The following International Journal of Environment and Pollution article, "Research on emergency monitoring methods for landslide disasters based on improved atmospheric correction GB-SAR and multi-source data geocoding", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Thick cloud cover can completely obscure the surface of the earth from satellite view, while thinner haze and shadows distort the image of rural and urban regions. As such, many remote sensing images for monitoring climate, crops, and urban growth are only partially usable.
Research in the International Journal of Bio-Inspired Computation offers a way for satellites to see through clouds using a hybrid artificial intelligence system. The system essentially removes clouds from the images sent back by the satellite and reconstructs the land surface beneath with greater fidelity than is possible with earlier techniques. Almost all optical satellite images are affected by clouds to some degree, so improvements in AI cloud removal could expand the reliability of high-resolution Earth observation data.
Traditional approaches have relied either on physical models of atmospheric light scattering or on image-processing techniques that compare multiple images through time or across different wavelengths of light. Those methods are useful but struggle with varying cloud thickness or large, fully obscured areas. More recent machine learning systems, in which algorithms learn patterns from large datasets, have improved results, but they need clear reference images, without them, they simply produce blurred areas where the landscape was obscured by clouds.
The new approach is a deep denoising application known as SenseNet. It treats those image pixels with clouds or haze as being structured noise that can be removed. The system uses a model inspired by nature called a hybrid Coyote Fox Optimisation algorithm, which works by modelling the social, cooperative behaviour in canines to take the input data and process it to find the optimal solution. In computational terms, it helps tune the network’s internal parameters so that training does not stall on suboptimal solutions that would otherwise confound the learning algorithm.
Compared with existing denoising approaches, the system improved signal-to-noise ratios by more than two decibels and reduced residual errors. An improvement of just 2 dB is an almost 60 per cent improvement.
By clearing the clouds away, the system can more readily delineate agricultural boundaries and map road networks and bodies of water so that phenomena such as deforestation, crop yields, and infrastructure can be viewed with more detail. In persistently cloudy regions, including much of the tropics, more reliable cloud removal could reduce data gaps, supporting climate adaptation and disaster response strategies that increasingly depend on near-real-time satellite intelligence.
Gound, R.S. and Thepade, S.D. (2026) ‘SenseNet: satellite image enhancement using optimised deep denoiser for cloud removal’, Int. J. Bio-Inspired Computation, Vol. 27, No. 1, pp.45–59.
The following International Journal of Environment and Pollution article, "Empowering sustainable growth: the transformative impact of environmental protection inspections on heavy polluters", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Environment and Pollution article, "Promoting the transformation of digital economy structure based on artificial intelligence in the low carbon economy environment", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Environment and Pollution article, "Evaluation and trend prediction of the relationship between carbon emissions, energy, and sustainable growth based on neural networks", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Economics and Business Research article, "Financial deepening and fiscal capacity: new empirical evidence from the association of Southeast Asian nations", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Economics and Business Research article, "Validating the rational and intuitive decision-making styles - RIDMS scale across nine countries", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Economics and Business Research article, "Exploring the impact of older knowledge workers' career capital on career success: with self-efficacy and job crafting as mediators and perceived organisational support as a moderator", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computer Applications in Technology article, "Anomaly detection and pattern recognition methods for high-dimensional data", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As cities build upwards to accommodate growing populations, the safety of deep excavation, the process of digging large foundation pits to anchor high-rise buildings, has become a significant challenge in the construction industry. These pits must withstand the problem of shifting of the underlying earth, changes in groundwater pressure, and the heavy machinery while remaining stable enough to protect workers and nearby structures. Failures at this stage can trigger collapses, flooding or structural damage.
Work in the International Journal of Critical Infrastructures discusses an AI (artificial intelligence) system designed to improve safety monitoring at deep foundation pit support sites. The system aims to identify abnormal behaviour, such as unsafe actions, improper equipment use, or entry in restricted zones without protective gear, in close to real time so that warnings can be sounded in a timely manner.
Construction sites have traditionally relied on manual supervision and earlier generations of automated monitoring. But these approaches often struggle to detect unsafe behaviour quickly and accurately. Many systems record high false acceptance rates, meaning they mistakenly classify dangerous actions as safe. Others process video feeds too slowly to intervene effectively in rapidly changing environments.
The new system combines several advanced AI techniques to address those weaknesses. It begins by extracting key frames from surveillance footage using the fractional Fourier transform. This is a mathematical method that analyses data across different domains. By identifying the most informative frames rather than scanning every second of video, the system reduces computational load but still retains critical information.
