- Construction and application effect analysis of engineering education knowledge graph based on graph convolutional network
- Evaluation of mechanical engineering classroom teaching effectiveness based on improved MTCNN algorithm
- Intelligent English translation scoring method based on multi-angle semantic feature calculation model
- Dynamic scene motion target segmentation method for physical education
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- Campus network public opinion monitoring method based on emotional feature extraction and classification
- Automatic scoring algorithm for English essays based on topic granularity segmentation and feature extraction
- Immersive learning path design of mixed reality technology in business English education
- Teaching content generation and semantic information extraction for art and design courses targeting AIGC
- Virtual teaching laboratory based on cloud computing and improved WLC algorithm
10 July 2026
Free Open Access special issue on "Intelligent Learning Ecosystems: AI, Metaverse and Emerging Technologies for Continuing Engineering Education – Part 1" published by International Journal of Continuing Engineering Education and Life-Long Learning
Click and make-up
A study of traditional cosmetics retailers in China’s Guangdong province suggests that digital skills alone are not enough to improve long-term business performance. The study, published in the International Journal of Business Information Systems, suggests that value depends on whether traditional companies can use digital skills to become more resilient and innovative.
The researchers surveyed some 424 retailers. They identified three factors that affected performance improvements: mobile marketing, artificial intelligence (AI) capability, and future-orientated managerial skills. These factors were all associated with better organisational resilience. They add that this greater resilience led to increased sustainability both directly and by improving innovation capability.
The findings address a growing challenge for traditional retailers in China, and perhaps elsewhere. Guangdong produces almost half of China’s cosmetics. However, smaller “bricks-and-mortar” businesses face mounting competition from digital-first brands that are changing consumer habits. They also now have to deal with tighter regulatory requirements.
The researchers argue that resilience and innovation bridge digital resources and sustainable performance. This supports two established management theories. The first, the resource-based view, which treats valuable organisational assets as a source of competitive advantage. Secondly, dynamic capabilities theory, which focuses on how firms adapt those resources to changing conditions.
They recommend that business owners invest in accessible AI tools, mobile customer engagement, and leadership development. Conversely, they encourage policymakers to expand programmes that strengthen digital skills among these kinds of small and medium-sized enterprises.
Wang, J. and Rattanapun, S. (2026) ‘Digital and managerial capabilities, resilience, and innovation for the sustainability of traditional cosmetic businesses in China’, Int. J. Business Information Systems, Vol. 52, No. 5, pp.1–20.
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Free sample articles newly available from International Journal of Hospitality and Event Management
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Free Open Access issue published by International Journal of Information and Communication Technology
- A deep knowledge reasoning graph for graduate skill requirements
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Prof. Khaled Hussainey appointed as new Editor in Chief of International Journal of Accounting, Auditing and Performance Evaluation
9 July 2026
Research pick: Pumping hash cash, saves on gas, gas, gas - "Benchmarking gas-saving patterns in AI-generated DeFi smart contract"
Researchers have developed a benchmarking framework to assess whether artificial intelligence (AI) can generate decentralised finance (DeFi) smart contracts that are efficient and cost-effective, lowering computational costs, known jargonistically as “gas”. The work might address a key problem seen in blockchain-based financial systems.
Decentralised finance (DeFi) is a blockchain-based financial system that provides services such as lending, trading, and asset management without the need for conventional intermediaries such as banks. It uses smart contracts, which are self-executing programs that automatically enforce agreed rules, to allow financial applications to operate on decentralised networks. There is a computational cost associated with transactions, the gas. Reducing gas consumption is the key to lowering costs for users.
The study in the International Journal of Agile Systems and Management looked at Code Llama and Code Llama–Python. These two large language models (LLMs) can generate computer code across three DeFi applications: digital tokens, tokenised vaults, and flash loans.
