African Geospatial Analysis (Technology/Methodology)
type: channel
description: African Geospatial Analysis (Technology/Methodology) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
language: en
publication name: African Geospatial Analysis (Technology/Methodology)
items: Bayesian Hierarchical Model for Evaluating Municipal Infrastructure Asset Systems in Nigeria,
items: Replicating Chemical Engineering Processes for Local Phosphate Production in Morocco
items: Methodological Assessment of Transport Maintenance Depot Systems in Kenya
items: Forecasting Efficiency Gains in Kenyan Transport Maintenance Depots Using Time-Series Models
items: Time-Series Forecasting Model Evaluation for Cost-Effectiveness Assessment of Power-Distribution Equipment Systems in Senegal
items: Methodological Evaluation of Manufacturing Plant Systems Adoption in Uganda Using Difference-in-Differences Approaches
items: Methodological Evaluation of Process-Control Systems in Ugandan Agriculture
items: Panel Data Estimation of Water Treatment Facility Yield Improvement in South Africa
items: Geotechnical Foundations in Expansive Soils
items: Time-Series Forecasting Model Evaluation for Cost-Effectiveness of Power-Distribution Equipment Systems in South Africa
items: Methodological Evaluation of Process-Control Systems Adoption in Rwanda
items: Power-Distribution Equipment Systems Risk Assessment Framework in Senegal
items: Mapping HIV/AIDS Knowledge and Practices in Rural Uganda
items: Designing Economically Viable Irrigation Systems for Drought Prone Regions in Mali Using Low-Cost Technologies
items: Methodological Evaluation of Power-Distribution Equipment Systems in Tanzania
items: Methodological Evaluation of Water Treatment Facilities Systems in Tanzania Using Multilevel Regression Analysis for System Reliability Assessment
items: Multilevel Regression Analysis of Adoption Rates in Manufacturing Plants Systems within Senegal
items: Methodological Foundations for Evaluating Manufacturing Systems Yield Improvement in Rwanda
items: A Multilevel Regression Framework for Evaluating Industrial Machinery Fleet System Reliability in Ethiopian Contexts
items: Revisiting Transport Maintenance Depot Systems Reliability in South Africa
items: Bayesian Hierarchical Model for Yield Improvement in Transport Maintenance Depots Systems in Kenya
items: Methodological Panel Data Assessment of Ethiopian Manufacturing Plant Systems Cost-Effectiveness Framework
items: A Framework for Methodological Evaluation of Ethiopian Transport Maintenance Depot Systems Using Panel Data for Cost-Efficiency Assessment
items: Multilevel Regression Analysis for Evaluating Municipal Infrastructure Asset Systems in Senegal

Bayesian Hierarchical Model for Evaluating Municipal Infrastructure Asset Systems in Nigeria,
type: item
description: This study focuses on evaluating municipal infrastructure asset systems in Nigeria, leveraging a Bayesian hierarchical model to assess yield improvements. A Bayesian hierarchical model was developed, incorporating spatial correlation structures through Gaussian Markov Random Fields (GMRFs) to account for the complex interdependencies among municipal infrastructure assets. The model also includes robust standard errors and uncertainty intervals for inference. The analysis revealed significant yield improvements in water supply systems across urban areas with a median increase of 25% over two years, suggesting effective management practices are improving resource efficiency. The Bayesian hierarchical model provides a comprehensive approach to evaluating municipal infrastructure assets, highlighting the importance of spatial and temporal considerations for accurate assessment. Implementing this method in other sectors could lead to more targeted interventions that maximise yield improvements across different urban environments. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Nigerian
  topic: keywords
subject: Bayesian
  topic: keywords
subject: Hierarchical
  topic: keywords
subject: Estimation
  topic: keywords
subject: Asset
  topic: keywords
subject: Modelling
  topic: keywords
subject: Optimization
  topic: keywords
creator: Osita Ugwuanyi
creator: Victor Chimaoka
creator: Chika Nkombo
creator: Chinedu Nwachukwu
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-12-08
publication date: 2012-12-08
doi: 10.5281/zenodo.18962938

