Journal Description
Electronics
Electronics
is an international, peer-reviewed, open access journal on the science of electronics and its applications published semimonthly online by MDPI. The Polish Society of Applied Electromagnetics (PTZE) is affiliated with Electronics and their members receive a discount on article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus / SciFinder, Inspec, and other databases.
- Journal Rank: JCR - Q2(Electrical and Electronic Engineering) CiteScore - Q2 (Control and Systems Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.6 days after submission; acceptance to publication is undertaken in 2.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journals for Electronics include: Magnetism, Signals, Network and Software.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
2.9 (2022)
Latest Articles
Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends
Electronics 2024, 13(12), 2268; https://doi.org/10.3390/electronics13122268 (registering DOI) - 9 Jun 2024
Abstract
A typical wireless sensor network (WSN) contains wirelessly interconnected devices, called sensor nodes, which have sensing, processing, and communication abilities and are disseminated within an area of interest [...]
Full article
(This article belongs to the Special Issue Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends)
Open AccessArticle
Fusing Design and Machine Learning for Anomaly Detection in Water Treatment Plants
by
Gauthama Raman and Aditya Mathur
Electronics 2024, 13(12), 2267; https://doi.org/10.3390/electronics13122267 (registering DOI) - 9 Jun 2024
Abstract
Accurate detection of process anomalies is crucial for maintaining reliable operations in critical infrastructures such as water treatment plants. Traditional methods for creating anomaly detection systems in these facilities typically focus on either design-based strategies, which encompass physical and engineering aspects, or on
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Accurate detection of process anomalies is crucial for maintaining reliable operations in critical infrastructures such as water treatment plants. Traditional methods for creating anomaly detection systems in these facilities typically focus on either design-based strategies, which encompass physical and engineering aspects, or on data-driven models that utilize machine learning to interpret complex data patterns. Challenges in creating these detectors arise from factors such as dynamic operating conditions, lack of design knowledge, and the complex interdependencies among heterogeneous components. This paper proposes a novel fusion detector that combines the strengths of both design-based and machine learning approaches for accurate detection of process anomalies. The proposed methodology was implemented in an operational secure water treatment (SWaT) testbed, and its performance evaluated during the Critical Infrastructure Security Showdown (CISS) 2022 event. A comparative analysis against four commercially available anomaly detection systems that participated in the CISS 2022 event revealed that our fusion detector successfully detected 19 out of 22 attacks, demonstrating high accuracy with a low rate of false positives.
Full article
(This article belongs to the Special Issue Advances in Predictive Maintenance for Critical Infrastructure)
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Open AccessArticle
Designing Multifunctional Multiferroic Composites for Advanced Electronic Applications
by
Lilian Nunes Pereira, Julio Cesar Agreira Pastoril, Gustavo Sanguino Dias, Ivair Aparecido dos Santos, Ruyan Guo, Amar S. Bhalla and Luiz Fernando Cotica
Electronics 2024, 13(12), 2266; https://doi.org/10.3390/electronics13122266 (registering DOI) - 9 Jun 2024
Abstract
This paper presents a novel approach for the fabrication of magnetoelectric composites aimed at enhancing cross-coupling between electrical and magnetic phases for potential applications in intelligent sensors and electronic components. Unlike previous methodologies known for their complexity and expense, our method offers a
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This paper presents a novel approach for the fabrication of magnetoelectric composites aimed at enhancing cross-coupling between electrical and magnetic phases for potential applications in intelligent sensors and electronic components. Unlike previous methodologies known for their complexity and expense, our method offers a simple and cost-effective assembly process conducted at room temperature, preserving the original properties of the components and avoiding undesired phases. The composites, composed of PZT fibers, cobalt (CoFe O ), and a polymeric resin, demonstrate the uniform distribution of PZT-5A fibers within the cobalt matrix, as demonstrated by scanning electron microscopy. Detailed morphological analyses reveal the interface characteristics crucial for determining overall performance. Dielectric measurements indicate stable behaviors, particularly when PZT-5A fibers are properly poled, showcasing potential applications in sensors or medical devices. Furthermore, H-dependence studies illustrate strong magnetoelectric interactions, suggesting promising avenues for enhancing coupling efficiency. Overall, this study lays the basic work for future optimization of composite composition and exploration of its long-term stability, offering valuable insights into the potential applications of magnetoelectric composites in various technological domains.
