2026 June - 71 articles
DoS and DDoS attacks remain a major threat to service availability in modern IP and IoT networks, yet many learning-based detectors depend on dataset-specific flow exports, feature tables, or preprocessing conventions. This article presents a unified...
Authentication is essential to hold users accountable across online services. Conventional authentication systems rely on centralized architectures or third-party identity providers, which, however, introduce single points of failure, privacy concern...
Driving behavior recognition plays a crucial role in intelligent driving systems and road traffic safety. Due to insufficient driving experience and limited ability to allocate visual attention, novice drivers are considered a high-risk group for tra...
Power systems continuously generate large-scale load time series data for forecasting, consumption analysis, and equipment health monitoring. However, real-world load measurements are often contaminated by anomalies caused by sensor faults, communica...
Edge vision systems require convolutional neural networks (CNNs) that preserve recognition accuracy under strict storage, computation, and latency constraints. Although ResNet18 is a compact residual backbone, direct deployment on resource-constraine...
The work described in this paper continues basic research aimed at improving clustering algorithms such as K-Means and Random Swap through careful seeding and genetic concepts. This paper, in particular, develops a variation in the Hartigan–Won...
Generative large language models (LLMs) are increasingly used to support writing feedback. However, the pedagogical safety and usefulness of LLM feedback for primary students remains under-evaluated. This study reports an educator-centered evaluation...
An electroencephalogram (EEG) signals provide vital insights for stroke rehabilitation, yet analyzing these complex, high-dimensional data to detect gait anomalies remains challenging. Artificial intelligence offers a promising solution to precisely...
High-fidelity motion cueing in driving simulators is essential for delivering a realistic and immersive user experience. However, the trade-off between motion accuracy and computational efficiency often hinders achieving this. Fixed-horizon Model Pre...
Existing cross-chain bridges over-rely on static collateralization and post-event penalties, leaving them vulnerable to concealed on–off attacks and rational group collusion. To address these limitations, this paper proposes a Dynamic Trust Eva...
Cyber-physical systems (CPSs) based on the Internet of Things (IoT) form the backbone of modern smart infrastructures, including smart cities, healthcare monitoring, industrial automation, and intelligent transportation. However, connecting many reso...
This systematic review investigates the application of computer-vision technologies for automated monitoring of personal protective equipment compliance in industrial environments. This review followed the PRISMA 2020 guidelines and covered studies p...
Affected by inter-annotator cognitive differences, fatigue effects, and data poisoning, training data inevitably contains a certain proportion of noise, which severely impairs model performance. Traditional manual verification is costly and inefficie...
The rapid growth of scientific spatiotemporal data poses increasing challenges for efficient storage and transmission while preserving sufficient reconstruction fidelity for downstream analysis. Existing compression methods remain limited in this set...
This article examines the medium to long-term enrollment patterns of an AI-based platform designed to support children in learning robotics and participating in a national robotics competition in Romania. Drawing on registration and participation dat...
Virtual Reality (VR) is increasingly used in clinical, educational, and supportive-care contexts, but evidence on VR-based creative interventions for vulnerable populations remains fragmented. This article presents a scoping review and proposes VR-CR...
Automatic gesture and movement recognition techniques are mainly used with adults for various purposes in public, clinical, and laboratory settings. Growing interest in this field has led to the increasing application of these methods in child behavi...
This paper proposes a prototype-level hierarchical visual–sensor framework for monitoring the Zamioculcas houseplant in complex indoor environments and supporting adaptive care-mode selection. The proposed framework combines a two-level visual...
Emotion recognition plays a crucial role in human–computer interaction, health monitoring, and affective computing by analysing physiological signals. Despite recent advancements, current research still faces challenges, including the lack of e...
Feature prioritization in early-stage software startups is a critical yet poorly structured challenge, as prevailing frameworks rely predominantly on expert intuition and fail to exploit patterns latent in historical delivery data and labor market dy...
Despite significant improvements in vehicle management efficiency achieved through the integration of VANET and Internet of Things technologies, Internet of Vehicles (IoV) networks remain vulnerable to cyberattacks. This is because the wireless data...
Global avocado production exceeds 10 million tons annually. Among the diseases affecting avocado fruit, anthracnose is one of the most significant, causing black lesions and fruit decay that can result in yield losses of 20–30%. To facilitate t...
The growing sophistication of the internet and web space has spawned highly dynamic, multi-vector cyber threats that cannot be handled by automated detectives and hence the necessity to introduce analyst-oriented, cognitively powerful security analys...
The exponential growth of cyber threats in modern digital infrastructure demands advanced detection systems that adapt to evolving attack patterns. Traditional cybersecurity approaches struggle with dynamic threats, requiring extensive labeled datase...
Inventory systems are typically evaluated using aggregate performance metrics such as out-of-stock and average inventory. In supply chain management, it is important to understand the underlying reasons for a period’s performance—specific...