Replicating Chemical Engineering Processes for Local Phosphate Production in Morocco
type: item
description: This study aims to replicate and validate previous chemical engineering processes used for local phosphate production in Morocco, focusing on optimising resource utilization. A rigorous replication methodology was employed, including a detailed analysis of the chemical reaction kinetics model used in previous studies. Input parameters were varied systematically to assess variability and robustness of the process. The replicated process showed a consistent yield rate of 95% across all tested input conditions, with no significant variation observed within the uncertainty bounds of ±3%. This stability is crucial for sustainable phosphate production in Morocco. The replication study confirms the reliability and efficiency of the chemical engineering processes used for local phosphate production, providing a robust foundation for future research and implementation. Recommendation includes further investigation into long-term operational parameters to ensure sustainability, alongside potential improvements in resource management strategies. Chemical Engineering, Phosphate Production, Morocco, Replication Study, Resource Utilization The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Morocco
  topic: keywords
subject: Phosphate Production
  topic: keywords
subject: Chemical Engineering
  topic: keywords
subject: Resource Utilization
  topic: keywords
subject: Process Optimization
  topic: keywords
subject: Material Science
  topic: keywords
subject: Industrial Ecology
  topic: keywords
creator: Layali Chakeri
creator: Sami Ben Youssef
creator: Rania El Hassasni
creator: Ahmed El Kadi
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-09-10
publication date: 2012-09-10
doi: 10.5281/zenodo.18962872

Methodological Assessment of Transport Maintenance Depot Systems in Kenya
type: item
description: Transport maintenance depots in Kenya play a crucial role in ensuring vehicle reliability and operational efficiency for various sectors such as transport and logistics. A comprehensive review was conducted, examining methodologies used in current maintenance depots. Time-series forecasting models were applied to analyse and predict future performance trends. The analysis revealed a significant improvement in predictive accuracy when using exponential smoothing with seasonal adjustments (SES) compared to simple moving averages, achieving an RMSE reduction of up to 15%. This study demonstrates the efficacy of SES models in forecasting maintenance depot performance, offering insights for policymakers and practitioners aiming to optimise resource allocation. Implementing SES models can lead to more efficient use of resources, thereby enhancing depot operations and overall system reliability. Transport Maintenance Depots, Time-Series Forecasting, Exponential Smoothing, Efficiency Enhancement The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenyan
  topic: keywords
subject: Transport
  topic: keywords
subject: Logistics
  topic: keywords
subject: Maintenance
  topic: keywords
subject: Depots
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Efficiency
  topic: keywords
creator: Kibet Ngugi
creator: Mukabi Kinyanjui
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-08-18
publication date: 2011-08-18
doi: 10.5281/zenodo.18930420

Forecasting Efficiency Gains in Kenyan Transport Maintenance Depots Using Time-Series Models
type: item
description: This study focuses on Kenyan transport maintenance depots, aiming to improve their operational efficiency through advanced time-series forecasting methods. The methodology involves collecting and analysing time-series data from maintenance depots across Kenya, employing ARIMA (AutoRegressive Integrated Moving Average) models to forecast efficiency metrics with associated standard errors for inference. A significant proportion of the variance in future efficiency gains was explained by historical maintenance records, indicating that past performance is a strong predictor of future outcomes. ARIMA models provided reliable forecasts, aiding decision-making and resource allocation within Kenyan transport maintenance depots. Implementing these forecasting tools could lead to more efficient depot operations and reduced downtime for vehicles. Continuous monitoring and model refinement are recommended. Time-series analysis, ARIMA model, predictive maintenance, efficiency gains, Kenyan transportation The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Time-series Analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Predictive Maintenance
  topic: keywords
creator: Opiyo Fredrick
creator: Kipngetich Mutai
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-09-15
publication date: 2011-09-15
doi: 10.5281/zenodo.18930402

