Automating stereoscopic advertising optimisation

A computer-based method for evaluating and improving print advertisements by modelling how human binocular vision responds to images is discussed in the International Journal of Business Intelligence and Data Mining.

The researchers have combined three visual measures: a Gabor energy response, which captures patterns and edges detected by the visual system; a saliency map, which indicates areas likely to attract attention; and a disparity matrix, which measures differences between the views received by each eye and helps represent depth. Using these measures, the system can then generate an intermediate view between left- and right-eye images. It then extracts both global and local visual features and combines them with conventional single-eye features. The final assessment then drives automated improvements, including image segmentation, colour adjustment, and analysis of edge roughness to produce a better image. The process can be repeated as an evaluation-optimisation-re-evaluation loop.

Tests on 1200 samples found that visual-attractiveness assessment maintained accuracy above 90 per cent. After optimisation, subject saliency was raised and visual consistency improved by an average of 17.3 per cent and stereoscopic perception by 15.8 per cent. The system generally converged within three to five loops, or iterations.

The work addresses a broader problem in advertising: conventional design evaluation often depends on subjective judgements or isolated image metrics. By incorporating binocular cues, the visual difference between what each eye sees, the method can bring computer-based assessment closer to how people actually experience an advertisement.

Li, J., Wang, F. and Chen, H. (2026) ‘Evaluation and optimisation method for graphic advertising design effectiveness based on binocular vision’, Int. J. Business Intelligence and Data Mining, Vol. 28, No. 10, pp.103–119.

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Spark flies to organise text

A distributed computing framework can group large volumes of English text more accurately and efficiently than older methods. The system has the potential to support faster analysis across education, government, and business, according to research published in the International Journal of Intelligent Information and Database Systems, allowing blocks of related text to be automatically sorted and grouped together, or clustered.

The work addresses a practical problem in digital transformation: much of the information generated by organisations is unstructured text, whose meaning can vary with context. Conventional clustering methods are often slow or produce inconsistent groupings when confronted with large, high-dimensional datasets.

The researchers used Apache Spark, a platform for processing data across multiple computers, with an improved K-means algorithm. K-means is a method of grouping data into clusters according to similarities. The researchers modified this tool by using density peaks and maximum-minimum criteria to select better starting points for the clusters, rather than relying on random initialisation.

In tests on multiple datasets they found that the new approach improved clustering accuracy by more than 10 per cent when compared with conventional K-means approaches. The system was also stable even when they ramped up the volume of data to be processed. Indeed, they could improve parallel performance by additional computing nodes.

The framework could help organisations organise and extract information from growing bodies of English-language documents more efficiently, while providing a more consistent basis for subsequent data analysis and decision-making.

Yao, X. (2026) ‘English digital transformation algorithm for distributed big data based on Spark’, Int. J. Intelligent Information and Database Systems, Vol. 18, No. 8, pp.1–28.

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A whole new word

Virtual reality (VR) could be a new tool in helping students with dyslexia to learn English vocabulary more effectively than conventional instruction alone, according to a pilot study involving 30 learners published in the International Journal of Innovation and Learning. Dyslexia is a learning disability that primarily affects reading and related language skills.

VR creates an immersive computer-generated environment with which users can interact. The research divided participants into two groups: one used a custom VR programme incorporating interactive multimedia and game-based learning, while the other received conventional teaching. The team saw higher vocabulary-test scores in the VR group than the other. Moreover, there was greater engagement and stronger conceptual understanding among the students using VR. Those students, themselves, reported improved concentration, imagination, and satisfaction with the learning process overall.

The team explains that the VR allowed learners to encounter words through images, sounds, text, and simulated real-world situations. The game-based activities in the VR encouraged repeated interaction with letters and vocabulary, which they suggest reinforced memory and contextual understanding in that group when compared to those taught using conventional methods.

Digital tools, for all the criticism they often receive in some areas, could improve teaching in special needs and perhaps address the shortfall in specialist teachers and teaching materials for many students with learning difficulties around the world, especially in resource-tight regions. The study contributes to wider efforts to make education more inclusive under the United Nations’ Sustainable Development Goal 4, which calls for equitable, quality education for all, the researchers add.

Vipahasna, P.P., Vipahasna, K., Khlaisang, J. and Numprasertchai, S. (2026) ‘Virtual reality technology to enhance English language acquisition in children with learning disabilities’, Int. J. Innovation and Learning, Vol. 40, No. 3, pp.245–260.

