2026 June - 59 articles
A single user-invariant tensor, kinematically impossible for any human finger to produce, bypasses bidirectional long short-term memory (BiLSTM) continuous-authentication defenders with numerically identical structure across four independently traine...
The growing worldwide prevalence of Diabetes Mellitus highlights the urgent need for effective early detection methods to enable prompt intervention. This study develops a machine learning-based decision-support prototype for predicting diabetes risk...
This article presents an integrated approach that combines Virtual Reality (VR), Augmented Reality (AR), and an Intelligent Virtual Assistant (IVA) to support training, on-the-job assistance, and maintenance in a textile manufacturing environment. Th...
Manual compliance auditing in cloud environments consumes up to 40% of IT security budgets annually, yet existing approaches verify control presence rather than effectiveness, leaving institutions vulnerable to adversarial evasion. This paper present...
A Retrieval-Augmented Generation (RAG) approach is widely used as a key element for intelligent assistants. However, the knowledge extraction stage from technical text corpora is fraught with difficulties due to the presence of highly specialized ter...
In the digital twin (DT) network, effective edge data processing is essential to meet the real-time requirements of DT models. However, edge servers (ESs) are self-interested and have limited computation resources. The virtual content operator (VCO)...
The development of accessible and experimentally validated robotic systems for engineering education is a challenge, especially in academic environments where industrial manipulators are economically inaccessible. This paper presents the design, mech...
The proliferation of large language model (LLM) agents has enabled increasingly complex multi-step automation; however, composing multiple agents into coherent systems introduces significant orchestration challenges that remain poorly documented. Thi...
Intelligent sensors and Internet of Medical Things (IoMT) platforms are rapidly changing smart healthcare by enabling continuous capture of physiological, behavioral, and clinical events outside conventional hospital settings. Yet the value of connec...
SYN flooding attacks remain a persistent threat to network availability, particularly in Distributed Denial-of-Service (DDoS) scenarios that exploit the TCP three-way handshake. Traditional SYN cookies mitigate half-open connection exhaustion but may...
Faculty governance in higher education depends on transparent participation, reliable quorum enforcement, accountable record keeping, and strict alignment with institutional regulations. Conventional departmental council processes provide formal auth...
Digital trust in online interactions is commonly established through mechanisms such as decentralized identifiers (DIDs), verifiable credentials (VCs), and digital wallets. While these technologies support the correctness of individual components, th...
5G technology was introduced in 2019 with the aim of transforming digital connectivity, enabling a new generation of communication capabilities, such as significantly faster mobile broadband, highly reliable low-latency links, and the capacity to sup...
Vehicle-to-Everything (V2X) communication is a critical enabler of autonomous driving, supporting real-time information exchange among vehicles, roadside infrastructure, pedestrians, and cloud services. However, the security of current V2X systems la...
Accurate and timely diagnosis of respiratory diseases remains a critical challenge in clinical practice, particularly in resource-limited and remote healthcare settings. This study proposes a web-based automated respiratory disease classification sys...
Post-quantum cryptographic (PQC) algorithms are being developed to guard against quantum-computing attacks, but their behavior in constrained Internet of Things (IoT) environments remains an important topic of discussion. In this work, we study the i...
Mobile edge computing (MEC) enables computation-intensive and latency-sensitive tasks to be offloaded from mobile devices to nearby edge servers. Most existing MEC task offloading studies formulate offloading as a selection problem over a fixed or fu...
Future Internet applications such as intelligent transportation, immersive services, and edge-assisted artificial intelligence require latency-sensitive service provisioning at the network edge. In containerized mobile edge computing (MEC), service o...
Mixed-reality (MR) technologies have enhanced anatomy education through immersive three-dimensional visualization; however, most existing systems lack tutoring capabilities that respond contextually during anatomical exploration. This paper presents...
Baseline web security configuration is a critical but often overlooked component of national cybersecurity posture, particularly in small and developing digital economies. This study presents a systematic empirical assessment of Tier-1 HTTP security...
Future 6G networks require higher performance and wider service coverage. Multi-domain Service Function Chain (SFC) deployment enables service provisioning across multiple network domains to meet these demands. However, when collaboration occurs amon...
Hierarchical cloud–edge networks rely on distributed control planes to manage large-scale heterogeneous infrastructures, where controller placement and node assignment strongly affect latency, load balancing, and resilience. Existing methods ty...
The rapid growth of the Internet of Things (IoT) has increased dependency on Transport Layer Security (TLS) for securing device communications, enhancing confidentiality while reducing the visibility required by traditional intrusion detection system...
Reliable public-sector labour-market forecasting requires models that can be updated as data sources, AI tools, and labour-market signals evolve. This paper proposes a provider-independent multi-agent framework for dynamic predictive evaluation of na...
Industrial control systems (ICS) are increasingly targeted by cyberattacks that manipulate physical processes while evading data-driven detectors trained on raw time-series data. This paper extracts 34–41 control-theoretic features, including t...
