Winter is coming and in many places with it the risk of ice accumulation on overhead power lines and all the problems that can lead to, including, in extreme cases, pylon collapse.

Writing in the International Journal of Energy Technology and Policy, a team from China describes a new approach to monitoring ice accumulation on power lines and pylons using unmanned aerial vehicles, drones, to acquire images of the infrastructure and image-processing algorithms to identify icy problems.

Yang Yang, Hongxia Wang, Meng Li, Minguan Zhao, Yuanhao Wan, and Shuyang Ma of Xinjiang Power Transmission, Urumqi, Shenbing Hua of China Electric Power Research Institute Co., Ltd., Qifei He of the Power Dispatch Control Center of State Grid Corporation of China, Beijing, China, suggest their work could improve winter safety and reliability of electricity networks. It has real implications for countries such as China where transmission lines cross vast and diverse terrains stretching across remote and largely inaccessible areas.

Conventional approaches to checking for dangerous ice accumulation have led operators to act either too conservatively and so undertaking unnecessary maintenance or less cautiously and too late, risking damage and power outages. The new method uses camera-equipped drones to capture live images of power lines and then applies compressive sensing theory to the images to remove environmental noise and clean the data for processing. The Canny algorithm is then applied to carry out advanced edge detection to reveal ice formation on power lines. A random Hough transform then finds the straight edges of the ice deposits and helps with calculations of the ice thickness to show which stretches of transmission lines are likely to be problematic.

With China's weather extremes, a better way to monitoring power lines in winter is crucial to keeping the lights on.

Yang, Y., Hua, S., Wang, H., Li, M., He, Q., Zhao, M., Wan, Y. and Ma, S. (2024) 'Detection method of icing thickness of overhead transmission lines based on canny algorithm', Int. J. Energy Technology and Policy, Vol. 19, Nos. 3/4, pp.344–362.
DOI: 10.1504/IJETP.2024.141389

A fictional business case study of an imaginary company known as Bright Lights is discussed in a research paper in the International Journal of Teaching and Case Studies. As the case study pans out, so the authors of the paper allude to the ethical decisions that a company might need to make and how these affect its response to strategic challenges, and ultimately its bottom line.

Lee Tyner and M. Suzanne Clinton of the University of Central Oklahoma in Edmond, Oklahoma, USA, consider Jim, one of Bright Light's top sales people. Jim's enterprising response to the company's new policies now has Bright Lights asking tough questions about loyalty, ethics, and the future of its corporate culture. Jim is known for generating strong sales through an innovative approach, but he is finding himself at odds with a major strategic shift initiated by the newly appointed national sales manager, Cindy. Cindy is a follower of the Pareto principle, 80% of revenue comes from 20% of clients. This has led her to nudge the company towards larger accounts, which has side lined smaller, loyal customers.

Cindy's approach is a data-driven approach common among many real businesses and is usually aimed are warding off rising competition and declining market share. But, it is implemented at a cost of carefully cultivated relationships of the kind that traditional salespeople may have cultivated over a long period with smaller but high-margin clients. In the imaginary case study, many of the smaller clients, no longer serviced by Bright Lights, feel abandoned, and face dissatisfaction with new suppliers. A common side effect of implementing the Pareto principle in the real world of business.

Jim has spotted an opportunity that will help him sustain his income and the lifestyle it brings. Jim's answer if not necessarily black hat, may nevertheless represent a grey area ethically speaking. Jim has formed a side business to fill the gap left by the strategic pivot of Bright Lights. This company buys up Bright Lights' inventory and then sells it to Jim's smaller clients who have been disenfranchised by Cindy's approach. Jim is not working in competition with his employer, strictly speaking, but it presents a dilemma for Bright Lights.

Should the company applaud Jim's initiative even if it blurs ethical lines and perhaps fragments the sales force or should it punish and so disenfranchise him, one of their top salespeople. How they respond will send a message to other salespeople in the company perhaps suggesting that innovative thinking and branching out in this way is not something the company wishes to promote.

The researchers suggest that the ethical dilemmas that their fictional case study raises could help companies examine the dynamics of their own place in the rapidly evolving business world where employees might take the initiative in improving their income.

