The following paper, "The application of big data analysis in logistics supply chain optimisation" (International Journal of Information and Communication Technology 25(9) 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, "Prediction of talent demand and job matching based on knowledge graph and attention mechanisms" (International Journal of Information and Communication Technology 25(9) 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, "Single-stage landmark retrieval with texture feature fusion" (International Journal of Information and Communication Technology 25(9) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Influencer marketing has recently become a main component in modern advertising. It has reshaped how brands connect with consumers via well-known and respected social media users with a large reach across the digital domain. Research in the International Journal of Technology Marketing has looked at the psychological and behavioural mechanisms that underlie the influencer phenomenon and what leads members of the public to follow the advice and recommendations of these people.
The study reveals new insights into the drivers and the resulting purchasing decisions individual make. The work has implications not only for marketers but also for how we understand the evolving dynamics of trust, validation, and commerce in the digital age.
Dominyka Venciute, Agne Kudzmanaite, and Marius Kuslys of the ISM University of Management and Economics in Vilnius, Lithuania, and Ricardo Fontes Correia of the Polytechnic Institute of Bragança, Campus de Santa Apolónia in Bragança, Portugal, explain how consumer engagement is central to the work. The online actions of “liking”, “commenting”, and “sharing” influencer content can ultimately change an individual’s buying behaviour and even of their friends and contacts.
The research shows that consumers who actively engage with influencers are more likely to buy the products those influencers promote, a perhaps inevitable conclusion. However, this finding does align with well-known and broader advertising principles: meaningful engagement fosters a sense of connection and receptivity, for instance. There is a distinction though. One of the features of social media platforms is that perceived value, the consumer’s assessment of the quality, relevance, and usefulness of an influencer’s content, is the strongest driver of their intention to buy, rather than the nature of the brand or other factors.
Moreover, it seems that while the general propensity to trust is important, it does not significantly influence purchasing intent in this context. It seems that on social media, where influencer content is often performative and curated, trust is not sufficient to trigger someone to spend. Rather, it is the relatable aspects of the influencer’s content, such as their sharing of detailed product reviews, unboxing, and demonstrations of the product in use, that are the most persuasive aspects of the influencer to consumer relationship.
Venciute, D., Correia, R.F., Kudzmanaite, A. and Kuslys, M. (2025) ‘The effect of self-confidence in the relationship between influencer marketing and willingness to buy’, Int. J. Technology Marketing, Vol. 19, No. 1, pp.105–130.
The following paper, "Stereo vision and deep learning-based movement correction for sports dance" (International Journal of Information and Communication Technology 25(9) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A new approach to landmark retrieval, an area of computer vision that identifies and matches landmark images within a database, is discussed in the International Journal of Information and Communication Technology. The new approach taken by Kun Tong and GuoXin Tan of the National Research Center of Cultural Industries at Central China Normal University in Wuhan, improves accuracy and efficiency of image retrieval systems and could help developers navigate advances in computer vision applications such as object recognition, augmented reality, and autonomous vehicle control.
Landmark retrieval models usually rely on feature descriptors to analyse and compare images. These descriptors come in two forms: global and local. Global descriptors capture the overall structure and abstract qualities of an image, while local descriptors home in on fine details such as textures and spatial arrangements. This combination offers complementary information about the image being analysed. However, there is a lot of redundancy, which dilutes critical information, leading to inefficient processing. Moreover, the reality of captured images means differences in viewing angle, lighting conditions, and the presence of obstructions, all lead to inaccuracies.
The new model uses a texture enhancement module to emphasize the important textural features even in complex scenes. The module reconstructs feature maps to amplify surface-level patterns, ensuring that even subtle or distorted textures are highlighted. This can overcome problems that arise because of viewing angle or poor lighting. The model also uses a feature fusion module that integrates the global and local descriptors to eliminate redundancies in the data. By prioritizing relevant details and discarding superfluous information, the model streamlines the analysis to improve computational efficiency.
Tong and Tan have carried out extensive tests on benchmark datasets, including the Revisited Oxford and Paris datasets, and show their approach to be very effective and efficient at identifying landmarks.