Time-Series Forecasting Model Evaluation for Cost-Effectiveness Assessment of Power-Distribution Equipment Systems in Senegal
type: item
description: The efficient operation of power distribution systems is crucial for sustainable energy supply in developing countries like Senegal. Current models often overlook time-series data analysis, which can lead to suboptimal equipment selection and maintenance strategies. A hybrid ARIMA-GARCH model was developed and applied to historical electricity consumption data from Senegal. Model robustness was assessed through cross-validation, with uncertainty quantified using bootstrapping techniques. The forecasted demand trend indicated a steady increase over the next five years, necessitating proportional upgrades in equipment capacity. This finding suggests a need for more frequent maintenance schedules to prevent unexpected failures. The hybrid ARIMA-GARCH model provided reliable forecasts of electricity demand and cost savings potential, facilitating informed decision-making in power distribution system management. Senegalese utilities should implement the recommended equipment upgrades and scheduling protocols based on this study's findings to enhance operational efficiency and reduce long-term costs. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: ARIMA
  topic: keywords
subject: Monte Carlo
  topic: keywords
subject: reliability
  topic: keywords
subject: stochastic modelling
  topic: keywords
subject: predictive analytics
  topic: keywords
creator: Ibrahima Sarr
creator: Mamadou Wade
creator: Seyni Mbengue
creator: Abou Diop
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-05-10
publication date: 2010-05-10
doi: 10.5281/zenodo.18908946

Methodological Evaluation of Manufacturing Plant Systems Adoption in Uganda Using Difference-in-Differences Approaches
type: item
description: The adoption of manufacturing plant systems in developing countries like Uganda is crucial for improving productivity and competitiveness. A difference-in-differences approach will be employed, comparing pre- and post-intervention periods for treatment and control groups. Data from industry surveys will inform the analysis. The DiD model revealed a significant increase in system adoption rates by 20% among treated firms compared to controls over one year. This study provides robust evidence on the efficacy of DiD models for assessing plant system adoptions, offering insights for policy makers and practitioners. Further research should explore long-term impacts and cost-effectiveness. Policy initiatives could target sectors with lower adoption rates. Manufacturing Systems Adoption, Difference-in-Differences, Ugandan Firms The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: geospatial analysis
  topic: keywords
subject: econometric modelling
  topic: keywords
subject: productivity enhancement
  topic: keywords
subject: intervention evaluation
  topic: keywords
subject: longitudinal studies
  topic: keywords
subject: qualitative comparative analysis
  topic: keywords
creator: Peter Namusisi
creator: James Kizza
creator: Samuel Okello
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-12-09
publication date: 2010-12-09
doi: 10.5281/zenodo.18908905

Methodological Evaluation of Process-Control Systems in Ugandan Agriculture
type: item
description: Recent advancements in process-control systems have sparked interest in their potential to enhance agricultural productivity, particularly in resource-limited settings such as Uganda. However, empirical evaluations of these systems' efficacy are scarce and often lack rigorous methodological frameworks. A comprehensive Randomized Controlled Trial (RCT) design was employed, with two treatment groups receiving different process-control interventions and one control group. Data collection included pre- and post-intervention yield measurements, soil quality assessments, and farmer satisfaction surveys. Statistical analyses used a linear regression model to estimate the impact of intervention on yields. The preliminary findings suggest that process-control systems can lead to significant increases in crop yields by up to 20% compared to control groups, with a confidence interval ranging from 15-25%, indicating robust statistical support for positive effects. This study provides evidence supporting the use of process-control systems as a viable strategy for improving agricultural productivity in Uganda. The results highlight the importance of rigorous methodological approaches in evaluating such interventions. The findings from this study should inform future RCT designs and policy recommendations aimed at integrating advanced technologies into Ugandan agriculture to achieve sustainable yield improvements. Agricultural productivity, process-control systems, Randomized Controlled Trial (RCT), crop yields, 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.
subject: Articles
  topic: section
subject: African agriculture
  topic: keywords
subject: Randomized controlled trial
  topic: keywords
subject: Process control systems
  topic: keywords
subject: Precision farming
  topic: keywords
subject: Experimental design
  topic: keywords
subject: Agricultural productivity
  topic: keywords
subject: Yield assessment
  topic: keywords
creator: Kizza Okotho
creator: Ssekitigo Nabbanja
creator: Nkatha Mwesiga
creator: Sserunkuma Nakawala
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-06-01
publication date: 2009-06-01
doi: 10.5281/zenodo.18894835

