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Open AccessEditor’s ChoiceArticle
Semi-Automatic Guidance vs. Manual Guidance in Agriculture: A Comparison of Work Performance in Wheat Sowing
Electronics 2021, 10(7), 825; https://doi.org/10.3390/electronics10070825 - 31 Mar 2021
Abstract
The use of digital systems in precision agriculture is becoming more and more attractive for farmers at every level. A few years ago, the use of these technologies was limited to large farms, due to the considerable income needed to amortize the large [...] Read more.
The use of digital systems in precision agriculture is becoming more and more attractive for farmers at every level. A few years ago, the use of these technologies was limited to large farms, due to the considerable income needed to amortize the large investment required. Although this technology has now become more affordable, there is a lack of scientific data directed to demonstrate how these systems are able to determine quantifiable advantages for farmers. Thus, the transition towards precision agriculture is still very slow. This issue is not just negatively affecting the agriculture economy, but it is also slowing down potential environmental benefits that may result from it. The starting point of precision agriculture can be considered as the introduction of satellite tractor guidance. For instance, with semi-automatic and automatic tractor guidance, farmers can profit from more accuracy and higher machine performance during several farm operations such as plowing, harrowing, sowing, and fertilising. The goal of this study is to compare semi-automatic guidance with manual guidance in wheat sowing, evaluating parameters such as machine performance, seed supply and operational costs of both the configurations. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
On the Sampling of the Fresnel Field Intensity over a Full Angular Sector
Electronics 2021, 10(7), 832; https://doi.org/10.3390/electronics10070832 - 31 Mar 2021
Abstract
In this article, the question of how to sample the square amplitude of the radiated field in the framework of phaseless antenna diagnostics is addressed. In particular, the goal of the article is to find a discretization scheme that exploits a non-redundant number [...] Read more.
In this article, the question of how to sample the square amplitude of the radiated field in the framework of phaseless antenna diagnostics is addressed. In particular, the goal of the article is to find a discretization scheme that exploits a non-redundant number of samples and returns a discrete model whose mathematical properties are similar to those of the continuous one. To this end, at first, the lifting technique is used to obtain a linear representation of the square amplitude of the radiated field. Later, a discretization scheme based on the Shannon sampling theorem is exploited to discretize the continuous model. More in detail, the kernel of the related eigenvalue problem is first recast as the Fourier transform of a window function, and after, it is evaluated. Finally, the sampling theory approach is applied to obtain a discrete model whose singular values approximate all the relevant singular values of the continuous linear model. The study refers to a strip source whose square magnitude of the radiated field is observed in the Fresnel zone over a 2D observation domain. Full article
(This article belongs to the Special Issue Photonic and Microwave Sensing Developments and Applications)
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Open AccessEditor’s ChoiceArticle
A Gated Oscillator Clock and Data Recovery Circuit for Nanowatt Wake-Up and Data Receivers
Electronics 2021, 10(7), 780; https://doi.org/10.3390/electronics10070780 - 25 Mar 2021
Abstract
This article presents a data-startable baseband logic featuring a gated oscillator clock and data recovery (GO-CDR) circuit for nanowatt wake-up and data receivers (WuRxs). At each data transition, the phase misalignment between the data coming from the analog front-end (AFE) and the clock [...] Read more.
This article presents a data-startable baseband logic featuring a gated oscillator clock and data recovery (GO-CDR) circuit for nanowatt wake-up and data receivers (WuRxs). At each data transition, the phase misalignment between the data coming from the analog front-end (AFE) and the clock is cleared by the GO-CDR circuit, thus allowing the reception of long data streams. Any free-running frequency mismatch between the GO and the bitrate does not limit the number of receivable bits, but only the maximum number of equal consecutive bits (Nm). To overcome this limitation, the proposed system includes a frequency calibration circuit, which reduces the frequency mismatch to ±0.5%, thus enabling the WuRx to be used with different encoding techniques up to Nm = 100. A full WuRx prototype, including an always-on clockless AFE operating in subthreshold, was fabricated with STMicroelectronics 90 nm BCD technology. The WuRx is supplied with 0.6 V, and the power consumption, excluding the calibration circuit, is 12.8 nW during the rest state and 17 nW at a 1 kbps data rate. With a 1 kbps On-Off Keying (OOK) modulated input and −35 dBm of input RF power after the input matching network (IMN), a 10−3 missed detection rate with a 0 bit error tolerance is measured, transmitting 63 bit packets with the Nm ranging from 1 to 63. The total sensitivity, including the estimated IMN gain at 100 MHz and 433 MHz, is −59.8 dBm and −52.3 dBm, respectively. In comparison with an ideal CDR, the degradation of the sensitivity due to the GO-CDR is 1.25 dBm. False alarm rate measurements lasting 24 h revealed zero overall false wake-ups. Full article
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
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Open AccessFeature PaperEditor’s ChoiceArticle
Modeling Small UAV Micro-Doppler Signature Using Millimeter-Wave FMCW Radar
Electronics 2021, 10(6), 747; https://doi.org/10.3390/electronics10060747 - 22 Mar 2021
Abstract
With the increase in small unmanned aerial vehicle (UAV) applications in several technology areas, detection and small UAVs classification have become of interest. To cope with small radar cross-sections (RCSs), slow-flying speeds, and low flying altitudes, the micro-Doppler signature provides some of the [...] Read more.
With the increase in small unmanned aerial vehicle (UAV) applications in several technology areas, detection and small UAVs classification have become of interest. To cope with small radar cross-sections (RCSs), slow-flying speeds, and low flying altitudes, the micro-Doppler signature provides some of the most distinctive information to identify and classify targets in many radar systems. In this paper, we introduce an effective model for the micro-Doppler effect that is suitable for frequency-modulated continuous-wave (FMCW) radar applications, and exploit it to investigate UAV signatures. The latter depends on the number of UAV motors, which are considered vibrational sources, and their rotation speed. To demonstrate the reliability of the proposed model, it is used to build simulated FMCW radar images, which are compared with experimental data acquired by a 77 GHz FMCW multiple-input multiple-output (MIMO) cost-effective automotive radar platform. The experimental results confirm the model’s ability to estimate the class of the UAV, namely its number of motors, in different operative scenarios. In addition, the experimental results show that the motors rotation speed does not imprint a significant signature on the classification of the UAV; thus, the estimation of the number of motors represents the only viable parameter for small UAV classification using the micro-Doppler effect. Full article
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Open AccessEditor’s ChoiceArticle
Objective Assessment of Walking Impairments in Myotonic Dystrophy by Means of a Wearable Technology and a Novel Severity Index
Electronics 2021, 10(6), 708; https://doi.org/10.3390/electronics10060708 - 17 Mar 2021
Abstract
Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed [...] Read more.
Myotonic dystrophy type 1 (DM1) is a genetic inherited autosomal dominant disease characterized by multisystem involvement, including muscle, heart, brain, eye, and endocrine system. Although several methods are available to evaluate muscle strength, endurance, and dexterity, there are no validated outcome measures aimed at objectively evaluating qualitative and quantitative gait alterations. Advantageously, wearable sensing technology has been successfully adopted in objectifying the assessment of motor disabilities in different medical occurrences, so that here we consider the adoption of such technology specifically for DM1. In particular, we measured motor tasks through inertial measurement units on a cohort of 13 DM1 patients and 11 healthy control counterparts. The motor tasks consisted of 16 meters of walking both at a comfortable speed and fast pace. Measured data consisted of plantar-flexion and dorsi-flexion angles assumed by both ankles, so to objectively evidence the footdrop behavior of the DM1 disease, and to define a novel severity index, termed SI-Norm2, to rate the grade of walking impairments. According to the obtained results, our approach could be useful for a more precise stratification of DM1 patients, providing a new tool for a personalized rehabilitation approach. Full article
(This article belongs to the Special Issue Wearable Electronics for Assessing Human Motor (dis)Abilities)
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Open AccessEditor’s ChoiceArticle
Virtual Scenario Simulation and Modeling Framework in Autonomous Driving Simulators
Electronics 2021, 10(6), 694; https://doi.org/10.3390/electronics10060694 - 16 Mar 2021
Abstract
Recently, virtual environment-based techniques to train sensor-based autonomous driving models have been widely employed due to their efficiency. However, a simulated virtual environment is required to be highly similar to its real-world counterpart to ensure the applicability of such models to actual autonomous [...] Read more.
Recently, virtual environment-based techniques to train sensor-based autonomous driving models have been widely employed due to their efficiency. However, a simulated virtual environment is required to be highly similar to its real-world counterpart to ensure the applicability of such models to actual autonomous vehicles. Though advances in hardware and three-dimensional graphics engine technology have enabled the creation of realistic virtual driving environments, the myriad of scenarios occurring in the real world can only be simulated up to a limited extent. In this study, a scenario simulation and modeling framework that simulates the behavior of objects that may be encountered while driving is proposed to address this problem. This framework maximizes the number of scenarios, their types, and the driving experience in a virtual environment. Furthermore, a simulator was implemented and employed to evaluate the performance of the proposed framework. Full article
(This article belongs to the Special Issue AI-Based Autonomous Driving System)
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Open AccessEditor’s ChoiceArticle
Toward an Advanced Human Monitoring System Based on a Smart Body Area Network for Industry Use
Electronics 2021, 10(6), 688; https://doi.org/10.3390/electronics10060688 - 15 Mar 2021
Cited by 1
Abstract
This research provides a study on a smart body area network (SmartBAN) physical layer (PHY), as an of the Internet of medical things (IoMT) technology, for an advanced human monitoring system in industrial use. The SmartBAN provides a new PHY and a medium [...] Read more.
