Drones on the line

Researchers have developed two algorithms to help fleets of drones inspect electricity infrastructure more efficiently, potentially cutting costs and reducing risks to human workers. They provide details in the International Journal of Systems, Control and Communications.

The work offers solutions to two inspection tasks. First, the checking of individual components on electricity pylons, such as insulators, and secondly, surveying transmission lines for hazards. If unmanned aerial vehicles (UAVs), drones, are to be used for these two tasks, then multiple drones operating from a single base to cover routes would be optimal, but there is a need to minimise total flight distance.

For component inspections, the researchers developed an improved genetic algorithm. This is a computational method inspired by natural selection that progressively refines possible solutions. It combines a technique called 2-opt, which improves routes by reversing sections of a flight path, with an adaptive mutation rate. Mutations introduce changes into the possible solutions, which helps the algorithm to avoid poor routes.

For transmission-line inspections, the team developed a separate adaptive genetic algorithm to allocate line segments among drones and minimise unnecessary travel.

Tests on maps of different sizes compared its performance with a conventional genetic algorithm. These showed improvements in solution quality and efficiency over earlier approaches. Indeed, the new methods also produced more stable results for component inspections and reduced flight distances while optimising the number of drones deployed for line surveys.

Li, H., Che, C., Duan, C., Zhang, X. and Sun, L. (2026) ‘Multi-UAV path planning methodology for dual-task power inspection scenarios based on genetic algorithm’, Int. J. Systems, Control and Communications, Vol. 17, No. 9, pp.1–27.

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Research pick: Won't you scroll away the scorn? - "Does using short video apps reduce people’s satisfaction with life quality? Evidence from China"

Frequent use of short video apps is associated with lower satisfaction with one’s quality of life, particularly over perceptions of the wealth gap, according to research in the International Journal of Mobile Communications, which examined the effects of digital media consumption.

The researchers analysed data from 7257 participants aged 16 to 69 in the China Family Panel Studies. They found that satisfaction with wealth inequality was more affected than other aspects of life quality. They also showed that the strongest association was among urban residents, people under 45, and those with at least a high school education.

Two possible explanations emerge. First, declining social trust and secondly, increased negative emotions. The findings have implications for public understanding in China, and perhaps elsewhere, where short video apps are a major source of information and entertainment. In China, 95.5 per cent of internet users use such apps, according to data from the National Radio and Television Administration Development Research Centre.

It is worth noting that short video apps do facilitate wider discussion of social issues. However, it is also well-known that their recommendation algorithms tailor content to one’s viewing habits and can lead to what is known as the bubble, or echo chamber, effect. This may reinforce existing beliefs, and with repetition or unreliable material, distort perceptions of economic and social reality.

The researchers highlight the need to understand how digital media consumption shapes public attitudes towards inequality and living conditions. Moreover, they suggest that there is a need for greater attention to be paid to content quality and information sources.

Tian, W. and Wang, X. (2026) ‘Does using short video apps reduce people’s satisfaction with life quality? Evidence from China’, Int. J. Mobile Communications, Vol. 28, No. 4, pp.400–418.

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Research pick: Concentrating on cricket, right? - "Performance evaluation of cricket players in Indian Premier League using DEA"

An analytical method could help high-level cricket franchises make more informed decisions about player recruitment, retention, and team selection, according to research in the International Journal of Services and Operations Management. The approach uses data envelopment analysis (DEA) to compare efficiency using multiple inputs and outputs. In the world of cricket, this means assessing players against their peers rather than relying on individual statistics.

The research used publicly available data to evaluate the playing of batters and bowlers, with a separate model applied to each group. Metrics included balls faced, runs scored, runs conceded, and wickets taken. The approach offers an effective assessment of players compared to baseline performance in the sport. Moreover, it can identify high performers whose value might be overlooked by conventional assessments.

While the instincts of coaches, managers, and others involved in selecting players will always play the biggest part in the process, having the statistics to back a controversial decision could improve the process while giving those making the decisions a factual basis to defend their decision.

