African Public Space Design (Planning/Social)
African Public Space Design (Planning/Social) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Replication Study on Climate-Resilient Urban Drainage Infrastructure Design in Coastal Ghana, 201X
Climate change exacerbates coastal flooding in Ghana's urban areas, necessitating resilient drainage infrastructure that can withstand increasing storm events. The replication study uses a hybrid modelling approach combining machine learning algorithms with traditional hydrological simulations to predict stormwater management outcomes under varying climate scenarios. A preliminary model suggests that incorporating green infrastructure elements like permeable pavements and bioswales can reduce peak discharge by up to 30% in high-impact rainfall events, aligning with local climate projections. The replication study confirms the effectiveness of the designed drainage system models in simulating realistic stormwater management responses for coastal Ghana's urban settings. Local authorities should consider integrating these design elements into future infrastructure projects to enhance resilience against future flooding events. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Geographic Terms: African Geography Methodological Terms: Modelling Techniques Theoretical Concepts: Climate Resilience Techniques: Hybrid Modelling Concepts: Urban Drainage Systems
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Evaluating Process-Control Systems Adoption Rates in Senegal
In Senegal, there is a growing interest in adopting process-control systems (PCSs) to enhance efficiency and accountability in various public sector operations. A mixed-methods approach was employed, including surveys for quantitative data collection and interviews for qualitative insights. Data from four public sector departments were analysed using logistic regression models to estimate the probability of PCS adoption based on departmental characteristics and performance metrics. The analysis revealed that among the surveyed departments, 65% reported adopting at least one type of PCS in the past year. Departments with higher levels of digital infrastructure had a significantly higher likelihood (OR = 1.87, CI: 1.03-3.42) of adopting PCSs. The quasi-experimental design provided robust evidence for understanding PCS adoption dynamics and highlighted the importance of technological readiness in facilitating PCS implementation. Public sector managers should prioritise investments in digital infrastructure to support the deployment of process-control systems, thereby improving operational efficiency and accountability.
Bayesian Hierarchical Model for Measuring Efficiency Gains in Municipal Infrastructure Asset Systems in South Africa
Public infrastructure in South Africa faces significant challenges in terms of efficiency and service delivery. The municipal asset systems are often inefficient due to poor management practices. A Bayesian hierarchical model will be employed to estimate and compare the performance of different municipal infrastructure assets. The model accounts for spatial heterogeneity and varying levels of management effectiveness across regions. The analysis reveals that some municipalities achieve efficiency gains through improved asset maintenance strategies, with an average improvement rate of 15% in service delivery metrics. The Bayesian hierarchical model provides a robust framework to identify areas where efficiency improvements are most needed and can guide targeted interventions for better municipal infrastructure management. Recommendation 1: Municipalities should prioritise asset maintenance strategies that align with the identified gains. Recommendation 2: Regular audits of asset management practices are essential for continuous improvement. Bayesian hierarchical model, efficiency gains, municipal infrastructure, South Africa 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/
Solutions for Industrial Pollution Control in Zambia
Industrial pollution in Zambia poses significant environmental challenges, necessitating robust solutions to mitigate adverse impacts on public health and ecosystems. The study employs a mixed-methods approach combining quantitative data analysis with qualitative field studies. A Bayesian hierarchical model is utilised to predict pollutant dispersion patterns across different regions of the country. Predicted pollutant concentrations show a clear gradient from urban centers to rural areas, indicating that targeted interventions are most effective in high-pollution zones. The methodological framework provides a robust tool for policymakers and engineers to prioritise pollution control efforts and ensure equitable environmental protection across Zambia. Implement the identified solutions based on the model's predictions and incorporate stakeholder feedback into ongoing policy development. Industrial Pollution, Environmental Engineering, Zambian Policy, Bayesian Hierarchical Model The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Panel Data Estimation for Measuring Adoption Rates of Power-Distribution Equipment Systems in Senegal
This article evaluates the methodological approach to measuring adoption rates of power-distribution equipment systems in Senegal. A mixed-methods approach combining quantitative panel-data analysis with qualitative insights was employed. Panel Data Estimation (PDE) using logistic regression models was applied to evaluate the impact of socio-economic factors on system adoption in Senegal's power distribution networks. The estimated probability of adoption for a new system reached 75%, indicating high potential interest among stakeholders despite initial skepticism. The panel data approach effectively captured variations in adoption rates across different regions, revealing significant differences influenced by infrastructure accessibility and economic conditions. Further research should consider incorporating additional variables to enhance the predictive power of future models. Power Distribution Equipment Systems, Panel Data Estimation, Adoption Rates, Senegal 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/
Evaluating Process-Control Systems in Ethiopian Public Spaces
This study addresses a current research gap in Engineering concerning Methodological evaluation of process-control systems systems in Ethiopia: quasi-experimental design for measuring risk reduction in Ethiopia. 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 process-control systems systems in Ethiopia: quasi-experimental design for measuring risk reduction, Ethiopia, Africa, Engineering, replication 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.
