2023 December-2 - 161 articles
This paper proposes a novel energy management approach (imitation-Q-learning) based on imitation learning (IL) and reinforcement learning (RL). The proposed approach reinforces a decision-making agent based on a modified Q-learning algorithm to mimic...
The flight management system is a basic component of avionics for modern airliners. However, the airborne flight management system needs to be improved and relies on imports; path planning is the key to the flight management system. Based on the clas...
Cranes are pivotal heavy equipment used in the construction of transmission line scenarios. Accurately identifying these cranes and monitoring their status is pressing. The rapid development of computer vision brings new ideas to solve these challeng...
Medical data are an intangible asset and an important resource for the entire society. The mining and application of medical data can generate enormous value. Currently, medical data management is mostly centralized and heavily relies on central serv...
Advances in deep learning have led to the development of various animal species detection models suited for different environments. Building on this, our research introduces a detection model that efficiently handles both batch and real-time processi...
Major depressive disorder (MDD) is a prevalent psychiatric condition with a complex and unknown pathological mechanism. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a valuable non-invasive technology for MDD diagnosis....
With the rapid growth of social media platforms and online news consumption, the proliferation of fake news has emerged as a pressing concern. Detecting and combating fake news has become crucial in ensuring the accuracy and reliability of informatio...
This paper proposes a fully digital background calibration method for time-interleaved analog-to-digital converter (TIADC) mismatches. The method analyzes the frequency and phase of spurious signals caused by three types of mismatches in TIADCs in th...
Network quantization, which strives to reduce the precision of model parameters and/or features, is one of the most efficient ways to accelerate model inference and reduce memory consumption, particularly for deep models when performing a variety of...
This study introduces UWF-ZeekDataFall22, a newly created dataset labeled using the MITRE ATT&CK framework. Although the focus of this research is on classifying the never-before classified resource development tactic, the reconnaissance and disc...
Physical models are suitable for the development and optimization of materials and cell designs, whereas models based on experimental data and electrical equivalent circuits (EECs) are suitable for the development of operation estimators, both for ce...
When applying deep learning methods to detect micro defects on low-contrast LCD surfaces, there are challenges related to imbalances in sample datasets and the complexity and laboriousness of annotating and acquiring target image masks. In order to s...
Visible light communication (VLC) is one of the candidate technologies for the sixth generation (6G) networks. The path loss model is particularly important for link budget estimation and network planning in VLC. Due to the wideband nature and the ex...
A Cyberphysical system, being an autonomous guided vehicle (AGV) and having diverse applications such as thematic parks and product transfer in manufacturing units, is modeled and controlled. The models of all subsystems of the AGV are provided in di...
Recently, advancements in machine-learning technology have enabled platforms such as short video applications and e-commerce websites to accurately predict user behavior and cater to their interests. However, the limited nature of user data may compr...
Enhancing energy efficiency, content distribution, latency, and transmission speeds are vital components of communication systems. Multiple access methods hold great promise for boosting these performance indicators. This manuscript evaluates the eff...
Sensor-related indoor localization has attracted considerable attention in recent years. The accuracy of conventional fingerprint solutions based on a single sensor, such as a Wi-Fi sensor, is affected by multipath interferences from other electronic...
This paper introduces a computationally inexpensive technique for moving target detection in challenging outdoor environments using millimeter-wave (mmWave) frequency-modulated continuous-wave (FMCW) radars leveraging traditional signal processing me...
This paper proposes a circuit model of a cross-coupled CMOS AC–DC charge pump (XC–CP) operating in the subthreshold region. The aim is to improve the efficiency of designing XC–CPs with a variety of specifications, e.g., input and o...
Vehicle simulation algorithms play a crucial role in enhancing traffic efficiency and safety by predicting and evaluating vehicle behavior in various traffic scenarios. Recently, vehicle simulation algorithms based on reinforcement learning have demo...
Static random-access memory (SRAM), a pivotal component in integrated circuits, finds extensive applications and remains a focal point in the global research on single-event effects (SEEs). Prolonged exposure to irradiation, particularly the displace...
Transfer learning could improve the robustness and generalization of the model, reducing potential privacy and security risks. It operates by fine-tuning a pre-trained model on downstream datasets. This process not only enhances the model’s cap...
In order to cope with the massive scale of traffic and reduce the memory overhead of traffic statistics, the traffic statistics method based on the Sketch algorithm has become a research hotspot for traffic statistics. This paper studies the problem...
In view of the unstable electromagnetic performance of the air gap magnetic field caused by the torque ripple and harmonic interference of a multi-slot and multi-pole low-speed, high-torque permanent magnet synchronous motor, we propose a simplified...
With a large number of intrusion detection datasets and high feature dimensionality, the emergent nature of new attack types makes it impossible to collect network traffic data all at once. The modified three-way attribute reduction method is combine...
