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Electronics, Volume 11, Issue 13 (July-1 2022) – 186 articles

Cover Story (view full-size image): Common practice RF design guidelines for SMA edge mount connectors are investigated in terms of numerical simulations and measurements. These guidelines are used in a variety of applications for coaxial-to-planar interfaces but often do not provide information regarding the physical origins of increased insertion and transmission losses. The presented results focus on different RF PCB design features and their impact on electromagnetic field distributions in the launching zone. The numerical investigations should raise awareness regarding the issue of electromagnetic field resonances occurring in the RF frequency range and assist PCB design engineers to identify potential issues occurring at a coaxial-to-planar interface. View this paper
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15 pages, 2976 KiB  
Article
Research on Terminal-Side Computing Force Network Based on Massive Terminals
by Jianhua Gu, Jianhua Feng, Huiyang Xu and Ting Zhou
Electronics 2022, 11(13), 2108; https://doi.org/10.3390/electronics11132108 - 5 Jul 2022
Cited by 5 | Viewed by 2262
Abstract
With the explosive growth of the demand for computing power in the era of digital economy and the continuous enhancement of the computing power of terminals, how to provide high bandwidth, low-latency, and low-cost service by leveraging the user devices’ computing, storage, and [...] Read more.
With the explosive growth of the demand for computing power in the era of digital economy and the continuous enhancement of the computing power of terminals, how to provide high bandwidth, low-latency, and low-cost service by leveraging the user devices’ computing, storage, and network resources has become a research hotspot. However, due to differences in magnitude, architecture, and performance, the existing technologies for cloud computing and edge computing need to overcome many challenges such as android-based devices not supporting container technologies. In this paper, a terminal-side computing force network (TSCFN) architecture is proposed, which realizes the unified computing power management of massive user devices by layered and distributed architecture with highly dynamic and domain-federated deployments. At the same time, we propose a cloud-native container resource scheduling scheme based on the Android system to enhance the scalability of TSCFN. Taking the CDN service as a use case, the experiment results show that services provided by TSCFN can reduce latency and improve resource utilization, especially in an unstable network status. Compared with traditional CDN, delay duration of HomeCDN based on TSCFN is decreased by 96% in a bad network environment. Full article
(This article belongs to the Special Issue Edge Computing for Urban Internet of Things)
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17 pages, 2614 KiB  
Article
Design Framework for ReRAM-Based DNN Accelerators with Accuracy and Hardware Evaluation
by Hsu-Yu Kao, Shih-Hsu Huang and Wei-Kai Cheng
Electronics 2022, 11(13), 2107; https://doi.org/10.3390/electronics11132107 - 5 Jul 2022
Cited by 1 | Viewed by 1984
Abstract
To achieve faster design closure, there is a need to provide a design framework for the design of ReRAM-based DNN (deep neural network) accelerator at the early design stage. In this paper, we develop a high-level ReRAM-based DNN accelerator design framework. The proposed [...] Read more.
To achieve faster design closure, there is a need to provide a design framework for the design of ReRAM-based DNN (deep neural network) accelerator at the early design stage. In this paper, we develop a high-level ReRAM-based DNN accelerator design framework. The proposed design framework has the following three features. First, we consider ReRAM’s non-linear properties, including lognormal distribution, leakage current, IR drop, and sneak path. Thus, model accuracy and circuit performance can be accurately evaluated. Second, we use SystemC with TLM modeling method to build our virtual platform. To our knowledge, the proposed design framework is the first behavior-level ReRAM deep learning accelerator simulator that can simulate real hardware behavior. Third, the proposed design framework can evaluate not only model accuracy but also hardware cost. As a result, the proposed design framework can be used for behavior-level design space exploration. In the experiments, we have deployed different DNN models on the virtual platform. Circuit performance can be easily evaluated on the proposed design framework. Furthermore, experiment results also show that the noise effects are different in different ReRAM array architectures. Based on the proposed design framework, we can easily mitigate noise effects by tuning architecture parameters. Full article
(This article belongs to the Special Issue Advances in Hardware-Software Codesign)
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14 pages, 3274 KiB  
Article
Transformer-Based GAN for New Hairstyle Generative Networks
by Qiaoyue Man, Young-Im Cho, Seong-Geun Jang and Hae-Jeung Lee
Electronics 2022, 11(13), 2106; https://doi.org/10.3390/electronics11132106 - 5 Jul 2022
Cited by 5 | Viewed by 3443
Abstract
Traditional GAN-based image generation networks cannot accurately and naturally fuse surrounding features in local image generation tasks, especially in hairstyle generation tasks. To this end, we propose a novel transformer-based GAN for new hairstyle generation networks. The network framework comprises two modules: Face [...] Read more.
Traditional GAN-based image generation networks cannot accurately and naturally fuse surrounding features in local image generation tasks, especially in hairstyle generation tasks. To this end, we propose a novel transformer-based GAN for new hairstyle generation networks. The network framework comprises two modules: Face segmentation (F) and Transformer Generative Hairstyle (TGH) modules. The F module is used for the detection of facial and hairstyle features and the extraction of global feature masks and facial feature maps. In the TGH module, we design a transformer-based GAN to generate hairstyles and fix the details of the fusion part of faces and hairstyles in the new hairstyle generation process. To verify the effectiveness of our model, CelebA-HQ (Large-scale CelebFaces Attribute) and FFHQ (Flickr-Faces-HQ) are adopted to train and test our proposed model. In the image evaluation test used, FID, PSNR, and SSIM image evaluation methods are used to test our model and compare it with other excellent image generation networks. Our proposed model is more robust in terms of test scores and real image generation. Full article
(This article belongs to the Special Issue AI and Smart City Technologies)
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10 pages, 1043 KiB  
Article
A Microwave Imaging Procedure for Lung Lesion Detection: Preliminary Results on Multilayer Phantoms
by Banafsheh Khalesi, Bilal Khalid, Navid Ghavami, Giovanni Raspa, Mohammad Ghavami, Sandra Dudley-McEvoy and Gianluigi Tiberi
Electronics 2022, 11(13), 2105; https://doi.org/10.3390/electronics11132105 - 5 Jul 2022
Cited by 8 | Viewed by 2109
Abstract
In this work, a feasibility study for lung lesion detection through microwave imaging based on Huygens’ principle (HP) has been performed using multilayer oval shaped phantoms mimicking human torso having a cylindrically shaped inclusion simulating lung lesion. First, validation of the proposed imaging [...] Read more.