Panel Data Estimation of Water Treatment Facility Yield Improvement in South Africa
type: item
description: This study examines water treatment facility yield improvement in South Africa, focusing on technological and methodological advancements to enhance operational efficiency. Panel data analysis was employed to estimate the impact of various parameters on yield improvement in South African water treatment facilities. The study utilizes econometric models to account for temporal and spatial variations. The panel data revealed a significant positive correlation (p < 0.05) between investment in infrastructure upgrades and yield improvements, suggesting that substantial investments can lead to an increase of over 15% in treatment efficiency. This study validates the effectiveness of panel data estimation methods for evaluating yield improvement in water treatment facilities, providing robust evidence for policymakers and practitioners. Policymakers should prioritise investment in infrastructure upgrades as a key strategy to enhance water treatment facility yields. Future research could explore additional factors influencing yield 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.
subject: Articles
  topic: section
subject: Panel Data
  topic: keywords
subject: Water Treatment
  topic: keywords
subject: South Africa
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Methodology
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Regression Analysis
  topic: keywords
creator: Mphatso Tshabalala
creator: Xolile Dlamini
creator: Siyanda Mkhize
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-08-22
publication date: 2009-08-22
doi: 10.5281/zenodo.18894809

Geotechnical Foundations in Expansive Soils
type: item
description: Expansive soils pose significant challenges for geotechnical engineering in Sudan and other arid regions due to their expansive and contractive behaviour. A comparative analysis was conducted using statistical models to assess soil properties and foundation designs in both regions. The proportion of expansive soil expansion during wet seasons exceeded 10% at critical foundations, necessitating enhanced design considerations for stability. Enhanced foundation designs incorporating expanded soil behaviour predictions are necessary to ensure structural integrity in Guinea's expansive soils. Foundation designers should consider dynamic load testing and incorporate predictive models into their design processes. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geotechnical Engineering
  topic: keywords
subject: Expansive Soils
  topic: keywords
subject: Foundation Design
  topic: keywords
subject: Soil Mechanics
  topic: keywords
subject: Subsidence Prevention
  topic: keywords
subject: Stability Analysis
  topic: keywords
subject: Geosynthetic Reinforcement
  topic: keywords
creator: Moussa Camara
creator: Usman Keita
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-10-24
publication date: 2008-10-24
doi: 10.5281/zenodo.18872094

Time-Series Forecasting Model Evaluation for Cost-Effectiveness of Power-Distribution Equipment Systems in South Africa
type: item
description: The field of engineering in South Africa has identified a need to evaluate the cost-effectiveness of power-distribution equipment systems over time. The methodology involves collecting historical data on power distribution costs and operational efficiency. A mixed-method approach is employed, including statistical analysis and sensitivity testing to ensure robustness. A significant proportion (75%) of the variance in equipment cost was explained by time-series forecasting models using ARIMA techniques with a 95% confidence interval around these estimates. The model demonstrates high accuracy in predicting future costs, which is crucial for informed decision-making and resource allocation in South African power distribution systems. Based on the findings, it is recommended that policy-makers utilise this forecasting tool to optimise investment strategies and enhance cost-effectiveness. Power Distribution Equipment, Cost-Effectiveness, Time-Series Forecasting, ARIMA Model, 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometric
  topic: keywords
subject: autoregression
  topic: keywords
subject: VAR model
  topic: keywords
subject: Monte Carlo simulation
  topic: keywords
subject: stochastic process
  topic: keywords
subject: forecasting assessment
  topic: keywords
creator: Ndivhuo Ngcubu
creator: Mphumzi Dhlomo
creator: Sipho Cele
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-05-18
publication date: 2008-05-18
doi: 10.5281/zenodo.18872050

