2026 February-1 - 226 articles
The actual implementation of fifth-generation (5G) and beyond networks faces persistent challenges, including environmental interference and limited coverage, which compromise transmission stability and network feasibility. Reconfigurable Intelligent...
Wide-bandgap transistors have short voltage rise and fall times, thus leading to overvoltage at the end of the cable connecting the inverter and the motor. In this paper, the overvoltage reduction possibilities have been investigated analytically, ex...
The light-trap attraction rate (LTARI) is an important metric for characterizing diel activity patterns and supports studies in insect behavioral ecology and pest management. However, conventional automatic light-trap devices often rely on lethal met...
With the rapid advancement of Generative Adversarial Networks (GANs), diffusion models, and other deep generative techniques, AI-generated images have achieved unprecedented levels of visual realism, posing severe challenges to the authenticity, secu...
Advancements in Industry 4.0 technologies, which combine big data analytics, robotics, and intelligent decision systems to enable new ways to increase automation in the industrial sector, have undergone significant transformations. In this research,...
Firm requirements on electromagnetic compatibility (EMC) of electronic devices demand low electromagnetic emissions (EMI) of high-speed circuits, especially in the automotive industry. To be able to apply cost-effective anti-perturbative measures tha...
Deep learning methods have been extensively used for drug–drug interaction (DDI) prediction, aiding the development of effective and safe combination therapies. Most studies focus on either the internal molecular structure or external contextua...
The accurate estimation of shield attitude deviation is related to the quality of tunnel construction. However, the existing recurrent neural network (RNN)-based methods are unable to efficiently capture the spatial correlation between different time...
Texture image retrieval based on subjective visual descriptions remains a significant challenge due to the “semantic gap”, where conventional Content-Based Image Retrieval (CBIR) methods rely on low-level features or reference images that...
Domain Name System (DNS) tunneling, a stealthy attack that exploits DNS infrastructure, poses critical threats to dynamic networks and is evolving with emerging attack patterns. This study aims to accurately classify multi-pattern legitimate and mali...
The integration of renewable energy sources into modern power systems requires advanced control strategies to maintain stability, reliability, and efficiency. This paper presents a comprehensive review of the application of artificial intelligence te...
Modern passport systems face significant challenges in secure data sharing, real-time verification, and user-controlled authorization, particularly in cross-border scenarios. Existing digital passport solutions, often built on permissioned blockchain...
The LLC resonant converter constitutes a high-order switching system characterized by multiple operational modes and region-dependent switching sequences. This complexity poses significant challenges to system modeling and dynamic analysis. Furthermo...
Magnetically coupled resonant wireless power transfer (MC-WPT) systems with multi-relay coupling structures can significantly extend the transmission distance. However, system performance is highly sensitive to the spatial positions and coupling cond...
This paper presents the FPGA implementation and verification of a lightweight one-dimensional convolutional neural network (1D-CNN) pipeline for real-time battery state-of-charge (SoC) estimation in automotive battery management systems. The proposed...
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The present paper compares and analyzes the design of AES-128 encryption and decryption using Finite State Machine (FSM) architecture on FPGA and MATLAB platforms. This study aims to evaluate performance disparities in terms of execution time, throug...
Proton exchange membrane fuel cells (PEMFCs) are attractive energy sources for clean and efficient power generation; however, their nonlinear characteristics and sensitivity to operating condition variations make maximum power point tracking (MPPT) a...
In this paper, new fast algorithms for computing the discrete cosine transform type VI (DCT-VI) are proposed, with a special emphasis on short input sequences of three to eight samples. Fast algorithms for small discrete trigonometric transformations...
This paper proposes a multi-behavior and sequence-aware recommendation method that effectively integrates diverse user–item interaction behaviors and their sequential dependencies to enhance recommendation accuracy. Unlike existing studies that...
Accurate estimation of the state of charge (SOC) of lithium-ion batteries is critical for assessing the safety and remaining range of electric vehicles. However, due to the complex and variable operating environment of batteries and their highly nonl...
Graph attention improves neighbor discrimination, but it remains limited by local receptive fields and by a strong dependence on the input topology, which is often unreliable on heterophilous graphs. We propose Geometric Graph Learning Network (G2LNe...
Attribute-based encryption (ABE) is an advanced public key encryption mechanism that enables the precise control of access to encrypted data based on attributes assigned to users and data. Attribute-based access control (ABAC), which is built on ABE,...
Railway timetabling requires resolving complex scheduling conflicts arising from shared tracks, station capacity limits, and strict safety intervals. Existing optimization or learning-based approaches often struggle to scale or generalize across dive...
Reconfigurable intelligent surfaces (RISs) are an emerging wireless communication technology that has attracted significant attention, particularly in the field of physical layer security (PLS). This paper proposes a novel double-RIS-aided PLS commun...