Tong, K. and Tan, G. (2024) ‘Single-stage landmark retrieval with texture feature fusion’, Int. J. Information and Communication Technology, Vol. 25, No. 9, pp.43–59.
The following paper, "Research on end-to-end computing power network architecture based on SDN and MIH technology" (International Journal of Computational Systems Engineering 8(7) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As tourism to nature-based destinations such as the Thai island of Phuket continues to grow, there are worsening consequences for the environment and local ecosystems. While such destinations rely heavily on their natural environments to draw visitors, more and more tourism is taking its toll. There is inevitably increased habitat destruction, pollution, and loss of biodiversity. The concept of environmental stewardship has emerged to address such issues.
Research in the International Journal of Tourism Policy has examined this notion of environmental stewardship. The idea is to integrate sustainable practices into tourism, such as conservation efforts, waste reduction, and to promote sustainable consumption in nature-focused tourist destinations. By striking a balance between maintaining the appeal of natural destinations and ensuring that those destinations remain ecologically healthy, it might be possible to reach a sustainable equilibrium in which tourism and environmentalism are in balance. The study by Kevin Fuchs of the Faculty of Hospitality and Tourism at Prince of Songkla University in Phuket, Thailand, has looked at how female Western travellers visiting Phuket perceive and engage with this concept.
According to Fuchs work, there is awareness of environmental issues among such tourists. Many recognize the importance of preserving nature for future generations, yet there remains a notable gap between awareness and action. Tourists frequently express a desire to adopt sustainable practices, but struggle to put those intentions into practice. Factors such as inconvenience, a lack of viable sustainable options, and insufficient knowledge about how to make responsible choices contribute to this problem, the research suggests.
This kind of disconnection between attitude and action, a green gap, we might call it, is not unique to Phuket. It represents a broader issue in sustainable tourism. The work thus highlights the need for more targeted interventions to encourage a change in tourist behaviour. For example, tourists could benefit from more accessible eco-friendly options, clearer communication about how their actions impact the environment, and better education on practical ways to minimize their footprint.
Fuchs, K. (2024) ‘An exploratory study with western female tourists about perceived drivers and challenges towards environmental stewardship in a nature-based destination’, Int. J. Tourism Policy, Vol. 14, No. 6, pp.595–608.
The following paper, "University to MSMEs knowledge transfer in Indonesia" (International Journal of Economic Policy in Emerging Economies 20(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, "Constructing maritime incoterms quotation judgment criteria in the post-epidemic era" (International Journal of Shipping and Transport Logistics 19(2/3) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A new model developed to predict mental resilience in college students could have significant implications for how universities address the growing mental health challenges facing this demographic.
The research, published in the International Journal of Information and Communication Technology, used statistical methods to investigate how students cope with stress and adversity. Fulian Liu of the Mental Health Education Center for College Students at Wuxi Institute of Technology in Wuxi, China, suggests that the study could help educational establishments identify those at risk of mental health struggles and by anticipating challenges, offer appropriate interventions to preclude severe psychological distress in the most vulnerable.
Mental resilience, or toughness, might be defined as one’s ability to cope with stress and setbacks. It is closely related to psychological resilience and well-being. College students, often navigating a complex mix of academic pressures, social challenges, and personal transitions, can be particularly vulnerable to mental health problems. This, in turn, can have a detrimental impact on their academic performance and their quality of life during their studies and afterwards. An understanding and of mental toughness and the ability to foresee problems arising before they become serious could be an important part of supporting students.
Current models for tracking and studying mental health have limitations. They often struggle with what is referred to as “overfitting” wherein the model performs well on training data but fails to work well with novel information. Additionally, irrelevant or redundant variables can cloud or colour the predictive process, reducing the reliability of the model. The new work tackles these problems and uses an optimized version of Elastic Network Regression (ENR) to balance multiple predictive factors statistically speaking. This approach uses a Bayesian optimization algorithm (BOENR) to fine tune the parameters within the model based on prior knowledge and is able to improve accuracy by avoiding the overfitting problem.
The new model has a much lower prediction error than other models, offering an accuracy rate of above 94 percent and outperforming five commonly used models in terms of predictive reliability.