Ultimately, such an approach could be used more broadly in cricket and other sports, helping organisations distinguish measurable productivity from reputation. This should bring greater transparency to decisions about investment, performance improvement, and the allocation of resources.

Bordoloi, S. and Sirigiri, V.S.P. (2026) 'Performance evaluation of cricket players in Indian Premier League using DEA', Int. J. Services and Operations Management, Vol. 55, No. 6, pp.1-36.

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Research pick: Moral machines - "AI-powered precision training pathways for engineering ethics and professional competence in Industry 4.0"

Research in the International Journal of Continuing Engineering Education and Life-Long Learning suggests that artificial intelligence (AI) is increasingly stepping beyond technical automation to train engineers in ethical decision-making. This, the work implies, could address a critical gap in the Industry 4.0 era.

According to new research, an AI-driven framework utilising natural language processing (NLP), knowledge graphs, and deep reinforcement learning can tailor ethics and professional competence training for individual engineers. By analysing engineering case studies against ethical guidelines and tracking user progress through dynamic learner profiles, the system might deliver personalised, adaptive teaching.

The researchers' tests on public datasets showed that their system worked better than traditional lecture-based methods and could predict professional competence and increase interactive training substantially.

Engineering education has in the past involved conventional lectures. That approach to teaching struggles to adapt to individual professional contexts or to incorporate ethical reasoning. Educational technology courses do exist online, but even they are typically optimised for simple performance metrics rather than measuring the true multifaceted value of what is taught and ultimately learned.

The work has implications for corporate compliance but also goes further. Automated and digitalised manufacturing systems are changing industries around the world. As such, the decisions engineers make have international societal and safety risks associated with them. By demonstrating that computers can model complex educational principles and foster a unity of knowledge and action, the team has shown that these computational tools are evolving from passive delivery platforms into what we might think of as active partners in professional development, especially when it comes to ethical and moral considerations.

Cai, S. and Lei, Y. (2026) ‘AI-powered precision training pathways for engineering ethics and professional competence in Industry 4.0’, Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 36, No. 12, pp.4–28.

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Research pick: Making the most of minerals - "Innovation for societal transformation in Africa: a strategic framework for inclusive growth"

Research in the International Journal of Business Innovation and Research suggests that African economies need to move beyond fragmented development strategies. This might be done by uniting digital technology, start-up networks, resource processing, and cross-sector partnerships into a single societal innovation ecosystem, the researchers explain.

The team proposes a conceptual framework designed to tackle persistent structural hurdles, including youth unemployment, energy poverty, and educational deficits. Such a framework might work by extending traditional innovation theories beyond corporate profits by putting more emphasis on broad social progress and inclusive growth.

Historically, innovation frameworks have been tailored to advanced Western economies. These prioritise company-level profits over poverty reduction. In contrast, the new framework discussed in IJBIR brings together various concepts and approaches, including digital technologies, entrepreneurial networks, and public-private collaboration, to help in the development of the domestic processing of raw critical minerals into higher-value products such as batteries prior to export. The approach circumvents the problems that arise when isolated initiatives, such as localized technology hubs or raw extraction projects, fail to generate widespread prosperity despite the potential for profits.

Demand for Africa's minerals is on the rise, partly thanks to the ongoing green energy transition. This new framework offers a strategic blueprint for resource-rich developing nations. Rather than remaining exporters of raw materials, such countries can build high-value domestic supply chains, boost employment, and leapfrog outdated industrial models.

Boikanyo, D.H. (2026) ‘Innovation for societal transformation in Africa: a strategic framework for inclusive growth’, Int. J. Business Innovation and Research, Vol. 41, No. 5, pp.1–26.

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Research pick: What makes money go round? - "The evolution of the digital finance literature on financial behaviour and market risk"

A study of almost 1000 research papers in the field of digital finance has mapped out how technology, investor behaviour, and financial-market risk are connected. The work identified three distinct foundations rather than a single framework with implications for understanding how psychological factors influence financial decisions as well as how to develop viable algorithms that provide automated investment guidance.

