Free Open Access issue published by International Journal of Business Information Systems

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

• Embracing artificial intelligence in audit processes: challenges and enablers from the perspective of independent audit firms in Vietnam
• Cloud-based accounting information systems acceptance by culinary MSMEs in Bandung City: UTAUT-3 modelling approach

The “bear” essentials in teaching economics

Research in the International Journal of Pluralism and Economics Education argues that “The Jungle Book” can serve as an unconventional teaching tool for undergraduate economics, using the original stories by Rudyard Kipling as well as the Disney film adaptations to introduce concepts ranging from scarcity and sustainability to happiness and development.

The researchers used qualitative content analysis, a technique that looks beyond the literal content of texts to identify underlying themes and patterns. They thus examined passages from the literary work and the 1967 animated film, as well as its 2016 live-action adaptation. They focused on the theme of the “bare necessities", the basic goods and conditions required for a decent quality of life. The concept was made punningly famous by the lyric sung by Phil Harris voicing the friendly bear of the story, Baloo.

The material is used to illustrate concepts including opportunity cost, the idea that choosing one option means giving up another; barter and monetary economies; sustainable production and consumption; and the relationship between income and happiness. The team suggests that the same material might allow teachers to develop more advanced lessons that even connect the stories to the United Nations Sustainable Development Goals and the “tragedy of the commons”, in which an individual’s pursuit of their own interests can deplete the resources the benefits of which everyone might otherwise share.

Laha, A. and Maji, S.K. (2026) ‘Bare necessities: understanding economics from The Jungle Book’, Int. J. Pluralism and Economics Education, Vol. 16, No. 2, pp.200–223.

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Free sample articles newly available from International Journal of Electronic Governance

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

• Structural equations and machine learning: an approach to measuring political stability and citizen support in social networks
• Impact of citizen participation through e-government platforms on satisfaction and trust
• Indian approach to data rights: survey of social structures, and personal data protection regimes in India
• E-governance and AI impact on the improvement of e-government services: transformative leadership as a mediator
• Adoption level of AI conversational systems by governments in Nigeria towards reducing inequality to information access

Free Open Access special issue on "Interdisciplinary Research of Energy Application, Governance, and Policy for Sustainability – Part 2" 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.

• The 3D digital revitalisation of industrial heritage in energy sector for the third front construction in Southwest China
• Fast identification algorithm for cacading failures of AC-DC hybrid green power grid considering heterogeneous characteristics
• The innovation of deep learning-based entrepreneurship capabilities of green tourism students under the Internet of Things
• Economic growth and carbon neutrality balancing: an optimal decision-making framework for emission reduction policies driven by reinforcement learning

Free sample articles newly available from Journal for Global Business Advancement

The following sample articles from the Journal for Global Business Advancement are now available here for free:

• Policy synthesis for sustainable trade: a panel data gravity model approach of India with European Union and ASEAN countries
• Brand trust and brand loyalty in electronics home appliances in Bangladesh: moderating role of demography and brand-origin, social media and its usage duration
• Audit procedures, auditors' experience and responsibility for fraud detection: a Javanese culture perspective
• Cultural intelligence: research field analysis through VOSviewer and CiteSpace software
• Factors influencing organic food purchasing behaviour: does gender matter? A comparative study between Malaysia and Pakistan
• The impact of content quality on visit intention through celebrity emotional attachment: evidence in hospitality

New Open Access article available: "Prediction of computer network security situation based on machine learning"

The following International Journal of Intelligent Information and Database Systems article, "Prediction of computer network security situation based on machine learning", is freely available for download as an open access article.

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

Research pick: Computer, protect thyself - "Prediction of computer network security situation based on machine learning"

A machine-learning model has been designed to predict emerging computer-network security threats with greater reported accuracy than support-vector-machine systems, according to research in the International Journal of Intelligent Information and Database Systems.

The approach described uses a radial basis function neural network (RBFNN). This is an AI, artificial intelligence, model designed to identify complex, non-linear relationships in data. The researchers trained the RBFNN on processed network-security information, including data that can be generated by intrusion-detection systems, firewalls and network traffic. The system ultimately makes network defence more proactive rather than relying on the predominantly reactive technology of firewalls and after-the-fact intrusion-detection systems. Instead of relying on predefined rules to recognise known threats, it can analyse incoming data and use its training to spot similar patterns and so act as an early-warning system.