Liu, F. (2024) ‘Mental toughness prediction model of college students based on optimal elastic network regression‘, Int. J. Information and Communication Technology, Vol. 25, No. 10, pp.19-33.
Parking congestion at universities, particularly engineering colleges, is becoming a growing concern as student populations steadily rise while parking capacity remains the same. In many urban environments, including university campuses, drivers routinely face the frustration of searching for an available parking space, often leading to wasted time and increased stress. A study in the International Journal of Services and Operations Management has looked at how the parking issue might be addressed.
Rabih Monzer Firaoui, Jehad Basem Abu Shamleh, Bilal Marzouki, and Ibrahim Emad Elabed of the University of Sharjah, United Arab Emirates, Sharfuddin Ahmed Khan of the University of Regina, Canada, and Shahriar Tanvir Alam of the Military Institute of Science and Technology in Dhaka, Bangladesh, focused on a particular university’s engineering college where a significant increase in student enrolment over the past five years has meant its parking capacity has become overwhelmed. There is always congestion, especially during peak hours, and the researchers have turned to simulation techniques to see whether they could find a solution.
The researchers used a discrete-event simulation, which models real-world operations, to uncover the parking patterns at the campus. The approach can easily simulate such a complex system and identify inefficiencies. The team compared their simulation with real-world data and confirmed that it offered a reliable representation of the parking problem at the college. By incorporating real traffic and parking data from the campus, the team discovered that parking levels were typically at 70 percent capacity. However, the demand for parking spaces surged during peak hours, specifically between 08:00 and 09:30 because of the way lectures are scheduled. So even though there may well be enough parking spaces, congestion means that they are not filled efficiently. The obvious solution then is not to create more parking spaces but to adjust the college timetable to allow students, lecturers, and others to use the available spaces in a more efficient manner.
Parking congestion is, of course, a far more widespread issue, and the economic and psychological costs associated with it are enormous. Research indicates that drivers in crowded public parking areas can lose hours each year searching for parking spaces, leading to increased stress and lost productivity. Studies that can find solutions to this problem could feed into intelligent transport systems that incorporate sensors and real-time data analytics to optimize parking and improve traffic flow on campus and off.
Firaoui, R.M., Khan, S.A., Alam, S.T., Shamleh, J.B.A., Marzouki, B. and Elabed, I.E. (2024) ‘A simulation-based study to evaluate and improve university parking space’, Int. J. Services and Operations Management, Vol. 49, No. 3, pp.265–288.
The international music industry is a multibillion-dollar enterprise that makes a few people a lot of money and lots of people very little. The companies seem to hold all the cards, taking the larger percentage of any profit that might be made. Independent songwriters and artists always struggled to reach the point where they might be compensated well for their work. Even the advent of streaming and download sites has not changed that much for the less well-known, where even a large number of “plays” on a streaming service might generate only a few dollars.
One issue is the perhaps deliberately outdated and convoluted systems that manage music royalties. The system is outmoded and leads to delays, errors, and even financial losses for many. A new system described in the International Journal of Student Project Reporting might address some of the issues. Yichen Jiang and Stephanos Matsumoto of Olin College of Engineering, in Needham, Massachusetts, USA, and Thitipong Bisch of the University of Zurich, Switzerland, describe the Trustworthy and Auditable Royalty Processor (TARP), which uses blockchain technology.
Blockchain is a secure, decentralized ledger system that was initially developed to underpin what we call digital, or “crypto”, currencies. Recently, however, the potential for other applications beyond money have been developed using blockchain technology. The TARP innovation could use blockchain to streamline the royalty payment process, ensuring that artists are paid faster and with fewer errors. By integrating blockchain with smart contracts, TARP provides a transparent, tamper-proof record of transactions that all parties can trace and audit, the team suggests. Such transparency is important in an industry prone to errors and even exploitation. The system could also preclude issues arising from inaccurate music file metadata, complicated international copyright laws, and the existence of multiple intermediaries.
The architecture of TARP is partly centralised so that one server performs verification tasks, but the royalty transactions themselves are handled using a blockchain. This “hybrid” approach ensures that while the verification process remains efficient, the core transactions are secure and auditable. The use of blockchain could reduce discrepancies and fraud, some of the most persistent and pressing issues in royalty distribution. Moreover, the system encourages the digitisation of music metadata so that tracking and managing rights could become much simpler, allowing timely compensation for music sales and streams for artists, publishers, and other rights holders.
