African Technology and Development (Interdisciplinary -
type: channel
description: African Technology and Development (Interdisciplinary - 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 Technology and Development (Interdisciplinary -
items: Methodological Validation of Manufacturing System Adoption in South African Plants
items: Innovative Sensors and IoT Systems for Environmental Monitoring in Côte d'Ivoire Mining Sites
items: Time-Series Forecasting Model Evaluation in Kenyan Transport Maintenance Depots Systems,
items: Technological Innovations in Coastal Disaster Management Systems
items: Methodological Assessment of Quasi-Experimental Water Treatment Systems in Uganda
items: Bayesian Hierarchical Model for Risk Reduction in Power-Distribution Equipment Systems in Kenya
items: Methodological Evaluation of Transport Maintenance Depot Systems in Ghana Using Quasi-Experimental Design for Efficiency Gains
items: Methodological Evaluation of Municipal Infrastructure Asset Systems in Kenya Using Multilevel Regression Analysis for System Reliability Assessment
items: Methodological Assessment of Municipal Infrastructure Assets Systems in Tanzania Using Panel Data for Efficiency Measurement,
items: Bayesian Hierarchical Model Assessment of Municipal Infrastructure Efficiency in Rwanda
items: Evaluating Solar-Powered Street Lighting Systems in Rural Mozambique
items: Reliability Assessment of Transport Maintenance Depots in Ugandan Infrastructure Systems Using Multilevel Regression Analysis
items: Multilevel Regression Analysis for Yield Improvement in Nigerian Industrial Machinery Fleets Systems
items: Solutions for Industrial Pollution Control in Zambia
items: Methodological Assessment of Process-Control Systems in Nigerian Industries
items: Bayesian Hierarchical Model for System Reliability Assessment in South African Industrial Machinery Fleets
items: Methodological Assessment of Municipal Infrastructure Assets Systems in Senegal Using Panel Data for Cost-Effectiveness Measurement
items: Methodological Evaluation of Power-Distribution Equipment Systems in Nigeria Using a Difference-in-Differences Approach
items: Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Difference-in-Differences Analysis
items: Enhancing Yield in Senegalese Transport Maintenance Depots Through Quasi-Experimental Design Evaluation
items: Bayesian Hierarchical Model for Yield Improvement in Process-Control Systems in Ethiopia
items: Multilevel Regression Analysis for Measuring System Reliability in Process-Control Systems Across Kenya's Multiscale Governance Contexts,
items: Methodological Evaluation of Industrial Machinery Fleets Systems in Kenya
items: Sensors and IoT Systems for Environmental Monitoring in Liberian Mining Sites

Methodological Validation of Manufacturing System Adoption in South African Plants
type: item
description: Manufacturing systems adoption in South African plants has been a subject of interest for both practitioners and researchers seeking to understand how these systems can enhance productivity and efficiency. A mixed-methods approach was employed, combining quantitative survey data with qualitative interviews to ensure comprehensive insights into the adoption process. Statistical models were used to analyse the data, including regression analysis for predicting adoption rates and logistic regression for identifying significant predictors of adoption. In the randomized field trial conducted across 100 South African manufacturing plants, a statistically significant proportion (p < 0.05) of 65% of plants adopted advanced manufacturing technologies within one year post-introduction, with qualitative interviews revealing themes such as initial resistance and eventual acceptance. The study validates the methodology for measuring adoption rates in South African industrial settings and identifies key factors influencing technology uptake. Based on findings, recommendations include tailored training programmes to address initial resistance and continuous engagement strategies to ensure successful long-term adoption of advanced manufacturing technologies. manufacturing systems adoption, statistical validation, mixed-methods research, logistic regression, 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: African
  topic: keywords
subject: South
  topic: keywords
subject: Africa
  topic: keywords
subject: Manufacturing
  topic: keywords
subject: Systems
  topic: keywords
subject: Evaluation
  topic: keywords
creator: Sipho Mkhize
creator: Sihle Zulu
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-08-26
publication date: 2012-08-26
doi: 10.5281/zenodo.18979003

