African Nanotechnology in Engineering (Environmental applications)
African Nanotechnology in Engineering (Environmental applications) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Bayesian Hierarchical Model Replication Study on Municipal Infrastructure Asset Systems in Nigeria
Recent studies have highlighted the challenges in assessing the reliability of municipal infrastructure systems in Nigeria. These challenges include inadequate data and methodological discrepancies. The study replicates previous work by reanalyzing existing data using the same Bayesian hierarchical model. Key aspects include specifying prior distributions and estimating posterior distributions through Markov Chain Monte Carlo methods. The analysis revealed that incorporating spatial dependencies significantly improved the accuracy of reliability estimates, with a notable improvement in system performance metrics across different regions. This replication study supports the utility of Bayesian hierarchical models for assessing municipal infrastructure systems in Nigeria, particularly when considering geographical variations. Future research should explore extensions to this model, such as incorporating additional environmental factors or improving data collection methods. Bayesian Hierarchical Model, Municipal Infrastructure, Reliability Assessment, Nigeria The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2013 https://creativecommons.org/licenses/by/4.0/
Innovative Diagnostic Devices in Eritrea's Resource-Limited Settings
Eritrea faces significant challenges in accessing advanced diagnostic devices due to resource limitations. In vitro diagnostics were designed, tested, and evaluated using a sample of 150 patients with known conditions. The novel diagnostic devices demonstrated an accuracy rate of 92% (CI: 87-96%) in identifying common diseases such as malaria and tuberculosis. The developed diagnostics showed high performance in resource-limited settings, offering a cost-effective alternative to traditional methods. Further clinical trials are recommended to validate these devices across different patient populations. Eritrea, diagnostic devices, biomedical engineering, resource-limited settings The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Bayesian Hierarchical Model for Evaluating Risk Reduction in Process-Control Systems in Rwanda
This paper focuses on evaluating risk reduction in process-control systems within industrial settings in Rwanda, a developing country with significant environmental challenges. A Bayesian hierarchical model will be used to analyse data collected from industrial processes across Rwanda, with a focus on identifying common risk factors and determining the impact of control measures. The analysis revealed that process-control systems in some sectors were effective in reducing operational risks by up to 30%, though variability existed between different industries. The Bayesian hierarchical model provided insights into the effectiveness of current control strategies, highlighting areas for improvement and suggesting new intervention points. Based on findings from this study, specific recommendations will be made for enhancing risk management in industrial processes to ensure greater operational safety and environmental sustainability. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
Design Optimisation for Low-Cost Irrigation Systems in Mali's Drought-Prone Regions
Irrigation systems are critical for sustainable agricultural productivity in Mali's drought-prone regions, where water scarcity is a significant challenge. A combination of hydrological models and cost-benefit analysis was employed to simulate system performance under varying climatic conditions and water availability scenarios. Simulations indicated a consistent 15% increase in crop yield with the proposed low-cost irrigation systems compared to traditional methods, despite variable rainfall patterns. The designed irrigation systems are effective in improving agricultural productivity without significantly increasing operational expenses. Further field trials should be conducted to validate these design parameters and inform policy recommendations for sustainable agriculture development. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Municipal Infrastructure Assets Systems in Rwanda Using Difference-in-Differences Approach for Risk Reduction Assessment
Rwanda aims to enhance its municipal infrastructure assets systems (MIAS) to reduce environmental risks and improve service delivery. A difference-in-differences model will be applied to assess the impact of MIAS improvements on environmental risk levels across municipalities. The analysis identified that MIAS upgrades led to a 20% decrease in water contamination incidents per year. MIAS improvements significantly reduced environmental risks, supporting policy recommendations for infrastructure investment. Continue and expand MIAS upgrades with targeted investments in vulnerable areas. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Process-Control Systems in Rwanda
This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Rwanda: randomized field trial for measuring system reliability in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A mixed-methods design was used, combining survey and interview data collected over the study period. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of process-control systems systems in Rwanda: randomized field trial for measuring system reliability, Rwanda, Africa, Engineering, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Bayesian Hierarchical Model for Measuring Cost-Effectiveness in Municipal Infrastructure Assets Systems, Uganda
This Data Descriptor focuses on the application of a Bayesian hierarchical model for evaluating municipal infrastructure assets systems in Uganda. A Bayesian hierarchical model was developed to analyse data from municipal infrastructure projects in Uganda. This approach accounts for variability across different regions and project types. The analysis revealed significant variation in the cost-effectiveness of assets managed by local governments, with some systems showing a 20% improvement over others after adjustments were made. The Bayesian hierarchical model successfully identified key factors influencing asset performance and provided recommendations for improving resource allocation efficiency. Based on the findings, municipalities should prioritise maintenance of critical infrastructure assets to enhance overall system effectiveness. Bayesian Hierarchical Model, Municipal Infrastructure, Cost-Effectiveness, Uganda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Assessment of Manufacturing Reliability Systems in Nigerian Plants Using Difference-in-Differences Analysis
Manufacturing reliability systems are critical for ensuring efficient operations in Nigerian plants. However, the effectiveness of these systems is not well-documented. The research employs a DiD model to compare pre- and post-intervention data from a sample of Nigerian plants. Key variables include system implementation dates, operational metrics, and external shocks. A significant improvement in production efficiency was observed for the treated group (n=50) compared to the control group (n=50), with an average increase of 12% in output quality over a six-month period. The DiD analysis provides robust evidence that manufacturing reliability systems can enhance plant performance and stability, contributing to better economic outcomes for Nigerian industries. Policy makers should prioritise the implementation and continuous improvement of manufacturing reliability systems as part of their industrial development strategies.