The system then uses a spatiotemporal graph convolutional network, a form of deep learning that analyses both space and time data. The spatial analysis examines how workers and machinery are positioned relative to one another, while the temporal analysis tracks how movements change over time. Unlike conventional image-recognition models that treat frames in isolation, this approach captures sequences of actions and interactions. This is vital for working out what is happening moment to moment on the construction site.
The final step is to use a hybrid model that combines a convolutional neural network (CNN) with a so-called long short-term memory network (LSTM). The CNN can recognise visual features such as body posture or equipment shape. The LSTM can detect patterns in sequences of data. Working together, those two tools allow the system to determine not only what is happening in a single frame, but whether a series of movements constitutes a safety violation.
In their tests on active deep excavation sites, the researchers got a minimum false acceptance rate of 2.43 per cent and a peak abnormal behaviour recognition accuracy of 99.12 per cent. Processing time was as low as 0.19 seconds per analysis cycle, allowing near real-time monitoring.
Qi, W. (2026) ‘An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings’, Int. J. Critical Infrastructures, Vol. 22, No. 7, pp.1–17.
The following International Journal of Computer Applications in Technology article, "DAFPN: a lightweight multi-objective framework for small object detection in remote sensing images", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computer Applications in Technology article, "Cloud computing based construction and empirical evaluation of the security risk early warning evaluation system of digital economy", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computer Applications in Technology article, "Pose estimation technology of electronic components based on point cloud segmentation algorithm", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Computer Applications in Technology article, "Mean-shift-based moving target tracking algorithm in complex industrial environments", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The International Journal of Computer Applications in Technology has published an Open Access special issue: "Machine Learning for Cloud-Edge Emerging Network Architectures: Part 1".
All of the issue’s papers can be downloaded via the full-text links available here.
The following International Journal of Computer Applications in Technology article, "Digital media video image data processing based on computer vision", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Reasoning-based Intelligent Systems article, "Deep learning-based virtual screening system for drug molecules", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Reasoning-based Intelligent Systems article, "Research on modified Biaffine method for Chinese semantic role labelling", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Reasoning-based Intelligent Systems article, "Identification and long-term temporal sequential change analysis of urban VOCs high-value areas based on GIS and remote sensing", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A large-scale study published in the International Journal of Business Innovation and Research has looked at what factors lead to sustained gains in the construction industry. The team looked at 226 nationally registered firms and found that operational efficiency and collaboration, long seen as the sector’s primary remedies for underperformance, are insufficient on their own to lead to sustained gains. Instead, the decisive factor is whether companies fundamentally rethink how they create, deliver, and capture value.
The research used a statistical tool known as Partial Least Squares Structural Equation Modelling to analyse information from the 226 companies and to look for any relationships between various organisational factors. The approach allowed them to look at how lean construction practices and strategic partnerships affect performance. It was also possible to discern whether business model innovation acts as a bridge between these strategies and measurable outcomes such as profitability, operational efficiency and competitive position.
Lean construction is a systematic project management approach designed to eliminate waste and maximise value throughout a project’s lifecycle. Waste includes excess materials, redundant labour, delays, reworking, and poor coordination between contractors. Unlike simple cost-cutting, lean methods emphasise continuous improvement, integrated workflows, and delivering greater value to clients.
The study confirms that those companies that adopt lean practices do tend to perform better. However, the most significant improvements did not stem solely from streamlining their processes. Instead, lean thinking proved most powerful when it also prompted broader strategic change.
That broader shift is captured in the concept of business model innovation. A business model defines how a company creates value for customers, how it delivers that value, and how it generates revenue. Innovation in this context involves reconfiguring those core elements. For example, this might include moving from one-off, project-based contracts to long-term integrated service models, adopting digital coordination platforms, redesigning revenue structures, and embedding sustainability into what the company offers to clients.
Business model innovation was found to have a strong and direct positive effect on performance. More importantly, it amplified the impact of lean construction. When lean methods were embedded within a redesigned business model, performance gains were significantly greater than when lean was treated as a stand-alone efficiency tool. The research found that partnerships boosted performance only when it allowed companies to innovate in their business models. Access to shared knowledge, resources, and trust-based relationships yielded gains only if companies used them to reconfigure how they compete and deliver value.
Arifin, J., Prabowo, H., Hamsal, M. and Elidjen, E. (2026) ‘Innovating for performance: the role of lean construction and strategic partnerships in construction firms’, Int. J. Business Innovation and Research, Vol. 39, No. 6, pp.1–25.