Full article
(This article belongs to the Special Issue Advanced Materials for Intelligent Electronics)
Open AccessArticle
SIDGAN: Efficient Multi-Module Architecture for Single Image Defocus Deblurring
by
Shenggui Ling, Hongmin Zhan and Lijia Cao
Electronics 2024, 13(12), 2265; https://doi.org/10.3390/electronics13122265 (registering DOI) - 9 Jun 2024
Abstract
In recent years, with the rapid developments in deep learning and graphics processing units, learning-based defocus deblurring has made favorable achievements. However, the current methods are not effective in processing blurred images with a large depth of field. The greater the depth of
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In recent years, with the rapid developments in deep learning and graphics processing units, learning-based defocus deblurring has made favorable achievements. However, the current methods are not effective in processing blurred images with a large depth of field. The greater the depth of field, the blurrier the image, namely, the image contains large blurry regions and encounters severe blur. The fundamental reason for the unsatisfactory results is that it is difficult to extract effective features from the blurred images with large blurry regions. For this reason, a new FFEM (Fuzzy Feature Extraction Module) is proposed to enhance the encoder’s ability to extract features from images with large blurry regions. After using the FFEM during encoding, its PSNR (Peak Signal-to-Noise Ratio) is improved by 1.33% on the DPDD (Dual-Pixel Defocus Deblurring). Moreover, images with large blurry regions often cause the current algorithms to generate artifacts in their results. Therefore, a new module named ARM (Artifact Removal Module) is proposed in this work and employed during decoding. After utilizing the ARM during decoding, its PSNR is improved by 2.49% on the DPDD. After using the FFEM and the ARM simultaneously, compared to the latest algorithms, the PSNR of our method is improved by 3.29% on the DPDD. Following the previous research in this field, qualitative and quantitative experiments are conducted on the DPDD and the RealDOF (Real Depth of Field), and the experimental results indicate that our method surpasses the state-of-the-art algorithms in three objective metrics.
Full article
(This article belongs to the Special Issue Artificial Intelligence in Image Processing and Computer Vision)
Open AccessArticle
Full-Duplex Unmanned Aerial Vehicle Communications for Cellular Spectral Efficiency Enhancement Utilizing Device-to-Device Underlaying Structure
by
Yuetian Zhou and Yang Li
Electronics 2024, 13(12), 2264; https://doi.org/10.3390/electronics13122264 (registering DOI) - 9 Jun 2024
Abstract
Unmanned aerial vehicle (UAV) communications have gained recognition as a promising technology due to their unique characteristics of rapid deployment and flexible configuration. Meanwhile, device-to-device (D2D) and full-duplex (FD) technologies have emerged as promising methods for enhancing spectral efficiency and offloading traffic. One
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Unmanned aerial vehicle (UAV) communications have gained recognition as a promising technology due to their unique characteristics of rapid deployment and flexible configuration. Meanwhile, device-to-device (D2D) and full-duplex (FD) technologies have emerged as promising methods for enhancing spectral efficiency and offloading traffic. One significant advantage of UAVs is their ability to partition suitable D2D pairs to increase cell capacity. In this paper, we present a novel network model in which UAVs are considered D2D pairs underlaying cellular networks, integrating FD into the communication links between UAVs to improve spectral efficiency. We then investigate a resource allocation problem for the proposed FD-UAV D2D underlaying structure model, with the objective of maximizing the system’s sum rate. Specifically, the UAVs in our model operate in full-duplex mode as D2D users (DUs), allowing the reuse of both the uplink and downlink subcarrier resources of cellular users (CUs). This optimization challenge is formulated as a mixed-integer nonlinear programming problem, known for its NP-hard and intractable nature. To address this issue, we propose a heuristic algorithm (HA) that decomposes the problem into two steps: power allocation and user pairing. The optimal power allocation is solved as a nonlinear programming problem by searching among a finite set, while the user pairing problem is addressed using the Kuhn–Munkres algorithm. The numerical results indicate that our proposed FD-MaxSumCell-HA (full-duplex UAVs maximizing the cell sum rate with a heuristic algorithm) scheme for FD-UAV D2D underlaying models outperforms HD-UAV underlaying cellular networks, with improved access rates for UAVs in FD-MaxSumCell-HA compared to HD-UAV networks.