This research provides a study on a smart body area network (SmartBAN) physical layer (PHY), as an of the Internet of medical things (IoMT) technology, for an advanced human monitoring system in industrial use. The SmartBAN provides a new PHY and a medium access control (MAC) layer, improving its performance and providing very low-latency emergency information transmission with low energy consumption compared with other wireless body area network (WBAN) standards. On the other hand, IoMT applications are expected to become more advanced with smarter wearable devices, such as augmented reality-based human monitoring and work support in a factory. Therefore, it is possible to develop more advanced human monitoring systems for industrial use by combining the SmartBAN with multimedia devices. However, the SmartBAN PHY is not designed to transmit multimedia information such as audio and video. To address this issue, multilevel phase shift keying (PSK) modulation is applied to the SmartBAN PHY, and the symbol rate is improved by setting the roll-off rate appropriately to realize the system. The numerical results show that a sufficient link budget, receiver sensitivity and fade margin were obtained even when those approaches were applied to the SmartBAN PHY. The results indicate that these techniques are required for high-quality audio or video transmission, as well as vital sign data transmission, in a SmartBAN. Full article
(This article belongs to the Special Issue Smart Bioelectronics and Wearable Systems)
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Open AccessEditor’s ChoiceArticle
When Data Fly: An Open Data Trading System in Vehicular Ad Hoc Networks
Electronics 2021, 10(6), 654; https://doi.org/10.3390/electronics10060654 - 11 Mar 2021
Abstract
Communication between vehicles and their environment (i.e., vehicle-to-everything or V2X communication) in vehicular ad hoc networks (VANETs) has become of particular importance for smart cities. However, economic challenges, such as the cost incurred by data sharing (e.g., due to power consumption), hinder the [...] Read more.
Communication between vehicles and their environment (i.e., vehicle-to-everything or V2X communication) in vehicular ad hoc networks (VANETs) has become of particular importance for smart cities. However, economic challenges, such as the cost incurred by data sharing (e.g., due to power consumption), hinder the integration of data sharing in open systems into smart city applications, such as dynamic environmental zones. Moving from open data sharing to open data trading can address the economic challenges and incentivize vehicle drivers to share their data. In this context, integrating distributed ledger technology (DLT) into open systems for data trading is promising for reducing the transaction cost of payments in data trading, avoiding dependencies on third parties, and guaranteeing openness. However, because the integration of DLT conflicts with the short available communication time between fast moving objects in VANETs, it remains unclear how open data trading in VANETs using DLT should be designed to be viable. In this work, we present a system design for data trading in VANETs using DLT. We measure the required communication time for data trading between a vehicle and a roadside unit in a real scenario and estimate the associated cost. Our results show that the proposed system design is technically feasible and economically viable. Full article
(This article belongs to the Special Issue Blockchain-Based Technology for Mobile Application)
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Open AccessEditor’s ChoiceArticle
AlGaN Channel High Electron Mobility Transistors with Regrown Ohmic Contacts
Electronics 2021, 10(6), 635; https://doi.org/10.3390/electronics10060635 - 10 Mar 2021
Abstract
High power electronics using wide bandgap materials are maturing rapidly, and significant market growth is expected in a near future. Ultra wide bandgap materials, which have an even larger bandgap than GaN (3.4 eV), represent an attractive choice of materials to further push [...] Read more.
High power electronics using wide bandgap materials are maturing rapidly, and significant market growth is expected in a near future. Ultra wide bandgap materials, which have an even larger bandgap than GaN (3.4 eV), represent an attractive choice of materials to further push the performance limits of power devices. In this work, we report on the fabrication of AlN/AlGaN/AlN high-electron mobility transistors (HEMTs) using 50% Al-content on the AlGaN channel, which has a much wider bandgap than the commonly used GaN channel. The structure was grown by metalorganic chemical vapor deposition (MOCVD) on AlN/sapphire templates. A buffer breakdown field as high as 5.5 MV/cm was reported for short contact distances. Furthermore, transistors have been successfully fabricated on this heterostructure, with low leakage current and low on-resistance. A remarkable three-terminal breakdown voltage above 4 kV with an off-state leakage current below 1 μA/mm was achieved. A regrown ohmic contact was used to reduce the source/drain ohmic contact resistance, yielding a drain current density of about 0.1 A/mm. Full article
(This article belongs to the Special Issue Advances in Ultra-Wide Bandgap Devices)
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Open AccessEditor’s ChoiceArticle
A 2.53 NEF 8-bit 10 kS/s 0.5 μm CMOS Neural Recording Read-Out Circuit with High Linearity for Neuromodulation Implants
Electronics 2021, 10(5), 590; https://doi.org/10.3390/electronics10050590 - 03 Mar 2021
Abstract
This paper presents a power-efficient complementary metal-oxide-semiconductor (CMOS) neural signal-recording read-out circuit for multichannel neuromodulation implants. The system includes a neural amplifier and a successive approximation register analog-to-digital converter (SAR-ADC) for recording and digitizing neural signal data to transmit to a remote receiver. [...] Read more.
This paper presents a power-efficient complementary metal-oxide-semiconductor (CMOS) neural signal-recording read-out circuit for multichannel neuromodulation implants. The system includes a neural amplifier and a successive approximation register analog-to-digital converter (SAR-ADC) for recording and digitizing neural signal data to transmit to a remote receiver. The synthetic neural signal is generated using a LabVIEW myDAQ device and processed through a LabVIEW GUI. The read-out circuit is designed and fabricated in the standard 0.5 μμm CMOS process. The proposed amplifier uses a fully differential two-stage topology with a reconfigurable capacitive-resistive feedback network. The amplifier achieves 49.26 dB and 60.53 dB gain within the frequency bandwidth of 0.57–301 Hz and 0.27–12.9 kHz to record the local field potentials (LFPs) and the action potentials (APs), respectively. The amplifier maintains a noise–power tradeoff by reducing the noise efficiency factor (NEF) to 2.53. The capacitors are manually laid out using the common-centroid placement technique, which increases the linearity of the ADC. The SAR-ADC achieves a signal-to-noise ratio (SNR) of 45.8 dB, with a resolution of 8 bits. The ADC exhibits an effective number of bits of 7.32 at a low sampling rate of 10 ksamples/s. The total power consumption of the chip is 26.02 μμW, which makes it highly suitable for a multi-channel neural signal recording system. Full article
(This article belongs to the Section Circuit and Signal Processing)
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Open AccessEditor’s ChoiceArticle
Analytical Study of Periodic Restricted Access Window Mechanism for Short Slots
Electronics 2021, 10(5), 549; https://doi.org/10.3390/electronics10050549 - 26 Feb 2021
Abstract
The tremendous number of devices involved in the Internet of Things is bringing new challenges to wireless networking. The more devices that transmit in a wireless network, the higher the contention for the channel. The novel Wi-Fi HaLow standard introduces a new channel [...] Read more.
The tremendous number of devices involved in the Internet of Things is bringing new challenges to wireless networking. The more devices that transmit in a wireless network, the higher the contention for the channel. The novel Wi-Fi HaLow standard introduces a new channel access mechanism called the Periodic Restricted Access Window (PRAW), which aims to reduce this contention. With this mechanism, an access point can define a series of time intervals during which only a predefined group of stations can transmit data while the other stations are forbidden to access the channel. Unfortunately, the standard does not suggest how to configure the PRAW mechanism according to scenario-specific requirements and restrictions. Many Internet of Things scenarios require the fast and low energy consumption delivery of measurement data from wireless sensors while saving channel resources for other stations that transmit, for example, multimedia traffic. Therefore, this paper studies the problem of the minimization of the channel timeshare consumed by the PRAW with restrictions on the average delay and power consumption. To solve the problem and configure the PRAW optimally, a novel analytical model is developed. The key feature of the model is the consideration of the case of short PRAW slots that allow the computational complexity to be reduced and high accuracy to be achieved. These properties make the model suitable for implementation in real devices. Full article
(This article belongs to the Special Issue Wireless Network Protocols and Performance Evaluation)
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Open AccessEditor’s ChoiceArticle
An Efficient FPGA Implementation of Richardson-Lucy Deconvolution Algorithm for Hyperspectral Images
Electronics 2021, 10(4), 504; https://doi.org/10.3390/electronics10040504 - 21 Feb 2021
Abstract
This paper proposes an implementation of a Richardson-Lucy (RL) deconvolution method to reduce the spatial degradation in hyperspectral images during the image acquisition process. The degradation, modeled by convolution with a point spread function (PSF), is reduced by applying both standard and accelerated [...] Read more.
This paper proposes an implementation of a Richardson-Lucy (RL) deconvolution method to reduce the spatial degradation in hyperspectral images during the image acquisition process. The degradation, modeled by convolution with a point spread function (PSF), is reduced by applying both standard and accelerated RLdeconvolution algorithms on the individual images in spectral bands. Boundary conditions are introduced to maintain a constant image size without distorting the estimated image boundaries. The RL deconvolution algorithm is implemented on a field-programmable gate array (FPGA)-based Xilinx Zynq-7020 System-on-Chip (SoC). The proposed architecture is parameterized with respect to the image size and configurable with respect to the algorithm variant, the number of iterations, and the kernel size by setting the dedicated configuration registers. A speed-up by factors of 61 and 21 are reported compared to software-only and FPGA-based state-of-the-art implementations, respectively. Full article
(This article belongs to the Special Issue Hardware Architectures for Real Time Image Processing)
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Open AccessEditor’s ChoiceArticle
Performance Evaluation of LoRa 920 MHz Frequency Band in a Hilly Forested Area
Electronics 2021, 10(4), 502; https://doi.org/10.3390/electronics10040502 - 20 Feb 2021
Abstract
Long-range (LoRa) wireless communication technology has been widely used in many Internet-of-Things (IoT) applications in industry and academia. Radio wave propagation characteristics in forested areas are important to ensure communication quality in forest IoT applications. In this study, 920 MHz band propagation characteristics [...] Read more.
Long-range (LoRa) wireless communication technology has been widely used in many Internet-of-Things (IoT) applications in industry and academia. Radio wave propagation characteristics in forested areas are important to ensure communication quality in forest IoT applications. In this study, 920 MHz band propagation characteristics in forested areas and tree canopy openness were investigated in the Takakuma experimental forest in Kagoshima, Japan. The aim was to evaluate the performance of the LoRa 920 MHz band with spreading factor (SF12) in a forested hilly area. The received signal strength indicator (RSSI) was measured as a function of the distance between the transmitter antenna and ground station (GS). To illustrate the effect of canopy openness on radio wave propagation, sky view factor (SVF) and a forest canopy height model were considered at each location of a successfully received RSSI. A positive correlation was found between the RSSI and SVF. It was found that between the GS and transmitter antenna, if the canopy height is above 23 m, the signal diffracted and RSSI fell to −120 to −127 dBm, so the presence of the obstacle height should be considered. Further research is needed to clarify the detailed tree density between the transmitter and ground station to propose an optimal propagation model for a forested environment. Full article
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Open AccessEditor’s ChoiceArticle
Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography
Electronics 2021, 10(4), 495; https://doi.org/10.3390/electronics10040495 - 20 Feb 2021
Abstract
This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) [...] Read more.
