2023 September-2 - 251 articles
In the context of electrical power systems, modeling the edge-end interaction involves understanding the dynamic relationship between different components and endpoints of the system. However, the time series of electrical power obtained by user term...
Hardware/software co-simulation is a technique that can help design and validate digital circuits controlled by embedded processors. Co-simulation has largely been applied to system-level models, and tools for SystemC or SystemVerilog are readily ava...
Elevated levels of fine particulate matter (PM2.5) in the atmosphere present substantial risks to human health and welfare. The accurate assessment of PM2.5 concentrations plays a pivotal role in facilitating prompt responses by pertinent regulatory...
This study focuses on harnessing deep-learning-based text-to-image transformation techniques to help webtoon creators’ creative outputs. We converted publicly available datasets (e.g., MSCOCO) into a multimodal webtoon dataset using CartoonGAN....
Federated learning (FL) has been broadly adopted in both academia and industry in recent years. As a bridge to connect the so-called “data islands”, FL has contributed greatly to promoting data utilization. In particular, FL enables disjo...
Traditional YOLO models face a dilemma when it comes to dim detection targets: the detection accuracy increases while the speed inevitably reduces, or vice versa. To resolve this issue, we propose a novel DME-YOLO model, which is characterized by the...
As a typical visual positioning system, monocular ranging is widely used in various fields. However, when the distance increases, there is a greater error. YOLOv8 network has the advantages of fast recognition speed and high accuracy. This paper prop...
This paper proposes a stereo matching method enhanced by object detection and instance segmentation results obtained through the use of a deep convolutional neural network. Then, this method is applied to generate a picking plan to solve bin picking...
Arrow signs found on roadway pavement are an important component of modern transportation systems. Given the rise in autonomous vehicles, public agencies are increasingly interested in accurately identifying and analysing detailed road pavement infor...
Multiphase drives have received a lot of interest because of their several features over traditional three-phase systems for high-power applications. Pulse-width modulation (PWM) approaches are necessary to regulate the supply for multiphase ac drive...
This paper focuses on embedded system modeling, proposing a solution to obtain a refined net via the refinement operation of an extended Petri net. Object-oriented technology and Petri net with inhibitor-arcs-based representation for embedded systems...
As a typical load, the constant power load (CPL) has negative impedance characteristics. The stability of the buck converter system with a mixed load of CPL and resistive load is affected by the size of the CPL. When the resistive load is larger than...
A DC converter is the core equipment of voltage conversion and power distribution in a DC distribution network. Its operating characteristics have a profound impact on the flexible regulation of distributed resources in an active distribution network...
This article presents two novel architectures of dual-band substrate-integrated waveguide (SIW) bandpass filters (BPFs). Initially, two identical open-loop ring resonators (OLRRs) were coupled face-to-face on the top of the SIW cavity to realize a du...
Within this study, we explored the augmented security measures for the electronics of unmanned aerial vehicles (UAVs) within an RF environment. UAVs are commonly utilised across various sectors, and their use as auxiliary platforms for cellular netwo...
As microgrids are the main carriers of renewable energy sources (RESs), research on them has been receiving more attention. When considering the increase in the penetration of renewable energy sources/distributed generators (DGs) in microgrids, their...
Anomaly detection (AD) algorithms can be instrumental in industrial scenarios to enhance the detection of potentially serious problems at a very early stage. Of course, the “Industry 4.0” revolution is fostering the implementation of inte...
Due to the complex specifications of current electronic systems, design decisions need to be explored automatically. However, the exploration process is a complex task given the plethora of design choices such as the selection of components, number o...
This paper proposes an enhanced YOLO v7-based method for detecting insulator defects in transmission lines, addressing the challenges of low accuracy and high leakage rates caused by complex backgrounds and electric poles alongside varying sizes of i...
This paper presents the benefit of the near-threshold design of random-access memory (SRAM) design to reduce software errors during very low-power operations in nanosatellites. The near-threshold design is based on an optimization of the use of the S...
A multi-strategy crazy sparrow search algorithm (LTMSSA) for logic-tent hybrid chaotic maps is given in the research to address the issues of poor population diversity, slow convergence, and easily falling into the local optimum of the sparrow search...
Although emotional speech recognition has received increasing emphasis in research and applications, it remains challenging due to the diversity and complexity of emotions and limited datasets. To address these limitations, we propose a novel approac...
With the rapid development of Internet of Things technology and cloud computing technology, all industries need to outsource massive data to third-party clouds for storage in order to reduce storage and computing costs. Verifiable and dynamic searcha...
This paper proposes a resource-efficient keyword spotting (KWS) system based on a convolutional neural network (CNN). The end-to-end KWS process is performed based solely on 1D-CNN inference, where features are first extracted from a few convolutiona...
Concrete embedded sensors play a very important role in structural health monitoring. However, the time of endurance of sensors remains a performance bottleneck and sensors need to be charged without damaging the structure as well. Wireless power tra...
