2026 March-2 - 202 articles
The remaining useful life (RUL) prediction of lithium-ion batteries remains challenging for hybrid models due to high computational redundancy and hyperparameter sensitivity under complex operating conditions. To address these issues, this paper prop...
Heterogeneous multi-core systems (HMCSs) typically face a dilemma: heuristics (e.g., Linux CFS) are fast but blind to global constraints, while meta-heuristics (e.g., GAs) are globally optimal but too slow for real-time OS interaction. To bridge this...
Video action recognition faces persistent challenges in balancing accuracy with computational efficiency. While state space models, such as Mamba, have emerged with linear complexity advantages, they exhibit inefficiency in capturing critical spatiot...
The A* algorithm is widely used in path planning for Automated Guided Vehicles (AGVs), but the path it generates is prone to collision with random obstacles. To address this issue, this paper proposes a hybrid path planning algorithm integrating the...
Securing resource-constrained Industrial Internet of Things (IIoT) devices requires guarantees of integrity and confidentiality. This paper presents a security framework developed under the CERTIFY project to document and justify trustworthy executio...
Nowadays, Convolutional Neural Networks (CNNs) are the mainstream model in the bearing fault diagnosis area. Aiming at the problems of “incomplete capture of multiscale fault features and insufficient use of key time and frequency domain inform...
Can machine learning generate statistically validated alpha in equity markets while adapting to changing market conditions? This study addresses this question by proposing a regime-aware LightGBM framework conditioned on market regimes detected via a...
To address the challenge that prolonged interruptions of Global Navigation Satellite System (GNSS) signals—such as those caused by urban obstructions—hinder signal re-locking and thereby reduce the number of available satellites for integ...
Infrared–visible multimodal object detection has attracted increasing attention for its robustness under challenging conditions such as low illumination, occlusion, and complex backgrounds. However, existing fusion methods often suffer from coa...
Benggang (Benggang), a typical landform characterized by severe erosion and a geohazard in the red-soil hilly regions of southern China, is characterized by a fragmented texture, irregular boundaries, and high similarity to background objects such as...
Advances in semiconductor technologies, particularly in power transistors and switching diodes, have enabled higher switching frequencies and converter efficiency, renewing interest in Switched Reluctance Motors (SRMs) for electric vehicles. This wor...
The rapid progress of large language models (LLMs) has fostered the development of domain-specific variants in law, medicine, and finance. However, existing legal LLMs still struggle to generate contextually grounded and regulation-compliant response...
Viewport prediction is a key component in tile-based 360° video streaming. Existing viewport prediction models based on Long Short-term Memory Networks (LSTM) or Transformer typically output a single deterministic future trajectory through determ...
Although many multi-objective evolutionary algorithms (MOEAs) have been proposed, many-objective optimization problems (MaOPs) with more than three objectives remain difficult because convergence and diversity are hard to balance in high-dimensional...
Traffic flow prediction plays an important role in intelligent transportation systems. However, accurately modeling traffic dynamics remains challenging due to complex temporal correlations and spatial interactions across road networks. In this work,...
Accurate and fast junction-temperature estimation in Silicon Carbide (SiC) power modules is crucial for reliable operation, health monitoring and predictive control of power electronic converters in different applications. However, direct temperature...
This paper introduces a novel cascaded softsign function-based PID (CSoft-PID) controller designed for precise pressure regulation in highly nonlinear shell-and-tube steam condenser systems. For the first time in the literature, the classical PID con...
Consistency checking across independently developed implementations of the same industrial control protocol provides an effective signal for defect discovery because an implementation whose response deviates from the majority under identical inputs i...
Reliable video transmission over error-prone channels remains a significant challenge due to the inherent trade-off between compression efficiency and noise resilience in conventional systems. To address these issues, this paper introduces a novel qu...
Recent advancements in intelligent transportation systems have enabled smart vehicles to autonomously detect, predict, and respond to potential hazards in real time. However, achieving sub-second reaction performance remains challenging due to comput...
We propose Distribution-Preserving Latent Steganography via Conditional Optimal Transport (DPL-COT), a coverless image steganography framework for latent diffusion models. Unlike classical cover-modifying schemes, DPL-COT embeds a bitstream directly...
This study systematically examines the robustness of the Akaike Information Criterion (AIC) in determining the optimal order (p) of an autoregressive (AR) model applied to the RR interval time series of the PhysioNet healthy subject database. The AR...
Vulnerabilities in industrial control components (ICCs) can be exploited to launch attacks, potentially disrupting the operation of industrial control systems. Ensuring the security of such systems requires establishing explicit associations between...
Stock-ranking prediction is an important task in quantitative finance because it directly influences portfolio construction and alpha generation. Recent Graph Neural Network (GNN) models provide a promising way to describe inter-stock dependencies, b...
To address the challenges of reduced delivery efficiency, complex routing decisions, and limited system robustness in cooperative transportation involving a single drone and an autonomous vehicle under dynamic weather conditions, this study investiga...
