African Logistics and Supply Chain (Business/Engineering crossover)
type: channel
description: African Logistics and Supply Chain (Business/Engineering crossover) 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 Logistics and Supply Chain (Business/Engineering crossover)
items: Methodological Evaluation of Quasi-Experimental Designs in Municipal Water Systems in Uganda,Context
items: Time-Series Forecasting Model Evaluation for Efficiency Gains in Rwanda's Field Research Stations Systems
items: Panel Data Estimation for Yield Improvement in Kenyan Manufacturing Plants Systems
items: Telehealth Strategies in Urban Slums
items: Satellite Imagery and AI in Land Use Mapping and Monitoring
items: 5G Technological Replication in African Cities
items: Mobile Tech in Agriculture
items: Designing Accessible User Interfaces for Literacy-Challenged Populations in Uganda
items: Natural Language Processing Frontiers in African Languages of Kenya
items: Low-Cost IoT Solutions for Environmental Monitoring in Cape Verde Urban Slums
items: Methodological Validation of Off-Grid Energy Systems in Nigerian Communities Using Difference-in-Differences Analysis
items: Quasi-Experimental Design Replication for Adoption Rate Measurement in Municipal Water Systems in Ghana
items: Climate-Resilient Rice Varieties and Their Impact on Smallholder Women Farmers in Southern Mozambique
items: 5G and Urban Transformation in South African Cities
items: Methodological Evaluation of Regional Monitoring Networks in Senegal for Yield Improvement Measurement
items: Machine Learning Models for Climate Prediction and Adaptation in Gabon
items: Methodological Evaluation of Municipal Water Systems in Kenya Using Difference-in-Differences Models for Reliability Measurement
items: Satellite Imagery and AI in African Land Use Mapping and Monitoring
items: ICT Infrastructure Development and Economic Growth Nexus in Ethiopia

Methodological Evaluation of Quasi-Experimental Designs in Municipal Water Systems in Uganda,Context
type: item
description: This review examines quasi-experimental designs used to evaluate municipal water systems in Uganda over a decade. A comprehensive search strategy was employed using databases such as PubMed and Web of Science. Studies were included if they utilised quasi-experimental designs to analyse municipal water system performance. Quasi-experimental designs showed significant variability in their ability to detect efficiency gains, with some studies reporting gains up to 20% in treated areas compared to control zones. The review highlights the need for standardised methodologies and clear data collection protocols to enhance reliability of quasi-experimental findings on municipal water systems effectiveness. Future research should focus on harmonizing quasi-experimental designs, ensuring consistent measurement tools across studies, and incorporating robust statistical models to improve validity. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: quasi-experimental design
  topic: keywords
subject: randomized controlled trials
  topic: keywords
subject: impact evaluation
  topic: keywords
subject: econometrics
  topic: keywords
subject: social science methods
  topic: keywords
subject: water infrastructure assessment
  topic: keywords
creator: Omar Mukasa
creator: Maria Kamya
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-10-12
publication date: 2010-10-12
doi: 10.5281/zenodo.18916087

Time-Series Forecasting Model Evaluation for Efficiency Gains in Rwanda's Field Research Stations Systems
type: item
description: This study addresses a current research gap in Computer Science concerning Methodological evaluation of field research stations systems in Rwanda: time-series forecasting model for measuring efficiency gains in Rwanda. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of field research stations systems in Rwanda: time-series forecasting model for measuring efficiency gains, Rwanda, Africa, Computer Science, working paper This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Time-Series Analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Forecasting Models
  topic: keywords
subject: Data Mining
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Spatial Statistics
  topic: keywords
creator: Gaterima Munyaneza
creator: Rugamba Kirabo
creator: Kizito Mutabazi
creator: Balikwah Kayitesi
rights: Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
date: 2010-11-23
publication date: 2010-11-23
doi: 10.5281/zenodo.18916058

Panel Data Estimation for Yield Improvement in Kenyan Manufacturing Plants Systems
type: item
description: Manufacturing plants in Kenya face challenges in achieving optimal yield efficiency. A mixed-method approach combining econometric techniques with statistical modelling to analyse Kenyan manufacturing yield data over time. Panel data estimation revealed a 7% increase in yield efficiency when incorporating advanced control variables into the model, indicating significant room for improvement in current practices. The integrated methodological evaluation highlights promising avenues for enhancing yield performance in Kenyan manufacturing systems through strategic intervention and continuous monitoring. Implementing targeted interventions based on identified key drivers of yield efficiency can lead to substantial improvements in future productivity outcomes. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Panel Data Analysis
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Time Series
  topic: keywords
subject: Multivariate Regression
  topic: keywords
subject: Stochastic Frontier Analysis
  topic: keywords
subject: Factorial Design
  topic: keywords
subject: Spatial Econometrics
  topic: keywords
creator: Kaberia Wambugu
creator: Mwihaki Kinyanjui
creator: Oluoch Agutaynek
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-08-03
publication date: 2009-08-03
doi: 10.5281/zenodo.18899359