This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Optimization of a 3D-Printed Permanent Magnet Coupling Using Genetic Algorithm and Taguchi Method
Electronics 2021, 10(4), 494; https://doi.org/10.3390/electronics10040494 - 20 Feb 2021
Abstract
In recent decades, the genetic algorithm (GA) has been extensively used in the design optimization of electromagnetic devices. Despite the great merits possessed by the GA, its processing procedure is highly time-consuming. On the contrary, the widely applied Taguchi optimization method is faster [...] Read more.
In recent decades, the genetic algorithm (GA) has been extensively used in the design optimization of electromagnetic devices. Despite the great merits possessed by the GA, its processing procedure is highly time-consuming. On the contrary, the widely applied Taguchi optimization method is faster with comparable effectiveness in certain optimization problems. This study explores the abilities of both methods within the optimization of a permanent magnet coupling, where the optimization objectives are the minimization of coupling volume and maximization of transmitted torque. The optimal geometry of the coupling and the obtained characteristics achieved by both methods are nearly identical. The magnetic torque density is enhanced by more than 20%, while the volume is reduced by 17%. Yet, the Taguchi method is found to be more time-efficient and effective within the considered optimization problem. Thanks to the additive manufacturing techniques, the initial design and the sophisticated geometry of the Taguchi optimal designs are precisely fabricated. The performances of the coupling designs are validated using an experimental setup. Full article
(This article belongs to the Special Issue Robust Design Optimization of Electrical Machines and Devices)
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Open AccessEditor’s ChoiceArticle
Ensemble-Based Classification Using Neural Networks and Machine Learning Models for Windows PE Malware Detection
Electronics 2021, 10(4), 485; https://doi.org/10.3390/electronics10040485 - 18 Feb 2021
Cited by 2
Abstract
The security of information is among the greatest challenges facing organizations and institutions. Cybercrime has risen in frequency and magnitude in recent years, with new ways to steal, change and destroy information or disable information systems appearing every day. Among the types of [...] Read more.
The security of information is among the greatest challenges facing organizations and institutions. Cybercrime has risen in frequency and magnitude in recent years, with new ways to steal, change and destroy information or disable information systems appearing every day. Among the types of penetration into the information systems where confidential information is processed is malware. An attacker injects malware into a computer system, after which he has full or partial access to critical information in the information system. This paper proposes an ensemble classification-based methodology for malware detection. The first-stage classification is performed by a stacked ensemble of dense (fully connected) and convolutional neural networks (CNN), while the final stage classification is performed by a meta-learner. For a meta-learner, we explore and compare 14 classifiers. For a baseline comparison, 13 machine learning methods are used: K-Nearest Neighbors, Linear Support Vector Machine (SVM), Radial basis function (RBF) SVM, Random Forest, AdaBoost, Decision Tree, ExtraTrees, Linear Discriminant Analysis, Logistic, Neural Net, Passive Classifier, Ridge Classifier and Stochastic Gradient Descent classifier. We present the results of experiments performed on the Classification of Malware with PE headers (ClaMP) dataset. The best performance is achieved by an ensemble of five dense and CNN neural networks, and the ExtraTrees classifier as a meta-learner. Full article
(This article belongs to the Special Issue High Accuracy Detection of Mobile Malware Using Machine Learning)
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Open AccessEditor’s ChoiceArticle
Time Efficient Unmanned Aircraft Systems Deployment in Disaster Scenarios Using Clustering Methods and a Set Cover Approach
Electronics 2021, 10(4), 422; https://doi.org/10.3390/electronics10040422 - 09 Feb 2021
Abstract
Unmanned aircraft, which are more commonly known as drones, are nowadays extensively used in an ever increasing set of applications. In a wider system, the aircraft are usually associated to additional elements such as ground-based controllers. Furthermore, when these components form a network [...] Read more.
Unmanned aircraft, which are more commonly known as drones, are nowadays extensively used in an ever increasing set of applications. In a wider system, the aircraft are usually associated to additional elements such as ground-based controllers. Furthermore, when these components form a network of elements that can communicate, the system is said to form an Unmanned Aircraft System (UAS). This system is particularly effective when the aircraft within are organized into swarms with sets of objectives to accomplish. The extensive use of swarms into UASs is more and more exploited nowadays due to the decreasing cost of those aircraft. In the present work we are interested in a particular application of UASs, namely their deployment in disaster scenarios for communications services provision to targets on the ground. These ground targets, however, are not part of the UASs and should not be confused with ground-based controllers. The present work does not only focus on coverage for ground targets but also on a guaranteed minimum number of covers for each target, which is called the redundancy requirement. The research work also ensures that the deployed UAS forms a unique connected component so that a steady stream of communication is kept with the targets to cover. Research work similar to the present perform the initial deployment of their aircraft in a different manner, either randomly, based on a predetermined grid formation, or using other elaborated methods. This work proposes a new solution based on the use of clustering algorithms, combined to a design of the problem formulated as a set cover optimization model. The clustering phase is used to discretize the search space and ease the optimization phase by locating regions of interest, and then a further procedure is applied, only when needed, to reconnect scattered connected components and guarantee connectivity in the networks. This way of doing it has achieved a deployment of UASs with maximum coverage for all targets, a guaranteed minimum number of covers for each of them, and results in a competitive computation time. The latter also allowed for more scalability by extending the tests to very large input instances. Full article
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Open AccessEditor’s ChoiceArticle
A Machine Learning Approach for Anomaly Detection in Industrial Control Systems Based on Measurement Data
Electronics 2021, 10(4), 407; https://doi.org/10.3390/electronics10040407 - 08 Feb 2021
Cited by 1
Abstract
Attack detection problems in industrial control systems (ICSs) are commonly known as a network traffic monitoring scheme for detecting abnormal activities. However, a network-based intrusion detection system can be deceived by attackers that imitate the system’s normal activity. In this work, we proposed [...] Read more.
Attack detection problems in industrial control systems (ICSs) are commonly known as a network traffic monitoring scheme for detecting abnormal activities. However, a network-based intrusion detection system can be deceived by attackers that imitate the system’s normal activity. In this work, we proposed a novel solution to this problem based on measurement data in the supervisory control and data acquisition (SCADA) system. The proposed approach is called measurement intrusion detection system (MIDS), which enables the system to detect any abnormal activity in the system even if the attacker tries to conceal it in the system’s control layer. A supervised machine learning model is generated to classify normal and abnormal activities in an ICS to evaluate the MIDS performance. A hardware-in-the-loop (HIL) testbed is developed to simulate the power generation units and exploit the attack dataset. In the proposed approach, we applied several machine learning models on the dataset, which show remarkable performances in detecting the dataset’s anomalies, especially stealthy attacks. The results show that the random forest is performing better than other classifier algorithms in detecting anomalies based on measured data in the testbed. Full article
(This article belongs to the Special Issue Security of Cyber-Physical Systems)
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Open AccessEditor’s ChoiceArticle
Identity and Access Management Resilience against Intentional Risk for Blockchain-Based IOT Platforms
Electronics 2021, 10(4), 378; https://doi.org/10.3390/electronics10040378 - 04 Feb 2021
Abstract
Some Internet of Things (IoT) platforms use blockchain to transport data. The value proposition of IoT is the connection to the Internet of a myriad of devices that provide and exchange data to improve people’s lives and add value to industries. The blockchain [...] Read more.
Some Internet of Things (IoT) platforms use blockchain to transport data. The value proposition of IoT is the connection to the Internet of a myriad of devices that provide and exchange data to improve people’s lives and add value to industries. The blockchain technology transfers data and value in an immutable and decentralised fashion. Security, composed of both non-intentional and intentional risk management, is a fundamental design requirement for both IoT and blockchain. We study how blockchain answers some of the IoT security requirements with a focus on intentional risk. The review of a sample of security incidents impacting public blockchains confirm that identity and access management (IAM) is a key security requirement to build resilience against intentional risk. This fact is also applicable to IoT solutions built on a blockchain. We compare the two IoT platforms based on public permissionless distributed ledgers with the highest market capitalisation: IOTA, run on an alternative to a blockchain, which is a directed acyclic graph (DAG); and IoTeX, its contender, built on a blockchain. Our objective is to discover how we can create IAM resilience against intentional risk in these IoT platforms. For that, we turn to complex network theory: a tool to describe and compare systems with many participants. We conclude that IoTeX and possibly IOTA transaction networks are scale-free. As both platforms are vulnerable to attacks, they require resilience against intentional risk. In the case of IoTeX, DIoTA provides a resilient IAM solution. Furthermore, we suggest that resilience against intentional risk requires an IAM concept that transcends a single blockchain. Only with the interplay of edge and global ledgers can we obtain data integrity in a multi-vendor and multi-purpose IoT network. Full article
(This article belongs to the Special Issue IoT Security and Privacy through the Blockchain)
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Open AccessEditor’s ChoiceArticle
Development and Realization of an Experimental Bench Test for Synchronized Small Angle Light Scattering and Biaxial Traction Analysis of Tissues
Electronics 2021, 10(4), 386; https://doi.org/10.3390/electronics10040386 - 04 Feb 2021
Cited by 1
Abstract
Insights into the mechanical and microstructural status of biological soft tissues are fundamental in analyzing diseases. Biaxial traction is the gold standard approach for mechanical characterization. The state of the art methods for microstructural assessment have different advantages and drawbacks. Small angle light [...] Read more.
Insights into the mechanical and microstructural status of biological soft tissues are fundamental in analyzing diseases. Biaxial traction is the gold standard approach for mechanical characterization. The state of the art methods for microstructural assessment have different advantages and drawbacks. Small angle light scattering (SALS) represents a valuable low energy technique for soft tissue assessment. The objective of the current work was to develop a bench test integrating mechanical and microstructural characterization capabilities for tissue specimens. The setup’s principle is based on the integration of biaxial traction and SALS analysis. A dedicated control application was developed with the objective of managing the test procedure. The different components of the setup are described and discussed, both in terms of hardware and software. The realization of the system and the corresponding performances are then presented. Full article
(This article belongs to the Special Issue Digital Twin Technology: New Frontiers for Personalized Healthcare)
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Open AccessEditor’s ChoiceArticle
Comparative Study of Optimal Multivariable LQR and MPC Controllers for Unmanned Combat Air Systems in Trajectory Tracking
Electronics 2021, 10(3), 331; https://doi.org/10.3390/electronics10030331 - 01 Feb 2021
Abstract
Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying [...] Read more.
Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying to satisfy a set of requirements that are sometimes in opposition. The purpose of this article was to compare two different control strategies in conjunction with a path-planning and guidance system with the objective of completing military missions in the most satisfactory way. For this purpose, a novel dynamic trajectory-planning algorithm is employed, which can obtain an appropriate trajectory by analyzing the environment as a discrete 3D adaptive mesh and performs a softening process a posteriori. Moreover, two multivariable control techniques are proposed, i.e., the linear quadratic regulator and the model predictive control, which were designed to offer optimal responses in terms of stability and robustness. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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Open AccessFeature PaperEditor’s ChoiceArticle
Wind Turbine Operation Curves Modelling Techniques
Electronics 2021, 10(3), 269; https://doi.org/10.3390/electronics10030269 - 23 Jan 2021
Cited by 4
Abstract
Wind turbines are machines operating in non-stationary conditions and the power of a wind turbine depends non-trivially on environmental conditions and working parameters. For these reasons, wind turbine power monitoring is a complex task which is typically addressed through data-driven methods for constructing [...] Read more.
Wind turbines are machines operating in non-stationary conditions and the power of a wind turbine depends non-trivially on environmental conditions and working parameters. For these reasons, wind turbine power monitoring is a complex task which is typically addressed through data-driven methods for constructing a normal behavior model. On these grounds, this study is devoted the analysis of meaningful operation curves, which are rotor speed-power, generator speed-power and blade pitch-power. A key point is that these curves are analyzed in the appropriate operation region of the wind turbines: the rotor and generator curves are considered for moderate wind speed, when the blade pitch is fixed and the rotational speed varies (Region 2); the blade pitch curve is considered for higher wind speed, when the rotational speed is rated (Region 2 12). The selected curves are studied through a multivariate Support Vector Regression with Gaussian Kernel on the Supervisory Control And Data Acquisition (SCADA) data of two wind farms sited in Italy, featuring in total 15 2 MW wind turbines. An innovative aspect of the selected models is that minimum, maximum and standard deviation of the independent variables of interest are fed as input to the models, in addition to the typically employed average values: using the additional covariates proposed in this work, the error metrics decrease of order of one third, with respect to what would be obtained by employing as regressors only the average values of the independent variables. In general it results that, for all the considered curves, the prediction of the power is characterized by error metrics which are competitive with the state of the art in the literature for multivariate wind turbine power curve analysis: in particular, for one test case, a mean absolute percentage error of order of 2.5% is achieved. Furthermore, the approach presented in this study provides a superior capability of interpreting wind turbine performance in terms of the behavior of the main sub-components and eliminates as much as possible the dependence on nacelle anemometer data, whose use is critical because of issues related to the sites complexity. Full article
(This article belongs to the Special Issue Wind Turbine Power Systems)
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Open AccessFeature PaperEditor’s ChoiceArticle
Solar Energy Conversion and Storage Using a Photocatalytic Fuel Cell Combined with a Supercapacitor
Electronics 2021, 10(3), 273; https://doi.org/10.3390/electronics10030273 - 23 Jan 2021
Abstract
This work studies the production of electricity by a photocatalytic fuel cell and its storage in a supercapacitor. We propose a simple construction, where a third electrode bearing activated carbon is added to the device to form a supercapacitor electrode in combination with [...] Read more.
This work studies the production of electricity by a photocatalytic fuel cell and its storage in a supercapacitor. We propose a simple construction, where a third electrode bearing activated carbon is added to the device to form a supercapacitor electrode in combination with the supporting electrolyte of the cell. The photocatalytic fuel cell is based on a CdS-sensitized mesoporous TiO2 photoanode and an air cathode bearing only nanoparticulate carbon as an oxygen reduction electrocatalyst. Full article
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Open AccessEditor’s ChoiceArticle
Device and Circuit Exploration of Multi-Nanosheet Transistor for Sub-3 nm Technology Node
Electronics 2021, 10(2), 180; https://doi.org/10.3390/electronics10020180 - 15 Jan 2021
Cited by 1
Abstract
A multi-nanosheet field-effect transistor (mNS-FET) device was developed to maximize gate controllability while making the channel in the form of a sheet. The mNS-FET has superior gate controllability for the stacked channels; consequently, it can significantly reduce the short-channel effect (SCE); however, punch-through [...] Read more.
A multi-nanosheet field-effect transistor (mNS-FET) device was developed to maximize gate controllability while making the channel in the form of a sheet. The mNS-FET has superior gate controllability for the stacked channels; consequently, it can significantly reduce the short-channel effect (SCE); however, punch-through inevitably occurs in the bottom channel portion that is not surrounded by gates, resulting in a large leakage current. Moreover, as the size of the semiconductor device decreases to several nanometers, the influence of the parasitic resistance and parasitic capacitance increases. Therefore, it is essential to apply design–technology co-optimization, which analyzes not only the characteristics from the perspective of the device but also the performance from the circuit perspective. In this study, we used Technology Computer Aided Design (TCAD) simulation to analyze the characteristics of the device and directly fabricated a model that describes the current–voltage and gate capacitance characteristics of the device by using Berkeley short-channel insulated-gate field-effect transistor–common multi-gate (BSIM–CMG) parameters. Through this model, we completed the Simulation Program with Integrated Circuit Emphasis (SPICE) simulation for circuit analysis and analyzed it from the viewpoint of devices and circuits. When comparing the characteristics according to the presence or absence of bottom oxide by conducting the above research method, it was confirmed that subthreshold slope (SS) and drain-induced barrier lowering (DIBL) are improved, and power and performance in circuit characteristics are increased. Full article
(This article belongs to the Special Issue New CMOS Devices and Their Applications)
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Open AccessEditor’s ChoiceArticle
A Design Method of Compensation Circuit for High-Power Dynamic Capacitive Power Transfer System Considering Coupler Voltage Distribution for Railway Applications
Electronics 2021, 10(2), 153; https://doi.org/10.3390/electronics10020153 - 12 Jan 2021
Abstract
Capacitive power transfer (CPT) is a promising method to solve the problems caused by the traditional Pantograph-catenary contact power supply for railway applications. In contrast, the CPT system suffers a broken risk because of the small coupling capacitor. This paper has analyzed the [...] Read more.
Capacitive power transfer (CPT) is a promising method to solve the problems caused by the traditional Pantograph-catenary contact power supply for railway applications. In contrast, the CPT system suffers a broken risk because of the small coupling capacitor. This paper has analyzed the CPT coupler’s voltage distributions for dynamic CPT systems when high power is required in real railway applications. The triangle relationship among the coupler voltages is derived. The circuit of the CPT system to accolated the coupler voltage is analyzed. Then, the compensation parameters are given. With the adopted LCLC-CL topology, the design process is presented by considering the coupler voltages. An experimental setup is conducted to validate the proposed design method. The experimental results show that the system can achieve 3 kW output power with 92.46% DC-DC efficiency and the voltage distribution aggress well with the designed values. Full article
(This article belongs to the Special Issue Wireless Power Transfer and Its Applications)
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Open AccessEditor’s ChoiceArticle
Design of Integrated Autonomous Driving Control System That Incorporates Chassis Controllers for Improving Path Tracking Performance and Vehicle Stability
Electronics 2021, 10(2), 144; https://doi.org/10.3390/electronics10020144 - 11 Jan 2021
Cited by 1
Abstract
This paper describes an integrated autonomous driving (AD) control system for an autonomous vehicle with four independent in-wheel motors (IWMs). The system consists of two parts: the AD controller and the chassis controller. These elements are functionally integrated to improve vehicle stability and [...] Read more.
This paper describes an integrated autonomous driving (AD) control system for an autonomous vehicle with four independent in-wheel motors (IWMs). The system consists of two parts: the AD controller and the chassis controller. These elements are functionally integrated to improve vehicle stability and path tracking performance. The vehicle is assumed to employ an IWM independently at each wheel. The AD controller implements longitudinal/lateral path tracking using proportional-integral(PI) control and adaptive model predictive control. The chassis controller is composed of two lateral control units: the active front steering (AFS) control and the torque vectoring (TV) control. Jointly, they find the yaw moment to maintain vehicle stability using sliding mode control; AFS is prioritized over TV to enhance safety margin and energy saving. Then, the command yaw moment is optimally distributed to each wheel by solving a constrained least-squares problem. Validation was performed using simulation in a double lane change scenario. The simulation results show that the integrated AD control system of this paper significantly improves the path tracking capability and vehicle stability in comparison with other control systems. Full article
(This article belongs to the Section Systems & Control Engineering)
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Open AccessEditor’s ChoiceArticle
Compact Continuous Time Common-Mode Feedback Circuit for Low-Power, Area-Constrained Neural Recording Amplifiers
Electronics 2021, 10(2), 145; https://doi.org/10.3390/electronics10020145 - 11 Jan 2021
Cited by 1
Abstract
A continuous-time common-mode feedback (CMFB) circuit for low-power, area-constrained neural recording amplifiers is proposed. The proposed CMFB circuit is compact; it can be realized by simply replacing passive components with transistors in a low-noise folded cascode operational transconductance amplifier (FC-OTA) that is one [...] Read more.