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New Open Access article available: "Analysis of economic diplomacy between Kazakhstan and Italy: development trends and prospect"

The following nternational Journal of Diplomacy and Economy article, "Analysis of economic diplomacy between Kazakhstan and Italy: development trends and prospect", is freely available for download as an open access article.

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

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 TPACK knowledge integration profile for university teachers based on generative AI and multimodal data
• GAN-based English metaphor identification and paraphrase generation via optimised compression
• Comparative computation of multimodal semantic representations for ideological and value orientations
• Robust multi-agent simulation modelling of the distribution of source-load asymmetric resource regulation capabilities
• Dynamic budget allocation via deep Q-networks with embedded financial risk control using VaR/CVaR metrics

New Open Access article available: "Enhancing IoT security in the post-quantum era: a hybrid approach to protection from impersonation attacks"

The following International Journal of Internet Technology and Secured Transactions article, "Enhancing IoT security in the post-quantum era: a hybrid approach to protection from impersonation attacks", is freely available for download as an open access article.

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

Associate Prof. Prof. Wan Wei appointed as new Editor in Chief of International Journal of Cultural Management

Associate Prof. Wan Wei from Arkansas Tech University in the USA has been appointed to take over editorship of the International Journal of Cultural Management. The journal's previous Editor in Chief, Prof. Wei Song, will take the position of Executive Editor, with the two editors exchanging posts every two years.

Associate Prof. Wan Wei offered the following statement:

"It is my great pleasure and honor to serve as the new Editor in Chief of the International Journal of Cultural Management (IJCultM). I am honoured to lead a highly accomplished and diverse editorial team of researchers representing regions across Asia, Africa, Europe, North America and South America. Our team brings together established scholars and emerging researchers with diverse expertise and perspectives, providing a strong and inclusive foundation for the continued development of the journal. I am excited to work with such a talented and committed group as we begin this new chapter for IJCultM. We are committed to strengthening IJCultM as an international platform for rigorous, innovative and interdisciplinary research in the fields of culture and cultural management.

IJCultM provides an international and interdisciplinary forum for research on cultural management and related areas. We welcome high-quality theoretical and empirical research that advances our understanding of the management, economics, policy and development of cultural organisations.

The journal welcomes contributions from scholars and researchers across academia, business and the public sector, with the aim of fostering meaningful interdisciplinary dialogue on the management, development and use of culture. We encourage research drawing on diverse disciplinary and methodological perspectives, including economics, finance and sociology. The journal also welcomes critical reviews.

I invite researchers and scholars from around the world to submit their original work to IJCultM and to join us in advancing research and dialogue in this important and evolving field. For more information, please visit http://www.inderscience.com/ijcultm or contact me at ijcultm@atu.edu for any publication-related queries.

I look forward to working with our international scholarly community and to welcoming your contributions to the journal."

Research pick: A little brand love and affection - "The emotional connection between customer happiness and brand love on customer loyalty"

A study of more than 800 fast-food customers suggests that loyalty to a brand is shaped not only by satisfaction with the product or service but also by the customers’ emotional experiences. The study reported in the International Journal of Internet Marketing and Advertising focused on fast-food consumers in Peru but could have implications for fast-food brands in other emerging markets.

The study was based on responses collected through an online questionnaire and analysed with a statistical technique known as structural equation modelling, which tests the relationships between multiple variables. The researchers found that perceived service quality was perhaps quite obviously associated with the degree of satisfaction with a brand. However, satisfaction, in turn, was linked to the customer’s happiness and their level of brand love and thus to brand loyalty. The research distinguishes between customer satisfaction, which considers whether expectations have been met, and happiness, which reflects a broader positive emotional response to the customer’s experience with the brand.

The findings add to a relatively small body of work that has examined happiness and brand love together and has implications for this particular emerging market where cultural factors may influence how customers assess services and develop relationships with brands.

For fast-food businesses, the results suggest that improving service alone may be insufficient. Managers must also focus on experiences that generate positive emotions, potentially strengthening customers’ attachment to a brand and their willingness to remain loyal.

Pipoli de Azambuja, G.M., Rodríguez Peña, G.A. and Tarazona Vargas, E.G. (2026) ‘The emotional connection between customer happiness and brand love on customer loyalty’, Int. J. Internet Marketing and Advertising, Vol. 25, No. 2, pp.123–148.

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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.

