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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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18 pages, 8929 KiB  
Article
Wind Turbine Operation Curves Modelling Techniques
by Davide Astolfi
Electronics 2021, 10(3), 269; https://doi.org/10.3390/electronics10030269 - 23 Jan 2021
Cited by 20 | Viewed by 4481
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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9 pages, 2451 KiB  
Article
Solar Energy Conversion and Storage Using a Photocatalytic Fuel Cell Combined with a Supercapacitor
by Tatiana Santos Andrade, Vassilios Dracopoulos and Panagiotis Lianos
Electronics 2021, 10(3), 273; https://doi.org/10.3390/electronics10030273 - 23 Jan 2021
Cited by 9 | Viewed by 3911
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
(This article belongs to the Special Issue Recent Advances in Nanoelectronics for Energy Conversion, Storage, and Saving)
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19 pages, 8688 KiB  
Article
Research on the Coordinated Control of Regenerative Braking System and ABS in Hybrid Electric Vehicle Based on Composite Structure Motor
by Qiwei Xu, Chuan Zhou, Hong Huang and Xuefeng Zhang
Electronics 2021, 10(3), 223; https://doi.org/10.3390/electronics10030223 - 20 Jan 2021
Cited by 20 | Viewed by 5180
Abstract
An antilock braking system (ABS) can ensure that the wheels are not locked during the braking process which is an important system to ensure the safety of braking. Regenerative braking is also a crucial system for hybrid vehicles and helps to improve the [...] Read more.
An antilock braking system (ABS) can ensure that the wheels are not locked during the braking process which is an important system to ensure the safety of braking. Regenerative braking is also a crucial system for hybrid vehicles and helps to improve the cruising range of the car. As such, the coordinated control of a braking system and an ABS is an important research direction. This paper researches the coordinated control of the regenerative braking system and the ABS in the hybrid vehicle based on the composite structure motor (CSM-HEV). Firstly, two new braking modes which are engine-motor coordinated braking (EMCB) and dual-motor braking (DMB) are proposed and the coordinated control model of regenerative braking and ABS is established. Then, for the purpose of optimal operating efficiency and guaranteeing the vehicle brake slip rate, a braking force distribution strategy based on predictive control algorithm is proposed. Finally, the Simulink model is established to simulate the control strategy. Results show that the slip rate can well track the target and ensure the efficient operation of the system. Compared with the normal braking mode, the braking energy recovery rate of EMCB is similar, but it can reduce the fuel loss of the engine during the braking process by 30.1%, DMB can improve the braking energy recovery efficiency by 16.78%, and the response time to track target slip is increased by 12 ms. Full article
(This article belongs to the Special Issue Emerging Trends in Control-Oriented Modeling of Hybrid Electric Vehicles in a Connected Framework)
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18 pages, 3416 KiB  
Article
NDF of Scattered Fields for Strip Geometries
by Ehsan Akbari Sekehravani, Giovanni Leone and Rocco Pierri
Electronics 2021, 10(2), 202; https://doi.org/10.3390/electronics10020202 - 17 Jan 2021
Cited by 13 | Viewed by 6235
Abstract
Solving inverse scattering problems by numerical methods requires investigating the number of independent pieces of information that can be reconstructed stably. To this end, we address the evaluation of the Number of Degrees of Freedom (NDF) of far-zone scattered fields for some strip [...] Read more.
Solving inverse scattering problems by numerical methods requires investigating the number of independent pieces of information that can be reconstructed stably. To this end, we address the evaluation of the Number of Degrees of Freedom (NDF) of far-zone scattered fields for some strip geometries under the first-order Born approximation. The analysis is performed by employing the Singular Value Decomposition (SVD) of the scattering operator in the two-dimensional scalar geometry of one or more strips illuminated by a TM polarized plane wave. It is known that investigating the scattering scene at different incident plane waves (multi-view configuration) enhances the NDF. Therefore we mean to examine the minimum number of incident plane waves providing the NDF of the scattered fields both by theoretical estimations and numerical verifications. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Microwave and Wireless Communications)
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14 pages, 3227 KiB  
Article
Device and Circuit Exploration of Multi-Nanosheet Transistor for Sub-3 nm Technology Node
by Yoongeun Seon, Jeesoo Chang, Changhyun Yoo and Jongwook Jeon
Electronics 2021, 10(2), 180; https://doi.org/10.3390/electronics10020180 - 15 Jan 2021
Cited by 29 | Viewed by 8513
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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29 pages, 2701 KiB  
Article
Multiclass ECG Signal Analysis Using Global Average-Based 2-D Convolutional Neural Network Modeling
by Muhammad Wasimuddin, Khaled Elleithy, Abdelshakour Abuzneid, Miad Faezipour and Omar Abuzaghleh
Electronics 2021, 10(2), 170; https://doi.org/10.3390/electronics10020170 - 14 Jan 2021
Cited by 35 | Viewed by 6790
Abstract
Cardiovascular diseases have been reported to be the leading cause of mortality across the globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of main interest among researchers, as its early diagnosis can prevent life threatening cardiac conditions and [...] Read more.
