2026 February-2 - 188 articles
To address the degradation in he ranging accuracy of phase-sensitive radar systems caused by RF front-end group delay mismatch, this paper establishes a nonlinear group delay interference model. Using Monte Carlo simulations, we derive the group dela...
Satellite–terrestrial spectrum sensing plays a crucial role in enhancing spectrum efficiency through reusing spectra. However, in a satellite–terrestrial converged system, the large SNR range, non-Gaussian signal characteristics and noise...
Physical layer security (PLS) is a fundamental challenge for sixth-generation (6G) wireless networks, particularly in integrated sensing and communication (ISAC) systems, where sensing targets may simultaneously act as potential eavesdroppers. In thi...
Large language models (LLMs) are increasingly used in software development, yet their ability to generate and maintain large, multi-module systems through natural language interaction remains insufficiently characterized. This study presents an empir...
This paper studies the problem of cold-start recommendation with graph contrastive learning. Graph contrastive learning has achieved state-of-the-art performance for the recommendation. However, it lacks robustness in cold-start scenarios due to nois...
Median crossover crashes are among the most severe roadway safety events due to their high-energy nature and strong association with fatal and incapacitating injuries, posing a substantial public health burden. This study develops a multimodal intell...
During high-speed cornering, the motion accuracy and efficiency of SCARA robots are often compromised by residual vibrations and cornering errors. Conventional control methods often fail to address these two coupled problems simultaneously. Therefore...
To address the limitations of traditional rolling bearing fault diagnosis methods—such as inadequate feature extraction, limited noise robustness, and weak generalization under variable working environments—this study proposes a fault dia...
In the field of electronic support and radar warning, it is necessary to effectively detect and recognize the modulation types of non-cooperative radar signals, especially for radars with Low Probability of Intercept (LPI) waveforms. Multiple intelli...
DC–DC converters have become a key component in the structure of renewable energy systems, where an interface to increase and regulate the output voltage is required. This paper presents a modular non-isolated topology that achieves high voltag...
This paper proposes an advanced three-dimensional optical encryption technique based on double random phase encryption for the simultaneous encryption of two primary datasets. While conventional double random phase encryption offers high-speed encryp...
With the increasing demand for heavy-haul railway freight, both the number and volume of heavy-haul freight cars continue to grow. As the core system of railway freight transportation, the reliable operation of the brake system is fundamental to ensu...
Ground-penetrating radar (GPR) is a key non-destructive technique for subsurface reconstruction, widely valued for its ability to image buried structures without disruption. Among its various implementations, vehicle-mounted GPR has emerged as partic...
The proliferation of unsolicited short messages (SMS spam) poses persistent challenges to mobile communication security and user privacy. This study presents a systematic benchmarking and analytical investigation of classical machine learning approac...
This paper discusses a multimodal AI system applied to legal reasoning for tax law. The results given here are very general and apply to systems developed for other areas besides tax law. A central goal of this work is to gain a better understanding...
With the rapid evolution of Generative Adversarial Networks (GANs) and diffusion models (DMs), the detection of synthetic images faces significant challenges due to non-rigid artifacts and complex frequency biases. In this paper, we propose SIDWA, a...
Traditional ergonomic considerations in human–machine and human–swarm systems have primarily relied on static diagnostic snapshots, which often fail to capture the temporal accumulation and non-linear dissipation of musculoskeletal fatigu...
Electromagnetic compatibility (EMC) diagnostics for high-density through-silicon via (TSV)-based chips face significant challenges due to complex three-dimensional electromagnetic coupling and inefficient source reconstruction workflows. This paper p...
The rapid evolution of Generative AI (GenAI) has created the conditions for developing innovative solutions that disrupt all fields of human-related activities. Within the healthcare sector, numerous AI-driven applications have emerged, offering comp...
Object detection, as a fundamental task, forms the cornerstone of intelligent applications in both UAV surveillance and satellite remote sensing. While most prior works concentrate on solving object scale and rotation angle variance caused by altitud...
Semi-supervised medical image segmentation has recently achieved great success, but assigning trustworthy pseudo-labels to unlabeled images has been a difficult problem in medical image processing. A common solution is to select reliable predicted pi...
Monitoring behavioural drift, a sustained shift in an individual’s daily activity, sleep, or social patterns, offers a significant lens for early mental health intervention. However, detecting these drifts in free-living settings remains challe...
As the smart home ecosystem expands with the adoption of Matter, a wide variety of Internet of Things (IoT) devices are entering the market, and these devices are becoming more complex, as they support diverse functionalities. Consequently, smart hom...
This paper presents the design and experimental evaluation of a bio-inspired gecko robot, focusing on mechanical design, vision-based obstacle perception, and rhythmic locomotion control as enabling technologies for future obstacle avoidance in compl...
Class imbalance in tabular datasets poses a challenge for machine learning classification tasks, often leading to biased models that underperform in predicting minority class instances. This study presents a comparative analysis of synthetic data gen...