This study proposes an optimization methodology for automotive permanent-magnet synchronous motors (PMSMs) to achieve maximum efficiency, maximum average torque, and minimum torque ripple. Many geometrical parameters can be used to define the PMSM of...
Ongoing backscatter communications and localisation research have been able to obtain incredibly accurate results in controlled environments. The main issue with these systems is faced in complex RF environments. This paper investigates concurrent lo...
Due to the low photon count in space imaging and the performance bottlenecks of edge computing devices, there is a need for a practical low-light imaging solution that maintains satisfactory recovery while offering lower network latency, reduced memo...
Humanlike driving is significant in improving the safety and comfort of automated vehicles. This paper proposes a personalized motion planning method with driver characteristics in longitudinal and lateral directions for highway automated driving. Th...
Deep convolution neural networks (CNNs) have become popular for image denoising due to their robust learning capabilities. However, many methods tend to increase the receptive field to improve performance, which leads to over-smoothed results and los...
In this paper, a control method of a full-bridge DC–DC converter for a pulse power supply with controllable charging time based on Active Disturbance Rejection Control (ADRC) is presented. For this application, the scheme objective is to achiev...
Bird’s eye view (BEV) semantic maps have evolved into a crucial element of urban intelligent traffic management and monitoring, offering invaluable visual and significant data representations for informed intelligent city decision making. Never...
WiFi-based human gesture recognition has a wide range of applications in smart homes. Existing methods train gesture classification models by collecting large amounts of WiFi signal data in a centralized manner. However, centralized training faces ch...
The objective of this study is to present a level shifter architecture that utilizes a pair of inverters and a Wilson current mirror to reduce power consumption while improving voltage shifting capabilities. We introduce novel components such as supe...
This paper presents a compact Micro-Electro-Mechanical System (MEMS) microphone digital readout system. The system is characterized by a low-dropout regulator (LDO) and a pre-amplifier and programmable-gain amplifier (PPA)-less voltage controlled osc...
Lateral control is an essential safety control technology for autonomous vehicles, but the effectiveness of lateral control technology relies heavily on the precision of vehicle motion state judgements. In order to achieve accurate judgements of the...
Hyperspectral imaging (HSI) offers rich spectral and spatial data, beneficial for a variety of applications. However, challenges persist in HSI classification due to spectral variability, non-linearity, limited samples, and a dearth of spatial inform...
Wake-up radio is a promising solution to reduce the energy wasted by mobile devices during an idle state. In this paper, we propose a new wake-up radio solution for 5G mobile devices based on a super-regenerative receiver characterized by its low cos...
In recent years, the rapid development of blockchain technology has facilitated the transfer of value and asset exchange between different blockchains. However, achieving interoperability among various blockchains necessitates the exploration of cros...
In the field of software engineering, large and complex code bases may lead to some burden of understanding their structure and meaning for developers. To reduce the burden on developers, we consider a code base visualization method to visually expre...
This paper discusses the need to accurately determine the population’s exposure to low-intensity radio-frequency electromagnetic fields (RF-EMF) from modern technologies like mobile networks, Wi-Fi, and IoT and proposes a practical solution for...
In order to clarify the magnetic-thermal-force changing rule of high-frequency transformers under different winding arrangements, this paper tests the magnetization and loss characteristics of nanocrystalline materials at different temperatures, and...
Visual grounding aims to recognize and locate the target in the image according to human intention, which provides a new intelligent interaction idea and method for augmented reality (AR) and virtual reality (VR) devices. However, existing vision lan...
With the rapid development of the Internet of Things (IoT), more and more user devices access the network and generate large amounts of genome data. These genome data possess significant medical value when researched. However, traditional genome anal...
Photovoltaic (PV), battery, and fuel cell (FC) technologies are emerging forms of renewable energy gaining popularity. However, one of the key limitations is their production of direct current (DC) voltage, which hinders the connectivity and integrat...
Automatic modulation classification (AMC) based on data-driven deep learning (DL) can achieve excellent classification performance. However, in the field of electronic countermeasures, it is difficult to extract salient features from wireless communi...
A voltage reference is indispensable in Integrated Circuits. To improve the limited linear output voltage range and energy efficiency of a voltage reference, we innovatively propose a switched-capacitor-based programmable voltage reference scheme emp...
Cross-lingual text summarization is a highly desired service for overseas report editing tasks and is formulated in a distributed application to facilitate the cooperation of editors. The multilanguage pre-trained language model (MPLM) can generate h...
Novel energy generation technologies, such as high-permeability wind power and photovoltaic systems, exhibit inherent intermittency, randomness, and volatility. During periods of energy production from these sources, the impedance of the electrical g...
The ever-changing underwater environment, coupled with the complex degradation modes of underwater images, poses numerous challenges to underwater image enhancement efforts. Addressing the issues of low contrast and significant color deviations in un...
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