AI, who drives the cars?

Urban congestion is a big problem in our cities. It leads to commuter delays  and economic inefficiency. More tragically, though, it leads to a million deaths annually worldwide. Research in the International Journal of Reasoning-based Intelligent Systems shows how artificial intelligence (AI) might be able to carry out real-time traffic forecasting and so provide a way for the authorities to manage our road networks better.

Road vehicles do not behave as individual entities, traffic flow is a dynamic system in which there are no truly isolated events at individual locations, but conditions that ebb and flow over time. The researchers describe this phenomenon as spatiotemporal dependency. Events at one point at a given time influence conditions elsewhere on the roads. For example, a slowdown on a motorway might trigger congestion further down the route or in areas fed by the motorway some time later.

The researchers explain that capturing these delayed and distributed effects has long proved difficult for conventional forecasting models. Existing systems rely on simplified assumptions or short-term data patterns. The new approach using a hybrid deep learning system known as STG-Former. This brings together two computational approaches: graph neural networks and transformer models. A graph neural network represents the road system as a network of connections. The model can thus learn about traffic conditions over an area. The transformer component uses an attention mechanism to identify the most relevant information at any given time. It can thus detect patterns as they change through time.

Tests with this new system on standard traffic datasets show the model is much more accurate in its predictions than even the leading rivals and works well during periods of peak congestion when those other models often fail. The improvement is significant in the context of urban congestion, where even a small improvement in predictions can help traffic management improve its operational decisions and so avoid gridlock or major stalls in the flow of traffic.

Cheng, H., Cao, Y. and Li, W. (2026) ‘Transformer-GNN hybrid architecture for optimising real-time traffic forecasting on highways’, Int. J. Reasoning-based Intelligent Systems, Vol. 18, No. 9, pp.38–50.

New Open Access article available: "An edge computing-based fast restoration for urban medium- and low-voltage distribution networks"

The following International Journal of Critical Infrastructures article, "An edge computing-based fast restoration for urban medium- and low-voltage distribution networks", is freely available for download as an open access article.

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

New Open Access article available: "Fuzzy best-worst method for analysing the threats of AI in education"

The following International Journal of Mathematics in Operational Research article, "Fuzzy best-worst method for analysing the threats of AI in education", is freely available for download as an open access article.

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

Free sample articles newly available from International Journal of Cloud Computing

The following sample articles from the International Journal of Cloud Computing are now available here for free:

• Federated architecture for serverless platforms aimed at transparent execution in the edge-cloud continuum
• An enhanced two-level data sanitisation and elliptic curve cryptography encryption model for securing electronic healthcare data in a hybrid cloud platform
• An effective algorithm for predicting load and dynamic task scheduling in cloud fog architecture for smart homes
• An optimised AI-driven swarm-based enhanced task scheduling model for cloud computing environment
• Designing a hybrid heuristic-aided approach for replica placement and migration strategy for SaaS applications in edge cloud

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Low-power mesh networks for off-grid communication systems: a 5G-fibre hybrid integration solution
• Neural networks and cognitive diagnostic modelling for OBE-oriented curriculum association maps
• Abstract art pattern generation via diffusion models and variational autoencoders
• An automatic English pronunciation scoring model using GAN-enhanced synthetic data and active learning
• Application of generative AI in composition assistance and creative music teaching

Research pick: Grid vibrations – AI detects power supply cyberattacks in less than two seconds - "Network security threat identification based on GNN-transformer fusion model in energy cyber systems"

Modern energy infrastructure is increasingly defined as cyber-physical systems where physical power distribution and digital communication are closely tied together. While this digitalisation boosts efficiency, it exposes electricity grids to sophisticated cybersecurity risks. To combat such threats, researchers have developed an artificial intelligence (AI) method that integrates network structure analysis with data tracking to identify complex attacks that conventional security systems might miss. Details are reported in the International Journal of Global Energy Issues.