Methodological Evaluation of Industrial Machinery Fleets in Rwanda
This study addresses a current research gap in Engineering concerning Methodological evaluation of industrial machinery fleets systems in Rwanda: randomized field trial for measuring system reliability in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of industrial machinery fleets systems in Rwanda: randomized field trial for measuring system reliability, Rwanda, Africa, Engineering, conference paper This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation in Municipal Infrastructure Assets Systems
Municipal infrastructure assets in South Africa are critical for urban development and environmental management. However, their reliability is often uncertain due to varying maintenance schedules and operational conditions. The study employs multiple linear regression analysis with robust standard errors, accounting for model uncertainty and providing confidence intervals on predicted values. A significant proportion (65%) of the variance in system reliability was explained by time-series forecasting models, indicating their potential as reliable tools for asset management. Time-series forecasting models offer a robust method for assessing municipal infrastructure systems' reliability and can inform future maintenance strategies. Further research should explore more complex models to account for non-linear relationships and incorporate real-time data sources for enhanced predictive accuracy. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Manufacturing Systems in South Africa Using Time-Series Forecasting Models for Efficiency Measurement
Manufacturing systems in South Africa face challenges related to efficiency measurement due to data availability and quality issues. A time-series analysis approach was employed, incorporating ARIMA model equations with robust standard errors estimated at a 95% confidence interval. The ARIMA model forecasts show an average error reduction of 12.6% in production output variability over the past year. Time-series forecasting models provide a reliable method for assessing manufacturing efficiency in South Africa, reducing forecast errors by improving data interpretation and prediction accuracy. Manufacturers should adopt ARIMA models to enhance their operational efficiency and strategic planning. Manufacturing Systems, Time-Series Forecasting, Efficiency Measurement, ARIMA Model, Robust Standard Errors The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Quasi-Experimental Cost-Effectiveness in Water Treatment Facilities in Uganda
Water scarcity is a significant challenge in Uganda, necessitating effective water treatment solutions. A mixed-method approach combining quantitative analysis and qualitative insights was employed to assess the performance of various water treatment systems in Uganda, focusing on operational costs, efficiency, and environmental impact. The study revealed a significant reduction (30%) in operational costs for a specific type of membrane filtration system compared to traditional sand filtration methods, with a confidence interval of ±5% around this estimate. Quasi-experimental design provided robust evidence supporting the cost-effectiveness and efficiency gains of membrane filtration systems over conventional methods. Ugandan policymakers are encouraged to adopt these findings for the development and implementation of sustainable water treatment infrastructure, particularly in rural areas where access to clean water is limited. Quasi-experimental design, Water treatment facilities, Cost-effectiveness, Uganda, Membrane filtration The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Assessment of Water Treatment Facilities in Uganda
Water treatment facilities in Uganda are essential for ensuring safe drinking water supplies. However, their effectiveness varies significantly across different regions and facilities. A randomized field trial was conducted across multiple regions in Uganda, with each facility receiving a standardised set of inputs and outputs monitored over a period of six months. Statistical models were used to analyse data on water quality parameters before and after treatment. The findings indicate that 75% of the facilities significantly reduced E.coli levels by more than 90%, with some achieving reductions as high as 98%. However, there was a notable variance in performance across different regions. This study provides valuable insights into the effectiveness and variability of water treatment systems in Uganda. The findings suggest that standardised monitoring is crucial for consistent risk reduction. Further research should focus on understanding regional-specific factors affecting facility performance to optimise resource allocation and improve overall system efficiency. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Measuring Adoption Rates of Water Treatment Facilities in Uganda
Water treatment facilities in Uganda have shown varying levels of adoption over time, necessitating a methodological approach to forecast future trends. A time-series analysis was employed, incorporating relevant historical data on facility installation and usage patterns. The ARIMA (AutoRegressive Integrated Moving Average) model with robust standard errors was used for forecasting adoption rates. The forecasted trend indicated a steady increase in the number of water treatment facilities installed from to , with an expected proportion reaching 15% by the end of the period. The ARIMA model provided reliable forecasts for future adoption rates, highlighting the potential impact on improving access to clean water in Uganda. Public health authorities should consider these findings to plan and allocate resources effectively for expanding water treatment facilities. water treatment facilities, time-series forecasting, ARIMA model, adoption rate, public health The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Multilevel Regression Analysis for Measuring Adoption Rates in Transport Maintenance Depots Systems in Uganda
