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.

• Recurrent neural network-based analysis of influencing factors on sports event communication effectiveness from the intelligent media perspective
• Dynamic optimisation algorithm for online learning intervention based on cognitive-emotional multimodal fusion
• Dynamic optimisation of visitor diversion in smart scenic areas using deep reinforcement learning
• Large language model-driven student career knowledge graph and interpretable adaptive reasoning
• A big data-driven personalised learning framework for education with adaptive content delivery

What comes around, comes around

A lack of trained workers may be one of the biggest obstacles to adopting circular economy practices, according to a survey of more than 100 industry experts involved in sustainability initiatives published in the International Journal of Product Lifecycle Management.

The study found that companies face not only technological and financial challenges, but also skills shortages among their staff. The researchers say this has implications for education providers as businesses seek workers capable of managing environmental and digital transformation.

The concept of the circular economy aims to keep products and materials in use for longer through repair, reuse, remanufacturing, and recycling. This ultimately reduces waste and resource consumption. Increasingly, these activities rely on fairly novel technologies, such as advanced data analysis, internet of things devices, and even artificial intelligence (AI). These all feed into “circular” product design and product lifecycle management.

The findings highlight the demands of a shift towards greener business models in parallel with greater digitalisation. The researchers argue this requires teams combining technical expertise with communication, negotiation, and strategic decision-making skills. As such, universities and vocational training providers need to align their programmes more closely with labour market needs to close the skills gap.

Trevisan, A.H., Acerbi, F., Pellucchi, I., Dukovska-Popovska, I., Mossa, G., Terzi, S. and Sassanelli, C. (2026) ‘A survey on skills and education needs for the industrial circular economy transition’, Int. J. Product Lifecycle Management, Vol. 16, No. 2, pp.218–251.

New Open Access article available: "Green procurement in practice: how buyer-supplier interaction differs across product categories"

The following International Journal of Procurement Management article, "Green procurement in practice: how buyer-supplier interaction differs across product categories", 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: "Power distance and intercultural communication in higher education: a three-pathway systematic review"

The following International Journal of Knowledge and Learning article, "Power distance and intercultural communication in higher education: a three-pathway systematic review", 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.

• Intelligent assessment and teaching optimisation of college Russian translation based on transformer multimodal representation learning
• Adaptive crawling strategies and quality-aware cleansing for Korean teaching resources
• Keyword association mining and topic evolution analysis algorithm for knowledge graph in the energy field
• Deep learning-based multimodal vocal emotion recognition
• A multimodal generative AI dialogue system for real-time intervention in English learning anxiety

Research pick: Integration, the key to computational thinking - "Unlocking computational thinking: immersive technologies for solving complex problems"

Training in computational thinking can improve a student’s ability to tackle complex problems, according to research in the International Journal of Technology Enhanced Learning, which examined both student perception of their own skills and their demonstrated performance. The findings come at a time when higher education faces increased pressure to equip students with transferable skills for the changing workplace.

Computational thinking is a structured approach to problem-solving that involves breaking problems into smaller parts, identifying patterns, focusing on essential information through abstraction, and designing step-by-step procedures known as algorithms to find a solution. Although often associated with computer science, the researchers argue that these skills are relevant across all disciplines. Previous research has linked computational thinking to critical thinking, creativity and innovation.

The study found that participants improved their ability to identify patterns, break down problems, and construct logical solutions. Students from one institution initially outperformed their peers, but with training, those differences were largely eliminated, the team found. In addition, improvements in abstraction, pattern recognition, and algorithm design appeared to reinforce each other. This finding supports the view that these skills develop most effectively when taught together as part of an overarching approach to problem-solving.

George-Reyes, C.E., Oliva-Córdova, L.M. and Bustamante-Ruiz, S.P. (2026) ‘Unlocking computational thinking: immersive technologies for solving complex problems’, Int. J. Technology Enhanced Learning, Vol. 18, No. 5, pp.1–24.

Free sample articles newly available from International Journal of Vehicle Noise and Vibration

The following sample articles from the International Journal of Vehicle Noise and Vibration are now available here for free:

• Machine learning based progressive crack fault monitoring on spur gear using vibration analysis
• Preview control of the random response of a full car vehicle model traversing a rough road
• Assessing the efficiency of TPI-NSI and NSI-TPI in isolating the vibration of driver's seat
• Kinematic simulations and design of a steering upright for a single seater electric car
• Intelligent fault detection of spark plugs using vibration signal analysis and artificial neural networks

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 analysis of unmanned coordination path considering line crossing and various disturbance factors
• Semantic analysis-integrated LSTM neural network: a novel spelling correction approach for academic English translation
• Generative adversarial network and parametric design algorithm for public art form generation
• A sustainable community user experience generation framework integrating the generative adversarial network and visual attention model
• Real-time image/surveillance waste sorting via MatMul-free-based encoder-decoder learning structure

Research pick: Don’t let the landslide bring the power down - "Change detection framework for power facilities in disaster scenarios"

Artificial intelligence (AI) can identify landslides and other geological changes that threaten electricity transmission towers, potentially helping operators intervene before infrastructure fails, according to research in the International Journal of Power and Energy Conversion.