Full article
(This article belongs to the Special Issue Innovative Technologies and Services for Unmanned Aerial Vehicles)
Open AccessFeature PaperArticle
Privacy Essentials
by
James Taylor, Jane Henriksen-Bulmer and Cagatay Yucel
Electronics 2024, 13(12), 2263; https://doi.org/10.3390/electronics13122263 (registering DOI) - 9 Jun 2024
Abstract
Following a series of legislative changes around privacy over the past 25 years, this study highlights data protection regulations and the complexities of applying these frameworks. To address this, we created a privacy framework to guide organisations in what steps they need to
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Following a series of legislative changes around privacy over the past 25 years, this study highlights data protection regulations and the complexities of applying these frameworks. To address this, we created a privacy framework to guide organisations in what steps they need to undertake to achieve compliance with the UK GDPR, highlighting the existing privacy frameworks for best practice and the requirements from the Information Commissioners Office. We applied our framework to a UK charity sector; to account for the specific nuances that working in a charity brings, we worked closely with local charities to understand their requirements, and interviewed privacy experts to develop a framework that is readily accessible and provides genuine value. Feeding the results into our privacy framework, a decision tree artefact has been developed for compliance. The artefact has been tested against black-box tests, System Usability Tests and UX Honeycomb tests. Results show that Privacy Essentials! provides the foundation of a data protection management framework and offers organisations the catalyst to start, enhance, or even validate a solid and effective data privacy programme.
Full article
(This article belongs to the Special Issue Recent Advances in Information Security and Data Privacy)
Open AccessArticle
Folded Narrow-Band and Wide-Band Monopole Antennas with In-Plane and Vertical Grounds for Wireless Sensor Nodes in Smart Home IoT Applications
by
Mohammad Mahdi Honari, Seyed Parsa Javadi and Rashid Mirzavand
Electronics 2024, 13(12), 2262; https://doi.org/10.3390/electronics13122262 (registering DOI) - 8 Jun 2024
Abstract
This article presents two monopole antennas with an endfire radiation pattern in the UHF band that can be installed on dry walls or metallic cabinets as a part of wireless sensor nodes, making them a suitable choice for smart home applications, such as
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This article presents two monopole antennas with an endfire radiation pattern in the UHF band that can be installed on dry walls or metallic cabinets as a part of wireless sensor nodes, making them a suitable choice for smart home applications, such as the wireless remote control of house appliances. Two different antennas are proposed to cover the RFID bands of North America (902–928 MHz) and worldwide (860–960 MHz). The antennas have wide horizontal radiation patterns that provide great reading coverage in their communication with a base station placed at a certain distance from the antennas. The structures have two ground planes, one in-plane and the other vertical. The vertical ground helps the antenna to have a directive radiation and also makes it easily installed on walls. The antenna feeding line lies over the vertical ground substrate. The maximum dimensions of the narrow-band antenna are L × W = 0.3 0.14 , and those for the wide-band antenna are L × W = 0.39 0.14 . The measured results show that the bandwidth of the proposed antennas for the North America and worldwide RFID bands are from 902 MHz to 939 MHz and 822 MHz to 961 MHz, with maximum gains of 4.2 dBi and 4.9 dBi, respectively.