Energy infrastructure is vulnerable to Advanced Persistent Threats (APTs). Unlike localised glitches, APTs involve long-term infiltration where attackers quietly gather data or manipulate operational signals. A major problem is the False Data Injection (FDI) attack, where sensor measurements are altered to feed operators misleading information. Such changes can cause catastrophic errors in energy flow and paralyse physical fuel supplies across entire regions. Such vulnerabilities are manifest as ransomware attacks, but increasingly, there are the risks associated with international conflict.

Detecting these incursions is difficult because malicious commands often mimic routine operational activity. Legacy detection systems use “signatures”, predefined rules based on known past threats. Such an approach is generally ineffectual in the face of new, “zero-day” exploits or attacks that otherwise do not match existing patterns.

The new AI approach uses two distinct types of information: structural information (the physical and digital layout of devices and control centres) and temporal information (the chronological sequence of commands and signals) to identify an ongoing attack. The dual-layered deep learning architecture is based on a Graph Neural Network (GNN) that maps the system’s spatial layout, and a Transformer model analyses data sequences over time. The former gives the AI a picture of the physical aspects of the infrastructure, and the latter understands how it changes over time. Such a spatiotemporal AI detection system can identify coordinated, multi-stage attacks that appear harmless when viewed as isolated events.

Testing with standard cybersecurity datasets proved the new AI model to have an accuracy of more than 93 per cent. Critically, it identifies suspicious activity in less than two seconds of it starting. This offers a viable way to near-real-time protection of power infrastructure, the research suggests.

Dai, Y., Lu, J., Li, Z., Li, J. and Rafieipour, M. (2026) ‘Network security threat identification based on GNN-transformer fusion model in energy cyber systems’, Int. J. Global Energy Issues, Vol. 48, No. 7, pp.64–84.

Free sample articles newly available from International Journal of Autonomous and Adaptive Communications Systems

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• Survey on sport video analysis and event detection
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• An improved salp swarm algorithm for collaborative scheduling of discrete manufacturing logistics with multiple depots

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Intelligent scoring method for English articles leveraging large language models
• An English vocabulary pronunciation evaluation model based on multidimensional audio features and machine learning
• Student dance teaching motion recognition and classification based on spatial temporal graph convolutional networks
• Blockchain-based carbon footprint tracking and circular network construction for the sharing economy
• Real-time detection and correction of pipa playing finger techniques based on video data analysis

Free sample articles newly available from International Journal of Internet Protocol Technology

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• Network big data association recommendation method based on modified entropy and improved FCM algorithm
• Data mining technology for machinery equipment and information networks
• An innovative method for highly accurate stock price forecasting: a case study on HSI
• Enhanced congestion control in transmission control protocol using harmonic red panda optimisation for heterogeneous networks
• Intelligent robot path planning based on multimodal deep learning algorithm

Free Open Access special issue on "Interdisciplinary Research of Energy Application, Governance, and Policy for Sustainability – Part 1" published by International Journal of Innovation and Sustainable Development

The International Journal of Innovation and Sustainable Development has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Stability of school-enterprise cooperation in energy education: interaction mechanisms and policy implications
• Modelling and diagnosis method of power transformer sound characteristics by integrating sparse representation and deep autoencoder network
• Spatial distribution of geographical indication agricultural product clusters and their impact on the sustainable development of the agricultural energy-economy system
• The high-quality development of China's green energy economy for promotion of digital finance under deep learning technology
• Graph neural network model for cable tunnel cost prediction under high-dimensional construction data

Associate Prof. Fa Zhu appointed as new Editor in Chief of International Journal of Granular Computing, Rough Sets and Intelligent Systems

Associate Prof. Fa Zhu from Nanjing Forestry University in China has been appointed to take over editorship of the International Journal of Granular Computing, Rough Sets and Intelligent Systems.