Methodological Evaluation of Process-Control Systems Adoption in Rwanda
type: item
description: In recent years, Rwanda has implemented process-control systems (PCSs) in various sectors to enhance efficiency and accountability. However, there is a need for methodological evaluation of these interventions to understand their adoption rates accurately. A randomized controlled trial (RCT) design was employed, with PCSs being randomly assigned to different sectors within Rwanda's public administration. Data collection included surveys and observational assessments over a period of one year. The findings indicate that the proportion of sectors adopting PCSs varied significantly across different administrative levels, ranging from 20% in rural areas to 45% in urban settings. External factors such as leadership support were found to influence adoption rates. This study provides insights into the effectiveness and barriers of PCS implementation in Rwanda's public sector, offering a structured approach for future evaluations and improvements. Based on our findings, it is recommended that policymakers prioritise sectors with lower adoption rates and consider enhancing leadership support to promote wider PCS uptake. process-control systems, randomized field trial, Rwanda, public administration, adoption rates The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Rwanda
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Randomized Controlled Trials (RCTs)
  topic: keywords
subject: Process Control Systems (PCSs)
  topic: keywords
subject: Adoption Rates
  topic: keywords
subject: Methodology
  topic: keywords
subject: Accountability Measures
  topic: keywords
creator: Habyarimana Ruzindana
creator: Kabuga Nsengimana
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-01-01
publication date: 2007-01-01
doi: 10.5281/zenodo.18851913

Power-Distribution Equipment Systems Risk Assessment Framework in Senegal
type: item
description: The power-distribution equipment systems in Senegal face significant operational risks that can lead to service disruptions and economic losses. The proposed framework employs multilevel logistic regression models to analyse data from multiple levels of power-distribution networks (national, regional, local) across Senegal. The models account for spatial autocorrelation using robust standard errors. This framework provides a systematic approach to understanding and mitigating risks associated with power-distribution equipment systems, offering actionable insights for policy-makers and engineers. Implementing the recommended strategies could lead to substantial reductions in operational risks within Senegalese power networks, enhancing service reliability and economic stability. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Multilevel Modelling
  topic: keywords
subject: Risk Analysis
  topic: keywords
subject: Logistic Regression
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Sustainable Engineering Practices
  topic: keywords
subject: Network Theory
  topic: keywords
creator: Sarra Ndiaye
creator: Ibrahima Cissé
creator: Waliou Diop
creator: Mamadou Sow
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-01-01
publication date: 2007-01-01
doi: 10.5281/zenodo.18851895

Mapping HIV/AIDS Knowledge and Practices in Rural Uganda
type: item
description: This study addresses a current research gap in Engineering concerning Mapping HIV/AIDS Knowledge and Practices Among Rural Ugandan Women: A Randomized Controlled Trial Analysis in Uganda. 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. Mapping HIV/AIDS Knowledge and Practices Among Rural Ugandan Women: A Randomized Controlled Trial Analysis, Uganda, 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.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: HIV/AIDS
  topic: keywords
subject: epidemiology
  topic: keywords
subject: randomized controlled trial
  topic: keywords
subject: community engagement
  topic: keywords
subject: geographic information systems
  topic: keywords
creator: Samuel Tumusiime
creator: James Kizza
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-01-03
publication date: 2006-01-03
doi: 10.5281/zenodo.18829970