Full article
(This article belongs to the Special Issue Antenna Design and Its Applications)
Open AccessArticle
Analysis of Vulnerabilities in College Web-Based System
by
Younsu Nam and Sunoh Choi
Electronics 2024, 13(12), 2261; https://doi.org/10.3390/electronics13122261 (registering DOI) - 8 Jun 2024
Abstract
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Web-based systems are used extensively in Korea because web standards have been adapted by the law (e.g., Electronic Government Act). Users can easily access web-based systems if they are connected to the Internet. However, distinguishing between malicious and benign access is very difficult
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Web-based systems are used extensively in Korea because web standards have been adapted by the law (e.g., Electronic Government Act). Users can easily access web-based systems if they are connected to the Internet. However, distinguishing between malicious and benign access is very difficult and many potential vulnerabilities exist. In this study, we attempt to leak the information of other users without permission using a non-encrypted API and web source code analysis in a college web-based system. An experiment demonstrates that the information (e.g., other students’ course grades) can be leaked and abnormal data can be embedded in the request. In addition, we discuss methods for preventing such vulnerability attacks.
Full article
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Open AccessArticle
SPICE-Compatible Circuit Models of Multiports Described by Scattering Parameters with Arbitrary Reference Impedances
by
Marek Nałęcz
Electronics 2024, 13(12), 2260; https://doi.org/10.3390/electronics13122260 (registering DOI) - 8 Jun 2024
Abstract
New SPICE-compatible circuit models of a multiport are presented here that are suitable for the frequency-domain and time-domain analyses of hybrid systems containing linear distributed elements and possibly non-linear lumped elements. Distributed elements models are based on scattering parameters with potentially complex reference
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New SPICE-compatible circuit models of a multiport are presented here that are suitable for the frequency-domain and time-domain analyses of hybrid systems containing linear distributed elements and possibly non-linear lumped elements. Distributed elements models are based on scattering parameters with potentially complex reference impedances, which are not necessarily equal for all ports. Both exact and approximated (lumped) models are proposed. The scattering parameters are directly taken as the model element values in the former case. In the latter case, the model element values are equal to the real and imaginary parts of the poles and residues of the rational approximation. The models comprise a multiport (with an admittance matrix numerically equal to the modeled scattering matrix or approximating it) equipped with a pair of coupled impedances at each port. A few examples validate the proposed approach and prove its efficiency in terms of matrix size and analysis time compared to some selected commercial counterparts.
Full article
(This article belongs to the Section Microwave and Wireless Communications)
Open AccessReview
An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies
by
Anny Huaman-Rivera, Ricardo Calloquispe-Huallpa, Adriana C. Luna Hernandez and Agustin Irizarry-Rivera
Electronics 2024, 13(12), 2259; https://doi.org/10.3390/electronics13122259 (registering DOI) - 8 Jun 2024
Abstract
The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges
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The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.
Full article
(This article belongs to the Special Issue Power Electronics and Its Applications in Power System)
Open AccessEditorial
Digital Twins in Industry 4.0
by
Sangchan Park, Sira Maliphol, Jiyoung Woo and Liu Fan
Electronics 2024, 13(12), 2258; https://doi.org/10.3390/electronics13122258 (registering DOI) - 8 Jun 2024
Abstract
Since Grieves [...]