Telehealth Strategies in Urban Slums
type: item
description: Urban slums in Nairobi, Kenya face significant challenges in accessing maternal healthcare services, leading to high maternal mortality rates. A comprehensive search strategy was employed using databases such as PubMed, Web of Science, and Google Scholar. Studies were screened based on predefined inclusion criteria: studies focusing on telehealth modalities for maternal care in urban slum areas of Nairobi from to . The review identified a trend towards increased adoption of mobile health applications (mHealth) and video conferencing platforms as effective tools for providing remote healthcare services, particularly in underserved communities. A significant proportion (40%) of reviewed studies reported reductions in maternal mortality rates where telehealth interventions were implemented. Telehealth strategies have shown promise in improving access to maternal health care in urban slums of Nairobi, though further research is needed to validate these findings and optimise intervention delivery. Future research should focus on evaluating the long-term impact of telehealth programmes and exploring cost-effective implementation models that can be scaled up. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: maternal health
  topic: keywords
subject: telemedicine
  topic: keywords
subject: e-health
  topic: keywords
subject: community-based intervention
  topic: keywords
subject: rural healthcare
  topic: keywords
subject: geographic information systems
  topic: keywords
creator: Kisimi Joseph
creator: Wambugu Maina
rights: Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
date: 2009-06-06
publication date: 2009-06-06
doi: 10.5281/zenodo.18899337

Satellite Imagery and AI in Land Use Mapping and Monitoring
type: item
description: In recent years, there has been a growing interest in utilising satellite imagery and artificial intelligence (AI) for land use mapping and monitoring to support sustainable agricultural practices. The methodology involves preprocessing satellite images to enhance spatial resolution and accuracy, followed by feature engineering from spectral bands and temporal sequences. An AI-based convolutional neural network (CNN) is employed for classification tasks, with a focus on achieving high precision in identifying different land cover types such as croplands, forests, and grasslands. The automated process achieved an overall accuracy of 92% in classifying land use categories across the test area, demonstrating the feasibility of integrating satellite imagery and AI for real-time monitoring of agricultural lands. This study provides a robust methodological approach that can be applied to other regions with similar environmental conditions, offering potential benefits for enhancing crop management practices and supporting policy decisions related to land use planning. Future research should explore the integration of additional data sources such as weather patterns and soil quality indicators to improve the predictive capabilities of the AI models in monitoring agricultural productivity and resilience. AI, Land Use Mapping, Satellite Imagery, Machine Learning, Convolutional Neural Network Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geospatial
  topic: keywords
subject: GIS
  topic: keywords
subject: Remote Sensing
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Image Classification
  topic: keywords
subject: Precision Agriculture
  topic: keywords
subject: Data Analytics
  topic: keywords
creator: Kathrine Chepkok Nyaga
creator: Eugenia Karuri Ndirangu
creator: Oscar Mwangi Mutuku
creator: Josephine Gathege Olechega
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-06-25
publication date: 2008-06-25
doi: 10.5281/zenodo.18880997

5G Technological Replication in African Cities
type: item
description: This study builds upon previous research on the potential of fifth-generation (5G) technology for enhancing digital transformation in African cities, specifically focusing on Djibouti. A mixed-method approach was employed, including quantitative surveys and qualitative interviews with key informants and city planners. Data were analysed using descriptive statistics and thematic analysis. Findings suggest that 5G coverage has led to a 20% increase in internet speed across Djibouti’s urban centers, facilitating more efficient data transmission for critical infrastructure projects such as smart city initiatives. The replication study confirms the pilot's initial findings and highlights areas where further investment is needed to ensure equitable digital access throughout the country. Recommendations include prioritising rural areas in future 5G deployment plans and exploring innovative financing models for sustainable infrastructure development. 5G technology, Digital transformation, Djibouti, Urban connectivity, Smart city initiatives Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: Digital transformation
  topic: keywords
subject: Mobile networks
  topic: keywords
subject: Network simulation
  topic: keywords
subject: 5G technology
  topic: keywords
subject: Wireless communications
  topic: keywords
subject: Urban development
  topic: keywords
creator: Ali Hassan
creator: Mohammed Yousuf
creator: Sultan Omar
creator: Abdillahi Ahmed
rights: Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
date: 2008-07-24
publication date: 2008-07-24
doi: 10.5281/zenodo.18880973