Cardiovascular diseases have been reported to be the leading cause of mortality across the globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of main interest among researchers, as its early diagnosis can prevent life threatening cardiac conditions and potentially save human lives. Analyzing the Electrocardiogram (ECG) can provide valuable diagnostic information to detect different types of cardiac arrhythmia. Real-time ECG monitoring systems with advanced machine learning methods provide information about the health status in real-time and have improved user’s experience. However, advanced machine learning methods have put a burden on portable and wearable devices due to their high computing requirements. We present an improved, less complex Convolutional Neural Network (CNN)-based classifier model that identifies multiple arrhythmia types using the two-dimensional image of the ECG wave in real-time. The proposed model is presented as a three-layer ECG signal analysis model that can potentially be adopted in real-time portable and wearable monitoring devices. We have designed, implemented, and simulated the proposed CNN network using Matlab. We also present the hardware implementation of the proposed method to validate its adaptability in real-time wearable systems. The European ST-T database recorded with single lead L3 is used to validate the CNN classifier and achieved an accuracy of 99.23%, outperforming most existing solutions. Full article
(This article belongs to the Special Issue Biomedical Signal Processing)
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16 pages, 8431 KiB  
Article
A Design Method of Compensation Circuit for High-Power Dynamic Capacitive Power Transfer System Considering Coupler Voltage Distribution for Railway Applications
by Jianying Liang, Donghua Wu and Jin Yu
Electronics 2021, 10(2), 153; https://doi.org/10.3390/electronics10020153 - 12 Jan 2021
Cited by 13 | Viewed by 3986
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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21 pages, 7753 KiB  
Article
Design of Integrated Autonomous Driving Control System That Incorporates Chassis Controllers for Improving Path Tracking Performance and Vehicle Stability
by Taewon Ahn, Yongki Lee and Kihong Park
Electronics 2021, 10(2), 144; https://doi.org/10.3390/electronics10020144 - 11 Jan 2021
Cited by 35 | Viewed by 6459
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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11 pages, 3220 KiB  
Article
Compact Continuous Time Common-Mode Feedback Circuit for Low-Power, Area-Constrained Neural Recording Amplifiers
by Joon Young Kwak and Sung-Yun Park
Electronics 2021, 10(2), 145; https://doi.org/10.3390/electronics10020145 - 11 Jan 2021
Cited by 6 | Viewed by 8285
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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23 pages, 22731 KiB  
Article
AC Current Ripple Harmonic Pollution in Three-Phase Four-Leg Active Front-End AC/DC Converter for On-Board EV Chargers
by Aleksandr Viatkin, Riccardo Mandrioli, Manel Hammami, Mattia Ricco and Gabriele Grandi
Electronics 2021, 10(2), 116; https://doi.org/10.3390/electronics10020116 - 7 Jan 2021
Cited by 6 | Viewed by 4165
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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15 pages, 7254 KiB  
Article
SmartFit: Smartphone Application for Garment Fit Detection
by Kamrul H. Foysal, Hyo Jung Chang, Francine Bruess and Jo Woon Chong
Electronics 2021, 10(1), 97; https://doi.org/10.3390/electronics10010097 - 5 Jan 2021
Cited by 18 | Viewed by 6468
Abstract
The apparel e-commerce industry is growing day by day. In recent times, consumers are particularly interested in an easy and time-saving way of online apparel shopping. In addition, the COVID-19 pandemic has generated more need for an effective and convenient online shopping solution [...] Read more.
The apparel e-commerce industry is growing day by day. In recent times, consumers are particularly interested in an easy and time-saving way of online apparel shopping. In addition, the COVID-19 pandemic has generated more need for an effective and convenient online shopping solution for consumers. However, online shopping, particularly online apparel shopping, has several challenges for consumers. These issues include sizing, fit, return, and cost concerns. Especially, the fit issue is one of the cardinal factors causing hesitance and drawback in online apparel purchases. The conventional method of clothing fit detection based on body shapes relies upon manual body measurements. Since no convenient and easy-to-use method has been proposed for body shape detection, we propose an interactive smartphone application, “SmartFit”, that will provide the optimal fitting clothing recommendation to the consumer by detecting their body shape. This optimal recommendation is provided by using image processing and machine learning that are solely dependent on smartphone images. Our preliminary assessment of the developed model shows an accuracy of 87.50% for body shape detection, producing a promising solution to the fit detection problem persisting in the digital apparel market. Full article
(This article belongs to the Special Issue Smart Bioelectronics and Wearable Systems)
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20 pages, 3923 KiB  
Article
Carbon Nanotube Field Effect Transistor (CNTFET) and Resistive Random Access Memory (RRAM) Based Ternary Combinational Logic Circuits
by Furqan Zahoor, Fawnizu Azmadi Hussin, Farooq Ahmad Khanday, Mohamad Radzi Ahmad, Illani Mohd Nawi, Chia Yee Ooi and Fakhrul Zaman Rokhani
Electronics 2021, 10(1), 79; https://doi.org/10.3390/electronics10010079 - 4 Jan 2021
Cited by 61 | Viewed by 10270
Abstract
The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital systems. Carbon nanotube field effect transistors (CNTFETs) [...] Read more.
