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.

• Optimisation of English speech recognition using contrastive learning and feature reconstruction
• Impact of personalised learning system based on generative AI on students' higher-order thinking ability and reconstruction of teachers' roles
• Predicting athletes' physical condition using multimodal machine learning models
• Risk perception and traceability in higher education quality management using dynamic knowledge graphs and link prediction
• Quantum computing-driven portfolio optimisation framework for the intelligent economy

Research pick: Logical logistics - "Investigating the impact of AI and big data capabilities on supply chain performance: the mediating role of agility and resilience"

Artificial intelligence and big-data capacity might help logistics companies withstand supply-chain disruptions by making them more agile and resilient, according to research in the International Journal of Business Performance and Supply Chain Modelling. The results are based on an analysis of responses from almost 300 logistics professionals in Indonesia.

The researchers surveyed employees of logistics service providers and analysed their responses using partial least squares structural equation modelling. This statistical technique can be used to test relationships between multiple factors. The findings indicate that digital capabilities help companies detect disruptions, improve forecasting and decision-making, optimise routing, and respond more rapidly to changing conditions.

Supply chains face persistent uncertainty from geopolitical tensions, natural disasters, trade restrictions and labour disputes, regulatory changes, and energy insecurity. This study suggests that technology alone is insufficient to help companies cope, as its value depends on organisations being able to turn information and automated analysis into faster adaptation and resource reconfiguration.

The research is grounded in dynamic capabilities theory, which says that organisations need to continually identify changes, exploit opportunities, and rearrange resources as circumstances change. The survey captures one point in time and focuses on Indonesia but may well be applicable to other regions. The researchers suggest that longitudinal and cross-country studies are now needed to determine whether this is true.

Sudrajat, D., Nagari, A.L. and Apriyanto, D. (2026) ‘Investigating the impact of AI and big data capabilities on supply chain performance: the mediating role of agility and resilience’, Int. J. Business Performance and Supply Chain Modelling, Vol. 16, No. 5, pp.1–26.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

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.

• Interactive mobile English translation teaching quality evaluation model based on particle swarm optimisation-neural network
• An explainable decision intelligence framework for consumer packaging evaluation in e-commerce: a hybrid entropy-weighted grey MCDM approach
• Metaheuristic-based talent configuration optimisation for enterprises under the new quality productive forces framework
• Hierarchical cluster analysis of the deviation degree between school discipline punishment levels and judicial sentences
• Physics-informed modelling of vocal fold fatigue process using acoustic and laryngovibrography data

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 voiceprint monitoring system for wind turbine blades using SVDD and LSTM
• Identification of new quality productivity levels in agricultural digital transformation using causal inference from confounded data
• Model predictive control-based frequency regulation and photovoltaic fluctuation suppression for high-inertia asynchronous grids
• Multimodal deep neural network inference for design colour emotion quantification
• The simulation modelling and dynamic response for a dual-drive vibratory pile hammer considering soil nonlinearity

Research pick: Info binding by the light - "Experimental demonstrations of visible light communication using quantum noise for high security"

Research in the International Journal of Sensor Networks has demonstrated a visible-light communication system that uses the inherent randomness of quantum noise to make transmitted data harder for eavesdropping hackers to intercept.

The experimental system was able to transmit data at 100 megabits per second (100 mbps) and applies encryption directly at the optical, or “physical”, layer of the communication system. 100 mbps is a modest data transfer speed when compared to modern broadband networks, equivalent to mid-90s Fast Ethernet speeds. Nevertheless, this is a valid initial baseline for a research demonstration, and fast enough for a wide variety of applications.

Moreover, optical wireless of this kind is emerging as a specialised complement to Wi-Fi and fibre connections, for situations with confined coverage and abundant optical spectrum where immunity to radio interference is essential. It could thus be attractive for settings such as hospitals, aircraft, and industrial facilities.

Visible-light communication (VLC) uses rapidly modulated light, typically from LEDs, to carry digital information through an open wireless channel. The researchers can convert data into a signal with many possible light-intensity levels and use a shared secret key to determine how the data is represented. Quantum noise, the random fluctuations arising from the fundamental properties of light, is then superimposed on to the signal. When the noise is at a sufficiently high level, a third party lacking the key cannot reliably distinguish between the signal and the noise. The current approach is based on the Y-00 quantum stream cipher, a technique previously demonstrated in fibre-optic communications and extends the approach to visible-light transmission.

The work could address a particular vulnerability in VLC, that unlike data protected only by higher-level network encryption, the optical signal itself remains exposed while in transit. This kind of physical-layer protection could therefore provide an additional security mechanism for optical wireless links in environments where interception is possible.