The researchers focused on change detection, a remote-sensing technique that compares images of the same location taken at different times to identify disturbances in the landscape. While widely used in environmental monitoring and disaster assessment, such systems have not historically worked well with landslides, because disaster datasets are limited.

The new model analyses satellite or drone images captured before and after a disaster using a twin-network architecture, in which two linked AI systems process and compare images from different periods. It also uses a visual foundation model, a large AI system pre-trained on remote-sensing imagery, to provide broader information about terrain and landscape features.

A key component of the approach is an attention-based alignment module, which allows the AI to focus on relevant information. Here, the module filters out irrelevant differences, such as seasonal vegetation changes or lighting variations, while highlighting structural changes linked to hazards.

Tests on a real disaster dataset showed the system outperformed several recent change-detection methods.

Wu, J., Tang, H., Cen, G. and Wang, K. (2026) ‘Change detection framework for power facilities in disaster scenarios’, Int. J. Power and Energy Conversion, Vol. 17, No. 5, pp.1–20.

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 case study on vision-based intelligent inspection for surface defect detection in CNC machining using YOLOv7 and transfer learning
• Zero-sample accounting standards migration framework empowered by meta-learning
• Multimodal knowledge fusion and intelligent generation model in decision support systems for energy industry
• A utility-aware scheduling model for online learning tasks based on dynamic psychological cognitive load perception
• Lightweighting and end-side deployment of multi-modal large model based on cross-modal attention distillation

Research pick: Colour feels - "Evaluating the impact of colour congruence on marketing effectiveness within Instagram campaigns"

Brands seeking attention on social media outlets, such as Instagram, may benefit from keeping the colours in their posts visually consistent, according to research in the International Journal of Mobile Communications.

The research analysed 365 responses from Instagram users. It found that they were more positively engaged with a post and its associated brand when the background colours of a post matched the main visual elements of the image. The team suggests that this effect is due to processing fluency, the ease with which people understand and interpret information.

Using a controlled experiment based on Instagram-style brand content, researchers compared posts with congruent colour schemes against those with contrasting colours. Participants exposed to the former reported stronger brand attitudes and greater intentions to revisit the brand’s Instagram page and purchase its products than those seeing the more conflicting colour schemes.

The findings suggest that colour does more than attract attention. In crowded digital environments, consumers often rely on visual cues to form rapid judgements about a brand. Consistent colour schemes appeared to reduce the mental effort required to interpret a post, allowing viewers to focus more on its message.

Chen, C-C. and Chiu, Y-P. (2026) ‘Evaluating the impact of colour congruence on marketing effectiveness within Instagram campaigns’, Int. J. Mobile Communications, Vol. 27, No. 4, pp.417–434.

New Open Access article available: "A survey on skills and education needs for the industrial circular economy transition"

The following International Journal of Product Lifecycle Management article, "A survey on skills and education needs for the industrial circular economy transition", is freely available for download as an open access article.

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

Research pick: Resetting your fingerprints - "Fingerprint template protection: cancellable biometrics"

The obvious problem with biometrics is that once someone has stolen your fingerprint or iris ID, you cannot simply reset those to block their access as you might a password. Now, research in the International Journal of Computational Vision and Robotics offers a new approach to protecting biometric authentication data so that the risk associated with this kind of irreversible identity theft can be largely avoided and give users an option to reset their fingerprints and other biometrics, as it were.

Biometric authentication systems identify individuals using physiological or behavioural characteristics, such as fingerprints, facial features, or even how they type or move a computer mouse rather than passwords or physical tokens. However, such traits are essentially fixed and so compromised data cannot simply be reset like a password. To address this, the study focuses on the idea of cancellable biometrics, a technique in which biometric data is deliberately transformed from the start so that it can be revoked and replaced if stolen, while still allowing accurate identity verification.

The proposed system combines several computational techniques to protect biometric templates. Feature extraction is performed using Speeded-Up Robust Features (SURF), a computer vision method that detects distinctive points in images. The resulting data is then processed using a Fast Fourier Transform (FFT), a mathematical tool that converts signals into frequency components. Security is further enhanced through index-of-maximum hashing, which encodes dominant features into compact representations, and a matrix-based operation used to combine vectors securely.

