2025 July-1 - 240 articles
The growing sophistication of malware and other cyber threats presents significant challenges for detection and prevention in modern cybersecurity systems. In this paper an efficient and novel malware classification model using the Hybrid Resnet-Tran...
In order to accurately grasp the operational state of DC protection devices in converter stations, a DC protection device state assessment method based on the variable weight theory and correlation degree analysis is proposed. Constructing condition...
In recent years, near-field networks have become a vital part of smart grids, raising growing concerns about their security. Studying threat evolution mechanisms is key to building proactive defense systems, while early identification of threats enha...
In recent years, with the rapid development of science and technology and the substantial improvement of computing power, various deep learning research topics have been promoted. However, existing autonomous driving technologies still face significa...
This study introduces a stochastic optimization framework designed to effectively manage power flows in flexible medium-voltage DC (MVDC) link systems within distribution networks (DNs). The proposed approach operates in coordination with a battery e...
Label Distribution Learning (LDL) has emerged as a powerful paradigm for addressing label ambiguity, offering a more nuanced quantification of the instance–label relationship compared to traditional single-label and multi-label learning approac...
Evaluating the coherence of narrative sequences extracted from large document collections is crucial for applications in information retrieval and knowledge discovery. While mathematical coherence metrics based on embedding similarities provide objec...
Beamforming plays a key role in improving the spectrum utilization efficiency of multi-antenna systems. However, we observe that (i) conventional beam prediction solutions suffer from high model training overhead and computational latency and thus ca...
To address the limitations of single-modality UWB/IMU systems in complex indoor environments, this study proposes a multimodal fusion localization method based on xLSTM. After extracting features from UWB and IMU data, the xLSTM network enables deep...
As the number of IoT (Internet of Things) devices continues to grow at an exceptional rate, so does the variety of use cases and operating environments. IoT now plays a crucial role in areas including smart cities, medicine and smart agriculture, whe...
Gamification has the potential to significantly enhance student engagement and motivation in educational contexts. However, there is a lack of empirical research that compares different guiding strategies between AI-driven gamified and non-gamified m...
In this study, a terahertz microfluidic multi-band sensor was designed. Unlike previous microfluidic absorption sensors that rely on dipole resonance, the proposed sensor uses a physical mechanism for absorption by exciting higher-order lattice reson...
Electromagnetic interference (EMI) has become a significant issue as electronic devices become more integrated and achieve high performance. In order to operate at high performance in an integrated system, a high-frequency clock signal is essential t...
The application of self-supervised learning (SSL) is increasingly imperative for advancing wireless communication technologies, particularly in scenarios with limited labeled data. Traditional data-augmentation-based SSL methods have struggled to acc...
Despite the advantages of using cloud computing, data breaches and security challenges remain, especially when dealing with sensitive information. The integration of deep learning (DL) techniques in a cloud environment ensures privacy preservation. T...
This study presents a cooperative unmanned aerial system (UAS) designed to enable precise autonomous landings in unstructured environments using low-cost onboard vision technology. This approach involves a carrier UAV with a stabilized RGB camera and...
Although the Power Internet of Things (PIoT) significantly improves operational efficiency by enabling real-time monitoring, intelligent control, and predictive maintenance across the grid, its inherently open and deeply interconnected cyber-physical...
Optical networks today constitute the fundamental backbone infrastructure of telecom and cloud operators. A possible medium-term solution to address the enormous increase in traffic demands faced by these operators is to rely on Super C+ L transmissi...
Backdoor attacks in self-supervised learning pose an increasing threat. Recent studies have shown that knowledge distillation can mitigate these attacks by altering feature representations. In response, we propose BASK, a novel backdoor attack that r...
To deal with the interphase circulating-current problem of modular multilevel converters (MMCs) in multiphase wind power systems, a cooperative circulating-current suppression strategy based on a second-order generalized integrator (SOGI) and passivi...
Recently, active impedance inverters based on non-Foster negative capacitors have been proposed for applications in widely tunable filters. These designs use a traditional Linvill’s topology of the negative capacitor. Unfortunately, the range o...
This paper proposes a general workflow for collecting and analyzing open data from Bicycle Sharing Systems (BSSs) that was developed using data from the Valenbisi system, operated in Valencia by the French company JCDecaux; however, the stages of the...
For data-intensive applications like edge AI and image processing, we present a new reconfigurable 8T SRAM-based in-memory computing (IMC) macro designed for high-performance and energy-efficient operation. This architecture mitigates von Neumann lim...
Energy consumption has emerged as a critical design constraint in deploying high-performance neural networks, especially on edge devices with limited power resources. In this paper, a comparative study is conducted for two prevalent deep learning par...
Ensuring the trustworthiness of artificial intelligence (AI) systems is critical as they become increasingly integrated into domains like healthcare, finance, and public administration. This paper explores frameworks and metrics for evaluating AI tru...