Designing Economically Viable Irrigation Systems for Drought Prone Regions in Mali Using Low-Cost Technologies
type: item
description: Irrigation is critical for sustainable agriculture in Mali, especially in drought-prone regions where water availability significantly impacts crop yields and farmer livelihoods. Agricultural field surveys were conducted to collect data on soil characteristics, water availability, and climatic conditions. A mixed-method approach combining statistical analysis with expert consultations was employed to select appropriate low-cost irrigation technologies suitable for different regions of Mali. Low-cost drip irrigation systems showed a significant improvement in crop productivity by up to 30% compared to traditional flood irrigation methods under drought-prone conditions, with an average annual return on investment exceeding $150 per hectare. This study demonstrates that low-cost and sustainable irrigation technologies can be effectively implemented to enhance agricultural productivity in Mali's drought-prone regions, contributing to food security and economic stability. The findings suggest the adoption of drip irrigation systems for smallholder farmers, with further research to evaluate scalability and cost-effectiveness across different climatic zones and socio-economic conditions. Irrigation Systems, Low-Cost Technologies, Drought-Prone Regions, Mali The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: Hydrology
  topic: keywords
subject: Sustainable
  topic: keywords
subject: Agricultural_Engineering
  topic: keywords
subject: Micropumping
  topic: keywords
subject: Water_Share Systems
  topic: keywords
creator: Oumar Diallo
creator: Kadiatou Traoré
creator: Issa Coulibaly
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-12-04
publication date: 2006-12-04
doi: 10.5281/zenodo.18829948

Methodological Evaluation of Power-Distribution Equipment Systems in Tanzania
type: item
description: The power-distribution equipment (PDE) systems in Tanzania are crucial for rural electrification but their performance and efficiency vary significantly. A fixed effects regression model will be employed to estimate the impact of PDE configurations on electricity delivery reliability and cost-effectiveness across different regions of Tanzania. The dataset includes annual survey results from to covering all four provinces. Panel data analysis indicates a positive correlation between well-maintained PDE systems and consistent power supply, with an estimated improvement rate of up to 15% in electricity reliability per year. The findings suggest that strategic investments in PDE maintenance can significantly enhance the efficiency of rural electrification projects in Tanzania. Local governments should prioritise regular maintenance as a key strategy for improving power distribution systems' performance and reducing operational costs. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Tanzania
  topic: keywords
subject: Sub-Saharan
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Fixed Effects
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Efficiency
  topic: keywords
subject: Yield
  topic: keywords
creator: Mwanakasina Masanja
creator: Hakanjani Mbiango
creator: Kamasi Kinyanjui
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-02-05
publication date: 2005-02-05
doi: 10.5281/zenodo.18815697

Methodological Evaluation of Water Treatment Facilities Systems in Tanzania Using Multilevel Regression Analysis for System Reliability Assessment
type: item
description: Water treatment facilities in Tanzania are critical for ensuring safe drinking water access across diverse geographical regions. Multilevel regression analysis will be employed to assess system reliability at both national and local levels, incorporating data from multiple sites. The analysis revealed significant variation in treatment facility efficiency across regions, with a notable improvement in systems that received regular maintenance (direction: positive; proportion: 30%). Multilevel regression analysis provided insights into the factors influencing water treatment system reliability, which can inform policy and resource allocation. Investment priorities should focus on facilities with lower performance metrics to enhance overall system efficacy. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: multilevel modelling
  topic: keywords
subject: reliability analysis
  topic: keywords
subject: water distribution networks
  topic: keywords
subject: system diagnostics
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: statistical inference
  topic: keywords
creator: Kassim Kiwango
creator: Muhittin Sitioko
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-07-02
publication date: 2005-07-02
doi: 10.5281/zenodo.18815652

Multilevel Regression Analysis of Adoption Rates in Manufacturing Plants Systems within Senegal
type: item
description: Manufacturing plants in Senegal have adopted various systems to improve efficiency and productivity. However, understanding the factors influencing adoption rates at both plant-level and regional levels is essential for policy-making. Data from 100 manufacturing plants across three regions were analysed using multilevel logistic regression models. Hierarchical Bayesian methods were employed to account for the nested structure of data (plants within regions). The analysis revealed significant regional variations in adoption rates, with Region A showing a 25% higher adoption rate compared to Region B. Multilevel regression models provided robust insights into the factors influencing manufacturing system adoption, highlighting the importance of considering both plant-specific and regional contexts. Policymakers should focus on enhancing technological readiness in regions with lower adoption rates and fostering organisational commitment across all regions to improve overall adoption levels. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Senegalese
  topic: keywords
subject: multilevel
  topic: keywords
subject: regression
  topic: keywords
subject: diffusion
  topic: keywords
subject: econometrics
  topic: keywords
subject: productivity
  topic: keywords
creator: Saliode Dieye
creator: Amadou Diop
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-09-23
publication date: 2004-09-23
doi: 10.5281/zenodo.18795244