Rather than comparing AI directly with human developers, the researchers examined gas-saving patterns in AI-generated contracts and created a benchmark that can be applied to both human- and machine-produced code. The results showed that improving gas efficiency is not a simple process, with different contract types requiring different optimisation approaches.
The researchers suggest that AI-assisted contract development could reduce development time, improve accessibility for non-specialists, and help smaller projects build decentralised applications. However, further work is needed to reduce “gas” costs.
Pratama, A.N.W. and Wicaksana, A. (2026) ‘Benchmarking gas-saving patterns in AI-generated DeFi smart contract’, Int. J. Agile Systems and Management, Vol. 19, No. 5, pp.1–26.
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New Open Access article available: "Large language models for vulnerability detection: a multi-use case comparative study"
The following International Journal of Applied Cryptography article, "Large language models for vulnerability detection: a multi-use case comparative study", is freely available for download as an open access article.
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Free sample articles newly available from African Journal of Economic and Sustainable Development
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New Open Access article available: "Supervisor social support and disability inclusion: examining mediation and moderation in employee performance"
The following International Journal of Business Innovation and Research article, "Supervisor social support and disability inclusion: examining mediation and moderation in employee performance", is freely available for download as an open access article.
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8 July 2026
New Open Access article available: "An adaptive variable frequency control method for motor speed based on PLC"
The following International Journal of Internet Manufacturing and Services article, "An adaptive variable frequency control method for motor speed based on PLC", is freely available for download as an open access article.
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Research pick: On the money - "A financial data forecasting and optimisation model combining LSTM and convolutional neural networks"
A hybrid artificial intelligence model that combines two well-established deep learning techniques has improved the accuracy of financial market forecasts across major stock indices and so-called cryptocurrency, according to work in the International Journal of Reasoning-based Intelligent Systems.
The researchers designed the model, CLSTM-HN, to address a long-standing problem in financial forecasting. That is to balance the detection of short-term market movements with recognition of longer-term trends. The researchers tested the system on publicly available data and achieved a forecasting error lower by 15 to 20 per cent compared with conventional long short-term memory (LSTM) models. They also saw an improvement in the accuracy of predicting whether prices would rise or fall by 10 to 14 per cent.
Financial markets are difficult to predict because prices are volatile, noisy and subject to sudden structural shifts. Traditional statistical approaches often rely on assumptions about market behaviour that break down during periods of instability.
The new system combines a convolutional neural network (CNN), which identifies local patterns within data, with an LSTM network, which retains information over long sequences. An adaptive alignment mechanism converts CNN outputs into a form the LSTM can process more effectively, while the training objective rewards both numerical accuracy and correct prediction of market direction.
Wang, M. and Wu, Y. (2026) ‘A financial data forecasting and optimisation model combining LSTM and convolutional neural networks’, Int. J. Reasoning-based Intelligent Systems, Vol. 18, No. 17, pp.83–99.
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Free sample articles newly available from International Journal of Critical Accounting
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Free Open Access issue published by International Journal of Electronic Marketing and Retailing
- The role of scarcity cues and consumer attitudes in driving compulsive buying: an S-O-R analysis of flash sales in e-commerce
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New Open Access article available: "Interpersonal relationships and career development competencies: a case study of the dynamic self-ball digital game"
The following International Journal of Innovation and Learning article, "Interpersonal relationships and career development competencies: a case study of the dynamic self-ball digital game", is freely available for download as an open access article.
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7 July 2026
New Open Access article available: "Learning under the inventory problem of economic order quantity: a behavioural study"
The following International Journal of Inventory Research article, "Learning under the inventory problem of economic order quantity: a behavioural study", is freely available for download as an open access article.
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Research pick: You can tell me by the way I walk - "Dual-stream spatiotemporal fusion with dynamic feature mapping for gait-based identity recognition"
Artificial Intelligence (AI) can identify people by the way they walk. The technology focuses on how a person’s joints move, rather than on body shape alone, and could improve long-distance identity verification for security and law enforcement.