In this work, a feasibility study for lung lesion detection through microwave imaging based on Huygens’ principle (HP) has been performed using multilayer oval shaped phantoms mimicking human torso having a cylindrically shaped inclusion simulating lung lesion. First, validation of the proposed imaging method has been performed through phantom experiments using a dedicated realistic human torso model inside an anechoic chamber, employing a frequency range of 1–5 GHz. Subsequently, the miniaturized torso phantom validation (using both single and double inclusion scenarios) has been accomplished using a microwave imaging (MWI) device, which operates in free space using two antennas in multi-bistatic configuration. The identification of the target’s presence in the lung layer has been achieved on the obtained images after applying both of the following artifact removal procedures: (i) the “rotation subtraction” method using two adjacent transmitting antenna positions, and (ii) the “ideal” artifact removal procedure utilizing the difference between received signals from unhealthy and healthy scenarios. In addition, a quantitative analysis of the obtained images was executed based on the definition of signal to clutter ratio (SCR). The obtained results verify that HP can be utilized successfully to discover the presence and location of the inclusion in the lung-mimicking phantom, achieving an SCR of 9.88 dB. Full article
(This article belongs to the Special Issue Electromagnetics in Biomedical Imaging)
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27 pages, 580 KiB  
Article
Hill-Climb-Assembler Encoding: Evolution of Small/Mid-Scale Artificial Neural Networks for Classification and Control Problems
by Tomasz Praczyk
Electronics 2022, 11(13), 2104; https://doi.org/10.3390/electronics11132104 - 5 Jul 2022
Cited by 6 | Viewed by 1587
Abstract
The paper presents a neuro-evolutionary algorithm called Hill Climb Assembler Encoding (HCAE) which is a light variant of Hill Climb Modular Assembler Encoding (HCMAE). While HCMAE, as the name implies, is dedicated to modular neural networks, the target application of HCAE is to [...] Read more.
The paper presents a neuro-evolutionary algorithm called Hill Climb Assembler Encoding (HCAE) which is a light variant of Hill Climb Modular Assembler Encoding (HCMAE). While HCMAE, as the name implies, is dedicated to modular neural networks, the target application of HCAE is to evolve small/mid-scale monolithic neural networks which, in spite of the great success of deep architectures, are still in use, for example, in robotic systems. The paper analyses the influence of different mechanisms incorporated into HCAE on the effectiveness of evolved neural networks and compares it with a number of rival algorithms. In order to verify the ability of HCAE to evolve effective small/mid-scale neural networks, both feed forward and recurrent, it was tested on fourteen identification problems including the two-spiral problem, which is a well-known binary classification benchmark, and on two control problems, i.e., the inverted-pendulum problem, which is a classical control benchmark, and the trajectory-following problem, which is a real problem in underwater robotics. Four other neuro-evolutionary algorithms, four particle swarm optimization methods, differential evolution, and a well-known back-propagation algorithm, were applied as a point of reference for HCAE. The experiments reported in the paper revealed that the evolutionary approach applied in the proposed algorithm makes it a more effective tool for solving the test problems than all the rivals. Full article
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14 pages, 27058 KiB  
Article
Polarization-Flexible and Frequency-Scanning Leaky-Wave HMSIW Antenna for Vehicular Applications
by Aixin Chen, Xuedong Fu, Weiwei Jiang and Kang An
Electronics 2022, 11(13), 2103; https://doi.org/10.3390/electronics11132103 - 5 Jul 2022
Cited by 2 | Viewed by 1887
Abstract
To achieve multifunctional communication and safe driving of a vehicle, a half-mode substrate-integrated waveguide (HMSIW) leaky-wave frequency-scanning antenna with flexible polarization is proposed in this article. It includes two linearly polarized interdigital slot antennas, a compact directional coupler, and microstrip transition lines. It [...] Read more.
To achieve multifunctional communication and safe driving of a vehicle, a half-mode substrate-integrated waveguide (HMSIW) leaky-wave frequency-scanning antenna with flexible polarization is proposed in this article. It includes two linearly polarized interdigital slot antennas, a compact directional coupler, and microstrip transition lines. It can generate either linear polarization (LP) for base station communication or circular polarization (CP) for satellite navigation by configuring the means of excitation. Its radiation beam can be continuously steered with varying frequency in either the LP or the CP state, which is of benefit to safe vehicular driving. In addition, the use of the HMSIW structure reduces the size of the antenna by almost one-half in comparison with the full SIW structure. Measurements were performed on antenna scattering parameters, radiation patterns, gain, and axial ratio (for CP states); the results show good agreement with the simulated results. With its low profile, low weight, low cost, and capability for continuous frequency scanning and variable polarization states, the multifunctional antenna could be extensively used for adapting to changes in environmental conditions or system requirements. Full article
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24 pages, 995 KiB  
Review
Review on Haptic Assistive Driving Systems Based on Drivers’ Steering-Wheel Operating Behaviour
by Simplice Igor Noubissie Tientcheu, Shengzhi Du and Karim Djouani
Electronics 2022, 11(13), 2102; https://doi.org/10.3390/electronics11132102 - 5 Jul 2022
Cited by 8 | Viewed by 3802
Abstract
With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine [...] Read more.
With the availability of modern assistive techniques, ambient intelligence, and the Internet of Things (IoT), various innovative assistive environments have been developed, such as driving assistance systems (DAS), where the human driver can be provided with physical and emotional assistance. In this human–machine collaboration system, haptic interaction interfaces are commonly employed because they provide drivers with a more manageable way to interact with other components. From the view of control system theory, this is a typical closed-loop feedback control system with a human in the loop. To make such a system work effectively, both the driving behaviour factors, and the electrical–mechanical components should be considered. However, the main challenge is how to deal with the high degree of uncertainties in human behaviour. This paper aims to provide an insightful overview of the relevant work. The impact of various types of haptic assistive driving systems (haptic guidance and warning systems) on driving behaviour performance is discussed and evaluated. In addition, various driving behaviour modelling systems are extensively investigated. Furthermore, the state-of-the-art driving behaviour controllers are analysed and discussed in driver–vehicle–road systems, with potential improvements and drawbacks addressed. Finally, a prospective approach is recommended to design a robust model-free controller that accounts for uncertainties and individual differences in driving styles in a haptic assistive driving system. The outcome indicated that the haptic feedback system applied to the drivers enhanced their driving performance, lowered their response time, and reduced their mental workload compared to a system with auditory or visual signals or without any haptic system, despite some annoyances and system conflicts. The driving behaviour modelling techniques and the driving behaviour control with a haptic feedback system have shown good matching and improved the steering wheel’s base operation performance. However, mathematical principles, a statistical approach, and the lack of consideration of the individual differences in the driver–vehicle–road system make the modelling and the controller less robust and inefficient for different driving styles. Full article
(This article belongs to the Special Issue Feature Papers in Systems & Control Engineering)
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11 pages, 3074 KiB  
Communication
Integrated Fiber-FSO WDM Access System with Fiber Fault Protection
by Chien-Hung Yeh, Wen-Piao Lin, Syu-Yang Jiang, Shang-En Hsieh, Ching-Hsuan Hsu and Chi-Wai Chow
Electronics 2022, 11(13), 2101; https://doi.org/10.3390/electronics11132101 - 5 Jul 2022
Cited by 6 | Viewed by 2190
Abstract
In this study, we propose a new wavelength-division-multiplexing passive optical network (WDM-PON) system to support the blended fiber-free space optics (FSO) signal access. To provide the fiber and FSO traffics simultaneously, the C- and L-band channels are applied in the presented PON, respectively. [...] Read more.
