The following paper, "Improved SSD-based visual sorting control for industrial robots" (International Journal of Information and Communication Technology 25(8) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Technology increasingly relies on facial recognition, whether to unlock one’s smartphone or to monitor public spaces. However, faces move, cameras rarely face catch use perfectly face on. People tilt their heads, glance sideways, or are caught in the periphery of a busy scene. This issue thus remains a challenge for facial recognition systems that tend to need our full attention, as it were.
Research in the International Journal of Information and Communication Technology discusses a new approach developed by a team in China – the Guided Deformable Attention (GDA) network. Bin Deng and Guanghui Dengof Hunan University of Technology in Zhuzhou, Hunan, China, say this approach steps up to address the problem of rotated faces. The system could improve security systems as well as have applications in gaming and the entertainment industry in general.
Standard facial recognition systems use convolutional neural networks (CNNs) to detect features such as our eyes and nose based on their expected position in a straightforward, front-facing portrait. They are quite rigid in how they work and require fixed kernels to detect those features and confirm an identity based on the precise positions, size, and shape in the acquired image of the person’s face. The CNNs have been improved in recent years by allowing deformable convolutions, but this still does not work well in complicated real-world environments such as crowds or other busy scenes.
The new GDA network approach could solve the problem by introducing a guiding mechanism that helps the system remain focused on the face itself, regardless of orientation or background noise. The key innovation here is the system’s ability to maintain its focus on the essential structure of a face even when there are distractions in the scene. The system, the researchers explain, knows what a face looks like and can remain locked on it. This is not dissimilar to the ability of many modern digital cameras to track a moving object, such as an animal, and to focus lock on to the animal’s eye for the best photograph.
The GDA first identifies the location of the face within an image using an affine matrix, a mathematical method that allows the system to rotate or scale the image to get a better understanding of where the face might be. The second step is to refine this detection process using those deformable convolutions. It does this in such a way as to remain locked on the face and not turns its digital attention to competing objects or noise in the acquired image.
Thus, in security surveillance, where faces in a crowd rarely present themselves in perfect profile, the system can home in on a chosen face, and accurately detect that face in the crowd for subsequent identification. The approach is not limited to security and law enforcement. It could be used in virtual reality and augmented reality, where users’ faces are often seen from different angles yet accurate face detection is important to creating an immersive, real-time experience for the user.
Deng, B. and Deng, G. (2024) ‘Rotation-invariant face detection with guided deformable attention’, Int. J. Information and Communication Technology, Vol. 25, No. 8, pp.32–48.
The following paper, "Spatial visual expression effect of fine art design considering virtual reality and augmented reality technology" (International Journal of Information and Communication Technology 25(8) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "Optimisation of news propagation path in media convergence era under interactive digital media technology" (International Journal of Information and Communication Technology 25(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
In an era where realism is expectated in animated films, motion capture technology (MCT) has emerged as the secret weapon of modern animation studios. Thanks to its ability to capture and replicate real-life movements, the technology has transformed the creative process, allowing digital characters to leap, stroll, and even blink with a degree of nuance that was not possible in animation just a few years ago.
Once upon a time, animators had to painstakingly create frames by hand to create the illusion of movement. Computers reduced the workload but the subtlety of human movement and facial expression was often lost and an animated character would never look quite as authentic as an actor. Motion capture opened up a more direct route to visual realism and allowed the creatives to tell their stories more evocatively than ever before. Today, digital artists can access libraries of real-world movements and expressions that can be incorporated into their work.
The impact of this technology can be seen in landmark films such as Avatar and The Lord of the Rings, where MCT breathed life into digital creatures and characters, making their movements appear real and adding emotional authenticity to the characters. Indeed, the technology’s ability to replicate dynamic body language and facial expressions with precision allows animations to mimic the subtleties of behaviour, whether that’s a playful wink from the heroine or the flick of a unicorn’s tail.
All that said, the application of motion capture is no longer the reserve of the movie industry. Writing in the International Journal of Information and Communication Technology, Zhuqing Liu of the Jin Zhong Vocational and Technical College in Shanxi, China, explains how this technology is now spilling into the virtual and augmented reality environments. Here it is leading to new approaches in creating immersive and interactive experiences.
Liu explains that motion capture systems are not perfect and still have challenges such as limb and hand detection for the most intricate movements crucial to truly life-like animation. Better sensors and higher-resolution cameras are allowing the initial motion capture to be done more accurately. The ongoing refinement of software, meanwhile, is heading inevitably into the area of advanced algorithms and machine learning which can analyse those captured movements and allow them to be replicated in an animation with intricate and realistic detail.
The technology has obvious applications in film and television, but also in video games, and even medical simulations as well as in research looking at how our bodies move in real life.
Liu, Z. (2024) ‘Optimisation of digital media technology for film and television animation post-production considering motion capture technology’, Int. J. Information and Communication Technology, Vol. 25, No. 8, pp.1–13.
The following paper, "Architecture and research of photovoltaic hybrid microgrid control system combined with renewable energy" (International Journal of Power and Energy Conversion 15(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "Chaotic colour image encryption based on differential evolutionary deep learning" (International Journal of Information and Communication Technology 25(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
There is an urgent need to transition from conventional energy sources to environmentally friendly, sustainable alternatives. Research in the International Journal of Power and Energy Conversion, discusses a control system that could be used to balance solar and wind power within a hybrid microgrid. The work could help address the issue of the inherent unpredictability of power generation involving solar and wind, so improving the overall reliability of a microgrid power supply.