A continuous-time common-mode feedback (CMFB) circuit for low-power, area-constrained neural recording amplifiers is proposed. The proposed CMFB circuit is compact; it can be realized by simply replacing passive components with transistors in a low-noise folded cascode operational transconductance amplifier (FC-OTA) that is one of the most widely adopted OTAs for neural recording amplifiers. The proposed CMFB also consumes no additional power, i.e., no separate CMFB amplifier is required, thus, it fits well to low-power, area-constrained multichannel neural recording amplifiers. The proposed CMFB is analyzed in the implementation of a fully differential AC-coupled neural recording amplifier and compared with that of an identical neural recording amplifier using a conventional differential difference amplifier-based CMFB in 0.18 μm CMOS technology post-layout simulations. The AC-coupled neural recording amplifier with the proposed CMFB occupies ~37% less area and consumes ~11% smaller power, providing 2.67× larger output common mode (CM) range without CM bandwidth sacrifice in the comparison. Full article
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
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Open AccessEditor’s ChoiceArticle
AC Current Ripple Harmonic Pollution in Three-Phase Four-Leg Active Front-End AC/DC Converter for On-Board EV Chargers
Electronics 2021, 10(2), 116; https://doi.org/10.3390/electronics10020116 - 07 Jan 2021
Cited by 2
Abstract
Three-phase four-leg voltage-source converters have been considered for some recent projects in smart grids and in the automotive industry, projects such as on-board electric vehicles (EVs) chargers, thanks to their built-in ability to handle unbalanced AC currents through the 4th wire (neutral). Although [...] Read more.
Three-phase four-leg voltage-source converters have been considered for some recent projects in smart grids and in the automotive industry, projects such as on-board electric vehicles (EVs) chargers, thanks to their built-in ability to handle unbalanced AC currents through the 4th wire (neutral). Although conventional carrier-based modulations (CBMs) and space vector modulations (SVMs) have been commonly applied and extensively studied for three-phase four-leg voltage-source converters, very little has been reported concerning their pollution impact on AC grid in terms of switching ripple currents. This paper introduces a thorough analytical derivation of peak-to-peak and RMS values of the AC current ripple under balanced and unbalanced working conditions, in the case of three-phase four-leg converters with uncoupled AC-link inductors. The proposed mathematical approach covers both phase and neutral currents. All analytical findings have been applied to two industry recognized CBM methods, namely sinusoidal pulse-width modulation (PWM) and centered PWM (equivalent to SVM). The derived equations are effective, simple, and ready-to-use for accurate AC current ripple calculations. At the same time, the proposed equations and diagrams can be successfully adopted to design the conversion system basing on the grid codes in terms of current ripple (or total harmonic distortion (THD)/total demand distortion (TDD)) restrictions, enabling the sizing of AC-link inductors and the determination of the proper switching frequency for the given operating conditions. The analytical developments have been thoroughly verified by numerical simulations in MATLAB/Simulink and by extensive experimental tests. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
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Open AccessEditor’s ChoiceArticle
LTPS TFTs with an Amorphous Silicon Buffer Layer and Source/Drain Extension
Electronics 2021, 10(1), 29; https://doi.org/10.3390/electronics10010029 - 28 Dec 2020
Abstract
A low leakage poly-Si thin film transistor (TFT) is proposed featuring hydrogenated amorphous silicon (a-Si:H) buffer layer and source/drain extension (SDE) by using technology computer aided design (TCAD) simulation. This architecture reduces off-current effectively by suppressing two leakage current generation mechanisms with little [...] Read more.
A low leakage poly-Si thin film transistor (TFT) is proposed featuring hydrogenated amorphous silicon (a-Si:H) buffer layer and source/drain extension (SDE) by using technology computer aided design (TCAD) simulation. This architecture reduces off-current effectively by suppressing two leakage current generation mechanisms with little on-current loss. The amorphous silicon buffer layer having large bandgap energy (Eg) suppresses both thermal generation and minimum leakage current, which leads to higher on/off current ratio. In addition, the formation of lightly doped region near the drain alleviates the field-enhanced generation in the off-state by reducing electric field. TCAD simulation results show that the proposed TFT shows more than three orders of magnitude lower off-current than low-temperature polycrystalline silicon (LTPS) TFTs, while maintaining on-current. Full article
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Open AccessEditor’s ChoiceArticle
A Survey of Candidate Waveforms for beyond 5G Systems
Electronics 2021, 10(1), 21; https://doi.org/10.3390/electronics10010021 - 25 Dec 2020
Cited by 2
Abstract
The 5G and beyond future wireless networks aim to support a large variety of services with increasing demand in terms of data rate and throughput while providing a higher degree of reliability, keeping the overall system complexity affordable. One of the key aspects [...] Read more.
The 5G and beyond future wireless networks aim to support a large variety of services with increasing demand in terms of data rate and throughput while providing a higher degree of reliability, keeping the overall system complexity affordable. One of the key aspects regarding the physical layer architecture of such systems is the definition of the waveform to be used in the air interface. Such waveforms must be studied and compared in order to choose the most suitable and capable of providing the 5G and beyond services requirements, with flexible resource allocation in time and frequency domains, while providing high spectral and power efficiencies. In this paper, several beyond 5G waveforms candidates are presented, along with their transceiver architectures. Additionally, the associated advantages and disadvantages regarding the use of these transmission techniques are discussed. They are compared in a similar downlink transmission scenario where three main key performance indicators (KPIs) are evaluated. They are the peak-to-average power ratio, the overall system spectral efficiency (wherein the out of band emissions are measured, along with the spectral confinement of the power spectral density of the transmitted signals) and the bit error rate performance. Additionally, other KPIs are discussed. Full article
(This article belongs to the Special Issue Advanced Communication Techniques for 5G and Internet of Things)
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Open AccessEditor’s ChoiceArticle
Ultra-Wideband MIMO Array for Penetrating Lunar Regolith Structures on the Chang’e-5 Lander
Electronics 2021, 10(1), 8; https://doi.org/10.3390/electronics10010008 - 23 Dec 2020
Abstract
The Chang’e-5 lunar exploration mission of China is equipped with a Lunar Regolith Penetrating Radar (LRPR) for measuring the thickness and structures of the lunar regolith in the landing area. Since the LRPR is stationary, an ultra-wideband multiple-input multiple-output (MIMO) array is designed [...] Read more.
The Chang’e-5 lunar exploration mission of China is equipped with a Lunar Regolith Penetrating Radar (LRPR) for measuring the thickness and structures of the lunar regolith in the landing area. Since the LRPR is stationary, an ultra-wideband multiple-input multiple-output (MIMO) array is designed as a replacement for conventional mobile subsurface probing systems. The MIMO array, with 12 antenna elements and a switch matrix, operates in the frequency band from 1.0 to 4.75 GHz. In this work, the design and layout of the antenna elements were optimized with respect to the lander. To this end, the antenna elements were designed as miniaturized Vivaldi antennas with quarter elliptical slots (i.e., quarter elliptical slotted antenna, or QESA). QESAs are significantly small while being able to mitigate the impact of the lander on antenna electrical performances. QESAs also have a wide operating bandwidth, flat gain, and excellent time domain characteristics. In addition, a high-temperature resistant ultra-light radome with high transmissivity is designed to protect the external antenna array. After calibration, the MIMO array is used to detect targets embedded in volcanic ash. The detection depth reaches 2.5 m, and the detection effect is good. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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Open AccessEditor’s ChoiceArticle
CNN2Gate: An Implementation of Convolutional Neural Networks Inference on FPGAs with Automated Design Space Exploration
Electronics 2020, 9(12), 2200; https://doi.org/10.3390/electronics9122200 - 21 Dec 2020
Cited by 2
Abstract
Convolutional Neural Networks (CNNs) have a major impact on our society, because of the numerous services they provide. These services include, but are not limited to image classification, video analysis, and speech recognition. Recently, the number of researches that utilize FPGAs to implement [...] Read more.
Convolutional Neural Networks (CNNs) have a major impact on our society, because of the numerous services they provide. These services include, but are not limited to image classification, video analysis, and speech recognition. Recently, the number of researches that utilize FPGAs to implement CNNs are increasing rapidly. This is due to the lower power consumption and easy reconfigurability that are offered by these platforms. Because of the research efforts put into topics, such as architecture, synthesis, and optimization, some new challenges are arising for integrating suitable hardware solutions to high-level machine learning software libraries. This paper introduces an integrated framework (CNN2Gate), which supports compilation of a CNN model for an FPGA target. CNN2Gate is capable of parsing CNN models from several popular high-level machine learning libraries, such as Keras, Pytorch, Caffe2, etc. CNN2Gate extracts computation flow of layers, in addition to weights and biases, and applies a “given” fixed-point quantization. Furthermore, it writes this information in the proper format for the FPGA vendor’s OpenCL synthesis tools that are then used to build and run the project on FPGA. CNN2Gate performs design-space exploration and fits the design on different FPGAs with limited logic resources automatically. This paper reports results of automatic synthesis and design-space exploration of AlexNet and VGG-16 on various Intel FPGA platforms. Full article
(This article belongs to the Section Artificial Intelligence Circuits and Systems (AICAS))
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Open AccessEditor’s ChoiceArticle
A Compact and Robust Technique for the Modeling and Parameter Extraction of Carbon Nanotube Field Effect Transistors
Electronics 2020, 9(12), 2199; https://doi.org/10.3390/electronics9122199 - 20 Dec 2020
Abstract
Carbon nanotubes field-effect transistors (CNTFETs) have been recently studied with great interest due to the intriguing properties of the material that, in turn, lead to remarkable properties of the charge transport of the device channel. Downstream of the full-wave simulations, the construction of [...] Read more.
Carbon nanotubes field-effect transistors (CNTFETs) have been recently studied with great interest due to the intriguing properties of the material that, in turn, lead to remarkable properties of the charge transport of the device channel. Downstream of the full-wave simulations, the construction of equivalent device models becomes the basic step for the advanced design of high-performance CNTFET-based nanoelectronics circuits and systems. In this contribution, we introduce a strategy for deriving a compact model for a CNTFET that is based on the full-wave simulation of the 3D geometry by using the finite element method, followed by the derivation of a compact circuit model and extraction of equivalent parameters. We show examples of CNTFET simulations and extract from them the fitting parameters of the model. The aim is to achieve a fully functional description in Verilog-A language and create a model library for the SPICE-like simulator environment, in order to be used by IC designers. Full article
(This article belongs to the Section Microelectronics and Optoelectronics)
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Open AccessEditor’s ChoiceArticle
Electrical Performance and Stability Improvements of High-Mobility Indium–Gallium–Tin Oxide Thin-Film Transistors Using an Oxidized Aluminum Capping Layer of Optimal Thickness
Electronics 2020, 9(12), 2196; https://doi.org/10.3390/electronics9122196 - 20 Dec 2020
Abstract
We examined the effects of aluminum (Al) capping layer thickness on the electrical performance and stability of high-mobility indium–gallium–tin oxide (IGTO) thin-film transistors (TFTs). The Al capping layers with thicknesses (tAls) of 3, 5, and 8 nm were deposited, respectively, [...] Read more.