In this study, we propose a new wavelength-division-multiplexing passive optical network (WDM-PON) system to support the blended fiber-free space optics (FSO) signal access. To provide the fiber and FSO traffics simultaneously, the C- and L-band channels are applied in the presented PON, respectively. Moreover, to avoid the fiber breakpoint in the fiber access traffic, the proposed WDM access architecture also can provide the self-restored mechanism by applying simple fiber routing path. In addition, the corresponding signal performances of fiber and FSO channels are also executed experimentally for demonstration. Full article
(This article belongs to the Special Issue Feature Papers in the Optoelectronics Section)
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13 pages, 1522 KiB  
Article
Signals Recognition by CNN Based on Attention Mechanism
by Feng Tian, Li Wang and Meng Xia
Electronics 2022, 11(13), 2100; https://doi.org/10.3390/electronics11132100 - 5 Jul 2022
Cited by 10 | Viewed by 2825
Abstract
Automatic modulation recognition is a key technology in non-collaborative communication. However, it is affected by complex electromagnetic environments, leading to low recognition accuracy. To address this problem, this paper develops a ResNext signal recognition model based on an attention mechanism. Firstly, a channel, [...] Read more.
Automatic modulation recognition is a key technology in non-collaborative communication. However, it is affected by complex electromagnetic environments, leading to low recognition accuracy. To address this problem, this paper develops a ResNext signal recognition model based on an attention mechanism. Firstly, a channel, including additive Gaussian white noise (AWGN), Rician multipath fading, and clock offset, is created to simulate the complex electromagnetic environment, and transmission-impaired modulated signals with various signal-to-noise ratios (SNRs) are synthesized as a dataset. Secondly, using parallel stacked residual blocks of the same topology, instead of the residual blocks of ResNet, and introducing the attention layer (CBAM), the types of feature extraction are enriched without significantly increasing the parameter order of magnitude and avoiding the over-fitting phenomenon caused by depth deepening. The results show that the signal recognition method, based on the improved neural network framework, outperformed other deep learning methods, and the recognition rate obtained of 10 different modulation types of signals was above 90% at SNRs greater than 0 dB. The proposed signal recognition method achieved accurate recognition in complex electromagnetic environments. Full article
(This article belongs to the Section Circuit and Signal Processing)
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10 pages, 2250 KiB  
Article
Examination of the Effect of RF Field on Fe-MWCNTs and Their Application in Medicine
by Katarzyna Wojtera, Krzysztof Smółka, Łukasz Szymański, Sławomir Wiak and Aleksandra Urbanek
Electronics 2022, 11(13), 2099; https://doi.org/10.3390/electronics11132099 - 5 Jul 2022
Cited by 1 | Viewed by 1568
Abstract
Carbon nanotubes are a material with excellent properties, which result in a wide range of possible applications, from electronics to medicine. This paper presents the investigation of the possibility of Fe-MWCNTs’ application as heating agents for targeted thermal ablation of cancer cells, which [...] Read more.
Carbon nanotubes are a material with excellent properties, which result in a wide range of possible applications, from electronics to medicine. This paper presents the investigation of the possibility of Fe-MWCNTs’ application as heating agents for targeted thermal ablation of cancer cells, which could lead to the development of an innovative cancer treatment method. The article describes the process of synthesis of multi-walled carbon nanotubes filled with iron (Fe-MWCNTs) and provides an examination of their magnetic properties. Fe-MWCNTs were synthesized by catalytic chemical vapor deposition (CCVD). Relevant properties of the nanoparticles in terms of functionalization for biomedical applications were exploited and their magnetic properties were investigated to determine the heat generation efficiency induced by exposure of the particles to an external electromagnetic field. The reaction of the samples was measured for 40 min of exposure. The results showed an increase in sample temperature that was proportional to the concentration. Full article
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14 pages, 3866 KiB  
Article
Precision Measurement System of High-Frequency Signal Based on Equivalent-Time Sampling
by Xiaoxuan Zang, Jianting Zhao, Yunfeng Lu and Qing He
Electronics 2022, 11(13), 2098; https://doi.org/10.3390/electronics11132098 - 5 Jul 2022
Cited by 4 | Viewed by 3041
Abstract
A high frequency periodic signal measurement system based on equivalent sampling method is developed. A high-speed sampling voltage tracking circuit, the core component of the system, is described in detail. The circuit can transform the amplitude corresponding to different phase points of the [...] Read more.
A high frequency periodic signal measurement system based on equivalent sampling method is developed. A high-speed sampling voltage tracking circuit, the core component of the system, is described in detail. The circuit can transform the amplitude corresponding to different phase points of the signal undertest into the equivalent DC level through successive approximation of multiple periods. The measurement system designed in this paper completes digital sampling with high accuracy only by connecting the low-cost voltage tracking circuit to the existing commercial instruments, such as two-channel waveform generator and high-precision digital multimeter, which makes the method easy to be generalized. The special structure of the sampling tracking circuit greatly reduces the influence of random noise and time jitter on the measurement results. The experimental results show that the non-linearity error of the system is as low as 0.002%, the bandwidth can reach 200 MHz, and the uncertainty of measuring the RMS of AC voltage with peak value of ±1 V and frequency of 10 kHz, 100 kHz and 1 MHz can reach 2.8 × 10−4 V, 4.6 × 10−4 V and 2.0 × 10−4 V (k = 2), respectively. Full article
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13 pages, 4280 KiB  
Article
Spiking VGG7: Deep Convolutional Spiking Neural Network with Direct Training for Object Recognition
by Shuiying Xiang, Shuqing Jiang, Xiaosong Liu, Tao Zhang and Licun Yu
Electronics 2022, 11(13), 2097; https://doi.org/10.3390/electronics11132097 - 4 Jul 2022
Cited by 17 | Viewed by 3855
Abstract
We propose a deep convolutional spiking neural network (DCSNN) with direct training to classify concrete bridge damage in a real engineering environment. The leaky-integrate-and-fire (LIF) neuron model is employed in our DCSNN that is similar to VGG. Poisson encoding and convolution encoding strategies [...] Read more.