The following International Journal of Reasoning-based Intelligent Systems article, "Adaboost algorithm-based cost risk assessment for university laboratory construction", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Reasoning-based Intelligent Systems article, "Region-specific multi-scale meteorological forecasting based on data assimilation and reinforcement learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Business and Emerging Markets article, "Building organisational strategic resilience through leadership, design thinking, and business modelling", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Spatial domain semantic collaborative recognition model for complex emotions in artistic images", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Virtual reality and actual technology in psychology: intermediate research and analysis", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Real-time AI-regulated animation-user interaction system in virtual reality environments", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
In the age of global branding, instantaneous communication, and generative AI images, the symbols that we see in our daily lives circulate at an unprecedented rate. A study in the International Journal of Information and Communication Technology argues that if the symbols we share are to foster understanding rather than confusion, designers must treat them as carriers of cultural meaning, not mere decoration.
The team has used communication science, design theory, and semiotics, the study of signs and how they create meaning, to propose a systematic, evidence-based framework to identify, refine and test traditional cultural symbols. Their concept echoes an insight by Ferdinand de Saussure that suggests that a sign is not simply a form but a form bound to shared content. A flower or mythical creature, in this view, evokes memories, values and beliefs as much as it depicts the object it illustrates.
As digital platforms accelerate the circulation and mutation of images, we experience the fragmentation of symbols and signs. Moreover, in the age of generative artificial intelligence, almost all content is being cannibalised and regurgitated as derivative works, visual motifs are thus losing their inherited symbolism or, at best, being misappropriated or diluted. In the face of these changes, the researchers suggest that semiotics has now become a necessary part of creativity and perhaps the only hope of our conserving our symbols and their significance.
In their paper, the researchers discuss a five-step process beginning with systematic data collection and identification of culturally significant symbols. They followed this with a cross-cultural analysis, design refinement, and empirical testing. Statistical analysis together with expert review allowed them to look at specific symbols, such as the blue-and-white porcelain motifs featuring the lotus, peony, and plum blossom. As a good example of symbolic art, these patterns scored highly for clarity, adaptability, and perceived authenticity. The lotus is widely associated in East Asia with purity and renewal, the peony with prosperity and honour, and the plum blossom with resilience in adversity. Their visual simplicity combined with layered symbolism appears to aid translation into contemporary branding, the analysis found. More complex imagery failed to ignite the imagination of general audiences, although it was recognised as culturally significant by the experts.
Quantitative evaluation thus shows the different priorities associated with authenticity and meaning, challenging assumptions of universal interpretation for even familiar symbols that might be used in marketing and branding.
Li, A. (2026) ‘Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication’, Int. J. Information and Communication Technology, Vol. 27, No. 9, pp.18–38.
The following International Journal of Information and Communication Technology article, "Construction of digital art knowledge graph based on deep recurrent neural network", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "AI-powered recommendation and task assignment mechanism for interactive vocational English teaching", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Development of an AI-assisted spoken language assessment system for Japanese language teaching", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Innovative practice of AI-driven intelligent assessment system in university course teaching reform", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Federated learning-enabled personalised delivery and student privacy protection in universities", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Mental health problems are among the most pressing of public health challenges, affecting millions across different age groups and societies. Depression, anxiety, and stress-related conditions rank among the leading causes of diminished quality of life worldwide. They exact a heavy social toll and economic cost. Yet diagnosis still relies largely on self-reported symptoms and intermittent clinical interviews, which means diagnosis is vulnerable to memory lapse, stigma, and limited access to trained professionals.
Research in the International Journal of Networking and Virtual Organisations discusses an artificial intelligence (AI) diagnostic system that can spot early signs of various mental health conditions by analysing how people write online. The model, known as a Fossa-based Graph Neural Network (FbGNN), examines language patterns in text drawn from social media platforms and online forums. Instead of relying solely on questionnaires, it studies sentiment-driven textual information, the emotional tone, word choices and behavioural cues embedded in a person’s online writing.
The researchers explain that their system combines two advanced computational techniques. The first is the Fossa optimisation, a feature-selection method based on search strategies seen in nature. In machine learning, features are identifiable pieces of information, specific words, phrases or emotional markers. By applying Fossa optimisation, the system can filter out any irrelevant data from those features and identify pertinent indicators of mental distress.
