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 (Electrical and Electronic 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
Hidden-SAGE: For the Inference of Complex Autonomous System Business Relationships Involving Hidden Links
Electronics 2024, 13(9), 1617; https://doi.org/10.3390/electronics13091617 - 23 Apr 2024
Abstract
Routing security is a crucial aspect of internet security. The main issues involved in routing security include Border Gateway Protocol (BGP) route leak and prefix hijacking. Currently, numerous solutions have been proposed for these issues, and significant breakthroughs have been achieved. However, these
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Routing security is a crucial aspect of internet security. The main issues involved in routing security include Border Gateway Protocol (BGP) route leak and prefix hijacking. Currently, numerous solutions have been proposed for these issues, and significant breakthroughs have been achieved. However, these methods focus on visible data on the internet, overlooking the limited coverage of vantage points (VPs). Existing research indicates that attackers can cleverly design route announcements to evade detection by route collectors, thus executing routing attacks. Furthermore, many current methods for detecting route leaks rely on traditional business relationships between Autonomous Systems (AS), but the modeling of traditional AS business relationships is increasingly challenging to comprehensively cover business interactions between ASs. Therefore, we have developed Hidden-SAGE. A framework that extends AS-level internet topology and extracts complex business relationships between ASs from limited routing information. Hidden-SAGE utilizes graph neural networks to discover hidden AS links and employs random forests to infer complex business relationships between links. It successfully reduces visual bias caused by uneven VP distribution and constructs a more comprehensive AS-level internet rich-text topology. Compared to advanced inference algorithms, Hidden-SAGE performs better across various metrics and imposes fewer restrictions on the inference target.
Full article
Open AccessArticle
A Proportional-Integral-Resonant Current Control Strategy for a Wind-Driven Brushless Doubly Fed Generator during Network Unbalance
by
Defu Cai, Haiguang Liu, Sheng Hu, Guanqun Sun, Erxi Wang and Jinrui Tang
Electronics 2024, 13(9), 1616; https://doi.org/10.3390/electronics13091616 - 23 Apr 2024
Abstract
This article proposes a proportional-integral-resonant (PIR) current control strategy for a wind-driven brushless doubly fed generator (WDBDFG) during network unbalance. Firstly, four control objectives of WDBDFG, including eliminating unbalanced currents of power winding (PW), pulsations of control winding (CW) currents, torque, and PW
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This article proposes a proportional-integral-resonant (PIR) current control strategy for a wind-driven brushless doubly fed generator (WDBDFG) during network unbalance. Firstly, four control objectives of WDBDFG, including eliminating unbalanced currents of power winding (PW), pulsations of control winding (CW) currents, torque, and PW power, are discussed and different from current controls in which the references to PW currents were computed; the CW current references are derived here. Then, an improved CW current controller using a PIR controller is proposed to achieve different control objectives. In contrast with current controls, CW currents are not involved with sequence extraction in the proposed control and can be totally regulated only in a positive synchronous reference frame. Hence, the system control structure is greatly simplified, and dynamic characteristics are improved. Furthermore, in order to obtain completely decoupled control of current and average power, feedforward control, considering all the couplings and perturbances, is also applied in CW current loops. Simulation results for a 2 MW grid-connected WDBDFG show that the proposed control is capable of achieving four control objectives, including canceling CW current distortion, PW current unbalance, pulsations of PW active power or pulsations of reactive power, and machine torque. Its dynamic process is much more smoothly and quickly than that of current controls, and therefore the proposed control has better dynamic control characteristics during network unbalance.
Full article
(This article belongs to the Special Issue Advances in Renewable Energy and Electricity Generation)
Open AccessArticle
Three-Dimensional Transient Electric Field Characteristics of High Pressure Electrode Boilers
by
Xiaoke He, Yushuai Ruan and Weishu Wang
Electronics 2024, 13(9), 1615; https://doi.org/10.3390/electronics13091615 - 23 Apr 2024
Abstract
An uneven electric field during the operation of an electrode boiler will lead to the emergence of a high field strength area and low field strength area in the furnace, which will endanger the safe and reliable operation and heating efficiency of the
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An uneven electric field during the operation of an electrode boiler will lead to the emergence of a high field strength area and low field strength area in the furnace, which will endanger the safe and reliable operation and heating efficiency of the electrode boiler. A numerical study of three-dimensional transient electric field distribution characteristics in a 10 kV high-voltage electrode boiler was carried out. The distribution characteristics of the global electric field of the electrode boiler under the nominal voltage of 10 kV were studied, and the distribution law of the electric field of the electrode boiler under poor power quality, such as different bus voltage and three-phase voltage imbalance, was explored. The results show that the electric field distribution characteristics of the three-phase transient are more obvious in the section closer to the electrode disc, and the electric field distribution is the most uniform in the section that is 1.4 m away from the furnace water. In the case of poor power quality, such as different bus voltage and three-phase voltage imbalance, the points of the maximum electric field intensity of the four surfaces change periodically with time, and the greater the bus voltage fluctuation, the more severe the impact on the transient electric field. The three-phase voltage imbalance will shift the peak value of the electric field intensity. The decrease or offset of electric field intensity in the electrode boiler caused by poor power quality will directly affect its heating efficiency. The electric field simulation results have a specific reference value for improving the internal electric field distribution and on-site operation and maintenance of the electrode boiler.