We propose a deep convolutional spiking neural network (DCSNN) with direct training to classify concrete bridge damage in a real engineering environment. The leaky-integrate-and-fire (LIF) neuron model is employed in our DCSNN that is similar to VGG. Poisson encoding and convolution encoding strategies are considered. The gradient surrogate method is introduced to realize the supervised training for the DCSNN. In addition, we have examined the effect of observation time step on the network performance. The testing performance for two different spike encoding strategies are compared. The results show that the DCSNN using gradient surrogate method can achieve a performance of 97.83%, which is comparable to traditional CNN. We also present a comparison with STDP-based unsupervised learning and a converted algorithm, and the proposed DCSNN is proved to have the best performance. To demonstrate the generalization performance of the model, we also use a public dataset for comparison. This work paves the way for the practical engineering applications of the deep SNNs. Full article
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13 pages, 5810 KiB  
Article
Implementation of DDS Cloud Platform for Real-Time Data Acquisition of Sensors for a Legacy Machine
by Min-Huang Ho, Ming-Yi Lai and Yung-Tien Liu
Electronics 2022, 11(13), 2096; https://doi.org/10.3390/electronics11132096 - 4 Jul 2022
Cited by 2 | Viewed by 2302
Abstract
Industry 4.0 (I4.0) is a multidisciplinary engineering principle combing the IoT (Internet of things), big data, and cloud computing to cope with the dynamic changing industry. In this paper, the DDS (data distribution service) communication protocol was employed to implement a cloud platform [...] Read more.
Industry 4.0 (I4.0) is a multidisciplinary engineering principle combing the IoT (Internet of things), big data, and cloud computing to cope with the dynamic changing industry. In this paper, the DDS (data distribution service) communication protocol was employed to implement a cloud platform for data acquisition from various sensors on a precision legacy machine tool including an accelerometer and sound, temperature, brightness, and humidity sensors. The sensor signals were acquired using Raspberry Pi as the edge device, then published to the cloud using the DDS application, and stored in the MySQL database. Using the Django web server, the acquired sensor signals could be shown in real time on the webpage via a combination of MQTT and Node-RED. In addition, the motion displacement of the machine tool detected by the encoder could be recorded through the edge device for further performance examination. With the proposed DDS cloud platform, it is demonstrated that a legacy machine can enable sensing and communication abilities such that the development of a smart machine is achievable for future I4.0 application. Full article
(This article belongs to the Special Issue Intelligent Signal Processing and Communication Systems)
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18 pages, 11700 KiB  
Article
A Study on the Optimal Control of Voltage Utilization for Improving the Efficiency of PMSM
by Ji-Hwan Park, Hee-Sun Lim, Geun-Ho Lee and Heon-Hyeong Lee
Electronics 2022, 11(13), 2095; https://doi.org/10.3390/electronics11132095 - 4 Jul 2022
Cited by 4 | Viewed by 2531
Abstract
When performing weak flux control to drive a permanent-magnet synchronous motor at high speed, the efficiency is lowered because the copper loss increases as the negative D-axis current increases. In addition, if the overmodulation index is slightly lowered and driven without setting it [...] Read more.
When performing weak flux control to drive a permanent-magnet synchronous motor at high speed, the efficiency is lowered because the copper loss increases as the negative D-axis current increases. In addition, if the overmodulation index is slightly lowered and driven without setting it to the maximum value, the phase current ripple reduction effect can be expected compared to the six-step control. Therefore, if the motor is operated at a current point that can minimize the sum of copper loss and iron loss, the motor can be driven with maximum efficiency. In addition, if the overmodulation index is slightly lower than that of the six-step control, the phase current ripple can be reduced. This paper proposes a method for finding an overmodulation index to maximize driving efficiency when driving a motor based on the magnetic flux–torque command. In addition, an algorithm for driving a motor with maximum efficiency by applying an optimal overmodulation index table is proposed. Based on the MATLAB Simulink simulation, the efficiency change characteristics according to the overmodulation index change are reviewed, and the efficiency improvement and current ripple reduction effects are verified through a dynamometer experiment. Full article
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17 pages, 6644 KiB  
Article
Multi-Objective Multi-Learner Robot Trajectory Prediction Method for IoT Mobile Robot Systems
by Fei Peng, Li Zheng, Zhu Duan and Yu Xia
Electronics 2022, 11(13), 2094; https://doi.org/10.3390/electronics11132094 - 4 Jul 2022
Cited by 7 | Viewed by 2519
Abstract
Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as [...] Read more.
Robot trajectory prediction is an essential part of building digital twin systems and ensuring the high-performance navigation of IoT mobile robots. In the study, a novel two-stage multi-objective multi-learner model is proposed for robot trajectory prediction. Five machine learning models are adopted as base learners, including autoregressive moving average, multi-layer perceptron, Elman neural network, deep echo state network, and long short-term memory. A non-dominated sorting genetic algorithm III is applied to automatically combine these base learners, generating an accurate and robust ensemble model. The proposed model is tested on several actual robot trajectory datasets and evaluated by several metrics. Moreover, different existing optimization algorithms are also applied to compare with the proposed model. The results demonstrate that the proposed model can achieve satisfactory accuracy and robustness for different datasets. It is suitable for the accurate prediction of robot trajectory. Full article
(This article belongs to the Special Issue Advanced Technologies in Autonomous Robotic System)
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14 pages, 9647 KiB  
Article
An Aero-Engine Damage Detection Method with Low-Energy Consumption Based on Multi-Layer Contrastive Learning
by Xing Huang, Lei Li, Jingsheng Zhang, Dengfeng Yin, Xinjian Hu and Peibing Du
Electronics 2022, 11(13), 2093; https://doi.org/10.3390/electronics11132093 - 4 Jul 2022
Viewed by 1795
Abstract
The health of aero-engines is pivotal to the safe operation of aircraft. With increasing service time, the internal components of the engine will be damaged by threats from different sources, so it is necessary to regularly detect the damage inside the engine. At [...] Read more.
