Previous Issue
Volume 13, November-1
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.6
Journals
Electronics
Volume 13
Issue 22
share announcement

Electronics, Volume 13, Issue 22 (November-2 2024) – 61 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
21 pages, 1726 KiB  
Article
Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems
by Heng Zhang, Hui Li and Xin Wang
Electronics 2024, 13(22), 4392; https://doi.org/10.3390/electronics13224392 (registering DOI) - 8 Nov 2024
Abstract
Under the ideal assumption of deploying only one central processing unit (CPU) in the entire system, cell-free (CF) systems can achieve significant macro-diversity gain, thereby providing uniformly reliable service to each user equipment (UE). However, due to limitations in system scalability and the [...] Read more.
Under the ideal assumption of deploying only one central processing unit (CPU) in the entire system, cell-free (CF) systems can achieve significant macro-diversity gain, thereby providing uniformly reliable service to each user equipment (UE). However, due to limitations in system scalability and the feasibility of strict phase synchronization, CF systems require a multi-CPU setup and perform coherent transmission at a smaller scale. Moreover, conventional CF systems typically operate in time-division duplex (TDD) mode and utilize statistical channel state information (CSI) for downlink (DL) decoding, but the channel hardening effect is not significant. These factors reduce downlink spectral efficiency (SE) and increase DL transmission time, leading to higher energy consumption in CF systems. To address these issues, we introduce downlink channel estimation (DLCE) in multi-CPU CF systems and derive the approximate achievable DL SE. To reduce DL pilot overhead, we propose an uplink–pilot-reuse-constrained DL pilot allocation principle. Based on this principle, we develop a farthest distance pilot allocation (FDPA) algorithm to mitigate pilot contamination. In addition, leveraging the characteristics of the heuristic distributed power allocation algorithm, we propose two access point (AP) clustering algorithms: one based on CSI (BCSI) and the other based on coherent group size (BCGS). Simulation results indicate that the introduction of DLCE significantly improves DL SE in multi-CPU CF massive MIMO systems, while the proposed FDPA algorithm further enhances DL SE. The BCSI and BCGS algorithms also effectively improve DL SE and help reduce energy consumption. By combining DLCE, the FDPA algorithm, and the proposed AP clustering algorithms, the energy consumption of multi-CPU CF systems can be significantly reduced. Full article
(This article belongs to the Special Issue Advanced Techniques for Massive MIMO Systems in Next-Generation Wireless Communication and Networks)
8 pages, 738 KiB  
Article
Double Resonance of Electromagnetically Induced Transparency of Rydberg Atom in Counter-Propagating Configuration
by Chao Li, Guo Ma, Mingwei Lei and Meng Shi
Electronics 2024, 13(22), 4391; https://doi.org/10.3390/electronics13224391 (registering DOI) - 8 Nov 2024
Abstract
The double resonance phenomenon of EIT is studied through the ladder three-level Rydberg system. A probe laser with the wavelength nm is used to coupling the ground state 6S1/2 to the middle state 6P3/2, and a coupling laser with the [...] Read more.
The double resonance phenomenon of EIT is studied through the ladder three-level Rydberg system. A probe laser with the wavelength nm is used to coupling the ground state 6S1/2 to the middle state 6P3/2, and a coupling laser with the wavelength nm is implemented to couple the state 6P3/2 to the Rydberg state 62D5/2. A special optical scheme is designed, in which the co-propagating and counter-propagating configurations are both used. As a result, the double resonance of electromagnetically induced transparency (EIT) with the Rydberg atom is observed. By comparing the distance between the double peaks, it is found that the double resonance phenomenon comes from the Doppler effect, and the distance between the two resonance peaks in the absorption spectrum is related to the detuning of the resonant lasers. Full article
(This article belongs to the Special Issue Advanced Wireless Technologies for Next-G Networks: Antennas, Circuits, and Systems)
15 pages, 5321 KiB  
Article
Design of a High-Voltage Arbitrary Waveform Generator Using a Modular Cascaded H-Bridge Topology
by Weichuan Zhao, Gijs Willem Lagerweij, Brecht Hurkmans and Mohamad Ghaffarian Niasar
Electronics 2024, 13(22), 4390; https://doi.org/10.3390/electronics13224390 (registering DOI) - 8 Nov 2024
Abstract
As the integration of renewable energy sources into the grid increases, the insulation systems of grid components such as transformers and switchgear encounter significant challenges due to the transients and harmonics generated by power-electronic-based converters. A test generator capable of replicating these component [...] Read more.
As the integration of renewable energy sources into the grid increases, the insulation systems of grid components such as transformers and switchgear encounter significant challenges due to the transients and harmonics generated by power-electronic-based converters. A test generator capable of replicating these component stresses is essential to accurately evaluate these insulation systems under real-grid conditions. This paper proposes a modular cascaded H-bridge-based high-voltage arbitrary waveform generator, prototyped with three stages to generate customized waveforms (triangular, sawtooth, pulse, and complex) up to 8 kV. The H-bridge modules are designed using Si MOSFETs with a maximum blocking voltage of 4.5 kV. The input to the HV H-bridge module is provided by a 10 kV medium-frequency transformer, whose design is described with a focus on the insulation system and winding configuration. This transformer is driven by a zero-voltage switching driver. This arbitrary waveform generator excels in several aspects, including a straightforward design procedure, compact size, high voltage capability, ease of integration, and cost. Full article
(This article belongs to the Section Power Electronics)
17 pages, 5816 KiB  
Article
Integrated AI Medical Emergency Diagnostics Advising System
by Sergey K. Aityan, Abdolreza Mosaddegh, Rolando Herrero, Francesco Inchingolo, Kieu C. D. Nguyen, Mario Balzanelli, Rita Lazzaro, Nicola Iacovazzo, Angelo Cefalo, Lucia Carriero, Manuel Mersini, Jacopo M. Legramante, Marilena Minieri, Luigi Santacroce and Ciro Gargiulo Isacco
Electronics 2024, 13(22), 4389; https://doi.org/10.3390/electronics13224389 (registering DOI) - 8 Nov 2024
Abstract
The application of AI (Artificial Intelligence) in emergency medicine helps significantly improve the quality of diagnostics under limitations of resources and time constraints in emergency cases. We have designed a comprehensive AI-based diagnostic and treatment plan decision-support system for emergency medicine by integrating [...] Read more.
The application of AI (Artificial Intelligence) in emergency medicine helps significantly improve the quality of diagnostics under limitations of resources and time constraints in emergency cases. We have designed a comprehensive AI-based diagnostic and treatment plan decision-support system for emergency medicine by integrating the available LLMs (Large Language Models), like ChatGPT, Gemini, Claude, and others, and tuning them up with additional training on actual emergency cases. There is a special focus on early detection of life-threatening and time-sensitive diseases like sepsis, stroke, and heart attack, which are the major causes of death in emergency medicine. Additional training was conducted on a total of 600 cases (300 sepsis; 300 non-sepsis). The collective capability of the integrated LLMs is much stronger than each individual engine. Emergency cases can be predicted based on information from multiple sensors and streaming sources combining traditional IT (Information Technology) infrastructure with Internet of Things (IoT) schemes. Medical personnel compare and validate the AI models used in this work. Full article
(This article belongs to the Special Issue Internet of Things (IoT) for Next-Generation Smart Systems)
►▼ Show Figures