Full article
Open AccessArticle
Modeling of Induction Motors and Variable Speed Drives for Multi-Domain System Simulations Using Modelica and the OpenIPSL Library
by
Fernando Fachini, Marcelo de Castro, Tetiana Bogodorova and Luigi Vanfretti
Electronics 2024, 13(9), 1614; https://doi.org/10.3390/electronics13091614 - 23 Apr 2024
Abstract
This paper introduces an innovative method for characterizing, implementing, and validating both three-phase and single-phase induction motor models, accompanied by a variable speed drive model. The primary goal is to investigate interactions between the electrical power grid and other dynamic domains (e.g., thermofluidic)
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This paper introduces an innovative method for characterizing, implementing, and validating both three-phase and single-phase induction motor models, accompanied by a variable speed drive model. The primary goal is to investigate interactions between the electrical power grid and other dynamic domains (e.g., thermofluidic) that impact motor/load drive behavior. Our approach involves establishing a mechanical interface based on a physically meaningful equation linking motor torque/speed to the electrical model in the phasor domain. This allows seamless integration of diverse domain subsystems into a unified multi-domain model using Modelica v4.0.0 and the OpenIPSL library v3.0.1, overcoming co-simulation limitations. The proposed model, which requires only one Modelica-compliant tool for simulation, introduces additional dynamics through the mechanical interface, enabling explicit simulation of load disturbances based on constitutive physics. This deepens our understanding of dynamic interactions between the electrical power domain and other subsystems connected through the motor. We detail the modeled components using mathematical equations and textual descriptions, emphasizing the Modelica modeling approach. Simulation examples validate the implementation, demonstrating the multi-domain modeling capabilities of the newly developed components.
Full article
(This article belongs to the Special Issue Planning, Operation and Control of Power Systems with Large Amounts of Variable Renewable Generation)
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Open AccessArticle
Comprehensive Security for IoT Devices with Kubernetes and Raspberry Pi Cluster
by
Ionut-Catalin Donca, Ovidiu Petru Stan, Marius Misaros, Anca Stan and Liviu Miclea
Electronics 2024, 13(9), 1613; https://doi.org/10.3390/electronics13091613 - 23 Apr 2024
Abstract
Environmental monitoring systems have gained prominence across diverse applications, necessitating the integration of cutting-edge technologies. This article comprehensively explores such a system, emphasizing the integration of a Raspberry Pi cluster with the BME680 environmental sensor within a Kubernetes framework. This study encompasses the
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Environmental monitoring systems have gained prominence across diverse applications, necessitating the integration of cutting-edge technologies. This article comprehensively explores such a system, emphasizing the integration of a Raspberry Pi cluster with the BME680 environmental sensor within a Kubernetes framework. This study encompasses the technical aspects of hardware configuration and places a significant focus on security benchmarks and robustness validation. The environmental monitoring infrastructure discussed in this article delves into the intricacies of the Raspberry Pi cluster’s hardware setup, including considerations for scalability and redundancy. This research addresses critical security gaps in contemporary environmental monitoring systems, particularly vulnerabilities linked to IoT deployments. Amidst increasing threats, this study introduces a robust framework that integrates advanced security tools—HashiCorp (San Francisco, CA, USA) Vault v1.16 for dynamic secret management and OpenID Connect for authentication processes—to enhance applications and system integrity and resilience within the Kubernetes environment. The approach involves a multi-layered security architecture that fortifies the storage and management of credentials and ensures authenticated and authorized interactions within IoT networks. Furthermore, our research incorporates a series of security benchmark tests, including vulnerability scanning, penetration testing, and access control assessments. Additionally, this article addresses crucial aspects related to data management and analysis, detailing the methodologies employed for storing, processing, and deriving insights from the collected environmental data. It further explores the integration of the monitoring system with existing infrastructure and systems, facilitating seamless data sharing and interoperability and offering valuable insights into the system’s ability to withstand potential threats and vulnerabilities. The integration of Raspberry Pi clusters with BME680 environmental sensors within a Kubernetes-managed framework significantly enhances the scalability and security of IoT systems. This study quantifies the improvements, demonstrating at least a 30% enhancement in system responsiveness and a minimum 40% reduction in vulnerability exposures, as verified by extensive security benchmarks, including penetration testing. These advancements facilitate robust, scalable IoT deployments, with potential applications extending beyond environmental monitoring to include industrial and urban settings. The incorporation of dynamic secret management with HashiCorp Vault and secure authentication with OpenID Connect provides a blueprint for developing resilient IoT architectures capable of supporting high-security and high-availability applications. In conclusion, this article contributes to the expanding body of knowledge in IoT and environmental monitoring and establishes a strong foundation for future work. These outcomes suggest promising directions for further research in secure IoT applications and present practical implications for the deployment of secure and scalable IoT solutions in critical infrastructures.