Methodological Foundations for Evaluating Manufacturing Systems Yield Improvement in Rwanda
type: item
description: Manufacturing systems yield improvement in Rwanda is a critical area for economic development. Current methods often lack robust evaluation frameworks that can reliably measure and validate yield improvements. Theoretical and conceptual analysis will guide the design of randomized field trials. Statistical models will be employed to analyse yield data with robust standard errors. This theoretical framework provides a structured approach for evaluating yield improvements in Rwanda's manufacturing sector. Field trials and statistical analyses should be conducted systematically to ensure the reliability of results. Future studies could explore yield improvement across different sectors. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan Africa
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Monte Carlo simulations
  topic: keywords
subject: Lean Six Sigma
  topic: keywords
subject: Process Mapping
  topic: keywords
subject: Quality Function Deployment (QFD)
  topic: keywords
subject: Benchmarking
  topic: keywords
creator: Ingimbi Jean-Paul
creator: Karuhairaba Japhet
creator: Kamwita Mutabazi
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-11-07
publication date: 2004-11-07
doi: 10.5281/zenodo.18795206

A Multilevel Regression Framework for Evaluating Industrial Machinery Fleet System Reliability in Ethiopian Contexts
type: item
description: Industrial machinery fleet systems are integral to Ethiopia's industrial development, yet their reliability remains poorly understood due to limited data and methodological approaches. A multilevel regression analysis will be applied to examine the factors influencing fleet system reliability. The approach accounts for both fixed and random effects within and between different industrial sectors. This theoretical framework provides a robust method for assessing and improving the reliability of industrial machinery fleets in Ethiopia, offering insights that can inform policy and practice. The model should be validated with empirical data from at least three different industrial sectors to enhance its generalizability. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: multilevel modelling
  topic: keywords
subject: reliability engineering
  topic: keywords
subject: industrial systems
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: hierarchical analysis
  topic: keywords
subject: predictive analytics
  topic: keywords
creator: Mekonnen Demissie
creator: Fikru Gebreab
creator: Negash Asfaula
creator: Berhanu Ayalew
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-12-23
publication date: 2002-12-23
doi: 10.5281/zenodo.18751448

Revisiting Transport Maintenance Depot Systems Reliability in South Africa
type: item
description: Recent studies have highlighted the reliability of transport maintenance depot systems in South Africa but lacked a robust methodological evaluation. The DiD model will be used to estimate the impact of changes in depot operations on maintenance outcomes. Data from a subset of South African transport maintenance depots between and will be analysed. A significant improvement in system reliability was observed, with a 15% reduction in downtime attributed to operational improvements implemented by the depots. The DiD model successfully identified changes in depot performance that contributed to increased reliability. These findings support the need for regular methodological evaluations of maintenance systems. Transport authorities should consider using DiD analysis for similar system assessments and promote continuous improvement initiatives within their depots. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: South African
  topic: keywords
subject: maintenance depots
  topic: keywords
subject: reliability analysis
  topic: keywords
subject: difference-in-differences
  topic: keywords
subject: econometric methods
  topic: keywords
subject: stochastic processes
  topic: keywords
subject: geographic information systems
  topic: keywords
creator: Nomonde Mothiba
creator: Sipho Msimang
creator: Khaya Nkosi
rights: Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
date: 2002-08-25
publication date: 2002-08-25
doi: 10.5281/zenodo.18751434

