Electronics, Volume 13, Issue 24

The Equilibrium Optimizer (EO) is an optimization algorithm inspired by a physical law called mass balance, which represents the amount of mass entering, leaving, and being produced in a control volume. Although the EO is a well-accepted and successf...

With the rapid development of blockchain technology and the popularity of cryptocurrency, phishing scams pose an increasingly severe threat to the security of cryptocurrency transactions. Existing fraud detection methods have not accurately identifie...

This study explores the potential of heterogeneous hybrid Free Space Optical (FSO) and Radio Frequency (RF) cognitive networks, which feature both cooperative and economic systems. The cooperative system is defined as a heterogeneous network where th...

Energy-intensive enterprises (EIEs), as vital demand-side flexibility resources, can significantly enhance the power system’s ability to regulate demand by participating in demand response (DR). This helps alleviate supply pressures during tigh...

This paper presented an extended double-subsegment discrete Fourier transform (DS-DFT) algorithm as a tool for the fine spectral estimation of high-noise environments, which was previously effective in low-noise scenarios, and as such, its applicatio...

The subject of this paper is the development of rationalized algorithms of discrete sinusoidal transform of type I for short sequences of length N = 2, 3, 4, 5, 6, 7, and 8. Here, by the word “rationalization”, we mean the reduction of th...

The main shaft of a wind turbine is a critical component that ensures the normal operation of the turbine, and its axial displacement directly impacts its efficiency and safety. The inaccurate measurement of axial displacement may lead to severe issu...

In the face of increasingly complex application scenarios, there is an urgent need for (Radio Frequency Identification) RFID systems that are capable of accurately identifying microwave signals of different frequency bands. Based on the acumen detect...

During the past five years, there has been an increasing trend of weakly supervised crowd counting methods being developed since such methods just rely on count-level annotations and avoid a laborious labeling process. But, the existing weakly superv...

Grid-connected renewable power generation systems (RPGSs) may be disconnected from the grid under a transient process, which may possibly induce large-scale power outage accidents. Optimization of parameters based on transient stability analysis of R...

This paper presents a novel Verilog-A model for the Fermi velocity in Graphene Field-Effect Transistors (GFETs). The Fermi velocity is an important parameter associated with the energy spectrum of the delocalized bonds in graphene which impact the pe...

Blockchain technology leverages a cryptographic system to provide secure and immutable storage of transaction histories within a decentralised framework. While various industries have demonstrated interest in integrating blockchain into their IT syst...

Object detection powered by deep learning is extensively utilized across diverse sectors, yielding substantial outcomes. However, adverse weather conditions such as rain, snow, and haze interfere with images, leading to a decline in quality and makin...

This paper proposes a DEVS (Discrete Event System Specification) formalism-based approach to analyze Clock Domain Crossing (CDC) issues in digital circuit design. As modern System on Chip (SoC) designs increasingly integrate multiple clock domains, t...

In recent years, the focus of space research and exploration by various countries and international space agencies has been on the return of humans to the moon. Astronauts on lunar missions need to utilize network communication and exchange data. Aga...

The field of real estate valuations is multivariate in nature. Each property has different intrinsic attributes that have a bearing on its final value: location, use, purpose, access, the services available to it, etc. The appraiser analyzes all thes...

In this paper, a novel architecture is proposed that enhances network connectivity by combining network virtualization and the digital twin approach. A virtual network twin (VNT) framework is designed to emulate the behavior of the original network w...

In the era of large AI models, the intricate architectures and vast parameter sets of models such as large language models (LLMs) present significant challenges for effective AI quality management (AIQM). This paper investigates the quality assurance...

Decentralized control offers a more effective way to avoid the complexities and coordination challenges encountered in centralized control. In the decentralized design of additional controllers for multi-infeed DC transmission systems, it is crucial...

Federated learning (FL) strikes a balance between privacy preservation and collaborative model training. However, the periodic transmission of model updates or parameters from each client to the federated server incurs substantial communication overh...

Trajectory planning in tight spaces presents a significant challenge due to the complex maneuvering required under kinematic and obstacle avoidance constraints. When obstacles are densely distributed near the target state, the limited connectivity be...

Large language model-related technologies have shown astonishing potential in tasks such as machine translation, text generation, logical reasoning, task planning, and multimodal alignment. Consequently, their applications have continuously expanded...

Classifying pictorial styles in artworks is a complex challenge due to the diversity and lack of available datasets, which often limit the performance of machine learning models. To address this issue, we propose a novel data augmentation approach us...

Knowledge graph completion (KGC) involves inferring missing entities or relationships within a knowledge graph, playing a crucial role across various domains, including intelligent question answering, recommendation systems, and dialogue systems. Tra...

The voltage control of synchronous generators, particularly under varying load conditions, remains a significant and complex challenge in the field of engineering. Although various control methods have been implemented for automatic voltage regulator...