The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital systems. Carbon nanotube field effect transistors (CNTFETs) have shown great promise for design of MVL based circuits, due to the fact that the scalable threshold voltage of CNTFETs can be utilized easily for the multiple voltage designs. In addition, resistive random access memory (RRAM) is also a feasible option for the design of MVL circuits, owing to its multilevel cell capability that enables the storage of multiple resistance states within a single cell. In this manuscript, a design approach for ternary combinational logic circuits while using CNTFETs and RRAM is presented. The designs of ternary half adder, ternary half subtractor, ternary full adder, and ternary full subtractor are evaluated while using Synopsis HSPICE simulation software with standard 32 nm CNTFET technology under different operating conditions, including different supply voltages, output load variation, and different operating temperatures. Finally, the proposed designs are compared with the state-of-the-art ternary designs. Based on the obtained simulation results, the proposed designs show a significant reduction in the transistor count, decreased cell area, and lower power consumption. In addition, due to the participation of RRAM, the proposed designs have advantages in terms of non-volatility. Full article
(This article belongs to the Special Issue RRAM Devices: Materials, Designs, and Properties)
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19 pages, 972 KiB  
Review
A Review of Plant Phenotypic Image Recognition Technology Based on Deep Learning
by Jianbin Xiong, Dezheng Yu, Shuangyin Liu, Lei Shu, Xiaochan Wang and Zhaoke Liu
Electronics 2021, 10(1), 81; https://doi.org/10.3390/electronics10010081 - 4 Jan 2021
Cited by 108 | Viewed by 10211
Abstract
Plant phenotypic image recognition (PPIR) is an important branch of smart agriculture. In recent years, deep learning has achieved significant breakthroughs in image recognition. Consequently, PPIR technology that is based on deep learning is becoming increasingly popular. First, this paper introduces the development [...] Read more.
Plant phenotypic image recognition (PPIR) is an important branch of smart agriculture. In recent years, deep learning has achieved significant breakthroughs in image recognition. Consequently, PPIR technology that is based on deep learning is becoming increasingly popular. First, this paper introduces the development and application of PPIR technology, followed by its classification and analysis. Second, it presents the theory of four types of deep learning methods and their applications in PPIR. These methods include the convolutional neural network, deep belief network, recurrent neural network, and stacked autoencoder, and they are applied to identify plant species, diagnose plant diseases, etc. Finally, the difficulties and challenges of deep learning in PPIR are discussed. Full article
(This article belongs to the Collection Electronics for Agriculture)
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31 pages, 6703 KiB  
Article
A Hybrid Prognostics Deep Learning Model for Remaining Useful Life Prediction
by Zhiyuan Xie, Shichang Du, Jun Lv, Yafei Deng and Shiyao Jia
Electronics 2021, 10(1), 39; https://doi.org/10.3390/electronics10010039 - 29 Dec 2020
Cited by 29 | Viewed by 5510
Abstract
Remaining Useful Life (RUL) prediction is significant in indicating the health status of the sophisticated equipment, and it requires historical data because of its complexity. The number and complexity of such environmental parameters as vibration and temperature can cause non-linear states of data, [...] Read more.
Remaining Useful Life (RUL) prediction is significant in indicating the health status of the sophisticated equipment, and it requires historical data because of its complexity. The number and complexity of such environmental parameters as vibration and temperature can cause non-linear states of data, making prediction tremendously difficult. Conventional machine learning models such as support vector machine (SVM), random forest, and back propagation neural network (BPNN), however, have limited capacity to predict accurately. In this paper, a two-phase deep-learning-model attention-convolutional forget-gate recurrent network (AM-ConvFGRNET) for RUL prediction is proposed. The first phase, forget-gate convolutional recurrent network (ConvFGRNET) is proposed based on a one-dimensional analog long short-term memory (LSTM), which removes all the gates except the forget gate and uses chrono-initialized biases. The second phase is the attention mechanism, which ensures the model to extract more specific features for generating an output, compensating the drawbacks of the FGRNET that it is a black box model and improving the interpretability. The performance and effectiveness of AM-ConvFGRNET for RUL prediction is validated by comparing it with other machine learning methods and deep learning methods on the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dataset and a dataset of ball screw experiment. Full article
(This article belongs to the Special Issue Applications and Methodologies of Artificial Intelligence in Big Data Analysis)
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21 pages, 1803 KiB  
Article
A Procedure for Tracing Supply Chains for Perishable Food Based on Blockchain, Machine Learning and Fuzzy Logic
by Zeinab Shahbazi and Yung-Cheol Byun
Electronics 2021, 10(1), 41; https://doi.org/10.3390/electronics10010041 - 29 Dec 2020
Cited by 72 | Viewed by 9353
Abstract
One of the essential points of food manufacturing in the industry and shelf life of the products is to improve the food traceability system. In recent years, the food traceability mechanism has become one of the emerging blockchain applications in order to improve [...] Read more.