A hybrid microgrid typically has a few core components: Renewable energy sources including solar panels, wind turbines, or sometimes hydroelectric systems. They also have conventional backup, such as a fossil fuel generators or other traditional energy source. They usually have batteries as an energy storage system. A control system integrates the different energy sources to give as steady and efficient an output as possible.
Such hybrid microgrids could be the power-generating mainstay of remote and off-grid areas of the world, such as remote villages or even mines and other industrial sites. They might also be employed in disaster zones when conventional power supply has been disrupted by extreme weather events, earthquakes and other geological activity, or due to military activity.
Guoku Wang of Harbin Institute of Petroleum, China, explains that while renewable energy is at the heart of global sustainability goals, it presents us with a major problem: instability. Solar power fluctuates with light conditions, while wind power is as changeable as the weather. A new approach that integrates photovoltaic (solar) power generation with direct-drive wind power within a smart system could automatically adjust its operations to accommodate changing environmental conditions.
The research demonstrates how the system can compensate for real-time changes in wind speed and sunlight. When wind conditions are unfavourable, the system responds by increasing the photovoltaic output to maintain a steady power supply. The adaptive balancing keeps power supply stable, mitigating for the dips and spikes that can be common with renewable energy supply.
Wang, G. (2024) ‘Architecture and research of photovoltaic hybrid microgrid control system combined with renewable energy’, Int. J. Power and Energy Conversion, Vol. 15, No. 5, pp.1–19.
The following paper, "Method of target damage probability distribution simulation and evaluation based on GPU parallel computing" (International Journal of Information and Communication Technology 25(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "Application of image colour matching algorithm based on visual perception model in clothing design" (International Journal of Information and Communication Technology 25(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Digital media technology has changed journalism considerably, and perhaps most obviously in data journalism. Data journalism uses the power of data analysis and visualization to develop news stories that can be highly engaging and accessible to the public. Yet, as this particular form of journalism matures, there are obstacles to its efficient sharing and consumption.
Research in the International Journal of Information and Communication Technology has looked at the pathways through which data-driven news is conveyed. Yizhou Gong of Macau University of Science and Technology and Zhihu Shi of the Jiangsu Broadcasting Corporation, China, used social network analysis and viral communication theories to identify the three main ways in which data-driven journalism is disseminated. The team found that the efficacy of the different channels is often compromised by simplistic communication tools, many of which have been used since this early days of data journalism. This limitation has restricted user interactivity, as well as narrowing the focus on familiar subjects, such as finance and entertainment.
The team points out that early platforms sharing data journalism stories simply integrated text with basic visuals. Given the power of the mobile devices so many people carry with them at all times, the inadequacy of those early approaches, which are still widely used, emphasises again and again how they fail to capture the public imagination in many cases. There is a pressing need for enhanced interactive features to engage the public once more in data journalism.
Moreover, the research points to a need to integrate adaptive recommendation algorithms to optimize how data news reaches the audience in the first place. Algorithms that might tailor content based on user interests and historical preferences could lead to a more personalized experience. Such an approach has the potential to broaden audience engagement and extend the reach of data-driven stories. This kind of change is essential if journalism, and specifically data journalism, is to remain relevant and thrive, the work suggests.
Gong, Y. and Shi, Z. (2024) ‘Optimisation of news propagation path in media convergence era under interactive digital media technology’, Int. J. Information and Communication Technology, Vol. 25, No. 7, pp.25–36.
The following paper, "Edge detection algorithm of insulator hydrophobic image in CPS system considering deconvolution and deblurring algorithm" (International Journal of Information and Communication Technology 25(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "Logics alignment in agile software design processes" (International Journal of Agile Systems and Management 17(6) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Traditional lessons in economics seem to have less of a place in this world when they fail to change students who are often more interested in the latest viral content and influencers. However, it could be the best day for educators who recognise this and speak now. They might turn to unexpected allies, such as pop culture icon Taylor Swift or maybe even social media influencer James Stephen Donaldson, better known to millions online as MrBeast.
Both stars are globally celebrated not only for their fame but for their remarkable business acumen. A new wave of research suggests that using their stories might be the key to engaging Generation Z students, the so-called Zoomers, in the subject of economics. Gen Z is demographically the generation born 1997 to 2012. Swift and Donaldson were born in 1989 and 1988 respectively and themselves are mid-generation Millennials (Gen Y, born 1981 to 1996). Millennials are usually considered the digital natives, individuals who grew up in a world where personal computing and communications had become almost ubiquitous.
Research in the International Journal of Pluralism and Economics Education suggests that an innovative approach to teaching economics might focus on how such celebrities, which many students already admire, develop their businesses. For instance, Swift’s record-breaking Eras Tour grossed more than $1 billion, while MrBeast’s YouTube “empire”, which includes entrepreneurial ventures such as his Feastables brand, offers real-world examples of economics in action. From pricing strategies to branding, these two have built formidable enterprises, making them ideal case studies to explain otherwise abstract economic concepts.