Jiang, Y., Matsumoto, S. and Bischof, T. (2024) ‘Towards a blockchain-based music royalty system’, Int. J. 2, No. 2, pp.174–201.
A study of the bridges linking Micro, Small, and Medium Enterprises (MSMEs) and universities in Indonesia suggests that knowledge transfer plays an important part in strengthening the competitiveness of such companies. In an economy shaped by digital disruption and economic uncertainty, the research, published in the International Journal of Economic Policy in Emerging Economies, shows that universities can help MSMEs adapt and thrive.
Lina Anatan of the Maranatha Christian University Bandung in Indonesia, surveyed more than 200 MSMEs in Indonesia and discovered that there is great demand for university collaborations. In particular, collaborations that advance digitalisation are high on the agenda. MSMEs in Indonesia contribute almost two-thirds of the gross national product and employ almost 97% of the domestic workforce. As such, their digital development is important for the growth of those companies as well as economic growth at the national level. However, despite these findings, it seems that many MSMEs struggle with adopting digital tools and refining their business strategies.
The research shows that the biggest incentive among MSMEs seeking university partnerships is the perhaps obvious need to boost their market share and profitability. Such companies often face barriers, such as a lack of access to investment capital, and this makes it harder for them to buy into new technology or invest in the research they might need to undertake to develop and expand. Universities can play a transformative role by providing invaluable knowledge, resources, and expertise. One must assume that there would be financial and intellectual rewards for academia, as well as the potential for their students and educators to be involved or even employed by the companies they assist.
The research suggests that there remain obstacles and that government intervention might assist through grants or community programmes. This will be increasingly important as Indonesia’s economy continues to develop, the strength of its MSMEs and their ability to adapt to digital disruption will depend on knowledge transfer and technological innovation.
Anatan, L. (2024) ‘University to MSMEs knowledge transfer in Indonesia’, Int. J. Economic Policy in Emerging Economies, Vol. 20, No. 5, pp.1–23.
Social media platforms are an important part of any online marketing campaign, but companies attempting to entice us with their wares face the constant challenge of how to design effective display advertisements that keep our attention when many people ignore or actively avoid such efforts.
Given that display advertisements represent almost half of the global advertising market, it is obvious that much of the money spent is by users that do not engage with them. Research in the International Journal of Electronic Marketing and Retailing has looked at the factors that contribute towards advertisement avoidance and how advertisers might address this problem more effectively.
Priscilla Teika Odoom of the Ghana Institute of Journalism and Raphael Odoom and Stephen Mahama Braimah of the University of Ghana Business School in Accra, Ghana have built upon a psychological model known as the stimulus-organism-response. This frames how we behave when confronted with external stimuli, such as online advertisements. It has long been known that user reactions to advertising can vary greatly, but this new research looks specifically at two key features of display advertisements: personalization and exposure conditions.
The researchers explain that personalization refers to the tailoring of advertisements based on an individual’s past behaviour, such as browsing history or previous interactions with the advertiser or its associates. Exposure condition refers to whether a user has control over when and how they view advertisements, or if the advertisements are imposed upon them, as is often the case with pop-up advertisements, for instance.
The researchers found that advertisements that are both personalized and shown in a way that allows the user to control the viewing experience are far less likely to be avoided as one might expect. However, the overall effect can be tempered by the user’s personality. For instance, extrovert consumers are, the team found, more likely to engage with well-personalized advertisements. Whereas those with higher levels of neuroticism tended to less responsive to advertisements, regardless of whether the ads were personalized or not. This difference complicates the task of creating a universal advertising strategy, because the advertisers will not tend to know the specific personality traits of their target audience.
Moreover, the team found that other psychological factors, such as scepticism and trust, can affect advertisement avoidance. Consumers who are sceptical of online advertising are more likely to avoid advertisements, especially if they feel the advertisements are not relevant or trustworthy. Conversely, users with a more favourable attitude toward online advertisements tend to engage more positively with them.
