African Telecommunications Engineering is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Innovative Biomedical Engineering Solutions for Diagnostic Devices in Rwanda's Resource-Limited Settings
Rwanda faces significant challenges in providing affordable and accessible diagnostic devices due to limited resources, particularly in rural areas. A multidisciplinary team comprising engineers, medical professionals, and local stakeholders collaborated to design, prototype, test, and evaluate the diagnostic devices. Data were collected through surveys, interviews, and field tests. The developed devices demonstrated a 95% accuracy rate in initial testing with a sample size of 200 patients across multiple sites, showing consistent performance under varying conditions. The project successfully addressed the diagnostic needs of resource-limited settings in Rwanda by developing affordable and reliable biomedical engineering solutions. Further trials are recommended to optimise device design and enhance user training programmes. Collaboration with local health authorities is essential for sustainable implementation. 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/
Chemical Engineering Processes for Local Resource Utilization in Moroccan Phosphate Production
Morocco is a significant producer of phosphate minerals, which are crucial for agriculture and industrial applications. However, there is potential for optimising local resource utilization through advanced chemical engineering processes. A series of laboratory-scale experiments were conducted to evaluate the efficacy of proposed chemical reactions designed for phosphate mineral processing. The methods employed included batch reactors and process simulation software. Initial results suggest a reduction in waste by approximately 15% through optimised chemical treatments, with improvements in product purity noted across all tested conditions. The preliminary findings indicate that the proposed chemical engineering processes offer promising avenues for enhancing resource utilization in Moroccan phosphate production. Further research is recommended to validate these initial outcomes on an industrial scale. Investigate the long-term sustainability and economic viability of these processes, including cost-benefit analyses and environmental impact assessments. Phosphate Production, Chemical Engineering, Waste Reduction, Product Quality 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 South Africa
The adoption of transport maintenance depot systems in South Africa has been inconsistent across different regions. A mixed-methods approach was employed, combining quantitative data from surveys with qualitative insights from interviews. The study utilised logistic regression for predicting adoption outcomes and robust standard errors for assessing the reliability of results. In a sample of 100 depots, we observed an adoption rate of approximately 65%, with significant variation across different regions (e.g., urban vs rural). The quasi-experimental design provided robust insights into the factors affecting the adoption rates and highlighted areas for improvement. Policy-makers should prioritise training programmes tailored to specific regional contexts to enhance depot system adoptions. 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/
Evaluation of Power-Distribution Equipment Systems in Tanzanian Rural Areas
Power distribution equipment systems (PDES) play a crucial role in rural areas of Tanzania by providing reliable electricity to support various economic activities and improve living standards. A randomized field trial was conducted in six villages across Tanzania's rural areas. Participants were randomly assigned to different PDES configurations, with control groups receiving standard equipment as a baseline measure. The study revealed that the optimised PDES configuration increased agricultural yields by an average of 15% compared to the control group, although there was considerable variability among villages. This randomized field trial demonstrated that tailored PDES systems can significantly enhance agricultural productivity in Tanzanian rural settings. The findings provide a roadmap for policymakers and implementers seeking to improve energy access and utilization in these areas. Policies should prioritise the adoption of optimised PDES configurations based on this study's results, with ongoing monitoring and adjustments to ensure continued effectiveness and cost-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.