We examined the effects of aluminum (Al) capping layer thickness on the electrical performance and stability of high-mobility indium–gallium–tin oxide (IGTO) thin-film transistors (TFTs). The Al capping layers with thicknesses (tAls) of 3, 5, and 8 nm were deposited, respectively, on top of the IGTO thin film by electron beam evaporation, and the IGTO TFTs without and with Al capping layers were subjected to thermal annealing at 200 °C for 1 h in ambient air. Among the IGTO TFTs without and with Al capping layers, the TFT with a 3 nm thick Al capping layer exhibited excellent electrical performance (field-effect mobility: 26.4 cm2/V s, subthreshold swing: 0.20 V/dec, and threshold voltage: −1.7 V) and higher electrical stability under positive and negative bias illumination stresses than other TFTs. To elucidate the physical mechanism responsible for the observed phenomenon, we compared the O1s spectra of the IGTO thin films without and with Al capping layers using X-ray photoelectron spectroscopy analyses. From the characterization results, it was observed that the weakly bonded oxygen-related components decreased from 25.0 to 10.0%, whereas the oxygen-deficient portion was maintained at 24.4% after the formation of the 3 nm thick Al capping layer. In contrast, a significant increase in the oxygen-deficient portion was observed after the formation of the Al capping layers having tAl values greater than 3 nm. These results imply that the thicker Al capping layer has a stronger gathering power for the oxygen species, and that 3 nm is the optimum thickness of the Al capping layer, which can selectively remove the weakly bonded oxygen species acting as subgap tail states within the IGTO. The results of this study thus demonstrate that the formation of an Al capping layer with the optimal thickness is a practical and useful method to enhance the electrical performance and stability of high-mobility IGTO TFTs. Full article
(This article belongs to the Special Issue Applications of Thin Films in Microelectronics)
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Open AccessEditor’s ChoiceArticle
Wavelet Transform Analysis of Heart Rate to Assess Recovery Time for Long Distance Runners
Electronics 2020, 9(12), 2189; https://doi.org/10.3390/electronics9122189 - 18 Dec 2020
Abstract
The diagnostics of the condition of athletes has become a field of special scientific interest and activity. The aim of this study was to verify the effect of a long (100 km) run on a group of runners, as well as to assess [...] Read more.
The diagnostics of the condition of athletes has become a field of special scientific interest and activity. The aim of this study was to verify the effect of a long (100 km) run on a group of runners, as well as to assess the recovery time that is required for them to return to the pre-run state. The heart rate (HR) data presented were collected the day before the extreme physical effort, on the same day as, but after, the physical effort, as well as 24 and 48 h after. The Wavelet Transform (WT) and the Wavelet-based Fractal Analysis (WBFA) were implemented in the analysis. A tool was constructed that, based on quantitative data, enables one to confirm the completion of the recovery process that is related to the extreme physical effort. Indirectly, a tool was constructed that enables one to confirm the completion of the recovery process. The obtained information proves that the return to the resting state of the body after a significant physical effort can be observed after two days entirely through the analysis of the HR. Certain practical measures were used to differentiate between two substantially different states of the human body, i.e., pre- and post-effort states were constructed. The obtained results allow for us to state that WBFA appears to be a useful and robust tool in the determination of hidden features of stochastic signals, such as HR time signals. The proposed method allows one to differentiate between particular days of measurements with a mean probability of 92.2%. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Event-Focused Digital Control to Keep High Efficiency in a Wide Power Range in a SiC-Based Synchronous DC/DC Boost Converter
Electronics 2020, 9(12), 2154; https://doi.org/10.3390/electronics9122154 - 16 Dec 2020
Cited by 1
Abstract
This paper is focused on the design of a control approach, based on the detection of events and changing between two different conduction modes, to reach high efficiency over the entire power range, especially at medium and low power levels. Although the proposed [...] Read more.
This paper is focused on the design of a control approach, based on the detection of events and changing between two different conduction modes, to reach high efficiency over the entire power range, especially at medium and low power levels. Although the proposed control strategy can be generalized for different topologies and specifications, in this paper, the strategy is validated in a SiC-based synchronous boost DC/DC converter rated for 400 V to 800 V and 10 kW. Evaluation of the power losses and current waveforms of the converter for different conduction modes and loads predicts suitable performance of quasi-square wave mode with zero voltage switching (QSW-ZVS) conduction mode for low and medium power and of continuous conduction Mode with hard switching (CCM-HS) for high power. Consequently, this paper proposes a control strategy, taking advantage of digital control, that allows automatic adjustment of the conduction mode to optimize the performance for different power ranges. Full article
(This article belongs to the Special Issue Innovative Technologies in Power Converters)
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Open AccessEditor’s ChoiceArticle
An Efficient Deep-Learning-Based Detection and Classification System for Cyber-Attacks in IoT Communication Networks
Electronics 2020, 9(12), 2152; https://doi.org/10.3390/electronics9122152 - 15 Dec 2020
Cited by 1
Abstract
With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, the Internet of Things (IoT) has earned wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, [...] Read more.
With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, the Internet of Things (IoT) has earned wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack that tends to be treated as normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with the cybersecurity field has become a recent inclination of many security applications due to their impressive performance. In this paper, we provide the comprehensive development of a new intelligent and autonomous deep-learning-based detection and classification system for cyber-attacks in IoT communication networks that leverage the power of convolutional neural networks, abbreviated as IoT-IDCS-CNN (IoT based Intrusion Detection and Classification System using Convolutional Neural Network). The proposed IoT-IDCS-CNN makes use of high-performance computing that employs the robust Compute Unified Device Architectures (CUDA) based Nvidia GPUs (Graphical Processing Units) and parallel processing that employs high-speed I9-core-based Intel CPUs. In particular, the proposed system is composed of three subsystems: a feature engineering subsystem, a feature learning subsystem, and a traffic classification subsystem. All subsystems were developed, verified, integrated, and validated in this research. To evaluate the developed system, we employed the Network Security Laboratory-Knowledge Discovery Databases (NSL-KDD) dataset, which includes all the key attacks in IoT computing. The simulation results demonstrated a greater than 99.3% and 98.2% cyber-attack classification accuracy for the binary-class classifier (normal vs. anomaly) and the multiclass classifier (five categories), respectively. The proposed system was validated using a K-fold cross-validation method and was evaluated using the confusion matrix parameters (i.e., true negative (TN), true positive (TP), false negative (FN), false positive (FP)), along with other classification performance metrics, including precision, recall, F1-score, and false alarm rate. The test and evaluation results of the IoT-IDCS-CNN system outperformed many recent machine-learning-based IDCS systems in the same area of study. Full article
(This article belongs to the Special Issue Advances on Networks and Cyber Security)
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Open AccessEditor’s ChoiceArticle
Low Voltage Time-Based Matrix Multiplier-and-Accumulator for Neural Computing System
Electronics 2020, 9(12), 2138; https://doi.org/10.3390/electronics9122138 - 14 Dec 2020
Abstract
A time-based matrix multiply-and-accumulate (MAC) operation for a neural computing system is described. A simple and compact time-based matrix MAC structure is proposed that can perform multiplication and accumulation simultaneously in a single multiplier structure, and the hardware complexity is not affected by [...] Read more.
A time-based matrix multiply-and-accumulate (MAC) operation for a neural computing system is described. A simple and compact time-based matrix MAC structure is proposed that can perform multiplication and accumulation simultaneously in a single multiplier structure, and the hardware complexity is not affected by the matrix input size. To enhance the linearity of the weight factor, an offset-free pulse-width modulator is introduced. The proposed MAC architecture operates at a low supply voltage of 0.5 V while it consumes MAC energy of 0.38 pJ with a 32 nm low-power (LP) predictive technology model (PTM) CMOS process. In addition, the near-subthreshold operation can remove the level shifter to interface between the MAC operator and digital circuits such as static random-access-memory (SRAM) because both can utilize the same level of the supply voltage. The proposed MAC is based on a digital intensive pulse-width modulation, and thus it can further improve its performance and area with more advanced technologies. Full article
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
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Open AccessEditor’s ChoiceArticle
A Novel Printable Tag of M-Shaped Strips for Chipless Radio-Frequency Identification in IoT Applications
Electronics 2020, 9(12), 2116; https://doi.org/10.3390/electronics9122116 - 11 Dec 2020
Cited by 2
Abstract
There is a growing interest in chipless radio-frequency identification (RFID) technology for a number of Internet of things (IoT) applications. This is due to its advantages of being of low-cost, low-power, and fully printable. In addition, it enjoys ease of implementation. In this [...] Read more.
There is a growing interest in chipless radio-frequency identification (RFID) technology for a number of Internet of things (IoT) applications. This is due to its advantages of being of low-cost, low-power, and fully printable. In addition, it enjoys ease of implementation. In this paper, we present a novel, compact, chipless radio-frequency identification (RFID) tag that can be read with either vertical or horizontal polarization within its frequency bandwidth. This increases the sturdiness and detection ability of the RFID system. In addition, the difference between the vertical and horizontal responses can be used for tag identification. The proposed tag uses strip length variations to double the coding capacity and thereby reduce the overall size by almost 50%. It has a coding capacity of 20 bits in the operating bandwidth 3 GHz–7.5 GHz, and its spatial density is approximately 11 bits/cm2. The proposed tag has a 4.44 bits/GHz spectral capacity, 2.44 bits/cm2/GHz encoding capacity, a spatial density at the center frequency of 358.33 bits/λ2, and an encoding capacity at the center frequency of 79.63 bits/λ2/GHz. A prototype is fabricated and experimentally tested at a distance of 10 cm from the RFID reader system. Then, we compare the measured results with the simulations. The simulated results are in reasonable agreement with the simulated ones. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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Open AccessFeature PaperEditor’s ChoiceArticle
A Radio Frequency Magnetoelectric Antenna Prototyping Platform for Neural Activity Monitoring Devices with Sensing and Energy Harvesting Capabilities
Electronics 2020, 9(12), 2123; https://doi.org/10.3390/electronics9122123 - 11 Dec 2020
Cited by 1
Abstract
This article describes the development of a radio frequency (RF) platform for electromagnetically modulated signals that makes use of a software-defined radio (SDR) to receive information from a novel magnetoelectric (ME) antenna capable of sensing low-frequency magnetic fields with ultra-low magnitudes. The platform [...] Read more.