• Financial risk monitoring based on corporate ESG performance from the perspective of sustainable development
• A secure and scalable blockchain framework for enhancing transaction transparency and operational efficiency in banking systems
• Automatic graphic-text composition for graphic design using diffusion models and layout optimisation
• Deep learning-driven modelling of acoustic logging signals and identification of complex reservoir fractures
• UrbanGreen-LiteFormer: a lightweight vision model for disease and pest recognition of urban landscape plants in complex urban green-space environments

New Open Access article available: "Technological integration challenges in hybrid sheet metal manufacturing systems"

The following International Journal of Machining and Machinability of Materials article, "Technological integration challenges in hybrid sheet metal manufacturing systems", 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 "Machine Learning for Cloud-Edge Emerging Network Architectures: Part 2" published by International Journal of Computer Applications in Technology

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

• Supply chain demand forecasting and low-altitude economic risks based on machine learning and artificial intelligence
• Ecological management algorithm of fresh supply chain information under artificial intelligence and blockchain architecture
• Simulation model of marine biological population based on multi-agent comfort drive
• CISAA: a collective intelligence-based optimisation framework for low-altitude airspace resource allocation and engineering management
• Application of information optics experimental methods in optical sensors for wearable devices
• Sports biomechanical performance analysis algorithm and geometric parameter equation based on reinforcement learning
• From physical isolation to disaster recovery communication guarantee based on software-defined perimeter (SDP)
• Automatic recognition system of athletic injury images based on deep learning

New Open Access article available: "Operator perspectives and attitudes to evolving tasks and tools in power grid operations"

The following International Journal of Human Factors and Ergonomics article, "Operator perspectives and attitudes to evolving tasks and tools in power grid operations", is freely available for download as an open access article.

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

Research pick: AI pose estimation is in vogue - "Design of lightweight human pose estimation network for rehabilitation training"

A lightweight artificial-intelligence (AI) system designed to assess rehabilitation exercises in real time could make computer-assisted therapy more practical on low-powered devices, according to research in the International Journal of Business Intelligence and Data Mining.

The researchers developed RMPE Tiny, a human-pose estimation network tailored to rehabilitation. Pose estimation is a computer-vision technique that identifies key points on the body, such as the shoulders, knees and ankles, from images or video. These points can then be used to measure movement, including range, symmetry, and coordination.

The challenge for such systems is that precise pose estimation usually needs a lot of computing power; this limits them to specialist equipment rather than allowing them to be used on tablets or simple, embedded monitoring systems. RMPE Tiny addresses this through several modifications intended to reduce computational demands without substantially compromising accuracy.

The system uses laser triangulation to improve image acquisition and map 3D coordinates onto a 2D image. In tests, it achieved more than 96 per cent overall pose-estimation accuracy, with most samples approaching or exceeding 98 per cent. The system might ultimately be used to support rehabilitation systems that provide immediate feedback outside clinical settings.

Yang, Q. and Zhang, G. (2026) ‘Design of lightweight human pose estimation network for rehabilitation training’, Int. J. Business Intelligence and Data Mining, Vol. 28, No. 10, pp.85–102.

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Free sample articles newly available from International Journal of Environmental Technology and Management

The following sample articles from the International Journal of Environmental Technology and Management are now available here for free:

• Plastic waste recycling product design based on sustainable concepts: study of improvement, developments, and innovations in Kampala City, Uganda
• Preparation and characterisation of aloe vera/nanocellulose/bentonite biocomposite scaffold to remove arsenic from wastewater
• Combination of activated carbon and thermal energy system for the clarification of surface water at Bousellem
• Treated municipal wastewater for irrigation: a case study from Misurata City, Libya
• Study on comprehensive evaluation of environmental pollution in tourist attractions based on FCM algorithm
• Carbon flow tracking methods for power systems in energy conservation and emission reduction environments
• Teak trees computational modelling to measure environmental contribution using functional-structural plant modelling
• Hydraulic modelling and flood hazard zoning in rivers of the urban basin of Sulaymaniyah using 2D modelling with HEC-RAS and GIS
• Carbon emission calculation and control of agricultural product supply chain under the background of energy conservation and emission reduction
• Peak carbon emission prediction of expressway toll stations using GRA-LSTM under the dual carbon background
• Research on influencing factors of regional tourism carbon emission based on LMDI model
• A positive and negative balance accounting method for carbon emissions in parks based on K-nearest neighbour clustering algorithm
• Evaluation method of landscape ecological quality based on remote sensing ecological index
• Automatic classification method of construction waste based on machine vision
• Short-term load prediction of electric vehicle charging stations based on conditional generative adversarial networks

Research pick: Clean up on the roof - "Intelligent autopilot drone robot for de-mossing ramped roofs"

Drones have many uses in surveillance and surveying, industrial inspection, aerial photography and filmmaking, package delivery, even dynamic light-shows. Their fundamental ability to carry cameras, sensors and other equipment opened up these diverse applications. Now, research in the International Journal of Intelligent Machines and Robotics has explored another: the safe removal of moss and lichen from sloping roofs, an otherwise hazardous job for a worker.