Methodological Evaluation of Manufacturing Systems in Senegal Using Time-Series Forecasting for Risk Reduction Assessment
Manufacturing systems in Senegal have faced challenges related to production inefficiencies and risk management. The study employs a time-series forecasting model (e.g., ARIMA) to analyse historical data from Senegalese manufacturing plants. Robust standard errors are used to quantify the uncertainty associated with predictions. A clear trend of increasing production risks was observed over the last five years, which can be attributed to fluctuating raw material prices and labour supply challenges. The time-series forecasting model effectively identified risk reduction strategies that could mitigate future uncertainties in Senegalese manufacturing environments. Manufacturing plants are recommended to implement robust procurement strategies for raw materials and enhance workforce management practices to reduce risks. time-series forecasting, manufacturing systems, risk assessment, Senegal 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/
Multilevel Regression Analysis to Evaluate Process-Control Systems Reliability in Rural Rwanda
Process-control systems are crucial for ensuring reliability in various engineering applications, including rural infrastructure projects such as water supply and irrigation systems in Rwanda. A multilevel regression model was employed to analyse data collected from multiple sites across Rwanda. The model accounts for both fixed and random effects to account for hierarchical structure within the data. The multilevel regression analysis revealed significant differences in system reliability across different regions of Rwanda, with an estimated coefficient indicating a 10% increase in system reliability per unit reduction in environmental variability. This study provides insights into the factors affecting process-control systems' reliability and offers recommendations for improving system performance in rural settings. Implementing targeted interventions to mitigate environmental stressors could enhance the reliability of process-control systems, particularly in regions with higher levels of environmental variability. multilevel regression analysis, process-control systems, reliability, engineering, rural 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.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Geotechnical Foundations on Expansive Soils
Geotechnical foundations on expansive soils are critical in regions where soil properties change significantly over time due to moisture content variations. Sudan and Senegal both face challenges with expansive clays, which can lead to significant foundation instability. A review of existing literature and field data from both countries was conducted. Standardised geotechnical tests were applied to representative soil samples to assess their behaviour under varying moisture conditions. The analysis revealed that while the proportion of expansive soils in Sudan (50%) is higher than in Senegal (20%), the direction of soil swelling and shrinkage patterns was similar, indicating comparable risks but different intensities. Despite regional differences, both countries face significant challenges with expansive soils, necessitating standardised geotechnical engineering approaches to mitigate foundation instability. Standardised testing protocols should be adopted in both regions to ensure consistent and reliable foundation designs. Enhanced collaboration between engineers and soil scientists is recommended for future research. Geotechnical Engineering, Expansive Soils, Sudan, Senegal, Foundation Design 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 Process-Control Systems in Ghana
Process-control systems are critical in managing risks within public space design and planning projects. A randomized field trial was conducted to assess the impact of process-control systems on risk reduction. Data were collected from five randomly selected public space design and planning projects across Ghana over a six-month period. In one project, implementing process-control systems led to a 20% reduction in construction delays (mean delay time: 15 days vs. 19 days with no system). Process-control systems significantly improved risk management outcomes in Ghanaian public space design projects. Public sector agencies and private contractors should adopt process-control systems to enhance safety and efficiency. public space, construction, risk reduction, process-control systems, randomized field trial 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/
Multilevel Regression Analysis of Process-Control Systems in South Africa
Process-control systems are employed in various sectors to ensure safety and efficiency. In South Africa, these systems have been implemented across industries such as mining and construction to mitigate risks associated with workplace accidents. A multilevel regression model was utilised, incorporating data from multiple sources including incident reports and employee surveys. Hierarchical random effects were incorporated to account for variations within and between organizations. The analysis revealed a significant reduction in workplace incidents at the organisational level (odds ratio = 0.75; CI: 0.68-0.83), indicating that process-control systems are effective in lowering risk levels across industries. Process-control systems have demonstrated an ability to reduce workplace incidents, particularly at the organisational level. Future research should explore long-term sustainability and broader impact of these systems. Organizations should continue implementing and refining their process-control systems based on this study's findings. Additionally, ongoing training for workers is recommended to ensure system effectiveness.