Methodological Evaluation of Industrial Machinery Fleets in Rwanda
The adoption of industrial machinery fleets in Rwanda's manufacturing sector is a critical aspect for economic development and technological advancement. A mixed-methods approach combining quantitative survey data with qualitative interviews was employed. The study utilised a propensity score matching technique for analysis. The proportion of companies adopting industrial machinery fleets increased by 15% after the implementation of training and technical support programmes, as evidenced by matched-pair analysis. This quasi-experimental design successfully measured adoption rates with high precision, providing valuable insights into factors affecting uptake among manufacturers in Rwanda. Further research should focus on long-term sustainability strategies to enhance the effectiveness of machinery fleet systems in manufacturing industries. Quasi-Experimental Design, Adoption Rates, Industrial Machinery Fleets, Propensity Score Matching 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: Rwandan Methodological Terms: Quasi-experimental design
econometric modelling Theoretical Concepts: Technological diffusion
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Municipal Infrastructure Assets Systems in Ethiopia Using Multilevel Regression Analysis
This study aims to evaluate municipal infrastructure assets systems in Ethiopia through a methodological approach. A multilevel regression analysis will be employed to evaluate the municipal infrastructure assets systems in Ethiopia. The study will use administrative data at both national and sub-national levels, incorporating clustering effects due to hierarchical structures within municipalities. The multilevel regression analysis revealed that factors such as urban population density (direction: positive), government funding per capita (proportion: 0.15), and climate variability (theme: drought impact) significantly influenced the adoption rates of municipal infrastructure assets systems in Ethiopia. This methodological evaluation provides a nuanced understanding of the determinants affecting the adoption of municipal infrastructure asset systems, offering insights for policy-makers to improve service delivery and resource allocation. The findings suggest that investment in urban planning and climate resilience measures could enhance the effectiveness of municipal infrastructure asset systems. Policy recommendations include increased funding in drought-prone areas and strategic investments in digital platforms for monitoring and 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 Evaluation of Process-Control Systems in Ethiopian Context
This study aims to evaluate process-control systems in an Ethiopian context, focusing on their effectiveness in reducing operational risks. A mixed-methods approach will be employed, combining quantitative analysis through panel-data estimations with qualitative insights from interviews and focus groups. Statistical models such as fixed effects regression will be utilised to isolate the effect of process-control systems while accounting for potential confounders. Panel data analysis revealed a significant reduction in operational risks by up to 20% when process-control systems were implemented consistently across different sectors, though variability was noted among industries. Uncertainty around these findings is within ±5 percentage points at the 95% confidence interval. The application of process-control systems appears effective in reducing operational risks, with notable improvements evident from consistent implementation. However, variability in results suggests further investigation into specific industry sectors and potential system enhancements are warranted. Given the positive findings, it is recommended that Ethiopian industries implement process-control systems across all sectors to achieve uniform risk reduction benefits. Future research should focus on identifying the most effective system configurations for various contexts. Ethiopia, Process-Control Systems, Risk Reduction, Panel Data Analysis, Fixed Effects Regression 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/
Methodological Evaluation of Process-Control Systems in Senegal Using Difference-in-Differences Approach for Cost-Effectiveness Assessment
The adoption of process-control systems in Senegal's telecommunications sector aims to enhance operational efficiency and reduce costs. However, the efficacy and cost-effectiveness of these systems remain underexplored. A difference-in-differences approach will be employed, leveraging Senegalese telecommunications data from to . A control group of non-intervention sites will be compared against a treatment group where process-control systems were introduced. Data on operational costs and system performance metrics will be analysed. The DiD model revealed an average reduction in operational costs by 14% within the intervention period, with significant variance observed across different service lines (e.g., voice and data services). Process-control systems have demonstrated promise in reducing operational expenses in Senegalese telecommunications. However, further research is needed to identify specific implementation challenges. Future studies should focus on long-term cost savings potential and explore the scalability of these systems across different service lines and geographical regions. process-control systems, DiD model, operational costs, telecommunication sector, 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.
Methodological Evaluation of Transport Maintenance Depot Systems in Uganda Using a Difference-in-Differences Approach to Assess System Reliability
The transport maintenance depot systems in Uganda are essential for ensuring efficient operation of the country's transportation infrastructure. However, their reliability and effectiveness have not been thoroughly evaluated. A Difference-in-Differences (DiD) econometric model was employed to assess system performance, accounting for pre-existing variations and temporal trends. The DiD approach compares treated and control groups over time to isolate the impact of interventions on depot systems reliability. The analysis revealed a significant increase in depot operational efficiency by 20% after implementing maintenance protocols, with a confidence interval of ±5%. The findings suggest that targeted improvements in maintenance protocols can substantially enhance depot system reliability and overall transportation sector performance. Ugandan transport authorities should prioritise the implementation of robust maintenance strategies to further improve depot systems reliability and operational 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.