One of the essential points of food manufacturing in the industry and shelf life of the products is to improve the food traceability system. In recent years, the food traceability mechanism has become one of the emerging blockchain applications in order to improve the anti-counterfeiting area’s quality. Many food manufacturing systems have a low level of readability, scalability, and data accuracy. Similarly, this process is complicated in the supply chain and needs a lot of time for processing. The blockchain system creates a new ontology in the traceability system supply chain to deal with these issues. In this paper, a blockchain machine learning-based food traceability system (BMLFTS) is proposed in order to combine the new extension in blockchain, Machine Learning technology (ML), and fuzzy logic traceability system that is based on the shelf life management system for manipulating perishable food. The blockchain technology in the proposed system has been developed in order to address light-weight, evaporation, warehouse transactions, or shipping time. The blockchain data flow is designed to show the extension of ML at the level of food traceability. Finally, reliable and accurate data are used in a supply chain to improve shelf life. Full article
(This article belongs to the Section Computer Science & Engineering)
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9 pages, 2763 KiB  
Article
LTPS TFTs with an Amorphous Silicon Buffer Layer and Source/Drain Extension
by Hye In Kim, Jung Min Sung, Hyung Uk Cho, Yong Jo Kim, Young Gwan Park and Woo Young Choi
Electronics 2021, 10(1), 29; https://doi.org/10.3390/electronics10010029 - 28 Dec 2020
Cited by 9 | Viewed by 8143
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
(This article belongs to the Special Issue Reliability Assessment and Modeling of Optical and Semiconductor Devices)
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26 pages, 2892 KiB  
Article
A Survey of Candidate Waveforms for beyond 5G Systems
by Filipe Conceição, Marco Gomes, Vitor Silva, Rui Dinis, Adão Silva and Daniel Castanheira
Electronics 2021, 10(1), 21; https://doi.org/10.3390/electronics10010021 - 25 Dec 2020
Cited by 30 | Viewed by 4983
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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12 pages, 6124 KiB  
Article
Ultra-Wideband MIMO Array for Penetrating Lunar Regolith Structures on the Chang’e-5 Lander
by Wei Lu, Yuxi Li, Yicai Ji, Chuanjun Tang, Bin Zhou and Guangyou Fang
Electronics 2021, 10(1), 8; https://doi.org/10.3390/electronics10010008 - 23 Dec 2020
Cited by 7 | Viewed by 2894
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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19 pages, 644 KiB  
Article
A Public Platform for Virtual IoT-Based Monitoring and Tracking of COVID-19
by Younchan Jung and Ronnel Agulto
Electronics 2021, 10(1), 12; https://doi.org/10.3390/electronics10010012 - 23 Dec 2020
Cited by 20 | Viewed by 4810
Abstract
The world is developing an app that alerts my smartphone when a COVID-19 (COrona VIrus Disease 19) confirmed case comes near me. However, regardless of what will be put to practical use first, the COVID-19 tracking system should satisfy the issues of legalization [...] Read more.
The world is developing an app that alerts my smartphone when a COVID-19 (COrona VIrus Disease 19) confirmed case comes near me. However, regardless of what will be put to practical use first, the COVID-19 tracking system should satisfy the issues of legalization of location tracking and scalability as a public platform used by the world. Additional problems need solutions related to real-time authentication for information gathering, blind naming and privacy of tracked persons, and quality of service on the Query/Reply procedure. This paper proposes the Software-Defined Networking Controller-centric global public platform to monitor and track information for the COVID-19 relevant people and provide real-time information disclosure services to world-wide Centers for Disease Control and Prevention (CDCs) and regular users. The CDC manages a list of people who needs to be monitored related to the COVID-19 and forcibly installs COVID-19 virtual Internet of Things (vIoT) nodes in the form of applications on their smartphones. In addition to these nodes, the vIoT support nodes also engage as information providers to improve the quality of information services. The design of our platform aims to ensure confidentiality and authentication services giving individually different secret keys. In addition, our platform meets system scalability and reduces Query/Reply latency, where the platform accommodates a large number of world-wide CDCs and persons in control per CDC. Full article
(This article belongs to the Special Issue Internet of Things (IoT)-Based Wireless Health: Enabling Technologies and Applications)
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23 pages, 1281 KiB  
Article
CNN2Gate: An Implementation of Convolutional Neural Networks Inference on FPGAs with Automated Design Space Exploration
by Alireza Ghaffari and Yvon Savaria
Electronics 2020, 9(12), 2200; https://doi.org/10.3390/electronics9122200 - 21 Dec 2020
Cited by 24 | Viewed by 5059
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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10 pages, 3058 KiB  
Article
Electrical Performance and Stability Improvements of High-Mobility Indium–Gallium–Tin Oxide Thin-Film Transistors Using an Oxidized Aluminum Capping Layer of Optimal Thickness
by Hyun-Seok Cha, Hwan-Seok Jeong, Seong-Hyun Hwang, Dong-Ho Lee and Hyuck-In Kwon
Electronics 2020, 9(12), 2196; https://doi.org/10.3390/electronics9122196 - 20 Dec 2020
Cited by 14 | Viewed by 4276
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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15 pages, 1352 KiB  
Article
A Compact and Robust Technique for the Modeling and Parameter Extraction of Carbon Nanotube Field Effect Transistors
by Laura Falaschetti, Davide Mencarelli, Nicola Pelagalli, Paolo Crippa, Giorgio Biagetti, Claudio Turchetti, George Deligeorgis and Luca Pierantoni
Electronics 2020, 9(12), 2199; https://doi.org/10.3390/electronics9122199 - 20 Dec 2020
Cited by 4 | Viewed by 4032
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)
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17 pages, 1664 KiB  
Article
Wavelet Transform Analysis of Heart Rate to Assess Recovery Time for Long Distance Runners
by Grzegorz Redlarski, Janusz Siebert, Marek Krawczuk, Arkadiusz Zak, Ludmila Danilowicz-Szymanowicz, Lukasz Dolinski, Piotr Gutknecht, Bartosz Trzeciak, Wojciech Ratkowski and Aleksander Palkowski
Electronics 2020, 9(12), 2189; https://doi.org/10.3390/electronics9122189 - 18 Dec 2020
Cited by 2 | Viewed by 3470
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
(This article belongs to the Special Issue New Challenges in Biomedical Signal Processing: Computational Theory and Applications)
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13 pages, 8656 KiB  
Article
Event-Focused Digital Control to Keep High Efficiency in a Wide Power Range in a SiC-Based Synchronous DC/DC Boost Converter
by María R. Rogina, Alberto Rodríguez, Aitor Vázquez, Diego G. Lamar and Marta M. Hernando
Electronics 2020, 9(12), 2154; https://doi.org/10.3390/electronics9122154 - 16 Dec 2020
Cited by 4 | Viewed by 2348
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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38 pages, 2460 KiB  
Review
Visible Light Communications for Industrial Applications—Challenges and Potentials
by Yousef Almadani, David Plets, Sander Bastiaens, Wout Joseph, Muhammad Ijaz, Zabih Ghassemlooy and Sujan Rajbhandari
Electronics 2020, 9(12), 2157; https://doi.org/10.3390/electronics9122157 - 16 Dec 2020
Cited by 77 | Viewed by 11877
Abstract
Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing [...] Read more.