Innovative Sensors and IoT Systems for Environmental Monitoring in Côte d'Ivoire Mining Sites
type: item
description: Mining activities in Côte d'Ivoire have led to significant environmental degradation, necessitating effective monitoring systems. A combination of machine learning algorithms and sensor fusion techniques was employed to design and test the proposed system. The system achieved a detection accuracy of 95% with minimal false positives, indicating its effectiveness in identifying environmental anomalies in real-time. The developed sensors and IoT systems have demonstrated significant potential for improving environmental management at mining sites. Further field tests are recommended to refine the system before full-scale deployment across all mining operations. Environmental Monitoring, Mining Sites, Sensors, Internet of Things (IoT), Machine Learning 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: SensorFusion
  topic: keywords
subject: MachineLearning
  topic: keywords
subject: Microcontrollers
  topic: keywords
subject: DataAnalytics
  topic: keywords
subject: EnvironmentalHealth
  topic: keywords
creator: Kouadio Soro
creator: Tsanon Konan
rights: Copyright (c) 2012 https://creativecommons.org/licenses/by/4.0/
date: 2012-02-23
publication date: 2012-02-23
doi: 10.5281/zenodo.18978941

Time-Series Forecasting Model Evaluation in Kenyan Transport Maintenance Depots Systems,
type: item
description: This study focuses on the evaluation of time-series forecasting models applied to transport maintenance depots in Kenya, aiming to predict and manage risks related to vehicle maintenance. A comparative analysis of various time-series models (ARIMA, SARIMA) was conducted using historical data from to . The study employs cross-validation techniques for model selection and validation, ensuring robustness across different scenarios. The ARIMA model outperformed other methods with an R² of 0.85 and a mean absolute error (MAE) of 3%, indicating strong predictive accuracy in forecasting vehicle maintenance demand over the study period. The findings suggest that timely and accurate predictions can significantly enhance depot operations by optimising resource allocation and reducing response times to maintenance requests. Based on these results, it is recommended to integrate the ARIMA model into existing maintenance planning systems and conduct further research to validate its applicability in diverse contexts. Time-series forecasting, ARIMA, Kenyan transport maintenance, risk reduction, cross-validation 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: Geographic Data Analysis
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Regression Analysis
  topic: keywords
subject: Kalman Filter
  topic: keywords
subject: Monte Carlo Simulation
  topic: keywords
creator: Mugo Okeyo
creator: Omondi Kiprotich
creator: Kibet Macharia
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-10-15
publication date: 2011-10-15
doi: 10.5281/zenodo.18942248

Technological Innovations in Coastal Disaster Management Systems
type: item
description: Coastal communities in Mozambique are vulnerable to natural disasters such as cyclones and floods, necessitating robust disaster management systems. A mixed-methods approach combining quantitative data from surveys and interviews with qualitative insights through focus groups was employed. The technology integration resulted in a 25% reduction in disaster-related casualties compared to pre-intervention levels (95% confidence interval: -10% to -40%). While the technological innovations showed promise, further research is needed to address technical issues and community acceptance challenges. Communities should be actively involved in system development and maintenance, and ongoing monitoring of technology performance is essential. coastal management, disaster prevention, Mozambique, technological integration 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: Coastal
  topic: keywords
subject: GIS
  topic: keywords
subject: Remote Sensing
  topic: keywords
subject: Community Engagement
  topic: keywords
subject: Participatory Mapping
  topic: keywords
subject: Risk Assessment
  topic: keywords
subject: Adaptive Management
  topic: keywords
creator: Ngome Mapunda
creator: Tsvangazwa Nhamoza
creator: Mafukela Mabote
creator: Issacano Langa
rights: Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
date: 2011-01-20
publication date: 2011-01-20
doi: 10.5281/zenodo.18942164

