2026 January-1 - 248 articles
Insider threats remain a serious concern for organisations in both public and private sectors. Detecting anomalous behaviour in enterprise environments is critical for preventing insider incidents. While many prior studies demonstrate promising resul...
To address the energy limitations, long-term operation demands, and load imbalance in fragment velocity measurement wireless sensor networks, this paper proposes an Energy-Balanced and Stability-Oriented Grey Wolf Optimization (EBSIGWO) algorithm. Th...
This work advances a 6G-ready, micro-granular SDN fabric that unifies high-performance edge data planes with intent-driven, multi-domain orchestration and cloud offloading. First, edge and cell-site whiteboxes are upgraded with Smart Network Interfac...
Reliable occluded object detection remains a persistent core challenge for autonomous driving perception systems, particularly in complex urban scenarios where targets are predominantly partially or fully obscured by static obstacles or dynamic agent...
The existing methods used for estimating generator matrixes of BCH codes, which are based on Galois Field Fourier transforms, need to exhaustively test all the possible codeword lengths and corresponding primitive polynomials. With the increase of co...
Virtual synchronous machine (VSG) technology provides a robust framework for integrating electric vehicle energy storage into modern microgrids. Nonetheless, conventional VSG control often suffers from intense interaction between active and reactive...
With the rapid evolution of cloud-native platforms, microservice-based systems have become increasingly large-scale and complex, making fast and accurate root cause localization and recovery a critical challenge. Runtime signals in such systems are i...
Large-scale disasters such as earthquakes and floods often cause the collapse of terrestrial communication networks, isolating affected communities and disrupting rescue coordination. Unmanned aerial vehicles (UAVs) can serve as rapid-deployment aeri...
Wireless medical sensor networks (WMSNs) have evolved alongside the development of communication systems, and the integration of cloud computing has enabled scalable and efficient medical data management. However, since the messages in WMSNs are tran...
Text-to-Speech (TTS) methods typically employ a sequential approach with an Acoustic Model (AM) and a vocoder, using a Mel spectrogram as an intermediate representation. However, in home environments, TTS systems often struggle with issues such as in...
The rapid development of artificial intelligence is reshaping learning concepts and instructional practices. Online learning overcomes temporal and spatial constraints, providing flexible and autonomous learning environments, and has become a central...
As the number of feature dimensions increases, the decision-making space exhibits extensive and discrete characteristics, which poses a severe challenge to multi-objective (MO) evolutionary algorithms when searching for the optimal feature subset. Ma...
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across vision–language tasks, yet their safety alignment remains vulnerable to adversarial manipulation. Existing jailbreak attacks typically optimize adversaria...
With the widespread deployment of the Advanced Metering Infrastructure (AMI) in Power Industrial Control Systems (PICS), a significant and inherent property of network traffic data is its pronounced class imbalance. The continuous emergence of new ty...
In this paper, low-pass corrugated filters based on half-mode groove gap waveguide (HMGGW) technology are proposed for the first time. The design process starts from the equivalent classical low-pass implementation in corrugated rectangular waveguide...
Single-phase-to-ground faults occur frequently in distribution networks, while traditional localization methods have limitations such as insufficient feature extraction and poor topological adaptability. To address these issues, this paper proposes a...
The high energy consumption and substantial electricity costs of cloud data centers pose significant challenges related to carbon emissions and operational expenses for service providers. The temporal variability of electricity pricing in real-world...
Accurate multivariate traffic flow forecasting is critical for intelligent transportation systems yet remains challenging due to the complex interplay of temporal dynamics and spatial interactions. While Transformer-based models have shown promise in...
Existing inspection systems for railway point machines often suffer from high latency and poor interpretability, which impedes the real-time detection of critical mechanical anomalies, thereby increasing the risks of derailment and leading to cascadi...
In this paper, the influences of leakage inductances are investigated for the integrated transformer of an input-series flyback converter, in which each input-series circuit is based on the single-switch flyback topology. First, the configuration of...
This paper proposes a symmetrized extrinsic information transfer (S-EXIT) chart analysis for probabilistic shaped (PS) systems to optimize the joint decoding of low-density parity-check (LDPC) codes and constant composition distribution matchers (CCD...
Network function virtualization (NFV) is an emerging technology that is gaining popularity for network function migration. NFV converts a network function from a dedicated hardware device into a virtual network function (VNF), thereby improving the a...
With the growing penetration of wind energy into modern power grids, the demand for high-performance converter control has increased significantly. In particular, precise current reference tracking is essential to guarantee efficient energy conversio...
Augmented reality (AR) has emerged as a transformative technology, allowing users to engage with digital content overlaid on the physical world. In the construction industry, AR shows significant potential to enhance visualization, collaboration, tra...
Dynamic objects present a major challenge for visual simultaneous localization and mapping (Visual SLAM), as feature measurements originating from moving regions can corrupt camera pose estimation and lead to inaccurate maps. In this paper, we propos...