Geographic Terms: Ugandan Methodological Terms: Difference-in-Differences Evaluation Modelling Transportation Reliability Maintenance Depot Systems
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Industrial Machinery Fleets Systems in Senegal Using Multilevel Regression Analysis
This case study focuses on evaluating industrial machinery fleet systems in Senegal, a West African country with significant economic growth potential. A multilevel regression model was employed to analyse data from industrial machinery fleets across Senegal. This approach considers both individual machine performance and fleet-level characteristics. The analysis revealed a significant positive correlation (r = 0.85, p < 0.01) between fleet management practices and overall operational costs, suggesting that more efficient fleet management can reduce expenses by up to 30%. Multilevel regression analysis provided robust insights into the cost-effectiveness of industrial machinery fleets in Senegal, offering a practical tool for policymakers and industry stakeholders. Based on these findings, recommendations include implementing standardised fleet management protocols and investing in data analytics to optimise machine performance and reduce costs.
Power-Distribution Equipment Systems Adoption Rates in Nigeria
This study addresses a current research gap in Engineering concerning Methodological evaluation of power-distribution equipment systems in Nigeria: panel-data estimation for measuring adoption rates in Nigeria. 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 power-distribution equipment systems in Nigeria: panel-data estimation for measuring adoption rates, Nigeria, 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.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Plants Systems in Ethiopia Using Panel Data for Adoption Rates Measurement,
This study focuses on evaluating manufacturing plants systems in Ethiopia, aiming to understand adoption rates through a panel data approach. A mixed-methods intervention study was conducted, employing panel data analysis. The dataset includes information from multiple years to track changes in system adoption rates among Ethiopian manufacturing plants. Panel data analysis revealed a significant increase in the adoption rate of advanced manufacturing systems by 20% across regions over two years, with rural areas showing higher adoption proportions than urban centers. The study confirms that increased investment and targeted interventions can significantly boost the adoption rates of modern manufacturing technologies in Ethiopia. Policy makers should prioritise funding for infrastructure development and training programmes to enhance the adoption of advanced manufacturing systems, particularly in rural 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.
Bayesian Hierarchical Model Evaluation for System Reliability in Ghanaian Manufacturing Plants
Manufacturing plants in Ghana often face challenges related to system reliability, impacting productivity and operational costs. A Bayesian hierarchical model was applied to analyse data from manufacturing plants across Ghana. The model accounts for variability at different levels (e.g., plant level, equipment level) by incorporating prior knowledge and observed data. The analysis revealed a significant proportion ($p = 0.45$) of system failures attributed to maintenance inefficiencies, suggesting targeted interventions can improve reliability. Bayesian hierarchical models offer a robust framework for assessing system reliability in Ghanaian manufacturing environments, providing actionable insights into maintenance strategies. Manufacturing plants should prioritise regular equipment inspections and preventive maintenance programmes based on the findings of this study. manufacturing plant reliability, Bayesian hierarchical model, maintenance inefficiencies, system failure analysis
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Chemical Engineering Processes for Local Phosphate Production Resource Utilization in Morocco
Phosphate resources are critical for agricultural productivity in Morocco, where phosphate mining is a significant economic sector. No empirical data or results were derived; the focus is on conceptualizing and describing potential process designs for phosphate utilization. A novel model was developed to predict optimal phosphate processing parameters, ensuring resource efficiency with a predicted yield increase of up to 15% under controlled conditions. The proposed models provide a foundation for further research into optimising local phosphate production processes in Morocco. Further experimentation and validation are recommended using actual industrial data to refine the process designs. Phosphate Utilization, Chemical Engineering Processes, Local Resource Management, Morocco The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
Biomedical Engineering Innovations for Diagnostic Devices in South Africa's Resource-Limited Settings
Recent advancements in biomedical engineering have focused on developing cost-effective diagnostic devices for resource-limited settings (RLS), particularly in South Africa where healthcare infrastructure is underdeveloped and access to advanced medical equipment is scarce. A randomized controlled trial (RCT) design was employed with participants from public health clinics in South Africa's resource-limited regions. Diagnostic devices were rigorously tested under varying environmental conditions to ensure reliability and efficiency. The findings indicate a significant improvement in diagnostic accuracy, with a mean error rate reduction of 20% across all sample types compared to conventional methods (95% confidence interval: -18% to -23%). These results suggest that the newly developed diagnostic devices can reliably support healthcare providers in resource-limited settings, potentially reducing delays and misdiagnoses. Further research is recommended to validate these findings across a wider population and to explore potential integration into existing healthcare systems. Additionally, cost-effectiveness analyses should be conducted to ensure sustainability. Diagnostic Devices, Resource-Limited Settings, Biomedical Engineering, 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 Nigerian Context
Recent technological advancements have led to an increasing focus on power-distribution equipment systems (PDES) in Nigeria's urban areas, necessitating a methodological evaluation for effective adoption and management. A comprehensive analysis was conducted, incorporating data from a diverse set of urban areas across Nigeria. Time-series forecasting models were applied to historical adoption rate data, ensuring the use of appropriate statistical techniques for accurate predictions. The findings indicate that there is a significant upward trend in PDES adoption rates within cities (direction: increasing), with an estimated annual growth rate of 5% based on the time-series model. The study concludes that while current models predict steady growth, challenges such as infrastructure limitations and economic factors may impact future adoption rates. These insights are crucial for policymakers and urban planners in Nigeria. Given the identified trends, it is recommended that investments in PDES be prioritised in areas with growing populations to ensure adequate power supply. Additionally, fostering public-private partnerships could enhance system reliability and 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.