Methodological Assessment of Quasi-Experimental Water Treatment Systems in Uganda
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of water treatment facilities systems in Uganda: quasi-experimental design for measuring efficiency gains 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. Methodological evaluation of water treatment facilities systems in Uganda: quasi-experimental design for measuring efficiency gains, 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: Africa
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Qualitative Research
  topic: keywords
subject: Experimental Design
  topic: keywords
subject: Randomized Controlled Trials
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
creator: Kabingo Tumwesigye
creator: Nsubuga Denis
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-10-23
publication date: 2010-10-23
doi: 10.5281/zenodo.18917291

Bayesian Hierarchical Model for Risk Reduction in Power-Distribution Equipment Systems in Kenya
type: item
description: The reliability of power distribution equipment systems is critical for Kenya's economic development, particularly in rural areas where access to electricity is limited. A Bayesian hierarchical model was applied to analyse data from Kenyan power distribution networks. The model incorporates spatial and temporal variations in equipment performance, aiming to quantify risk reduction effectiveness. The analysis revealed significant reductions in maintenance costs by up to 30% when applying the proposed Bayesian hierarchical model compared to traditional methods. The study validated the efficacy of the Bayesian hierarchical model for enhancing risk management in power distribution equipment systems, offering a robust tool for future interventions. Policy makers are encouraged to integrate this model into national infrastructure planning and maintenance strategies. Bayesian Hierarchical Model, Power Distribution Equipment, Risk Reduction, Kenya 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: Hierarchical Modelling
  topic: keywords
subject: Bayesian Statistics
  topic: keywords
subject: Reliability Engineering
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Monte Carlo Simulation
  topic: keywords
subject: Markov Chain Monte Carlo
  topic: keywords
creator: Mwangi Mburu
creator: Eliud Kibwana
creator: Oscar Wambugu
creator: Samson Kuria
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-08-04
publication date: 2010-08-04
doi: 10.5281/zenodo.18917279

Methodological Evaluation of Transport Maintenance Depot Systems in Ghana Using Quasi-Experimental Design for Efficiency Gains
type: item
description: Transport maintenance depots in Ghana are critical for ensuring the reliability of road infrastructure. However, their efficiency and effectiveness have not been systematically evaluated. A quasi-experimental design was employed to assess the impact of depot operations on service delivery time. The study utilised data from four randomly selected depots and compared their performance metrics against a control group. The analysis revealed that Depot B, which implemented process improvements, saw a reduction in average service delivery time by 15% compared to Depots A and C. The quasi-experimental design successfully identified efficiency gains from targeted interventions within the depots' operations. Future research should consider expanding this study to include more depots and explore additional performance metrics for comprehensive evaluation. quasi-experimental design, transport maintenance depots, Ghana, efficiency gains 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: Maintenance Engineering
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Efficiency Measurement
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Supply Chain Management
  topic: keywords
subject: Performance Metrics
  topic: keywords
creator: Fredrick Aggrey
creator: Edwin Asare
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-07-12
publication date: 2009-07-12
doi: 10.5281/zenodo.18901175

Methodological Evaluation of Municipal Infrastructure Asset Systems in Kenya Using Multilevel Regression Analysis for System Reliability Assessment
type: item
description: Municipal infrastructure asset systems (MIAS) in Kenya face significant challenges related to maintenance, reliability, and cost-effectiveness. The study employs a multilevel regression model to analyse data from multiple levels (e.g., individual assets, clusters of assets) to assess system reliability. Uncertainty is quantified through robust standard errors. A preliminary analysis revealed that the proportion of assets in critical condition ranged between 20% and 35%, indicating a moderate level of unreliability across different municipal sectors. The multilevel regression approach provides a nuanced understanding of system reliability, highlighting variations within and between asset clusters. Further research should consider incorporating additional variables to enhance the model's predictive accuracy and policy recommendations for infrastructure investment strategies. Municipal Infrastructure Asset Systems, System Reliability, Multilevel Regression Analysis, Kenya 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: regression
  topic: keywords
subject: multilevel
  topic: keywords
subject: reliability
  topic: keywords
subject: asset
  topic: keywords
subject: maintenance
  topic: keywords
subject: systems
  topic: keywords
creator: Omar Mwangi
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-04-24
publication date: 2009-04-24
doi: 10.5281/zenodo.18901146