Full article
(This article belongs to the Section Systems & Control Engineering)
Open AccessArticle
A Fusion Adaptive Cubature Kalman Filter Approach for False Data Injection Attack Detection of DC Microgrids
by
Po Wu, Jiangnan Zhang, Shengyao Luo, Yanlou Song, Jiawei Zhang and Yi Wang
Electronics 2024, 13(9), 1612; https://doi.org/10.3390/electronics13091612 - 23 Apr 2024
Abstract
With the widespread application of information technology in microgrids, microgrids are evolving into a class of power cyber–physical systems (CPSs) that are deeply integrated with physical and information systems. Due to the high dependence of microgrids’ distributed cooperative control on real-time communication and
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With the widespread application of information technology in microgrids, microgrids are evolving into a class of power cyber–physical systems (CPSs) that are deeply integrated with physical and information systems. Due to the high dependence of microgrids’ distributed cooperative control on real-time communication and system state information, they are increasingly susceptible to false data injection attacks (FDIAs). To deal with this issue, in this paper, a novel false data injection attack detection method for direct-current microgrids (DC MGs) was proposed, based on fusion adaptive cubature Kalman filter (FACKF) approach. Firstly, a DC MG model with false data injection attack is established, and the system under attack is analyzed. Subsequently, an FACKF approach is proposed to detect attacks, capable of accurately identifying the attacks on the DC MG and determining the measurement units injected with false data. Finally, simulation validations were conducted under various DC MG model conditions. The extensive simulation results demonstrate that the proposed method surpasses traditional CKF detection methods in accuracy and effectiveness across different conditions.
Full article
(This article belongs to the Special Issue Situational Awareness and Protection Technologies for Low-Carbon Economic Operation of New Power Systems)
Open AccessArticle
Modified Rime-Ice Growth Optimizer with Polynomial Differential Learning Operator for Single- and Double-Diode PV Parameter Estimation Problem
by
Sultan Hassan Hakmi, Hashim Alnami, Ghareeb Moustafa, Ahmed R. Ginidi and Abdullah M. Shaheen
Electronics 2024, 13(9), 1611; https://doi.org/10.3390/electronics13091611 - 23 Apr 2024
Abstract
A recent optimization algorithm, the Rime Optimization Algorithm (RIME), was developed to efficiently utilize the physical phenomenon of rime-ice growth. It simulates the hard-rime and soft-rime processes, constructing the mechanisms of hard-rime puncture and soft-rime search. In this study, an enhanced version, termed
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A recent optimization algorithm, the Rime Optimization Algorithm (RIME), was developed to efficiently utilize the physical phenomenon of rime-ice growth. It simulates the hard-rime and soft-rime processes, constructing the mechanisms of hard-rime puncture and soft-rime search. In this study, an enhanced version, termed Modified RIME (MRIME), is introduced, integrating a Polynomial Differential Learning Operator (PDLO). The incorporation of PDLO introduces non-linearities to the RIME algorithm, enhancing its adaptability, convergence speed, and global search capability compared to the conventional RIME approach. The proposed MRIME algorithm is designed to identify photovoltaic (PV) module characteristics by considering diverse equivalent circuits, including the One-Diode Model (ONE-DM) and Two-Diode Model TWO-DM, to determine the unspecified parameters of the PV. The MRIME approach is compared to the conventional RIME method using two commercial PV modules, namely the STM6-40/36 module and R.T.C. France cell. The simulation results are juxtaposed with those from contemporary algorithms based on published research. The outcomes related to recent algorithms are also compared with those of the MRIME algorithm in relation to various existing studies. The simulation results indicate that the MRIME algorithm demonstrates substantial improvement rates for the STM6-40/36 module and R.T.C. France cell, achieving 1.16% and 18.45% improvement for the ONE-DM, respectively. For the TWO-DM, it shows significant improvement rates for the two modules, reaching 1.14% and 50.42%, respectively. The MRIME algorithm, in comparison to previously published results, establishes substantial superiority and robustness.