Online hotel reviews provide a major source of information for understanding guest satisfaction, yet rating prediction remains difficult because review text is often short, highly skewed toward positive scores, and affected by inconsistent or repetit...
Efficient water resource management is critically important for arid regions such as southern Kazakhstan. This paper presents a hybrid Internet of Things (IoT) and Vision-based Internet of Things (VIoT) architecture for real-time monitoring of water...
Continuous Integration pipelines rely on large-scale automated testing to support rapid releases. However, flaky tests exhibit non-deterministic outcomes under an identical code and configuration, substantially increasing rerun costs and hindering fa...
One of the remaining challenges in deploying 3D CNN models in resource-constrained environments is the high computational demand. In this paper, we design three lightweight architectures that have distinct spatiotemporal topologies, namely, Lite-R21D...
Traffic congestion poses a significant challenge in urban environments. The use of digital techniques has emerged as a pivotal trend, as it offers substantial safety to and mitigates stress and frustration for road users. The purpose of this survey w...
This study investigates data augmentation as a strategy for addressing dataset scarcity in Internet of Medical Things (IoMT) cybersecurity and improving intrusion-detection system performance. Four augmentation methods—Rule-Based, Tabular Varia...
Structured Query Language injection (SQLi) remains a persistent threat to web applications due to the obfuscation, diversity, and evolving structure of malicious payloads, which limit the effectiveness of conventional rule and signature-based Web App...
Java middleware platforms expose powerful management functions through HTTP-accessible interfaces such as Jolokia. This article discusses the analysis of CVE-2023-50780 in Apache ActiveMQ Artemis by framing the vulnerability as a management-plane sta...
The field of pose estimation is a major problem in computer vision, enabling the direct transformation of an input image into a hierarchical representation of the human skeleton for application in the fields of virtual/augmented reality and human&nda...
Lung cancer is still one of the major contributors to cancer-related mortality. Treatment effectiveness depends directly on early diagnosis and accurate prediction of disease progression. This study focuses on the application of classical machine lea...
Industrial automation systems are increasingly cyber-physical, interconnected, and software-dependent, which expands both their operational capability and their cybersecurity exposure. This article reports a systematic literature review, conducted fo...
Ray tracing is a fundamental technique in computer graphics that requires highly efficient algorithms to achieve real-time rendering performance. A key bottleneck in this process is the traversal of Bounding Volume Hierarchies (BVHs). This paper intr...
The evolution of 5G networks has introduced new challenges in securing mobile infrastructures against increasingly sophisticated cyber threats. Intrusion detection in such environments has been widely studied using traditional datasets such as the Ca...
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that requires early and accurate diagnosis to improve patient outcomes. In this paper, an attention-enhanced hybrid deep learning (DL) framework is proposed that combines Conv...
Vaccination stands as a preeminent public health measure in the fight against infectious diseases, with a proven track record of significantly reducing morbidity and mortality rates. However, the presence of vaccine hesitancy and misinformation, part...
Precise segmentation of kidney tumors in medical images is crucial for diagnosis, treatment planning, and prognosis assessment. In this work, we present a newly proposed hybrid deep learning model that combines the merits of U-Net and the Swin Transf...
Building Information Modeling (BIM) implementation is increasingly adopted in the architecture, engineering, and construction (AEC) industries. However, its integration into the academic curricula in developing countries remains limited. Therefore, t...
Prioritizing product features is a crucial task for software startups due to scarce resources and rapidly changing markets. Existing prioritization approaches (for example, MoSCoW, Kano) are subjective and struggle to handle large sets of user feedba...
Federal post-quantum cryptography migration is scoped around three categories of cryptographic assets: libraries, protocols, and key stores. We argue that this scoping is incomplete. Cryptographic functions and key material can be realized in the par...
Recently, the volume of the generated data has increased significantly, leading to the need for computational techniques capable of handling such data efficiently. As a result, many quantum algorithms have been developed, and the domain of quantum ma...
The growing fragmentation of digital evidence in modern computing environments poses significant challenges for digital forensic analysis. Data is often deleted, overwritten, or distributed across heterogeneous platforms, limiting the effectiveness o...
Effective dementia care is often hindered by fragmented communication among patients, informal caregivers, and clinicians. To address this, we introduce an ambient assisted living (AAL) framework designed to establish a continuous, virtual, and unobt...
Detecting fake news is a challenging task and an important area of research for social media researchers. This task also involves clarifying accountability mechanisms that demonstrate the credibility of quotable sources, such as networks that documen...
The of personal computer (PC) tasks represents a systems-level challenge that integrates natural language processing, visual perception and mouse–keyboard action control. While existing approaches mainly focus on the application programming int...
Behavioural analytics remain a dominant approach for modelling learner engagement and predicting performance in digital learning environments. However, existing approaches are largely retrospective, relying on observable behavioural outcomes rather t...
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