Figure 1

33 pages, 9052 KiB  
Article
A Q-Learning-Based Approach to Design an Energy-Efficient MAC Protocol for UWSNs Through Collision Avoidance
by Qiao Gang, Wazir Ur Rahman, Feng Zhou, Muhammad Bilal, Wasiq Ali, Sajid Ullah Khan and Muhammad Ilyas Khattak
Electronics 2024, 13(22), 4388; https://doi.org/10.3390/electronics13224388 (registering DOI) - 8 Nov 2024
Abstract
Deploying and effectively utilizing wireless sensor networks (WSNs) in underwater habitats remains a challenging task. In underwater wireless sensors networks (UWSNs), the availability of a continuous energy source for communicating with nodes is either very costly or is prohibited due to the marine [...] Read more.
Deploying and effectively utilizing wireless sensor networks (WSNs) in underwater habitats remains a challenging task. In underwater wireless sensors networks (UWSNs), the availability of a continuous energy source for communicating with nodes is either very costly or is prohibited due to the marine life law enforcement agencies. So, in order to address this issue, we present a Q-learning-based approach to designing an energy-efficient medium access control (MAC) protocol for UWSNs through collision avoidance. The main goal is to prolong the network’s lifespan by optimizing the communication methods, specifically focusing on improving the energy efficiency of the MAC protocols. Factors affecting the energy consumption in communication are adjustments to the interference ranges, i.e., changing frequencies repeatedly to obtain optimal communication; data packet retransmissions in case of a false acknowledgment; and data packet collision occurrences in the channel. Our chosen protocol stands out by enabling sensor (Rx) nodes to avoid collisions without needing extra communication or prior interference knowledge. According to the results obtained through simulations, our protocol may increase the network’s performance in terms of network throughput by up to 23% when compared to benchmark protocols depending on the typical traffic load. It simultaneously decreases end-to-end latency, increases the packet delivery ratio (PDR), boosts channel usage, and lessens packet collisions by over 38%. All these gains result in minimizing the network’s energy consumption, with a proportional gain. Full article
(This article belongs to the Special Issue New Advances in Underwater Communication Systems)
15 pages, 2348 KiB  
Review
System-Level Statistical Eye Diagram for Signal Integrity
by Junyong Park and Hyunwook Park
Electronics 2024, 13(22), 4387; https://doi.org/10.3390/electronics13224387 (registering DOI) - 8 Nov 2024
Abstract
This paper reviews a statistical signal integrity (SI) analysis at the system level for a high-speed system design. An eye diagram graphically shows a system’s performance. However, an eye diagram requires a long acquisition time for accurate results. The time-consuming nature of this [...] Read more.
This paper reviews a statistical signal integrity (SI) analysis at the system level for a high-speed system design. An eye diagram graphically shows a system’s performance. However, an eye diagram requires a long acquisition time for accurate results. The time-consuming nature of this process makes an eye-diagram-based SI analysis inefficient. Thus, a statistical eye diagram was introduced for an efficient SI analysis. The statistical eye diagram provides not only SI metrics such as eye height (EH) and eye width (EW), but also the bit-error rate (BER) profile for each channel. The data transmitted over the high-speed channels are determined by an upper hierarchy such as a system. In other words, the data are a function of the system parameters. In conclusion, a statistical eye diagram is determined by the high-speed channels and the system parameters. Therefore, the previous works on statistical eye diagrams at the channel and system levels have been introduced, respectively. This paper reviews the previous works for a system-level statistical SI analysis with a statistical eye diagram. Full article
(This article belongs to the Special Issue Advances in Signals and Systems Research)
►▼ Show Figures

Figure 1

19 pages, 6828 KiB  
Article
Research on Quadrotor Control Based on Genetic Algorithm and Particle Swarm Optimization for PID Tuning and Fuzzy Control-Based Linear Active Disturbance Rejection Control
by Kelin Li, Yalei Bai and Haoyu Zhou
Electronics 2024, 13(22), 4386; https://doi.org/10.3390/electronics13224386 (registering DOI) - 8 Nov 2024
Abstract
The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In [...] Read more.
The control system of a quadrotor aircraft is characterized by nonlinearity, strong coupling, and underactuation, making it susceptible to external disturbances that can affect flight performance. To address this issue, this paper proposes a novel control system based on inner–outer loop architecture. In this system, the outer loop position control adopts a PID controller optimized by Genetic Algorithm-based Particle Swarm Optimization (GA-PSO), while the inner loop attitude control employs a Linear Active Disturbance Rejection Controller (LADRC) with fuzzy algorithm-based adaptive tuning, forming a dual-loop control structure. Comparisons with traditional dual-loop cascaded PID controllers, conventional PID in the outer loop with LADRC in the inner loop, and conventional PID in the outer loop with fuzzy algorithm-based adaptive tuning in the inner loop demonstrate that the proposed control system can stably track the desired position and attitude angles under certain external disturbances, exhibiting excellent anti-disturbance capability and stability. Full article
►▼ Show Figures

Figure 1

17 pages, 4318 KiB  
Article
Dynamic Path Planning Scheme for OHT in AMHS Based on Map Information Double Deep Q-Network
by Qi Ao, Yue Zhou, Wei Guo, Wenguang Wang and Ying Ye
Electronics 2024, 13(22), 4385; https://doi.org/10.3390/electronics13224385 - 8 Nov 2024
Abstract
AMHSs (Automated Material Handling Systems) are widely used in major Fabs (semiconductor fabrication plants). The OHT in an AMHS is responsible for handling the FOUP (Front Opening Unified Pod) within the Fabs. Due to the unidirectional track, the movement path of the OHT [...] Read more.
AMHSs (Automated Material Handling Systems) are widely used in major Fabs (semiconductor fabrication plants). The OHT in an AMHS is responsible for handling the FOUP (Front Opening Unified Pod) within the Fabs. Due to the unidirectional track, the movement path of the OHT aims to avoid congested areas caused by operations or malfunctions as much as possible, to improve the overall FOUP handling efficiency. To do so, we propose a dynamic path planning method, MI-DDQN (Map Information Double Deep Q-Network), driven by deep reinforcement learning and based on map information. Firstly, we design and establish a map information state space model based on the core elements of the OHT path planning in the AMHS. Then, we design an OHT motion simulator to simulate the position coordinate transformation of the OHT, providing real-time coordinate update data for the OHT during the algorithm training process. We design a deep reinforcement learning algorithm structure based on map information model and a convolutional neural network model structure and use the algorithm to train the network model. Finally, the designed task generation module and OHT motion simulator are used to randomly generate the starting position and task position of the OHT during the training process to enhance the richness of the data. The addition of a “fault” OHT verifies the method’s ability to plan routes in complex road conditions such as congestion that may occur at any time. Full article
►▼ Show Figures

