{"title":"Editors and reviewers","authors":"","doi":"10.23919/SAIEE.2025.11129189","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129189","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"138-138"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Notes for authors","authors":"","doi":"10.23919/SAIEE.2025.11129187","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129187","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"169-169"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An investigation into the technology transfer barriers of the electronic train control systems installed on the South African railway network — A study into SA's freight rail operator","authors":"Simphiwe D. Mtanti;Getnet B. Fanta","doi":"10.23919/SAIEE.2025.11129188","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129188","url":null,"abstract":"Technology transfer is the process of moving technology for use and understanding from one organisation to another for the technology recipient to achieve and implement technology developments and innovations. The technology transfer process is a complex, volatile and iterative one, which requires the flow of information and knowledge between the transferor and the transferee. This qualitative research aims to identify and investigate barriers to the technology transfer of the electronic train control projects undertaken by a South African freight rail operator (FRO) to upgrade its train control systems on several pilot sites. Ten staff members involved in the FRO's project management, maintenance, operations and training functions were interviewed. They have worked or are working on the various installed electronic train control systems. The thematic analysis findings revealed that the FRO is not equipped to exploit and further develop the technology. The barriers that contribute to this include the loss of vital skills internally, the project management of these technology transfer projects and the lack of flexibility of the technology regarding the local conditions and requirements of the FRO. The broadly analysed impact of the loss of skills in freight rail operations resulted in skills retention, adding to the initially proposed research model as a factor that contributes to the technology transfer process alongside learning, the transferor and transferee environment, language and procurement. Including a technology transfer office (internally or externally) could mitigate most of the identified barriers.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"140-149"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Development of a solar photovoltaic-biogas hybrid microgrid for off-grid rural communities in Uganda","authors":"Emmanuel Wokulira Miyingo;David Sunday Tusubira;Roseline Nyongarwizi Akol;Sheila N. Mugala;Davis Kayiza Kawooya","doi":"10.23919/SAIEE.2025.11129186","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129186","url":null,"abstract":"Electricity is vital for social-economic growth and development. However, over 80% of rural dwellers in Uganda do not have access to it due to the absence of the national electricity grid. Most rural inhabitants use biomass to meet their energy needs using primitive conversion devices, e.g., the 3-stone stoves. They are mainly agricultural and generate a lot of waste, whose disposal is usually open dumping and burning. Such practices lead to environmental concerns and limited economic opportunities. This research aimed to address energy poverty and waste management in off-grid Ugandan communities. The study focused on solar photovoltaic (PV)-biogas hybrid microgrids as a potential solution, given the abundance of solar and bio-waste, particularly animal dung. Field surveys were conducted in Mubende District to gather data on energy usage, appliances, and demographics. Technical simulations and financial analyses were performed for different energy supply scenarios. The results indicated that the solar PV-biogas hybrid system was financially viable, with positive internal rate of return, net present value, and return on investment, whereas solar PV only was not. A pilot project was successfully implemented in one community with seven end users and has been operating since April 2024. The feedback from the end users is full of praise and excitement, and many more users wish to be connected. The study concluded that solar PV-biogas hybrid microgrids can be a valuable solution for providing energy access to off-grid communities in Uganda. Scaling up such systems is recommended to address the energy needs of such areas.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"150-159"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A deep learning-based channel estimation scheme for cell-free massive MIMO systems","authors":"Malcolm Sande;Giscard Binini","doi":"10.23919/SAIEE.2025.11129185","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11129185","url":null,"abstract":"Cell-free massive multiple-input-multiple-output (MIMO) is a technique that couples the cell-free network architecture and massive antenna arrays. In cell-free massive MIMO, multiple access points (APs) are collocated to serve fewer user equipment (UEs), which results in a system with more APs than UEs. To achieve optimum transmission performance, massive MIMO requires knowledge of accurate channel state information (CSI). However, the conventional method of CSI estimation, based on minimum mean square error, suffers from high computational complexity, pilot contamination, and noise interference, which degrade the performance of the system. In this paper, we propose a deep learning-based channel estimation approach that makes use of a deep neural network to provide a scalable and efficient channel estimation scheme. Simulation results showed that the proposed scheme consistently outperformed conventional cell-free massive MIMO, small cell network, and cellular massive MIMO architectures.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 4","pages":"160-168"},"PeriodicalIF":0.