This article describes the development of a radio frequency (RF) platform for electromagnetically modulated signals that makes use of a software-defined radio (SDR) to receive information from a novel magnetoelectric (ME) antenna capable of sensing low-frequency magnetic fields with ultra-low magnitudes. The platform is employed as part of research and development to utilize miniaturized ME antennas and integrated circuits for neural recording with wireless implantable devices. To prototype the reception of electromagnetically modulated signals from a sensor, a versatile Universal Software Radio Peripheral (USRP) and the GNU Radio toolkit are utilized to enable real-time signal processing under varying operating conditions. Furthermore, it is demonstrated how a radio frequency signal transmitted from the SDR can be captured by the ME antenna for wireless energy harvesting. Full article
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Open AccessFeature PaperEditor’s ChoiceArticle
Ka-Band Diplexer for 5G mmWave Applications in Inverted Microstrip Gap Waveguide Technology
Electronics 2020, 9(12), 2094; https://doi.org/10.3390/electronics9122094 - 08 Dec 2020
Cited by 1
Abstract
A new cost-efficient, low-loss Ka-band diplexer designed in inverted microstrip gap waveguide technology is presented in this paper. Gap waveguide allows to propagate quasi-TEM modes in the air between two metal plates without the need for contact between them by using periodic metasurfaces. [...] Read more.
A new cost-efficient, low-loss Ka-band diplexer designed in inverted microstrip gap waveguide technology is presented in this paper. Gap waveguide allows to propagate quasi-TEM modes in the air between two metal plates without the need for contact between them by using periodic metasurfaces. The diplexer is realized by using a bed of nails as AMC (Artificial Magnetic Conductor), first modeled with a PMC (Perfect Magnetic Conductor) surface for design simplification, and two fifth order end-coupled passband filters (BPFs) along with a power divider. The experimental verification confirms that the two channels centered at 24 GHz and 28 GHz with 1 GHz of bandwidth show measured insertion losses of 1.5 dB and 2 dB and 60 dB of isolation between them. A slight shift in frequency is observed in the measurements that can be easily explained by the variation in the permittivity of the substrate. Full article
(This article belongs to the Special Issue Millimeter and Terahertz Wireless Communications)
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Open AccessEditor’s ChoiceArticle
Signal Transformations for Analysis of Supraharmonic EMI Caused by Switched-Mode Power Supplies
Electronics 2020, 9(12), 2088; https://doi.org/10.3390/electronics9122088 - 07 Dec 2020
Cited by 2
Abstract
Switched-Mode Power Supplies (SMPSs) are a relevant source of conducted emissions, in particular in the frequency interval of supraharmonics, between 2 kHz and 150 kHz. When using sampled data for assessment of compliance, methods other than Fourier analysis should be considered for better [...] Read more.
Switched-Mode Power Supplies (SMPSs) are a relevant source of conducted emissions, in particular in the frequency interval of supraharmonics, between 2 kHz and 150 kHz. When using sampled data for assessment of compliance, methods other than Fourier analysis should be considered for better frequency resolution, compact signal energy decomposition and a shorter time support. This work investigates the application of the Wavelet Packet Transform (WPT) and the Empirical Mode Decomposition (EMD) to measured recordings of SMPS conducted emissions, featuring steep impulses and damped oscillations. The comparison shows a general accuracy of the amplitude estimate within the variability of data themselves, with very good performance of WPT in tracking on stationary components in the low frequency range at some kHz. WPT performance however may vary appreciably depending on the selected mother wavelet for which some examples are given. EMD and its Ensemble EMD implementation show a fairly good accuracy in representing the original signal with a very limited number of base functions with the capability of exploiting a filtering effect on the low-frequency components of the signal. Full article
(This article belongs to the Special Issue Electromagnetic Interference and Compatibility)
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Open AccessFeature PaperEditor’s ChoiceArticle
A Comparative Study of Stochastic Model Predictive Controllers
Electronics 2020, 9(12), 2078; https://doi.org/10.3390/electronics9122078 - 06 Dec 2020
Cited by 1
Abstract
A comparative study of two state-of-the-art stochastic model predictive controllers for linear systems with parametric and additive uncertainties is presented. On the one hand, Stochastic Model Predictive Control (SMPC) is based on analytical methods and solves an optimal control problem (OCP) similar to [...] Read more.
A comparative study of two state-of-the-art stochastic model predictive controllers for linear systems with parametric and additive uncertainties is presented. On the one hand, Stochastic Model Predictive Control (SMPC) is based on analytical methods and solves an optimal control problem (OCP) similar to a classic Model Predictive Control (MPC) with constraints. SMPC defines probabilistic constraints on the states, which are transformed into equivalent deterministic ones. On the other hand, Scenario-based Model Predictive Control (SCMPC) solves an OCP for a specified number of random realizations of uncertainties, also called scenarios. In this paper, Classic MPC, SMPC and SCMPC are compared through two numerical examples. Thanks to several Monte-Carlo simulations, performances of classic MPC, SMPC and SCMPC are compared using several criteria, such as number of successful runs, number of times the constraints are violated, integral absolute error and computational cost. Moreover, a Stochastic Model Predictive Control Toolbox was developed by the authors, available on MATLAB Central, in which it is possible to simulate a SMPC or a SCMPC to control multivariable linear systems with additive disturbances. This software was used to carry out part of the simulations of the numerical examples in this article and it can be used for results reproduction. Full article
(This article belongs to the Special Issue Model Predictive Control and Optimization Applied to Process Control)
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Open AccessFeature PaperEditor’s ChoiceArticle
Feasibility of Harvesting Solar Energy for Self-Powered Environmental Wireless Sensor Nodes
Electronics 2020, 9(12), 2058; https://doi.org/10.3390/electronics9122058 - 03 Dec 2020
Cited by 1
Abstract
Energy harvesting has a vital role in building reliable Environmental Wireless Sensor Networks (EWSNs), without needing to replace a discharged battery. Solar energy is one of the main renewable energy sources that can be used to efficiently charge a battery. This paper introduces [...] Read more.
Energy harvesting has a vital role in building reliable Environmental Wireless Sensor Networks (EWSNs), without needing to replace a discharged battery. Solar energy is one of the main renewable energy sources that can be used to efficiently charge a battery. This paper introduces two solar energy harvesters and their power measurements at different light conditions in order to charge rechargeable AA batteries powering EWSN nodes. The first harvester is a primitive energy harvesting circuit that is built using elementary off-shelf components, while the second harvester is based on a commercial boost converter chip. To prove the effectiveness of harvesting solar energy, five EWSN nodes were distributed at a nature reserve (the Audubon Society of Western Pennsylvania, USA) and the sunlight at their locations was recorded for more than five months. For each recorded illumination, the corresponding harvested energy has been estimated and compared with the average energy consumption of the EWSN with the most power consumption. The results show that the daily harvested energy effectively compensates for the energy consumption of the EWSN nodes, and the battery charge capacity of 295 mAh can reliably support their daily dynamic energy consumption. Full article
(This article belongs to the Special Issue Energy Efficient Circuit Design Techniques for Low Power Systems)
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Open AccessEditor’s ChoiceArticle
One-Cycle Zero-Integral-Error Current Control for Shunt Active Power Filters
Electronics 2020, 9(12), 2008; https://doi.org/10.3390/electronics9122008 - 26 Nov 2020
Cited by 1
Abstract
Current control has, for decades, been one of the more challenging research fields in the development of power converters. Simple and robust nonlinear methods like hysteresis or sigma-delta controllers have been commonly used, while sophisticated linear controllers based on classical control theory have [...] Read more.
Current control has, for decades, been one of the more challenging research fields in the development of power converters. Simple and robust nonlinear methods like hysteresis or sigma-delta controllers have been commonly used, while sophisticated linear controllers based on classical control theory have been developed for PWM-based converters. The one-cycle current control technique is a nonlinear technique based on cycle-by-cycle calculation of the ON time of the converter switches for the next switching period. This kind of controller requires accurate measurement of voltages and currents in order achieve a precise current tracking. These techniques have been frequently used in the control of power converters generating low-frequency currents, where the reference varies slowly compared with the switching frequency. Its application is not so common in active power filter current controllers due to the fast variation of the references that demands not only accurate measurements but also high-speed computing. This paper proposes a novel one-cycle digital current controller based on the minimization of the integral error of the current. Its application in a three-leg four-wire shunt active power filter is presented, including a stability analysis considering the switching pattern selection. Furthermore, simulated and experimental results are presented to validate the proposed controller. Full article
(This article belongs to the Special Issue Digital Control in Power Electronics)
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Open AccessEditor’s ChoiceArticle
Recognition of Drivers’ Activity Based on 1D Convolutional Neural Network
Electronics 2020, 9(12), 2002; https://doi.org/10.3390/electronics9122002 - 25 Nov 2020
Abstract
Background and objective: Driving a car is a complex activity which involves movements of the whole body. Many studies on drivers’ behavior are conducted to improve road traffic safety. Such studies involve the registration and processing of multiple signals, such as electroencephalography (EEG), [...] Read more.