The team used standard bibliometric analysis to find patterns and relationships across the literature published in this niche from 1991 to 2025. They carried out co-citation analysis to identify research that is frequently cited together, as well as keyword analysis to trace connections between research areas. Details are reported in the International Journal of Business and Emerging Markets.

Four main research streams were found: FinTech (financial technology) and investor behaviour, artificial-intelligence-driven investment decisions, market prediction, and automated trading and risk management. FinTech, market volatility and machine learning were identified as established “motor themes”, meaning areas that are both prominent and strongly connected to other research.

The researchers argue that their mapping of the literature has practical implications for developers, financial institutions, and regulators. Automated investment services may require clearer risk information and greater transparency about how recommendations are produced. Regulators could also pay closer attention to model risk and common signals used in automated trading.

Van Nguyen, N., Phan, H.T. and Tran, L.T. (2026) ‘The evolution of the digital finance literature on financial behaviour and market risk’, Int. J. Business and Emerging Markets, Vol. 18, No. 10, pp.1–32.

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Free Open Access issue published by International Journal of Reasoning-based Intelligent Systems

The International Journal of Reasoning-based Intelligent Systems has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Aesthetic evaluation system of artificial intelligence generated graphic design based on convolutional neural network and expert scoring
• The informationisation and precise management mechanism of physical education teaching by introducing VGG19 network
• Automated audit report generation and risk insight based on large language models
• A computational framework for large-scale tail-risk assessment of CSI 300 constituents: algorithmic EVT-POT estimation, cross-sectional diagnostics and automated stress testing
• Athletes' physical fitness assessment and load regulation system based on TimesNet and short-term memory network

New Open Access article available: "Real-time logistics route planning and energy consumption simulation modelling from a green computing perspective"

The following International Journal of Simulation and Process Modelling article, "Real-time logistics route planning and energy consumption simulation modelling from a green computing perspective", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.

Free Open Access special issue on "Intelligent Learning Ecosystems: AI, Metaverse and Emerging Technologies for Continuing Engineering Education – Part 2" published by International Journal of Continuing Engineering Education and Life-Long Learning

The International Journal of Continuing Engineering Education and Life-Long Learning has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Intelligent English composition scoring method based on transfer paragraph segmentation and Pearson detection
• Construction of an English academic writing teaching algorithm integrating LLM and move segmentation
• ITGAM: a co-attention and multi scale attention tandem convolutional network for multimodal sentiment analysis in English speech
• English essay topic analysis using conceptual prior knowledge and Bi-GRU
• English machine translation based on parallel corpus mining and transfer learning

All quiet in the firing line

A study of the oil, gas and petroleum industry has found that “quiet firing” by employers is associated with higher levels of “quiet quitting” among employees, while strong workplace relationships can weaken that effect. The research appears in the International Journal of Business Information Systems.

Quiet quitting, a term that has gained prominence in recent years, describes employees limiting their work to their formal responsibilities rather than taking on additional effort. Quiet firing refers to employers indirectly encouraging workers to leave by creating an undesirable working environment or withholding opportunities and support.

The research showed that there is a positive relationship between the two practices: as quiet firing increased, so did quiet quitting. But the relationship was weaker where workplaces had greater social capital, the networks, trust, shared norms and relationships that enable people to cooperate and communicate with each other more effectively.

The findings have implications for human resource management as attention might move from the disengagement of individuals and the impact on turnover to overarching organisational behaviour. Rather than treating quiet quitting solely as a problem of employee motivation, the research suggests that management practices can contribute to withdrawal and should be considered too.

Rajabpour, E., Mohammadi, H., Amoozegar, A., Falahat, M., Shakib, S. and Omar, M.M. (2026) ‘Silent strategies: navigating the complex web of quiet firing and quiet quitting with social capital mediation’, Int. J. Business Information Systems, Vol. 53, No. 5, pp.1–25.

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New Open Access article available: "Multimodal simulation for diagnosing microstrabismus integrating electrooculogram and electroencephalographic signals"

The following International Journal of Simulation and Process Modelling article, "Multimodal simulation for diagnosing microstrabismus integrating electrooculogram and electroencephalographic signals", is freely available for download as an open access article.

It can be downloaded via the full-text link available here.