Educators know all too well that engaging case studies are important in navigating the treacherous world of teaching economics, where a blank space might disenfranchise even the keenest student. What sets apart a method that focuses on such well-known figures as case studies, is that they have a ready-made resonance with Gen Z. This generation was raised on digital content and stereotypically has a short attention span and yet prizes entrepreneurship and innovation.
Even in their wildest dreams, students in a typical high school economics class will be taught little more than equations and theoretical models. Even if all they had to do was stay, this can seem distant and irrelevant to many students. Call it what you want, but by incorporating Swift and MrBeast into the curriculum, the teacher’s new end game is to illustrate complex economic ideas, such as supply and demand, monetization strategies, and market engagement, in the afterglow of personalities they admire and follow closely or at the very least know a lot about. It can be an epiphany.
The work hints at an educational gold rush, where this shift in focus could transform the way economics is taught and how well students understand and learn about the subject. To cut a long story shot, by moving beyond dry textbooks, a pop culture approach might draw into economics a diverse and inclusive group of students.
It doesn’t take a mastermind to navigate the labyrinth of thinking on how this all might come to more than sweet nothing. Many young people already admire the entrepreneurial journeys of their favourite influencers and celebrities. If educators can demonstrate that economics is more than spreadsheet and Wall Street, then the creativity, audience engagement, and smart financial decisions of those celebrities will appear almost bejewelled and show how economics is part of all our lives, it is, in a sense, everyday alchemy.
Dahlberg, K.H., DeWind, S., Geerling, W. and Mateer, G.D. (2024) ‘Behind the billions: how Taylor Swift and MrBeast can be used to teach economics’, Int. J. Pluralism and Economics Education, Vol. 15, No. 1, pp.69–89.
The following paper, "Prototyping in motorsports: exploring manufacturer-supplier collaboration in Formula One" (International Journal of Automotive Technology and Management 24(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Managing an increasingly diverse workforce is no longer a mere rubber-stamping exercise for companies, it is an essential and beneficial part of the corporate agenda. Organizations are beginning to recognise that diversity underpins success in the modern world.
A comprehensive review of more than 2500 research papers, shows that unlocking the full potential of a diverse workforce lies at the intersection of human resource management and what we might term diversity management. The review published in the International Journal of Management Practice suggests that many companies in disparate areas are yet to reach this intersection.
Federica Testa, Alessandro Hinna, and Rocco Palumbo of the University of Rome Tor Vergata, and Federico Ceschel of the University of Rome Tre, Italy, explain that diversity management refers to policies and practices that are aimed fundamentally at creating an inclusive work environment. It ensures that all employees feel valued, respected, and empowered to contribute. This inclusiveness has direct and measurable effects on motivation, performance, and innovation, the review suggests. Moreover, companies that successfully manage diversity often outperform their competitors.
Where conventional human resource management is involved in how an organization manages its people, the employment lifecycle, from recruitment and training to compensation and performance evaluation, diversity management adds critical functions. The research highlights how these might best be incorporated into business practice to the benefit of all employees and the company itself.
The review suggests that until recently, much of the practice in the area of diversity management has been rather piecemeal. Organizations might implement diversity initiatives in one area, such as inclusive hiring practices, but then do not necessarily follow through with that in performance evaluations, training, and even compensation structures. This fragmented approach reduces the effectiveness of diversity initiatives and risks making them seem irrelevant to the main objectives of an organization, the review suggests.
There is perhaps a growing need for a holistic strategy that brings together diversity management and human resource practices. Instead of isolated efforts, diversity must be part of all human resources functions. For instance, a company that hires diversely should ensure that its training programs are tailored to support all employees. Similarly, performance reviews should be designed with inclusiveness in mind, ensuring that no group is disadvantaged by unconscious biases or outdated criteria. There is a need for a top-down commitment across corporations that ensures diversity initiatives receive the resources and attention they ought to have, again for the benefit of all employees and the corporations themselves.
Testa, F., Ceschel, F., Hinna, A. and Palumbo, R. (2024) ‘Does it make sense to manage people ‘diversely’? A scoping review on human resource management practices rooted in diversity’, Int. J. Management Practice, Vol. 17, No. 6, pp.635–668.
The following paper, "Towards a new division of labour in Southeast Asia: Indonesian and Thai Industrial policy and the electric vehicle value chain in ASEAN" (International Journal of Automotive Technology and Management 24(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following paper, "In-house software development for software-defined vehicles: major changes ahead in automotive value chains?" (International Journal of Automotive Technology and Management 24(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Information and Communication Technology describes a new approach to the encryption of digital images. The method could be used to protective sensitive information, such as medical and scientific images, online. By using chaotic systems to do the work, the approach, developed by Zhengbao Cai of the College of Information Technology in Lu’an, China, improves on existing approaches.
Digital image transmission has made encryption essential for safeguarding personal data, medical records, business, political, and military intelligence. However, traditional encryption methods, such as the Advanced Encryption Standard (AES), have limitations when it comes to handling complex and dense data of the kind found in a digital image file. To work around the various problems, Cai turned to a chaotic encryption system. Such an approach uses the irregular and nonlinear dynamics of chaos theory to obscure data. The new work introduces a six-dimensional cellular neural network (CNN) that can encrypt colour more efficiently and with lower demands on computing resources than earlier chaos-based methods.