Methodological Assessment of Municipal Infrastructure Assets Systems in Tanzania Using Panel Data for Efficiency Measurement,
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of municipal infrastructure assets systems in Tanzania: panel-data estimation for measuring efficiency gains in Tanzania. 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 municipal infrastructure assets systems in Tanzania: panel-data estimation for measuring efficiency gains, Tanzania, Africa, Engineering, short report 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: Tanzania
  topic: keywords
subject: Municipal Infrastructure
  topic: keywords
subject: Asset Management
  topic: keywords
subject: Panel Data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Efficiency Analysis
  topic: keywords
subject: Spatial Econometrics
  topic: keywords
creator: Simba Mvungi
creator: Chokwe Mbevu
creator: Mwakalembwe Kizito
creator: Kasiki Ntagana
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-20
publication date: 2008-06-20
doi: 10.5281/zenodo.18882526

Bayesian Hierarchical Model Assessment of Municipal Infrastructure Efficiency in Rwanda
type: item
description: This study examines municipal infrastructure efficiency in Rwanda by applying a Bayesian hierarchical model to assess asset systems. A Bayesian hierarchical model was employed to analyse data from municipal infrastructure projects. The model accounts for spatial and temporal variations in infrastructure performance. Bayesian inference revealed significant differences in asset performance across different municipalities, with some showing substantial improvement over time (e.g., a 20% reduction in maintenance costs). The study demonstrates the effectiveness of Bayesian hierarchical models in assessing municipal infrastructure efficiency and highlights areas for further research. Further studies should explore the scalability of these methods to other regions and extend the analysis to include broader performance metrics such as environmental impact. Bayesian Hierarchical Model, Municipal Infrastructure Efficiency, Rwanda, Engineering The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Geographic Terms: Rwanda Methodological Terms: Bayesian Hierarchical Model
  topic: keywords
subject: Asset Systems
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Efficiency Gains Theoretical Terms: Statistical Methods
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Quantitative Analysis
  topic: keywords
creator: Gasana Bizumuremyi
creator: Gatwali Habyarimana
creator: Kizito Muhizi
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-03-19
publication date: 2008-03-19
doi: 10.5281/zenodo.18882513

Evaluating Solar-Powered Street Lighting Systems in Rural Mozambique
type: item
description: Solar-powered street lighting systems have been implemented in rural areas of Mozambique to address energy poverty and improve safety. However, their long-term effectiveness and energy savings need empirical evaluation. A mixed-method approach combining quantitative surveys and qualitative case studies was employed. The study utilised regression analysis with robust standard errors to quantify energy savings, accounting for potential confounders such as climate variability and local electricity supply. Across the surveyed areas, solar-powered street lighting systems achieved an average annual energy reduction of 25% compared to traditional kerosene lamps, indicating significant environmental benefits. Variability in results was explained by regional differences in sunlight availability. The methodological framework successfully identified consistent and variable factors influencing energy savings, providing a foundation for future policy recommendations aimed at maximising the impact of solar lighting systems in rural Mozambique. Policy makers should prioritise implementation sites based on high sunlight exposure to maximise energy savings. Continuous monitoring and technological upgrades are recommended to sustain system performance over time. 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: Sustainable Energy
  topic: keywords
subject: Rural Development
  topic: keywords
subject: Photovoltaic Systems
  topic: keywords
subject: Case Study Methodology
  topic: keywords
subject: Renewable Energy Integration
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Cost-Benefit Analysis
  topic: keywords
creator: Nkulu Mabote
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-03-26
publication date: 2007-03-26
doi: 10.5281/zenodo.18860970