Process-Control Systems Evaluation in Senegal
In Senegal, process-control systems are essential for ensuring quality in manufacturing processes. However, evaluations of these systems often lack a robust methodological framework. A DD model was applied to compare changes in system performance before and after the implementation of control measures. Data from two industrial sectors were analysed for robustness assessment. The DD analysis revealed a significant improvement in process quality post-intervention, with an average increase of 15% in defect rates reduction across all monitored processes. This study provides evidence that the difference-in-differences model can effectively assess system reliability and highlight areas for further improvement. Industry stakeholders should prioritise continuous monitoring and maintenance of process-control systems to maintain optimal performance levels. Process-Control Systems, DD Model, System Reliability, Senegal 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/
Power-Distribution Equipment Systems in Rwanda
Power distribution in Rwanda relies on a network of equipment systems that are crucial for ensuring reliable electricity supply across the country. A mixed-method approach combining quantitative data analysis and qualitative field observations was employed to assess the efficiency and economic viability of power-distribution equipment in Rwanda. The preliminary findings suggest that there is a significant variation (20-35%) in cost-effectiveness across different regions, with urban areas generally outperforming rural ones. This study highlights the need for tailored investment strategies to enhance the efficiency and reduce costs of power distribution equipment systems in Rwanda. Recommendation is made for targeted investments in underperforming regions to improve overall system performance at a lower cost, thus increasing economic benefits. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Time-Series Forecasting Model for Risk Reduction in Manufacturing Plants Systems in Rwanda,
In manufacturing plants in Rwanda, there is a need to enhance system performance through risk reduction strategies. A time-series analysis approach was utilised, incorporating data from existing records of manufacturing plant operations over the period -. The time-series forecasting model showed a significant reduction in operational risks by approximately 15%, indicating potential for improved system performance. The developed model demonstrated effectiveness in risk reduction, offering insights into future applications within the manufacturing sector of Rwanda. Further studies should explore scalability and adaptability of this model across different types of manufacturing systems. 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) 2003 https://creativecommons.org/licenses/by/4.0/
Comparative Environmental Engineering Solutions to Industrial Pollution in Zambia 2003
Industrial pollution in Zambia has been a significant environmental challenge, contributing to air, water, and soil contamination. A comparative analysis of case studies was conducted, including interviews with industry representatives, regulatory bodies, and academic experts. Data from government reports and published research were also reviewed. Two specific engineering solutions—waste treatment plants and industrial effluent management systems—showed significant improvement in pollution levels by 30% and 25%, respectively, over a five-year period. The study concludes that while both types of solutions were effective, the waste treatment plants provided a more sustainable long-term solution due to lower operational costs and higher compliance rates with environmental regulations. Further research should focus on developing comprehensive waste management strategies for industrial sites in Zambia, incorporating technology transfer and capacity building programmes. 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 Cost-Effectiveness Evaluation of Industrial Machinery Fleets in South Africa
Industrial machinery fleets play a crucial role in South Africa's manufacturing sector, influencing productivity and operational costs. The study employs a Bayesian hierarchical model to analyse data from multiple industrial machinery fleets across South Africa. This approach accounts for variability in operational costs and productivity within different sectors. A key finding is that the proportion of fleets achieving cost savings through targeted maintenance interventions exceeded 60%, highlighting the effectiveness of predictive analytics in fleet management. The Bayesian hierarchical model successfully quantifies the impact of various fleet management strategies on overall costs and efficiency, providing actionable insights for policymakers and industry leaders. Implementing preventive maintenance programmes is recommended to further enhance fleet cost-effectiveness. Future research should explore scalability issues in implementing these models across diverse industries. Bayesian hierarchical model, industrial machinery fleets, cost-effectiveness, predictive analytics, South Africa 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/
Methodological Evaluation of Power-Distribution Equipment Systems in Tanzania
Power distribution equipment (PDE) systems are critical for reliable power supply in rural Tanzania. However, their effectiveness and reliability vary significantly across different regions. A randomized field trial was conducted in four rural districts. Randomized block design was used with stratified randomization by district type (urban vs. rural) and population density (high vs. low). Data collection included pre- and post-trial surveys, equipment performance metrics, and community feedback. In the high-density urban areas, there was a statistically significant improvement in power supply reliability with an $R^2 = 0.65$ ($p < 0.01$) indicating that up to 65% of the variance in power supply stability can be attributed to PDE system upgrades. The randomized field trial demonstrated the effectiveness of PDE system improvements in enhancing power supply reliability, particularly in high-density urban areas where infrastructure resilience was significantly bolstered. Based on findings, immediate investment and maintenance strategies should focus on upgrading PDE systems in high-density urban districts to ensure consistent power supply for communities. Power distribution equipment, randomized field trial, risk reduction, reliability, R^2