Conventional two- or three-dimensional CNNs models generate sequences of chaotic numbers that are highly unpredictable. By taking that approach to a higher dimension, Cai improves on the degree of unpredictability as well as making the encrypted output more stable when encrypting large, high-dimensional datasets like high-resolution medical scans or satellite images.
Tests demonstrate that Cai’s encrypted images are much better at resisting attempt to reverse-engineer them to view the original image than conventional encryption methods.
There is a pressing need for secure, efficient, and scalable encryption methods for a wide range of digital image types. The current research with its novel combination of a six-dimensional CNN and the use of a differential evolutionary algorithm could make those sensitive digital images more secure than ever before.
Cai, Z. (2024) ‘Chaotic colour image encryption based on differential evolutionary deep learning’, Int. J. Information and Communication Technology, Vol. 25, No. 7, pp.57–74.
The following paper, "Industrial policy imitation: the perils of matching the US Inflation Reduction Act to attract battery plants" (International Journal of Automotive Technology and Management 24(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Software development is a fast-paced environment where it is easy to get lost in the code and lose sight of the bigger picture. Research in the International Journal of Agile Systems and Management looks at how design, technology, and business might work more effectively together to help in the development of digital platforms, particularly for small and medium-sized manufacturers in Europe.
Diana Chronéer, Mari Runardotter, and Jeaneth Johansson of Luleå University of Technology, Sweden, describe the frameworks, or logics, that represent different ways of thinking. A clearer understanding of these logics can be used to guide different aspects of development in terms of the technology, the service, and the design logic. Each logic has its own priorities, but the researchers suggest that the key to success is ensuring that all three work synergistically. Achieving this synergy is, of course, easier said than done.
The team explains that the technological logic revolves around the working details of software development, the writing of code, the addition of new features, and the squashing of bugs. This logic, the team suggests, is the engine of agile development in this context, driving incremental progress and flexibility and allowing the developers to fine tune a system to meet new demands.
The demands of the design logic are entirely different. It homes in on the user experience (UX) and aims to ensure that platforms are intuitive, accessible, and effective for the people who have to use them. Design logic is user-focused and considers the wants, the needs, and the behaviour of users, which can then determine the look and feel of the platform. However, there is often conflict between the design logic and the rapid cycles of technological development, where deadlines and technical constraints can take priority over a flawless UX.
The third logic, the service-dominant logic, focuses on the business aspects of development its currency is value exchange and in the world of business-to-business (B2B) platforms, this means boosting collaboration, sharing services, and adding mutual value. This logic nudges the developers to think beyond the technology or the UX to see how the platform will improve the company’s bottom line.
Balancing these three logics is thus key to success. A team that focuses too much on the technology might develop a sound platform that is difficult to use. Conversely, an overemphasis on design might result in a platform that looks good but fails to address key business or technical needs.
The researchers propose a new logic, a new framework, “adaptive space” to help manage the three core logics. Adaptive space is a theoretical and practical approach designed to make the ongoing interplay between the three main aspects of development visible and manageable. It maps out the competing priorities of the three logics and emphasises regular reflection and co-creation, so that different perspectives are considered holistically.
The work suggests that a new approach is not simply about improving software, but about rethinking how we build technology in an era of rapid innovation. Software development in this new paradigm would be not purely a technical or design problem, but a sociotechnical process, a blending of human and technical elements working together.
Chronéer, D., Runardotter, M. and Johansson, J. (2024) ‘Logics alignment in agile software design processes’, Int. J. Agile Systems and Management, Vol. 17, No. 6, pp.1–31.
Formula 1 (F1) is the highest level of international motorsport, known for its fast, high-performance, single-seat racing cars. It is governed by the Fédération Internationale de l’Automobile (FIA), and features a series of races, Grands Prix, held on racing circuits worldwide. The races are known for their speed, technical precision, and intense strategy.
A study in the International Journal of Automotive Technology and Management discusses how this global racing series acts as a real-time laboratory that can test and refine motoring technologies that often take a turn into the world of the road vehicles. In other words, Laura Rehberg of the Institute of Entrepreneurship and Innovation Science at the University of Stuttgart, Germany, suggests, F1 is in the driving seat when it comes to shaping the future of the automotive industry.
Rehberg has investigated the world of prototyping within F1 showing how car manufacturers and their suppliers collaborate with one of the most competitive sporting environments. Prototyping refers to the stage in development where experimental versions of components are created and tested. Often, new technologies are pushed to their limits in this environment before they ever go into production. Within F1, prototyping is high-pressure, with the requisite innovation being relentless and having the drive to cut seconds off lap times. Of course, innovation is constrained by the strict FIA regulations, but some important inventions have emerged from F1 innovation, and many of those, such as mild-hybrid vehicles, were actually driven by the regulations themselves.
It is the collaboration between original equipment manufacturers (OEMs), the carmakers, their suppliers, and the F1 teams that at the heart of Rehberg’s work. The research shows that the sport has pulled away from the conventional, arms-length relationships and a change of gear has led to “collaborative prototyping,” where suppliers are not merely vendors but partners, contributing to the design and testing process itself. Such integration allows for more rapid innovation and precludes many of the costly mistakes that can occur later in development when innovation moves on to the production line. Innovations in engine efficiency, vehicle aerodynamics, and materials science are all tested to the extreme in F1 and many developments that have improved times and fuel efficiency on the racing track have act as a catalyst for production cars to hit the roads.