Writing in the International Journal of Reasoning-based Intelligent Systems, the team describes the SKDMap-Net system, which analyses a person’s gait using estimated body keypoints from video input. The system calculates joint positions, angles, and angular velocity and acceleration to capture the distinctive features of an individual’s gait. It copes with the effects of different types of clothing, camera angle, and even partial obstruction.
The model processes body position and movement information separately before combining them. It also uses an attention mechanism, a machine learning technique that assigns greater importance to different body parts depending on the scene, such as arm movements if the legs are obscured.
In tests on three public gait-recognition datasets, the system outperformed existing approaches. The approach could make gait recognition more reliable and at the same time reduce the amount of personal visual information that must be processed.
Quan, B. and Zhang, B. (2026) ‘Dual-stream spatiotemporal fusion with dynamic feature mapping for gait-based identity recognition’, Int. J. Reasoning-based Intelligent Systems, Vol. 18, No. 17, pp.67–82.
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Free sample articles newly available from International Journal of Advanced Intelligence Paradigms
- Document summarisation using recurrent neural network
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Free Open Access issue published by International Journal of Reasoning-based Intelligent Systems
- Automated assessment of mental health integrating emojis and BERT
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6 July 2026
Research pick: Brand attachment blunts consumer risk perception - "When negative news fails to deter: the emotional shielding effect of brand attachment on perceived risk"
Strong emotional attachment to a brand may help explain why some consumers remain loyal even in the wake of negative publicity, according to research in the International Journal of Business and Emerging Markets.
The team analysed survey responses from 189 consumers and found that trust increased purchase intentions while reducing perceived risk. Perceived risk is the likelihood that buying a product could lead to financial, safety or other problems. However, emotional attachment to the brand affects how these factors interact. Those consumers with a weaker attachment tended to follow a conventional pattern. In this case, greater trust reduced perceived risk and supported purchase decisions. Among consumers with a stronger brand attachment, their emotional commitment led them to be less influenced by risk assessments.
The researchers describe this as an emotional shielding effect. The brand is so linked to the consumer’s identity that negative information about the brand carries less weight than for those people where the emotional ties don’t shape their decision-making and they are more rational about their purchasing choices.
The findings are based on a cross-sectional survey, which means they reveal a statistical association rather than a direct cause and effect. The survey was associated with a particular vehicle brand and its customers in China.
The work highlights a shift in marketing theory. As social media accelerates the spread of bad news of product failures, data breaches, and corporate controversies, companies must not view their customer relationships as being based on more than trust alone. Emotional attachment, the study suggests, can shape how consumers interpret negative information and whether they remain loyal. This could guide marketing practice.
Xue, X., Zhang, Y. and Zhang, Q. (2026) ‘When negative news fails to deter: the emotional shielding effect of brand attachment on perceived risk’, Int. J. Business and Emerging Markets, Vol. 18, No. 8, pp. 1–29.
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3 July 2026
Research pick: Speak up! Closing the cultural gap in education - "Power distance and intercultural communication in higher education: a three-pathway systematic review"
A systematic review of research on intercultural communication in higher education finds that cultural “power distance”, which is the extent to which people accept unequal authority, continues to shape who speaks, who is heard, and how knowledge is shared in multicultural classrooms.
The review, published in the International Journal of Knowledge and Learning, used a structured method for transparent evidence selection and thematic coding to identify patterns across the relevant literature. In their analysis, the researchers considered three communication pathways: student-to-student, student-to-teacher, and teacher-to-student interactions.
Student-to-student exchanges were found to most consistently support empathy and intercultural learning. However, they did find that language barriers and stereotypes often limited participation. Student-to-teacher communication emerged as the least explored pathway in the literature. It was frequently constrained by hesitation to challenge authority or fear of negative evaluation. Teacher-to-student interaction remained largely shaped by traditional transmissive teaching, where information flows primarily from lecturer to student. However, participatory teaching methods and digital tools were reported to have reduced problems with hierarchy in some contexts.
