Electronics, Volume 14, Issue 2

Large language models (LLMs) such as ChatGPT have risen in prominence recently, leading to the need to analyze their strengths and limitations for various tasks. The objective of this work was to evaluate the performance of large language models for...

Accurate remaining capacity prediction (RCP) of lithium-ion batteries (LIBs) is crucial for ensuring their safety, reliability, and performance, particularly amidst the growing energy crisis and environmental concerns. However, the complex aging proc...

Noise in 3D photogrammetric point clouds—both close-range and UAV-generated—poses a significant challenge to the accuracy and usability of digital models. This study presents a novel deep learning-based approach to improve the quality of...

A comprehensive framework for designing a micro-nuclear magnetic resonance (NMR) front-end is presented. Key radio frequency (RF) engineering principles are established to enable efficient excitation and detection of NMR signals. This foundation aims...

Machine learning-based object detection systems are preferred due to their cost-effectiveness compared to deep learning approaches. Among machine learning methods, the Viola-Jones classifier stands out for its reasonable accuracy and efficient resour...

Internet of Things aims to simplify and automate complicated tasks by using sensors and other inputs for collecting huge amounts of data, processing them in the cloud and on the edge networks, and allowing decision making toward further interactions...

Graph Contrastive Learning (GCL) seeks to learn nodal or graph representations that contain maximal consistent information from graph-structured data. While node-level contrasting modes are dominating, some efforts have commenced to explore consisten...

Soil is one of the most important factors of agricultural productivity, directly influencing crop growth, water management, and overall yield. However, inefficient soil moisture monitoring methods, such as manual observation and gravimetric in rural...

The effective capacitance of the common mode port serves as a critical metric for assessing the common mode noise suppression capability of transformers in power converters. Conventionally, the evaluation of transformers in single-ended topologies, s...

To meet the ever-increasing strict transmission requirements of services in the Energy Internet (EI), reliable routing algorithms for service are necessary. Most of the existing routing algorithms in the Internet Protocol (IP) layer concentrate on se...

Next- generation wireless communications are projected to integrate reconfigurable intelligent surfaces (RISs) to perpetrate enhanced spectral and energy efficiencies. To quantify the performance of RIS-aided wireless networks, the statistics of a si...

Mode competition is a significant barrier to advancing gyrotrons towards high frequency, high power, and high efficiency. An axis-encircling beam enables gyrotrons to achieve high interaction efficiency while maintaining stable operation at higher-or...

As an important piece of equipment in photovoltaic power generation systems, the bidirectional DC-DC converter plays a vital role in improving the conversion efficiency of photovoltaic power generation system. The energy transfer in PV systems heavil...

The increasing demand on electrical power consumption all over the world makes the need for stable and reliable electrical power grids is indispensable. Meanwhile, power grid fault diagnosis based on fault recording data is an important technology to...

In this article, a novel method of achieving a single-layer, dual-band, dual-circularly polarized (CP) shared-aperture phased array antenna with wide beam scanning coverage is presented. The space antenna was designed to provide direct-to-cellular co...

While large language models (LLMs) are vital for retrieving relevant information from extensive knowledge bases, they always face challenges, including high costs and issues of credibility. Here, we developed a question answering system focused on hu...

Virtual reality (VR) can play an important role in supporting remote care for cancer patients. The purpose of this study is to explore the possible applications of VR in-home cancer care to support patients and healthcare practitioners. We conducted...

Advanced Encryption Standard (AES) key expansion unit is usually implemented by chain structure with a long critical path length. That makes key expansion unit become the bottleneck of high-speed AES implementations. In this paper, a design method of...

To enhance the path-tracking accuracy of unmanned articulated road roller (UARR) operating on low-adhesion, slippery surfaces, this paper proposes a hierarchical cascaded control (HCC) architecture integrated with real-time ground adhesion coefficien...

The global transition to sustainable energy systems has placed the use of electric vehicles (EVs) among the areas that might contribute to reducing carbon emissions and optimizing energy usage. This paper presents a bibliometric analysis of the inter...

Human–machine pair inspection refers to a technique that supports programmers and machines working together as a “pair” in source code inspection tasks. The machine provides guidance, while the programmer performs the inspection bas...

Pre-trained neural networks like GPT-4 and Llama2 have revolutionized intelligent information processing, but their deployment in industrial applications faces challenges, particularly in harsh environments. To address these related issues, model off...

Traditional coal mine gas risk assessment relies on manual operations, leading to inefficiencies, incomplete information integration, and insufficient evaluation accuracy, ultimately affecting safety oversight. This paper proposes an intelligent gas...

In the current mobile edge computing (MEC) system, the user dynamics, diversity of applications, and heterogeneity of services have made cooperative service caching and task offloading decision increasingly important. Service caching and task offload...

Fine-grained image classification is faced with the challenge of significant intra-class differences and subtle similarities between classes, with a limited number of labelled data. Previous few-shot learning approaches, however, often fail to recogn...

