2026 September - 61 articles
The rapid evolution of sophisticated cyber threats has drastically increased the cybersecurity risks in Industrial Internet of Things environments due to the massive interconnection of industrial devices, sensors, programmable logic controllers, gate...
Approximate multipliers have potential to improve energy efficiency in Deep Neural Networks but introduce computational errors that degrade accuracy. This paper introduces a novel method, leveraging approximate multipliers to enhance accuracy, while...
Transformer-based detectors model long-range context effectively, yet their representations remain dominated by RGB appearance and can become unreliable in cluttered, occluded, or crowded scenes. We present BMF-DETR, a pseudo-depth-guided detector th...
The rapid advancement of large language models (LLMs) has created new opportunities for intelligent fault diagnosis, particularly in complex industrial systems, such as heating, ventilation, and air conditioning (HVAC) in urban rail transit. Although...
Retailers managing large stock-keeping unit (SKU) catalogues need a compact, auditable view of how individual products behave in order to plan replenishment, assortment and promotions. We present an interpretable analytics pipeline that derives SKU-l...
Automated evaluation of movement quality can enhance physiotherapeutic treatment and sports training by providing objective, real-time feedback. However, deep learning models that assess movements captured by inertial measurement units (IMUs) are oft...
Recent advances in large language model (LLM) agents have shown promise for autonomous decision-making in recommender systems. However, existing approaches suffer from two fundamental limitations: flat agent memories that conflate different informati...
The reliable detection of spot-weld defects in automotive structural components is challenged by large variations in defect scale, severe background interference and limited detection accuracy. Here, we propose YOLOv8-RFA-iEMA-RH, an improved YOLOv8n...
Congenital heart disease (CHD) is a major cause of infant morbidity and mortality, and timely diagnosis remains difficult where advanced imaging is not consistently available. Automated phonocardiogram (PCG) screening can support early triage, but pe...
Deep electrocardiogram (ECG) classifiers can achieve strong predictive performance, yet their latent evidence remains difficult to audit, and explanation pipelines can become misleading when semantic contracts or label provenance fail. In this work,...
This study develops a specialized method for the synthesis of intelligent platforms for cross-referral transition between cognitive basis systems (CBSs) in the field of HCI object perception subjectivization, within the context of global scientific a...
Annotated medical imaging data remain scarce, and labels are often weak and noisy: in mammography, an examination comprises several high-resolution views, yet the diagnostic outcome is recorded only at the breast level. Such problems are naturally ca...
Accurate 3D topography measurement of micro-structured surfaces remains challenging due to the limitations of conventional autostereoscopic systems, particularly the intrinsic constraints of light-field imaging and dependence on single-source data. B...
Traditional imitation learning is prone to distribution shift and trajectory divergence in highly dynamic, strongly time-varying flight tasks. To address this, we propose a temporally adaptive action-chunking framework built on temporal-derivative en...
The convergence of additive manufacturing (AM) and artificial intelligence (AI) is poised to redefine the landscape of modern production; however, the literature remains fragmented across isolated applications, lacking a unified perspective on the en...
We compared four large language models (LLMs; ChatGPT, Grok, Gemini, and DeepSeek) with humans on tests of cognitive development, assessing relational integration, linguistic awareness, general and domain-specific reasoning, and cognitive self-awaren...
Information architecture may shape harmful conduct in dynamic multi-agent systems, yet its relationship to objectively measured misrepresentation remains unclear. We examine seller-only communication and market-wide public history in a repeated hidde...
This paper raises a methodological question: How can we assess machine-made Old English when there is no parallel reference text and the standard metrics do not fit the task? We propose a pipeline with five measuring layers plus two compliance compon...
Environmental-monitoring systems often bundle sensing, communication, storage, visualization, and control into one application, making later changes difficult. We designed a service-oriented platform that separates these functions through defined int...
Visual Question Answering (VQA) in embodied settings draws on computer vision, natural language processing, and robotics. Unlike traditional VQA, Embodied Question Answering (EQA) may require an agent to acquire and retain evidence from a 3D environm...
AI and machine learning deployments in regulated decision contexts face an intolerance for inadmissible outputs (“hallucinations” when the model is generative) that current explainability methods address only after the fact. Bounded AI de...
This study evaluated unconditional synthetic mammography generation with Deep Convolutional Generative Adversarial Networks (DCGANs). The dataset comprised 690 anonymized mammograms, equally distributed across BI-RADS 1–6 (115 images/category)....
Sustainable agricultural planning requires predictive frameworks that can capture spatiotemporal variability, sustainability dynamics, and the potential outcomes of alternative management scenarios. The research proposes TSAFI-DT, a retrospectively v...
Artificial intelligence (AI) is transforming civil and construction engineering (CCE) education. CCE students must develop both AI technical proficiency and ethical awareness, ensuring that AI tools reflect the varied experiences of project clients....
Crash reports are critical for software debugging and maintenance. In software maintenance, developers reproduce a crash to locate the root cause via analyzing the crash report. A crash report is a document that records details of the crash as it occ...