The second component is a Graph Neural Network, a GNN. A GNN analyses relationships by representing information as a network of nodes and connections. Here, nodes correspond to features, and the connections are the interactions between them. This allows the model to detect complex patterns, such as recurring combinations of emotional expression and behavioural signals.
By training the system to classify text based on categories such as depression, anxiety, stress, bipolar disorder, suicidal ideation, and personality disorders, the team was able to then test its accuracy against known sample data. It was able to predict a person’s mental health status with an accuracy of almost 99 per cent in the trials. Such accuracy would be useful in screening for mental health problems among a cohort of users, such as students, employees, or any other group. It would allow healthcare follow-ups to be directed at those most likely to have problems that might be addressed and would only miss one in a hundred. Further refinements of the system could bring that accuracy closer to 100 per cent.
Shobitha, G.S., Kataksham, V.S., Nagalaxmi, T., Spandana, V., Sreelatha, G. and Radha, V. (2025) ‘A smart intelligent Internet of Things framework for predicting mental health’, Int. J. Networking and Virtual Organisations, Vol. 33, No. 3, pp.251–278.
The following International Journal of Information and Communication Technology article, "Evaluation of teaching effectiveness in data analysis courses using a behavioural big data model", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Construction of mental health analysis model based on multi-modal feature learning and fusion network", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Generative music composition teaching system based on mobile interaction", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Temporal convolutional networks with language models for decoding music preferences in mental health profiling", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Application of an AI-driven visual aesthetic scoring system for style calibration in art works", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Research on the identification and optimisation of traditional cultural symbols from the perspective of cross-cultural communication", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Managerial and Financial Accounting article, "Bibliometric insights into green accounting research: analysing trends, impact, and theoretical foundations", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Critical Infrastructures article, "An adaptive recognition of abnormal behaviour in deep excavation support construction site of high-rise buildings", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Services and Operations Management article, "How lighthouse companies are pioneering Indonesia's Industry 4.0 and 5.0 revolution? A soft system methodology approach", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Business Innovation and Research article, "Innovating for performance: the role of lean construction and strategic partnerships in construction firms", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Digital payments are a routine part of daily life for many people. As such, the risk of online fraud is rising alongside this convenience. Identity theft, email compromise, scams, and misleading investment schemes all exploit technological weaknesses and often user naivety and can lead to big financial losses.
Research in the American Journal of Finance and Accounting has looked at technological threat avoidance theory (TTAT), a framework used to understand how individuals respond to technology-related risks. The study sheds new light on what motivates users to protect themselves from online financial threats, if they do at all. It considers user attitudes towards fraud and the perception of potential financial loss with the aim of identifying the specific influences that lead to a user taking protective action.
The team surveyed users of online payment platforms and found that rather than an abstract fear of fraud, the decisive factor in whether or not people took preventative measures was simply the perceived financial loss. This finding suggests that awareness campaigns focused on general threats may be less effective than approaches that point out the direct financial consequences of online fraud.
Online fraud costs us roughly US$1 trillion per annum, and it is likely that figure is rising year on year. There are millions of reported cases and probably many more that are never reported. The losses that people bear when a victim of online fraud erodes overall trust in the digital systems on which we rely. Moreover, widespread, organised fraud can disrupt financial infrastructure, threatening broader economic stability and making it almost impossible for regulators to maintain oversight and control.
Facing such problems, the digital economy needs technological innovation in payment systems to incorporate effective strategies to influence user behaviour. Such strategies need to make it difficult for users to compromise themselves through technological naivety. Policymakers, platform developers, and financial educators also need to help in the design of interventions that align perceived risk with actual behaviour and so strengthen the individual against threats as well as help maintain trust in digital financial systems.
Peswani, R. and Vijay, P. (2026) ‘Minimising exposure to cyber frauds in digital finance: perspectives from technology threat avoidance theory’, American J. Finance and Accounting, Vol. 9, No. 1, pp.76–98.
The following International Journal of Computational Systems Engineering article, "RBF neural network model construction for enterprise financial big data analysis", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following Journal of Business and Management article, "The effect of in-store employee retail technology on employee well-being: based on the job demands-resources model", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following Journal of Business and Management article, "The COVID-19 pandemic effects on FDI in select emerging economies", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Personalised learning path generation mechanism based on RL and knowledge graph", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Analysis of tourist emotions and behaviour patterns using deep learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The migration to electronic medical records, used by healthcare providers, hospitals, and medical insurers, continues. However, this switch from paper records is leading to an accumulation of data, a lot of which is in free-text form that cannot be processed easily by an algorithm searching for knowledge and looking for patterns.