The health of aero-engines is pivotal to the safe operation of aircraft. With increasing service time, the internal components of the engine will be damaged by threats from different sources, so it is necessary to regularly detect the damage inside the engine. At present, most of the detection methods of major airlines rely on the internal images of the engine obtained by manual use of a borescope to detect damage or traditional machine learning methods, which consume high levels of human and computational resources but have low efficiency. Artificial intelligence in various fields can achieve better performance than traditional methods, but to achieve the industrialization standard of Green AI, we need further research. Accordingly, we introduce a multi-layer contrastive learning method to a lightweight target detection model design, which is applied to real aero-engine borescope images of complex components to accomplish real-time damage detection. We intensively conduct comparative experiments to evaluate the effectiveness of our method. The verification results demonstrate that the method can help our model perform excellently compared with other available baseline models. Full article
(This article belongs to the Special Issue Defining, Engineering, and Governing Green Artificial Intelligence)
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8 pages, 1359 KiB  
Article
Algorithm Verification of Single-Shot Relativistic Emittance Proposed Measuring Method
by Leon Feigin, Amir Weinberg and Ariel Nause
Electronics 2022, 11(13), 2092; https://doi.org/10.3390/electronics11132092 - 4 Jul 2022
Cited by 3 | Viewed by 1750
Abstract
A 6 MeV hybrid photo-cathode gun is driving a THz-FEL in Ariel University, as well as other applications. An electron bunch with small transverse emittance is extracted from a copper photo-cathode using a 1 ps UV laser pulse, and then accelerated to a [...] Read more.
A 6 MeV hybrid photo-cathode gun is driving a THz-FEL in Ariel University, as well as other applications. An electron bunch with small transverse emittance is extracted from a copper photo-cathode using a 1 ps UV laser pulse, and then accelerated to a kinetic energy of 6.5 MeV. The Hybrid term is due to the unique standing wave-traveling wave sections in a single RF cavity. Since low emittance is crucial for FEL operation, the characterization of the electron beam requires measuring the transverse emittance, which will be compared with the predicted design and the 3D simulation obtained values, in order to verify their correctness. In this paper, we confirm the use of the multi-slit technique to measure emittance in the Hybrid beam in a single shot and develop a simple and convenient algorithm to be used in the experimental measurements. The experimental analysis requires image processing of the measured data, combined with a custom LabVIEW and Matlab scripts to control the hardware, and analyze the obtained data. Prior to experimentally measuring emittance, we perform a simulated experiment, using a simulated beam from the General Particle Tracer (GPT) code to test these algorithms and scripts, and compare the emittance obtained using the algorithm with GPT’s estimated emittance. Once concluded, this method will allow for a simple, fast and accurate single shot emittance measurement for the Hybrid accelerator beam. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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6 pages, 2356 KiB  
Article
WR-3.4 Overmoded Waveguide Module for the Packaging of a Linear Integrated-Circuit Array
by Juhee Lee, Yang Woo Kim, Sanggeun Jeon and Moonil Kim
Electronics 2022, 11(13), 2091; https://doi.org/10.3390/electronics11132091 - 4 Jul 2022
Cited by 1 | Viewed by 1652
Abstract
The performance of WR-3.4 overmoded waveguide modules containing a linear array of discrete terahertz integrated circuits is presented to verify a new power-combining technique. Custom-designed thru-line IC chips that include back-to-back broadband antenna transitions were fabricated with an area of 390 × 750 [...] Read more.
The performance of WR-3.4 overmoded waveguide modules containing a linear array of discrete terahertz integrated circuits is presented to verify a new power-combining technique. Custom-designed thru-line IC chips that include back-to-back broadband antenna transitions were fabricated with an area of 390 × 750 mm2 for waveguide packaging. Multiple array modules were assembled to verify the repeatability in performance. The array modules exhibited almost identical amounts of insertion losses compared with single-element modules, showing the best insertion loss of 2.6 dB over a 1 dB bandwidth of 95 GHz. Full article
(This article belongs to the Section Circuit and Signal Processing)
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15 pages, 3223 KiB  
Article
ICT Usage for Cross-Curricular Connections in Music and Visual Arts during Emergency Remote Teaching in Slovenia
by Eda Birsa, Matjaž Kljun and Barbara Kopačin
Electronics 2022, 11(13), 2090; https://doi.org/10.3390/electronics11132090 - 3 Jul 2022
Cited by 5 | Viewed by 2726
Abstract
Due to the COVID-19 pandemic, the entire process of teaching and learning moved online. This forced teachers and pupils to heavily rely on information and communications technology (ICT) and make adjustments to the new mode of teaching and learning in educational institutions. We [...] Read more.
Due to the COVID-19 pandemic, the entire process of teaching and learning moved online. This forced teachers and pupils to heavily rely on information and communications technology (ICT) and make adjustments to the new mode of teaching and learning in educational institutions. We conducted a qualitative case study by interviewing 24 teachers from Slovene primary schools focusing on the implementation of cross-curricular connections in music and visual arts content with the support of ICT during the period of emergency remote teaching. We found that when planning and implementing the cross-curricular learning process, teachers insufficiently took advantage of possibilities offered by modern ICT. The manner of implementing cross-curricular connections showed uncertainties in terms of understanding their specifics, resulting in the inefficient transfer of concepts taught, the results of which were seen in pupils’ work. This might additionally show the negative influence of parental supervision on the creative thinking and expression of pupils. The present study emphasizes the lack of ICT competences on the part of all participants in the educational process. Our findings show the need to educate teachers by eliminating the uncertainties related to the implementation of distant cross-curricular connections while meaningfully applying ICT adapted to pupils’ competences. Full article
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16 pages, 5655 KiB  
Article
Embedded Real-Time Implementation of Bio-Inspired Central Pattern Generator with Self-Repairing Function
by Jinda Xu, Meili Lu, Zhen Zhang and Xile Wei
Electronics 2022, 11(13), 2089; https://doi.org/10.3390/electronics11132089 - 3 Jul 2022
Viewed by 1696
Abstract
Both robustness and self-repairing of the rhythmic behaviors generated by central pattern generators (CPGs) play significant roles in locomotion control. Although current CPG models have been established to mimic rhythmic outputs, the mechanisms by which the self-repairing capacities of CPG systems are formed [...] Read more.