Early stroke risk prediction offers an opportunity for timely interventions and may help reduce the clinical burden associated with stroke. Artificial intelligence (AI) provides medical practitioners with tools to analyse clinical biomarkers and pred...
Multi-modal MRI provides essential anatomical and pathological information for accurate brain tumor segmentation. However, deep learning-based segmentation methods are hampered by limited annotated data and incomplete modality acquisition in clinical...
Behaviour-Driven Development (BDD) encodes acceptance criteria in Gherkin, but hand-authoring is laborious, and it is unclear which large language model (LLM) drafts it best. We benchmark eight LLMs generating Gherkin from three requirement corpora (...
Smart systems, the Industrial Internet of Things, and cyber-physical networks increasingly make decisions on the devices where data is generated, on nodes short of memory, compute, energy, and bandwidth, and exposed to real adversaries. Two research...
Precise segmentation of the retinal microvasculature is vital for early detection and longitudinal monitoring of systemic cardiovascular and ophthalmic diseases. However, contemporary deep learning models struggle to simultaneously preserve fine-vess...
Home-based physiotherapy is performed without supervision, which leads to incorrect execution and motivates systems that assess movement automatically from inertial measurement units (IMUs). Such systems assign each repetition to a category, yet a re...
The You Only Look Once (YOLO) has been widely adopted in aquaculture monitoring and management due to its real-time performance and deployment flexibility. The recently introduced YOLO26 architecture incorporates Non-Maximum Suppression (NMS)-free en...
Background: Smartphones and generative artificial intelligence (GenAI) are increasingly integrated into everyday life, influencing information access, digital interaction, and cognitive tasks. While problematic smartphone use and cognitive offloading...
Test-time refinement aims to improve generated programs through additional inference, but its value after an initial candidate has been produced remains unclear. We conduct a controlled evaluation of one-round Self-Refine and Self-Debug across seven...
This chapter offers a conceptual and philosophical analysis of the ontological, epistemological, and ethical issues associated with the design, development, and use of Agentic AI in moral and legal decision-making. Its aim is to map, classify, and br...
The detection of audio deepfakes has emerged as a significant problem in the field of voice biometrics systems, aiming to distinguish real human voices from those generated by Artificial Intelligence (AI). With synthetic voice becoming increasingly h...
The rising number and the complexity of crises in Europe, including the COVID-19 pandemic, migration, and cybersecurity threats, have accelerated the adoption of digital transformation and artificial intelligence (AI) in public administration. This p...
Small, heterogeneous clinical datasets pose a challenge for whole-cohort prediction because clinically meaningful treatment or response patterns may be diluted across biologically diverse patients. We describe and evaluate NetraAI, an interpretable d...
Different imaging modalities exhibit inherent discrepancies in intensity characteristics and information representation, resulting in pronounced heterogeneity among multimodal features. When these heterogeneous features are directly learned and fused...
Agentic artificial intelligence (AI) systems are increasingly deployed across distributed cloud–edge–radio infrastructures, where autonomous agents make decisions with direct operational and economic impact. Smart contracts (SCs) enforce...
Zero-day network attacks pose a significant threat because their unknown signatures evade traditional detection mechanisms. This research develops an AI-enhanced intrusion detection system that aims to detect such attacks while providing interpretabl...
Predicting emergencies caused by uncontrolled and sometimes sudden changes in methane concentration within working and adjacent zones of coal mines remains a critical and challenging task, the solution for which can greatly enhance mining safety. Thi...
Existing deepfake detectors often perform well on in-domain data but generalize poorly to unseen datasets or manipulation methods. This limitation is largely attributed to their reliance on dataset-specific semantic cues rather than transferable forg...
Artificial intelligence is increasingly used in sport science to classify movement, analyse tactics, estimate readiness, forecast performance and injury risk, and support rehabilitation. Predictive performance alone, however, does not establish pract...
The effective resolution of non-deterministic polynomial time hard (NP-hard) combinatorial optimization problems requires a delicate balance between global exploration and local exploitation. While Quantum-Inspired Algorithms (QIAs) leverage principl...
The standard 12-lead ECG is the gold-standard tool for cardiac diagnosis and monitoring; however, its multi-electrode configuration limits its use in prolonged monitoring and wearable devices. Existing portable ECG devices typically record only a sin...
Transformer architectures, originally developed for language modeling, have been increasingly applied to time-series forecasting, but deploying them on sensitive data such as patient vital signs, financial records, or energy use raises privacy risks...
Urban rail transit systems require reliable decision-support methods to assist operators in handling complex fault events. Although large language models provide strong reasoning and knowledge integration capabilities, their open-ended generation may...
Solar energy makes a considerable contribution to global power generation, necessitating photovoltaic (PV) fault detection to ensure high yields in solar power systems. In real-world solar installations, operational data are geographically dispersed,...
Artificial intelligence (AI) is increasingly being incorporated into oral healthcare and dental education, yet the quality and effectiveness of randomized evidence supporting these interventions remain uncertain. We systematically reviewed randomized...
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