Figure 1

21 pages, 2218 KiB  
Article
Overbounding the Model Uncertainty for Kalman Filter-Based Advanced Receiver Autonomous Integrity Monitoring in the Presence of Time Correlation by the Hybrid Evolutionary Algorithm
by Hengwei Zhang and Yiping Jiang
Electronics 2024, 13(22), 4384; https://doi.org/10.3390/electronics13224384 - 8 Nov 2024
Abstract
Overbounding the integrity risk is a significant challenge for Kalman filter (KF)-based advanced receiver autonomous integrity monitoring (ARAIM) when the measurement error has an uncertain time correlation. Thus, this paper presents a method that addresses this challenge by effectively bounding the integrity risk [...] Read more.
Overbounding the integrity risk is a significant challenge for Kalman filter (KF)-based advanced receiver autonomous integrity monitoring (ARAIM) when the measurement error has an uncertain time correlation. Thus, this paper presents a method that addresses this challenge by effectively bounding the integrity risk for KF-based ARAIM while considering the uncertainty in the model of the time-correlated error. Firstly, the recursive equation for covariance is derived, establishing a direct mathematical expression that links the integrity risk and the correlation time constant. Subsequently, a min–max optimization model is constructed, utilizing the obtained expression as the objective function, to simultaneously bound the integrity risk and reduce conservatism. To effectively address the current min–max optimization problem, a hybrid evolutionary algorithm is proposed, which conducts global searching followed by local searching. The simulation result demonstrates that it outperforms other algorithms, enabling rapid attainment of the minimum upper bound on the integrity risk. Full article
(This article belongs to the Special Issue Constellation Satellite Design and Application)
►▼ Show Figures

Figure 1

33 pages, 1700 KiB  
Article
How Does the Nexus Between Digitalization and Banking Performance Drive Digital Transformation in Central and Eastern European Countries?
by Alina Georgiana Manta, Roxana Maria Bădîrcea, Claudia Gherțescu and Liviu Florin Manta
Electronics 2024, 13(22), 4383; https://doi.org/10.3390/electronics13224383 - 8 Nov 2024
Abstract
The aim of this paper is to create a digitalization index for banking sectors using a set of indicators based on World Bank data for the period of 2010–2021, which will allow us to rank the sectors of Central and Eastern European countries [...] Read more.
The aim of this paper is to create a digitalization index for banking sectors using a set of indicators based on World Bank data for the period of 2010–2021, which will allow us to rank the sectors of Central and Eastern European countries (CEECs). The digitalization index is built based on how ready banks are for digitalization, the potential customers available for digital banking, and the level of digital infrastructure, with each of these aspects representing one pillar. Based on the calculation of the digitalization index, we emphasize that Romania is the leader, followed by Latvia and Lithuania, while Hungary and Estonia are at the opposite pole. Furthermore, we applied the fully modified ordinary least squares (FMOLS) method to measure the impact of digitalization on banking performance. This study reveals that Romania, Latvia, and Lithuania lead in digital banking transformation due to significant investments in infrastructure and customer engagement, while Hungary and Poland lag in terms of digital readiness. The results indicate that digitalization has a significant positive effect on banking performance (ROE), although countries experiencing market saturation had the potential to see a decline post-2018, necessitating further innovation to sustain growth. In the digitalization context, the results are relevant for policymakers, showing that investing more in digitalization is important and that there is a need to help people have greater access to banking services due to a lack of willingness and financial education, factors which prevent them from embracing digital changes. The results show that improving banking digitalization positively influences banking performances. This study provides an innovative and complex index for assessing banking digitalization in Central and Eastern Europe, with valuable implications for policymakers. We highlight the need to align digitalization policies with the specific level of digital development of each country in order to optimize the integration of digital technologies and enhance economic competitiveness. Full article
(This article belongs to the Special Issue The Role of Digital Technologies in Sustainability Accounting and Reporting)
►▼ Show Figures

Figure 1

16 pages, 6775 KiB  
Article
Effect of Coupling Impedance on Stability Assessment of Grid-Forming Converters Under Various Grid Conditions
by Haiguo Tang, Jinhao Wang, Chao Wu and Yong Wang
Electronics 2024, 13(22), 4382; https://doi.org/10.3390/electronics13224382 - 8 Nov 2024
Abstract
The phenomenon of frequency coupling is widely observed in grid-forming (GFM) converters due to the presence of asymmetrical controls and nonlinear blocks. However, the factors influencing frequency coupling have not been thoroughly explored. This paper introduces a systematic small-signal impedance model of GFM [...] Read more.
The phenomenon of frequency coupling is widely observed in grid-forming (GFM) converters due to the presence of asymmetrical controls and nonlinear blocks. However, the factors influencing frequency coupling have not been thoroughly explored. This paper introduces a systematic small-signal impedance model of GFM converters that intuitively reflects the factors affecting frequency coupling and provides a detailed analysis of how coupling impedance affects stability. It is demonstrated that the influencing factors of coupling impedance are an active power loop and reactive power loop. Specifically, the active power loop influences coupling impedance characteristics near the fundamental frequency, while the reactive power loop impacts the entire frequency range. This paper first reveals that the reactive power loop has a more pronounced effect on frequency coupling than the active power loop. Additionally, the variation in the steady-state operating points also affects the degree of frequency coupling of the GFM converters, primarily affecting the coupling impedance characteristics beyond the fundamental frequency, and the low operating points tend to affect system stability adversely. Finally, simulation results validate the accuracy of the mathematical model and theoretical analysis. Full article
►▼ Show Figures

Figure 1

21 pages, 7973 KiB  
Article
Research on Target Hybrid Recognition and Localization Methods Based on an Industrial Camera and a Depth Camera in Complex Scenes
by Mingxin Yuan, Jie Li, Borui Cao, Shihao Bao, Li Sun and Xiangbin Li
Electronics 2024, 13(22), 4381; https://doi.org/10.3390/electronics13224381 - 8 Nov 2024
Viewed by 23
Abstract
In order to improve the target visual recognition and localization accuracy of robotic arms in complex scenes with similar targets, hybrid recognition and localization methods based on an industrial camera and depth camera are proposed. First, according to the speed and accuracy requirements [...] Read more.
In order to improve the target visual recognition and localization accuracy of robotic arms in complex scenes with similar targets, hybrid recognition and localization methods based on an industrial camera and depth camera are proposed. First, according to the speed and accuracy requirements of target recognition and localization, YOLOv5s is introduced as the basic algorithm model for target hybrid recognition and localization. Then, in order to improve the accuracy of target recognition and coarse localization based on an industrial camera (eye-to-hand), the AFPN feature fusion module, simple and parameter-free attention module (SimAM), and soft non-maximum suppression (Soft NMS) are introduced. In order to improve the accuracy of target recognition and fine localization based on a depth camera (eye-in-hand), the SENetV2 backbone network structure, dynamic head module, deformable attention mechanism, and chain-of-thought prompted adaptive enhancer network are introduced. After that, on the basis of constructing a dual camera platform for target hybrid recognition and localization, the hand–eye calibration, collection and production of image datasets required for model training are completed. Finally, for the docking of the oil filling port, the hybrid recognition and localization experimental tests are completed in sequence. The test results show that in target recognition and coarse localization based on the industrial camera, the recognition accuracy of the designed model reaches 99%, and the average localization errors in the horizontal and vertical directions are 2.22 mm and 3.66 mm, respectively. In target recognition and fine localization based on the depth camera, the recognition accuracy of the designed model reaches 98%, and the average errors in depth, horizontal, and vertical directions are 0.12 mm, 0.28 mm, and 0.16 mm, respectively. These not only verify the effectiveness of the target hybrid recognition and localization methods based on dual cameras, but also demonstrate that they meet the high-precision recognition and localization requirements in complex scenes. Full article
(This article belongs to the Special Issue Applications and Challenges of Image Processing in Smart Environment)
►▼ Show Figures