Full article
Open AccessArticle
Asynchronous Privacy-Preservation Federated Learning Method for Mobile Edge Network in Industrial Internet of Things Ecosystem
by
John Owoicho Odeh, Xiaolong Yang, Cosmas Ifeanyi Nwakanma and Sahraoui Dhelim
Electronics 2024, 13(9), 1610; https://doi.org/10.3390/electronics13091610 - 23 Apr 2024
Abstract
The typical industrial Internet of Things (IIoT) network system relies on a real-time data upload for timely processing. However, the incidence of device heterogeneity, high network latency, or a malicious central server during transmission has a propensity for privacy leakage or loss of
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The typical industrial Internet of Things (IIoT) network system relies on a real-time data upload for timely processing. However, the incidence of device heterogeneity, high network latency, or a malicious central server during transmission has a propensity for privacy leakage or loss of model accuracy. Federated learning comes in handy, as the edge server requires less time and enables local data processing to reduce the delay to the data upload. It allows neighboring edge nodes to share data while maintaining data privacy and confidentiality. However, this can be challenged by a network disruption making edge nodes or sensors go offline or experience an alteration in the learning process, thereby exposing the already transmitted model to a malicious server that eavesdrops on the channel, intercepts the model in transit, and gleans the information, evading the privacy of the model within the network. To mitigate this effect, this paper proposes asynchronous privacy-preservation federated learning for mobile edge networks in the IIoT ecosystem (APPFL-MEN) that incorporates the iteration model design update strategy (IMDUS) scheme, enabling the edge server to share more real-time model updates with online nodes and less data sharing with offline nodes, without exposing the privacy of the data to a malicious node or a hack. In addition, it adopts a double-weight modification strategy during communication between the edge node and the edge server or gateway for an enhanced model training process. Furthermore, it allows a convergence boosting process, resulting in a less error-prone, secured global model. The performance evaluation with numerical results shows good accuracy, efficiency, and lower bandwidth usage by APPFL-MEN while preserving model privacy compared to state-of-the-art methods.
Full article
(This article belongs to the Section Networks)
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Open AccessArticle
Modular Intelligent Control System in the Pre-Assembly Stage
by
Branislav Micieta, Peter Macek, Vladimira Binasova, Luboslav Dulina, Martin Gaso and Jan Zuzik
Electronics 2024, 13(9), 1609; https://doi.org/10.3390/electronics13091609 - 23 Apr 2024
Abstract
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This paper presents a novel approach to developing fully automated intelligent control systems for use within production-based organizations, with a specific focus on advancing research into intelligent production systems. This analysis underscores a prevailing deficiency in control operations preceding assembly, where single-purpose control
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This paper presents a novel approach to developing fully automated intelligent control systems for use within production-based organizations, with a specific focus on advancing research into intelligent production systems. This analysis underscores a prevailing deficiency in control operations preceding assembly, where single-purpose control machines are commonly utilized, thus presenting inherent limitations. Conversely, while accurate multipurpose measurement centers exist, they often fail to deliver comprehensive quality control for manufactured parts due to cost and time constraints associated with the measuring process. The primary aim in this study was to develop an intelligent modular control system capable of overseeing the production of diverse components effectively. The modular intelligent control system is designed to meticulously monitor the quality of each module during the pre-assembly phase. By integrating sophisticated sensors, diagnostic tools, and intelligent control mechanisms, this system ensures precise control over module production processes. It facilitates the monitoring of multiple parameters and critical quality features, while integrated sensors and diagnostic methods promptly identify discrepancies and inaccuracies, enabling the swift diagnosis of issues within specific modules. The system’s intelligent control algorithms optimize production processes and ensure synchronization among individual modules, thereby ensuring consistent quality and performance. Notably, the implementation of this solution reduces inspection time by an average of 40 to 60% compared to manual inspection methods. Moreover, the system enables the comprehensive archiving of measurement data, eliminating the substantial error rates introduced by human involvement in the inspection process. Furthermore, the system enhances overall project efficiency, predictability, and safety, while allowing for rapid adjustments in order to meet standards and requirements. This innovative approach represents a significant advancement in intelligent control systems for use in production organizations, offering substantial benefits in terms of efficiency, accuracy, and adaptability.
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Open AccessArticle
Performance Improvements via Peephole Optimization in Dynamic Binary Translation
by
Wenbing Xie, Qiaoling Luo, Xue Tian, Junyi Huang and Fengbin Qi
Electronics 2024, 13(9), 1608; https://doi.org/10.3390/electronics13091608 - 23 Apr 2024
Abstract
The emergence of new instruction set architectures (ISAs) poses challenges in ensuring compatibility with legacy applications. Dynamic binary translation (DBT) serves as a crucial approach for achieving cross-ISA compatibility, enabling legacy applications to run compatibly with cross-ISAs. However, software-based translation encounters significant performance
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The emergence of new instruction set architectures (ISAs) poses challenges in ensuring compatibility with legacy applications. Dynamic binary translation (DBT) serves as a crucial approach for achieving cross-ISA compatibility, enabling legacy applications to run compatibly with cross-ISAs. However, software-based translation encounters significant performance overhead, including substantial memory access and insufficient exploitation of target architecture features. The significant performance overhead challenges hinder the practical implementation of DBT. In this paper, we investigate a novel peephole optimization approach. First, we perform peephole analysis to identify redundant memory access and suboptimal instruction sequences. Next, we leverage live variable analysis to eliminate redundant memory-access instructions. Additionally, we bridge the gaps between cross-ISAs by exploiting ISA-specific features through instruction fusion. Finally, we implement the proposed optimization design using the open-source QEMU and extensively evaluate it on both ARM64 and SW64 platforms. The experimental results reveal that SPEC2006 benchmark effectively gets a maximum performance speedup of 1.52×, alongside a reduction in code size of up to 13.98%. These results affirm the effectiveness of our optimization approach in DBT performance and code sizes.