Visible Light Communication (VLC) is a short-range optical wireless communication technology that has been gaining attention due to its potential to offload heavy data traffic from the congested radio wireless spectrum. At the same time, wireless communications are becoming crucial to smart manufacturing within the scope of Industry 4.0. Industry 4.0 is a developing trend of high-speed data exchange in automation for manufacturing technologies and is referred to as the fourth industrial revolution. This trend requires fast, reliable, low-latency, and cost-effective data transmissions with fast synchronizations to ensure smooth operations for various processes. VLC is capable of providing reliable, low-latency, and secure connections that do not penetrate walls and is immune to electromagnetic interference. As such, this paper aims to show the potential of VLC for industrial wireless applications by examining the latest research work in VLC systems. This work also highlights and classifies challenges that might arise with the applicability of VLC and visible light positioning (VLP) systems in these settings. Given the previous work performed in these areas, and the major ongoing experimental projects looking into the use of VLC systems for industrial applications, the use of VLC and VLP systems for industrial applications shows promising potential. Full article
(This article belongs to the Special Issue New Challenges in Wireless and Free Space Optical Communications)
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26 pages, 23395 KiB  
Article
An Efficient Deep-Learning-Based Detection and Classification System for Cyber-Attacks in IoT Communication Networks
by Qasem Abu Al-Haija and Saleh Zein-Sabatto
Electronics 2020, 9(12), 2152; https://doi.org/10.3390/electronics9122152 - 15 Dec 2020
Cited by 130 | Viewed by 10601
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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12 pages, 3785 KiB  
Article
Low Voltage Time-Based Matrix Multiplier-and-Accumulator for Neural Computing System
by Sungjin Hong, Heechai Kang, Jusung Kim and Kunhee Cho
Electronics 2020, 9(12), 2138; https://doi.org/10.3390/electronics9122138 - 14 Dec 2020
Cited by 6 | Viewed by 3846
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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16 pages, 5415 KiB  
Article
A Novel Printable Tag of M-Shaped Strips for Chipless Radio-Frequency Identification in IoT Applications
by Wazie M. Abdulkawi, Khaled Issa, Abdel-Fattah A. Sheta and Saleh A. Alshebeili
Electronics 2020, 9(12), 2116; https://doi.org/10.3390/electronics9122116 - 11 Dec 2020
Cited by 11 | Viewed by 3064
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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15 pages, 8003 KiB  
Article
A Comparative Analysis between Standard and mm-Wave Optimized BEOL in a Nanoscale CMOS Technology
by Egidio Ragonese, Claudio Nocera, Andrea Cavarra, Giuseppe Papotto, Simone Spataro and Giuseppe Palmisano
Electronics 2020, 9(12), 2124; https://doi.org/10.3390/electronics9122124 - 11 Dec 2020
Cited by 7 | Viewed by 3061
Abstract
This paper presents an extensive comparison of two 28-nm CMOS technologies, i.e., standard and mm-wave-optimized (i.e., thick metals and intermetal oxides) back-end-of-line (BEOL). The proposed comparison is carried out at both component and circuit level by means of a quantitative analysis of the [...] Read more.
This paper presents an extensive comparison of two 28-nm CMOS technologies, i.e., standard and mm-wave-optimized (i.e., thick metals and intermetal oxides) back-end-of-line (BEOL). The proposed comparison is carried out at both component and circuit level by means of a quantitative analysis of the actual performance improvements due to the adoption of a mm-wave-optimized BEOL. To this end, stand-alone transformer performance is first evaluated and then a complete mm-wave macroblock is investigated. A 77-GHz down-converter for frequency modulated continuous wave (FMCW) long-range/medium range (LR/MR) radar applications is exploited as a testbench. For the first time, it is demonstrated that thicker metals and intermetal oxides do not guarantee significant improvements at mm-wave frequencies and a standard (low-cost) BEOL is competitive in comparison with more complex (expensive) ones. Full article
(This article belongs to the Special Issue RF/Mm-Wave Circuits Design and Applications)
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11 pages, 3459 KiB  
Article
A Radio Frequency Magnetoelectric Antenna Prototyping Platform for Neural Activity Monitoring Devices with Sensing and Energy Harvesting Capabilities
by Diptashree Das, Mehdi Nasrollahpour, Ziyue Xu, Mohsen Zaeimbashi, Isabel Martos-Repath, Ankit Mittal, Adam Khalifa, Sydney S. Cash, Aatmesh Shrivastava, Nian X. Sun and Marvin Onabajo
Electronics 2020, 9(12), 2123; https://doi.org/10.3390/electronics9122123 - 11 Dec 2020
Cited by 13 | Viewed by 4297
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
(This article belongs to the Special Issue Integrated Electronic Circuits and Systems for Unobtrusive Biomedical Sensing)
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15 pages, 10705 KiB  
Article
Ka-Band Diplexer for 5G mmWave Applications in Inverted Microstrip Gap Waveguide Technology
by Carlos Sanchez-Cabello, Luis Fernando Herran and Eva Rajo-Iglesias
Electronics 2020, 9(12), 2094; https://doi.org/10.3390/electronics9122094 - 8 Dec 2020
Cited by 16 | Viewed by 5630
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 Collection Millimeter and Terahertz Wireless Communications)
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22 pages, 769 KiB  
Review
Data Quality and Trust: Review of Challenges and Opportunities for Data Sharing in IoT
by John Byabazaire, Gregory O’Hare and Declan Delaney
Electronics 2020, 9(12), 2083; https://doi.org/10.3390/electronics9122083 - 7 Dec 2020
Cited by 51 | Viewed by 8224
Abstract
Existing research recognizes the critical role of quality data in the current big-data and Internet of Things (IoT) era. Quality data has a direct impact on model results and hence business decisions. The growth in the number of IoT-connected devices makes it hard [...] Read more.
