating Future Skills: Digital Literacy and Critical Thinking for 21st-Century
    (RELX Group (Netherlands), 2025) Dumbuya, Emmanuel
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    IMPACT OF CLIMATE SMART RESILIENT PRACTICES ON ENHANCING SUSTAINABLE AGRICULTURAL PRODUCTIVITY. CASE STUDY OF RICE, COCOA AND OIL PALM VALUE CHAINS DEVELOPMENT
    (2025-09-26) M and E/GIS Officer-Agricultural Value Chain Development Project(AVDP), Ministry of Agriculture, Forestry and Food Security (MAFFS) Sierra Leone .
    The goal of the study was to evaluate the impacts of agricultural productivity through climate smart agricultural practices for selected value chains (IVS-Rice, Cocoa and Oil Palm) in a bid to boost resilience and enhance livelihood opportunities for rural farmers in Bo District. The objectives were to determine the effectiveness of climate-smart agricultural practices in increasing crop yields and productivity, and identify barriers to the adoption of climate-smart practices among rural farmers. The study adopted a mixed method approach using both quantitative and qualitative research method approaches. The findings revealed that climate smart agricultural (CSA) practices led to improved yields across all value chains with cocoa and IVS rice farmers achieving higher yields (above 25%) compared to moderate gains (10-25%) among Oil Palm farmers.The study concludes that Climate Smart Agricultural (CSA) practices have significantly enhanced agricultural productivity of farmers dealing with the IVS rice, cocoa, and oil palm value chains in Bo District. Although farmers continue to face challenges such as financial constraints, limited training opportunities, uncertain weather conditions, and restricted access to inputs, the evidence demonstrates that CSA practices consistently improve yields, with rice and cocoa farmers recording the highest gains and adoption rates are encouraging.Moreover, stakeholders acknowledge that CSA awareness is steadily increasing, particularly among younger male farmers, and that practices like inter-cropping are becoming more common. Overall, the findings affirm that CSA is a viable pathway to strengthen resilience, boost rural livelihoods, and support sustainable agricultural development in the district, provided that financial, institutional, and policy support systems are strengthened to scale adoption.
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    Evaluating the Efficiency and Performance of Minimalist Neural Network Architectures with Hybrid Activation Functions
    (2025-10-23) Makieu, Peter
    This research introduces an Adaptive Hybrid Activation Function (AHAF) for minimalist neural networks, addressing efficiency and performance challenges in resource-constrained applications.Unlike existing hybrid activations (e.g., Swish) or minimalist approaches (e.g., Lottery Ticket Hypothesis (LTH)), AHAF incorporates dynamic α-adaptation (0.50-2.13 range) with theoretical guarantees, achieving O(1/√T) convergence (Theorem 1) and gradient saturation mitigation (Lemma 2).Evaluated on Iris and Modified National Institute of Standards and Technology (MNIST) datasets, 8-unit AHAF networks matched 128-unit Rectified Linear Unit (ReLU) models in accuracy (96.67%) while reducing parameters by 84% and improving convergence speed by 18-22%.AHAF demonstrated superior adversarial robustness under Projected Gradient Descent (PGD) attacks (ϵ=0.1),showing only 1.18% accuracy drop versus ReLU's 3.42% (p 1.0).These results challenge conventional assumptions about hybrid activation overhead, establishing AHAF as a framework for sustainable Artificial Intelligence (AI) deployment in edge computing and adversarial-prone environments.The study bridges two key paradigms -dynamic activation adaptation and minimalist architecture design -offering both theoretical advances (formalized convergence proofs) and empirical validation (energy efficiency metrics, adversarial testing).By demonstrating that small networks with meta-learned activations can outperform traditional architectures, this work provides actionable insights for developing efficient, robust AI systems without sacrificing accuracy.The replicable methodology and open benchmarks further support adoption in real-world applications where computational resources and model stability are critical constraints.
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    Evaluating the Adoption of Virtualization and Cloud Computing as Strategic IT Outsourcing Solutions for Enhancing Educational Efficiency at Njala University
    (2025) Koroma, Mohamed
    The rapid evolution of virtualization and cloud computing presents transformative potential for higher education institutions (HEIs), particularly in resourceconstrained settings like Sierra Leone. Despite their proven benefits in developed nations, significant gaps remain in understanding their adoption challenges and impacts in African HEIs. This study evaluates the implementation of these technologies at Njala University, addressing critical research gaps in IT outsourcing strategies for developing regions. Employing a mixedmethods approach, the research combines quantitative surveys (N = 1,000) and qualitative interviews (n = 15) to assess three key hypotheses: the impact on IT resource management (H₁), operational efficiency (H₂), and educational outcomes (H₃). Findings reveal strong correlations (r = 0.805–0.939, p < 0.001), confirming significant improvements in all areas, with 87.6% of respondents reporting enhanced IT management and 76.7% observing better educational efficiency. However, infrastructural deficits (e.g., unreliable internet) and skill gaps emerged as critical moderators. The study validates the Technology-Organization-Environment (TOE) framework while proposing "infrastructure viability" as a new construct for developing contexts. Practical implications include prioritizing bandwidth upgrades, capacity building, and localized cloud policies. Despite its contributions, the single-institution focus limits generalizability, suggesting the need for cross-national studies. Future research should explore longitudinal costbenefit analyses and policy frameworks to support scalable adoption. This work provides actionable insights for HEIs and policymakers, bridging the gap between theoretical models and real-world implementation in resourceconstrained environments.