The team has tested their approach on standard fingerprint datasets and found it to be comparable with existing methods but stronger than some in terms of strengthening resistance to attacks, including record multiplicity attacks, where adversaries attempt to reconstruct original data by linking multiple compromised templates.

Shaikh, A.S. and Patel, V.D. (2026) ‘Fingerprint template protection: cancellable biometrics’, Int. J. Computational Vision and Robotics, Vol. 16, No. 4, pp.399–410.

New Open Access article available: "AI and linguistics give a new meaning to the concept of semantic interoperability in electronic medical records systems"

The following International Journal of Healthcare Technology and Management article, "AI and linguistics give a new meaning to the concept of semantic interoperability in electronic medical records systems", 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: "Generative adversarial networks for simulating emotional resonance in industrial product design"

The following International Journal of Simulation and Process Modelling article, "Generative adversarial networks for simulating emotional resonance in industrial product design", 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: "Simulation modelling of fashion colour harmonisation with visual transformers"

The following International Journal of Simulation and Process Modelling article, "Simulation modelling of fashion colour harmonisation with visual transformers", is freely available for download as an open access article.

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

New Scopus and Clarivate Web of Science achievements for Inderscience journals

Scopus and Clarivate have released their latest CiteScores, impact factors and citation indicators, and Inderscience's Editorial Office is pleased to announce that several Inderscience journals have increased their Scopus CiteScores, particularly the International Journal of Hydromechatronics, International Journal of Mobile Learning and Organisation and International Journal of Environment and Health.

With regard to Clarivate, the International Journal of Hydromechatronics, International Journal of Mobile Learning and Organisation, International Journal of Bio-Inspired Computation and International Journal of Managerial and Financial Accounting continue to maintain notably high impact factors, with the International of Mobile Learning and Organisation and International Journal of Hydromechatronics performing particularly well in terms of citation indicators.

CiteScores and impact factors can be found on all indexed journals' homepages. We thank and congratulate all the editors, board members, reviewers and authors who have played their part in these latest indexing achievements.

New Open Access article available: "Endoscopic ultrasonography in differential diagnostics of benign and malignant pathology of the common bile ducts utilising fuzzy mathematical technologies"

The following International Journal of Medical Engineering and Informatics article, "Endoscopic ultrasonography in differential diagnostics of benign and malignant pathology of the common bile ducts utilising fuzzy mathematical technologies", is freely available for download as an open access article.

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

Research pick: Under the radar love for brands - "Unveiling the recall power of covert advertising: a study on stealth advertising in Indian reality shows"

A study of advertising embedded in Indian reality television examines how stealth, or subliminal, advertising, affects brand recall in a media environment saturated with promotional messages. The work, published in the International Journal of Indian Culture and Business Management, looks at how audiences exposed to thousands of brand impressions daily are affected by this approach to advertising. The findings have implications for marketing departments, which are increasingly using subtle product placement to familiarise potential and known customers with brands.

The research used within-subject experiments where participants viewed 12-minute clips from five Indian reality programmes containing embedded brand appearances. Recall was measured using standardised questionnaires assessing brand memory after exposure. Across 20 brands, most achieved moderate recall through this form of advertising.

The team found that two factors most influenced brand recall: whether the placement was spoken or visual and whether it meshed with the premise or arc of the segment. The results showed that verbal references were more effective than visual placements, but higher congruity between brand and the storyline of the segment improved recall.

Perhaps paradoxically, visual prominence of a product did not affect brand recall significantly. This challenges the marketing assumption that visibility drives effectiveness. The researchers concluded that embedded advertising depends largely on more subtle cues than straightforward visibility in the segment. Product placement is on the rise across TV, streaming platforms, and in digital content. Marketing departments hoping to familiarise consumers with their products need to understand these findings to benefit the most.

Dua, G.G., Vaidya, R.D. and Bapat, G.S. (2026) ‘Unveiling the recall power of covert advertising: a study on stealth advertising in Indian reality shows’, Int. J. Indian Culture and Business Management, Vol. 38, No. 1, pp.68–93.

Free Open Access special issue on "Green Supply Chain Management: Innovations in Sustainable Business Environment and Digital Transformation – Part 2" published by International Journal of Environment and Sustainable Development

The International Journal of Environment 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.