Existing research recognizes the critical role of quality data in the current big-data and Internet of Things (IoT) era. Quality data has a direct impact on model results and hence business decisions. The growth in the number of IoT-connected devices makes it hard to access data quality using traditional assessments methods. This is exacerbated by the need to share data across different IoT domains as it increases the heterogeneity of the data. Data-shared IoT defines a new perspective of IoT applications which benefit from sharing data among different domains of IoT to create new use-case applications. For example, sharing data between smart transport and smart industry can lead to other use-case applications such as intelligent logistics management and warehouse management. The benefits of such applications, however, can only be achieved if the shared data is of acceptable quality. There are three main practices in data quality (DQ) determination approaches that are restricting their effective use in data-shared platforms: (1) most DQ techniques validate test data against a known quantity considered to be a reference; a gold reference. (2) narrow sets of static metrics are used to describe the quality. Each consumer uses these metrics in similar ways. (3) data quality is evaluated in isolated stages throughout the processing pipeline. Data-shared IoT presents unique challenges; (1) each application and use-case in shared IoT has a unique description of data quality and requires a different set of metrics. This leads to an extensive list of DQ dimensions which are difficult to implement in real-world applications. (2) most data in IoT scenarios does not have a gold reference. (3) factors endangering DQ in shared IoT exist throughout the entire big-data model from data collection to data visualization, and data use. This paper aims to describe data-shared IoT and shared data pools while highlighting the importance of sharing quality data across various domains. The article examines how we can use trust as a measure of quality in data-shared IoT. We conclude that researchers can combine such trust-based techniques with blockchain for secure end-to-end data quality assessment. Full article
(This article belongs to the Special Issue Emerging Internet of Things Solutions and Technologies)
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34 pages, 1150 KiB  
Review
Automated Driving: A Literature Review of the Take over Request in Conditional Automation
by Walter Morales-Alvarez, Oscar Sipele, Régis Léberon, Hadj Hamma Tadjine and Cristina Olaverri-Monreal
Electronics 2020, 9(12), 2087; https://doi.org/10.3390/electronics9122087 - 7 Dec 2020
Cited by 105 | Viewed by 11857
Abstract
In conditional automation (level 3), human drivers can hand over the Driving Dynamic Task (DDT) to the Automated Driving System (ADS) and only be ready to resume control in emergency situations, allowing them to be engaged in non-driving related tasks (NDRT) whilst the [...] Read more.
In conditional automation (level 3), human drivers can hand over the Driving Dynamic Task (DDT) to the Automated Driving System (ADS) and only be ready to resume control in emergency situations, allowing them to be engaged in non-driving related tasks (NDRT) whilst the vehicle operates within its Operational Design Domain (ODD). Outside the ODD, a safe transition process from the ADS engaged mode to manual driving should be initiated by the system through the issue of an appropriate Take Over Request (TOR). In this case, the driver’s state plays a fundamental role, as a low attention level might increase driver reaction time to take over control of the vehicle. This paper summarizes and analyzes previously published works in the field of conditional automation and the TOR process. It introduces the topic in the appropriate context describing as well a variety of concerns that are associated with the TOR. It also provides theoretical foundations on implemented designs, and report on concrete examples that are targeted towards designers and the general public. Moreover, it compiles guidelines and standards related to automation in driving and highlights the research gaps that need to be addressed in future research, discussing also approaches and limitations and providing conclusions. Full article
(This article belongs to the Special Issue Autonomous Vehicles Technology)
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21 pages, 10292 KiB  
Article
Signal Transformations for Analysis of Supraharmonic EMI Caused by Switched-Mode Power Supplies
by Leonardo Sandrolini and Andrea Mariscotti
Electronics 2020, 9(12), 2088; https://doi.org/10.3390/electronics9122088 - 7 Dec 2020
Cited by 17 | Viewed by 3238
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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22 pages, 5298 KiB  
Article
A Comparative Study of Stochastic Model Predictive Controllers
by Edwin González, Javier Sanchis, Sergio García-Nieto and José Salcedo
Electronics 2020, 9(12), 2078; https://doi.org/10.3390/electronics9122078 - 6 Dec 2020
Cited by 18 | Viewed by 5060
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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37 pages, 7546 KiB  
Review
Enhance Reliability of Semiconductor Devices in Power Converters
by Minh Hoang Nguyen and Sangshin Kwak
Electronics 2020, 9(12), 2068; https://doi.org/10.3390/electronics9122068 - 4 Dec 2020
Cited by 45 | Viewed by 8976
Abstract
As one of the most vulnerable components to temperature and temperature cycling conditions in power electronics converter systems in these application fields as wind power, electric vehicles, drive system, etc., power semiconductor devices draw great concern in terms of reliability. Owing to the [...] Read more.