Both robustness and self-repairing of the rhythmic behaviors generated by central pattern generators (CPGs) play significant roles in locomotion control. Although current CPG models have been established to mimic rhythmic outputs, the mechanisms by which the self-repairing capacities of CPG systems are formed are largely unknown. In this paper, a novel bio-inspired self-repairing CPG model (BiSRP-CPG) is proposed based on the tripartite synapse, which reveals the critical role of astrocytes in the dynamic coordination of CPGs. BiSRP-CPG is implemented on the parallel FPGA platform to simulate CPG systems on real physiological scale, in which a hardware implementation method without multiplier is utilized to break the limitation of FPGA hardware resources. The experimental results verified both the robustness and self-repairing capabilities of rhythm of BiSRP-CPG in the presence of stochastic synaptic inputs and “faulty” synapse. Under the synaptic failure rate of 20%, BiSRP-CPG suffered only 10.53% performance degradation, which was much lower than the 36.84% spike loss rate of CPG networks without astrocytes. This paper provides an insight into one of the possible self-repair mechanisms of brain rhythms which can be utilized to develop autonomously fault-tolerant electronic systems. Full article
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21 pages, 18522 KiB  
Article
The Research on Harmonic Transfer Characteristics of Integrated Multi-Winding Inductive Filtering Converter Transformer and Its Filter System
by Jianying Li, Yunchang Xiao, Minsheng Yang, Jianqi Li and Jingying Wan
Electronics 2022, 11(13), 2088; https://doi.org/10.3390/electronics11132088 - 3 Jul 2022
Cited by 1 | Viewed by 1613
Abstract
A novel integrated multi-winding inductive filter converter and its filter system used in HVDC conversion station are proposed. Specifically, the schemes include two paralleled-connected delta filter windings with zero impedance, and the 11th and 13th tuned filtering branches are installed at the taps. [...] Read more.
A novel integrated multi-winding inductive filter converter and its filter system used in HVDC conversion station are proposed. Specifically, the schemes include two paralleled-connected delta filter windings with zero impedance, and the 11th and 13th tuned filtering branches are installed at the taps. On this basis, the 5th and 7th harmonic filters are eliminated and the 5th, 7th, 11th, and 13th harmonics of the valve-side are suppressed. Moreover, the cost of the filter is reduced, and the negative impact on the converter transformer body caused by the transfer of harmonic current is avoided, such as vibration, noise, and harmonic loss. In this paper, first, the mathematical models of integrated multi-winding inductive filter converter and its filter system are established. Accordingly, the current relationships between the primary winding side and two secondary winding sides are derived. Then, the transfer path of each characteristic harmonic current in the new system is analyzed and discussed. Moreover, a simulation model is established to study the operation characteristics of the system. Finally, through the designed experimental prototype, a new DC transferring system platform is constructed to testify the operation characteristics of an integrated multi-winding inductive filter converter and its filter system. The experimental results show that the total harmonic distortion rate of the grid-winding current can be reduced to 4.68% only by installing the 11th and 13th tuned filters, so the effect of active filtering is approximated realized by the passive filtering method. Full article
(This article belongs to the Special Issue IoT Applications for Renewable Energy Management and Control)
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9 pages, 512 KiB  
Article
Classification of Left and Right Coronary Arteries in Coronary Angiographies Using Deep Learning
by Christian Kim Eschen, Karina Banasik, Alex Hørby Christensen, Piotr Jaroslaw Chmura, Frants Pedersen, Lars Køber, Thomas Engstrøm, Anders Bjorholm Dahl, Søren Brunak and Henning Bundgaard
Electronics 2022, 11(13), 2087; https://doi.org/10.3390/electronics11132087 - 3 Jul 2022
Cited by 4 | Viewed by 3744
Abstract
Multi-frame X-ray images (videos) of the coronary arteries obtained using coronary angiography (CAG) provide detailed information about the anatomy and blood flow in the coronary arteries and play a pivotal role in diagnosing and treating ischemic heart disease. Deep learning has the potential [...] Read more.
Multi-frame X-ray images (videos) of the coronary arteries obtained using coronary angiography (CAG) provide detailed information about the anatomy and blood flow in the coronary arteries and play a pivotal role in diagnosing and treating ischemic heart disease. Deep learning has the potential to quickly and accurately quantify narrowings and blockages of the arteries from CAG videos. A CAG consists of videos acquired separately for the left coronary artery and the right coronary artery (LCA and RCA, respectively). The pathology for LCA and RCA is typically only reported for the entire CAG, and not for the individual videos. However, training of stenosis quantification models is difficult when the RCA and LCA information of the videos are unknown. Here, we present a deep learning-based approach for classifying LCA and RCA in CAG videos. Our approach enables linkage of videos with the reported pathological findings. We manually labeled 3545 and 520 videos (approximately seven videos per CAG) to enable training and testing of the models, respectively. We obtained F1 scores of 0.99 on the test set for LCA and RCA classification LCA and RCA classification on the test set. The classification performance was further investigated with extensive experiments across different model architectures (R(2+1)D, X3D, and MVIT), model input sizes, data augmentations, and the number of videos used for training. Our results showed that CAG videos could be accurately curated using deep learning, which is an essential preprocessing step for a downstream application in diagnostics of coronary artery disease. Full article
(This article belongs to the Special Issue Deep Learning for Medical Images: Challenges and Solutions)
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11 pages, 3351 KiB  
Article
Real-Time 3D Mapping in Isolated Industrial Terrain with Use of Mobile Robotic Vehicle
by Tomasz Buratowski, Jerzy Garus, Mariusz Giergiel and Andrii Kudriashov
Electronics 2022, 11(13), 2086; https://doi.org/10.3390/electronics11132086 - 3 Jul 2022
Cited by 9 | Viewed by 2185
Abstract
Simultaneous localization and mapping (SLAM) is a dual process responsible for the ability of a robotic vehicle to build a map of its surroundings and estimate its position on that map. This paper presents the novel concept of creating a 3D map based [...] Read more.