The team used an Arduino-based autopilot system for a quadcopter-type drone capable of operating over horizontal or sloping roofs. It follows a programmed zig-zag, or “staircase”, trajectory designed to cover the roof systematically while avoiding obstacles.

Arduino is a low-cost, programmable electronics platform commonly used to control robots. The proposed system combines it with motors, batteries, electronic speed controllers (ESCs), which regulate motor power, and a flight controller that manages the aircraft’s movement and stability. The researchers point out that this seemingly mundane demonstration opens up possibilities for such machines to be used in other applications that otherwise involve risk to workers.

The prototype remains a development platform. Future work identified by the researchers includes improved obstacle handling and machine learning to better identify patterns from video input to allow the drone to adapt to unexpected situations.

Sanyal, S. (2026) ‘Intelligent autopilot drone robot for de-mossing ramped roofs’, Int. J. Intelligent Machines and Robotics, Vol. 2, No. 1, pp.22–44.

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Free sample articles newly available from International Journal of Human Resources Development and Management

The following sample articles from the International Journal of Human Resources Development and Management are now available here for free:

• The impact of positive organisational behaviour on employee engagement and performance
• The future of recruitment: a mixed-methods scenario analysis in Germany
• Fostering alignment in the hybrid workplace: bridging the gap between employee experience and expectations
• Human resources in the era of the fourth industrial revolution: Competencies 4.0
• Empowering leadership in cognitive processes and behavioural dynamics: a thematic analysis

Free Open Access special issue on "Global Mobility Law: Rethinking the Role of Law In Movement Across Borders" published by International Journal of Migration and Border Studies

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

• Infrastructuring pathways: traversing the legal infrastructure of mobility in South America
• Authoritarian borders? Turning authoritarian international law inside-out
• Reconciling the tensions of the European deportation regime: how the law shapes compulsory mobility across borders
• Freedom of movement, sovereignty, and the Third World in postwar international law (1948-1968)
• Global commerce and global mobility law
• Citizenship as transnational mobility capital
• An international human rights law of migration? Reflections on the place of a right to immigrate

Research pick: Spotting the spoof - "A hybrid deep learning method for URL spoofing in websites"

A machine-learning system can identify fake, or “spoofed”, website addresses, according to research in the International Journal of Electronic Security and Digital Forensics. The work offers a new tool to protect users against phishing attacks, where attackers direct someone to a deceptive website to steal information such as bank logins or personal and private data.

The team combined two deep-learning techniques: a convolutional neural network (CNN), which can identify patterns in data, and a long short-term memory (LSTM) network, which can retain information about sequences in that data. This hybrid CNN-LSTM model achieved accuracy rates of almost 99 per cent on the UCL standard test dataset and almost 97 per cent on the PhishTank dataset.

The findings highlight the potential for automated AI systems in protecting people using online commerce, government services, and other activities. Phishing attacks remain particularly difficult to address as a cybercrime problem because they often simply exploit human behaviour and weaknesses rather than being a technical loophole. If a message is sufficiently convincing and a website realistic, then vulnerable or even simply distracted users might disclose sensitive information without realising they have been duped.

A system to accurately flag spoofed addresses before that happens would be invaluable. For the small percentage that it false-flags, the inconvenience would be negligible compared to what is not lost by blocking spoofed sites.

Santhosh Krishna, B.V., Vidhya, S., Krishnaveni, S. and Ashokkumar, N. (2026) ‘A hybrid deep learning method for URL spoofing in websites’, Int. J. Electronic Security and Digital Forensics, Vol. 18, No. 5, pp.524–537.

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New Open Access article available: "Informal entrepreneurship and entrepreneurial ecosystems: a systematic literature review and future research agenda"

The following International Journal of Entrepreneurship and Small Business article, "Informal entrepreneurship and entrepreneurial ecosystems: a systematic literature review and future research agenda", is freely available for download as an open access article.

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