Free sample articles newly available from International Journal of Markets and Business Systems

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• The electrification of passenger transport for sustainable mobility: challenges and opportunities from the perspective of key stakeholders
• Sustainability disclosures and firm value: evidence from the Ghana Stock Exchange
• Attributions of QR code-driven perceived flow on customer satisfaction
• The prevalence of emotionality and spirituality over rationality in knowmads' career decision making: a qualitative case study on individual knowledge dynamics
• Mapping the impact of sales promotions on consumer perception and behaviour: a bibliometric analysis

Free sample articles newly available from Asian Journal of Management Science and Applications

The following sample articles from the Asian Journal of Management Science and Applications are now available here for free:

• Estimation of average TSP distance considering zone length-width ratio: implications for territory design
• Optimal operation and social evaluation in a closed-loop supply chain with quality and reuse of used electric vehicle batteries under government subsidy
• Hierarchical production planning system for a plastic container manufacturer with a combined processing-assembly and hybrid flow shop
• A study of the multi-objective flexible job-shop scheduling model considering human factors
• An optimised vehicle routing model for minimising distribution costs in cold-chain logistics

Free Open Access issue published by International Journal of Information and Communication Technology

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• Low-altitude UAVs and IoT-empowered fresh cold chain logistics system for mountainous areas
• Artistic image restoration and semantic reconstruction driven by multimodal AIGC
• Deep learning-based power transformer condition monitoring and fault diagnosis algorithm
• Optimising privacy protection for cross-border data flow based on federated learning
• Agent-driven big data interaction empowers personalised marketing efficiency

Research pick: Don’t cross the streams - "Evolving copyright paradigms in the age of live streaming in music and video piracies"

Digital technologies have over the last few decades reshaped how we consume music, films, and live performances. Consumers can access content with the click of a mouse or the tapping of an icon, and while there are countless legitimate sources for that content, there are perhaps just as many illegal sources, so-called pirate sites.

Content piracy is nothing new. Back in the pre-recorded days when many people had musical instruments, such as pianos, in their homes or access to them in pubs and other venues, printed sheet music was the equivalent of a recording of a song. You could recreate the song in your own home for pennies or less if you could get hold of a pirated copy of said sheet music. Today, the world is a very different place, but the principles are the same. People want to hear music, and many of them don’t want to pay much, if anything, for that privilege.

Research in the International Journal of Intellectual Property Management has looked at piracy in the age of online live streaming. The work shows that copyright systems are struggling to keep pace with technological change, particularly in fast-growing digital markets such as India. The study focuses on the legal and technological obstacles confronting regulators as new forms of piracy proliferate.

Digital piracy refers to the unauthorised copying, distribution or use of copyrighted works. Copyright itself is a form of intellectual property protection covering creative output such as music, books, films, sculpture, artworks, artistic performances, and even light shows. Unlike patents and trademarks, copyright largely operates as what legal scholars call a negative right. This means that rights holders cannot compel others to use their work but can prevent others from reproducing or distributing it without permission or payment.

Copyright is meant to encourage creators to produce new work by protecting their economic interests, while at the same time allowing the public to gain reasonable access to knowledge and culture. That balance becomes more difficult in a digital environment where copying and distribution occur almost instantaneously across global networks. Online streaming services, user-content platforms are on the cold front of the copyright conflict. Platforms support legitimate creative activity but also make it easy for users to distribute unauthorised material.

To counter copyright theft, rightsholders often use Digital Rights Management, or DRM. DRM refers to technological systems designed to control how digital content can be used. These protections may limit copying, restrict access only to authorised devices, or require authentication through a paid account. However, as with much of illegal activity, those developing DRM systems are increasingly vulnerable to circumvention from pirates who develop their own systems to counter the DRM systems. The newest programmes, sometimes enhanced or even developed with generative artificial intelligence, GenAI, can break or evade DRM protection with relative ease.

International agreements such as the Rome Convention and treaties administered by the World Intellectual Property Organization have common standards recognising performers’ rights and requiring member states to extend equivalent protection to foreign creators, but with increasingly sophisticated piracy techniques, legal mechanisms lag way behind.