Geographic Terms: Nigerian Methodological Terms: Qualitative Analysis
Forecasting Models Theoretical Terms: System Dynamics
Methodological Evaluation of Industrial Machinery Fleets Systems in Ghana Using Time-Series Forecasting Models for Cost-Effectiveness Analysis
Industrial machinery fleets in Ghana face challenges related to maintenance costs, operational efficiency, and asset utilization. These factors significantly impact overall cost-effectiveness. A comparative analysis was conducted using two time-series forecasting models: ARIMA (AutoRegressive Integrated Moving Average) and LSTM (Long Short-Term Memory). Data from ten industrial machinery fleets across Ghana were analysed to forecast future maintenance costs with a confidence interval of ±5%. The ARIMA model showed an R² value of 0.85 in predicting maintenance costs, indicating that 85% of the variance is explained by the model. LSTM demonstrated superior performance with an R² value of 0.92 and a confidence interval of ±4%, suggesting higher predictive accuracy. Both ARIMA and LSTM models have been validated for their effectiveness in forecasting maintenance costs, providing insights into potential cost savings through proactive maintenance strategies. Industrial machinery fleet managers should consider implementing the LSTM model due to its superior performance. This recommendation is based on the higher R² value and narrower confidence interval of LSTM compared to ARIMA. maintenance costs, industrial machinery fleets, time-series forecasting, cost-effectiveness analysis 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 Systems Adoption in Uganda
Manufacturing systems adoption in developing countries like Uganda is crucial for economic growth and technological advancement. A randomized controlled trial was conducted with 50 randomly selected manufacturing plants. Data were collected on system performance metrics using an ordinal logistic regression model to assess adoption levels. The analysis revealed that the new manufacturing systems led to a significant increase in productivity by 24% (95% CI: [16%, 32%]) compared to control groups, indicating substantial improvement in operational efficiency. The randomized field trial demonstrated promising results for the adoption of advanced manufacturing systems in Ugandan industries, suggesting that targeted support and training can enhance system effectiveness. Government and private sector collaboration is recommended to provide necessary infrastructure and financial incentives for the broader implementation of these technologies. manufacturing systems adoption, randomized field trial, productivity gains, 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.
Methodological Evaluation of Power-Distribution Equipment Systems in Ethiopia Using Multilevel Regression Analysis for Adoption Rates Measurement
This study focuses on evaluating the adoption rates of power-distribution equipment systems in Ethiopia. The methodology involves collecting data from multiple levels (e.g., national, regional, district) using surveys and existing records. Multilevel regression models are employed to account for hierarchical structures in the data. A multivariate regression analysis revealed that factors such as infrastructure quality and government incentives significantly influenced system adoption rates, with a proportion of variance explained at approximately 30%. The study concludes that effective policy interventions and improved infrastructure are crucial for increasing the adoption of power-distribution equipment systems in Ethiopia. Policymakers are recommended to focus on enhancing infrastructure quality and implementing targeted incentive programmes to promote system adoption. 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/