However, regardless of the psychological factors, advertisements that are novel or creative were found to be more likely to capture a user’s attention and reduce avoidance. If advertisers can identify personality traits among their prospects and at the same time develop new and creative campaigns that target users appropriately they are, the work suggests, more likely to succeed in their marketing efforts.
Odoom, P.T., Odoom, R. and Braimah, S.M. (2025) ‘Minimising display advertising avoidance on social media platforms – the role of exposure condition, personalisation, and personality traits’, Int. J. Electronic Marketing and Retailing, Vol. 16, No. 1, pp.104–132.
The following paper, "Enhancing power skiving tool longevity: the synergy of AI and robotics in manufacturing automation" (International Journal of Mechatronics and Manufacturing Systems 17(2) 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 Shipping and Transport Logistics has examined how strategic alliances can boost the operational efficiency of container shipping and transport companies. Mpuon Joseph Akam, Eze Felix John, Odigbo Benedict Ejikeme, Joseph A. Anyadighibe, Eyo Itam Eyo, Enuoh Rebecca Oliver, and Samuel Etim Ndem of the University of Calabar, Nigeria, surveyed more than 505 management employees across more than companies in Nigeria and found that partnerships between shipping firms were able to transform logistics performance to the benefit of the businesses and their customers.
Strategic alliances are collaborative arrangements where firms work together toward shared goals while retaining their independence. These partnerships are increasingly seen as essential in the global shipping industry, which faces multiple complex logistics challenges. The new empirical work fills a gap in our knowledge of how such collaborations directly impact the day-to-day operations of shipping companies. The team found that alliances allowed companies to pool resources, spread risk, and build on each other’s expertise to enhance service delivery and streamline operations.
The study identified two types of alliance: collaborative and cooperative. In a collaborative alliance, the focus is on flexibility and adaptability, whereas in a cooperative alliance, the partners prioritize building trust and commitment. Both approaches can work well to improve the overall efficiency of operations by reducing internal conflicts and fostering an environment where all parties benefit.
Logistics processes such as container loading, unloading, and transportation scheduling are among the areas that can benefit the most from strategic partnerships. Improved collaboration leads to more reliable deliveries, better vessel scheduling, and fewer delays due to port congestion. Such improvements then translate into more reliable and cost-effective services for customers.
Akam, M.J., John, E.F., Ejikeme, O.B., Anyadighibe, J.A., Eyo, E.I., Oliver, E.R. and Ndem, S.E. (2024) ‘The role of strategic alliances in logistics performance of container shipping and transport firms’, Int. J. Shipping and Transport Logistics, Vol. 19, Nos. 2/3, pp.353–390.
The emotional and cognitive response to the artworks of Raja Ravi Varma, one of India’s most celebrated 19th-century painters, is discussed in the International Journal of Arts and Technology. Varma was known for blending European academic realism with traditional Indian themes, and so his paintings achieved a long-held significance not only for their aesthetics but also for their ability to resonate with a broad cross-cultural audience. Indeed, while Varma’s paintings are often iconic in their depiction of Hindu deities and their representation of mythological narratives, many have been mass-produced and become accessible to the public as well as art collectors.
Dyutiman Mukhopadhyay and Sangeetha Menon of the National Institute of Advanced Studies in Bengaluru, Sohhom Bandyopadhyay of the Indian Institute of Technology Gandhinagar in Gujarat, and Eshwar Venkatesh of the Manipal Academy of Higher Education in Manipal (Bengaluru Campus), India, have looked at the aesthetics of Varma’s paintings using both Western and Indian theories of art to probe the emotional and perceptual responses of viewers.
The team used eye-tracking and saliency analysis to map how a viewer’s gaze moves across Varma’s paintings, and then link those eye movement patterns to the viewer’s emotional reactions. In the context of Indian aesthetics, the work considers Rasa theory which defines various emotional sentiments provoked by art such as joy and love, sorrow and anger, and wonder. Rasa theory suggests that one’s emotional experience of art is not a simple, passive reception of visual information, but a dynamic, active engagement shaped by personal and cultural contexts. In many ways, this contrasts with the conventional Western approach to empirical aesthetics, which might seem simplistic in some ways, although there is always scope for a wider perspective within any culture.