Transport maintenance depots (TMDs) play a crucial role in ensuring efficient vehicle operations in Uganda's transportation sector. Despite their importance, there is limited empirical evidence on how these systems are adopted and utilised across different locations. The research employed multilevel logistic regression models to analyse data from multiple sources including interviews and surveys conducted across different TMDs. The model accounts for both fixed effects (e.g., depot characteristics) and random effects (e.g., location-specific variables). Multilevel analysis revealed that the adoption rate of TMDs in Ugandan depots varied significantly, with a proportion of 45% across different regions. Factors such as local infrastructure support and depot management practices were found to be significant predictors of adoption. The multilevel regression approach provides valuable insights into the factors affecting the adoption rates of TMDs in Ugandan depots, which can inform policy decisions aimed at improving vehicle maintenance efficiency. Policymakers should prioritise supportive local infrastructure and engage with depot managers to enhance the effectiveness of TMDs. Additionally, targeted training programmes for maintenance staff could further improve system utilization. Transport Maintenance Depots, Adoption Rates, Multilevel Regression Analysis, Uganda, Vehicle Operations The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model Evaluation for Transport Maintenance Depot System Reliability in Rwanda
This study evaluates a time-series forecasting model to assess the reliability of transport maintenance depots in Rwanda. A time-series analysis was conducted using an ARIMA (AutoRegressive Integrated Moving Average) model, with robust standard errors accounting for prediction uncertainties. The ARIMA model demonstrated a predictive accuracy rate of 85% in forecasting depot maintenance intervals over the study period. The findings suggest that integrating time-series analysis can significantly enhance the reliability and efficiency of transport maintenance systems in Rwanda. Transport authorities should consider implementing this model to optimise depot operation schedules and reduce downtime. time-series forecasting, ARIMA model, transportation maintenance depots, reliability, Rwanda The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Assessment of Transport Maintenance Depot Systems in Ethiopia Using Difference-in-Differences Modelling for System Reliability Evaluation
Ethiopia's transport maintenance depots are crucial for ensuring vehicle reliability and safety in its transportation sector. The study employs a DiD model to analyse pre- and post-intervention data from Ethiopian depots. Uncertainty is addressed through robust standard errors. An improvement in average vehicle maintenance times by 15% was observed after the intervention period, with a confidence interval of ±3%. The DiD model effectively measures system reliability improvements and highlights potential areas for further optimization. Further research should explore cost-effectiveness and scalability of the interventions identified in this study. Difference-in-Differences, Transport Maintenance Depots, System Reliability, Ethiopia The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model Assessment of Transport Maintenance Depot Systems in Nigeria,
This study evaluates the maintenance efficiency of transport systems in Nigeria by applying Bayesian hierarchical models to assess yield improvement. Bayesian hierarchical models were utilised to evaluate the operational efficiency of transportation maintenance depots in Nigeria. This approach allows for the integration of spatial and temporal variability, providing a comprehensive assessment. The analysis revealed that the transport maintenance depots had an average yield improvement rate of 15% over the study period, with significant variance across different regions. The findings suggest that targeted interventions can significantly boost depot performance, thereby improving overall system efficiency and environmental impact reduction. Implementing predictive maintenance strategies and optimising resource allocation are recommended to enhance depot yield further. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
This study addresses a current research gap in Engineering concerning Innovative Nanotechnology-Based Water Filtration Systems for Urban Youth in Nairobi Slums: Performance Outcomes and Cost-Benefit Analysis in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Innovative Nanotechnology-Based Water Filtration Systems for Urban Youth in Nairobi Slums: Performance Outcomes and Cost-Benefit Analysis, Kenya, Africa, Engineering, comparative study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Development of Sensors and IoT Systems for Environmental Monitoring in Burkina Faso Mining Sites
Mining activities in Burkina Faso’s mining sites have led to significant environmental degradation, necessitating advanced monitoring systems for sustainable development. A combination of sensor technology and IoT architecture was employed to create a comprehensive system capable of detecting pollutants such as heavy metals, sulfur dioxide, and particulate matter in the air and water. The system integrated hardware components with software algorithms for data collection, analysis, and transmission. The developed sensors detected pollutant levels exceeding the World Health Organisation (WHO) guidelines by 20-30% at several mining sites, indicating a need for immediate mitigation strategies. The IoT system demonstrated high sensitivity and specificity in detecting environmental pollutants, thus enhancing the efficiency of monitoring efforts. Further research is recommended to integrate machine learning models into the current system for predictive analysis and continuous improvement. Environmental Monitoring, Sensors, Internet of Things, Burkina Faso Mining Sites The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Evaluation of Power-Distribution Equipment Systems in Tanzania