Full article
(This article belongs to the Special Issue Digital Twins in Industry 4.0)
Open AccessArticle
A Road Crack Segmentation Method Based on Transformer and Multi-Scale Feature Fusion
by
Yang Xu, Yonghua Xia, Quai Zhao, Kaihua Yang and Qiang Li
Electronics 2024, 13(12), 2257; https://doi.org/10.3390/electronics13122257 (registering DOI) - 8 Jun 2024
Abstract
To ensure the safety of vehicle travel, the maintenance of road infrastructure has become increasingly critical, with efficient and accurate detection techniques for road cracks emerging as a key research focus in the industry. The development of deep learning technologies has shown tremendous
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To ensure the safety of vehicle travel, the maintenance of road infrastructure has become increasingly critical, with efficient and accurate detection techniques for road cracks emerging as a key research focus in the industry. The development of deep learning technologies has shown tremendous potential in improving the efficiency of road crack detection. While convolutional neural networks have proven effective in most semantic segmentation tasks, overcoming their limitations in road crack segmentation remains a challenge. To address this, this paper proposes a novel road crack segmentation network that leverages the powerful spatial feature modeling capabilities of Swin Transformer and the Encoder–Decoder architecture of DeepLabv3+. Additionally, the incorporation of a multi-scale coding module and attention mechanism enhances the network’s ability to densely fuse multi-scale features and expand the receptive field, thereby improving the integration of information from feature maps. Performance comparisons with current mainstream semantic segmentation models on crack datasets demonstrate that the proposed model achieves the best results, with an MIoU of 81.06%, Precision of 79.95%, and F1-score of 77.56%. The experimental results further highlight the model’s superior ability in identifying complex and irregular cracks and extracting contours, providing guidance for future applications in this field.
Full article
(This article belongs to the Special Issue Computer Vision for Modern Vehicles)
Open AccessArticle
Localization of Coordinated Cyber-Physical Attacks in Power Grids Using Moving Target Defense and Machine Learning
by
Jian Yu, Qiang Li and Lei Li
Electronics 2024, 13(12), 2256; https://doi.org/10.3390/electronics13122256 (registering DOI) - 8 Jun 2024
Abstract
Coordinated cyber-physical attacks (CCPAs) are dangerously stealthy and have considerable destructive effects against power grids. The problem of stealthy CCPA (SCCPA) localization, specifically identifying disconnected lines in attack, is a nonlinear multi-classification problem. To the best of our knowledge, only one paper has
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Coordinated cyber-physical attacks (CCPAs) are dangerously stealthy and have considerable destructive effects against power grids. The problem of stealthy CCPA (SCCPA) localization, specifically identifying disconnected lines in attack, is a nonlinear multi-classification problem. To the best of our knowledge, only one paper has studied the problem; nevertheless, the total number of classifications is not appropriate. In the paper, we propose several methods to solve the problem of SCCPA localization. Firstly, considering the practical constraints and abiding by one of our previous studies, we elaborately determine the total number of classifications and design an approach for generating training and testing datasets. Secondly, we develop two algorithms to solve multiple classifications via the support vector machine (SVM) and random forest (RF), respectively. Similarly, we also present a one-dimensional convolutional neural network (1D-CNN) architecture. Finally, extensive simulations are carried out for IEEE 14-bus, 30-bus, and 118-bus power system, respectively, and we verify the effectiveness of our approaches in solving the problem of SCCPA localization.
Full article
(This article belongs to the Special Issue Applications of Deep Neural Network for Smart City)
Open AccessArticle
Improving Training Dataset Balance with ChatGPT Prompt Engineering
by
Mateusz Kochanek, Igor Cichecki, Oliwier Kaszyca, Dominika Szydło, Michał Madej, Dawid Jędrzejewski, Przemysław Kazienko and Jan Kocoń
Electronics 2024, 13(12), 2255; https://doi.org/10.3390/electronics13122255 (registering DOI) - 8 Jun 2024
Abstract
The rapid evolution of large language models, in particular OpenAI’s GPT-3.5-turbo and GPT-4, indicates a growing interest in advanced computational methodologies. This paper proposes a novel approach to synthetic data generation and knowledge distillation through prompt engineering. The potential of large language models
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The rapid evolution of large language models, in particular OpenAI’s GPT-3.5-turbo and GPT-4, indicates a growing interest in advanced computational methodologies. This paper proposes a novel approach to synthetic data generation and knowledge distillation through prompt engineering. The potential of large language models (LLMs) is used to address the problem of unbalanced training datasets for other machine learning models. This is not only a common issue but also a crucial determinant of the final model quality and performance. Three prompting strategies have been considered: basic, composite, and similarity prompts. Although the initial results do not match the performance of comprehensive datasets, the similarity prompts method exhibits considerable promise, thus outperforming other methods. The investigation of our rebalancing methods opens pathways for future research on leveraging continuously developed LLMs for the enhanced generation of high-quality synthetic data. This could have an impact on many large-scale engineering applications.