In modern operating systems, CPU scheduling policy selection and evaluation still rely mainly on heuristic methods, especially at the single-processor level or the abstract ready-queue level, and there is still a lack of systematic modeling and inter...
The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and...
This paper addresses the growing need for reliable methods to evaluate the quality of artificial intelligence (AI) systems as they become widely used in both critical domains and everyday applications. The study aims to develop a metric-based approac...
As intelligent vehicle technologies evolve, reliable driver monitoring systems have become increasingly critical for ensuring the safety of human drivers and operational reliability. This paper proposes a novel visual computing framework for Driver F...
Advancements in energy storage systems (ESS) are important to attaining a sustainable and resilient energy future. Despite significant advancements in battery technologies, including lithium-ion, sodium-ion, and redox flow batteries, numerous problem...
Traditional power management for organic electroluminescent (OLED) displays is performed by two different converters, providing both positive and negative power rails and thus raising fabrication costs due to the usage of two inductors, in addition t...
Non-line-of-sight (NLOS) propagation remains a major obstacle to high-accuracy ultra-wideband (UWB) indoor positioning. To address this issue, this study investigates solutions from two complementary perspectives: NLOS identification and error mitiga...
Fifth-Generation (5G) communication systems necessitate highly integrated technologies to facilitate ultra-fast data rates, low latency, and compact system configurations. The realization of these objectives depends on the advancement of packaging te...
Today, the use of UASs (unmanned aerial systems) is rapidly expanding across civil, military, and scientific applications. The deployment of drones in close proximity to urban areas is becoming increasingly common, particularly during missions conduc...
Cybersecurity threats are evolving constantly, and the arrival of quantum computing raises serious doubts about whether today’s cryptographic methods will hold up over time. This concern has motivated interest in algorithms designed to resist f...
In today’s world, the demand for compact, high-efficiency, and low-cost motors plays a significant role in the design of low-power electric machines. In combi fan applications, single-phase brushless direct current (BLDC) motors are generally p...
With the increasing penetration of renewable energy sources and power-electronic devices, modern power systems exhibit pronounced wideband oscillation characteristics with large frequency spans, strong modal coupling, and significant time-varying beh...
Low-voltage AC series arc faults are a leading cause of electrical fires, posing significant risks to life and property. While artificial intelligence-based detection methods have achieved high accuracy, they often suffer from limited interpretabilit...
As the threat from malicious UAVs continues to intensify, accurate identification of individual UAVs has become a critical challenge in regulatory and security domains. Existing single-signal analysis methods suffer from limited recognition accuracy....
In this work, we present the design and evaluation of the X2000, a new development kit created to simplify and accelerate research for advanced driver-assistance systems (ADAS). The X2000 is a complete ADAS development kit for the Ford Mach-E. It inc...
This paper explores the feasibility of using acoustic wave propagation, particularly in the ultrasonic range, as a solution for data transmission in environments where traditional radio frequency (RF) communication is ineffective due to signal attenu...
A novel resonant-type defected ground structure (DGS) featuring a modified internal structure is proposed to enhance the suppression of cross-polarized (XP) radiation of rectangular microstrip antennas (RMAs) on slot-type DGS. Specifically, integrati...
Autonomous surface vehicles can support water-quality monitoring, but they require planners that place measurements where they most improve the environmental estimate under mission constraints. This paper proposes ACO-Path, an informative path planne...
This paper presents an all-digital fractional-N phase-locked loop (ADPLL) operating in the 2.86–3.2 GHz range, optimized for IoT and high-frequency RF transceiver applications demanding stringent phase noise performance, fast settling time, and...
The emergence of radio frequency machine learning has significantly propelled the application of deep learning (DL) methods in automatic modulation classification (AMC). However, under non-cooperative scenarios, the performance of DL-based AMC suffer...
Semiconductor manufacturing relies heavily on automatic test equipment (ATE), and yet thermal aging poses a critical risk to equipment reliability. This study proposes a novel anomaly detection framework for ATE driver boards by integrating cumulativ...
The increasing recognition within the infrastructure sector of the transformative potential of 3D point cloud data for civil structure management has prompted a growing interest. However, the inherent complexity of these data poses significant challe...
In this work, we present a Physics-Informed Neural Network (PINN) framework for the classification of oil palm fresh fruit bunch (FFB) ripeness using RGB images. Unlike conventional Convolutional Neural Networks (CNNs) that learn solely from visual p...
This paper introduces AdamN, a nested-momentum adaptive optimizer that replaces the single Exponential Moving Average (EMA) numerator in Adam/AdamW with a compounded EMA of gradients plus an EMA of that EMA, paired with an exact double-EMA bias corre...
Vehicle repositioning is essential for improving efficiency and service quality in ride-sharing platforms, yet existing approaches typically optimize proxy rewards that fail to reflect human-centered preferences such as wait time, service coverage, a...
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