Indigenous cultures in Taiwan embody rich ecological knowledge and strong environmental conservation values. However, elementary and secondary education often provides limited exposure to these cultures due to geographic constraints and insufficient...
Existing standards for distribution network safety under combined typhoon–rain hazards often overlook the nonlinear coupling effects induced by rain impact. To address this issue, this paper proposes a refined modeling and threshold-based failu...
With the widespread integration of smart buildings equipped with distributed photovoltaics (PV) and electric vehicles (EVs), distribution networks face significant challenges arising from source-load fluctuations. Conventional centralized dispatch ap...
Low-power NPUs enable on-device LLM inference through efficient integer and fixed-point algebra, yet their lack of native exponential support makes Transformer softmax a critical performance bottleneck. Existing NPU kernels approximate
High noise levels in industrial workplaces pose significant challenges to occupational safety, particularly with hearing protection and effective communication. Traditional hearing protection devices, while effectively attenuating harmful noise, ofte...
This paper presents an ultra-miniaturized and high-quality factor embedded loaded coaxial substrate integrated waveguide (ELCSIW) filter. Integrating a substrate-integrated coaxial resonator with a capacitively loaded air cavity achieves a 99% reduct...
Radio Frequency Fingerprinting (RFF) would be a promising Physical Layer Security (PLS) solution for the Internet of Things (IoT) that requires robust, low-overhead security techniques. However, practical implementation of RFF may pose challenges, in...
Traffic accidents are among the leading causes of injury worldwide, highlighting the urgent need to better understand the factors that contribute to accident occurrence and severity in order to improve road safety and reduce injuries and fatalities....
This paper presents a quadruple step-down (QSD) trans-inductor voltage regulator (TLVR) converter to accommodate the high-current and fast-transient requirements of processor power supplies. Evolved from dual-step-down (DSD) topology, the QSD configu...
Security organizations increasingly rely on cyber threat intelligence (CTI) sharing to enhance their resilience against cyberattacks. Indicators of Compromise (IoCs) play a critical operational role in CTI by providing malicious artifacts that suppor...
Indoor pedestrian navigation tasks, as a key part of smart cities and navigation services, face dual challenges of accuracy and cost under complex building environments. Currently, neural inertial navigation is at the vanguard of current research in...
This paper presents a dual-phase dual-path hybrid buck–boost (DPBB) converter with an offset-controlled zero-current detector for Li-ion battery applications. Compared with inductive buck–boost converters, the proposed hybrid converter ha...
Bundle recommendation has gained significant attention, but it faces two key challenges: sparse interaction data and complex UB, UI, and BI relations. Recent work uses multi-view contrastive learning, yet current frameworks rely on fixed-weight fusio...
Large-scale Virtual Power Plants (VPPs) are increasingly essential as Distributed Energy Resources (DERs) assume ancillary service duties once supplied by conventional generation, yet scaling a VPP exposes a persistent trilemma among economic efficie...
A monolithic digital Silicon Photomultiplier (SiPM) featuring 1024 microcells with a 30-micrometer pitch and a 50% fill factor has been designed in a 110-nanometer CMOS image sensor technology. The device under consideration integrates both SPAD sens...
Building extraction is a core task in the semantic segmentation of satellite remote sensing imagery. Conventional pixel-level segmentation methods often prioritize texture over geometric structure, resulting in suboptimal performance in complex scene...
Modern computing platforms increasingly rely on random number generators (RNGs) for modeling probabilistic processes in simulation, probabilistic computing, and system validation. They are also essential for cryptographic operations such as key gener...
To tackle the degraded stability and non-smooth mode transitions under wide-range grid-strength variations with high renewable penetration, an adaptive fusion and disturbance-free switching control strategy is proposed, where parameter stability regi...
To address the state-of-charge (SOC) imbalance and the limited convergence speed of conventional SOC balancing strategies in cascaded power conversion systems (PCSs) under practical grid-connected conditions, this paper investigates the control of ca...
Spiking neural networks are promising for energy-efficient edge intelligence, but mapping 1-bit spikes onto high-precision vector datapaths leads to underutilization and low compute density. This paper presents DeVSA, a 16-lane vector SNN accelerator...
Artificial intelligence (AI) is propelling space exploration into a new era. Synergistic breakthroughs in chip design and high-speed communications have facilitated the large-scale deployment of on-board satellite computing. Assessing the reliability...
Traditional craft education relies heavily on hands-on practice; however, novice learners often struggle with procedural complexity, material behavior, and the tacit knowledge typically transmitted through prolonged apprenticeship. This paper present...
Diffusion models have emerged as a powerful class of generative models, demonstrating impressive results across visual domains such as image and video synthesis. This survey provides a comprehensive taxonomy of generative models, with a particular fo...
Federated recommender systems (FRS) enable privacy-preserving collaborative training without sharing raw user data, while explainable recommender systems (XRS) aim to improve transparency, trust, and accountability. However, research that integrates...
Generative adversarial networks (GANs) are increasingly applied to mitigate extreme class imbalance in intrusion detection systems, yet reported improvements often obscure role augmentation intensity and adversarial stability. This paper presents a c...
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