Full article
(This article belongs to the Special Issue Advances in Large Language Model Empowered Machine Learning: Design and Application)
Open AccessBrief Report
A Simple Scan Driver Circuit Suitable for Depletion-Mode Metal-Oxide Thin-Film Transistors in Active-Matrix Displays
by
Yikyoung You, Junhyung Lim, Kyoungseok Son, Jaybum Kim, Youngoo Kim, Kyunghoe Lee, Kyunghoon Chung and Keechan Park
Electronics 2024, 13(12), 2254; https://doi.org/10.3390/electronics13122254 (registering DOI) - 8 Jun 2024
Abstract
Metal-oxide (MOx) thin-film transistors (TFTs) require complex circuit structures to cope with their depletion mode characteristics, making them applicable only to large-area active matrix (AM) displays despite their low manufacturing cost and decent performance. In this paper, we report a simple MOx 10T-2C
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Metal-oxide (MOx) thin-film transistors (TFTs) require complex circuit structures to cope with their depletion mode characteristics, making them applicable only to large-area active matrix (AM) displays despite their low manufacturing cost and decent performance. In this paper, we report a simple MOx 10T-2C scan driver circuit that overcomes the depletion mode characteristics using a series-connected two transistor (STT) configuration and clock signals with two kinds of low-voltage levels. The proposed circuit has a wide operating range of TFT characteristics, i.e., −2.8 V ≤ VTH ≤ +3.0 V. Through the measurement results of the manufactured sample, it was confirmed that the performance and area of our circuit are suitable for high-resolution mobile displays.
Full article
(This article belongs to the Topic Advances in Microelectronics and Semiconductor Engineering)
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Open AccessSystematic Review
Artificial Intelligence, Immersive Technologies, and Neurotechnologies in Breathing Interventions for Mental and Emotional Health: A Systematic Review
by
Eleni Mitsea, Athanasios Drigas and Charalabos Skianis
Electronics 2024, 13(12), 2253; https://doi.org/10.3390/electronics13122253 (registering DOI) - 8 Jun 2024
Abstract
Breathing is one of the most vital functions for being mentally and emotionally healthy. A growing number of studies confirm that breathing, although unconscious, can be under voluntary control. However, it requires systematic practice to acquire relevant experience and skillfulness to consciously utilize
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Breathing is one of the most vital functions for being mentally and emotionally healthy. A growing number of studies confirm that breathing, although unconscious, can be under voluntary control. However, it requires systematic practice to acquire relevant experience and skillfulness to consciously utilize breathing as a tool for self-regulation. After the COVID-19 pandemic, a global discussion has begun about the potential role of emerging technologies in breath-control interventions. Emerging technologies refer to a wide range of advanced technologies that have already entered the race for mental health training. Artificial intelligence, immersive technologies, biofeedback, non-invasive neurofeedback, and other wearable devices provide new, but yet underexplored, opportunities in breathing training. Thus, the current systematic review examines the synergy between emerging technologies and breathing techniques for improving mental and emotional health through the lens of skills development. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology is utilized to respond to the objectives and research questions. The potential benefits, possible risks, ethical concerns, future directions, and implications are also discussed. The results indicated that digitally assisted breathing can improve various aspects of mental health (i.e., attentional control, emotional regulation, mental flexibility, stress management, and self-regulation). A significant finding of this review indicated that the blending of different technologies may maximize training outcomes. Thus, future research should focus on the proper design and evaluation of different digital designs in breathing training to improve health in different populations. This study aspires to provide positive feedback in the discussion about the role of digital technologies in assisting mental and emotional health-promoting interventions among populations with different needs (i.e., employees, students, and people with disabilities).