In distribution grids with the large-scale integration of renewable energy sources and energy storage systems, power signals are often contaminated with time-varying noise and frequency deviation caused by low-frequency inertia. To achieve an accurat...

Embedding intelligence into the control design of unmanned aerial vehicles (UAVs) has become increasingly critical as these systems are deployed in complex and uncertain environments, often requiring them to adapt dynamically to unpredictable events...

Deep learning (DL) technology has shown outstanding performance in various fields such as object recognition and classification, speech recognition, and natural language processing. However, it is well known that DL models are vulnerable to data pois...

This paper proposes a transformer temperature early warning method based on an adaptive sliding window and stacking ensemble learning algorithm, aiming to improve the accuracy and robustness of temperature prediction. The transformer temperature earl...

A gesture recognition method is proposed in this paper, which leverages millimeter-wave radar point clouds, primarily for identifying six basic human gestures. First, the raw radar signals collected by the MIMO millimeter-wave radar are converted int...

Incremental Delta-Sigma (I-DS) analog-to-digital converters (ADCs) are one of the best candidates for integrated sensor interface systems when it comes to high resolution and power efficiency. Advanced architectures such as Multistage noise shaping (...

To overcome the challenges during the crop growth process, e.g., pest infestation, inadequate environmental monitoring, and poor intelligence, this study proposes a crop growth information collection system based on a solar insecticidal lamp. The sys...

Laser heterodyne interferometry plays a crucial role in measuring the velocity of water particles during the calibration of hydrophones with the optical method. The velocity of water particles acts as an indicator of acoustic-pressure variations and...

The evolution from 5G to 6G networks is driven by the need to meet the stringent requirements, i.e., ultra-reliable, low-latency, and high-throughput communication. The new services are called Further-Enhanced Mobile Broadband (feMBB), Extremely Reli...

This study introduces a machine learning (ML)-driven approach to next-generation microwave filter design that enhances both accuracy and efficiency via repeated refinement. The approach includes generating a coupling matrix from filter specifications...

Federated learning, with its unique privacy protection mechanisms and distributed model training capabilities, provides an effective solution for data security by addressing the challenges associated with the inability to directly share private data...

Efficient custom hardware motivates the use of fixed-point arithmetic in the implementation of digital signal-processing (DSP) algorithms. This conversion to finite precision arithmetic introduces quantization noise in the system, which affects the s...

The paper proposes an original single-phase transformerless three-level (S-PT) photovoltaic (PV) inverter in the cascade H bridge (CHB) configuration. The DC-link voltage of the inverter is created by two serial voltage sources with a voltage twice a...

Video instance segmentation (VIS) is plagued by the high cost of pixel-level annotation and defects of weakly supervised segmentation, leading to the urgent need for a trade-off between annotation cost and performance. We propose a novel In-Depth Col...

Finger vein recognition has gained significant attention for its importance in enhancing security, safeguarding privacy, and ensuring reliable liveness detection. As a foundation of vein recognition systems, vein detection faces challenges, including...

To address the issues of high single-point failure risk, weak privacy protection, and poor resistance to poisoning attacks in edge federated learning, an edge federated learning privacy protection scheme based on blockchain and fully homomorphic encr...

The simulation results presented based on the proposed system demonstrated significant improvements in communication reliability, packet loss reduction and signal stability, highlighting its superiority in real urban traffic conditions. Using the IEE...

This study explores the potential of the Metaverse in designing trade-fair stands for the exhibition of products and services related to the textile sector, with a particular focus on upholstery fabrics. The primary aim is to enhance relations betwee...

This paper presents a methodology for detecting the pest Aleurothrixus floccosus in citrus crops in Pedregal de Arequipa, Peru. The study employs simple random sampling during image collection to minimize bias, alternating and extracting leaves from...

This article presents a dynamic modeling and control strategy for a non-ideal buck DC–DC (direct current) converter using a PID neural controller. Unlike conventional approaches that rely on fixed-gain PID (Proportional Integral Derivative) con...

Given the difficulty of effectively detecting small target objects using traditional detection technology in current scenic waste disposal settings, this paper proposes an improved detection algorithm based on YOLOv8n deployed on mobile carts. Firstl...

This paper presents an efficient wideband data recovery circuit (DRC) for forward data transfer in the over-coupled mode of dynamic SWPDT systems. In the over-coupled mode, where the operating frequency varies, conventional DRCs often become ineffect...

Eco-evo-devo is an interdisciplinary field integrating ecology, evolutionary biology, and developmental biology. Niche construction refers to the phenomenon where organisms alter selection pressures through ecological activities, and ecological inher...

Image denoising is a classic yet challenging problem in low-level image processing. Traditional image denoising approaches using convex regularized prior (e.g., $L_1$-norm) often bring bias problems. To address this issue, a novel prior model based on a...

Power consumption (PC) data are fundamental for optimizing energy use and managing industrial operations. However, with the widespread adoption of data-driven technologies in the energy sector, maintaining the integrity and quality of these data has...