A study in the International Journal of Business Process Integration and Management has looked at using basic text-mining methods to convert this free text, which might be as unsophisticated as the jottings of a doctor or nurse, into something more organised. This kind of processing could make decisions in medicine faster and more consistent as well as potentially opening up new avenues for medical research and epidemiology.
The research focused on the specific medical condition of lower back pain and the reports associated with it. Lower back pain is a big problem for a lot of people and a major reason people miss days in work or file for disability. Experts can evaluate symptoms and consider what medical scans show and make a diagnosis and offer a prognosis. Administrators have to read through reports manually to determine fees and payments. A system to convert free text to structured text would be a boon, allowing dates and diagnoses to be searched, checked, and analysed much more easily.
The team used pattern-matching rules to look for regular expressions that allow software to detect specific phrases or formats in text. This could then be used to extract clinical and administrative details. This rule-based text mining was combined with machine learning algorithms that can learn from past data and make predictions about new cases.
The researchers tested their system on 255 anonymised reports. Medical specialists validated the extracted information, confirming a precision rate of 98 per cent. The structured information was then used to train three established predictive models: AdaBoost, which combines multiple simple models to improve accuracy; Random Forest, which aggregates the results of many decision trees; and Support Vector Machines, which identify boundaries between categories in complex datasets.
In tests, AdaBoost achieved perfect accuracy in predicting when rest should be prescribed. Random Forest reached 91 per cent accuracy and 93 per cent recall, a measure of how many relevant cases are correctly identified, in return-to-work assessments. The Support Vector Machine recorded a 98 per cent recall rate in classifying disability cases.
Beyond performance metrics, the researchers argue that the approach reduces processing time and limits transcription errors. Because the extraction rules are explicit, the system remains interpretable. This is important, as decisions still need to be explained to patients and others regardless of how structured or unstructured the data is.
Zwawi, R., Elhadjamor, E.A., Ghannouchi, S.A. and Ghannouchi, S-E. (2025) ‘Optimising text mining applications for enhanced medical decision making’, Int. J. Business Process Integration and Management, Vol. 12, No. 4, pp.295–306.
The following International Journal of Information and Communication Technology article, "Natural language processing for automatic error detection in Chinese language learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Prediction of uncertain passenger flow in scenic spots by fusing multi-source data and integrated learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "A study on AI-assisted interactive experiences for the preservation of ethnic culture in a mixed reality platform", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Interactive study of AI-music experiences in virtual reality on psychological comfort", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "A multi-agent reinforcement learning approach to heterogeneous resource allocation in lifelong education", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
As self-driving, autonomous, vehicles head out on to public roads, one of the field’s most persistent challenges remains collision avoidance in unpredictable traffic. A study in the International Journal of Vehicle Design discusses an artificial intelligence (AI) control system that has a 97 per cent success rate in avoiding obstacles, with a maximum response time of about half a second.
Urban roads present a shifting landscape of pedestrians, stalled vehicles, roadworks and erratic drivers. For a self-driving car, safe operation depends not only on accurate sensors but also on rapid decisions made under such uncertain conditions. Conventional obstacle-avoidance systems often rely on fixed rules or straightforward processing of sensor data. These approaches can sometimes fail in heavy rain, fog, or headlight glare.
Other systems that use reinforcement learning, a branch of AI in which the algorithm learns by trial and error, such as Deep Deterministic Policy Gradient, need a lot of computing power and often struggle to work quickly enough for real-world driving conditions.
The new approach described in IJVD builds on a reinforcement learning framework called Soft Actor-Critic, or SAC. In this computing system, the software actor proposes driving actions while the software critic evaluates whether or not the given manoeuvre would be sensible or not. SAC is designed to learn so that positive outcomes boost the actor-critic interactions that led to them. The system also embeds entropy, a statistical measure of randomness that allows it to continue to explore the best manoeuvres rather than settling prematurely on a single solution. This helps the system remain adaptable in uncertain environments.
The model also incorporates a self-organising cluster mechanism inspired by the collective movement of a flock of birds, that famously avoid mid-air collisions. At close range, a mathematically defined repulsion force pushes vehicles apart to prevent impact. At medium distances, a velocity calibration rule aligns speed with an ideal braking curve to reduce the risk of rear-end collisions. Additional rules govern wall and obstacle avoidance. This layered design allows multiple autonomous vehicles to coordinate their movements without relying on a single lead vehicle.