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(This article belongs to the Section Industrial Electronics)
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Open AccessArticle
FPGA-Based Implementation of a Digital Insulin-Glucose Regulator for Type 2 Diabetic Patients
by
Guido Di Patrizio Stanchieri, Andrea De Marcellis, Marco Faccio, Elia Palange, Mario Di Ferdinando, Stefano Di Gennaro and Pierdomenico Pepe
Electronics 2024, 13(9), 1607; https://doi.org/10.3390/electronics13091607 - 23 Apr 2024
Abstract
This paper reports on the hardware implementation of a digital insulin-glucose regulator for type 2 diabetic patients by using a Field Programmable Gate Array board. For a real time-control of the patient insulin concentration, the insulin-regulator needs to measure only his blood glucose
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This paper reports on the hardware implementation of a digital insulin-glucose regulator for type 2 diabetic patients by using a Field Programmable Gate Array board. For a real time-control of the patient insulin concentration, the insulin-regulator needs to measure only his blood glucose concentration. With respect to other reported solutions using general-purpose programmable hardware’s, the proposed insulin-glucose regulator allows to design a software-free, fully-hardware architecture of the system here described in detail. A prototype has been developed so to validate its functionality in the following two operating modes: (i) in the open loop condition for which only the insulin-glucose regulator is operating; (ii) in the closed loop condition for which the insulin-glucose regulator acting as an artificial pancreas is connected to a population of one hundred virtual patients individuated by employing a comprehensive theoretical model recognized by the U.S. Food and Drug Administration for the pre-clinical validation of glucose control strategies. These virtual patients present the same trend of the variation of the glucose concentration achieving different maximum and minimum values of glucose concentrations when eating a meal. The paper presents and discusses the experimental results by comparing them with those ones obtained by implementing the theoretical model through numerical simulations performed in SIMULINK. Relative errors lower than ±1% have been achieved by performing this comparison so demonstrating a very high accuracy of the proposed insulin-glucose regulator digital system. The implemented hardware solution of the digital controller can process the input data related to the glucose concentration of each virtual patient in about 1.1 μs with an estimated power consumption of about 36 mW. These achievements open the way for further investigations on digital architectures for glucose regulators to be integrated in VLSI as System-on-Chips and/or Lab-on-Chips for portable, wearable, and implantable solutions in real biomedical applications.
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(This article belongs to the Special Issue Emerging Electronic Technologies for Biomedical Applications)
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Open AccessArticle
SlowR50-SA: A Self-Attention Enhanced Dynamic Facial Expression Recognition Model for Tactile Internet Applications
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Nikolay Neshov, Nicole Christoff, Teodora Sechkova, Krasimir Tonchev and Agata Manolova
Electronics 2024, 13(9), 1606; https://doi.org/10.3390/electronics13091606 - 23 Apr 2024
Abstract
Emotion recognition from facial expressions is a challenging task due to the subtle and nuanced nature of facial expressions. Within the framework of Tactile Internet (TI), the integration of this technology has the capacity to completely transform real-time user interactions, by delivering customized
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Emotion recognition from facial expressions is a challenging task due to the subtle and nuanced nature of facial expressions. Within the framework of Tactile Internet (TI), the integration of this technology has the capacity to completely transform real-time user interactions, by delivering customized emotional input. The influence of this technology is far-reaching, as it may be used in immersive virtual reality interactions and remote tele-care applications to identify emotional states in patients. In this paper, a novel emotion recognition algorithm is presented that integrates a Self-Attention (SA) module into the SlowR50 backbone (SlowR50-SA). The experiments on the DFEW and FERV39K datasets demonstrate that the proposed model achieves good performance in terms of both Unweighted Average Recall (UAR) and Weighted Average Recall (WAR) metrics, achieving a UAR (WAR) of 57.09% (69.87%) on the DFEW dataset, and UAR (WAR) of 39.48% (49.34%) on the FERV39K dataset. Notably, SlowR50-SA operates with only eight frames of input at low temporal resolution, highlighting its efficiency. Furthermore, the algorithm has the potential to be integrated into Tactile Internet applications, where it can be used to enhance the user experience by providing real-time emotion feedback. SlowR50-SA can also be used to enhance virtual reality experiences by providing personalized haptic feedback based on the user’s emotional state. It can also be used in remote tele-care applications to detect signs of stress, anxiety, or depression in patients.