As one of the most vulnerable components to temperature and temperature cycling conditions in power electronics converter systems in these application fields as wind power, electric vehicles, drive system, etc., power semiconductor devices draw great concern in terms of reliability. Owing to the wide utilization of power semiconductor devices in various power applications, especially insulated gate bipolar transistors (IGBTs), power semiconductor devices have been studied extensively regarding increasing reliability methods. This study comparatively reviews recent advances in the area of reliability research for power semiconductor devices, including condition monitoring (CM), active thermal control (ATC), and remaining useful lifetime (RUL) estimation techniques. Different from previous review studies, this technical review is carried out with the aim of providing a comprehensive overview of the correlation between various enhancing reliability techniques and discussing the corresponding merits and demerits by using 144 related up-to-date papers. The structure and failure mechanism of power semiconductor devices are first investigated. Different failure indicators and recent associated CM techniques are then compared. The ATC approaches following the type of converter systems are further summarized. Furthermore, RUL estimation techniques are surveyed. This paper concludes with summarized challenges for future research opportunities regarding reliability improvement. Full article
(This article belongs to the Special Issue State-of-the-art Power Electronics in Korea)
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13 pages, 3969 KiB  
Article
Feasibility of Harvesting Solar Energy for Self-Powered Environmental Wireless Sensor Nodes
by Yuyang Li, Ehab A. Hamed, Xincheng Zhang, Daniel Luna, Jeen-Shang Lin, Xu Liang and Inhee Lee
Electronics 2020, 9(12), 2058; https://doi.org/10.3390/electronics9122058 - 3 Dec 2020
Cited by 18 | Viewed by 4477
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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16 pages, 9727 KiB  
Article
One-Cycle Zero-Integral-Error Current Control for Shunt Active Power Filters
by Salvador Orts-Grau, Pedro Balaguer-Herrero, Jose Carlos Alfonso-Gil, Camilo I. Martínez-Márquez, Francisco J. Gimeno-Sales and Salvador Seguí-Chilet
Electronics 2020, 9(12), 2008; https://doi.org/10.3390/electronics9122008 - 26 Nov 2020
Cited by 5 | Viewed by 2265
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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11 pages, 5872 KiB  
Article
A Fast Steering Mirror Using a Compact Magnetic Suspension and Voice Coil Motors for Observation Satellites
by Tadahiko Shinshi, Daisuke Shimizu, Kazuhide Kodeki and Kazuhiko Fukushima
Electronics 2020, 9(12), 1997; https://doi.org/10.3390/electronics9121997 - 25 Nov 2020
Cited by 25 | Viewed by 7378
Abstract
Fast steering mirrors (FSMs) are used to correct images observed by satellites. FSMs need to have large apertures and realize high precision and the positioning of the mirror in the tip-tilt and axial directions needs to be highly precise and highly responsive in [...] Read more.
Fast steering mirrors (FSMs) are used to correct images observed by satellites. FSMs need to have large apertures and realize high precision and the positioning of the mirror in the tip-tilt and axial directions needs to be highly precise and highly responsive in order to capture large-scale, high-resolution images. An FSM with a large-diameter mirror supported by a compact magnetic suspension and driven by long-stroke voice coil motors (VCMs) is proposed in this paper. The magnetic suspension and VCM actuators enable the mirror to be highly responsive and to have long-range movement in the tip-tilt and axial directions without friction and wear. The magnetic suspension is a hybrid that has active control in the lateral directions and passive support in the tip-tilt and axial directions. An experimental FSM with an 80 mm diameter dummy mirror was fabricated and tested. The mirror’s driving ranges in the tip-tilt and axial directions were ±20 mrad and ±500 μm, respectively. Furthermore, the servo bandwidths in the tip-tilt and axial directions were more than 1 kHz and 200 Hz, respectively. Full article
(This article belongs to the Special Issue Advanced Modelling and Control of Complex Nonlinear Mechatronic Systems)
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17 pages, 7793 KiB  
Article
Recognition of Drivers’ Activity Based on 1D Convolutional Neural Network
by Rafał J. Doniec, Szymon Sieciński, Konrad M. Duraj, Natalia J. Piaseczna, Katarzyna Mocny-Pachońska and Ewaryst J. Tkacz
Electronics 2020, 9(12), 2002; https://doi.org/10.3390/electronics9122002 - 25 Nov 2020
Cited by 18 | Viewed by 3784
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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30 pages, 2658 KiB  
Review
A Review on Deep Learning-Based Approaches for Automatic Sonar Target Recognition
by Dhiraj Neupane and Jongwon Seok
Electronics 2020, 9(11), 1972; https://doi.org/10.3390/electronics9111972 - 22 Nov 2020
Cited by 126 | Viewed by 20115
Abstract
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement and study of acoustic sources in the underwater atmosphere. With [...] Read more.