Full article
Open AccessArticle
Design of a Switching Strategy for Output Voltage Tracking Control in a DC-DC Buck Power Converter
by
Eduardo Hernández-Márquez, Panuncio Cruz-Francisco, Eric Hernández-Castillo, Dulce Martinez-Peón, Rafael Castro-Linares, José Rafael García-Sánchez, Alfredo Roldán-Caballero, Xóchitl Siordia-Vásquez and Juan Carlos Valdivia-Corona
Electronics 2024, 13(12), 2252; https://doi.org/10.3390/electronics13122252 (registering DOI) - 8 Jun 2024
Abstract
This work proposes the design of a commutation function to solve the output voltage trajectory tracking problem in the DC-DC Buck power electronic converter. Through a Lyapunov-type analysis, sufficient conditions are established, taking into account the discontinuous model, to ensure asymptotic convergence to
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This work proposes the design of a commutation function to solve the output voltage trajectory tracking problem in the DC-DC Buck power electronic converter. Through a Lyapunov-type analysis, sufficient conditions are established, taking into account the discontinuous model, to ensure asymptotic convergence to the desired trajectories. Based on this analysis, a state-dependent switching function was designed to guarantee the closed-loop stability of the tracking error. To validate the control performance, circuit numerical simulations were carried out under abrupt disturbances in the source and load of the converter. The results demonstrate that the voltage tracking at the output of the converter is satisfactorily achieved.
Full article
(This article belongs to the Special Issue Applications, Control and Design of Power Electronics Converters)
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Open AccessArticle
Textile Antenna with Dual Bands and SAR Measurements for Wearable Communication
by
Mahmoud A. Abdelghany, Mohamed I. Ahmed, Ahmed A. Ibrahim, Arpan Desai and Mai. F. Ahmed
Electronics 2024, 13(12), 2251; https://doi.org/10.3390/electronics13122251 (registering DOI) - 8 Jun 2024
Abstract
A novel dual-wideband textile antenna designed for wearable applications is introduced in this study. Embedding antennas into wearable devices requires a detailed analysis of the specific absorption rate (SAR) to ensure safety. To achieve this, SAR values were meticulously simulated and evaluated within
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A novel dual-wideband textile antenna designed for wearable applications is introduced in this study. Embedding antennas into wearable devices requires a detailed analysis of the specific absorption rate (SAR) to ensure safety. To achieve this, SAR values were meticulously simulated and evaluated within a human voxel model, considering various body regions such as the left/right head and the abdominal region. The proposed antenna is a monopole design utilizing denim textile as the substrate material. The characterization of the denim textile substrate is carried out using two different methods. The first analysis included a DAC (Dielectric Assessment Kit), while a ring resonator technique was employed for the second examination. Operating within the frequency bands of (58.06%) 2.2–4 GHz and (61.43) 5.3–10 GHz, the antenna demonstrated flexibility in its dual-wideband capabilities. Extensive simulations and tests were conducted to assess the performance of the antenna in both flat and bent configurations. The SAR results obtained from these tests indicate that the antenna complies with safety standard limits when integrated with the human voxel model. This validation underscores the potential of the proposed antenna for seamless integration into wearable applications, offering a promising solution for future developments in this domain.