Evaluating Water Treatment Systems in Kenya through Randomized Field Trials
Water treatment systems are critical for improving water quality in Kenya's public spaces. However, there is a need to evaluate their effectiveness and ensure they effectively reduce health risks. A randomized controlled trial design was employed to evaluate the water treatment systems in two different regions of Kenya. Participants were randomly assigned to either receive a standard water treatment system or no intervention control group. Data collection included microbiological analysis, user feedback surveys, and continuous monitoring of water quality parameters over six months. The randomized field trials revealed that the treated water had significantly lower levels of pathogenic bacteria compared to untreated sources (p < 0.05), suggesting an effective risk reduction strategy in reducing health risks associated with unsafe drinking water. This study provides evidence-based insights into the effectiveness of water treatment systems in mitigating public health risks, particularly in underserved communities where access to safe water is limited. Based on the findings, it is recommended that policymakers prioritise investment in sustainable and effective water treatment infrastructure as a key component for improving public health outcomes in Kenya. water treatment systems, randomized field trials, risk reduction, microbiological analysis, 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.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Plant Systems in Ghana
Manufacturing plants in Ghana are critical for economic development but face significant operational risks that can hinder productivity and sustainability. A randomized controlled trial (RCT) was conducted to assess the impact of implementing advanced control systems and predictive maintenance protocols across randomly selected manufacturing plants. Data collection included pre- and post-intervention performance metrics such as production efficiency, downtime, and safety incidents. The analysis revealed a statistically significant reduction in operational risks by 20% (p < 0.05) following the implementation of the new control systems compared to baseline conditions. The randomized field trial demonstrated that advanced manufacturing plant systems can effectively mitigate operational risks, leading to enhanced productivity and cost savings. Manufacturing companies in Ghana should consider adopting similar risk reduction strategies to improve their operational performance and competitiveness. manufacturing plants, operational risks, randomised controlled trial, process optimization, predictive maintenance 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 Industrial Machinery Fleet Systems in Ethiopia Through Multilevel Regression Analysis
The industrial machinery fleet systems in Ethiopia have been pivotal to economic growth but face significant operational challenges. A multilevel regression model was employed to analyse data at both the national and regional levels, accounting for variability across different sectors and regions in Ethiopia. The multilevel regression model revealed a significant reduction (p < 0.05) in operational risks by adopting advanced maintenance protocols in machinery fleets. Multilevel regression analysis provided robust insights into the effectiveness of risk mitigation strategies within industrial machinery fleet systems, demonstrating that systematic improvements can lead to substantial reductions in operational inefficiencies. The findings suggest implementing a standardised maintenance schedule and regular training for operators as key interventions to enhance system performance and safety. Industrial Machinery Fleet Systems, Multilevel Regression Analysis, Risk Reduction, 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) 2000 https://creativecommons.org/licenses/by/4.0/
Biomedical Engineering Innovations in Diagnostic Devices across Resource-Limited Settings in Ethiopia
Biomedical engineering innovations in diagnostic devices have become crucial for improving healthcare access in resource-limited settings (RLS). In Ethiopia, these innovations are aimed at enhancing the quality and efficiency of health services. A comparative case study approach was employed, involving qualitative data collection through interviews and surveys. Quantitative analysis assessed device performance metrics and user satisfaction levels using a Likert scale. The findings indicate that the innovative point-of-care diagnostic devices (POCDs) in RLS settings have led to an 80% reduction in patient wait times, with user acceptance rates exceeding 95%. These devices are particularly effective in rural areas where infrastructure is limited. Innovative biomedical engineering solutions for POCDs show significant promise in improving diagnostic accuracy and accessibility in Ethiopia’s RLS. They have the potential to scale up across different regions if supported with appropriate training and maintenance resources. Policy makers should prioritise investment in these devices, alongside robust training programmes for healthcare providers. Continuous monitoring of device performance is essential to ensure their longevity and efficacy in RLS environments. Biomedical Engineering Innovations, Diagnostic Devices, Resource-Limited Settings, 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.