Wildfire events are increasing in frequency and severity, creating an urgent need for early, accurate, and energy-efficient forest fire prediction systems that can operate at a large scale. A fundamental challenge in edge-level forest fire prediction...
A significant bottleneck for the practical deployment of fluid antenna systems (FASs) in 6G high-mobility scenarios is the conflicting demands of low outage probability and the high overhead of full port channel estimation. To resolve this problem, a...
Superconducting electrodynamic suspension (EDS) maglev technology has strong potential for ultra-high-speed transportation, with advantages such as self-stability and a large suspension gap. The magneto-electric force relationship between the onboard...
Optical networks constitute the backbone of contemporary communication infrastructures, supporting massive bandwidth, low-latency services, and high levels of scalability across core, metro, and access domains. As these systems evolve toward elastic,...
Current generative AI systems primarily utilize a prompt–response interaction model that restricts user intervention during the creative process. This lack of granular control creates a significant disconnect between user intent and machine out...
Traditional multiple-input multiple-output (MIMO) systems are confronted with significant challenges in realizing ubiquitous connectivity for sixth-generation (6G) networks, particularly in environments characterized by severe signal blockage and dyn...
The digital world has witnessed an unparalleled surge in social online gaming platforms, with Roblox standing out as a prominent platform that predominantly attracts younger users. Unfortunately, these gaming platforms are also targeted by malicious...
Existing methods for power load anomaly detection suffer from several limitations, including insufficient extraction of multi-scale temporal features, difficulty in capturing long-range dependencies, and inefficient fusion of heterogeneous Time-Graph...
With the advancement of smart education and carbon neutrality goals, optimizing Indoor Environmental Quality (IEQ) while minimizing energy consumption is critical. Traditional PID or rule-based strategies struggle with the strong non-linearity and ti...
This paper presents a comprehensive experimental study addressing the lack of consistent low-temperature data on magnetic materials for high-efficiency cryogenic power electronics. A unified dataset is provided for the first time, covering temperatur...
Intrusion detection systems face challenges in processing high-volume network traffic while maintaining accuracy across diverse low volume attack types. This study presents a hybrid approach combining ARIMA time series forecasting with Decision Tree...
Large language models (LLMs) with the Transformer architecture as the core have made significant progress in the field of natural language processing, and their application value in English teaching has also attracted much attention. In tasks such as...
Infrared small target detection under complex backgrounds remains challenging due to the extremely small target size and low contrast with the surrounding background. These factors make contour information difficult to extract and often cause target...
Iterative self-training of language models presents a promising avenue for realizing self-improving Artificial Intelligence systems; however, this process is often hindered by the fundamental challenge of “Model Collapse.” Existing resear...
Real-time semantic segmentation has been widely adopted in resource-constrained applications such as mobile devices, autonomous driving, and drones due to its high efficiency. However, existing lightweight networks often compromise segmentation accur...
Low-Power Wide-Area Network (LPWAN) technologies play a central role in large-scale wireless sensor network (WSN) deployments, where energy efficiency, coverage and reliability dominate over throughput. Among them, Long Range (LoRa) technology has em...
The rapid deployment of electric vehicle (EV) charging infrastructure, coupled with the integration of 5G/6G and Internet of Vehicles (IoV) technologies, has transformed charging stations into cyber–physical systems that rely on wireless commun...
The accurate labeling of darknet traffic plays a vital role in real-time cybersecurity systems, as it enables the reliable identification and control of encrypted network applications. State-of-the-art studies have depended mainly on traditional mach...
Health Internet of Things (Health IoT) systems continuously stream sensitive physiological data, making data access governance safety-critical under conflicting objectives such as privacy risk, latency, energy/resource cost, and robustness, especiall...
Propelled by the “dual-carbon” strategy, green and intelligent ports are rapidly advancing toward low-carbon and intelligent development. However, the large-scale incorporation of renewable energy and the extensive electrification of tran...
Skin-lesion recognition from clinical photographs is clinically valuable yet computationally challenging due to large intra-class variation, subtle inter-class boundaries, class imbalance, and heterogeneous acquisition conditions. To address these co...
TMR-based magnetic encoders provide sensitive SIN/COS signals, but practical accuracy is degraded by channel mismatch and decoder dynamics. This study evaluates an end-to-end embedded implementation on a PMSM (Permanent Magnet Synchronous Motor) benc...
City-scale forecasting is essential for both electric-vehicle (EV) charging operations (e.g., peak management and resource allocation) and urban mobility management (e.g., road-network flow monitoring and incident response). Spatio-temporal graph neu...
Based on the electron cyclotron maser instability, gyrotrons are capable of generating high-power electromagnetic vortex waves. In conventional axisymmetric configurations, the electron beam typically lifts the azimuthal degeneracy between co-rotatin...
This paper presents a constraint-aware and systematic methodology for the design of LCL filters in grid-connected electric vehicle (EV) fast chargers. The proposed step-by-step process provides analytical sizing equations for the passive components
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