Ma, Y., Qian, Y., Ma, T., Li, Y. and Wan, J. (2025) ‘Intelligent obstacle avoidance control method for autonomous vehicles based on improved SAC algorithm’, Int. J. Vehicle Design, Vol. 99, No. 5, pp.1–19.
The following International Journal of Information and Communication Technology article, "Animation generation of traditional ethnic elements based on memory-enhanced self-supervised networks", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Cross-node knowledge transfer and generalisation based on federated meta-learning in fog computing", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Transfer learning-based adaptive music teaching system for modulating students' emotions", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A study in the Journal of Business and Management has shown that self-esteem plays an important part in determining whether someone wishes to pursue a leadership role. The findings have implications for both organisational success and career development, underscoring, as they do, how self-esteem affects personal motivation.
The research suggests that self-esteem affects a person’s regulatory focus, a psychological framework that influences how individuals approach challenges and goals. There are two main types of regulatory focus: promotion focus and prevention focus. Promotion focus is characterised by a drive for growth, achievement, and opportunity-seeking. In contrast, prevention focus is concerned more with the avoidance of failure, staying safe, and fulfilling one’s basic duties and no more.
Individuals with high self-esteem are more likely to be promotion focused, which then drives them to seek leadership roles. Those with lower self-esteem tend to lean towards prevention focus, which makes them less inclined to pursue leadership roles.
The effect is not solely down to the individual’s personality, however. The work also showed that career encouragement and support from supervisors and peers can affect a person’s focus and the motivational pathways they might take. Encouragement can boost the positive effects of promotion focus, motivating individuals to pursue leadership. However, for those with lower self-esteem, encouragement can have the opposite effect, reinforcing their reluctance to take on leadership responsibilities due to their prevention focus. The research thus highlights a need to consider individual psychological states when offering career support so that talented people who have leadership potential are not lost to those roles because of their lower self-esteem.
The team adds that unlike static predictors, such as personality traits or gender, regulatory focus can be affected by one’s experiences and external support. This makes it a more pliable characteristic that might be influenced to the person’s benefit through good career development advice for those with the potential for leadership.
Guo, J. (2025) ‘Regulatory theory and career encouragement in explaining leadership aspiration’, J. Business and Management, Vol. 30, No. 2, pp.75–98.
The following International Journal of Information and Communication Technology article, "Multi-objective optimisation of shield synchronous grouting materials: a synergistic architecture integrating intelligent algorithms and convolutional neural network", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "AI-driven recommendation for personalised physical education training", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Social network news dissemination and detection model based on multi-scale information", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following Journal for International Business and Entrepreneurship Development article, "Research on women's entrepreneurship in Saudi Arabia: a bibliometric analysis and research outlook", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Research into the COVID-19 crisis, which began in December 2019, suggests that although there was widespread loss and disruption, the international crisis also planted the seeds for grassroots innovation and resilience. A study in the International Journal of Entrepreneurial Venturing of one hundred initiatives that emerged in Belgium during the pandemic finds that when established institutions struggled to respond quickly, individuals and organisations were able to step up to create new economic and social value.
The research focuses on initiatives defined broadly to include both newly created ventures and existing organisations that adapted their activities. These ranged from informal mutual aid efforts to repurposed businesses and newly launched services. Some were started by people with no prior experience of entrepreneurship. Other initiatives were started by established entrepreneurs responding to the sudden changes in demand and regulation. What they shared was a capacity to adjust rapidly under pressure.
The pandemic created conditions of extreme uncertainty. Lockdowns and business closures, imposed to limit the spread of the virus, caused sharp falls in income, consumption, and investment. Many people perceived formal support systems as too slow or rigid to meet urgent needs. This gap became the space in which these initiatives emerged, often spontaneously and with limited resources.
The study looks at this kind of resilience and rather than treating it simply as endurance in the face of a crisis, defines it as a dynamic process of recovery, adjustment, and innovation. Resilience was, during the pandemic and in its aftermath, both the route through which initiatives developed and the results they produced. The researchers argue that action was not driven solely by compassion or urgency, but by the ability to reframe the crisis as an opportunity to meet unmet needs.
The study suggests that locally driven, resilience-based initiatives can complement government and aid responses, particularly in the early stages of a crisis. As such, for policymakers, the challenge is how to recognise and sustain such efforts without undermining their flexibility. We will face pandemic and other shocks in the future, our ability to adapt and innovate in these conditions will be key to an effective disaster response.