The researchers suggest that communication inequalities are not simply interpersonal but embedded in institutional structures that regulate participation and legitimacy in academic dialogue. They suggest that a new framework might connect previously fragmented research and allow new insights to be found to guide education and improve learning opportunities in globalised universities.
MenjÃvar, C.H.H. and Mayorga, C.A.E. (2026) ‘Power distance and intercultural communication in higher education: a three-pathway systematic review’, Int. J. Knowledge and Learning, Vol. 19, No. 5, pp.1–22.
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New Open Access article available: "Benchmarking gas-saving patterns in AI-generated DeFi smart contract"
The following International Journal of Agile Systems and Management article, "Benchmarking gas-saving patterns in AI-generated DeFi smart contract", is freely available for download as an open access article.
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Free Open Access issue published by International Journal of Business Information Systems
- Digital and managerial capabilities, resilience, and innovation for the sustainability of traditional cosmetic businesses in China
- Assessing brand equity through customer reviews: a naïve Bayes classifier approach
New Open Access article available: "Linking business ecosystem structure to risk perception: a network analysis of Indonesia's bamboo craft industry"
The following International Journal of Business Innovation and Research article, "Linking business ecosystem structure to risk perception: a network analysis of Indonesia's bamboo craft industry", is freely available for download as an open access article.
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Free Open Access issue published by International Journal of Information and Communication Technology
- 3D visual generation system based on the fusion of multi-view geometry reconstruction and deep learning
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2 July 2026
Free Open Access issue published by International Journal of Information and Communication Technology
- Process control of financial informatisation in industrial enterprises based on data mining and RPA technology
- Urban spatial morphology evolution mechanism and resilience assessment based on multi-source data fusion
- Transformer-based cross-cultural intelligent translation system for international communication
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Research pick: AI design for life - "Forms and innovative applications of fine arts factors in the design of literary and artistic products"
Researchers have developed an artificial intelligence (AI) system that evaluates the visual appeal of literary and artistic product designs by mimicking how people naturally direct their attention across an image, a step that could help designers create products that better match consumer preferences. The work was published in the International Journal of Engineering Systems Modelling and Simulation.
The researchers suggest that existing image-aesthetics systems focus too much on isolated visual features while overlooking visual saliency. Visual saliency is the idea that parts of an image are instinctively more attractive to human attention. Additionally, those earlier models ignore composition, the arrangement of visual elements such as lines, shapes, and background within an image.
The new algorithmic method combines two approaches. The first analyses edge patterns to capture the structure and balance of a design. The second uses weakly supervised learning, a machine-learning technique that learns from limited labelled examples, and an attention mechanism, which enables the model to prioritise the most important parts of an image during analysis.
Tests on two widely used image-aesthetics datasets found that the approach outperformed established deep-learning models. Having built the system on the EfficientNet architecture that also achieved a favourable balance between accuracy, speed, and computing cost.
The team suggests that the method could provide designers with measurable guidance on how changes to composition or focal points affect perceived quality. They also suggest it could help preserve cultural identity in product design by incorporating aesthetic principles rooted in different artistic traditions, rather than relying on imitation of dominant international styles.
Yu, X. (2026) ‘Forms and innovative applications of fine arts factors in the design of literary and artistic products’, Int. J. Engineering Systems Modelling and Simulation, Vol. 17, No. 7, pp.1–11.
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New Open Access article available: "Digital marketing, customer engagement, supply chain agility, and flexible logistics as capability drivers of dynamic marketing channel performance: an operations management perspective"
The following International Journal of Services and Operations Management article, "Digital marketing, customer engagement, supply chain agility, and flexible logistics as capability drivers of dynamic marketing channel performance: an operations management perspective", is freely available for download as an open access article.
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New Open Access article available: "Research on intelligent clothing design integrating visual communication and embedded system - taking the blind safety clothing as an example"
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