In tests, the RBFNN correctly classified more than 95% of normal network activity and Heartbleed attacks and achieved 97% accuracy in identifying , denial of service (DoS) attacks. Its accuracy for brute-force attacks was somewhat lower, at up to 93%. However, it had an overall misclassification rate of less than 5%.

The researchers envisage a real-time service capable of automatically analysing data, detecting anomalies and generating alerts. Such systems could become increasingly important as attacks and advanced persistent threats become more varied and difficult to identify using fixed rules.

Liu, Y. (2026) ‘Prediction of computer network security situation based on machine learning’, Int. J. Intelligent Information and Database Systems, Vol. 18, No. 7, pp.1–18.

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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.

• Construction of cross-media semantic relevance model for college English teaching based on output-driven hypothesis and two-way attention feature learning
• Neural ordinary differential equation waveform modelling for multidimensional analysis of singing technique
• Real-time capture and simulation system of gymnastics motion based on 3D vision transformer and multi-objective optimisation
• Intelligent human-computer collaborative scoring system for English writing using large-scale model representation learning and knowledge reasoning
• Cyber-physical system-based adaptive PID power regulation for cooling tower pumps

New Open Access article available: "Safety risk perception of high-rise building construction process based on digital twin technology"

The following International Journal of Critical Infrastructures article, "Safety risk perception of high-rise building construction process based on digital twin technology", 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 Computational Biology and Drug Design

The following sample articles from the International Journal of Computational Biology and Drug Design are now available here for free:

• Innovating prosthetic foot design: integrating big data and computational biology for enhanced lower limb rehabilitation
• ADMET analysis and molecular docking of phytocompounds of Magnolia champaca leaf essential oil as potential inhibitors of α-Glucosidase, Estrogen Receptor-α, TNF-α, and Xanthine Oxidase
• Costunolide and Lupeol reinforce IRF3 gene activity in human immune response against COVID-19
• Liver tumour segmentation and classification using MV3CNN-KHO: a combination of multiparameterised inception V3 CNN and Krill Herd optimisation
• AdaCluCSL: an approach for autism spectrum disorder prediction using adaptive clustering smote and cost-sensitive learning

Research pick: AI optimises energy production and cuts carbon emissions in seconds - "Modelling and predicting energy consumption patterns using generative adversarial networks for effective carbon management"

A new AI model for predicting energy consumption could help managers plan ahead as well as open up opportunities for cutting carbon emissions, according to research in the International Journal of Information and Communication Technology.

The system uses a transformer-based generative adversarial network (GAN) to learn complex patterns in energy use. GANs are machine-learning systems in which two neural networks work against each other to produce realistic data. By adding Bayesian statistical optimisation, the team could set the system for best performance.

They tested the model on 2000 hourly energy and emissions records drawn from smart meters, building management systems, and industrial grids. They removed references to missing data and deleted outliers to normalise the input. The model made predictions that closely matched the observed energy data while taking only a few seconds to train and run.

The researchers explain that their computer-generated scenarios will allow operators to test demand-shifting measures, integrate renewable generation, and identify inefficiencies ahead of actual power generation and emission formation.

The approach addresses several weaknesses in conventional predictive models, which are known to struggle with non-linear consumption patterns, sudden spikes and troughs, and multiple external factors. This carbon-aware energy optimisation could be used across sites with internal power generation, such as industrial sites and in wider energy systems.

Liu, Y. and Li, B. (2026) ‘Modelling and predicting energy consumption patterns using generative adversarial networks for effective carbon management’, Int. J. Information and Communication Technology, Vol. 27, No. 92, pp.79–110.