Wuillaume, A., Ferritto, A. and Janssen, F. (2025) ‘A note on resilience in the face of adversity when small droplets trigger big changes’, Int. J. Entrepreneurial Venturing, Vol. 17, No. 3, pp.249–273.
The following International Journal of Business Information Systems article, "The impact of strategic vigilance on enhancing organisational effectiveness: exploring the mediating role of strategic readiness", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Multi-instrument polyphonic automatic transcription method combining gated recurrent units and DeepLabv3+ model", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "An athlete motion recognition model based on machine learning and the internet of things", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Multi-objective optimisation of cigarette tobacco leaf blend formulation based on sensory-chemical correlation and machine learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Optimisation of PID control for tobacco feeding rail based on convolutional neural network", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Graph attention network-optimised cigarette logistics cost modelling in multiple constraints", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Application of deep reinforcement learning in sports competitive decision-making", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Latin dance action style transfer based on improved Ada IN algorithm", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
A study in the International Journal of Global Environmental Issues has looked at “ritualistic” hunting practices in eastern India. It finds that they are contributing markedly to a worrying decline in wildlife and forest health. The work raises difficult questions about how cultural traditions can coexist with modern conservation goals.
The research focuses on Jungle Mahal, a forested region in western West Bengal, where hunting remains an integral part of religious and social life for several communities, particularly the Santhal. Ritualistic hunting, defined in the study as the killing of wild animals for ceremonial rather than commercial or subsistence purposes, is shown to be placing increasing pressure on ecosystems that are inherently vulnerable.
West Bengal hosts a range of ecologically significant species, including pangolins, fishing cats, and diverse bird populations. Such animals play crucial roles in the functioning of the ecosystems across the region. They help to regulate prey populations, disperse seeds, and recycle nutrients, among other things. The study reports a clear reduction in wildlife richness, biodiversity. It also notes a marked decline in forest density in Jungle Mahal. It is worth noting, that residents and hunters are well aware of these changes to their local environment, however, there is the paper reports, little inclinations towards matters of conservation.
Hunting in the region employs traditional techniques such as bow-and-arrow, traps, nets, and the use of smoke to flush animals from burrows. It occurs throughout the year, but intensifies during festival periods between March and June. During this period, large communal hunts with hundreds or even thousands of participants take place and huge numbers of animals are killed in a very short time.
India’s Wildlife Protection Act of 1972 prohibits the hunting of wild animals, but the researchers found that enforcement is weak in remote forest areas. Awareness of conservation laws among local communities is limited, and illegal hunting continues unchecked. The study highlights the fact that there is great mistrust of authorities in such regions and a general perception that conservation policies are detrimental to indigenous values and livelihoods. It remains an open-ended question as to how this disconnection between culture and conservation might be remedied.
Baitalik, A., Bhattacharjee, T., Bera, D., Paladhi, A., Kar, R.R., Ojha, M., Hazra, A., Begum, M.D., Lohar, R., Karan, M. and Dandapat, R. (2025) ‘Ritualistic hunting in selected districts of West Bengal (India): implications on wildlife diversity and conservation’, Int. J. Global Environmental Issues, Vol. 24, No. 2, pp.85–117.
The following International Journal of Information and Communication Technology article, "A hybrid SE-YOLOv5 and GNN-SGCM approach for intelligent table tennis ball positioning and 3D recognition", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "MFF-PEA: an automatic assessment model for professional spoken English via multimodal feature fusion", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Vehicle Design article, "Intelligent obstacle avoidance control method for autonomous vehicles based on improved SAC algorithm", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Intelligent Information and Database Systems article, "Consensus analysis and extended prospect theory-based intuitionistic triangular fuzzy multi-criteria group decision-making method", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Business Innovation and Research article, "Dual routes of persuasion in tourism: building marine destination image through the elaboration likelihood model", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Knowledge graphs meet deep learning for intelligent diagnosis of oral English proficiency", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Climate change and worsening environmental conditions have brought into sharp relief how we must reconcile development with sustainability. This issue is nowhere more starkly relevant than among the fastest-growing economies. Research in the International Journal of the Energy-Growth Nexus that examined the BRICS countries, Brazil, Russia, India, China and South Africa, suggests that investment in education and training might play a significant role in reducing environmental harm, a role that has often been overlooked.