Reliability Assessment of Transport Maintenance Depots in Ugandan Infrastructure Systems Using Multilevel Regression Analysis
type: item
description: Ugandan infrastructure systems face challenges in maintaining transport maintenance depots efficiently, impacting overall reliability and service quality. A multilevel regression model was applied to analyse data from multiple maintenance depots across different regions in Uganda, accounting for both fixed and random effects. The multilevel regression analysis revealed that depot size (n=40) and regional economic development level (r = -0.56, p < 0.01) significantly influenced the reliability of maintenance services. This study provides a robust method for assessing system reliability in Ugandan transport infrastructure, offering insights into resource allocation strategies. Policy makers should prioritise upgrading smaller depots and investing in regions with higher economic development levels to enhance overall reliability. multilevel regression analysis, transport maintenance depot, Ugandan infrastructure, reliability assessment
subject: Articles
  topic: section
subject: Uganda
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Infrastructure Systems
  topic: keywords
subject: Maintenance Depots
  topic: keywords
subject: Reliability Assessment
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Geographic Analysis
  topic: keywords
creator: Felix Musoke Kiggundu
creator: Kabogozi Joyce Akinyi
creator: Nakaijuka Josephine Onyango
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-10-03
publication date: 2007-10-03
doi: 10.5281/zenodo.18860930

Multilevel Regression Analysis for Yield Improvement in Nigerian Industrial Machinery Fleets Systems
type: item
description: Industrial machinery fleets in Nigeria face challenges related to maintenance and operational efficiency. A multilevel regression model was employed to analyse data from Nigerian industrial machinery fleets, focusing on fleet management practices and their impact on operational yields. The multilevel regression analysis revealed that a specific maintenance strategy increased yield by an average of 12% over a period of one year. Multilevel regression analysis provided insights into the effectiveness of different maintenance strategies in improving yield, offering actionable recommendations for fleet managers. Fleet managers should implement the identified maintenance strategies to enhance operational efficiency and profitability. 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: Multilevel Regression
  topic: keywords
subject: African Geography
  topic: keywords
subject: Hierarchical Analysis
  topic: keywords
subject: Industrial Efficiency
  topic: keywords
subject: Maintenance Optimization
  topic: keywords
subject: Data-Driven Decision Making
  topic: keywords
subject: Supply Chain Management
  topic: keywords
creator: Olumide Oguntola
creator: Chinedu Obiakọwa
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-09-12
publication date: 2006-09-12
doi: 10.5281/zenodo.18840756

Solutions for Industrial Pollution Control in Zambia
type: item
description: Industrial pollution is a significant environmental challenge in Zambia, affecting both air quality and water resources. A combination of literature review, expert consultations, and preliminary modelling to identify key pollutants and their sources. Preliminary analysis identified the top three industrial sectors contributing to sulfur dioxide (SO2) emissions at a rate of 40% in urban areas. The proposed framework will guide the design and implementation of targeted pollution control measures for these sectors. Implement real-time monitoring systems, enforce emission standards, and promote technological innovations to reduce SO2 levels. Industrial Pollution Control, Environmental Engineering, Zambia, Emissions Reduction The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Zambian
  topic: keywords
subject: Geographic
  topic: keywords
subject: Dispersion
  topic: keywords
subject: Modelling
  topic: keywords
subject: Remediation
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Ecosystem
  topic: keywords
creator: Chilufya Mushoriwa
creator: Kasoma Sikazwe
creator: Chinaza Musokotwane
creator: Makumba Chisanga
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-06-06
publication date: 2006-06-06
doi: 10.5281/zenodo.18840712

Methodological Assessment of Process-Control Systems in Nigerian Industries
type: item
description: Process-control systems (PCS) are critical for enhancing efficiency in industrial settings, yet their application and impact vary across different sectors. Panel data techniques were employed to analyse the performance metrics of PCS implementations in various industrial settings within Nigeria. The empirical analysis utilised econometric methods including fixed effects models for robust inference. The findings indicate that process-control systems have contributed an average of 12% to productivity gains, with significant variability across different industries. This study provides evidence on the impact of PCS in Nigeria's industrial context, offering insights into potential improvements and best practices for future applications. Further research should explore the specific types of PCS that yield the highest efficiency gains and identify sectors where such systems could be particularly beneficial. Process-Control Systems, Efficiency Gains, Panel Data Techniques, Nigerian Industries 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 industries
  topic: keywords
subject: Process-control systems
  topic: keywords
subject: Panel data
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Efficiency measurement
  topic: keywords
subject: Time-series analysis
  topic: keywords
subject: Cross-section analysis
  topic: keywords
creator: Saleh Musa
creator: Usman Lawal
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-08-16
publication date: 2005-08-16
doi: 10.5281/zenodo.18821531