Full article
(This article belongs to the Section Electronic Multimedia)
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Open AccessArticle
Advancing into Millimeter Wavelengths for IoT: Multibeam Modified Planar Luneburg Lens Antenna with Porous Plastic Material
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Javad Pourahmadazar, Bal S. Virdee and Tayeb A. Denidni
Electronics 2024, 13(9), 1605; https://doi.org/10.3390/electronics13091605 - 23 Apr 2024
Abstract
This paper introduces an innovative antenna design utilizing a cylindrical dielectric Luneburg lens tailored for 60 GHz Internet of Things (IoT) applications. To optimize V-band communications, the permittivity of the dielectric medium is strategically adjusted by precisely manipulating the physical porosity. In IoT
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This paper introduces an innovative antenna design utilizing a cylindrical dielectric Luneburg lens tailored for 60 GHz Internet of Things (IoT) applications. To optimize V-band communications, the permittivity of the dielectric medium is strategically adjusted by precisely manipulating the physical porosity. In IoT scenarios, employing a microstrip dipole antenna with an emission pattern resembling cos10 enhances beam illumination within the waveguide, thereby improving communication and sensing capabilities. The refractive index gradient of the Luneburg lens is modified by manipulating the material’s porosity using air holes, prioritizing signal accuracy and reliability. Fabricated with polyimide using 3D printing, the proposed antenna features a slim profile ideal for IoT applications with space constraints, such as smart homes and unmanned aerial vehicles. Its innovative design is underscored by selective laser sintering (SLS), offering scalable and cost-effective production. Measured results demonstrate the antenna’s exceptional performance, surpassing IoT deployment standards. This pioneering approach to designing multibeam Luneburg lens antennas, leveraging 3D printing’s porosity control for millimeter-wave applications, represents a significant advancement in antenna technology with scanning ability between −67 and 67 degrees. It paves the way for enhanced IoT infrastructure characterized by advanced sensing capabilities and improved connectivity.
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(This article belongs to the Special Issue Antennas for IoT Devices)
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Open AccessArticle
Research on Communication Signal Modulation Recognition Based on a CCLDNN
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Zijin He and Xiaodong Zeng
Electronics 2024, 13(9), 1604; https://doi.org/10.3390/electronics13091604 - 23 Apr 2024
Abstract
In this paper, a new automatic modulation recognition (AMR) method named CCLDNN (complex-valued convolution long short-term memory deep neural network) is proposed. It is designed to significantly improve the recognition accuracy of modulation modes in low signal-to-noise ratio (SNR) environments. The model integrates
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In this paper, a new automatic modulation recognition (AMR) method named CCLDNN (complex-valued convolution long short-term memory deep neural network) is proposed. It is designed to significantly improve the recognition accuracy of modulation modes in low signal-to-noise ratio (SNR) environments. The model integrates the advantages of existing mainstream neural networks. The phase and amplitude information of complex signals is effectively captured through a complex module in the input layer. The Squeeze-and-Excitation (SE) attention mechanism, Bi-LSTM layer, and deep convolutional layer are introduced in the feature extraction layer to gradually enhance feature expression. Among these, the introduction of LSTM enables the model to capture the sequence dependence of signals, and the application of the SE attention mechanism further improves the model’s ability to focus on key features. Tests using the RadioML2016.10a dataset show that the model performs well at multiple SNR levels, achieving an average recognition accuracy of more than 80% over an SNR range of 0 dB to 18 dB. However, under the condition of a low SNR from −20 dB to −2 dB, the model still maintains a high recognition ability. The advanced CCLDNN method shows great deep learning potential in solving practical communication problems.
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(This article belongs to the Section Microwave and Wireless Communications)
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Open AccessArticle
Random Numbers Generated Based on Dual-Channel Chaotic Light
by
Guopeng Liu, Penghua Mu, Kun Wang, Gang Guo, Xintian Liu and Pengfei He
Electronics 2024, 13(9), 1603; https://doi.org/10.3390/electronics13091603 - 23 Apr 2024
Abstract
This paper presents a chaotic system based on novel semiconductor nanolasers (NLs), systematically analyzing its chaotic region and investigating the influence of key parameters on the unpredictability of chaotic output. This study found that under optical feedback conditions, NLs generate chaos across a
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This paper presents a chaotic system based on novel semiconductor nanolasers (NLs), systematically analyzing its chaotic region and investigating the influence of key parameters on the unpredictability of chaotic output. This study found that under optical feedback conditions, NLs generate chaos across a wide range of feedback parameters, with the highly unpredictable region completely overlapping with the chaotic region. Further injection into the slave lasers enhances the chaotic output, expanding the range of unpredictability. Additionally, we analyzed the impact of internal parameter mismatch on the complexity of chaotic signals and found it to be similar to the scenario when parameters are matched. Using this chaotic system as an entropy source, we constructed a random number generator (RNG) and investigated the effects of internal parameters mismatch and differences in the injection parameters on the generator’s performance. The simulation results show that the RNG performs well under different parameter settings, and the generated random sequences pass all random number tests successfully. Therefore, this chaotic system can yield a high-complexity chaotic light source with appropriate parameter selection, and when combined with effective post-processing, it can generate high-quality random numbers. This is crucial for advancing the realization of small-sized, high-randomness RNGs.