Tyner, L. and Clinton, M.S. (2024) 'Case study: when a bright idea creates a business dilemma', Int. J. Teaching and Case Studies, Vol. 14, No. 4, pp.384–392.
DOI: 10.1504/IJTCS.2024.139178

Research in the International Journal of Technological Learning, Innovation and Development considers the growing influence of the large language model (LLM) ChatGPT. This and related tools are often colloquially referred to as generative artificial intelligence (AI) algorithms. The team has looked at how it might affect higher education.

Sami Mejri of Khalifa University, Moatsum Al Awida of Abu Dhabi University, Stavroula Kalogeras of Heriot-Watt University, Dubai, and Bayan Abu Shawar of Al Ain University, UAE, discuss some of the opportunities and risks faced by academic institutions where students and educators are using LLMs. This kind of software can be prompted to generate text that has many of the characteristics of human-written text and has already become a powerful tool in many areas. However, there are growing concerns about the impact of LLMs and related tools on academic integrity and the nature of education.

The team surveyed faculty, staff, and student groups and found that there is a tension between the potential for AI-driven educational innovation and the need to safeguard the principles of academic integrity. The researchers found that many respondents suggested that ChatGPT has the potential to reshape student engagement, creativity, and communication. However, there are risks associated with its use, not least reduced student effort and an increase in what might be considered academic dishonesty.

The ability of such tools to auto-generate coherent text from the vast datasets used to train ChatGPT, like a glorified autocomplete, one might ungenerously say, would suggest that its widespread use might undermine student intellectual development. Conversely, it might be argued that, aside from the issue of the origins of those datasets and copyright and plagiarism issues, the use of LLMs requires a level of creativity in devising prompts to trigger particular kinds of output from the LLMs and to make them useful. There is also a great need to validate and fact check any output from such tools.

The researchers suggest that there are various implications of their research. Higher education must adapt to the digital age and the emergence of AI tools like ChatGPT and others. These tools might transform not only how students learn but also how educators assess them. Traditional methods of assessment, such as essays or written exams, may need to be rethought as LLMs come to the fore.

As mentioned, there is creativity to be developed in prompting the likes of ChatGPT and it might be that the long-term effects on developing critical thinking, a foundational skill of education, could be taught or tailored to the assessment and validation of LLM output in ways not previously possible with published text, say. Educators might prompt their students to prompt an AI, but the learning and critical thinking skills then come from interpretation and assessment of the LLM output itself and comparison with how people might respond to those prompts.

There is no obvious answer to how we decided on where AI sits within education. We should recognise that AI and LLMs are tools, all tools can be used for good or bad. Educators will need to acquire an overarching understanding of these new tools, just as they did with earlier technological developments, and then be the guide for their students in their use as well as their instructors so that students can learn to use the tools positively.

Mejri, S., Al Awida, M., Kalogeras, S. and Shawar, B.A. (2024) 'ChatGPT: an emerging innovation or a threat to creativity and knowledge generation?', Int. J. Technological Learning, Innovation and Development, Vol. 15, No. 4, pp.425–448.
DOI: 10.1504/IJTLID.2024.140320

A little-known threat to tourists in the form of stinging jellyfish could affect those who like to take a dip in between lazing in the heat on the sun-drenched beaches of Málaga. These sea creatures are of increasing concern along Spain's most tourism-dependent coastline, the Costa del Sol with more and more frequent outbreaks of jellyfish swarms since the summer of 2018. While beachgoers are often preoccupied with sunscreen and sangria, it turns out that jellyfish are creating a new kind of trouble in paradise, according to research published in Progress in Industrial Ecology, An International Journal.

Francisco José Cantarero Prados and Ana Luisa de la Fuente Roselló of the Department of Geography at the University of Málaga have studied the jellyfish swarms along Málaga's coastline, pinpointing the sections where swimmers are most at risk of encountering the creatures. To gather data, the researchers turned to citizen science and two mobile apps: Infomedusa and Medusapp. These apps allowed ordinary beachgoers to report jellyfish sightings in real-time. The crowdsourced data could then be combined with historical scientific data from the regional government. The team suggests that the citizen science data represents a useful, scalable, and cost-effective means of environmental monitoring.

The researchers then used geographic information system (GIS) technology to chart detailed maps of the coast and show that a 50-kilometre stretch from Benalmádena to Torre del Mar is particularly risky based on the historical and citizen science data. The implications of the research are important for beach tourism. Jellyfish blooms can shake up tourism, deterring visitors and so threatening the local economy.

The same approach to citizen science and GIS might also be used in the future to map and monitor other harmful coastal phenomena such as algal blooms, shark sightings, or even the effects of climate change on local marine ecosystems.