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Free sample articles newly available from International Journal of Web Based Communities

The following sample articles from the International Journal of Web Based Communities are now available here for free:

• The hidden impact of hashtags on Instagram: navigational heuristics on source trustworthiness
• Exploring the impact of COVID-19 pandemic and vaccine dissemination on Airbnb's popularity and sentiment on Twitter
• Customer churn prediction based on customer value and user evaluation emotions in online marketing
• A supply chain risk identification method of foreign trade e-commerce enterprises based on social network analysis
• False information recognition of social media platforms based on multi-modal feature fusion
• A method for evaluating confidence of social media information based on time series analysis
• Study on redundant data dimension reduction algorithm for cloud computing in the internet of things environment
• Large scale MicroBlog location data capture method based on dynamic web page parsing
• Dynamic collaborative mining method of user perceived interest points in mobile e-commerce platform
• Personalised recommendation method for live streaming e-commerce products based on multimedia social networks

New Open Access article available: "Developing community-based waste management for public spaces in coastal tourism villages: establishing institutions with local champions"

The following International Journal of Tourism Anthropology article, "Developing community-based waste management for public spaces in coastal tourism villages: establishing institutions with local champions", is freely available for download as an open access article.

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

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.

• Enhanced multimodal recognition and genealogy research of Maonan ethnic Nuo masks based on YOLOv10 and CLIP fusion approach
• Artificial intelligence-enhanced Chinese academic writing instruction for cross-cultural communication: a framework for Sino-French and Sino-African contexts
• GAN-based reconstruction for the automatic generation of business English emails and its potential
• Modelling and predicting energy consumption patterns using generative adversarial networks for effective carbon management
• Design and development of a student information management platform based on support vector machines and data mining

New Open Access article available: "Air pollution and asthma hospitalisations in New York City: a borough-level information analysis of spatial, seasonal, and socio-economic determinants"

The following International Journal of Business Information Systems article, "Air pollution and asthma hospitalisations in New York City: a borough-level information analysis of spatial, seasonal, and socio-economic determinants", 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 Networking and Virtual Organisations

The following sample articles from the International Journal of Networking and Virtual Organisations are now available here for free:

• Networks between industry academia: a statistical approach based on India
• Application of particle swarm optimisation in collaborative scheduling of logistics and supply chain
• From personality to connection: the mediating role of tie strength in HEXACO traits and job networking behaviour
• Efficient call admission control in LTE networks with cascade feed forward network
• Social media for climate action in developing countries

Research pick: Not a waste! - "Developing community-based waste management for public spaces in coastal tourism villages: establishing institutions with local champions"

Local action may offer a model for waste management in rural tourism, according to research in the International Journal of Tourism Anthropology.

A study of waste problems in Kampung Nipah, a coastal tourism hamlet in North Sumatra, Indonesia, argues that rural communities with limited public services may need locally governed waste systems rather than relying solely on municipal provision. The researchers found that fly-tipping and littering in Kampung Nipah is linked to inadequate infrastructure. However, it also occurs because of established cultural practices, weak collective responsibility, and an absence of an institution responsible for managing waste across the wider village. The team explains that government waste-collection services do not reach the area, while rubbish from residents, tourists and rivers can accumulate along the coast.

The study involved ethnographic methods, a close, but extended, study of people and their everyday practices. It was able to show how social behaviour and institutional arrangements contribute to the problem of local waste in such a place. To overcome this problem, the team proposes a community-based model centred on local champions, residents who take an active leadership role, who work alongside tourism managers and other stakeholders to change the waste culture.

While the work focuses on only one location, it may well prove to have wider implications for rural coastal tourism elsewhere.

Zuska, F. and Zulkifli, Z. (2026) ‘Developing community-based waste management for public spaces in coastal tourism villages: establishing institutions with local champions’, Int. J. Tourism Anthropology, Vol. 10, No. 5, pp.1–22.

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New Open Access article available: "Government support and digital strategy driving MSME performance: the mediating role of digital transformation"

The following International Journal of Business Innovation and Research article, "Government support and digital strategy driving MSME performance: the mediating role of digital transformation", is freely available for download as an open access article.

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

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.

New Open Access article available: "Core genes and pathways underlying ferroptosis in chondrosarcoma pathogenesis: through bioinformatics analysis"

The following International Journal of Data Mining and Bioinformatics article, "Core genes and pathways underlying ferroptosis in chondrosarcoma pathogenesis: through bioinformatics analysis", is freely available for download as an open access article.

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

Research pick: Reaching new heights, with safety in mind - "Safety risk perception of high-rise building construction process based on digital twin technology"

Research in the International Journal of Critical Infrastructures describes a digital-twin system that could make safety monitoring on construction sites for high-rise buildings more effective. The system could allow accident risks to be identified as they appear rather than the site simply responding to hazards after the fact.