• Evaluation on the impact of digital transformation on the economic eco-environmental benefits of enterprises under the background of sustainable development
• Coordinated development of rural green industry planning based on ecological sustainable model and the internet of things
• From smart facilities to smart services: building a new ecosystem integrating tourism and smart cities
• Environmental variable regulation and optimisation strategy in forest seedling cultivation based on reinforcement learning
• Optimisation of landscape feature intelligent recognition algorithm based on deep learning
• AI-based green ecological construction of sustainable environment
• Landscape infrastructure optimisation design based on a BIM-GIS coupling model

New Open Access article available: "Fuelling the customer experience: an exploration of service quality in fuel stations through importance-performance analysis"

The following International Journal of Business Innovation and Research article, "Fuelling the customer experience: an exploration of service quality in fuel stations through importance-performance analysis", is freely available for download as an open access article.

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

Newly announced journal: International Journal of Technology and Digital Intelligence

 

The International Journal of Technology and Digital Intelligence proposes and fosters discussion on the convergence of emerging technology ecosystems, sector-specific digital transformation and human-centred digital intelligence, examined through a practice-to-policy lens. Rather than focusing on algorithms or computational systems, IJTDI foregrounds the sociotechnical dynamics through which intelligent digital technologies reshape industries, organisations, governance frameworks and human experience. This perspective acknowledges digital intelligence as an interface between technological innovation, organisational practice and societal governance.

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.

• The stable diffusion model incorporating group feature constraints and interactive guidance, and a high-fidelity generation method for public group portraits
• Water-economic collaborative management in the Yellow River Basin by dual-channel adaptive spatio-temporal graph transformer
• Multi-feature fusion model for interactive behaviour recognition in university classrooms using convolutional neural networks and temporal attention mechanisms
• Characteristic mapping using HTTGCN in structural materials
• A multimodal adaptive deep network for emotion recognition in artistic images

Research pick: Cruise through crime prediction with AI - "Multidimensional crime prediction technique optimisation combining feature extraction and GAN"

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing approaches by combining information about where crimes occur, when they happen, and wider social patterns. They report details of the approach in the International Journal of Innovative Computing and Applications.

The model combines a graph convolutional network, which identifies relationships between locations, with a transformer, an AI architecture designed to detect patterns over time. Together, the techniques allow the system to capture both spatial and temporal trends in criminal activity. The researchers also incorporated a generative adversarial network (GAN), a system in which two AI models compete to improve performance. The GAN was enhanced using a variational autoencoder, a method that helps generate more representative data while reducing common training problems such as biased outputs and vanishing gradients, where learning slows or stops.

The system integrates several machine-learning techniques to analyse complex datasets that traditional methods often struggle to process. In tests on historical data from several US cities, including Los Angeles and Seattle, the model achieved an accuracy rate of 86.3 per cent when predicting robberies. The strongest competing systems had an accuracy of 83.2 per cent. The new system also gave strong results across other crime categories.

The researchers suggest that accurate forecasting could help law enforcement allocate resources more effectively and identify areas at higher risk of crime. However, there are limitations. The system was less accurate in areas with sparse crime data and struggled to make predictions in locations with little or no historical information. Future work will focus on adapting the model to such environments through transfer learning, which will allow knowledge gained in one setting to be applied to another.

Xie, M. (2026) ‘Multidimensional crime prediction technique optimisation combining feature extraction and GAN’, Int. J. Innovative Computing and Applications, Vol. 15, No. 5, pp.289–299.

New Open Access article available: "Quantifying wall effects on spherical particle settling with the Lattice Boltzmann method"

The following Progress in Computational Fluid Dynamics, An International Journal article, "Quantifying wall effects on spherical particle settling with the Lattice Boltzmann method", is freely available for download as an open access article.

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

Free Open Access special issue on "Exploring AI: Methods and Applications for Data Mining – Part 1" 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.

• Improved multi-objective quantum genetic algorithm for low-carbon economic dispatch in power grids
• Optimisation of nursing human resources allocation in large hospitals based on improved particle swarm optimisation algorithm
• Study on fault diagnosis and recovery for digital distribution networks: ITOT fusion
• Automatic correction of subjective sentence similarity questions based on text image recognition
• Research on personalised recommendation of tourist attractions based on improved collaborative filtering algorithm
• Research on fuzzy clustering of ideological and political MOOC resources under the background of 'Internet plus'
• A colour restoration method for multi-texture oil painting images based on colour transfer
• An operation status prediction of transformer calibration instrument using PSO-attention-LSTM algorithm
• Automatic classification and mining algorithm for massive big data based on machine learning
• An identification method of enterprise financial information transparency based on blockchain
• An optimisation of power system load forecasting driven by deep learning model

New Open Access article available: "Classroom student emotion recognition using an improved segmentation clustering and multi-feature fusion emotion recognition algorithm"

The following International Journal of Continuing Engineering Education and Life-Long Learning article, "Classroom student emotion recognition using an improved segmentation clustering and multi-feature fusion emotion recognition algorithm", is freely available for download as an open access article.

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