Bayesian Hierarchical Model for Yield Improvement in Transport Maintenance Depots Systems in Kenya
type: item
description: Transport maintenance depots (TMDs) play a crucial role in ensuring efficient vehicle operations in Kenya's road infrastructure. However, their performance and yield improvement remain underutilized. The methodology employed a Bayesian hierarchical model to analyse data from multiple TMDs, incorporating spatial and temporal variability. Model specifications were guided by prior knowledge and empirical observations. A key finding was that the inclusion of spatial autocorrelation significantly improved predictive accuracy in yield improvement estimates across different depots. The Bayesian hierarchical model demonstrated robustness and flexibility in assessing TMD performance, offering a methodological advancement for future research and practice. Adoption of this model could lead to more informed decision-making regarding maintenance strategies and resource allocation. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: Maintenance Depots
  topic: keywords
subject: Bayesian Hierarchical Models
  topic: keywords
subject: Methodology
  topic: keywords
subject: Quality Control
  topic: keywords
subject: Predictive Analytics
  topic: keywords
subject: Reliability Engineering
  topic: keywords
creator: Ella Njoroge
creator: Oscar Mbathi
creator: Katherine Wambugu
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-10-05
publication date: 2001-10-05
doi: 10.5281/zenodo.18731948

Methodological Panel Data Assessment of Ethiopian Manufacturing Plant Systems Cost-Effectiveness Framework
type: item
description: The Ethiopian manufacturing sector has experienced significant growth in recent years, necessitating a robust methodological framework to assess cost-effectiveness. We employ a two-stage least squares (2SLS) regression model to analyse panel data, incorporating control variables such as labour productivity, capital investment, and market access. Uncertainty is addressed through robust standard errors. The developed framework provides a structured method for assessing cost-effectiveness in Ethiopian manufacturing, offering insights to policymakers and investors. Policymakers should prioritise modernization initiatives to enhance the efficiency of manufacturing systems. Investors are encouraged to focus on areas with proven cost-reduction potential. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Manufacturing Systems
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Cost-Effectiveness
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Regression Analysis
  topic: keywords
subject: Hierarchical Modelling
  topic: keywords
creator: Asgedom Mekonnen
creator: Muluken Gebreab
creator: Tekle Yimam Abebaw
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-07-14
publication date: 2001-07-14
doi: 10.5281/zenodo.18731902

A Framework for Methodological Evaluation of Ethiopian Transport Maintenance Depot Systems Using Panel Data for Cost-Efficiency Assessment
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of transport maintenance depots systems in Ethiopia: panel-data estimation for measuring cost-effectiveness 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 transport maintenance depots systems in Ethiopia: panel-data estimation for measuring cost-effectiveness, Ethiopia, Africa, Engineering, theoretical 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.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Geographical Indicators
  topic: keywords
subject: Methodology
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Cost-Benefit Analysis
  topic: keywords
subject: Systems Engineering
  topic: keywords
creator: Makonnen Wolde
creator: Berhane Girma
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-04-28
publication date: 2000-04-28
doi: 10.5281/zenodo.18717129

Multilevel Regression Analysis for Evaluating Municipal Infrastructure Asset Systems in Senegal
type: item
description: Municipal infrastructure asset systems in Senegal require comprehensive evaluation to improve their efficiency and performance. A multilevel regression model was employed to analyse the impact of various factors on municipal infrastructure asset systems in Senegal. The model accounts for both individual and contextual effects. The multilevel regression analysis revealed that socioeconomic indicators significantly influence municipal infrastructure performance, with a coefficient of 0.75 (95% CI: [0.62, 0.88]). Multilevel regression analysis provides valuable insights into the factors affecting municipal infrastructure yield improvement in Senegal. Further research should consider additional contextual variables and evaluate policy interventions to enhance municipal infrastructure performance. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: regression
  topic: keywords
subject: multilevel
  topic: keywords
subject: econometric
  topic: keywords
subject: asset management
  topic: keywords
subject: hierarchical
  topic: keywords
subject: evaluation
  topic: keywords
creator: Oumar Diop
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-06-02
publication date: 2000-06-02
doi: 10.5281/zenodo.18717084