Rehberg, L. (2024) ‘Prototyping in motorsports: exploring manufacturer-supplier collaboration in Formula One‘, Int. J. Automotive Technology and Management, Vol. 24, No. 5, pp.100-118.
Diet plays an important role in health. A study in the International Journal of Business and Systems Research has looked closely at the relationship between nutrition and the prevention of chronic diseases such as diabetes, cardiovascular disease, and cancer. It is worth noting that despite increasing public awareness of the link between poor diet and disease, many people struggle to make healthy choices for themselves.
The researchers, Suvendu Kumar Nayak, Sangram Keshari Swain, of Centurion University of Technology and Management, Mamata Garanayak Kalinga of the Deemed to be University, and Bijay Kumar Paikaray of the Siksha ‘O’ Anusandhan (Deemed to be) University, Odisha, India, point out that tracking food intake and nutritional value and making informed dietary choices can be overwhelming. This then can lead to bad habits that contribute to the risk of chronic illness.
In recognizing this gap between information and application and nutritional awareness, the researchers have proposed a new approach to offering personalized dietary advice that is tailored to individual health profiles and preferences. Their system determines a patient’s nutritional needs in conjunction with their medical history and current health conditions using the K-Nearest Neighbours (K-NN) algorithm. The algorithm, trained on data from a range of people with different conditions and dietary requirements, allows it to find the optimal diet most beneficial to the current patient.
The team explains that by introducing a structured approach to nutrition using their approach, it might be possible to reduce the dietary risk factors associated with many chronic diseases. This could improve health for individuals but also lower the burden on healthcare systems. There is already a growing trend towards personalized healthcare, such as fitness trackers and other health apps, the addition of dietary tools will help guide those individuals who hope to improve their health in these and other ways.
Nayak, S.K., Garanayak, M., Swain, S.K. and Paikaray, B.K. (2024) ‘A prototype for intelligent diet recommendations by considering disease and medical condition of the patient’, Int. J. Business and Systems Research, Vol. 18, No. 6, pp.515–538.
Wearable technology is well known to anyone with a fitness tracker but it is also moving into critical care medicine. Research in the International Journal of Systems, Control and Communications has looked at how wearables might change the management of patients in intensive care units (ICUs). Such devices can provide continuous, real-time data for healthcare professionals following the vital signs and movements of critically ill patients. The technology might offer a more personalized and less invasive approach to treatment.
Decheng Fan of the University of Shanghai for Science and Technology, Junmin Li and Jingjing Fang of The Second Military Medical University, Jianbo Su of Shanghai Jiao Tong University, Shanghai, China, explain that conventional ICU monitoring usually relies on bulky equipment such as heart monitors, devices for monitoring respiratory function, and measuring blood pressure, for instance. These methods, while effective, usually require active and regular intervention from the healthcare workers. There is also usually a need for taking samples of blood and urine etc, which is usually invasive and carries a risk of introducing infection.
Wearable technology could offer a viable alternative to the more intrusive and invasive technologies that have been used for many years. One of the biggest benefits is the non-invasive and continuous monitoring that wearables could offer. Wearables will support healthcare by transmitting personalized data to clinicians, allowing them to make decisions in real time to assist patients with complex, life-threatening conditions such as multi-organ failure.
Researchers are already working on multifunctional sensors that could be integrated into a single device to streamline the whole process of data assimilation and transmission. Such devices could be of great benefit in specialist care settings where resources are scarce, such as during a pandemic, for instance.
Fan, D., Li, J., Su, J. and Fang, J. (2024) ‘Wearable sensors in critical care medicine’, Int. J. Systems, Control and Communications, Vol. 15, No. 3, pp.312–324.
There is seemingly no endeavour untouched by the potential of algorithms and artificial intelligence. Writing in the International Journal of Communication Networks and Distributed Systems, a Czech team discusses the potential for chatbots to carry out initial job interviews with candidates.
A chatbot-mediated screening process could allow wholly unsuitable candidates to be quickly removed from the short list so that interviewers can focus on those applicants best suited to the role being sought. Such a change in the way recruitment is undertaken raises ethical issues about just how fair is screening job applicants in this way, especially given many of the known problems surrounding algorithm training bias and other issues that have been raised about artificial intelligence carrying out human jobs.
Insights from the research could help guide exactly how companies approach recruitment in the wake of these intriguing technological developments. There are three important aspects that Helena Řepová, Jan Zouhar, and Pavel Král of Prague University of Economics and Business consider in their paper: procedural justice, in other words, fairness in decision-making, interactional justice, fairness in how candidates are treated, and interpersonal justice, the quality of personal interaction.
The researchers compared applicant perceptions of these forms of justice across different interview formats, including interviews conducted by humans, chatbots, and those where the interview type wasn’t revealed.
Chatbots offer a clear efficiency advantage to companies in screening applicants. But, for applicants accustomed to conventional interviews, issues of fairness, or a lack thereof, are apparent. Indeed, an applicant’s perception of justice in recruitment might alter their opinion of the organization itself and deter bright and well-suited applicants from applying for a position with a given company in the first place based on that company using chatbots for initial interviews. Companies could miss out on talent and the talented candidates could miss out on their dream role!