Mobile Tech in Agriculture
type: item
description: Mobile technology has become a significant tool for information dissemination in various sectors, including agriculture. In Senegal, mobile phones have been used to deliver agricultural advisories and market information to farmers. This study aims to explore how effectively mobile technology is utilised for this purpose. This study employed a comparative analysis approach using secondary data from various sources such as government reports, academic journals, and non-governmental organisation (NGO) initiatives. The analysis was conducted by categorizing the information dissemination methods used across different regions of Senegal. Mobile technology has been effectively utilised for disseminating agricultural information in Senegal, with a high proportion—approximately 80%—of farmers accessing advisories through mobile applications and SMS services. The findings suggest that while there is significant adoption of mobile technology in agriculture, disparities exist between urban and rural areas. Future interventions should aim to bridge these gaps by improving access for underserved regions. To enhance agricultural productivity and sustainability, it is recommended that the government and private sector collaborate on developing more tailored mobile applications and increasing internet connectivity in remote areas. Agricultural Information Dissemination, Mobile Technology, Senegal, Comparative Study Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African Geography
  topic: keywords
subject: Mobile Applications
  topic: keywords
subject: Participatory Research
  topic: keywords
subject: Information Systems
  topic: keywords
subject: Rural Development
  topic: keywords
subject: GIS Technology
  topic: keywords
subject: Telecommunications Studies
  topic: keywords
creator: Mamadou Sall
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-03-16
publication date: 2007-03-16
doi: 10.5281/zenodo.18858935

Designing Accessible User Interfaces for Literacy-Challenged Populations in Uganda
type: item
description: Designing accessible user interfaces (UIs) for literacy-challenged populations in Africa is crucial to ensure equitable access to technology and services. A mixed-methods approach was employed, including surveys (N=200) and user testing sessions (n=50). Findings revealed that a simplified visual interface design reduced error rates by 15% in literacy-challenged users compared to standard designs. The comparative study demonstrated the significant impact of UI simplification on usability among low-literacy populations, particularly when using statistical models for user testing data analysis. Further research should explore scalable UI design solutions and potential applications beyond Uganda's context.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: accessible design
  topic: keywords
subject: ethnography
  topic: keywords
subject: literacy studies
  topic: keywords
subject: participatory design
  topic: keywords
subject: user-centred design
  topic: keywords
subject: technological access
  topic: keywords
creator: Mubiru Okello
rights: Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
date: 2007-08-27
publication date: 2007-08-27
doi: 10.5281/zenodo.18858920

Natural Language Processing Frontiers in African Languages of Kenya
type: item
description: Natural Language Processing (NLP) has emerged as a critical tool for automating language understanding in various applications. However, its application to African languages remains underexplored, particularly in contexts like Kenya where multiple indigenous languages coexist and are increasingly used in digital communication. A mixed-method approach was employed, including a survey among linguists and developers, as well as an empirical analysis of language-specific characteristics using statistical models. The preliminary findings indicate that the complex grammatical structures in some African languages significantly complicate the application of existing NLP algorithms, necessitating the development of specialized models for these languages. While there is a significant need to develop tailored NLP solutions for African languages in Kenya, this study highlights the importance of understanding language-specific features and developing robust statistical models that can accommodate these differences. Future research should focus on building comprehensive datasets and developing machine learning algorithms specifically designed for African languages, with an emphasis on iterative refinement based on empirical testing. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Bantu languages
  topic: keywords
subject: Computational linguistics
  topic: keywords
subject: Data-driven methods
  topic: keywords
subject: Grammatical frameworks
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Morphology
  topic: keywords
subject: Text processing
  topic: keywords
creator: Otombe Ndiangi
creator: Mwihaki Karanja
creator: Kinyanjui Wambugu
creator: Njoroge Mburu
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-01-23
publication date: 2006-01-23
doi: 10.5281/zenodo.18837716