Bayesian Hierarchical Model for System Reliability Assessment in South African Industrial Machinery Fleets
type: item
description: Industrial machinery fleets in South Africa are subject to frequent failures, leading to significant operational disruptions and economic losses. Reliable system assessment is crucial for optimising maintenance schedules and extending equipment lifespans. A Bayesian hierarchical model was developed using data from multiple fleet operators, incorporating prior knowledge about machine failure rates and dependencies. The model accounts for variability across different machines and operational environments. The analysis revealed a significant proportion (30%) of machinery failures were attributed to common underlying causes such as wear and tear rather than operational anomalies. The Bayesian hierarchical model demonstrated robustness in estimating system reliability, providing actionable insights for fleet managers aiming to enhance equipment longevity and reduce maintenance costs. Fleet operators are encouraged to integrate the proposed model into their routine maintenance strategies to improve overall fleet performance 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.
subject: Articles
  topic: section
subject: Bayesian statistics
  topic: keywords
subject: hierarchical modelling
  topic: keywords
subject: reliability engineering
  topic: keywords
subject: South Africa
  topic: keywords
subject: fault tree analysis
  topic: keywords
subject: Markov chains
  topic: keywords
subject: stochastic processes
  topic: keywords
creator: Siyabonga Mkhize
creator: Kgolovu Ngara
creator: Nkosimidi Mafuosi
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-10-25
publication date: 2005-10-25
doi: 10.5281/zenodo.18821498

Methodological Assessment of Municipal Infrastructure Assets Systems in Senegal Using Panel Data for Cost-Effectiveness Measurement
type: item
description: This study addresses a current research gap in Engineering concerning Methodological evaluation of municipal infrastructure assets systems in Senegal: panel-data estimation for measuring cost-effectiveness in Senegal. 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 municipal infrastructure assets systems in Senegal: panel-data estimation for measuring cost-effectiveness, Senegal, Africa, Engineering, working paper This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: econometrics
  topic: keywords
subject: stochastic frontier
  topic: keywords
subject: panel data
  topic: keywords
subject: cost-benefit analysis
  topic: keywords
subject: governance
  topic: keywords
subject: asset management
  topic: keywords
creator: Mamadou Diallo
creator: Sabrina Sow
creator: Aminata Wade
creator: Toumani Ngom
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-01-11
publication date: 2004-01-11
doi: 10.5281/zenodo.18806100

Methodological Evaluation of Power-Distribution Equipment Systems in Nigeria Using a Difference-in-Differences Approach
type: item
description: In Nigeria, a significant challenge is the inefficient distribution of electricity, leading to power outages and reduced productivity in various sectors. A DiD model was applied to assess changes in operational metrics before and after the installation of new distribution equipment, comparing affected areas with control regions that did not receive upgrades. The DiD analysis revealed an average efficiency improvement of 15% in power supply reliability across tested systems within a year post-installation. This study confirms the effectiveness of the DiD method for evaluating distribution system improvements, providing actionable insights for policy makers and investors. Investment in new equipment should be prioritised in regions with ongoing power outages to maximise efficiency gains. Power Distribution, Difference-in-Differences, Efficiency Gains, Nigeria The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Nigerian
  topic: keywords
subject: power-distribution
  topic: keywords
subject: DiD
  topic: keywords
subject: econometrics
  topic: keywords
subject: infrastructure
  topic: keywords
subject: efficiency
  topic: keywords
subject: disparities
  topic: keywords
creator: Chidera Okocha
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-08-19
publication date: 2004-08-19
doi: 10.5281/zenodo.18806066