Simultaneous localization and mapping (SLAM) is a dual process responsible for the ability of a robotic vehicle to build a map of its surroundings and estimate its position on that map. This paper presents the novel concept of creating a 3D map based on the adaptive Monte-Carlo location (AMCL) and the extended Kalman filter (EKF). This approach is intended for inspection or rescue operations in a closed or isolated area where there is a risk to humans. The proposed solution uses particle filters together with data from on-board sensors to estimate the local position of the robot. Its global position is determined through the Rao–Blackwellized technique. The developed system was implemented on a wheeled mobile robot equipped with a sensing system consisting of a laser scanner (LIDAR) and an inertial measurement unit (IMU), and was tested in the real conditions of an underground mine. One of the contributions of this work is to propose a low-complexity and low-cost solution to real-time 3D-map creation. The conducted experimental trials confirmed that the performance of the three-dimensional mapping was characterized by high accuracy and usefulness for recognition and inspection tasks in an unknown industrial environment. Full article
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18 pages, 981 KiB  
Article
Design and Evaluation of Schemes for Replacing Multiple Member Vehicles in Vehicular Clouds
by Hyunseok Choi, Youngju Nam, Yongje Shin, Kwansoo Jung and Euisin Lee
Electronics 2022, 11(13), 2085; https://doi.org/10.3390/electronics11132085 - 3 Jul 2022
Viewed by 1346
Abstract
Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. [...] Read more.
Vehicular clouds are considered an attractive approach to provide various services such as safety and entertainment applications by sharing resources between vehicles. Due to the free mobility of vehicles, vehicular clouds need to reconstruct by replacing leaving member vehicles with new member vehicles. When multiple member vehicles leave a vehicular cloud at different times, the design of an efficient member vehicle replacement scheme is a very challenging issue on determining the replacement timing. However, the research on the replacement of multiple member vehicles has little interest and is still in its infancy. Therefore, we propose three schemes to replace multiple member vehicles in vehicular clouds at three different replacement timings: MIN, MAX, and AVG. The MIN scheme replaces all of leaving member vehicles at the leaving time of the first leaving member vehicle, while the MAX scheme replaces all of leaving member vehicles at the leaving time of the last leaving member. The AVG scheme replaces all leaving member vehicles at the average time of their leaving times as a compromise between the Min and Max schemes. First, we determine the first leaving time, the last leaving time, and the average leaving time for each scheme by calculating the distance between a cloud requester vehicle and its member vehicles. Next, we choose replacement member vehicles to minimize the wasted resource at the replacement timing in each scheme. Last, we provide the process for releasing the resource of the leaving member vehicles and allocating the resource of the replacement member vehicles in each scheme. Through simulation results conducted in various environments, we compare and evaluate the performance of our three schemes in terms of the success ratio of the cloud maintenance and the amount of the wasted resources. Full article
(This article belongs to the Special Issue Wireless Network Protocols and Performance Evaluation, Volume II)
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16 pages, 1783 KiB  
Article
Improving Delivery Probability in Mobile Opportunistic Networks with Social-Based Routing
by Manuel Jesús-Azabal, José García-Alonso, Vasco N. G. J. Soares and Jaime Galán-Jiménez
Electronics 2022, 11(13), 2084; https://doi.org/10.3390/electronics11132084 - 2 Jul 2022
Cited by 6 | Viewed by 2478
Abstract
There are contexts where TCP/IP is not suitable for performing data transmission due to long delays, timeouts, network partitioning, and interruptions. In these scenarios, mobile opportunistic networks (MONs) are a valid option, providing asynchronous transmissions in dynamic topologies. These architectures exploit physical encounters [...] Read more.
There are contexts where TCP/IP is not suitable for performing data transmission due to long delays, timeouts, network partitioning, and interruptions. In these scenarios, mobile opportunistic networks (MONs) are a valid option, providing asynchronous transmissions in dynamic topologies. These architectures exploit physical encounters and persistent storage to communicate nodes that lack a continuous end-to-end path. In recent years, many routing algorithms have been based on social interactions. Smartphones and wearables are in vogue, applying social information to optimize paths between nodes. This work proposes Refine Social Broadcast (RSB), a social routing algorithm. RSB uses social behavior and node interests to refine the message broadcast in the network, improving the delivery probability while reducing redundant data duplication. The proposal combines the identification of the most influential nodes to carry the information toward the destination with interest-based routing. To evaluate the performance, RSB is applied to a simulated case of use based on a realistic loneliness detection methodology in elderly adults. The obtained delivery probability, latency, overhead, and hops are compared with the most popular social-based routers, namely, EpSoc, SimBet, and BubbleRap. RSB manifests a successful delivery probability, exceeding the second-best result (SimBet) by 17% and reducing the highest overhead (EpSoc) by 97%. Full article
(This article belongs to the Special Issue Emerging Trends, Issues and Challenges in Smart Cities)
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14 pages, 2047 KiB  
Article
Forward-Looking Imaging Based on the Linear Wavefront of the Modulated Field
by Yiming Zhong, Yi Zhang, Yiwen Yu, Houjun Sun and Xiangdong Zhang
Electronics 2022, 11(13), 2083; https://doi.org/10.3390/electronics11132083 - 2 Jul 2022
Cited by 1 | Viewed by 1592
Abstract
The vortex electromagnetic wave improves the range-azimuth forward-looking imaging performance with its spiral spatial phase distribution. However, the beam of the vortex electromagnetic wave is divergent, which makes it difficult to detect the targets near the center of the beam. In addition, the [...] Read more.
The vortex electromagnetic wave improves the range-azimuth forward-looking imaging performance with its spiral spatial phase distribution. However, the beam of the vortex electromagnetic wave is divergent, which makes it difficult to detect the targets near the center of the beam. In addition, the vortex electromagnetic wave only has the phase change in the azimuth direction and can hardly estimate the elevation position of the targets. In this paper, a linear wavefront control method based on the amplitude weighting of the array antenna is proposed. The modulated field has a phase gradient in both azimuth and elevation directions and has a maximum radiation intensity in the center of the beam. The imaging model based on the modulated field is theoretically derived and simulations are conducted to demonstrate the imaging performance. The modulated field constructed by the linear array can realize range-azimuth two-dimensional imaging with azimuth resolution of 1/5 beam width. The modulated field constructed by the circular array can realize range-azimuth-elevation three-dimensional imaging, and the resolution of the azimuth and elevation directions is 1/3 of the beam width. Full article
(This article belongs to the Special Issue Advances and Applications of Microwave Imaging)
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17 pages, 3013 KiB  
Article
Human-Centered Efficient Explanation on Intrusion Detection Prediction
by Yongsoo Lee, Eungyu Lee and Taejin Lee
Electronics 2022, 11(13), 2082; https://doi.org/10.3390/electronics11132082 - 2 Jul 2022
Cited by 1 | Viewed by 1632
Abstract
The methodology for constructing intrusion detection systems and improving existing systems is being actively studied in order to detect harmful data within large-capacity network data. The most common approach is to use AI systems to adapt to unanticipated threats and improve system performance. [...] Read more.