Řepová, H., Zouhar, J. and Král, P. (2024) ‘Attractiveness of firms with chatbot as job interviewers: does the interviewer-type matter in the first contact with candidates?’, Int. J. Communication Networks and Distributed Systems, Vol. 30, No. 6, pp.711–732.
A powerful algorithm that can automatically classify different singing voices by vocal characteristics is described in the International Journal of Bio-Inspired Computation. Balachandra Kumaraswamy of the B.M.S. College of Engineering in Bangalore, India, suggests that the development is an important step forward in music technology, allowing a system to quickly and accurately distinguish one voice from another without human intervention.
Everyone’s singing voice is shaped by a range of physiological characteristics such as their vocal folds, lung capacity and diaphragm, the shape of their nose and mouth, the tongue and teeth, and more. Add to that the emotional delivery and stylistic choices a singer might make, and each of us sounds unique. It is fairly easy for us to tell singers apart, even if the singing is within a complex and textured musical environment. However, using machine learning to distinguish voices has remained challenging. Kumaraswamy’s system performs well and could be employed in a wide range of contexts such as music cataloguing, streaming, recommendation, music production, and even for legal purposes such as copyright control.
The new approach takes four steps to distinguish between singers. The first is pre-processing in which an advanced convolutional neural network (CNN) identifies and isolates the vocals from a complex audio recording, discarding instrumentation and other non-vocal sounds.
The second step is feature extraction whereby key characteristics of the voice are obtained from the audio track and various metrics, such as the zero crossing rate (ZCR), which measures the frequency of signal changes, capture the characteristics of the singer’s voice.
The third step involves an algorithm identifying the vibration patterns of the notes being sung and so can create a profile distribution of the harmonics to map the timbre, or texture, of the voice.
The final step used yet more neural networking in the form of bidirectional gated recurrent units (BI-GRU) and long short-term memory (LSTM) networks to analyse the vocal data. These two models can process sequences and so reveal the flow of a singer’s performance over time. This last step is key to the success of Kumaraswamy’s approach.
At this point in the development of the system, the neural networks used require extensive computational resources and large datasets for training. For now, this might limit scalability. However, such issues can be addressed with optimisation of the way the algorithms are applied and the training data used.
Kumaraswamy, B. (2024) ‘Improved harmonic spectral envelope extraction for singer classification with hybridised model’, Int. J. Bio-Inspired Computation, Vol. 24, No. 3, pp.150–163.
The sale of refurbished products, refurbs, represents a delicate balancing act for companies attempting to retain a share of their market and to incorporate recycling strategies into their approach. A study in the European Journal of Industrial Engineering discusses this balancing act in the context of new and refurbished sales, where consumers weigh affordability against quality.
According to Yeu-Shiang Huang of National Cheng Kung University, Taiwan, Chih-Chiang of Zhaoqing University, China, and Yi-Hsiang Tsao of the National Cheng Kung University, Taiwan, businesses must decide how to stay competitive while addressing environmental concerns. The team has used game theory to model the kinds of decisions that retailers must make and offers them tips on that balancing act.
Selling refurbished as opposed to brand-new products, especially electronic gadgets and devices, represents a classic dilemma in economics. Refurbished products are usually sold at lower cost and so offer less profit for the retailer, but they might be more attractive to the consumer because they have eco-friendly credentials. Refurbs can thus undercut the sales of brand-new items. As such, manufacturers themselves remain hesitant in their adoption of remanufacturing, despite its environmental benefits. But, for retailers, offering refurbished goods can lead to a new class of sale.
The researchers have modelled the strategic interactions between manufacturers and retailers to look at how manufacturers set the official price for the wholesale cost of their new products, while retailers respond by adding refurbs to the mix and setting the best price for those and for the brand-new products they sell.
The research emphasises that it is the environmental rather than the economic that is at stake. Strict recycling laws mean that there is a drive towards refurbishment and recycling that the retailers can be happy with, but the original manufacturers may well not be. Indeed, if retailers can take control of recycling and remanufacturing and connect directly with the end consumers of refurbs, the manufacturers’ share might shrink at least until the refurbished products have become wholly obsolete and can only be recycled for components and materials and a new product must enter the market. Retailers by working to their own economic strategy might thus play a critical role in driving sustainable practices.
Huang, Y-S., Fang, C-C. and Tsao, Y-H. (2024) ‘A study on pricing and recycling strategies for retailers with consideration of selling new and refurbished products’, European J. Industrial Engineering, Vol. 18, No. 6, pp.791–816.
A comprehensive literature review in the International Journal of Process Management and Benchmarking sheds light on research into the notion of toxic leadership and how this increasingly pervasive issue affects the workplace and can damage organisations.
Emily Maria K. Jose and Bijay Prasad Kushwaha of the Vellore Institute of Technology, India, used a systematic approach to extract relevant research articles from a scholarly database. Their analysis of these papers revealed five principal characteristics of toxic leadership: authoritarian leadership, abusive supervision, narcissism, unpredictability, and maladjustment. Their findings highlight the nature of toxic leadership but also point to how it can affect employee engagement, performance, and retention.