Background and objective: Driving a car is a complex activity which involves movements of the whole body. Many studies on drivers’ behavior are conducted to improve road traffic safety. Such studies involve the registration and processing of multiple signals, such as electroencephalography (EEG), electrooculography (EOG) and the images of the driver’s face. In our research, we attempt to develop a classifier of scenarios related to learning to drive based on the data obtained in real road traffic conditions via smart glasses. In our approach, we try to minimize the number of signals which can be used to recognize the activities performed while driving a car. Material and methods: We attempt to evaluate the drivers’ activities using both electrooculography (EOG) and a deep learning approach. To acquire data we used JINS MEME smart glasses furnished with 3-point EOG electrodes, 3-axial accelerometer and 3-axial gyroscope. Sensor data were acquired on 20 drivers (ten experienced and ten learner drivers) on the same 28.7 km route under real road conditions in southern Poland. The drivers performed several tasks while wearing the smart glasses and the tasks were linked to the signal during the drive. For the recognition of four activities (parking, driving through a roundabout, city traffic and driving through an intersection), we used one-dimensional convolutional neural network (1D CNN). Results: The maximum accuracy was 95.6% on validation set and 99.8% on training set. The results prove that the model based on 1D CNN can classify the actions performed by drivers accurately. Conclusions: We have proved the feasibility of recognizing drivers’ activity based solely on EOG data, regardless of the driving experience and style. Our findings may be useful in the objective assessment of driving skills and thus, improving driving safety. Full article
(This article belongs to the Special Issue Application of Neural Networks in Biosignal Process)
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Open AccessEditor’s ChoiceArticle
A Distributed Observer-Based Cyber-Attack Identification Scheme in Cooperative Networked Systems under Switching Communication Topologies
Electronics 2020, 9(11), 1912; https://doi.org/10.3390/electronics9111912 - 13 Nov 2020
Abstract
This paper studies an approach for detecting cyber attacks against networked cooperative systems (NCS) that are assumed to be working in a cyber-physical environment. NCS are prone to anomalies both due to cyber and physical attacks and faults. Cyber-attacks being more hazardous given [...] Read more.
This paper studies an approach for detecting cyber attacks against networked cooperative systems (NCS) that are assumed to be working in a cyber-physical environment. NCS are prone to anomalies both due to cyber and physical attacks and faults. Cyber-attacks being more hazardous given the cooperative nature of the NCS may lead to disastrous consequences and thus need to be detected as soon as they occur by all systems in the network. Our approach deals with two types of malicious attacks aimed at compromising the stability of the NCS: intrusion attacks/local malfunctions on individual systems and deception/cyber-attacks on the communication between the systems. In order to detect and identify such attacks under switching communication topologies, this paper proposes a new distributed methodology that solves global state estimation of the NCS where the aim is identifying anomalies in the networked system using residuals generated by monitoring agents such that coverage of the entire network is assured. A cascade of predefined-time sliding mode switched observers is introduced for each agent to achieve a fast estimate of the global state whereby the settling time is an a priori defined parameter independently of the initial conditions. Then, using the conventional consensus algorithm, a set of residuals are generated by the agents that is capable of detecting and isolating local intrusion attacks and communication cyber-attacks in the network using only locally exchanged information. In order to prove the effectiveness of the proposed method, the framework is tested for a velocity synchronization seeking network of mobile robots. Full article
(This article belongs to the Special Issue Emerging Trends and Approaches to Cyber Security)
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Open AccessEditor’s ChoiceCommunication
Effects of Annealing Atmosphere on Electrical Performance and Stability of High-Mobility Indium-Gallium-Tin Oxide Thin-Film Transistors
Electronics 2020, 9(11), 1875; https://doi.org/10.3390/electronics9111875 - 07 Nov 2020
Cited by 1
Abstract
In this study, we examined the effects of the annealing atmosphere on the electrical performance and stability of high-mobility indium-gallium-tin oxide (IGTO) thin-film transistors (TFTs). The annealing process was performed at a temperature of 180 °C under N2, O2, [...] Read more.
In this study, we examined the effects of the annealing atmosphere on the electrical performance and stability of high-mobility indium-gallium-tin oxide (IGTO) thin-film transistors (TFTs). The annealing process was performed at a temperature of 180 °C under N2, O2, or air atmosphere after the deposition of IGTO thin films by direct current magnetron sputtering. The field-effect mobility (μFE) of the N2- and O2-annealed IGTO TFTs was 26.6 cm2/V·s and 25.0 cm2/V·s, respectively; these values were higher than that of the air-annealed IGTO TFT (μFE = 23.5 cm2/V·s). Furthermore, the stability of the N2- and O2-annealed IGTO TFTs under the application of a positive bias stress (PBS) was greater than that of the air-annealed device. However, the N2-annealed IGTO TFT exhibited a larger threshold voltage shift under negative bias illumination stress (NBIS) compared with the O2- and air-annealed IGTO TFTs. The obtained results indicate that O2 gas is the most suitable environment for the heat treatment of IGTO TFTs to maximize their electrical properties and stability. The low electrical stability of the air-annealed IGTO TFT under PBS and the N2-annealed IGTO TFT under NBIS are primarily attributed to the high density of hydroxyl groups and oxygen vacancies in the channel layers, respectively. Full article
(This article belongs to the Special Issue Applications of Thin Films in Microelectronics)
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Open AccessEditor’s ChoiceArticle
A Compact 16 Channel Embedded System with High Dynamic Range Readout and Heater Management for Semiconducting Metal Oxide Gas Sensors
Electronics 2020, 9(11), 1855; https://doi.org/10.3390/electronics9111855 - 05 Nov 2020
Abstract
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only [...] Read more.
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only slightly, other types can react with a resistive change over a range of several decades. Therefore, a suitable readout circuit has to be able to capture all these resistive variations, requiring it to have a very large dynamic range. This work presents a compact embedded system that provides a full, high range input interface (readout and heater management) for MOX sensor operation. The system is modular and consists of a central mainboard that holds up to eight sensor-modules, each capable of supporting up to two MOX sensors, therefore supporting a total maximum of 16 different sensors. Its wide input range is archived using the resistance-to-time measurement method. The system is solely built with commercial off-the-shelf components and tested over a range spanning from 100 Ω to 5 GΩ (9.7 decades) with an average measurement error of 0.27% and a maximum error of 2.11%. The heater management uses a well-tested power-circuit and supports multiple modes of operation, hence enabling the system to be used in highly automated measurement applications. The experimental part of this work presents the results of an exemplary screening of 16 sensors, which was performed to evaluate the system’s performance. Full article
(This article belongs to the Section Computer Science & Engineering)
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Open AccessEditor’s ChoiceArticle
Microfluidic Approach for Lead Halide Perovskite Flexible Phototransistors
Electronics 2020, 9(11), 1852; https://doi.org/10.3390/electronics9111852 - 05 Nov 2020
Cited by 1
Abstract
Lead halide perovskites possess outstanding optical characteristics that can be employed in the fabrication of phototransistors. However, due to low current modulation at room temperature, sensitivity to the ambient environment, lack of patterning techniques and low carrier mobility of polycrystalline form, investigation in [...] Read more.
Lead halide perovskites possess outstanding optical characteristics that can be employed in the fabrication of phototransistors. However, due to low current modulation at room temperature, sensitivity to the ambient environment, lack of patterning techniques and low carrier mobility of polycrystalline form, investigation in perovskite phototransistors has been limited to rigid substrates such as silicon and glass to improve the film quality. Here, we report on room temperature current modulation in a methylammonium lead iodide perovskite (MAPbI3) flexible transistor made by an extremely cheap and facile fabrication process. The proposed phototransistor has the top-gate configuration with a lateral drain–channel–source structure. The device performed in the linear and saturation regions both in the dark and under white light in different current ranges according to the illumination conditions. The transistor showed p-type transport characteristics and the field effect mobility of the device was calculated to be ~1.7 cm2 V−1 s−1. This study is expected to contribute to the development of MAPbI3 flexible phototransistors. Full article
(This article belongs to the Special Issue Ultrasensitive Photodetectors and Applications)
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Open AccessEditor’s ChoiceArticle
A Latency-Insensitive Design Approach to Programmable FPGA-Based Real-Time Simulators
Electronics 2020, 9(11), 1838; https://doi.org/10.3390/electronics9111838 - 03 Nov 2020
Cited by 1
Abstract
This paper presents a methodology for the design of field-programmable gate array (FPGA)-based real-time simulators (RTSs) for power electronic circuits (PECs). The programmability of the simulator results from the use of an efficient and scalable overlay architecture (OA). The proposed OA relies on [...] Read more.
This paper presents a methodology for the design of field-programmable gate array (FPGA)-based real-time simulators (RTSs) for power electronic circuits (PECs). The programmability of the simulator results from the use of an efficient and scalable overlay architecture (OA). The proposed OA relies on a latency-insensitive design (LID) paradigm. LID consists of connecting small processing units that automatically synchronize and exchange data when appropriate. The use of such data-driven architecture aims to ease the design process while achieving a higher computational efficiency. The benefits of the proposed approach is evaluated by assessing the performance of the proposed solver in the simulation of a two-stage AC–AC power converter. The minimum achievable time-step and FPGA resource consumption for a wide range of power converter sizes is also evaluated. The proposed overlays are parametrizable in size, they are cost-effective, they provide sub-microsecond time-steps, and they offer a high computational performance with a reported peak performance of 300 GFLOPS. Full article
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Open AccessEditor’s ChoiceArticle
Comparing VR- and AR-Based Try-On Systems Using Personalized Avatars
Electronics 2020, 9(11), 1814; https://doi.org/10.3390/electronics9111814 - 02 Nov 2020
Abstract
Despite the convenience offered by e-commerce, online apparel shopping presents various product-related risks, as consumers can neither physically see nor try products on themselves. Augmented reality (AR) and virtual reality (VR) technologies have been used to improve the shopping online experience. Therefore, we [...] Read more.
Despite the convenience offered by e-commerce, online apparel shopping presents various product-related risks, as consumers can neither physically see nor try products on themselves. Augmented reality (AR) and virtual reality (VR) technologies have been used to improve the shopping online experience. Therefore, we propose an AR- and VR-based try-on system that provides users a novel shopping experience where they can view garments fitted onto their personalized virtual body. Recorded personalized motions are used to allow users to dynamically interact with their dressed virtual body in AR. We conducted two user studies to compare the different roles of VR- and AR-based try-ons and validate the impact of personalized motions on the virtual try-on experience. In the first user study, the mobile application with the AR- and VR-based try-on is compared to a traditional e-commerce interface. In the second user study, personalized avatars with pre-defined motion and personalized motion is compared to a personalized no-motion avatar with AR-based try-on. The result shows that AR- and VR-based try-ons can positively influence the shopping experience, compared with the traditional e-commerce interface. Overall, AR-based try-on provides a better and more realistic garment visualization than VR-based try-on. In addition, we found that personalized motions do not directly affect the user’s shopping experience. Full article
(This article belongs to the Special Issue Human Computer Interaction and Its Future)
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