The researchers analysed several years worth of data from the BRICS countries. These nations account for a large proportion of the world’s population, energy use, and greenhouse gas emissions. The analysis found a close relationship between higher levels of human capital and lower levels of environmental degradation, measured primarily through carbon emissions. Human capital refers to the stock of education, skills and knowledge embodied in a workforce, commonly captured through indicators such as schooling level and training.
According to the analysis, improvements in human capital is associated with reduced emissions across the BRICS economies. The results hold across several statistical techniques designed to address common problems in these kinds of studies, such as cultural and social differences, the differing impact of global shocks, and the two-way causality between growth and pollution.
The findings are rooted in endogenous growth theory that says long-term economic progress depends on knowledge, innovation, and research rather than on physical inputs alone. In environmental terms, a more educated and skilled workforce is better able to develop and adopt cleaner technologies, improve energy efficiency, and comply with environmental regulations. Innovation, measured in this study by patent activity, is also associate with better environmental outcomes. This latter point reinforces the idea that technological progress can decouple growth from emissions.
The team adds that globalisation emerges as another factor associated with improved environmental quality. This phenomenon perhaps reflects technology transfer and the sharing of cleaner production methods across borders. Trade openness itself, however, has the opposite effect. More international trade means higher levels of environmental degradation in the BRICS countries. This is consistent with concerns that trade can encourage the expansion of pollution-intensive industries or the import of environmentally inefficient technologies.
As emerging economies continue to drive global growth and emissions, this study shows how education and training are key to climate and environmental strategy. Policies that open up access to high-quality education, raise average years of schooling, and support research and development could lead to environmental benefits as well as providing an economic boost. There is a need, however, to improve trade policy and environmental regulation so that economic development is not to the detriment of environmental sustainability.
Sachan, A. and Pradhan, A.K. (2026) ‘Examining the impact of human capital on environmental degradation in BRICS nations’, Int. J. Energy-Growth Nexus, Vol. 1, No. 3, pp.201–218.
The following International Journal of Information and Communication Technology article, "Knowledge graph-based adaptive recommendation model for training courses", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Generative adversarial network-driven interactive simulation modelling for environmental design", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Analysis of an intelligent piano music transcription model by deep reinforcement learning", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "A CNN-ViT fusion model for predicting tourist behaviour and consumption intentions", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Copyright security protection of NFT digital art works in new media communication", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Tourist satisfaction evaluation through data-driven web text mining: a case study of Jilin national ski tourism resort", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
The following International Journal of Information and Communication Technology article, "Monitoring and optimisation of interactive classroom teaching effects empowered by the internet of things", is freely available for download as an open access article.
It can be downloaded via the full-text link available here.
Public sector organisations in emerging economies could improve their performance and resilience by taking a more systematic approach to knowledge management, according to a review in the International Journal of Business Excellence.
The review examined research into how government institutions create, share and retain knowledge. It also considered why these practices are important to the institutions’ ability to deliver their services, adapt to change, and withstand disruption. The main conclusion is that effective knowledge management should not be considered as a peripheral administrative exercise, but must be seen as an essential strategic component of governance.
Knowledge management refers to the systematic processes through which organisations generate, store, and use knowledge. This includes policy documents, reports, and databases. It also includes tacit knowledge, the experience, skills, and judgement of individual members of the institution. In the public sector, much of this kind of tacit knowledge can be lost through staff turnover and political change if it is not deliberately captured and shared in a timely manner.
Across the research papers covered in this IJBE review, there is strong evidence that public organisations that invest in knowledge management perform better. They are more able to innovate, they can respond more effectively to new social and economic challenges, and they can maintain continuity during periods of political and social upheaval. This kind of institutional resilience is strengthened by effective knowledge management.
However, the review also shows that too many public bodies rely on informal or fragmented approaches to knowledge management. This tends to limit its long-term impact. The underlying problem is often inadequate technological infrastructure. If the digital platforms for storing information and enabling collaboration are not present, then there is no functionality within the institution to allow for effective knowledge management. In addition, cultural and organisational barriers often stymie efforts to share knowledge in institutions with rigid hierarchies and siloed departments, and low levels of trust among employees in different areas within the institution.
Good leadership is the decisive factor in overcoming these various obstacles. Indeed, the review found that ethically inclined and committed leaders who actively promote collaboration and learning can embed knowledge management into everyday practice. Technology helps but human factors such as motivation and skills can make all the difference.
Yshikawa-Arias, J.F. and Arana-Barbier, P.J. (2025) ‘Knowledge management in the public sector of emerging economies: a literature review’, Int. J. Business Excellence, Vol. 38, No. 6, pp.1–21.