Toxic leadership is defined as management behaviour that is ultimately harmful to both employees and the company for which they work. Toxic leaders are commonly indifferent to employee well-being and prioritize self-interest. The result is the creation of a working environment filled with fear and instability. The current review suggests that common toxic behaviour affects individual employees but also propagates through the corporate culture and so can affect an organisation deeply.
Jose and Kushwaha found that toxic leadership leads to high employee turnover rates. Indeed, almost three quarters of employees faced with toxic leadership will contemplate leaving their jobs. High staff turnover leads to a loss of team cohesion and other negative effects that will eventually have financial repercussions for the company if not remedied. Research suggests that toxic leadership can lead to almost a third of business failures each year.
The study discusses psychological safety and employee engagement, both of which can be affected negatively by toxic leadership. In a toxic work environment, employees become disenfranchised, which leads to a fall in their productivity and a deterioration of their work-life balance. A vicious cycle of dissatisfaction then feeds the toxic culture still further. There is thus a critical need for organisations to recognize and address this potentially destructive problem more proactively now than ever before. Effective coaching, constructive feedback, and monitoring should be key to mitigating the risks associated with toxic leadership behaviour, the research suggests.
Jose, E.M.K. and Kushwaha, B.P. (2024) ‘The dark side of organisation identification: systematic literature review and bibliometric analysis on toxic leadership on employee’s behaviour’, Int. J. Process Management and Benchmarking, Vol. 18, No. 2, pp.240–265.
Can companies do well by doing good? Research in the International Journal of Productivity and Quality Management that has looked at companies listed on the Tehran Stock Exchange (TSE) provides a positive answer to that question. The researchers found that there is a strong link between corporate social responsibility (CSR) and financial performance. They also suggest that risk management is an important mediator of this effect.
Nasrin Dadashi and Seyyed Saeb of the Islamic Azad University, Rasht, Iran, and Ali Mayeli of Stony Brook University, New York, USA, explain that CSR is a rather broad term that covers a company’s ethical conduct and its contributions to society. It spans three areas: economic, social, and environmental. CSR is, they suggest, no longer about box-ticking, green-washing, or rubber-stamping, and goes hand-in-hand with a company’s financial health as well reflecting investor confidence. The team demonstrated that those companies that embraced CSR saw significant improvements.
This, they emphasise, is only half the story. Risk management, specifically Enterprise Risk Management (ERM), also emerged from the work as a key factor in the overall equation. ERM involves identifying, assessing, and mitigating potential threats to a company’s objectives, is nothing new, yet the study shows it to play an important part not only in enhancing CSR, but also in boosting the positive impact CSR has on financial performance. CSR is no longer merely a moral imperative. CSR is a strategic imperative.
The team suggests that the integration of CSR and ERM into a company’s core strategies will not only build trust and reduce the information gap between the company and its stakeholders, but also position it better for long-term success financially speaking. From the investor perspective, these findings also carry significant weight. When money is so often the only matter arising on an investor’s agenda, they could do well to consider an investment’s CSR and ERM, as they emerge as good indicators of future performance.
Dadashi, N., Mousavi, S.S. and Mayeli, A. (2024) ‘The effect of social responsibility on financial performance with emphasis on the moderating role of risk management’, Int. J. Productivity and Quality Management, Vol. 43, No. 1, pp.26–45.
Social media is now rooted in the terrain of our daily lives. Research in the International Journal of Mobile Communications has looked at whether the psychological toll of our constant use of these tools and our comparing ourselves to others online is doing more harm than good. With the advent of always-on, ubiquitous messaging apps, we catch sight of more and more people participating in and enjoying the things we imagine we ourselves should be doing.
The notion of FOMO – fear of missing out – is always at the back of our minds even when other notions, detachment, acceptance, and mindfulness, are high on the mental health agenda. The researchers have studied the well known Chinese app WeChat and looked at the impact of social comparison and observed how it can go beyond merely influencing our thoughts and emotions but might shape online behaviour in unpredictable and putatively troubling ways.
Bao Dai of Hefei University of Technology, Anhui, and Lingling Yu and Ying of Shanghai University, Shanghai, China, explain that users of WeChat and similar apps often share highly curated, glossy snapshots of their lives. This leads others with perhaps less glamorous opportunities to experience envy and mental fatigue. Envy, in this context, refers to the unpleasant feeling that arises when individuals believe others are more successful, attractive, or happier than themselves. Fatigue, on the other hand, is the mental exhaustion that stems from constantly being bombarded with these idealized portrayals of life. Both emotions can act as catalysts, transforming the stress of comparison into tangible behavioural changes.
The team found that envy is much more detrimental than fatigue. Feeling like one is falling short can trigger a much stronger behavioural change that is not necessarily positive. They add that many users, overwhelmed by these emotions, choose to disengage. This disengagement takes two forms: discontinuance and information avoidance. Discontinuance is a full or partial withdrawal from the social media platform, where users cut back on their usage or quit entirely to avoid further emotional strain. Information avoidance, a more subtle but no less troubling response, occurs when users selectively filter out certain content and so avoid updates or posts that could reignite feelings of envy or inadequacy.