Power-distribution equipment systems in Tanzania face significant challenges related to reliability and efficiency. A randomized controlled trial was conducted across five regions of Tanzania, assessing the impact of different system configurations on performance metrics such as power loss and downtime. The analysis revealed that a specific configuration reduced power losses by an average of 12.5% compared to traditional systems (95% confidence interval: -14.2% to -10.8%). The randomized field trial demonstrated the effectiveness of the new system in improving reliability and reducing operational risks. Implementing the recommended configuration is expected to result in significant cost savings and improved service delivery across Tanzania’s power distribution networks. Power Distribution, Randomized Field Trial, Risk Reduction, Power Loss, Downtime The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Quasi-Experimental Design Assessment of Water Treatment Facilities in Tanzania
Water scarcity is a significant challenge in Tanzania, necessitating robust water treatment facilities to ensure sustainable supply. A quasi-experimental design was employed to evaluate the performance of water treatment facilities across different regions in Tanzania, focusing on identifying yield improvement potential. An average yield increase of 15% was observed in treated water volumes when comparing pre- and post-treatment data from selected sites. The quasi-experimental design proved effective in measuring yield improvements without the need for controlled experiments, providing actionable insights into system optimization. Further studies should investigate the impact of local environmental conditions on treatment facility performance to enhance overall efficacy. quasi-experimental design, water treatment facilities, Tanzania, yield improvement, engineering The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Solar-Powered Irrigation for Ethiopian Women Farmers in Highland Ecosystems
Solar-powered irrigation systems are increasingly being promoted as a sustainable solution for smallholder farmers in arid and semi-arid regions, including Ethiopia’s highland ecosystems. A mixed-methods approach combining quantitative data from pump efficiency tests and qualitative interviews with farmer participants was employed. Solar pumps demonstrated an average daily lift capacity of 20% higher than conventional diesel pumps, reducing electricity costs by approximately 65% for farmers. The economic benefits of solar irrigation systems significantly outweigh the initial investment costs, particularly for women farmers who often lack access to formal credit markets. Government subsidies and public-private partnerships should be encouraged to facilitate widespread adoption of solar-powered irrigation in Ethiopian highlands. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Power-Distribution Equipment Systems in Nigeria
Power distribution equipment systems in Nigeria face significant challenges related to reliability, safety, and efficiency. These issues are exacerbated by a lack of standardised design guidelines and maintenance practices. A quasi-experimental design was employed to compare operational performance metrics between well-maintained and less maintained systems. Statistical analysis will incorporate robust standard errors to account for potential confounding factors. The preliminary findings suggest that a consistent maintenance schedule can reduce equipment failures by approximately 20%, with significant reductions in downtime attributed to preventive maintenance interventions. This quasi-experimental design provides a robust framework for assessing the impact of maintenance practices on power distribution system reliability and safety in Nigeria. Policy recommendations include implementing standardised maintenance guidelines, training programmes for technicians, and regular inspections as key components of risk reduction strategies. Power Distribution Systems, Quasi-Experimental Design, Maintenance Practices, Risk Reduction The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Methodological Evaluation of Power-Distribution Equipment Systems in Rwanda Using Difference-in-Differences Models for Efficiency Gains
In Rwanda, power-distribution equipment systems are crucial for efficient energy delivery to various sectors. A difference-in-differences model will be employed to assess the impact of new infrastructure investments on system performance. New data suggests an average improvement of 15% in power transmission efficiency post-intervention, with a 95% confidence interval. The methodology demonstrated robustness and effectiveness in measuring efficiency gains under controlled conditions. Further research should explore scalability and cost-effectiveness of the identified improvements. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Evaluating Power-Distribution Efficiency in Uganda
Power distribution efficiency in Uganda is a critical issue affecting both economic development and environmental sustainability. A Bayesian hierarchical model was applied to analyse data from power distribution systems across different regions of Uganda. The model accounts for variability and uncertainty at multiple levels of aggregation (e.g., national, regional, local). The analysis revealed a significant variation in efficiency among the sampled power-distribution equipment, with some units showing gains up to 20% over current practices. The Bayesian hierarchical model provided insights into the performance of various power distribution systems and identified specific areas that require further optimization. Policy recommendations include targeted investments in more efficient equipment and ongoing monitoring of system performance to ensure continuous improvement. Bayesian hierarchical model, power distribution efficiency, Uganda, engineering The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.