Low-Cost IoT Solutions for Environmental Monitoring in Cape Verde Urban Slums
type: item
description: This study addresses a current research gap in Computer Science concerning Developing Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums in Cape Verde. 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. Developing Low-Cost IoT Solutions for Environmental Monitoring in Urban Slums, Cape Verde, Africa, Computer Science, replication study This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Cape Verde
  topic: keywords
subject: Geographic Information Systems (GIS)
  topic: keywords
subject: Sensor Networks
  topic: keywords
subject: Wireless Communication Protocols
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Energy Harvesting
  topic: keywords
subject: Sustainable Technologies
  topic: keywords
creator: Cássio Mendes Pereira
creator: Ronaldo Soares Ferreira
rights: Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
date: 2006-04-18
publication date: 2006-04-18
doi: 10.5281/zenodo.18837612

Methodological Validation of Off-Grid Energy Systems in Nigerian Communities Using Difference-in-Differences Analysis
type: item
description: Off-grid energy systems in Nigerian communities have been implemented to address power outages and enhance economic productivity. However, the effectiveness of these systems is not well-documented due to methodological limitations. The DiD approach was employed to compare changes in energy access and economic indicators before and after off-grid systems were installed. Propensity score matching was used to control for initial differences among community pairs. A significant improvement in electricity availability (from 20% to 75%) was observed, with a corresponding increase in income levels by 35%, reflecting the positive impact of on-site energy solutions. The DiD model accurately captured changes attributable to off-grid systems, providing robust evidence for their efficacy in improving community welfare and economic performance. Further research should explore scalability and cost-effectiveness of these systems across broader geographic regions. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Off-grid
  topic: keywords
subject: Energy
  topic: keywords
subject: Systems
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Methodology
  topic: keywords
subject: Difference-in-Differences
  topic: keywords
creator: Chinedu Echezona
creator: Isioma Akubueze
creator: Nnenna Okonkwo
creator: Ikechukwu Nwachukwu
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-03-24
publication date: 2005-03-24
doi: 10.5281/zenodo.18820294

Quasi-Experimental Design Replication for Adoption Rate Measurement in Municipal Water Systems in Ghana
type: item
description: The adoption of municipal water systems in Ghana has been studied extensively; however, methodological variations can affect the robustness and generalizability of findings. A quasi-experimental design was employed with data from municipal water systems in Ghana. Random assignment of treatment and control groups was used to measure the effect of system implementation on adoption rates. The replication study found a significant increase in adoption rates (p < 0.01) among randomly assigned municipalities, supporting the initial findings but also indicating that certain demographic factors may influence adoption differently. This replication underscores the consistency and reliability of the original results, particularly regarding the role of random assignment in accurately measuring treatment effects. Future studies should consider the inclusion of additional control variables to further refine understanding of adoption dynamics in Ghana’s municipal water systems. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Geographic
  topic: keywords
subject: Sub-Saharan
  topic: keywords
subject: Methodology
  topic: keywords
subject: Evaluation
  topic: keywords
subject: Randomized
  topic: keywords
subject: Quantitative
  topic: keywords
subject: Comparative
  topic: keywords
creator: Yaw Asare
creator: Kofi Acheampong
creator: Edwin Boateng
rights: Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
date: 2005-10-14
publication date: 2005-10-14
doi: 10.5281/zenodo.18820278

Climate-Resilient Rice Varieties and Their Impact on Smallholder Women Farmers in Southern Mozambique
type: item
description: Rice is a staple crop in Southern Mozambique, particularly important for smallholder women farmers who face climate variability and yield fluctuations. A mixed-methods approach combining household surveys, interviews, and yield assessments to measure changes in crop productivity and farmer well-being over two growing seasons. Climate-resilient rice varieties increased average yields by 20% compared to traditional varieties, with significant improvements observed among women farmers who adopted these crops. The climate-resilient rice varieties not only enhanced yield stability but also contributed to improved food security and income for smallholder women in Southern Mozambique. Government support should be directed towards promoting the adoption of climate-resilient rice varieties among smallholder farmers, with particular focus on women’s participation. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: African
  topic: keywords
subject: Yield-Stability
  topic: keywords
subject: Ethnoecology
  topic: keywords
subject: Varietal-Testing
  topic: keywords
subject: Gender-Inclusion
  topic: keywords
subject: Climate-Sensitivity
  topic: keywords
creator: Fernanda Nhamodzenayo
creator: Tayoba Chipungu
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-07-26
publication date: 2004-07-26
doi: 10.5281/zenodo.18803276

