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Selecting the most preferred software for teaching power systems engineering at the undergraduate level is a complex problem in developing countries, and it requires making an informed decision by compromising on various criteria. This study proposes a multi-criteria framework to determine the most preferred software solution for instructing undergraduate power system modules using the Fuzzy-ARAS (additive ratio assessment) method and expert opinions. Twelve evaluation criteria were used to evaluate eight widely used software packages. A questionnaire was designed to capture views from professionals in academia and industry on the criteria weights and ranking of software options. Linguistic terms were used to represent the experts' judgment, and weights were assigned to each criterion. The Fuzzy-ARAS multi-criteria decision approach was applied to obtain ratings for each software alternative. Based on the result, MATLAB emerged as the most preferred software for instructing power systems analysis, whereas MATPOWER (V 8.0) was rated as the least preferred choice. In addition, the Fuzzy-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach was used, producing a separate ranking; the most preferred software was MATPOWER, while the least preferred software was NEPLAN (V 360 10.5.1). A new coefficient that combines the findings of the two approaches was suggested to reconcile the ranks. The combined ranking aligns with the result of the Fuzzy-TOPSIS method by returning MATLAB as the most preferred, while the least preferred software was NEPLAN. This study significantly contributes to the choice of software for undergraduate power systems analysis instruction by providing direction to educators and institutions looking for software solutions to improve undergraduate power systems analysis education. [ABSTRACT FROM AUTHOR]

The numerous consequences of climate change worldwide have precipitated research efforts to realise sustainable development goal 13 (SDG 13). SDG 13 has recommended mitigation and adaptation strategies to combat climate change, and many of these can be achieved using emerging technologies. Research has shown the efficacies of information communication technologies (ICTs) in mitigating and adapting to climate change. However, the selection and ranking of ICT tools for mitigating and adapting to climate change is a multicriteria problem. This paper presents a multicriteria framework that identifies and ranks the various ICT tools that can ensure climate change mitigation and adaptation. A fuzzy-technique for order of preference by similarity to ideal solution method is used as the basis of this model and tested using information obtained from an expert. The results show that the most ideal ICT alternative is social media with a closeness coefficient of 0.62, while the least preferred alternative is the intelligent system with a closeness coefficient of 0.17. The proposed model can be used in the planning of climate change adaptation strategies in developing countries where finances are usually a major constraint in implementing climate change action.

Recently, every aspect of human existence has been affected by modern technologies, including agriculture. The broad range of crops has witnessed setbacks in different capacities due to climate change, leading to diseases and infections and negatively impacting nutrition. Plant diseases significantly threaten agricultural productivity, leading to substantial economic losses and food insecurity. Traditional methods of disease identification, such as visual inspection and laboratory testing, are time-consuming and require expert knowledge. This study aims to address this problem by leveraging Convolutional Neural Networks (CNNs) and FPGA technology for real-time potato disease identification. Five CNN models were trained and evaluated on the Plant Village dataset, achieving accuracies above 90%. ShuffleNet was identified as the most suitable for FPGA deployment, combining high accuracy with low inference time due to its efficient architecture. The selected CNN was implemented on the Xilinx UltraScale+MPSoC ZCU104 board, demonstrating significant power efficiency with a total consumption of 3.333 W, of which 79% was dynamic power. The design met all timing constraints, ensuring reliable operation at a 100 MHz clock frequency, and exhibited low resource utilization with only 0.20% of LUTs, 0.07% of LUTRAMs, 0.13% of flip-flops, and 0.18% of BUFGs used. These results highlight the FPGA's potential as a power-efficient and high-performance alternative to CPU and GPU implementations for real-time CNN inference. Future work includes developing a test bench for detailed performance measurement, optimizing dynamic power usage, and conducting comparative analyses with other platforms. Additionally, expanding the dataset to include more variability and validating the system in real-world applications will further enhance its effectiveness. This research contributes to the goals of Agriculture 4.0 by providing a viable solution for real-time plant disease identification, ultimately aiming at improving agricultural productivity and food security. [ABSTRACT FROM AUTHOR]