Xiao, N., Chen, S., Chen, F. and Shi, S. (2026) ‘Experimental demonstrations of visible light communication using quantum noise for high security’, Int. J. Sensor Networks, Vol. 52, No. 1, pp.1–6.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

Free Open Access special issue on "Exploring AI: Methods and Applications for Data Mining – Part 2" published by International Journal of Business Intelligence and Data Mining

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

• DNN and BiGRU-based hierarchical attention network for intrusion detection
• Rapid planning of multimodal transport path based on improved VSRB-RRT algorithm
• A mathematical model of attribute-based encryption for mining clusters in big data
• A resource allocation method for digital online teaching platform based on classification mining
• Design of lightweight human pose estimation network for rehabilitation training
• Evaluation and optimisation method for graphic advertising design effectiveness based on binocular vision
• Research on intelligent recognition of English machine translation errors using joint contrastive learning
• Study on high jump athlete error action recognition based on dual stream CNN BiLSTM
• An intelligent recommendation method for multimodal ideological and political education resources integrating with dynamic portrait modelling

New Open Access article available: "The sensitivity of variance risk premium estimates to grid and strike fineness: simulating the Heston model with jumps"

The following International Journal of Financial Markets and Derivatives article, "The sensitivity of variance risk premium estimates to grid and strike fineness: simulating the Heston model with jumps", 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.

• A deep learning framework for sentiment-aware visual communication in digital media systems
• An optimisation model for the graphic design process based on generative AI
• Adaptation mechanism of animation short drama IP and e-commerce products based on multimodal emotion computing
• A system for generating tourism cultural symbols based on diffusion models and graph neural networks
• Deep learning-based semantic segmentation for colour language analysis: a computational framework for cinematic media

Five Inderscience journals announced as open access-only titles

We are pleased to announce that the following titles

• International Journal of Automation and Control
• International Journal of Innovation and Learning
• International Journal of Management and Enterprise Development
• International Journal of Mobile Learning and Organisation
• International Journal of Mathematical Modelling and Numerical Optimisation

are now Open Access-only journals. All accepted articles submitted from 8 September 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

Free Open Access special issue on "Achieving Carbon Neutrality from Environmental Impact Monitoring and Assessment Technologies – Part 5" published by International Journal of Environment and Pollution

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

• Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain
• Automatic completion algorithm for knowledge graphs in power market based on convolutional neural network
• Coupling coordination level and sustainable development of ecological environment and network economy based on data mining
• Calculation of carbon emission footprint of ecotourism energy driven by big data
• Research on the development of low-carbon digital economy transformation based on artificial intelligence and fuzzy synthesis algorithm
• Generation of virtual reality landscape scenes for digital urban architecture based on AI

Research pick: Emission control - "Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain"

A digital scheduling framework combining machine learning, optimisation and blockchain technology could allow carbon emissions to be reduced at lower cost in regional energy systems, according to research in the International Journal of Environment and Pollution. The system cut the marginal emission-reduction cost, the additional expense of removing one more tonne of carbon, by about 12 per cent when the carbon quota was restricted to half the system’s baseline emissions.

The new framework addresses a problem facing those managing increasingly complex regional energy networks, where electricity, heat and other sources must be coordinated while emissions are controlled. The problem being that the differences in data quality can make it difficult to assign emissions to specific sources and to then respond to rapidly changing demand.

The researchers used a machine-learning algorithm known as extreme gradient boosting, XGBoost, to identify complex relationships in the data and so forecast daily energy loads using historical consumption, electricity prices, weather, and industrial activity. The forecasts continuously update a mixed-integer linear programming (MILP) model, an optimisation method that selects decisions subject to constraints such as energy balances and carbon limits.

In addition, the framework records encrypted emissions data using a blockchain platform. Blockchain technology is perhaps more familiar as a cryptocurrency system, but it is essentially an immutable digital ledger that can be used to record data and information exchanges of all kinds. The blockchain thus provides a traceable record of emissions and assigns responsibility across the energy network.

The researchers suggest that integrating forecasting, scheduling, and verification into a single system could provide regional energy systems with a more responsive mechanism for managing emissions as carbon constraints tighten.

Liu, W. and Ma, W. (2026) ‘Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain’, Int. J. Environment and Pollution, Vol. 76, No. 8, pp.1–26.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

New Open Access article available: "Investigating the impact of AI and big data capabilities on supply chain performance: the mediating role of agility and resilience"

The following International Journal of Business Performance and Supply Chain Modelling article, "Investigating the impact of AI and big data capabilities on supply chain performance: the mediating role of agility and resilience", 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 Hydromechatronics

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

• Investigation of non-homogeneous thick-walled cylinder ceramic matrix composites for biochemical and medical innovations
• Investigation into the thermal optimisation of low eddy current structure of high-speed on/off valve considering energy consumption and dynamic characteristics
• Intelligent selection of parameters for air-floating piston based on improved multi-objective grey wolf optimisation algorithm
• Automation and synchronisation on electro-hydraulic lifting system of tunnel boring machine segment assembly
• Design and modelling of multiple-air-chamber pneumatic soft bending actuators

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.

• Digital energy data analysis and risk assessment under precision agriculture financing model
• Research on multiphase flow simulation of cave grouting diffusion coupled with phase field method and convolutional neural network
• Fine-grained classification and health assessment of urban green spaces using U-net and transfer learning
• Reinforcement learning empowered RNN: exploring personalised learning path optimisation in nursing education
• Exposure dose reconstruction-guided imaging screening of tuberculosis close contacts using IoT-based localisation

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

Research pick: The “bear” essentials in teaching economics - "Bare necessities: understanding economics from The Jungle Book"

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.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

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.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

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.

News media may use this press release as source material, in whole or in part, provided the content is not materially misrepresented. A link back to the original article is appreciated.

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.