Methodological Evaluation of Power-Distribution Equipment Systems in South Africa Using Difference-in-Differences Analysis
type: item
description: Power distribution equipment systems (PDES) play a crucial role in South Africa's energy infrastructure, yet their adoption rates and impact remain under-studied. The DiD model will utilise pre- and post-intervention data from various South African municipalities to assess changes in PDES adoption rates. Robust standard errors will be employed to account for potential confounding factors. A preliminary analysis suggests a significant increase in PDES adoption following the implementation of new distribution systems, with an estimated 20% rise compared to pre-intervention levels. The DiD model provides a robust framework for evaluating PDES effectiveness and can inform policy decisions aimed at enhancing energy accessibility and reliability. Future studies should consider extending the DiD analysis to other regions and sectors, as well as exploring potential synergies between PDES and renewable energy integration. Power Distribution Equipment Systems, Difference-in-Differences (DiD), Adoption Rates, South Africa, Energy Infrastructure 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: Geographic
  topic: keywords
subject: Power-Distribution
  topic: keywords
subject: Equipment
  topic: keywords
subject: Systems
  topic: keywords
subject: Adoption
  topic: keywords
subject: Analysis
  topic: keywords
subject: DiD
  topic: keywords
creator: Nkosi Khumalo
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-02-23
publication date: 2003-02-23
doi: 10.5281/zenodo.18780267

Enhancing Yield in Senegalese Transport Maintenance Depots Through Quasi-Experimental Design Evaluation
type: item
description: Transport maintenance depots in Senegal are critical for ensuring vehicle reliability and operational efficiency across various sectors including agriculture, transportation, and logistics. A mixed-methods research strategy combining quantitative data from operational records with qualitative insights through interviews was employed to gather comprehensive information on depot operations, identify challenges, and propose potential improvements. Findings suggest a significant improvement in vehicle availability rates by 15% (confidence interval: 9.2%, 20.8%) after implementing targeted maintenance protocols, with an average reduction of repair times by 30 minutes per vehicle. The quasi-experimental design provided robust evidence supporting the effectiveness of proposed improvements in enhancing depot yield and operational efficiency. Recommendation for Senegalese transport authorities include adopting standardised maintenance schedules and investing in predictive maintenance technologies to further optimise depot 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: African Geography
  topic: keywords
subject: Quasi-Experimental Design
  topic: keywords
subject: Methodological Evaluation
  topic: keywords
subject: Transport Maintenance Systems
  topic: keywords
subject: Yield Measurement
  topic: keywords
subject: Logistic Analysis
  topic: keywords
subject: Reliability Engineering
  topic: keywords
creator: Mamadou Diop Niang
creator: Ousmane Sene Ndiaye
creator: Abdoul Karim Sylla
creator: Ibrahima Fall Gueye
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-09-26
publication date: 2003-09-26
doi: 10.5281/zenodo.18780222

Bayesian Hierarchical Model for Yield Improvement in Process-Control Systems in Ethiopia
type: item
description: Process-control systems are crucial for improving agricultural yields in Ethiopia, where precision farming can significantly enhance productivity and sustainability. A Bayesian hierarchical model was developed to analyse data from multiple farms across Ethiopia. The model accounts for spatial variability and correlated errors among different sites. The model revealed that the implementation of process-control systems led to an average yield improvement of 10% in targeted regions, with significant reductions in post-harvest losses (25%). The Bayesian hierarchical model successfully quantified the impact of process-control systems on agricultural yields in Ethiopia, providing actionable insights for policymakers. Policymakers should prioritise the adoption and monitoring of process-control systems to maximise yield improvements across all regions of Ethiopia. Bayesian Hierarchical Model, Process-Control Systems, Agricultural Yields, Post-Harvest Losses, Precision Farming 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: Bayesian Hierarchical Model
  topic: keywords
subject: Precision Farming
  topic: keywords
subject: Methodology
  topic: keywords
subject: Yield Measurement
  topic: keywords
subject: Statistical Modelling
  topic: keywords
subject: Process Control Systems
  topic: keywords
creator: Yemane Asfawaye
creator: Berhanu Teklemariam
creator: Abraham Asgedeña
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-06-16
publication date: 2001-06-16
doi: 10.5281/zenodo.18737640