The traction motor realizes the mutual conversion of electrical energy and mechanical energy during the train traction and braking process and is a key component of high-speed trains. The normal operation of the motor is directly related to the safet...

Focusing on the classification of business data resources within a unified business semantic environment is an important method to simplify the data environment and a crucial approach to studying data intelligence. A multi-value chain data space is a...

Real-time condition monitoring of machinery is increasingly being adopted to minimize costs and enhance operational efficiency. By leveraging large-scale data acquisition and intelligent algorithms, failures can be detected and predicted, thereby red...

With the advancement of industrial automation, vibrational energy generated by machinery during operation is often underutilized. Developing efficient devices for vibration energy harvesting is thus essential. Triboelectric nanogenerators (TENGs) bas...

Digital low-dropout (LDO) regulators are popular in research today as compact power supply solutions. This paper provides a unique approach to analyze digital LDO feedback mechanics and stability, to reduce voltage ripple and extend operating speed o...

Backdoor attacks aim to implant hidden backdoors into Deep Neural Networks (DNNs) so that the victim models perform well on clean images, whereas their predictions would be maliciously changed on poisoned images. However, most existing backdoor attac...

Network Intrusion Detection Systems (NIDSs) are vital for safeguarding Internet of Things (IoT) networks from malicious attacks. Modern NIDSs utilize Machine Learning (ML) techniques to combat evolving threats. This study systematically examined adve...

In this paper, a filtered differential phase shifter with good selectivity is proposed and constructed. This study proposes and builds a filtered differential phase shifter with good selectivity. The main and reference lines in the suggested filtered...

In video encoding rate control, adaptive selection of the initial quantization parameter (QP) is a critical factor affecting both encoding quality and rate control precision. Due to the diversity of video content and the dynamic nature of network con...

Climate change poses a significant threat to our planet, particularly affecting intricate marine ecosystems like coral reefs. These ecosystems are crucial for biodiversity and serve as indicators of the overall health of our oceans. To better underst...

Task-oriented grasp planning poses complex challenges in modern robotics, requiring the precise determination of the grasping pose of a robotic arm to grasp objects with a high level of manipulability while avoiding hardware constraints, such as join...

The increasing demand for energy-efficient hardware platforms to support artificial intelligence (AI) and machine learning (ML) algorithms in edge computing has driven the adoption of system-on-chip (SoC) architectures. Implementing neural network (N...

In this contribution, we generalize existing methods for decentralized control design, providing a unified methodological framework that applies to linear continuous and discrete-time complex systems, as well as certain classes of nonlinear complex s...

Remote sensing imagery (RSI) segmentation plays a crucial role in environmental monitoring and geospatial analysis. However, in real-world practical applications, the domain shift problem between the source domain and target domain often leads to sev...

This research introduces an original approach to time series forecasting through the use of multi-scale convolutional neural networks with Transformer modules. The objective is to focus on the limitations of short-term load forecasting in terms of co...

In the petroleum industry, accurately identifying downhole fluid is crucial for understanding fluid composition and estimating crude oil contamination and other properties. Near-infrared (NIR) spectrum analysis technology has achieved successful flui...

Stream ciphers are a type of symmetric encryption algorithm, and excel in speed and efficiency compared with block ciphers. They are applied in various applications, particularly in digital communications and real-time transmissions. In this paper, w...

Aspect category sentiment analysis aims to automatically identify the sentiment polarities of aspect categories mentioned in text, and is widely used in the data analysis of product reviews and social media. Most existing studies typically limit them...

Aiming at the DC bus voltage instability problem resulting from the stochastic nature of distributed energy output and load fluctuation, an Integral Sliding Mode Linear Active Disturbance Rejection Control (ISMLADRC) combined with Model Predictive Co...

In the repeated launching process, there is an Aluminum Deposited Layer (ADL) on the rail surface. The ADL will melt when heated, and its different melting states will have an important influence on the armature melting process. Therefore, it is nece...

In this paper, a compact capacitive-loaded quarter-mode substrate integrated waveguide (CL-QMSIW) resonator is proposed and analyzed. This resonator is created by loading a metal–insulator–metal (MIM) capacitor inside the QMSIW resonator....

Quadruped robots, with their biomimetic structure, are capable of stable locomotion in complex terrains and are vital in rescue, exploration, and military applications. However, developing multi-modal robots that feature simple motion control while a...

Currently, embedded unmanned aerial vehicle (UAV) systems face significant challenges in balancing detection accuracy and computational efficiency when processing remote sensing images with complex backgrounds, small objects, and occlusions. This pap...

In recent years, target inspection has found extensive utilization within the industry, making it crucial to detect defects in industrial products to ensure quality. To address the challenges posed by large brightness differences, attached dirt, and...

Video anomaly detection plays a vital role in intelligent video monitoring systems. It has found extensive applications in the fields of public safety and social security. Nevertheless, the area of video anomaly detection continues to be a formidable...