The team combined three techniques to build their system. First, they used an improved form of grey relational analysis, a statistical approach that works with incomplete data. Secondly, the incorporated local linear embedding reduces data complexity without compromising the relationships. Finally, they embedded a digital twin, a virtual representation of the physical construction site, linked to live measurements from the real environment.

Tests across 90 cases produced recall rates of around 96 to 99 per cent in under a second of processing time. The accuracy of risk factor identification was up to almost 98 per cent.

Fundamentally, accounting for interactions between hazards could help address risks that conventional systems overlook, including falls, struck-by incidents, collapses, mechanical injuries, and electric shocks. The short processing time will allow interventions to be made on-site in a more timely manner when conditions can change rapidly.

Deng, R. and Zhou, L. (2026) ‘Safety risk perception of high-rise building construction process based on digital twin technology’, Int. J. Critical Infrastructures, Vol. 22, No. 12, pp.1–23.

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International Journal of Arts and Technology is now an open access-only journal

We are pleased to announce that the International Journal of Arts and Technology is now an Open Access-only journal. All accepted articles submitted from 31 August 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

Research pick: Using AI to track bird migration - "Advancements and challenges in bird migration models: a comprehensive survey"

On hearing the first cuckoo of spring, the poet’s heart might sing, and while one swallow does not a summer make, the annual migrations of bird species across continents have fascinated us for centuries. Today, however, technology is giving ornithologists the means to follow these incredible journeys in ways that would have been unimaginable to earlier generations of naturalists.

Research in the International Journal of Global Environmental Issues shows that artificial intelligence (AI) is being used by conservationists to help predict bird migration timings and patterns. The technology might allow them to identify how climate change and habitat loss are affecting the journeys of many migratory bird species.

The team looked at research into machine learning and deep learning models used to analyse migration, habitat preferences, and bird populations. They explain that machine learning refers to computer systems that identify patterns in data, while deep learning is a form of machine learning that uses layered neural networks to detect more complex patterns. Increasingly, automated sound recording devices that pick up bird calls and songs as they migrate overhead are providing useful data where visual monitoring is simply not possible.

These remote monitoring systems can operate for long periods with relatively little human intervention, building up a picture of migration activity over many nights, seasons, and even years. They offer researchers a way to monitor birds at a scale that would be extremely difficult to achieve with conventional field observations. This technology could thus strengthen monitoring, as habitats and migration routes respond to rising temperatures, changing rainfall, and land development. More accurate forecasts will help determine which habitats require greater protection and inform policy to ensure migratory bird conservation remains central to climate adaptation strategies.

Musale, P.P. and Sonawani, S.S. (2026) ‘Advancements and challenges in bird migration models: a comprehensive survey’, Int. J. Global Environmental Issues, Vol. 25, No. 1, pp.1–26.

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Research pick: Masking for a friend - "Fusion of periocular and forehead features for masked face recognition"

A face-recognition system that can see who you are even if you're wearing a face mask covering nose and mouth is discussed in the International Journal of Computational Vision and Robotics. The new system uses biometrics from around the eyes and forehead.

The research addresses a weakness in face recognition as a technology that was exposed during the pandemic. During that period when masks were often compulsory, their use caused conventional face-recognition systems to reject some authorised users. Unlike iris recognition, which can require specialised near-infrared imaging and controlled conditions, periocular recognition can operate with ordinary visible-light cameras.

The team has combined several types of visual information. First, a deep-learning model extracts features from around the eyes. Secondly, two image-processing techniques, local binary patterns and histograms of orientated gradients, analyse the person's forehead. The approach then combines the data to identify or verify an individual with an accuracy up to about 96 per cent in tests on one database but rather less on other testbeds.

Given that, the approach might be used as an initial screening step rather than as definitive proof of identity. A facial match could prompt further authentication with a second factor such as a password, PIN or security token. However, the team explains that they should be able to add other feature recognition into the same system, ears, face shape or profile, and those should improve performance significantly.

Agarwal, D. and Bansal, A. (2026) 'Fusion of periocular and forehead features for masked face recognition', Int. J. Computational Vision and Robotics, Vol. 17, No. 2, pp.133-158.

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