Nath, A. and Chakravarty, G. (2026) ‘Evolving copyright paradigms in the age of live streaming in music and video piracies’, Int. J. Intellectual Property Management, Vol. 16, No. 1, pp.28–44.

Research pick: Understanding urban green space dynamics - "Dynamic monitoring and evolution of urban green space landscape sustainability based on spatiotemporal analysis algorithm"

Rapid urbanisation is reshaping cities across the globe. This is having a detrimental effect on many green spaces, such as parks, urban forests, green corridors, and landscaped public areas. Ultimately, these changes represent a loss of ecological and social benefits, such as helping moderate temperatures, improve air quality, manage stormwater, support biodiversity, and contribute to the wellbeing of city dwellers.

Of course, as people head for the cities, housing, infrastructure, and commercial development must change to accommodate their needs. Understanding how urbanisation and the loss of green spaces affect the city’s sustainability is high on the agenda for urban planners and environmental scientists.

A study in the International Journal of Environment and Sustainable Development has looked at one of the limitations of earlier research: the reliance on a static assessment of those urban green spaces. Conventional approaches capture conditions at a single moment in time or compare only a few snapshots, and this does not reflect the complex and dynamic nature of urban landscapes. In reality, green spaces expand, contract, and shift unevenly across neighbourhoods and time periods. This makes it difficult to home in on the causes and consequences of change.

To tackle this problem, the researchers have turned to advanced spatiotemporal analytical methods. Spatiotemporal refers to the combined study of where and when changes occur. An algorithm then detects clusters within the complex shifting datasets and identifies hotspots where green space coverage changed significantly and areas where landscapes became increasingly fragmented.

The team then used a second layer of analysis to understand the underlying causes. They used a geographically and temporally weighted regression model, which considers how population growth, development intensity, land-use policy, and other factors vary across locations and over time. Their approach could then link changes in landscape structure directly to the degradation of the ecological “services” provided by those urban green spaces and point to how urban planning might be used to remedy the problem by countering the losses.

Ouyang, L., He, Y., Chen, Z. and He, K. (2026) ‘Dynamic monitoring and evolution of urban green space landscape sustainability based on spatiotemporal analysis algorithm’, Int. J. Environment and Sustainable Development, Vol. 25, No. 5, pp.3–23.

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

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

• Dynamic cost control methods for computer-integrated engineering based on digital twins
• Immersive virtual reality art generation via neural style transfer
• Integrated design of performance-oriented cost accounting in colleges and universities driven by artificial intelligence
• Transformer-GNN hybrid architecture for optimising real-time traffic forecasting on highways
• Legal loophole detection model based on multi-agent reinforcement learning

Free sample articles newly available from International Journal of Continuing Engineering Education and Life-Long Learning

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• Learners' eye movement behaviour in a conceptual knowledge video lecture: a Chinese case study
• Advanced ideological and political education strategy based on artificial intelligence: edge computing method
• Semiotics in engineering education for enhancing communication awareness
• Construction and implementation of exploratory teaching model based on social network analysis
• Based on the S-O-R model – how does interaction influence engineering students' English learning continuance on online platforms

Free Open Access special issue on "Contemporary Technology Progress for Creativity, Innovation, and Entrepreneurship Management in the Global Energy Sector: Part 1" published by International Journal of Global Energy Issues

The International Journal of Global Energy Issues has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Marine ecological governance and green development in Beibu Gulf of Guangxi under the digital context
• A digital technology for energy-saving ventilation control in underground infrastructures: integrating coupled simulation and BP algorithm
• Effect of international new energy teaching on promoting regional new energy communication based on intelligent BP algorithm
• Network security threat identification based on GNN-transformer fusion model in energy cyber systems
• Carbon comfort prediction and innovation enhancement for campus building clusters based on k-means clustering

Free sample articles newly available from International Journal of Simulation and Process Modelling

The following sample articles from the International Journal of Simulation and Process Modelling are now available here for free:

• Agent-based simulation model for evacuation operations in fire disasters
• Bi-objective optimisation for intelligent warehouse scheduling based on student psychology mechanism
• The role of discrete-event simulation in emergency management during the COVID-19 pandemic
• Optimising multi-modal fusion with a tri-encoder tensor network for process applications
• Efficient master production scheduling for manufacturing systems using an enhanced SARSA algorithm
• Defect detection method of Chinese mitten crab based on improved EfficientVit
• Simulation-driven fault diagnosis for track circuits using multi-scale convolution and transformers under imbalanced data conditions
• Improving maritime distress target detection through modelling and simulation with YOLOv5s and Next-ViT
• Optimising healthcare process efficiency with HyperBERT: embedding ICD code hierarchy for national healthcare systems simulation and improvement

Research pick: Like attracts like - "The effect of female supervisors on the structure and dynamics of the management board"

Efforts to increase gender diversity on corporate boards have often been justified on grounds of fairness and representation. Research in the International Journal of Corporate Governance suggests that the presence of women in supervisory roles may also shape how companies are run, influencing both who becomes a top executive and how closely senior leaders are monitored.

The study examined publicly listed German companies during a period when political pressure to increase female representation in corporate leadership was high on the agenda. Germany formally introduced a gender quota in 2016 requiring large listed companies to ensure that at least 30 per cent of supervisory board members are women. This led to a significant increase in female representation on supervisory boards by the end of the decade. Yet, say the researchers, women were not as well represented on management boards. A mere one per cent of executive roles were held by women in the mid-2000s, and that figure had only risen to about 10 per cent by 2019.

To understand how female representation influences corporate leadership, the study analysed almost 100 publicly listed firms subject to codetermination rules. It focused on two outcomes: the composition of management boards, particularly the presence of female executives, and executive turnover, the rate at which top leaders leave their positions. The analysis focused on chief executive officers (CEOs), chief financial officers (CFOs), and chief human resources officers (CHRO).

The study used a statistical method known as an instrumental variable approach to address a common difficulty in this kind of research, endogeneity. Endogeneity arises when cause and effect are intertwined. For example, firms that are already committed to diversity may appoint more female supervisors and promote more women to executive roles, making it difficult to determine whether one caused the other. By using earlier levels of female representation as a statistical instrument, the analysis could isolate the causal impact of women serving on supervisory boards.

The results suggest that the influence of female supervisors depends less on their overall numbers than on where they sit within the governance structure. Women serving as shareholder representatives on the remuneration and personnel committee significantly increase the proportion of women on management boards. Because this committee prepares decisions about executive appointments, membership provides direct influence over who joins the leadership team.

This pattern is consistent with a concept in social science known as the similarity attraction paradigm, like attracts like, if you will. The theory holds that individuals often favour colleagues who resemble themselves, whether in background, experience or identity. Applied to corporate boards, it suggests that female supervisors may be more likely to support female candidates for executive roles, particularly when they have direct authority over appointments.

Carow, J. (2026) ‘The effect of female supervisors on the structure and dynamics of the management board‘, Int. J. Corporate Governance, Vol. 16, No. 1, pp.1-37.

Free sample articles newly available from International Journal of Electronic Customer Relationship Management

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• Impact of logistic flows of service quality and delivery dimension towards customer satisfaction: an empirical study
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• Integration of customer relationship management in e-commerce
• Impact of influencer marketing on buying behaviour of millennials and generation Z

New Open Access article available: "Multimodal transformer-driven consistent environment design generation simulation modelling"

The following International Journal of Simulation and Process Modelling article, "Multimodal transformer-driven consistent environment design generation simulation modelling", is freely available for download as an open access article.

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Free sample articles newly available from International Journal of Corporate Governance

The following sample articles from the International Journal of Corporate Governance are now available here for free:

• Effect of board attributes on the quality of integrated reports: evidence from India
• Do female directors influence the relationship between environmental, social and governance scores and firm market value in emerging economies?
• Foreign family directors, gender diversity, and debt costs for family business firms
• Do unhealthy cities produce unhealthy returns?