Road marking lines can be extracted from aerial images using semantic segmentation (SS) models; however, in this work, a conditional generative adversarial network, RoadMark-cGAN, is proposed for direct extraction of these representations with image-...
Knowledge graph completion (KGC) necessitates comprehensive modeling of heterogeneous relations by effectively integrating both graph structural information and textual semantics. Current approaches often exhibit fragmented feature utilization or sub...
The swift development of digital financial services has increased transaction volumes and heightened system performance requirements. Cardless cash deposit transactions at PT Bank XYZ have significantly increased since 2022. This growth necessitates...
Brain age has been widely recognized as an important biomarker for monitoring adolescent brain development and assessing dementia risk. However, existing model visualization methods primarily highlight brain regions associated with aging, making it d...
Following the persistent evolution of terrestrial 5G wireless systems, a new field of underwater communication has emerged for various related applications like environmental monitoring, underwater mining, and marine research. However, establishing r...
Effective knowledge management is critical for preserving institutional expertise and improving the efficiency of workforce training in state transportation agencies. Traditional approaches, such as static documentation, classroom-based instruction,...
This work presents a unified benchmarking framework for evaluating classical machine-learning–based heart-rate estimation from remote photoplethysmography (rPPG) across both RGB and near-infrared (NIR) modalities. Despite extensive research on...
Recently, image haze removal has gained increasing attention in the field of image restoration. Data-driven and model-based methods are popular among researchers. The dark channel prior prevails in model-based methods, where the model parameters, atm...
In this paper, a novel 8-bit approximate multiplier, called INVCAM, is proposed in which the inverted partial products (PPs) are summed using approximate 4:2 compressors. This design allows for flexibility in applying approximations, enabling the mul...
The designs of lossless data compression architectures create a natural trade-off between throughput, power consumption, and compression efficiency, making it difficult for designers to identify an optimal configuration that satisfies all three crite...
The overall energy efficiency of a multi-compressor system varies greatly depending on its operating strategy. In most industrial facilities, the strategy is still determined empirically by operators, which often fails to achieve optimal energy effic...
Deep anomaly detection in multilingual environments remains challenging due to limited labeled data, semantic inconsistency across languages, and the unstable distribution of rare abnormal patterns. These challenges are particularly severe in low-res...
Low-altitude Unmanned Aerial Vehicle (UAV) detection using LiDAR range images faces persistent challenges. These include sparse features for long-range targets, large scale variations caused by viewpoint changes, and severe interference from complex...
Laser pulses are essential in various scientific fields, yet existing laser diode drivers offer limited adjustability. This paper presents a digitally adjustable subnanosecond gain-switched laser diode driver, a first one with step sizes of the contr...
Pipelines are critical infrastructures in both industrial production and daily life. However, defects frequently arise due to environmental and manufacturing factors, which may lead to severe safety risks. To overcome the limitations of traditional o...
Faults in chiller systems can significantly reduce energy efficiency and operational performance. To address this, fault detection and diagnosis (FDD) algorithms are increasingly integrated into building management systems (BMS). This study proposes...
Discrete cosine transforms (DCTs) are widely used in intelligent electronic systems for storing, processing, and transmitting data. Their popularity stems, on the one hand, from their unique properties and, on the other hand, from the availability of...
Spoofing attacks remain among the most critical security threats in Connected and Autonomous Vehicles (CAVs). This work introduces a lightweight, two-level spoofing detection framework based on Kalman filtering, designed for real-time deployment in v...
Near-infrared spectroscopy (NIRS) is widely used in food, pharmaceutical, and agricultural analyses but is highly susceptible to noise. To address this, we propose BiLSTM-FuseNet, a denoising framework that combines temporal modeling and explicit noi...
Weak-signal fluorescence channels (e.g., 4′,6-diamidino-2-phenylindole (DAPI)) often fail to provide reliable structural details due to low signal-to-noise ratio (SNR) and insufficient high-frequency information, limiting the ability of single-...
Dynamic task planning for heterogeneous platforms across land, sea, air, and space is essential for achieving integrated situational awareness, yet current systems suffer from limited spatiotemporal coverage and inefficient resource scheduling. To ad...
Based on a large-signal chip model, this paper designs and implements an L-band broadband continuous-wave 400 W high-efficiency power amplifier fabricated using 0.5 μm GaN High Electron Mobility Transistor (HEMT) technology. The input-matching cir...
Stress has become one of the most pervasive health challenges in modern societies, contributing to cardiovascular, cognitive, and emotional disorders that degrade overall well-being and productivity. Continuous monitoring of stress in everyday settin...
Recognizing human actions in low-light industrial environments remains a significant challenge for safety-critical applications in power systems. In this paper, we propose a Low-Light Pose-Action Collaborative Network (LPAC-Net), an integrated framew...
A novel wideband 1-bit reconfigurable transmitarray (RTA) is proposed, which is based on a substrate-integrated cavity-backed patch (SCIBP) element. The RTA element consists of a pair of SCIBP antennas, achieving wideband operational capability throu...
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