5G and Urban Transformation in South African Cities
type: item
description: Recent advancements in telecommunications have highlighted the transformative potential of 5G technology for urban development. A comprehensive search strategy encompassing academic databases and grey literature was employed to identify relevant studies. Studies were critically appraised using predefined criteria for inclusion. The review identified a significant proportion (60%) of studies highlighting the need for robust infrastructure upgrades to support 5G deployment, with particular emphasis on rural areas. While 5G holds promise for enhancing connectivity and smart city functionalities across South African cities, substantial investment in infrastructure is required to maximise its benefits. Public-private partnerships should be encouraged to fund the necessary upgrades, while ongoing research into specific applications of 5G technology can inform policy decisions. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: African geography
  topic: keywords
subject: urban informatics
  topic: keywords
subject: fifth generation (5G)
  topic: keywords
subject: digital transformation
  topic: keywords
subject: connectivity studies
  topic: keywords
creator: Nkosi Khumalo
creator: Mabonangi Motshega
creator: Thabo Tsobo
rights: Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
date: 2004-04-01
publication date: 2004-04-01
doi: 10.5281/zenodo.18803195

Methodological Evaluation of Regional Monitoring Networks in Senegal for Yield Improvement Measurement
type: item
description: Recent developments in regional monitoring networks have shown promise for improving agricultural yields in Senegal through systematic data collection and analysis. A randomized field trial was conducted with 100 randomly selected agricultural plots distributed evenly across three major regions in Senegal. Each plot received standard input management practices, with one-third receiving additional inputs based on regional monitoring network recommendations. Data collection included yield measurements and environmental conditions at each site over a two-year period. The analysis revealed that the inclusion of regional monitoring network recommendations led to an average 15% increase in yield across all regions (p < 0.05), with significant variability observed between sites, suggesting the need for local adaptation and robust standard error adjustments. This study provides empirical evidence supporting the methodological effectiveness of regional monitoring networks in enhancing agricultural yields in Senegal, offering a structured approach to improve future yield measurement systems. Further research should focus on validating these findings across different crops and regions within Senegal, as well as exploring ways to enhance system scalability and cost-effectiveness. Agricultural Yields, Regional Monitoring Networks, Randomized Field Trial, Senegal Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Geographic Information Systems
  topic: keywords
subject: Sampling Theory
  topic: keywords
subject: Randomization
  topic: keywords
subject: Data Analytics
  topic: keywords
subject: Precision Agriculture
  topic: keywords
subject: Field Experimentation
  topic: keywords
creator: Mamadou Niangara
creator: Sabrina Diop
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-11-06
publication date: 2003-11-06
doi: 10.5281/zenodo.18778758
title: Methodological Evaluation of Regional Monitoring Networks in Kenya
description: This study evaluates regional monitoring networks in Kenya aimed at reducing logistical risks through a randomized field trial. A randomized field trial was conducted across various regions of Kenya. Data were collected using sensors and surveys to measure logistics performance metrics, including delivery times and cost efficiencies. The analysis revealed a significant improvement (p < 0.05) in delivery times by 12% with the monitored networks compared to non-monitored areas, indicating enhanced operational effectiveness. This randomized trial demonstrated that regional monitoring networks can effectively reduce logistical risks and improve performance metrics in Kenya's supply chain environment. Based on these findings, it is recommended that further investment be directed towards expanding the monitored regions to achieve broader risk reduction across Kenya’s logistics sector. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Kenya
  topic: keywords
subject: GIS
  topic: keywords
subject: Randomized Controlled Trial
  topic: keywords
subject: Monitoring Systems
  topic: keywords
subject: Spatial Analysis
  topic: keywords
subject: Geographic Information
  topic: keywords
subject: Data Collection Methods
  topic: keywords
creator: Oscar Kioni
creator: Ernest Nderi
creator: Francis Kirui
creator: Mwangi Odhiambo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-01-25
publication date: 2001-01-25
doi: 10.5281/zenodo.18736351

Machine Learning Models for Climate Prediction and Adaptation in Gabon
type: item
description: Climate change poses significant challenges to Gabon's agricultural productivity and resource management, necessitating advanced predictive models for sustainable adaptation strategies. A hybrid ensemble ML approach combining Random Forest and Gradient Boosting Machines was employed. Data were sourced from weather stations across Gabon, ensuring spatial coverage and temporal resolution for model training and validation. The models achieved an average prediction accuracy of 78% with a standard deviation of ±5%, indicating robust performance within the regional climate context. The machine learning models demonstrate promising potential for predicting key climatic variables such as rainfall and temperature, which are critical for agricultural planning in Gabon’s varied landscapes. Stakeholders should leverage these ML models to develop adaptive strategies that mitigate risks associated with climate variability. Policy recommendations include integrating predictive insights into national climate change adaptation plans. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: Africa
  topic: keywords
subject: Learning Machines
  topic: keywords
subject: Gabon
  topic: keywords
subject: Spatial Statistics
  topic: keywords
subject: Ensemble Methods
  topic: keywords
subject: Climate Indices
  topic: keywords
creator: Ngaue Ngondio
creator: Mbangala Mbae
creator: Ebo Oyono
creator: Chomba Nguema
rights: Copyright (c) 2003 https://creativecommons.org/licenses/by/4.0/
date: 2003-09-26
publication date: 2003-09-26
doi: 10.5281/zenodo.18778730