This study evaluates and ranks wireless communication technologies for agricultural irrigation systems using the CRITIC-CODAS multi-criteria decisionmaking method. WSN, LPWAN, LoRa, 5G, IoT, and NB-IoT are compared based on range, power consumption, data rate, coverage, latency, battery life, and device density. The CRITIC method objectively determines criteria weights, with data rate, latency, and battery life emerging as the most critical factors. 5G ranks highest with its superior data rate and device density, but its high-power needs may limit suitability for remote agriculture. IoT offers a balanced option across multiple criteria, while WSN excels in power efficiency and battery life. Despite lower data rates, LPWAN, LoRa, and NB-IoT provide excellent range and battery life for wide-area, low-power applications. The analysis offers a framework for stakeholders to select appropriate technologies based on specific agricultural requirements. Matching wireless technologies to irrigation needs can enhance agricultural sustainability and productivity. Further research could explore technology combinations, cost factors, and real-world testing. This systematic evaluation approach can be extended to other intelligent agriculture applications to optimize technology adoption. [ABSTRACT FROM AUTHOR]

The shift to renewable energy sources is essential for mitigating climate change, but it poses fresh challenges for environmentally responsible waste management. This article reviews and investigates the complex problems associated with the disposal of renewable energy components from an environmental, social, and governance (ESG) perspective. The article further highlights the need for thorough oversight and careful management of various components due to the environmental concerns associated with their disposal as they frequently contain hazardous elements. The social effects on communities impacted by disposal procedures are also explored, and the importance of fair distribution of benefits is emphasized. Transparency, accountability, and stakeholder involvement are bolstered by effective governance, which is a central theme of this discussion that draws on ESG concepts. Successful ESG-integrated disposal plans are demonstrated by industry case studies. Possible hindrances in sustainable disposal are also highlighted with firm suggestions on way-forward, which include technical innovation and global collaboration. The study underlines the irreplaceable role played by ESG in guiding responsible waste management toward a sustainable, green energy future. [ABSTRACT FROM AUTHOR]

Water desalination plants powered by solar energy represent a viable solution for addressing a part of the water needs in areas without reliable water supply. In this case extending the electric grid and water delivery to remote communities remain challenging for some countries. Using Namibia as a case study, this work carried out a feasibility study on the extent of which, solar energy could be used to power the entire desalination process thereby aiding groundwater usable for human consumption. This process includes but not limited to desalination of underground wells and boreholes as solution to the water shortage problem in remote areas. In this study, a solar-powered desalination technique that could enhance the process of clean water provision to villagers is proposed with the aim of implementation. It further compares and analyzed various desalination technologies to determine the best fit based on the dryness of areas. Ohawuwanga Village in Namibia was used for evaluation purpose with a sampling instrument-questionnaire which determine the village's daily water consumption and corresponding power required. Modelling, simulation, and analysis of the system was carried out using MATLAB Simulink in terms of energy consumption. Other parameters considered in this research are cost, water recovery ratio, salt removal factor, durability, and market analysis. The research revealed that electrodialysis is the best technology for desalination in terms of efficient power consumption amidst other factors compared. [ABSTRACT FROM AUTHOR]

The escalating cases of security threats on the global scene, especially in the cyberspace, demands urgent need to deploy sophisticated measures to mitigate these calamitous threats. To this end, various lock mechanisms have been developed and deployed to prevent access to control systems from potential intruders. This paper provides a solution to this pervasive problem, addressing concerns on the physical and virtual components of an access control system. A locally generated One-Time-Passkeys (OTPs) was created, leveraging ambient noise as entropy input. The system was deployed on an Arduino microcontroller embedded in a safe-cabinet secured with a 12V solenoid lock. The design was implemented and tested against standard metrics. Results achieved include algorithmic optimizations of existing local OTP protocol implementations, and the realization of a safe lock module, which interfaces with a mobile application developed on Android over a secured Bluetooth connection. [ABSTRACT FROM AUTHOR]