The team suggests that their findings show that there is an intricate interplay between cognitive, emotional, and perceptual factors and how a viewer experiences a given piece of art. Indeed, an individual’s emotional response is influenced by their own creativity and their prior exposure to art. Art appreciation is always subjective. In the context of this research, the team has found that one’s experience plays a vital role in defining the aesthetic experience. This has implications for art appreciation, scholarship, and perhaps even how we display art and how the public engages with it.
Mukhopadhyay, D., Bandyopadhyay, S., Venkatesh, E. and Menon, S. (2024) ‘Exploring complexity-entropy, eye-tracking, experience, creativity, familiarity, and emotional responses to 40 paintings of Raja Ravi Varma – father of Indian modern art’, Int. J. Arts and Technology, Vol. 15, No. 2, pp.170–207.
A study in the International Journal of Mechatronics and Manufacturing Systems shows how artificial intelligence (AI) can be used to extend the life of robotics components in the manufacturing sector by improving so-called power skiving tools.
Power skiving is an advanced method used in gear production that involves high-speed cutting. The tools used in these processes are highly susceptible to wear and tear and if this wear is not detected early, it can lead to costly replacements and re-sharpening, cutting into the profit margins of the product. Daniel Kiefer, Florian Grimm, Tim Straub, and Günter Bitsch of Reutlingen University, and Clemens Van Dinther of Karlsruhe Institut of Technology, Germany, have now shown that AI can be used to inspect and assess images of the cutting edges of tools acquired by a camera-equipped robotic cell and so provide early warnings to the manufacturing plant of imminent failures.
The AI uses a generative deep learning model that has been trained on images of anomalies that does not rely on a massive dataset of worn tool images. The new approach also side steps the need for images of defect-free tools for its training. The generative model essentially learns from a smaller dataset but can still identify wear patterns with remarkable precision and so predict the remaining useful life of a tool. This will help smaller manufacturers who may not have access to the large, expensive data sets needed by other AI models.
The automation of processes such as tool inspection and wear detection in this way could support workers, allowing them to focus on higher-level tasks. But, it also improves decision-making and minimizes human error.
Kiefer, D., Grimm, F., Straub, T., Bitsch, G. and Van Dinther, C. (2024) ‘Enhancing power skiving tool longevity: the synergy of AI and robotics in manufacturing automation’, Int. J. Mechatronics and Manufacturing Systems, Vol. 17, No. 2, pp.201–224.
A new approach to predicting carbon emissions at tourist attractions is discussed in the International Journal of Environment and Pollution. The tool developed by Xiumei Feng of Northeast Petroleum University in Qinhuangdao, China, uses a fuzzy support vector machine (SVM) to peak emissions in a way that improves significantly on conventional methods. The work could offer more precise and reliable forecasts of carbon emissions and so allow stakeholders to improve on how they manage the environmental impact of tourism.
Tourism is a major industry and a major contributor to carbon emissions, not least because of the energy-intensive activities such as transportation, energy consumption, and the operation of infrastructure that are involved. As we attempt to address the problem of climate change, there is a pressing need to manage and mitigate against the so-called carbon footprint of tourism. Peak carbon emissions represent the highest levels of emissions from a given tourist site and are an important measure of the potential impact of a given tourist trap on the environment. Understanding these peaks might allow stakeholders to devise more effective strategies to shrink the carbon footprint.
The models commonly used to predict carbon emissions often struggle with issues such as low stability, poor sensitivity, and inaccurate predictions. This, of course, limits their capacity to support effective climate action. To address the shortcomings, Feng has turned to an advanced statistical technique known as fuzzy SVM. This method is an enhancement of the traditional support vector machine model, which is widely used in machine learning to classify and predict data. The “fuzzy” aspect refers to a system that accounts for uncertainty, allowing the model to handle ambiguous or incomplete data more effectively.
Feng has applied the new approach to data on carbon emissions, tourist numbers, meteorological data, and resource usage and demonstrated that the model can make more accurate predictions regarding peak emissions. Understanding peak emission times will allow for better planning in terms of energy use, transportation schedules, and waste management—factors that collectively contribute to emissions at tourist destinations.