Full article
(This article belongs to the Special Issue Recent Advances in Chaotic Systems and Their Security Applications, 2nd edition)
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Open AccessArticle
Graphical Design Approach for UWB Stacked CG LNA Using Inversion Coefficient
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Ahmed Hamed and Ayman Ismail
Electronics 2024, 13(9), 1602; https://doi.org/10.3390/electronics13091602 - 23 Apr 2024
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The design of ultra-wide-band (UWB) low-noise amplifiers (LNAs) entails a large number of design challenges and tradeoffs, which include sustaining good input matching over a wide bandwidth along with finding a proper compromise between various LNA performance metrics, such as gain, bandwidth, noise
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The design of ultra-wide-band (UWB) low-noise amplifiers (LNAs) entails a large number of design challenges and tradeoffs, which include sustaining good input matching over a wide bandwidth along with finding a proper compromise between various LNA performance metrics, such as gain, bandwidth, noise figure, power, and linearity. This paper presents a design approach for UWB LNAs based on the inversion coefficient (IC). The proposed approach is a graphical design approach where the proper operating point is chosen based on predefined constraints. A complete systematic solution is presented for the problem of UWB input matching with a high degree of analytical accuracy. The design approach is illustrated through the design of two UWB stacked common-gate LNAs in 65 nm technology. The post-layout simulation results show very good agreement with analytical expectations. The first LNA achieves an better than −8.2 dB over a 27.6 GHz frequency range, a gain of 12.4 dB over a 16.5 GHz bandwidth, a minimum noise-figure, NF, of 4.5 dB, and an of −5.2 dBm while consuming only 530 W. The second LNA achieves an better than −15 dB over an 8.8 GHz frequency range, a gain of 12.5 dB over a 6.8 GHz bandwidth, a minimum NF of 4 dB, and an of −4.3 dBm while consuming only 550 W.
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Open AccessArticle
Design of Fractional-Order Non-Singular Terminal Sliding Mode Observer Sensorless System for Surface-Mounted Permanent Magnet Synchronous Motor
by
Guozhong Yao, Jinlong Gao, Jilin Lei, Shaojun Han and Yuhan Xiao
Electronics 2024, 13(8), 1601; https://doi.org/10.3390/electronics13081601 - 22 Apr 2024
Abstract
A new sensorless speed control system for a fractional-order terminal non-singular sliding mode surface-mounted permanent magnet synchronous motor is proposed. The fractional terminal non-singular sliding mode surface, which can converge in finite time, is designed by combining the fractional-order control theory with the
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A new sensorless speed control system for a fractional-order terminal non-singular sliding mode surface-mounted permanent magnet synchronous motor is proposed. The fractional terminal non-singular sliding mode surface, which can converge in finite time, is designed by combining the fractional-order control theory with the terminal attractor concept. Then, a new control rate is proposed to reduce system buffeting. Secondly, an adaptive back electromotive force filter is designed to reduce the harmonics in the sliding mode function estimation and improve the observation accuracy. In addition, the theoretical analysis of the designed system proves that the system can converge in a finite time. Then, a fraction-order phase-locked loop with variable factors is designed to make the system more capable of tracking the rotor. Finally, a simulation and experiment platform is built, and a comparison experiment is carried out, which proves that the designed algorithm has a stronger rotor position tracking ability and a better dynamic performance of the system.