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11129185","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144868368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Autism spectrum disorder detection using parallel DCNN with improved teaching learning optimization feature selection scheme","authors":"Triveni Dhamale;Sheetal Bhandari;Varsha Harpale;Pramod Sakhi;Kiran Napte;Anurag Mahajan","doi":"10.23919/SAIEE.2025.11090064","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11090064","url":null,"abstract":"The identification of a neurological disorder known as autism spectrum disorder (ASD) is essential and vital for improving the quality of life and providing appropriate medical care for those with autism. Good health and well-being are essential for individuals with autism, just like anyone else. In the last decade, numerous machine learning (ML) and deep learning (DL) based techniques and methods were used for Autism Disorder Detection (ASD) with the help of magnetic resonance images (MRI). The performance of this technique is susceptible to poor feature representation, redundant features, complexity of DL frameworks, and poor visual quality of the images. This paper presents ASDD based on a parallel Deep Convolution Neural Network (PDCNN). It includes image enhancement, feature extraction, feature selection, deep feature representation, and ASDD. It presents an improved double-stage Gaussian Weiner Filtering scheme to minimize blur, contrast, and uneven illumination in some images. Further, it offers the shape and texture feature extraction of functional MRI (fMRI) with gray level co-occurrence matrix (GLCM), local binary pattern (LBP), and histogram of oriented gradient (HOG), and local directional pattern (LDP). Afterward, an improved teaching-learning-based scheme is utilized to select prominent features to minimize the computational intricacy of the PDCNN. The outcomes of the system are validated on the ABIDE-I dataset.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 3","pages":"89-100"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11090064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimization of a grid-connected hybrid energy system with battery storage for hydrogen production in South Africa","authors":"Esmeralda Mukon;Karen S. Garner","doi":"10.23919/SAIEE.2025.11090062","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11090062","url":null,"abstract":"This paper presents an optimization study for a grid-connected hybrid energy system combining wind, solar PV, and a battery energy storage system (BESS) for hydrogen production. To address the intermittency of wind and solar resources, the grid compensates for insufficient energy to meet the electrolyzer load demand, while excess or curtailed energy is stored in the BESS to enhance reliability. The study employs a constrained multi-objective non-dominated genetic algorithm within the Python-based Pymoo framework. The optimization identifies an ideal grid-connected hybrid energy system with minimized electricity costs and maximized efficiency at high reliability. Subsequently, the BESS is optimized to reduce storage and electricity costs while maintaining reliability. The optimized BESS is successfully integrated into the hybrid system. Cost of electricity and reliability are assessed based on time-of-use tariffs and loss of power supply probability, respectively. Using a 2 MW proton exchange membrane electrolyzer, the study achieves a highly efficient hybrid system with the BESS applied to six Renewable Energy Development Zones in South Africa. Including the BESS reduces electricity costs, improves reliability, and lowers curtailment ratios by 40–66%.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 3","pages":"125-134"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11090062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"From local legacy to global impact: The SAIEE Africa research journal's journey through international indices","authors":"S. Sinha;B. Lacquet;B. T. J. Maharaj;N. Maddali","doi":"10.23919/SAIEE.2025.11090066","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11090066","url":null,"abstract":"The SAIEE Africa Research Journal, incorporating the Transactions of the South African Institute of Electrical Engineers (SAIEE), has evolved from a local cornerstone of South African engineering research into a globally recognized publication platform. Since its establishment in 1909, the journal has consistently fostered innovation and academic excellence in electrical engineering and related disciplines. This article summarizes the journal's transformative journey, highlighting its integration into prominent global databases/indices such as IEEE Xplore, Scopus, SciELO SA, DOAJ and WoS. These achievements have amplified its international visibility and impact, as reflected in steadily increasing SCImago Journal Rank (SJR) metrics and the attainment of its first Impact Factor in 2024. The journal's commitment to ethical publishing practices and alignment with global best practices in peer-review have further bolstered its credibility. Key milestones, such as the integration of over a century of archives into IEEE Xplore and the adoption of Open Access Creative Commons licensing, highlight the journal's mission to make African engineering research globally accessible. Additionally, its diverse editorial board and international collaboration highlight its role as a bridge between researchers worldwide.","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 3","pages":"84-88"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11090066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Notes for authors","authors":"","doi":"10.23919/SAIEE.2025.11090061","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11090061","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 3","pages":"135-135"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11090061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Editors and reviewers","authors":"","doi":"10.23919/SAIEE.2025.11090065","DOIUrl":"https://doi.org/10.23919/SAIEE.2025.11090065","url":null,"abstract":"","PeriodicalId":42493,"journal":{"name":"SAIEE Africa Research Journal","volume":"116 3","pages":"82-82"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11090065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}