Figure 1

20 pages, 11249 KiB  
Article
Design and Equivalent Circuit Model Extraction of a Fractal Slot-Loaded 3–40 GHz Super Wideband Antenna
by Wasan Alamro, Boon-Chong Seet, Lulu Wang and Prabakar Parthiban
Electronics 2024, 13(22), 4380; https://doi.org/10.3390/electronics13224380 - 8 Nov 2024
Viewed by 32
Abstract
In this paper, we present the design and equivalent circuit model (ECM) of a fractal slot-loaded super wideband (SWB) antenna for compact and high-performance applications operating in the 3–40 GHz range. The proposed antenna features a compact dimension of 40 × 35 × [...] Read more.
In this paper, we present the design and equivalent circuit model (ECM) of a fractal slot-loaded super wideband (SWB) antenna for compact and high-performance applications operating in the 3–40 GHz range. The proposed antenna features a compact dimension of 40 × 35 × 1.57 mm³, a measured bandwidth ratio of 13:1, a peak gain of 9.7 dBi, an average radiation efficiency of 94%, and a low cross-polarization level across the entire bandwidth. The presented ECM is derived using transmission line theory and incorporates the individual behavior of each constituting element of the antenna. A dual sequential optimization approach is employed to determine the optimal element values. The ECM results show good agreement with both simulated and measured results in terms of the magnitude of reflection coefficient |S11| and both real and imaginary impedances with low mean absolute percentage errors of 4.9%, 7.5%, and 7.7%, respectively, demonstrating the model’s ability to accurately predict the antenna’s performance. Full article
(This article belongs to the Section Microwave and Wireless Communications)
►▼ Show Figures

Figure 1

12 pages, 5731 KiB  
Article
A Programmable Gate Driver Module-Based Multistage Voltage Regulation SiC MOSFET Switching Strategy
by Jixiang Tan, Zhongfu Zhou and Gongjie Zou
Electronics 2024, 13(22), 4379; https://doi.org/10.3390/electronics13224379 - 8 Nov 2024
Viewed by 97
Abstract
Silicon carbide (SiC) metal-oxide semiconductor field-effect transistors (MOSFETs), as a new material, have the advantages of low drain-source resistance, high thermal conductivity, low leakage current, and high switching frequency compared with silicon (Si)-based MOSFETs. Therefore, in many industrial applications, Si MOSFETs have been [...] Read more.
Silicon carbide (SiC) metal-oxide semiconductor field-effect transistors (MOSFETs), as a new material, have the advantages of low drain-source resistance, high thermal conductivity, low leakage current, and high switching frequency compared with silicon (Si)-based MOSFETs. Therefore, in many industrial applications, Si MOSFETs have been replaced by SiC MOSFETs. However, as the switching speed increases exponentially, some problems are amplified, the most serious of which is the overshoot of current and voltage. The increase in voltage and current slope caused by high switching speeds inevitably leads to overshoot, oscillations, and additional losses in the circuit. This paper focusses on the actual performance of the optimised switching strategy (OSS) in circuit testing and combines the existing simulation results to verify the practicability of OSS. In this paper, the optimised switching strategy is introduced first, and then, the LTspice model of SiC MOSFET is established in detail and verifies the feasibility of the OSS through half-bridge circuit simulation. Finally, the test platform is built using a programmable gate drive module (2ASC-12A1HP). Through a 400 V/30 A double-pulse test, the practicality of the OSS is verified. The experiments show that the OSS can greatly improve the switching performance of SiC MOSFETs. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances of Power Electronics)
►▼ Show Figures

Figure 1

12 pages, 1186 KiB  
Article
Nets4Learning: A Web Platform for Designing and Testing ANN/DNN Models
by Antonio Mudarra, David Valdivia, Pietro Ducange, Manuel Germán, Antonio J. Rivera and M. Dolores Pérez-Godoy
Electronics 2024, 13(22), 4378; https://doi.org/10.3390/electronics13224378 - 8 Nov 2024
Viewed by 99
Abstract
Nowadays, any research discipline is interested in tackling its problems with artificial intelligence and, therefore, is demanding knowledge and frameworks with the aim of developing and using intelligent methods. Within this scenario, neural networks stand out for the important results they have achieved. [...] Read more.
Nowadays, any research discipline is interested in tackling its problems with artificial intelligence and, therefore, is demanding knowledge and frameworks with the aim of developing and using intelligent methods. Within this scenario, neural networks stand out for the important results they have achieved. This paper introduces Nets4Learning, a web platform for designing, training and testing artificial/deep neural network models. The application deals with some of the most popular tasks in the data science field such as tabular classification, regression, image classification and object detection. Nets4Learning has been designed so that any researcher from any discipline can easily develop neural network models without special programming or digital skills. In fact, the user does not have to install anything as the application is publicly available and can be accessed from any device. The site also has manuals, glossaries, etc., and all this code is available on GitHub. Full article
(This article belongs to the Special Issue Signal, Image and Video Processing: Development and Applications)
►▼ Show Figures