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(This article belongs to the Special Issue Advances in Control for Permanent Magnet Synchronous Motor (PMSM))
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Open AccessArticle
Advanced Interference Mitigation Method Based on Joint Direction of Arrival Estimation and Adaptive Beamforming for L-Band Digital Aeronautical Communication System
by
Lei Wang, Xiaoxiao Hu and Haitao Liu
Electronics 2024, 13(8), 1600; https://doi.org/10.3390/electronics13081600 - 22 Apr 2024
Abstract
The L-band digital aeronautical communication system (LDACS) is one of the candidate technologies for future broadband digital aeronautical communications, utilizing the unused L-band spectrum between distance measuring equipment (DME) channels. However, the higher signal power of DME complicates LDACS implementation. This paper proposes
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The L-band digital aeronautical communication system (LDACS) is one of the candidate technologies for future broadband digital aeronautical communications, utilizing the unused L-band spectrum between distance measuring equipment (DME) channels. However, the higher signal power of DME complicates LDACS implementation. This paper proposes an advanced DME mitigation approach for the LDACS, integrating joint direction of arrival (DOA) estimation with adaptive beamforming techniques. The proposed method begins by exploiting the cyclostationary characteristics of signals, accurately obtaining the preliminary direction of the LDACS signal using the Cyclic-MUSIC method. Subsequent precise steering vectors (SVs) are selected through Capon spectrum search, followed by the reconstruction of the interference plus noise covariance matrix (INCM). Using the obtained SV and INCM, the weight vector is calculated and beamforming is performed. Simulation results validate that the proposed method not only accurately estimates the direction of LDACS signal but also efficiently mitigates DME interference, demonstrating a superior performance and reduced algorithmic complexity, even in scenarios with lower signal-to-noise ratios (SNRs) and the presence of DOA estimation errors. Additionally, the proposed method achieves a low bit error rate (BER), further validating its ability to ensure communication quality and enhance the reliability of LDACS.
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(This article belongs to the Section Microwave and Wireless Communications)
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Using Data Augmentation to Improve the Accuracy of Blood Pressure Measurement Based on Photoplethysmography
by
Hanlin Mou, Congjian Li, Haoran Zhou, Daobing Zhang, Wensheng Wang, Junsheng Yu and Jing Tian
Electronics 2024, 13(8), 1599; https://doi.org/10.3390/electronics13081599 - 22 Apr 2024
Abstract
Convenient and accurate blood pressure (BP) measurement is of great importance in both clinical and daily life. Although deep learning (DL) can achieve cuff-less BP measurement based on Photoplethysmography (PPG), the performance of DL is affected by few-shot data. Data augmentation becomes an
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Convenient and accurate blood pressure (BP) measurement is of great importance in both clinical and daily life. Although deep learning (DL) can achieve cuff-less BP measurement based on Photoplethysmography (PPG), the performance of DL is affected by few-shot data. Data augmentation becomes an effective way to enhance the size of the training data. In this paper, we use cropping, flipping, DTW barycentric averaging (DBA), generative adversarial network (GAN) and variational auto-encoder (VAE) for the data augmentation of PPG. Furthermore, a PE–CNN–GRU model is designed for cuff-less BP measurement applying position encoding (PE), convolutional neural networks (CNNs) and gated recurrent unit (GRU) networks. Experiment results based on real-life datasets show that VAE is the most suitable method for PPG data augmentation, which can reduce the mean absolute error (MAE) of PE–CNN–GRU when measuring systolic blood pressure (SBP) and diastolic blood pressure (DBP) by 18.80% and 19.84%. After the data augmentation of PPG, PE–CNN–GRU achieves accurate and cuff-less BP measurement, thus providing convenient support for preventing cardiovascular diseases.
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(This article belongs to the Special Issue Artificial Intelligence Technologies for Biomedicine and Healthcare Applications)
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A Hardware Implementation of the PID Algorithm Using Floating-Point Arithmetic
by
Józef Kulisz and Filip Jokiel
Electronics 2024, 13(8), 1598; https://doi.org/10.3390/electronics13081598 - 22 Apr 2024
Abstract
The purpose of the paper is to propose a new implementation of the PID (proportional–integral–derivative) algorithm in digital hardware. The proposed structure is optimized for cost. It follows a serialized, rather than parallel, scheme. It uses only one arithmetic block, performing the multiply-and-add
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The purpose of the paper is to propose a new implementation of the PID (proportional–integral–derivative) algorithm in digital hardware. The proposed structure is optimized for cost. It follows a serialized, rather than parallel, scheme. It uses only one arithmetic block, performing the multiply-and-add operation. The calculations are carried out in a sequentially cyclic manner. The proposed circuit operates on standard single-precision (32-bit) floating-point numbers. It implements an extended PID formula, containing a non-ideal derivative component, and weighting coefficients, which enable reducing the influence of setpoint changes in the proportional and derivative components. The circuit was implemented in a Cyclone V FPGA (Field-Programmable Gate Array) device from Intel, Santa Clara, CA, USA. The proper operation of the circuit was verified in a simulation. For the specific implementation, which is reported in the paper, the sampling period of 516 ns was obtained, which means that the proposed solution is comparable in terms of speed with other hardware implementations of the PID algorithm operating on single-precision floating-point numbers. However, the presented solution is much more efficient in terms of cost. It uses 1173 LUT (Look-up Table) blocks, 1026 registers, and 1 DSP (Digital Signal Processing) block, i.e., about 30% of logic resources required by comparable solutions.
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(This article belongs to the Special Issue Energy Technologies in Electronics and Electrical Engineering)
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