International Journal of Engineering Research in Africa Vol. 51

Abstract: Bacterial Wilt disease is the most determinant factor as it results in a serious reduction in the quality and quantity of food produced by Enset crop. Therefore, early detection of Bacterial Wilt disease is important to diagnose and fight the disease. To this end, a deep learning approach that can detect the disease by using healthy and infected leave images of the crop is proposed. In particular, a convolutional neural network architecture is designed to classify the images collected from different farms as diseased or healthy. A total of 4896 images that were captured directly from the farm with the help of experts in the field of agriculture was used to train the proposed model. The proposed model was trained using these images and data augmentation techniques was applied to generate more images. Besides training the proposed model, a pre-trained model namely VGG16 is trained by using our dataset. The proposed model achieved a mean accuracy of 98.5% and the VGG16 pre-trained model achieved a mean accuracy of 96.6% by using a mini-batch size of 32 and a learning rate of 0.001. The preliminary results demonstrated that the effectiveness of the proposed approach under challenging conditions such as illumination, complex background, different resolutions, variable scale, rotation, and orientation of the real scene images.

Abstract: Flexible alternating current transmission systems (FACTS) deployments and applications are on the increase in modern day power network systems because of their advantages over conventional ways of power network physical expansion. Therefore, a comprehensive review of FACTS controllers with their various applications is carried out in this paper. Formation of different applications and advantages of FACTS devices into voltage control, power flow control, system stability control, power quality control, and economic benefits as inferred from the literatures is among the vantage points of this presentation. FACTS background alongside different techniques of deployments, leading to various applications and performance of these devices, hitherto organized structurally based on target objectives are also explored, presented and discussed. Summarily, this study provides an overview of the background, topological structures, deployment techniques and cutting-edge utilization of FACTS controllers, with a view to acquainting power players, electrical engineers, network designers as well as researchers, with the trends in the development, status and future direction of FACTS applications. Convincingly, the content of this article will benefit all the stakeholders in the area of FACTS deployments and utilizations.

Abstract: The exceptional mechanical and thermal properties, conceivable with carbon nanotubes (CNTs) make a distinction of them as excellent choices for natural rubber nanocomposite reinforcement. Nigeria, in recent years, has been awash with foreign prostheses, many of which fail to meet the criteria of the International Society of Prosthetics and Orthotics (ISPO) for developing countries. However, there are major marked gaps that make them susceptibility to premature failure and dimensional instability, caused by a high rate of water absorption in a humid environment; owing to the dynamic nature of human gait. This paper critically examines the effect of water absorption, thermogravimetric and dynamic mechanical properties, on carbon nanotube-reinforced natural rubber nanocomposite (NC) for prosthetic foot application. CNTs were synthesised via catalytic chemical vapour deposition (CCVD) technique and the NCs were produced by using an electrically heated hydraulic press. Thermogravimetric analysis (TGA), water absorption rate and dynamic mechanical analysis (DMA) of the nanocomposites were carried out with a view to comparing the various compositions used in this paper. Of the five NCs developed (NR/MWCNT-0, NR/MWCNT-3, NR/MWCNT-6, NR/MWCNT-9, NR/MWCNT-12 and NR/MWCNT-15), NR/MWCNT-3 (3 g of MWCNT in 100 g of natural rubber) showed the highest thermal stability of 260 °C, optimal water absorption rate of 0.1% and highest quality energy storage and dissipation capacity, as indicated by 2.239 DMA loss factor curve amplitude, hence giving it a comfortable edge over its existing counterparts. The results of the various analyses carried out indicated, therefore, that reinforcing natural rubber with multi-walled carbon nanotube offers a reliable alternative material for the prosthetic industry.