Automatic modulation classification is an important component in many modern aeronautical communication systems to achieve efficient spectrum usage in congested wireless environments and other communications systems applications. In recent years, num...
Recently, deep-learning-based quantitative investment is playing an increasingly important role in the field of finance. However, due to the complexity of the stock market, establishing effective quantitative investment methods is facing challenges f...
Spatial co-location pattern is a subset of spatial features which shows association relationships based on the spatial neighborhoods. Because the previous prevalence measurements of a co-location pattern have not considered the visited information of...
Updating the most recent set of point cloud data is critical in autonomous driving environments. However, existing systems for point cloud data management often fail to ensure real-time updates or encounter situations in which data cannot be effectiv...
The proliferation of immersive services, including virtual reality/augmented reality, holographic content, and the metaverse, has led to an increase in the complexity of communication networks, and consequently, the complexity of network management....
The Internet of Things (IoT) is increasingly becoming a part of our daily lives, raising significant concerns about future cybersecurity risks and the need for reliable solutions. This study conducts a comprehensive systematic literature review to ex...
Requirements engineering (RE) is a significant aspect of system development stages in generating reliable software (SW). Despite RE’s decisive impact on project success, SW systems still fail since there is a perplexity in sorting out requireme...
This study presents the development of a deep learning model to predict droughts in the coastal region of Ecuador. Historical information from local meteorological stations was used, including data on precipitation, temperature, humidity, evapotransp...
The separation of time–frequency mixing signals composed of radar, communication, and jamming is the first step in integrated reception processing, which requires higher accuracy for complex blind source separation (CVBSS). However, traditional...
Augmented Reality (AR) and Virtual Reality (VR) are poised to revolutionize education by offering immersive and interactive learning experiences. This research comprehensively evaluates the educational applications of AR and VR, specifically emphasiz...
The popularity of social media is continuously growing, as it endeavors to bridge the gap in communication between individuals. YouTube, one of the most well-known social media platforms with millions of users, stands out due to its remarkable abilit...
Bundle recommendations provide personalized suggestions to users by combining related items into bundles, aiming to enhance users’ shopping experiences and boost merchants’ sales revenue. Existing solutions based on graph neural networks (GNN) face s...
Broadcasting is a critical feature in V2X communication, allowing for the simultaneous dissemination of safety-critical messages to all nearby vehicles. However, the requirement for low latency in information dissemination and the need for reliable a...
Predicting Local Area Network (LAN) equipment failure is of utmost importance to ensure the uninterrupted operation of modern communication networks. This study explores the use of machine learning algorithms to enhance the accuracy of equipment fail...
The development of smart grids requires the active participation of end users through demand response mechanisms to provide technical benefits to the distribution network and receive economic savings. Integrating advanced machine learning tools makes...
Micro-expressions reveal underlying emotions and are widely applied in political psychology, lie detection, law enforcement and medical care. Micro-expression spotting aims to detect the temporal locations of facial expressions from video sequences a...
Fixed-wing Unmanned Aerial Vehicles (UAVs) cannot fly at speeds lower than critical stall speeds. As a result, hovering during a potential collision scenario, like with rotary-wing UAVs, is impossible. Moreover, hovering is not an optimal solution fo...
Recently, the growing demands for ultra-high speed applications require more advanced and optimal data transmission techniques. Wireless autoencoders have gained significant attention since they provide global optimization of the transceiver structur...
In order to automate defect detection with few samples using unsupervised learning, this paper, considering materials commonly used in aircraft, proposes a phased array ultrasonic detection defect identification method using non-defect samples for tr...
Semantic segmentation is significant for robotic indoor activities. However, relying solely on RGB modality often leads to poor results due to limited information. Introducing other modalities can improve performance but also increases complexity and...
Modern neural networks addressing dense Non-Rigid Structure from Motion (NRSFM) dilemmas often grapple with intricate a priori constraints, deterring scalability, or overlook the imperative of consistent application of a priori knowledge throughout t...
This paper proposes a switchable polarization-insensitive frequency selective rasorber (FSR) within the X-band. The FSR comprises a lossy layer, a lossless layer, and an intermediate air layer. The lossy layer consists of metal patches, folded wires,...
The rise of the Internet of Things (IoT) has led to an exponential increase in data generated by connected devices. Machine Learning (ML) has emerged as a powerful tool to analyze these data and enable intelligent IoT applications. However, developin...
The grid terminal deploys numerous types of communication equipment for the digital construction of the smart grid. Once communication equipment failure occurs, it might jeopardize the safety of the power grid. The massive amount of communication equ...
In the face of increasing concerns around privacy and security in the use of unmanned aerial vehicles (UAVs) for mobile edge computing (MEC), this study proposes a novel approach to secure UAV-assisted federated learning. This research integrates a t...
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