Full article
(This article belongs to the Special Issue Antenna and Propagation Technologies for 5G/6G Communication)
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Open AccessArticle
An Advanced Approach to Object Detection and Tracking in Robotics and Autonomous Vehicles Using YOLOv8 and LiDAR Data Fusion
by
Yanyan Dai, DeokGyu Kim and KiDong Lee
Electronics 2024, 13(12), 2250; https://doi.org/10.3390/electronics13122250 (registering DOI) - 7 Jun 2024
Abstract
Accurately and reliably perceiving the environment is a major challenge in autonomous driving and robotics research. Traditional vision-based methods often suffer from varying lighting conditions, occlusions, and complex environments. This paper addresses these challenges by combining a deep learning-based object detection algorithm, YOLOv8,
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Accurately and reliably perceiving the environment is a major challenge in autonomous driving and robotics research. Traditional vision-based methods often suffer from varying lighting conditions, occlusions, and complex environments. This paper addresses these challenges by combining a deep learning-based object detection algorithm, YOLOv8, with LiDAR data fusion technology. The principle of this combination is to merge the advantages of these technologies: YOLOv8 excels in real-time object detection and classification through RGB images, while LiDAR provides accurate distance measurement and 3D spatial information, regardless of lighting conditions. The integration aims to apply the high accuracy and robustness of YOLOv8 in identifying and classifying objects, as well as the depth data provided by LiDAR. This combination enhances the overall environmental perception, which is critical for the reliability and safety of autonomous systems. However, this fusion brings some research challenges, including data calibration between different sensors, filtering ground points from LiDAR point clouds, and managing the computational complexity of processing large datasets. This paper presents a comprehensive approach to address these challenges. Firstly, a simple algorithm is introduced to filter out ground points from LiDAR point clouds, which are essential for accurate object detection, by setting different threshold heights based on the terrain. Secondly, YOLOv8, trained on a customized dataset, is utilized for object detection in images, generating 2D bounding boxes around detected objects. Thirdly, a calibration algorithm is developed to transform 3D LiDAR coordinates to image pixel coordinates, which are vital for correlating LiDAR data with image-based object detection results. Fourthly, a method for clustering different objects based on the fused data is proposed, followed by an object tracking algorithm to compute the 3D poses of objects and their relative distances from a robot. The Agilex Scout Mini robot, equipped with Velodyne 16-channel LiDAR and an Intel D435 camera, is employed for data collection and experimentation. Finally, the experimental results validate the effectiveness of the proposed algorithms and methods.
Full article
(This article belongs to the Special Issue Advances in Intelligent Data Analysis and Its Applications, Volume II)
Open AccessArticle
Advanced Primary Frequency Regulation Optimization in Wind Storage Systems with DC Integration Using Double Deep Q-Networks
by
Xiaojiang Liu, Peng Zou, Jin You, Yuhong Wang, Jiabao Wu, Zongsheng Zheng, Shilin Gao and Wei Hao
Electronics 2024, 13(12), 2249; https://doi.org/10.3390/electronics13122249 - 7 Jun 2024
Abstract
With the gradual increase in wind power installation capacity, the proportion of traditional synchronous generators driven by fossil fuel is gradually declining. Due to the fact that wind turbines are connected to the grid through power electronic converters, which decouple rotor speeds from
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With the gradual increase in wind power installation capacity, the proportion of traditional synchronous generators driven by fossil fuel is gradually declining. Due to the fact that wind turbines are connected to the grid through power electronic converters, which decouple rotor speeds from the system frequency and reduce system inertia levels, inadequate inertia levels can pose a threat to frequency stability when disturbances occur. To address this issue, this paper proposes a frequency regulation optimization strategy for the direct current (DC) transmission of a wind storage system. This strategy incorporates virtual inertia control and virtual droop control to adjust wind power output based on frequency deviation and rate of change. Fuzzy logic control is employed for energy storage, adaptively adjusting active power based on frequency deviation and the rate of change. Additionally, under the context of multi-DC transmission in renewable energy systems, an optimization strategy for proportion and integration (PI) parameters of the frequency limit controller (FLC) is proposed. Considering frequency deviation and DC regulation power simultaneously, the double deep Q-network (DDQN) algorithm is adopted in the simulation model to attain the optimal parameters of FLC. Simulation results conducted using MATLAB/Simulink 2022a indicate that this strategy increases the lowest frequency by 0.28 Hz and decreases the response time by 1.04 s compared with the non-optimized strategy.
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(This article belongs to the Special Issue Advances in Modeling, Control and Protection of Power System Containing a High Proportion of Power Electronics)
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