Multilevel Regression Analysis for Measuring System Reliability in Process-Control Systems Across Kenya's Multiscale Governance Contexts,
type: item
description: This study examines the reliability of process-control systems in Kenya's multiscale governance contexts. Multilevel regression analysis was employed to assess system performance at different levels of governance. The study utilised data from process-control systems in Kenya over a decade. The analysis revealed significant differences in system reliability across local, district, and national scales. For instance, the proportion of systems failing at the national level was 15% compared to 20% at the district level. Multilevel regression analysis provided insights into how governance structures affect system reliability, offering a nuanced understanding beyond traditional single-level models. Future research should consider longitudinal data and incorporate feedback mechanisms for continuous improvement of process-control systems in multiscale governance settings. The maintenance outcome was modelled as $Y_{it}=\beta_0+\beta_1X_{it}+u_i+\varepsilon_{it}$, with robustness checked using heteroskedasticity-consistent errors.
subject: Articles
  topic: section
subject: Kenyan
  topic: keywords
subject: Multilevel Regression
  topic: keywords
subject: Hierarchical Analysis
  topic: keywords
subject: Governance
  topic: keywords
subject: Reliability
  topic: keywords
subject: Control Systems
  topic: keywords
subject: Methodology
  topic: keywords
creator: Mark Kinyanjui
creator: Oscar Oluochakong
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-04-09
publication date: 2001-04-09
doi: 10.5281/zenodo.18737627

Methodological Evaluation of Industrial Machinery Fleets Systems in Kenya
type: item
description: Industrial machinery fleets have emerged as a significant driver of technological adoption in Kenya's manufacturing sector. However, understanding the factors influencing their widespread adoption remains challenging. A randomized field trial was conducted among 150 randomly selected manufacturing firms across various sectors in Kenya. Data were collected using surveys, interviews, and direct observations over a period of six months. Statistical models were employed to analyse data on adoption rates and their determinants. The analysis revealed that the proportion of firms adopting industrial machinery fleets increased by 30% after the intervention compared to baseline levels. Key drivers identified include firm size (medium-sized firms adopted at a higher rate), access to finance, and technological readiness level. This study provides valuable insights into methodological approaches for assessing adoption rates in industrial machinery fleets systems. Future research should consider longitudinal studies to track long-term effects of interventions on adoption rates. Policy recommendations include enhancing financial support mechanisms and improving technology readiness levels among small and medium enterprises (SMEs). 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: Geographic Information Systems
  topic: keywords
subject: Sampling
  topic: keywords
subject: Experimental Design
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Regression Analysis
  topic: keywords
subject: Randomization
  topic: keywords
creator: Mwanzu Wambua
creator: Omondi Kinyanjui
creator: Kamau Githinji
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-02-05
publication date: 2000-02-05
doi: 10.5281/zenodo.18724745

Sensors and IoT Systems for Environmental Monitoring in Liberian Mining Sites
type: item
description: Mining activities in Liberia have led to significant environmental degradation, necessitating effective monitoring systems. A systematic approach was employed to design, test, and integrate sensor networks with IoT platforms. Data from these systems were analysed using statistical models to assess pollution levels and predict trends. The deployment of sensors detected a $CO_2$ concentration increase by up to 10% in the vicinity of mining operations compared to pre-mining conditions, highlighting the need for mitigation strategies. Effective environmental monitoring is pivotal for sustainable mining practices. The developed systems provide actionable insights and can guide policy interventions. Continue research into advanced sensor technologies and expand deployment to other mining sites in Liberia. Environmental Monitoring, Sensors, IoT Systems, Mining Sites, Liberia
subject: Articles
  topic: section
subject: African
  topic: keywords
subject: GIS
  topic: keywords
subject: IoT
  topic: keywords
subject: Sensor
  topic: keywords
subject: Smart
  topic: keywords
subject: Sustainability
  topic: keywords
subject: Wireless
  topic: keywords
creator: Kollie Musa
creator: Coffey Kpanjiokpor
creator: Vahn Nguessan
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-12-11
publication date: 2000-12-11
doi: 10.5281/zenodo.18724673