We propose the Deformable and Dilated Feature Fusion Module (D2FM) in this paper to enhance the adaptability and flexibility of feature extraction in object detection tasks. Unlike traditional convolutions and Deformable Convolutional Networks (DCNs)...
Geostationary Earth orbit (GEO) satellite communication systems have become increasingly significant in global communication networks and national strategic infrastructure, owing to their advantages of extensive coverage, high capacity, and robust re...
With the vigorous development of Internet of Things technologies, Cell-Free Radio Access Network (CF-RAN), leveraging its distributed coverage and single/multi-antenna Access Point (AP) coordination advantages, has become a key technology for support...
This paper presents the design and implementation of an autonomous robotic facility for textile sorting and recycling, leveraging advanced computer vision and machine learning technologies. The system enables real-time textile classification, localiz...
This paper explores an event-triggered load frequency control (LFC) strategy for smart grids incorporating electric vehicles (EVs) under the influence of random deception attacks. The aggressive attack signals are launched over the channels between t...
Single-frequency global navigation satellite system/inertial navigation system (GNSS/INS) integration has wide application prospects in urban environments; however, correct integer ambiguity is the major challenge because of GNSS-blocked environments...
The proliferation of mobile devices has generated exponential data growth, driving efforts to extract value. However, mobile data often presents non-independent and identically distributed (non-IID) challenges owing to varying device, environmental,...
Non-orthogonal multiple access (NOMA) is a multiple access scheme using superposition coding (SC) and successive interference cancellation (SIC). Recently, a lossless NOMA implementation without SIC was proposed using correlated SC (CSC), namely, the...
This study investigates the evolution and prospective directions of big data applications within the global digital economy over the past twelve years. A comprehensive bibliometric analysis was conducted using Biblioshiny and included 752 documents a...
Millimeter-wave (mmWave) antennas and antenna arrays have gained significant attention due to their pivotal role in emerging wireless communication, sensing, and imaging technologies. With the rapid deployment of 5G and the transition toward 6G netwo...
Swarm-based unmanned aerial vehicle (UAV) systems offer enhanced spatial coverage, collaborative intelligence, and mission scalability for various applications, including environmental monitoring and emergency response. However, their onboard process...
To address the dual challenges of achieving high classification accuracy and real-time performance when detecting abnormal traffic in cloud environments, this study introduces an improved lightweight real-time detection model, IM-MobileNetV3. By stan...
This paper examines near-term generative large language models (GenLLM) for cybersecurity applications. We experimentally study three common use cases, namely the use of GenLLM as a digital assistant, analysts for threat hunting and incident response...
The increasing integration of digital technologies in healthcare has expanded the attack surface for privacy violations in critical systems such as electronic health records (EHRs), telehealth platforms, and medical device software. However, current...
Frequent and complex boarding operations require an effective management process for specialized tools. Traditional manual statistical analysis exhibits low efficiency, poor accuracy, and a lack of electronic records, making it difficult to meet the...
The temperature of a power inductor operated up to saturation in a DC/DC converter is estimated based on its current profile. A dataset built by a proper model of the non-linear inductor was generated, reproducing its current profiles in different op...
This study presents a convolutional neural network (CNN)-based feature-scheduling aggregation clustering framework designed to address the limitations of conventional clustering algorithms in handling high-dimensional data structures. The proposed fr...
Automated font generation for complex, compositional scripts like Korean Hangul presents a significant challenge due to the 11,172 characters and their complicated component-based structure. While existing component-based methods for font image gener...
Next-generation smart sensing devices necessitate on-chip integration of power-efficient reference circuits. The latters are required to provide other circuit blocks with highly reliable bias signals, even in the presence of temperature shifts and su...
Frequency-modulated continuous-wave (FMCW) LiDAR systems frequently experience noise interference during multi-target measurements in real-world applications, resulting in target overlapping and diminished detection accuracy. Conventional denoising a...
The increasing threat of quantum computing to traditional cryptographic systems has prompted intense research into post-quantum schemes. Despite SNOVA’s potential for lightweight and secure digital signatures, its performance on embedded device...
In the last decade, countries have experienced increased solar radiation, leading to an increase in the use of solar photovoltaic (PV) systems to boost renewable energy generation. However, the high solar penetration into these systems can disrupt th...
Efficient procurement processes are pivotal for strategic performance in digital organizations, requiring continuous refinement driven by automation, integration, and performance monitoring. This research investigates and demonstrates the potential f...
To solve the problem of the limited capability of multimodal image feature descriptors constructed by gradient information and the phase consistency principle, a method of cumulative structure feature descriptor construction with rotation invariance...
A modified dual hierarchical terminal sliding mode control (MDHTSMC) strategy is developed in this study for the control of a two-wheeled self-balancing robot (TWSBR). The control framework incorporates individually designed sliding surfaces within a...
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