Cantarero Prados, F.J. and de la Fuente Roselló, A.L. (2024) 'Citizen science as a resource to define threats to bathing on beaches: the case of jellyfish in Malaga', Progress in Industrial Ecology – An International Journal, Vol. 17, Nos. 1/2, pp.26–39.
DOI: 10.1504/PIE.2024.140515

The concept of rurality is well-trodden ground in policy discussions, but less attention has been given to its more elusive sibling, remote-rurality. A study in the World Review of Entrepreneurship, Management and Sustainable Development has looked at this concept and reveals the complexities of defining and addressing the needs of remote-rural areas, particularly in Scotland, where the distinction is not merely academic but vital to economic sustainability and infrastructure planning.

Sayed Abdul Majid Gilani and Naveed Yasin of the Canadian University Dubai, UAE, and Peter Duncan and Anne M.J. Smith of Glasgow Caledonian University, UK, introduce five dimensions to discuss remote-rural regions: population size, proximity to urban centres, level of development, cultural characteristics, and social perception. These categories highlight the inadequacy of relying on a single definition for remote-rural areas, emphasizing the need for a multidimensional approach.

Defining "rural" is no simple task, the team points out, as various countries use different metrics – such as population thresholds of under 2500 in the USA and fewer than 10000 in the UK. However, the addition of remote-rurality introduces further layers of isolation, limited services, and distinct cultural identities that demand attention from researchers and thence from policymakers.

In Scotland, the government distinguishes between "accessible-rural" and "remote-rural" regions, the latter being considerably more isolated from urban hubs. This distinction is more than theoretical – it has implications for infrastructure, most notably transport, food availability, and now, broadband connectivity, which remains alarmingly inadequate in many remote-rural areas. The research highlights that over 80% of businesses in Scotland's remote regions are small or medium-sized enterprises (SMEs), many of which cannot operate effectively nor efficiently because they lack access to basic services those in urban regions take for granted.

In this study, the team urges policymakers to adopt a more nuanced understanding of remote-rural areas when considering infrastructure investments. By addressing the challenges faced by such communities, governments might create conditions that enable businesses not just to survive, but to thrive, and so preclude the exodus of SMEs to the cities. This would not only benefit those business but reduce some of the pressure on already overcrowded cities as well as reducing the cultural and economic divide between urban and rural areas.

The team emphasizes that enhanced broadband access, for instance, could allow SMEs to operate more efficiently and allow them to exploit national and global markets more effectively. The survival of these SMEs, is often critical to the economic sustainability of remote-rural regions.

Gilani, S.A.M., Yasin, N., Duncan, P. and Smith, A.M.J. (2024) 'What is remote-rural and why is it important?', World Review of Entrepreneurship, Management and Sustainable Development, Vol. 20, No. 5, pp.517–537.
DOI: 10.1504/WREMSD.2024.140706

A new system aimed at improving the monitoring and detection of forest fires through advanced real-time image processing is reported in the International Journal of Information and Communication Technology. The work could lead to faster and more accurate detection and so help improve the emergency response to reduce the environmental, human, and economic impacts.

Zhuangwei Ji and Xincheng Zhong of Changzhi College, in Shanxi, China, describe an image segmentation model based on STDCNet, an enhanced version of the BiseNet model. Image segmentation involves classifying areas within an image to allow flames and forest background to be differentiated. The STDCNet approach can extract relevant features efficiently without demanding excessive computational resources.

The team explains how their approach uses a bidirectional attention module (BAM). This allows it to focus on distinct characteristics of different image features and determine the relationships between adjacent areas in the image within the same feature. This dual approach improves the precision of fire boundary detection, particularly for small-scale fires that are often missed until they have grown much larger.

Tests with the model on a public dataset showed better performance than existing approaches in terms of both accuracy and computational efficiency. This bolsters the potential for real-time fire detection, where early identification can prevent fires from spreading uncontrollably.

The new system has several advantages over standard fire detection methods, such as ground-based sensors and satellite imagery. These have limitations such as high maintenance costs, signal transmission issues, and interference from environmental factors such as clouds and rugged terrain. The researchers suggest that drones equipped with the new image processing technology could offer a more adaptable and cost-effective alternative to sensors or satellites, allowing fire detection to be carried out in different weather conditions and in challenging environments.