The research highlights the often hidden emotional price of staying connected in the digital age. While social media is lauded for its ability to foster communication and self-expression, it can also nurture environments where users feel more isolated or inferior. There is perhaps an urgent need for more research and for users and platform providers to address the darker side of digital connectivity.
Dai, B., Yu, L. and Chen, Y. (2024) ‘Exploring users’ behavioural responses to social comparison on social media: the mediating roles of envy and fatigue’, Int. J. Mobile Communications, Vol. 24, No. 3, pp.330–354.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
The following paper, "In-depth analysis of coal chemical structural properties response to flue gas saturation: perspective on long-term CO2 sequestration" (International Journal of Oil, Gas and Coal Technology 36(5) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research in the International Journal of Computational Science and Engineering describes a new approach to spotting messages hidden in digital images. The work contributes to the field of steganalysis, which plays a key role in cybersecurity and digital forensics.
Steganography involves embedding data within a common media, such as words hidden among the bits and bytes of a digital image. The image looks no different when displayed on a screen, but someone who knows there is a hidden message can extract or display the message. Given the vast numbers of digital images that now exist, and that number grows at a remarkable rate every day, it is difficult to see how such hidden information might be found by a third party, such as law enforcement. Indeed, in a sense it is security by obscurity, but it is a powerful technique nevertheless. There are legitimate uses of steganography, of course, but there are perhaps more nefarious uses and so effective detection is important for law enforcement and security.
Ankita Gupta, Rita Chhikara, and Prabha Sharma of The NorthCap University in Gurugram, India, have introduced a new approach that improves detection accuracy while addressing the computational challenges associated with processing the requisite large amounts of data.
Steganalysis involves identifying whether an image contains hidden data. Usually, the spatial rich model (SRM) is employed to detect those hidden messages. It analyses the image to identify tiny changes in the fingerprint that would be present due to the addition of hidden data. However, SRM is complex, has a large number of features, and can overwhelm detection algorithms, leading to reduced effectiveness. This issue is often referred to as the “curse of dimensionality.”
The team has turned to a hybrid optimisation algorithm called DEHHPSO, which combines three algorithms: the Harris Hawks Optimiser (HHO), Particle Swarm Optimisation (PSO), and Differential Evolution (DE). Each of these algorithms was inspired by natural processes. For example, the HHO algorithm simulates the hunting behaviour of Harris Hawks and balances exploration of the environment with targeting optimal solutions. The team explains that by combining HHO, PSO, and DE, they can work through complex feature sets much more quickly than is possible with a current single algorithm, however sophisticated.
The hybrid approach reduces computational demand by eliminating more than 94% of the features that would otherwise have to be processed. The stripped back information can then be processed with a support vector machine (SVM) classifier. The team says this method works better than meta-heuristic (essentially trial-and-error methods) and better even than several deep learning methods, which are usually used to solve more complex problems than steganalysis.
Gupta, A., Chhikara, R. and Sharma, P. (2024) ‘An improved continuous and discrete Harris Hawks optimiser applied to feature selection for image steganalysis’, Int. J. Computational Science and Engineering, Vol. 27, No. 5, pp.515–535.
Cloud computing has become an important part of information technology ventures. It offers a flexible and cost-effective alternative to conventional desktop and local computer infrastructures for storage, processing, and other activities. The biggest advantage to startup companies is that while conventional systems require significant upfront investment in hardware and software, cloud computing gives them the power and capacity on a “pay-as-you-go” basis. This model not only reduces initial capital expenditures at a time when a company may need to invest elsewhere but also allows businesses to scale their resources based on demand without extensive, repeated, and costly physical upgrades.
A study in the International Journal of Business Information Systems has highlighted the role of fuzzy logic in evaluating the cost benefits of migrating to cloud computing. Fuzzy logic, a method for dealing with uncertainty and imprecision, offers a more flexible approach compared to traditional binary logic. Fuzzy logic recognises the shades of grey inherent in most business decisions rather than seeing things in black and white.
The team, Aveek Basu and Sraboni Dutta of the Birla Institute of Technology in Jharkhand, and Sanchita Ghosh of the Salt Lake City Electronics Complex, Kolkata, India, explains that conventional cost-benefit analyses often fall short when assessing cloud migration due to the inherent unpredictability in factors such as data duplication, workload fluctuations, and capital expenditures. Fuzzy logic, on the other hand, addresses these challenges by allowing decisions to be made that take into account the uncertainties of the real world.
The team applied fuzzy logic to evaluate three factors associated with the adoption of cloud computing platforms. First, the probability of data duplication, secondly capital expenditure, and finally workload variation. By incorporating these different factors into the analysis, the team obtained a comprehensive view of the potential benefits and drawbacks of cloud computing from the perspective of a startup company. The approach offers a more adaptable assessment than traditional models.
One of the key findings is that cloud computing leads to a huge reduction in the complexity and costs associated with managing business software and the requisite hardware as well as the endless upgrades and IT support often needed. Cloud service providers manage all of that on behalf of their clients, allowing the business to focus instead on its primary operations rather than IT.
Basu, A., Ghosh, S. and Dutta, S. (2024) ‘Analysing the cloud efficacy by fuzzy logic’, Int. J. Business Information Systems, Vol. 46, No. 4, pp.460–490.