The rapid evolution of Smart Homes and Smart Buildings is driven by the transition from the Internet of Things (IoT) to the Artificial Intelligence of Things (AIoT). Within this scenario, Security Systems are particularly critical and data-intensive...
Federated learning (FL) enables distributed model training in IoT environments while keeping raw data on local devices. However, protecting model-update exchange is difficult on microcontroller-class devices due to strict latency, memory, and energy...
Effective intrusion detection for Internet of Things (IoT) environments requires balancing predictive performance, resource efficiency, and interpretability—particularly in real-world deployments where traffic distributions and attack scenarios...
Knee Osteoarthritis (KOA) is a leading contributor to global physical disability, where delayed diagnosis often results in irreversible joint damage and socio-economic cost. Early diagnosis remains challenging due to subtle radiographic biomarkers an...
This study analyzes the transition of the Artificial Intelligence of Things (AIoT) toward a Human-Centered Artificial Intelligence (HCAI) approach. Following PRISMA 2020 guidelines, a Systematic Literature Review was conducted on 1 April 2026, retrie...
With the growing need for collaborative machine learning across institutions holding sensitive data, ensuring data privacy without compromising model performance has become an important challenge. This work introduces secure federated learning algori...
Unauthorized commercial drone activity around critical infrastructure motivates the development of trajectory-level anomaly detection. We present a rigorous benchmarking study of variational autoencoder methods for drone trajectory anomaly detection...
Future internet services are expected to increasingly depend on IoT–edge deployments, in which intrusion detection must operate close to constrained, heterogeneous devices rather than only in cloud or data-center environments. Although the lite...
Recent improvements in hardware and software have enabled a paradigm shift in satellite computing, moving from purpose-built satellites running a single application to platforms capable of executing and even receiving new workloads on orbit. This evo...
The integration of heterogeneous healthcare data sources remains a major challenge in developing reliable and personalized predictive systems for digital healthcare applications. Traditional machine learning methods perform well on structured clinica...
Driven by the rapid advancement of intelligence and connectivity, traditional distributed and signal-oriented automotive architectures are gradually being replaced by centralized, service-oriented architectures. In response to this transition, In-Veh...
Artificial Intelligence of Things (AIoT) is transforming Internet of Things (IoT) systems from cloud-centric data processing into distributed intelligence across device, edge, fog, and cloud tiers. However, existing reviews often emphasize specific c...
Critical infrastructures are increasingly Internet-connected cyber–physical systems whose recovery after cyber incidents must satisfy safety, timing, regulatory, and interdependency constraints. Yet, the use of large language models (LLMs) for...
In this work, the newly developed functional bootstrapping (FBT) for the Cheon–Kim–Kim–Song (CKKS) scheme is used for the first time to homomorphically evaluate an encrypted neural network. The advantage of FBT over previous approac...
This paper presents the design, implementation, and controlled evaluation of a proof-of-concept ear-level wearable system that integrates local artificial intelligence for real-time physiological monitoring in construction safety applications. The pr...
In highly dynamic vehicular ad hoc networks (VANETs), vehicles frequently move across the coverage areas of multiple roadside units (RSUs), making secure and efficient continuous vehicle-to-infrastructure access essential. However, repeated full auth...
The rapid global expansion of photovoltaic capacity, now exceeding 1 TW, has transformed solar power forecasting from an engineering problem into a financially critical investment decision. Yet virtually all published forecasting studies optimise sta...
Handover management is a fundamental process in modern mobile networks, ensuring service continuity under user mobility. However, the relationship between network conditions and handover behavior remains insufficiently understood under real-world mea...
Adverse drug–drug interactions (DDIs) are a leading cause of preventable medication-related harm, and their automatic detection from the biomedical literature is critical for pharmacovigilance and clinical decision support. Most existing system...
As 6G mobile communications evolve, Low Earth Orbit (LEO) satellite mobile edge computing (MEC) enables globally seamless computing. However, the high mobility of LEO satellites disrupts service continuity and resource stability. Existing approaches...
Machine-learning-based intrusion detection for Internet of Things systems has often been evaluated through model-centered pipelines that use weakly governed partitioning, limited leakage auditing, and closed-set assumptions. Consequently, reported pe...
Background: Continuously monitoring an ECG signal is vital for patients who cannot articulate their symptoms in a healthcare setting. To identify abnormalities, we introduce a compact one-dimensional convolutional autoencoder (CNN-AE) that can operat...
Federated Learning (FL) enables privacy-preserving model training in edge and IoT environments. However, in adversarial settings, FL suffers from two key challenges: robustness degradation due to data heterogeneity and poisoning attacks, and runtime...
Financial analysis increasingly depends on the ability to transform heterogeneous textual evidence into reliable, verifiable, and actionable knowledge. However, adoption in finance requires generated outputs to be not only accurate, but also traceabl...
Contemporary vulnerability management relies on the Common Vulnerability Scoring System (CVSS) and the Exploit Prediction Scoring System (EPSS), both of which evaluate Common Vulnerabilities and Exposures (CVE) entry in isolation, disregarding the ne...
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