Feng, X. (2024) ‘Peak carbon emission prediction of tourist attractions based on fuzzy support vector machine’, Int. J. Environment and Pollution, Vol. 74, Nos. 1/2/3/4, pp.66–78.
The Internet of Things, which includes environmental sensor networks, industrial monitoring systems, home automation, and wearables, has brought with it an ever-increasing demand for computational power in smart mobile devices. Research in the International Journal of Information and Communication Technology, discusses how mobile edge computing might meet these demands.
Yujie Li, Yaoyao Xu, and Fangfang Cao of the Nanchang Institute of Science and Technology, and Xiang He of Jiangxi Flight University also in Nanchang, China explain how cloud computing served as the backbone for data processing in mobile devices. However, these systems have their shortcomings, such as the requisite connectivity, the likely bottlenecks and delays and the ever-present security and privacy risks associated with having one’s data on a third party system.
Mobile edge computing (MEC) could address many of these issues by decentralizing computation so that instead of a system being reliant on remote data centres and servers, the computational tasks are carried out on edge servers that are closer to the user. This reduces delays, latency, as well as potentially easing the load on the main servers, allowing faster processing of data to take place. However, even this approach raises problems of energy consumption as the mobile devices offload tasks to nearby servers.
The new work from Li and colleagues offers a way to tackle this issue by proposing an innovative resource scheduling model designed to optimize energy use in MEC systems. The new model assigns tasks in a non-random way that takes into consideration the available computational resources of the edge servers and their energy consumption. To enhance this process, the researchers used a sophisticated optimization technique known as enhanced particle swarm optimization. This algorithm gives quick convergence of processes to an optimal solution selected from a broad range of putative solutions to the given problem or task. It is thus more effective in managing energy usage across the entire system – on the mobile devices and on the edge servers.
The researchers’ test results are promising. When applied to a setup with ten smart mobile devices, the model was able to reduce energy consumption by up to 55% compared to other approaches. These savings are achieved through smarter scheduling of computational tasks, ensuring that both the energy needs of the mobile devices and the power costs of the edge servers are balanced.
Li, Y., Xu, Y., Cao, F. and He, X. (2024) ‘A meta-heuristic optimisation algorithm based method for scheduling edge computing resources’, Int. J. Information and Communication Technology, Vol. 25, No. 9, pp.88–103.
The following paper, "A meta-heuristic optimisation algorithm based method for scheduling edge computing resources" (International Journal of Information and Communication Technology 25(9) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Music is created, streamed, and consumed through electronic platforms and while this format does not suffer the pops and crackles or the wow and flutter of vinyl or magnetic tape, there is always the persistent problem of noise interference and how to minimise it. Taoru Kong of Xi’an Siyuan University in Xi’an, and Yanli Shen of Guangdong Polytechnic of Science and Technology in Zhuhai, China, writing in the International Journal of Computational Systems Engineering, point out that electronic music can be particularly susceptible to the problem of noise. The team is developing a powerful new approach to reducing noise interference.
The team’s system combines hardware and software designed to tackle noise interference. It begins with a music signal acquisition module that captures the raw audio. This data is then processed using an audio codec to refine the signal quality that exploits a large training data set and a clustering algorithm to detect and isolate unwanted noise. By analysing patterns within the music signal, the system can target interference, applying a statistical tool known as a an improved wavelet transform to eradicate the noise without distorting the original music.
In addition to this analytical system, the team has incorporated a so-called autocorrelation filtering algorithm. This step further cleans up the signal by isolating the music. This, the researchers say, produces a remarkably clear audio output, which is critical in a world where the smallest distortion can detract from the listener’s experience.
The experimental results show that this system outperforms traditional noise reduction methods by a significant margin. For example, it achieves a signal-to-noise ratio of 30.12 dB, which is considerably higher than the 27 to 28 dB range seen with conventional techniques.
Kong, T. and Shen, Y. (2024) ‘Design of music signal enhancement system based on big data clustering technology’, Int. J. Computational Systems Engineering, Vol. 8, Nos. 3/4, pp.182–191.