Figure 1

22 pages, 2149 KiB  
Article
Robust Biometric Verification Using Phonocardiogram Fingerprinting and a Multilayer-Perceptron-Based Classifier
by Roberta Avanzato, Francesco Beritelli and Salvatore Serrano
Electronics 2024, 13(22), 4377; https://doi.org/10.3390/electronics13224377 - 8 Nov 2024
Viewed by 109
Abstract
Recently, a new set of biometric traits, called medical biometrics, have been explored for human identity verification. This study introduces a novel framework for recognizing human identity through heart sound signals, commonly referred to as phonocardiograms (PCGs). The framework is built on extracting [...] Read more.
Recently, a new set of biometric traits, called medical biometrics, have been explored for human identity verification. This study introduces a novel framework for recognizing human identity through heart sound signals, commonly referred to as phonocardiograms (PCGs). The framework is built on extracting and suitably processing Mel-Frequency Cepstral Coefficients (MFCCs) from PCGs and on a classifier based on a Multilayer Perceptron (MLP) network. A large dataset containing heart sounds acquired from 206 people has been used to perform the experiments. The classifier was tuned to obtain the same false positive and false negative misclassification rates (equal error rate: EER = FPR = FNR) on chunks of audio lasting 2 s. This target has been reached, splitting the dataset into 70% and 30% training and testing non-overlapped subsets, respectively. A recurrence filter has been applied to also improve the performance of the system in the presence of noisy recordings. After the application of the filter on chunks of audio signal lasting from 2 to 22 s, the performance of the system has been evaluated in terms of recall, specificity, precision, negative predictive value, accuracy, and F1-score. All the performance metrics are higher than 97.86% with the recurrence filter applied on a window lasting 22 s and in different noise conditions. Full article
(This article belongs to the Special Issue Machine Learning in Electronic and Biomedical Engineering, 3rd Edition)
►▼ Show Figures

Figure 1

12 pages, 2453 KiB  
Article
Threshold Filtering for Detecting Label Inference Attacks in Vertical Federated Learning
by Liansheng Ding, Haibin Bao, Qingzhe Lv, Feng Zhang, Zhouyang Zhang, Jianliang Han and Shuang Ding
Electronics 2024, 13(22), 4376; https://doi.org/10.3390/electronics13224376 - 8 Nov 2024
Viewed by 154
Abstract
Federated learning, as an emerging machine-learning method, has received widespread attention because it allows users to train locally during the training process and uses relevant cryptographic knowledge to safeguard the privacy of data during model aggregation. However, existing federated learning is also susceptible [...] Read more.
Federated learning, as an emerging machine-learning method, has received widespread attention because it allows users to train locally during the training process and uses relevant cryptographic knowledge to safeguard the privacy of data during model aggregation. However, existing federated learning is also susceptible to privacy breaches, e.g., label inference attacks against vertical federated learning scenarios, where an adversary is able to reason about the labels of other participants based on the trained model, leading to serious privacy breaches. In this paper, we design a detection method for label inference attacks in vertical federated learning scenarios, which is able to detect the attacks based on the principles of the attacks. We design a threshold-filtering detection method based on the principle of attack to determine that the model is under attack when the threshold value is greater than a set parameter. Furthermore, we have created six threat model classifications based on different a priori conditions of the adversary to comprehensively analyze the adversary’s attacks. In addition to the detection method of attacks, the extent of attacks on the model and the effectiveness of the defense can also be evaluated. The evaluation module will experimentally measure the changes in the relevant metrics such as the accuracy of the attack, the F1 score, and the change in the accuracy after the defense method. For example, detection in the full connected neural network model assesses the attack and defense effectiveness of the model with an attack accuracy of 86.72% in the breast cancer Wisconsin dataset and an F1 score of 0.743, which is reduced to 36.36% after dispersed training. This ensures that users have an overall grasp of the extent to which the training model is under attack before deploying the model. Full article
(This article belongs to the Special Issue Recent Advances in Cybersecurity and Information Security)
►▼ Show Figures

Figure 1

19 pages, 1960 KiB  
Article
Proposed Explainable Interference Control Technique in 6G Networks Using Large Language Models (LLMs)
by H. Ahmed Tahir, Walaa Alayed, Waqar Ul Hassan and Amir Haider
Electronics 2024, 13(22), 4375; https://doi.org/10.3390/electronics13224375 - 8 Nov 2024
Viewed by 240
Abstract
After the advent of 5th generation (5G) and 6th generation (6G) cellular networks, the complexity of managing real-time signal interference has increased in dense and dynamic environments. Traditional interference techniques, such as frequency reuse and allocation, while effective, lack robust adaptability and transparency [...] Read more.
After the advent of 5th generation (5G) and 6th generation (6G) cellular networks, the complexity of managing real-time signal interference has increased in dense and dynamic environments. Traditional interference techniques, such as frequency reuse and allocation, while effective, lack robust adaptability and transparency needed to reduce interference in advanced communication networks. This paper introduces a novel approach that fuses large language models (LLMs) and Explainable Artificial Intelligence (XAI) to mitigate interference and enhance interference management in the mathematical foundations of 6G networks. The proposed approach provides accurate interference predictions, which the LLM balances with its complex architecture, necessary to meet the demands of beyond 5G and 6G networks, along with interpretable explanations to ensure transparency in decision-making. The proposed framework has been evaluated across various performance metrics. Interference latency consistently achieves lower rates of 0.95 s, compared to traditional techniques, which average around 1 s. Furthermore, the confidence score of the LLM shows a stable value of 0.87 throughout the system, compared to 0.85 in techniques without LLMs. Overall, the XAI-driven LLM demonstrates the potential of incorporating LLMs and XAI into wireless networks to improve resilience in next-generation networks. This proof of concept introduces a novel framework that offers new dimensions in wireless communication, particularly for interference management, prediction, and mitigation. Full article
(This article belongs to the Special Issue Trends and Prospects in 6G Wireless Communication)
►▼ Show Figures

Figure 1

21 pages, 8999 KiB  
Article
An MPC-DCM Control Method for a Forward-Bending Biped Robot Based on Force and Moment Control
by Zhongshan Wei, Wenyan Deng, Zhengyong Feng, Tao Wang and Xinxiang Huang
Electronics 2024, 13(22), 4374; https://doi.org/10.3390/electronics13224374 - 8 Nov 2024
Viewed by 253
Abstract
For a forward-bending biped robot with 10 degrees of freedom on its legs, a new control framework of MPC-DCM based on force and moment is proposed in this paper. Specifically, the Diverging Component of Motion (DCM) is a stability criterion for biped robots [...] Read more.
For a forward-bending biped robot with 10 degrees of freedom on its legs, a new control framework of MPC-DCM based on force and moment is proposed in this paper. Specifically, the Diverging Component of Motion (DCM) is a stability criterion for biped robots based on linear inverted pendulum, and Model Predictive Control (MPC) is an optimization solution strategy using rolling optimization. In this paper, DCM theory is applied to the state transition matrix of the system, combined with simplified rigid body dynamics, the mathematical description of the biped robot system is established, the classical MPC method is used to optimize the control input, and DCM constraints are added to the constraints of MPC, making the real-time DCM approximate to a straight line in the walking single gait. At the same time, the linear angle and friction cone constraints are considered to enhance the stability of the robot during walking. In this paper, MATLAB/Simulink is used to simulate the robot. Under the control of this algorithm, the robot can reach a walking speed of 0.75 m/s and has a certain anti-disturbance ability and ground adaptability. In this paper, the Model-H16 robot is used to deploy the physical algorithm, and the linear walking and obstacle walking of the physical robot are realized. Full article
►▼ Show Figures