Ji, Z. and Zhong, X. (2024) 'Bidirectional attention network for real-time segmentation of forest fires based on UAV images', Int. J. Information and Communication Technology, Vol. 25, No. 6, pp.38–51.
DOI: 10.1504/IJICT.2024.141434

Online gaming is increasingly popular. As such, server efficiency is becoming an increasingly urgent priority. With millions of players interacting in real-time, game servers are under enormous pressure to process a huge amount of data without latency (delays) or crashes. Research in the International Journal of Information and Communication Technology discusses an innovative solution to the problem, offering a promising path to greater stability and performance in mobile real-time strategy games and beyond.

WenZhen Wang of the Animation Art Department at Zibo Vocational Institute, Zibo, Shandong, China, hope to address the most critical issue in online multiplayer games – load balancing to ensure there is a high level of concurrency and interactivity. Load balancing refers to the distribution of work across multiple servers to prevent any one server from being overwhelmed. If a server receives too many requests at once, it can slow down, leading to frustrating lag or even server crashes. Ensuring efficient distribution of this workload is essential to maintaining a seamless gaming experience.

Wang has introduced a new method for handling load balancing using a "consistent hash" algorithm. In simple terms, a hash function takes an input – player activity or game data – and converts it into a fixed-size output, a sequence of characters, or hash. This consistent hash helps the system allocate data and tasks across multiple servers more evenly because it knows in advance the size of the packets of data, rather than having to handle packets of different sizes on the fly. The main advantage lies in its adaptability to the highly dynamic environments of multiplayer games, where the number of players and the complexity of in-game interactions changes quickly throughout the game.

To test the effectiveness of the algorithm, Wang ran virtual simulations replicating real-world game scenarios and demonstrated that the approach allowed for load balancing that led to stable server operations. The system could then handle large numbers of simultaneous player interactions while maintaining performance quality.

Wang, W. (2024) 'Virtual simulation of game scene based on communication load balancing algorithm', Int. J. Information and Communication Technology, Vol. 25, No. 6, pp.18–37.
DOI: 10.1504/IJICT.2024.141435

The media landscape is increasingly complicated. It is also plagued by sensationalism and a disconnection between media literacy and management practices. Many observers worry about the proliferation of 'click bait' and "fake news". Misleading reports rife with hyperbole exacerbate the problems faced by many people, and the distortion of serious issues creates a turbulent environment where the lines between information, disinformation, and misinformation are often blurred. Moreover, the lack of a clear distinction between the news and the public relations and marketing output of companies, especially in the age of influencers, is also of increasing concern.

Research in the International Journal of Information and Communication Technology, suggests that the only way to address these problems is to make a determined shift towards more rigorous news ethics, adapted to the modern media environment. An Shi of Fujian Business University, in Fuzhou, Fujian, China, points out that the use of mathematical algorithms, specifically the Fredholm integral equation algorithm, could help us tackle many of the complex problems we have with the news media. Despite the often negative press about artificial intelligence (AI), ironically it is the use of machine learning, trained algorithms, and neural networks that might provide us with an escape route from the era of clickbait and fake news.

It is worth noting that the concept of 'non-standard' press behaviour has been with us for many years – a term introduced to address deviations from accepted professional standards in the media. Where these ethical shortcomings undermine societal responsibilities and negatively affect audiences, there is a serious problem. This has been exacerbated by the move from traditional media channels, such as newspapers, radio, and television – to dynamic platforms like social media and online news outlets where the frontiers are wide open.

Empirical studies have demonstrated that the influence of unethical practices in the media extends way beyond public perception into financial markets and politics. The rapid dissemination of news can significantly impact stock prices and market stability and even affect the outcomes of election and referenda, or at the least colour the public response to them. The current work offers policy recommendations and governance schemes that could help market regulators and company managers ameliorate the negative impact of clickbait and fake news.

Shi, A. (2024) 'News media coverage and market efficiency research based on Fredholm integral equation algorithm', Int. J. Information and Communication Technology, Vol. 25, No. 6, pp.68–77.
DOI: 10.1504/IJICT.2024.141438

Research published in the International Journal of Information and Communication Technology may soon help solve a long-standing challenge in semiconductor manufacture: the accurate detection of surface defects on silicon wafers. Crystalline silicon is the critical material used in the production of integrated circuits and in order to provide the computing power for everyday electronics and advanced automotive systems needs to be as pristine as possible prior to printing of the microscopic features of the circuit on the silicon surface.