New Open Access article available: "Enhancing retail decision-making accuracy through deep learning-based consumer sentiment simulation modelling"

The following International Journal of Simulation and Process Modelling article, "Enhancing retail decision-making accuracy through deep learning-based consumer sentiment simulation modelling", is freely available for download as an open access article.

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

Research pick: Women lead on corporate sustainability - "Females on board and sustainability performance: evidence from the emerging markets"

Research in the International Journal of Corporate Governance suggests that the makeup of corporate boards can affect how companies approach sustainability, particularly in emerging economies where governance systems are still developing.

The study is based on observations amounting to almost 20000 firm-years across 25 emerging markets. A firm-year is a single observation representing one company’s data for one year in empirical business research. Thus, 20,000 firm-years consists of data collected for many companies over several years, where each company contributes one observation for each year it appears in the data.

The work shows that companies with more women on their boards tend to have better environmental, social, and governance (ESG) performance. The work also questions the received wisdom of governance that increasing the number of independent directors strengthens corporate responsibility.

Sustainability performance refers to how companies manage ESG issues. Environmental factors include carbon emissions, pollution, and resource use. Social factors relate to employee welfare, diversity, and community engagement. Governance concerns how firms are directed and controlled, including leadership accountability and board oversight. These various factors can be scored together to give investors and regulators a single metric with which they can assess long-term corporate risk and resilience.

A key feature of the current study is that it distinguishes between female executive directors who hold senior management positions and influence operational decisions and non-executive directors that provide oversight and strategic guidance but are not involved in the daily management of the company.

The works shows that the presence of women in both types of role is associated with better ESG scores. The researchers suggest that gender diversity broadens perspective in boardroom decision-making and encourages focus on long-term risks and stakeholder concerns.

The analysis also identifies an unexpected pattern regarding board independence. Independent directors—board members who are not part of company management—are widely viewed as essential for objective oversight. However, the study finds that a higher proportion of independent directors is linked to lower sustainability scores in the sampled emerging markets.

Elbayoumi, A.F., Elmoursy, H., Eljilany, S.M., Bouaddi, M. and Basuony, M.A.K. (2026) ‘Females on board and sustainability performance: evidence from the emerging markets’, Int. J. Corporate Governance, Vol. 16, No. 1, pp.67–89.

Free Open Access issue published by International Journal of Information and Communication Technology

The International Journal of Information and Communication Technology has published an Open Access issue. All of the issue’s papers can be downloaded via the full-text links available here.

• Research on analysis and improvement strategies of consumer loyalty on e-commerce platforms based on big data
• Enterprise energy management optimisation and decision support system based on big data analysis
• Coordinated design of a smart charging control device for the distribution transformer side, integrating AI and optimisation technologies
• A meta-learning-based reinforcement learning framework for rapidly adaptive emotion intervention
• Machine learning-based forecast of procurement budgets for low-value consumables

New Open Access article available: "Discrete-event simulation modelling of inventory turnover under supply chain financial collaboration"

The following International Journal of Simulation and Process Modelling article, "Discrete-event simulation modelling of inventory turnover under supply chain financial collaboration", is freely available for download as an open access article.

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

Free sample articles newly available from International Journal of Intellectual Property Management

The following sample articles from the International Journal of Intellectual Property Management are now available here for free:

• The impact of intellectual capital on financial performance for selected Indian pharmaceutical companies
• The danger of deepfakes, Indian laws and platform responsibility
• Understanding the possibilities, challenges, and opportunities in relationship between IPRs and food technology
• An empirical study on message forwarding on social networking sites: a sample of Vietnamese users
• Knowledge diffusion and new technologies: a spillover analysis on the artificial intelligence case

Prof. Mahamadou Biga Diambeidou appointed as new Editor in Chief of International Journal of Comparative Management

Prof. Mahamadou Biga Diambeidou from UCLouvain in Belgium has been appointed to take over editorship of the International Journal of Comparative Management.