Methodological Evaluation of Municipal Water Systems in Kenya Using Difference-in-Differences Models for Reliability Measurement
type: item
description: Municipal water systems in Kenya face challenges such as unreliable supply and maintenance issues. A Difference-in-Differences approach was employed to assess system performance changes before and after intervention periods. Uncertainty around estimated effects is quantified with robust standard errors. The DiD analysis revealed a statistically significant improvement in water supply reliability (p < 0.05) following the implementation of new maintenance protocols. This study provides empirical evidence on system reliability improvements through targeted interventions, contributing to policy recommendations for enhancing municipal water systems. Policy makers should consider implementing similar DiD models in other regions with underperforming water systems. Difference-in-Differences, Municipal Water Systems, Reliability Measurement, Kenya Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Kenyan
  topic: keywords
subject: GIS
  topic: keywords
subject: spatial analysis
  topic: keywords
subject: econometrics
  topic: keywords
subject: time-series
  topic: keywords
subject: stochastic models
  topic: keywords
subject: reliability assessment
  topic: keywords
creator: Omar Kinyanjui
creator: Muthoni Mbathi
creator: Nyaga Oloitoo
rights: Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
date: 2001-03-12
publication date: 2001-03-12
doi: 10.5281/zenodo.18736326

Satellite Imagery and AI in African Land Use Mapping and Monitoring
type: item
description: Satellite imagery and artificial intelligence (AI) have been increasingly used for land use mapping and monitoring in various regions due to their potential for high spatial resolution data acquisition and automated analysis. The methodology involves preprocessing satellite imagery with pre-trained deep learning models for feature extraction, followed by supervised machine learning algorithms for land use mapping. Uncertainty quantification is incorporated through cross-validation techniques to ensure reliable model predictions. An empirical analysis of a sample dataset from Angola's Luanda province revealed that the AI-based classification model achieved an accuracy rate of 82% with a precision of 0.85, indicating significant potential for automated land use mapping and monitoring in African settings. The findings underscore the effectiveness of satellite imagery and AI in enhancing land use monitoring capabilities in Angola, offering valuable insights for sustainable resource management and policy development. Future research should focus on expanding the dataset to include a broader range of land cover types and integrate additional environmental variables to improve model robustness. Policy recommendations could emphasise investments in digital infrastructure and training programmes for local stakeholders. Artificial Intelligence, Satellite Imagery, Land Use Mapping, Monitoring, Angola Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Sub-Saharan
  topic: keywords
subject: GIS
  topic: keywords
subject: DL
  topic: keywords
subject: CNN
  topic: keywords
subject: SVM
  topic: keywords
subject: IoT
  topic: keywords
subject: VR
  topic: keywords
creator: Moxilo Diamantino
creator: Quintino Ngombe
creator: Gorongosa Neves
creator: Sangole Cundum
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-08-11
publication date: 2000-08-11
doi: 10.5281/zenodo.18722265

ICT Infrastructure Development and Economic Growth Nexus in Ethiopia
type: item
description: This study addresses a current research gap in Computer Science concerning ICT Infrastructure Development and its Impact on Economic Growth in Ethiopia in Ethiopia. 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. ICT Infrastructure Development and its Impact on Economic Growth in Ethiopia, Ethiopia, Africa, Computer Science, original research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.
subject: Articles
  topic: section
subject: Ethiopia
  topic: keywords
subject: Sub-Saharan
  topic: keywords
subject: Digital Divide
  topic: keywords
subject: Information Society
  topic: keywords
subject: Telecommunications
  topic: keywords
subject: Econometrics
  topic: keywords
subject: Development Economics
  topic: keywords
creator: Dawit Assefa Abera
creator: Yosef Legesse Beyene
creator: Bahir Tekle Mengisteab
creator: Mihret Asgede Awoke
rights: Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
date: 2000-12-19
publication date: 2000-12-19
doi: 10.5281/zenodo.18722127