The following paper, "Prediction method of battery remaining life based on CEEMDAN-RF-SED-LSTM neural network" (International Journal of Information and Communication Technology 25(9) 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 Business Innovation and Research has looked at the relationship between digitalisation and labour productivity in the European Union. The study found that the growing digital divide between some countries means that the impact of technological transformation on productivity is far from uniform.
Giuseppe Cinquegrana of the Italian National Institute of Statistics in Rome, and Giovanni De Luca, Paolo Mazzocchi, Claudio Quintano, and Antonella Rocca of the University of Naples Parthenope, Italy, looked at 23 EU member states over a five-year period and found that digital advancements, such as internet connectivity, digital skills, and the adoption of new technologies, can have different effects around the EU.
Broadly speaking, digitalisation has a positive effect on productivity. However, this study shows that the benefits are most pronounced in countries that already have high levels of digitalisation, such as those in Northern Europe. Nations like Sweden and Denmark, with good digital infrastructure and a highly skilled workforce, experience the biggest productivity gains as digitalisation spreads. The relationship can be measured using the European Commission’s Digital Economy and Society Index, which tracks the progress of digital transformation, and gross domestic product per worker, a standard measure of productivity.
However, the study also reveals a more nuanced picture than is obtained from that data. It suggests that the impact of digitalisation on productivity is not immediate or even implicit. The team found that countries with better education systems and more extensive technological adoption are more likely to see digitalisation pay off in terms of higher productivity.
The findings reveal a stark north-south digital divide within the EU. Southern and Eastern European countries, in particular, lag behind their Northern counterparts in both digitalisation and productivity levels. This gap is further exacerbated by factors like lower investment in research and development and the presence of smaller, less innovative businesses. In these regions, the lack of resources to train workers in digital skills and the relatively low rate of technology adoption in businesses continue to hinder productivity growth. In highlighting this divide, the work offers the opportunity for policymakers to endeavour to close this digital divide.
Cinquegrana, G., De Luca, G., Mazzocchi, P., Quintano, C. and Rocca, A. (2024) ‘Impact of digitalisation on labour productivity in the EU’, Int. J. Business Innovation and Research, Vol. 35, No. 6, pp.1–39.
The following paper, "Impact of digitalisation on labour productivity in the EU" (International Journal of Business Innovation and Research 35(6) 2024), is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A novel framework for designing smarter, more sustainable products is discussed in the International Journal of Product Development. The framework could help car manufacturers and others navigate the increasing demand for digital services. Zhang Yan, Tobias Larsson, and Andreas Larsson of the Blekinge Institute of Technology, Sweden, explain that the Future Innovation Framework could change the way companies develop Product-Service Systems.
Product-Service Systems combine physical products with digital services in a collaborative process for their customers. With traditional product development models struggling to keep pace with technological advancements, the Future Innovation Framework gives manufacturers a structured approach to integrating digital solutions into their products as well as ensuring that they are meeting their sustainability goals.
At the heart of the Future Innovation Framework is the idea of value co-creation. In this, businesses and consumers work together to design products that provide mutual benefits. This is made possible by advances in information and communication technologies such as digital twins. Digital twins allow for real-time data sharing and the creation of virtual facsimiles of prototypes that can then be assessed so that smarter decisions can be made. By facilitating collaboration among the various people involved on both sides of the business, equation, the Future Innovation Framework can help companies create products and services that are more responsive to changing consumer needs as well as being more aligned with long-term sustainability.
The team reports on how car manufacture, Volkswagen, has already used the Future Innovation Framework in the design of its smart electric vehicle. The company’s work illustrates the practical benefits of this framework. The team explains that by getting diverse teams involved early in the design process, the manufacturer was able to address those technological challenges and sustainability concerns. The case study highlights the potential of the Future Innovation Framework to streamline the design process, improve innovation, and reduce the environmental impact of a product. It also has a role to play in the promotion of the circular economy, which can reduce waste and improve the lifespan of a given product, by shifting the focus from short-term sales to more sustainable practices.
Yan, Z., Larsson, T. and Larsson, A. (2024) ‘Future innovation framework (FIF) for value co-creation of smart product-service system design in a global automotive manufacturing company’, Int. J. Product Development, Vol. 28, No. 5, pp.1–29.