Figure 1

16 pages, 2966 KiB  
Article
Integrated Extraction of Entities and Relations via Attentive Graph Convolutional Networks
by Chuhan Gao, Guixian Xu and Yueting Meng
Electronics 2024, 13(22), 4373; https://doi.org/10.3390/electronics13224373 - 8 Nov 2024
Viewed by 246
Abstract
For information security, entity and relation extraction can be applied in sensitive information protection, data leakage detection, and other aspects. The current approaches to entity relation extraction not only ignore the relevance and dependency between name entity recognition and relation extraction but also [...] Read more.
For information security, entity and relation extraction can be applied in sensitive information protection, data leakage detection, and other aspects. The current approaches to entity relation extraction not only ignore the relevance and dependency between name entity recognition and relation extraction but also may result in the cumulative propagation of errors. To solve this problem, it is proposed that an end-to-end joint entity and relation extraction model based on the Attention mechanism and Graph Convolutional Network (GCN) to simultaneously extract named entities and their relationships. The model includes three parts: the detection of entity span, the construction of an entity relation weighted graph, and the inference of entity relation type. Firstly, the detection of entity spans is viewed as a sequence labeling problem, and a multi-feature fusion approach for word embedding representation is designed to calculate all entity spans in a sentence to form an entity span matrix. Secondly, the entity span matrix is employed in the Multi-Head Attention mechanism for constructing the weighted adjacency matrix of the entity relation graph. Finally, for the inference of entity relation type, considering the interaction between entities and relations, the entity span matrix and relation connection matrix are simultaneously fed into the GCN for integrated extraction of entities and relations. Our model is evaluated on the public NYT dataset, attaining a precision of 66.4%, a recall of 63.1%, and an F1 score of 64.7% for joint entity and relation extraction, significantly outperforming other approaches. Experiments demonstrate that the proposed model is helpful for inferring entities and relations, considering the interaction between entities and relations through the Attention mechanism and GCN. Full article
(This article belongs to the Special Issue Network Security Management in Heterogeneous Networks)
►▼ Show Figures

Figure 1

15 pages, 1240 KiB  
Article
Position-Guided Multi-Head Alignment and Fusion for Video Super-Resolution
by Yanbo Gao, Xun Cai, Shuai Li, Jiajing Chai and Chuankun Li
Electronics 2024, 13(22), 4372; https://doi.org/10.3390/electronics13224372 - 7 Nov 2024
Viewed by 291
Abstract
Video super-resolution (VSR), which takes advantage of multiple low-resolution (LR) video frames to reconstruct corresponding high-resolution (HR) frames in a video, has raised increasing interest. To upsample an LR frame (denoted by a reference frame), VSR methods usually align multiple neighboring frames (denoted [...] Read more.
Video super-resolution (VSR), which takes advantage of multiple low-resolution (LR) video frames to reconstruct corresponding high-resolution (HR) frames in a video, has raised increasing interest. To upsample an LR frame (denoted by a reference frame), VSR methods usually align multiple neighboring frames (denoted by supporting frames) to the reference frame first in order to provide more relevant information. The existing VSR methods usually employ deformable convolution to conduct the frame alignment, where the whole supporting frame is aligned to the reference frame without a specific target and without supervision. Thus, the aligned features are not explicitly learned to provide the HR frame information and cannot fully explore the supporting frames. To address this problem, in this work, we propose a novel video super-resolution framework with Position-Guided Multi-Head Alignment, termed as PGMH-A, to explicitly align the supporting frames to different spatial positions of the HR frame (denoted by different heads). It injects explicit position information to obtain multi-head-aligned features of supporting frames to better formulate the HR frame. PGMH-A can be trained individually or end-to-end with the ground-truth HR frames. Moreover, a Position-Guided Multi-Head Fusion, termed as PGMH-F, is developed based on the attention mechanism to further fuse the spatial–temporal information across temporal supporting frames, across multiple heads corresponding to the different spatial positions of an HR frame, and across multiple channels. Together, the proposed Position-Guided Multi-Head Alignment and Fusion (PGMH-AF) can provide VSR with better local details and temporal coherence. The experimental results demonstrate that the proposed method outperforms the state-of-the-art VSR networks. Ablation studies have also been conducted to verify the effectiveness of the proposed modules. Full article
(This article belongs to the Special Issue Challenges and Applications in Multimedia and Visual Computing)
►▼ Show Figures

Figure 1

17 pages, 4687 KiB  
Article
LTE: Lightweight Transformer Encoder for Orbit Prediction
by Seungwon Jeong and Youjin Shin
Electronics 2024, 13(22), 4371; https://doi.org/10.3390/electronics13224371 - 7 Nov 2024
Viewed by 252
Abstract
As the focus of space exploration has recently shifted from national efforts to private enterprises, interest in the space industry has increased. With the rising number of satellite launches, the risk of collisions between satellites and between satellites and space debris has grown, [...] Read more.
As the focus of space exploration has recently shifted from national efforts to private enterprises, interest in the space industry has increased. With the rising number of satellite launches, the risk of collisions between satellites and between satellites and space debris has grown, which can lead not only to property damage but also casualties caused by the debris. To address this issue, various machine learning and deep learning-based methods have been researched to improve the accuracy of satellite orbit prediction and mitigate these risks. However, most studies have applied basic machine learning models to orbit prediction without considering the model size and execution time, even though satellite operations require lightweight models that offer both a strong prediction performance and rapid execution. In this study, we propose a time series forecasting framework, the Lightweight Transformer Encoder (LTE), for satellite orbit prediction. The LTE is a prediction model that modifies the encoder structure of the Transformer model to enhance the accuracy of satellite orbit prediction and reduce the computational resources used. To evaluate its performance, we conducted experiments using about 4.8 million data points collected every minute from January 2016 to December 2018 by the KOMPSAT-3, KOMPSAT-3A, and KOMPSAT-5 satellites, which are part of the Korea Multi-Purpose Satellite (KOMPSAT) series operated by the Korea Aerospace Research Institute (KARI). We compare the performance of our model against various baseline models in terms of prediction error, execution time, and the number of parameters used. Our LTE model demonstrates significant improvements: it reduces the orbit prediction error by 50.61% in the KOMPSAT-3 dataset, 42.40% in the KOMPSAT-3A dataset, and 30.00% in the KOMPSAT-5 dataset compared to the next-best-performing model. Additionally, in the KOMPSAT-3 dataset, it decreases the execution time by 36.86% (from 1731 to 1093 s) and lowers the number of parameters by 2.33% compared to the next-best-performing model. Full article
(This article belongs to the Special Issue Deep and Classic Machine Learning in Signal, Image, and Video Analysis)
►▼ Show Figures