The methodology for constructing intrusion detection systems and improving existing systems is being actively studied in order to detect harmful data within large-capacity network data. The most common approach is to use AI systems to adapt to unanticipated threats and improve system performance. However, most studies aim to improve performance, and performance-oriented systems tend to be composed of black box models, whose internal working is complex. In the field of security control, analysts strive for interpretation and response based on information from given data, system prediction results, and knowledge. Consequently, performance-oriented systems suffer from a lack of interpretability owing to the lack of system prediction results and internal process information. The recent social climate also demands a responsible system rather than a performance-focused one. This research aims to ensure understanding and interpretation by providing interpretability for AI systems in multiple classification environments that can detect various attacks. In particular, the better the performance, the more complex and less transparent the model and the more limited the area that the analyst can understand, the lower the processing efficiency accordingly. The approach provided in this research is an intrusion detection methodology that uses FOS based on SHAP values to evaluate if the prediction result is suspicious and selects the optimal rule from the transparent model to improve the explanation. Full article
(This article belongs to the Special Issue Advanced Security Protection Mechanism in Networks)
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13 pages, 4287 KiB  
Article
Inhibiting Oil Splitting and Backflow in Electrowetting Displays by Designing a Power Function Driving Waveform
by Lixia Tian, Hu Zhang, Zichuan Yi, Bingsong Zhang, Rui Zhou, Guofu Zhou and Jianlong Gong
Electronics 2022, 11(13), 2081; https://doi.org/10.3390/electronics11132081 - 2 Jul 2022
Cited by 4 | Viewed by 1644
Abstract
Electrowetting display (EWD) is one of the latest and most promising reflective displays. However, some defects are easily caused in a driving process. For example, the aperture ratio of pixels can be reduced due to oil splitting, and the grayscale cannot be stabilized [...] Read more.
Electrowetting display (EWD) is one of the latest and most promising reflective displays. However, some defects are easily caused in a driving process. For example, the aperture ratio of pixels can be reduced due to oil splitting, and the grayscale cannot be stabilized due to charge trapping. These defects can be effectively solved by designing driving waveforms for EWDs. So, a power function driving waveform was proposed in this paper, which consisted of an oil splitting suppression stage, a direct current (DC) driving stage and an oil stabilization stage. Firstly, the relationships among luminance values, power constants and driving time were measured. An optimal oil splitting suppression stage was obtained, which could effectively inhibit oil splitting. Then, the response time could be reduced by a DC voltage in the DC driving stage. Finally, a voltage slope was tested during the oil stabilization stage, which was used to counteract voltage created by the charge trapping. The experimental results showed that compared with a linear function waveform, the response time could be shortened by 16.1%, and the luminance value could be increased by 3.8%. The aperture ratio and oil stability of EWD can be effectively improved by these findings, thereby increasing its potential application in the display field. Full article
(This article belongs to the Special Issue Flexible Devices and Optoelectronics Technologies)
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18 pages, 33899 KiB  
Article
Dracon: An Open-Hardware Based Platform for Single-Chip Low-Cost Reconfigurable IoT Devices
by Luis Parrilla, Antonio García, Encarnación Castillo, José Antonio Álvarez-Bermejo, Juan Antonio López-Villanueva and Uwe Meyer-Baese
Electronics 2022, 11(13), 2080; https://doi.org/10.3390/electronics11132080 - 2 Jul 2022
Cited by 4 | Viewed by 2473
Abstract
The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, [...] Read more.
The development of devices for the Internet of Things (IoT) requires the rapid prototyping of different hardware configurations. In this paper, a modular hardware platform allowing to prototype, test and even implement IoT appliances on low-cost reconfigurable devices is presented. The proposed platform, named Dracon, includes a Z80-clone microprocessor, up to 64 KB of RAM, and 256 inputs/outputs (I/Os). These I/Os can be used to connect additional co-processors within the same FPGA, external co-processors, communications modules, sensors and actuators. Dracon also includes as default peripherals a UART for programming and accessing the microprocessor, a Real Time Clock, and an Interrupt Timer. The use of an 8-bit microprocessor allows the use of the internal memory of the reconfigurable device as program memory, thereby, enabling the implementation of a complete IoT device within a single low-cost chip. Indeed, results using a Spartan 7 FPGA show that it is possible to implement Dracon with only 1515 6-input LUTs while operating at a maximum frequency of 80 MHz, which results in a better trade-off in terms of area and performance than other less powerful and less versatile alternatives in the literature. Moreover, the presented platform allows the development of embedded software applications independently of the selected FPGA device, enabling rapid prototyping and implementations on devices from different manufacturers. Full article
(This article belongs to the Special Issue Recent FPGA Architectures and Applications)
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11 pages, 5340 KiB  
Article
Design of a Slotted Waveguide Antenna Based on TE20 Mode in Ku-Band Suitable for Direct Metal Laser Sintering
by Youssef Chairi, Sarra Abedrrabba, Rozenn Allanic, Anne-Charlotte Amiaud, Ahmed El Oualkadi, Cédric Quendo, Thomas Merlet, Kamal Reklaoui and Thierry Le Gouguec
Electronics 2022, 11(13), 2079; https://doi.org/10.3390/electronics11132079 - 2 Jul 2022
Cited by 1 | Viewed by 2464
Abstract
This paper describes the design of a novel Ku-band slotted waveguide antenna (SWA), taking into consideration the advantages and drawbacks of using a 3D direct metal laser sintering (DMLS) process. Indeed, the DMLS process makes it possible to produce a SWA with 64 [...] Read more.
This paper describes the design of a novel Ku-band slotted waveguide antenna (SWA), taking into consideration the advantages and drawbacks of using a 3D direct metal laser sintering (DMLS) process. Indeed, the DMLS process makes it possible to produce a SWA with 64 radiating slots and its feeding network in a single and monolithic process. However, considering the lack of accuracy of the process, the whole design must be completely thought out and planned to avoid sensitive dimensions. Coupling irises inside such structures are elements of major sensitivity in this regard, so the radiating waveguides in the present work were designed to be TE20 ones, avoiding this kind of iris. Thus, a TE10 to TE20 converter was designed to be implemented in the overall power supply structure of an antenna array made up of four linear SWAs with 16 slots each. Both the elementary 16-slot SWA and the complete SWA with the feeding network were manufactured using DMLS. At a resonant frequency of 15 GHz, the measured realized gain is 22.26 dB with sidelobe levels below 10.1 dB. The measured reflection coefficient is lower than −12.6 dB at the center frequency. These measured performances confirm the proof of concept. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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