Abstract: Removal of heat generation is an important characteristic needs to be considered in electromechanical and electronic devices which improve the stability and feasibility of system. Despite numerous cooling methods, heat pipes are recent updating in research line. Heat pipes are one of the super conducting medium of heat energy and it is being used as an equipment to absorb more heat through phase change process of cooling medium circulated in it. It ensures the direct enhancement in heat transfer capacity and characteristics. Nowadays, improvement of the thermal performance in heat pipes getting up with various technologies, especially combination of heat pipe and Nano fluids. It has been experimentally practiced and various results are observed by previous researches that wick structure also a part of reason in improvement. The aim of this research work is to analyze the influence of wick material to improve heat transfer characteristics in heat pipes. In addition, combination of nano coated wick material with heat pipes is comparatively analyzed. From the final observed results it was found that, the best combination of wick material is supporting the better cooling requirements in electronic devices.

Abstract: The introduction of IEC-61850 digital-based Substation Automation System (SAS) eases implementation of elaborate schemes; however, its reliability and availability continue to be investigated for executing mission-critical applications. Independent repairable multi-channel systems with voting capability such as ‘one-out-of-two’ tripping schemes are often used for critical safety-related functions because the individual scheme channels hardly ever fail simultaneously. The system configuration enables the scheme to self-reconfigure when a link failure occurs in one of the channels, as well as being repairable with no interruption to the overall mission. This paper reviews the reliability and availability of evaluation methods to highlight their advantages and disadvantages. Structure-function modelling, as well as Markov process incorporating Systems Thinking and Mathematical Expectation are used to model the reliability of IEC-61850 based SCN to demonstrate the shortcomings of combinatorial methods in the evaluation of mission-critical systems where diagnostic capabilities of the systems and imperfect repairs should be considered. It is evident from the results of the study that system diagnostic capability and repair efficiency cannot be ignored for mission-critical applications for the reason that the simplifying assumptions of combinatorial analysis methods greatly over-state the reliability and availability performance of the system as observed from the results.

Abstract: The present study evaluates the influence of kitchen wastes on animal manures via anaerobic digestion for biogas production. The digestion was done using a digester with a capacity of 5L. The digester was loaded with the slurry of wastes prepared by mixing the wastes with water in ratio 1:1, and operated at mesophilic temperature of 37 ± 2°C for 30 days. The co-digestion of kitchen wastes with poultry droppings produced highest biogas yield (814.0 ml/kg VS fed) and the least (365.84 ml/kg VS fed) was from the co-digestion of kitchen wastes with the mixture of poultry droppings and cow dung. Composition analysis of the biogas showed the highest methane content (63.1%) from kitchen wastes and the lowest (56.2%) from co-digestion of kitchen wastes with poultry droppings. The pH range for optimum biogas production varied between 5.25 and 7.5. The study concluded that biogas yield from co-digestion of substrates, among other factors depends on the composition of participating substrates.

Abstract: The enhanced automation of the shipping industry has increased the demand of real data exchange. The ship-owners are looking more and more to optimize the operational cost of ship, to monitor remotely the cargo and to ensure a satisfactory level of safety and security, in compliance with the international maritime organization requirements. As per international convention for the safety of life at sea requirements, a conventional ship must carry a global maritime distress safety system, depending on the sea areas where it is operating. We assume that assuring a reliable communication service in the shipping industry is a challenging issue, in an era of internet of things and the need for a ship to be continuously connected to its ecosystem. This connectivity should be with a high data rate transmission. However, the future implementation of autonomous ship beside the existing conventional ship as an alternative for a sustainable maritime industry, requires the implementation of a reliable and cost-effective communication carrier, capable to transfer operational data on live basis from ship-to-ship and from ship-to-shore without interruption with a very low latency. To achieve this goal, we propose in this work, the implementation of 5G network as a maritime communication carrier, using unmanned aerial vehicle base stations, which are placed at optimum positions. This placement results in a maximization of uplink and downlink communication data rate, low latency and efficient optimization of transmission power. These make of 5G a potential maritime communication service carrier, capable to support the safe operation of deep-sea conventional vessels and the future deployment of autonomous ships.