Figure 1

8 pages, 2153 KiB  
Article
A Tunable Microstrip-to-Waveguide Transition for Emergency Satellite Communication Systems
by Ying Xiong, Dawei Gao and Xianfeng Tang
Electronics 2024, 13(22), 4370; https://doi.org/10.3390/electronics13224370 - 7 Nov 2024
Viewed by 290
Abstract
A tunable microstrip-to-waveguide transition is proposed for the ground station of emergency satellite communication systems. The proposed transition, consisting of a microstrip, three matched patches, three waveguides, and three metal screws, can not only convert the microstrip’s TEM-dominated mode into the waveguide’s TE [...] Read more.
A tunable microstrip-to-waveguide transition is proposed for the ground station of emergency satellite communication systems. The proposed transition, consisting of a microstrip, three matched patches, three waveguides, and three metal screws, can not only convert the microstrip’s TEM-dominated mode into the waveguide’s TE mode within the transmitting frequency band, but also possesses the ability to filter out the amplified noise signals within the receiving frequency band around 12.5 GHz. Importantly, by adjusting the screws’ lengths, it is feasible to change the suppression frequency within the receiving frequency band and keep a good match within the transmitting frequency band. The measured results demonstrate that the proposed transition has a return loss of over 10 dB from 14 to 14.5 GHz and an out-of-band suppression of over 20 dB, from 12.25 to 12.7 GHz, with a typical value of −48 dB around 12.55 GHz. This unique feature eliminates the need for additional waveguide filters that prevent the amplified noise signal, thereby contributing to the miniaturization of the ground station. Full article
(This article belongs to the Special Issue Microwave Devices: Analysis, Design, and Application)
►▼ Show Figures

Figure 1

19 pages, 688 KiB  
Article
Advancing Pulmonary Nodule Detection with ARSGNet: EfficientNet and Transformer Synergy
by Maroua Oumlaz, Yassine Oumlaz, Aziz Oukaira, Amrou Zyad Benelhaouare and Ahmed Lakhssassi
Electronics 2024, 13(22), 4369; https://doi.org/10.3390/electronics13224369 - 7 Nov 2024
Viewed by 333
Abstract
Lung cancer, the leading cause of cancer-related deaths globally, presents significant challenges in early detection and diagnosis. The effective analysis of pulmonary medical imaging, particularly computed tomography (CT) scans, is critical in this endeavor. Traditional diagnostic methods, which are manual and time-intensive, underscore [...] Read more.
Lung cancer, the leading cause of cancer-related deaths globally, presents significant challenges in early detection and diagnosis. The effective analysis of pulmonary medical imaging, particularly computed tomography (CT) scans, is critical in this endeavor. Traditional diagnostic methods, which are manual and time-intensive, underscore the need for innovative, efficient, and accurate detection approaches. To address this need, we introduce the Adaptive Range Slice Grouping Network (ARSGNet), a novel deep learning framework that enhances early lung cancer diagnosis through advanced segmentation and classification techniques in CT imaging. ARSGNet synergistically integrates the strengths of EfficientNet and Transformer architectures, leveraging their superior feature extraction and contextual processing capabilities. This hybrid model proficiently handles the complexities of 3D CT images, ensuring precise and reliable lung nodule detection. The algorithm processes CT scans using short slice grouping (SSG) and long slice grouping (LSG) techniques to extract critical features from each slice, culminating in the generation of nodule probabilities and the identification of potential nodular regions. Incorporating shapley additive explanations (SHAP) analysis further enhances model interpretability by highlighting the contributory features. Our extensive experimentation demonstrated a significant improvement in diagnostic accuracy, with training accuracy increasing from 0.9126 to 0.9817. This advancement not only reflects the model’s efficient learning curve but also its high proficiency in accurately classifying a majority of training samples. Given its high accuracy, interpretability, and consistent reduction in training loss, ARSGNet holds substantial potential as a groundbreaking tool for early lung cancer detection and diagnosis. Full article
(This article belongs to the Special Issue Recent Trends in Artificial Learning and Data Processing for Biomedical Engineering)
►▼ Show Figures

Figure 1

12 pages, 1323 KiB  
Article
Analytical Analysis of Power-Constrained Repeaters’ Insertion in Large-Scale CMOS Chips
by Luigi Gaioni
Electronics 2024, 13(22), 4368; https://doi.org/10.3390/electronics13224368 - 7 Nov 2024
Viewed by 235
Abstract
As the die area of CMOS integrated circuits continues to increase, interconnects will become dominant in determining the performance of the circuits from the standpoint of speed and power consumption. Uniform repeater insertion is an effective method used to reduce the propagation delay [...] Read more.
As the die area of CMOS integrated circuits continues to increase, interconnects will become dominant in determining the performance of the circuits from the standpoint of speed and power consumption. Uniform repeater insertion is an effective method used to reduce the propagation delay of a signal in long resistive-capacitive lines. However, non-optimal repeaters’ insertion yields non-optimal circuit performance. In this work, we provide a mathematical treatment for optimal repeater insertion with power consumption constraints. In particular, a closed-form expression for the optimum number and size of repeaters is given for a two-stage buffer used as a repeater. The validation of the analytical solution is assessed by means of circuit simulations, by comparing the theoretical optimal number and size of the repeaters to be placed in the long resistive-capacitive line with the simulated values. Full article
(This article belongs to the Special Issue Advances in Low Power Circuit and System Design and Applications)
►▼ Show Figures

Figure 1

22 pages, 1556 KiB  
Article
Mobility-Based Multi-Hop Content Precaching Scheme in Content-Centric Vehicular Networks
by Hyunseok Choi, Youngju Nam, Gayeong Kim and Euisin Lee
Electronics 2024, 13(22), 4367; https://doi.org/10.3390/electronics13224367 - 7 Nov 2024
Viewed by 209
Abstract
Due to the rapid development of smart vehicles, such as self-driving cars, the demand for mobile data traffic by vehicle users has increased so much that base stations cannot handle it, causing delays in content provision. The burden on the base station can [...] Read more.
Due to the rapid development of smart vehicles, such as self-driving cars, the demand for mobile data traffic by vehicle users has increased so much that base stations cannot handle it, causing delays in content provision. The burden on the base station can be alleviated through roadside units (RSUs) to distribute the demand. However, outage zones, which fall outside the communication range of RSUs, still exist due to their high deployment cost. Existing schemes for covering outage zones have only considered single-hop precaching vehicles to provide precached content, which is insufficient to reduce outage zones effectively. Therefore, we propose a scheme to reduce outage zones by maximizing the amount of precached content using multi-hop precaching vehicles. The proposed scheme optimally selects precaching vehicles through a numerical model that calculates the amount of precached content. It enhances the process of multi-hop precaching by comparing the connection time of vehicles with the dark area time in the outage zone. To prevent excessive overheads due to frequent precaching vehicle handovers, the proposed scheme limits the selection to vehicles with a longer communication time, based on a precaching restriction indicator in the multi-hop precaching vehicle selection process. The simulation results show that our scheme outperforms representative schemes based on single-hop precaching. Full article
(This article belongs to the Special Issue Advances in Wireless Communication Performance Analysis)
►▼ Show Figures