Of course, no manufacturing technology is perfect and the intricate process of fabricating semiconductor chips inevitably leads to some defects on the silicon wafers. This reduces the number of working chips in a batch and leads to a small, but significant proportion of the production line output failing.

The usual way to spot defects on silicon wafers has been done manually, with human operators examining each wafer by eye. This is both time-consuming and error-prone due to the fine attention to detail required. As wafer production has ramped up globally to meet demand and the defects themselves have become harder to detect by eye, the limitations of this approach have become more apparent.

Chen Tang, Lijie Yin and Yongchao Xie of the Hunan Railway Professional Technology College in Zhuzhou, Hunan Province, China explain that automated detection systems have emerged as a possible solution. These too present efficiency and accuracy issues in large-scale production environments. As such, the team has turned to deep learning, particularly convolutional neural networks (CNNs), to improve wafer defect detection.

The researchers explain that CNNs have demonstrated significant potential in image recognition. They have now demonstrated that this can be used to identify minute irregularities on the surface of a silicon wafer. The "You Only Look Once" series of object detection algorithms is well known for being able to balances accuracy against detection speed.

The Hunan team has taken the YOLOv7 algorithm a step further to address the specific problems faced in wafer defect detection. The main innovation in the work lies in using SPD-Conv, a specialized convolutional operation to enhance the ability of the algorithm to extract fine details from images of silicon wafers. Additionally, the researchers incorporated a Convolutional Block Attention Module (CBAM) into the model to sharpen the system's focus on smaller defects that are often missed in manual inspection or by other algorithms.

When tested on the standard dataset (WM-811k) for assessing wafer defect detection systems, the team's refined YOLOv7 algorithm achieved a mean average precision of 92.5% and had a recall rate of 94.1%. It did this quickly, at a rate of 136 images per second, which is faster than earlier systems.

Tang, C., Yin, L. and Xie, Y. (2024) 'Wafer surface defect detection with enhanced YOLOv7', Int. J. Information and Communication Technology, Vol. 25, No. 6, pp.1–17.
DOI: 10.1504/IJICT.2024.141433

Odd as it may seem, coal seams that cannot be mined might provide an underground storage medium for carbon dioxide produced by industries burning coal above ground. Research in the International Journal of Oil, Gas and Coal Technology has undertaken controlled experiments designed to simulate the deep geological environments where carbon dioxide might be trapped as a way to reduce the global carbon footprint and ameliorate some of the impact of our burning fossil fuels. Coal seams represent a potential repository for long-term storage of carbon dioxide sequestered from flue gases, as they can trap a lot of carbon dioxide gas in a small volume.

Major Mabuza of the University of Johannesburg, Johannesburg, Kasturie Premlall of Tshwane University of Technology, Pretoria, and Mandlenkosi G.R. Mahlobo of the University of South Africa, Florida, South Africa, subjected coals to a synthetic flue gas for 90 days at high pressure (9.0 megapascals) and a mildly high raised temperatures of 60 degrees Celsius. These conditions were intended to replicate the pressures and temperatures found deep underground, providing a realistic model for how coal might behave when used for carbon dioxide sequestration.

The team then looked at how the chemical structure of coal was changed by exposure to flue gas under these conditions using various advanced analytical chemistry techniques – carbon-13 solid-state nuclear magnetic resonance spectroscopy, universal attenuated total reflectance-Fourier transform infrared spectroscopy, field emission gun scanning electron microscopy with energy dispersive X-ray spectroscopy, and wide-angle X-ray diffraction.

The results showed that exposure to synthetic flue gas led to major changes to the chemical makeup of the coal. For instance, key functional groups, such as aliphatic hydroxyl groups, aromatic carbon-hydrogen bonds, and carbon-oxygen bonds, were all weakened by the process and the overall physical properties of the coal were also changed.

By clarifying how coal interacts with flue gas under simulated, but realistic, conditions, the team fills important gaps in our knowledge about the long-term stability and effectiveness of carbon dioxide storage below ground and specifically in coal seams.

Mabuza, M., Premlall, K. and Mahlobo, M.G.R. (2024) 'In-depth analysis of coal chemical structural properties response to flue gas saturation: perspective on long-term CO2 sequestration', Int. J. Oil, Gas and Coal Technology, Vol. 36, No. 5, pp.1–17.
DOI: 10.1504/IJOGCT.2024.141437