Figure 1

20 pages, 12356 KiB  
Article
Quantifying the Remote Driver’s Interaction with 5G-Enabled Level 4 Automated Vehicles: A Real-World Study
by Shuo Li, Yanghanzi Zhang, Simon Edwards and Phil Blythe
Electronics 2024, 13(22), 4366; https://doi.org/10.3390/electronics13224366 - 7 Nov 2024
Viewed by 281
Abstract
This real-world investigation aimed to quantify the human–machine interaction between remote drivers of teleoperation systems and the Level 4 automated vehicle in a real-world setting. The primary goal was to investigate the effects of disengagement and distraction on remote driver performance and behaviour. [...] Read more.
This real-world investigation aimed to quantify the human–machine interaction between remote drivers of teleoperation systems and the Level 4 automated vehicle in a real-world setting. The primary goal was to investigate the effects of disengagement and distraction on remote driver performance and behaviour. Key findings revealed that mental disengagement, achieved through distraction via a reading task, significantly slowed the remote driver’s reaction time by an average of 5.309 s when the Level 4 automated system required intervention. Similarly, disengagement resulted in a 4.232 s delay in decision-making time for remote drivers when they needed to step in and make critical strategic decisions. Moreover, mental disengagement affected the remote drivers’ attention focus on the road and increased their cognitive workload compared to constant monitoring. Furthermore, when actively controlling the vehicle remotely, drivers experienced a higher cognitive workload than in both “monitoring” and “disengagement” conditions. The findings emphasize the importance of designing teleoperation systems that keep remote drivers actively engaged with their environment, minimise distractions, and reduce disengagement. Such designs are essential for enhancing safety and effectiveness in remote driving scenarios, ultimately supporting the successful deployment of Level 4 automated vehicles in real-world applications. Full article
(This article belongs to the Special Issue Advanced Technologies in Intelligent Transport Systems)
►▼ Show Figures

Figure 1

21 pages, 5026 KiB  
Article
Open-Source Telemedicine Platform Based on WebSockets for Management of Biosignals
by Leonardo Juan Ramirez Lopez, Norman Eduardo Jaimes Salazar and Juan Sabastian Orozco Duran
Electronics 2024, 13(22), 4365; https://doi.org/10.3390/electronics13224365 - 7 Nov 2024
Viewed by 274
Abstract
The main objective of this project was to develop a remote monitoring solution using an open-source platform, the e-health platform V2.0, which served as the foundation for this solution due to its capability to integrate various tools and technologies. The project involved measurements [...] Read more.
The main objective of this project was to develop a remote monitoring solution using an open-source platform, the e-health platform V2.0, which served as the foundation for this solution due to its capability to integrate various tools and technologies. The project involved measurements from six sensors including “temperature, electrocardiogram, airflow, beats per minute, blood oxygen saturation”, and focused on finding a method to implement these communications. WebSockets were identified as a suitable solution, facilitating the task of interconnection. Leveraging backend frameworks like Express and frontend frameworks like React allowed for a seamless integration of different components within the project. The integration of these frameworks enhanced project development efficiency and enabled an easy implementation of new functionalities. By utilizing the e-health platform V2.0 and leveraging WebSocket along with backend and frontend frameworks, this project successfully developed a remote monitoring solution for the seamless management of biosignals. The solution’s flexibility and scalability provide a solid foundation for further advancements and the integration of additional features. Full article
(This article belongs to the Topic Innovation, Communication and Engineering)
►▼ Show Figures

Figure 1

26 pages, 2800 KiB  
Article
Reflective Dialogues with a Humanoid Robot Integrated with an LLM and a Curated NLU System for Positive Behavioral Change in Older Adults
by Ryan Browne, Mirza Mohtashim Alam, Qasid Saleem, Abrar Hyder, Tatsuya Kudo, Francesca D’Agresti, Martino Maggio, Keiko Homma, Eerik-Juhanna Siitonen, Naoko Kounosu, Kristiina Jokinen, Michael McTear, Giulio Napolitano, Kyoungsook Kim, Junichi Tsujii, Rainer Wieching, Toshimi Ogawa and Yasuyuki Taki
Electronics 2024, 13(22), 4364; https://doi.org/10.3390/electronics13224364 - 7 Nov 2024
Viewed by 281
Abstract
We developed an innovative system that combines Natural Language Understanding (NLU), a curated knowledge base, and the efficient management of a Large Language Model (LLM) to support motivational health coaching. Using Rasa as the core framework, we enhanced it by integrating the GPT-3.5-turbo [...] Read more.
We developed an innovative system that combines Natural Language Understanding (NLU), a curated knowledge base, and the efficient management of a Large Language Model (LLM) to support motivational health coaching. Using Rasa as the core framework, we enhanced it by integrating the GPT-3.5-turbo model. Users opt into reflective dialogues during conversations. When they respond to open-ended questions, their input goes directly to the GPT-3.5-turbo model, allowing for more flexible responses. To provide curated trustworthy content, we integrated a knowledge provision component that searches a PDF-based knowledge base and generates user-friendly responses using Retrieval-Augmented Generation. We tested the system in a real-world scenario by deploying it on a Nao robot in seven older adults’ homes for 1–2 weeks, encouraging positive behavioral changes in some users. Our system serves as a valuable foundation for building an even more integrated, personalized system that can connect with other Application Programing Interfaces (APIs) and integrate with home sensors and edge devices. Full article
(This article belongs to the Special Issue Human-Computer Interactions in E-health)
►▼ Show Figures

Figure 1

17 pages, 7420 KiB  
Article
Very-High-Frequency Resonant Flyback Converter with Integrated Magnetics
by Yuchao Huang, Kui Yan, Qidong Li, Xiangyi Song, Desheng Zhang and Qiao Zhang
Electronics 2024, 13(22), 4363; https://doi.org/10.3390/electronics13224363 - 7 Nov 2024
Viewed by 257
Abstract
This paper proposes a gallium nitride (GaN)-based very-high-frequency (VHF) resonant flyback converter with integrated magnetics, which utilizes the parasitic inductance and capacitance to reduce the passive components count and volume of the converter. Both the primary leakage inductance and the secondary leakage inductance [...] Read more.
This paper proposes a gallium nitride (GaN)-based very-high-frequency (VHF) resonant flyback converter with integrated magnetics, which utilizes the parasitic inductance and capacitance to reduce the passive components count and volume of the converter. Both the primary leakage inductance and the secondary leakage inductance of the transformer are utilized as the resonance inductor, while the parasitic capacitance of the power devices is utilized as the resonance capacitor. An analytical circuit model is proposed to determine the electrical parameters of the transformer so as to achieve zero voltage switching (ZVS) and zero current switching (ZCS). Furthermore, an air-core transformer was designed using the improved Wheeler’s formula, and finite element analyses were carried out to fine-tune the structure to achieve the accurate design of the electrical parameters. Finally, a 30 MHz, 15 W VHF resonant flyback converter prototype is built with an efficiency of 83.1% for the rated power. Full article
(This article belongs to the Special Issue Control and Optimization of Power Converters and Drives)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-61
Previous Issue
Back to TopTop