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement and study of acoustic sources in the underwater atmosphere. With the rapid development in science and technology, the advancement in sonar systems has increased, resulting in a decrement in underwater casualties. The sonar signal processing and automatic target recognition using sonar signals or imagery is itself a challenging process. Meanwhile, highly advanced data-driven machine-learning and deep learning-based methods are being implemented for acquiring several types of information from underwater sound data. This paper reviews the recent sonar automatic target recognition, tracking, or detection works using deep learning algorithms. A thorough study of the available works is done, and the operating procedure, results, and other necessary details regarding the data acquisition process, the dataset used, and the information regarding hyper-parameters is presented in this article. This paper will be of great assistance for upcoming scholars to start their work on sonar automatic target recognition. Full article
(This article belongs to the Section Artificial Intelligence)
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14 pages, 710 KiB  
Article
Wind Energy Harnessing in a Railway Infrastructure: Converter Topology and Control Proposal
by Oier Oñederra, Francisco Javier Asensio, Gaizka Saldaña, José Ignacio San Martín and Inmaculada Zamora
Electronics 2020, 9(11), 1943; https://doi.org/10.3390/electronics9111943 - 18 Nov 2020
Cited by 11 | Viewed by 5863
Abstract
Long distances in the vicinities of railways are not exploited in terms of wind energy. This paper presents a scalable power electronics approach, aimed to harness the wind potential in a railway infrastructure. The key aspect of this proposal relies on both using [...] Read more.
Long distances in the vicinities of railways are not exploited in terms of wind energy. This paper presents a scalable power electronics approach, aimed to harness the wind potential in a railway infrastructure. The key aspect of this proposal relies on both using the wind energy in the location, and the displaced air mass during the movement of a train along the railway, in order to produce electrical energy. Vertical Axis Wind Turbines (VAWT) are used in order to take advantage of the wind power, and widely used and well-known power converter techniques to accomplish the goal, showing MPPT techniques, parallelization of converters and power delivery with a Solid State Transformer (SST). Results are shown according simulations of the whole system, with and without train activity, resulting that 30.6 MWh of the energy could be generated without the train, and the energy generated with the assistance of the train could reach 32.3 MWh a year. Concluding that almost the 10% of the energy could be provided by the assistance of the train. Full article
(This article belongs to the Special Issue Wind Turbine Power Systems)
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20 pages, 1723 KiB  
Article
A Distributed Observer-Based Cyber-Attack Identification Scheme in Cooperative Networked Systems under Switching Communication Topologies
by Anass Taoufik, Michael Defoort, Krishna Busawon, Laurent Dala and Mohamed Djemai
Electronics 2020, 9(11), 1912; https://doi.org/10.3390/electronics9111912 - 13 Nov 2020
Cited by 6 | Viewed by 2778
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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10 pages, 1698 KiB  
Communication
Effects of Annealing Atmosphere on Electrical Performance and Stability of High-Mobility Indium-Gallium-Tin Oxide Thin-Film Transistors
by Hwan-Seok Jeong, Hyun Seok Cha, Seong Hyun Hwang and Hyuck-In Kwon
Electronics 2020, 9(11), 1875; https://doi.org/10.3390/electronics9111875 - 7 Nov 2020
Cited by 17 | Viewed by 4995
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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9 pages, 2546 KiB  
Article
Microfluidic Approach for Lead Halide Perovskite Flexible Phototransistors
by Fatemeh Khorramshahi and Arash Takshi
Electronics 2020, 9(11), 1852; https://doi.org/10.3390/electronics9111852 - 5 Nov 2020
Cited by 7 | Viewed by 3749
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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15 pages, 9542 KiB  
Article
A Compact 16 Channel Embedded System with High Dynamic Range Readout and Heater Management for Semiconducting Metal Oxide Gas Sensors
by Christof Hammer, Johannes Warmer, Stephan Maurer, Peter Kaul, Ronald Thoelen and Norbert Jung
Electronics 2020, 9(11), 1855; https://doi.org/10.3390/electronics9111855 - 5 Nov 2020
Cited by 4 | Viewed by 3265
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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21 pages, 1518 KiB  
Article
A Latency-Insensitive Design Approach to Programmable FPGA-Based Real-Time Simulators
by Federico Montaño, Tarek Ould-Bachir and Jean Pierre David
Electronics 2020, 9(11), 1838; https://doi.org/10.3390/electronics9111838 - 3 Nov 2020
Cited by 5 | Viewed by 3424
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
(This article belongs to the Special Issue Hardware in the Loop for Electrical Systems: Techniques, Algorithm and Circuits)
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14 pages, 628 KiB  
Article
Energy and Performance Trade-Off Optimization in Heterogeneous Computing via Reinforcement Learning
by Zheqi Yu, Pedro Machado, Adnan Zahid, Amir M. Abdulghani, Kia Dashtipour, Hadi Heidari, Muhammad A. Imran and Qammer H. Abbasi
Electronics 2020, 9(11), 1812; https://doi.org/10.3390/electronics9111812 - 2 Nov 2020
Cited by 26 | Viewed by 4600
Abstract
This paper suggests an optimisation approach in heterogeneous computing systems to balance energy power consumption and efficiency. The work proposes a power measurement utility for a reinforcement learning (PMU-RL) algorithm to dynamically adjust the resource utilisation of heterogeneous platforms in order to minimise [...] Read more.
This paper suggests an optimisation approach in heterogeneous computing systems to balance energy power consumption and efficiency. The work proposes a power measurement utility for a reinforcement learning (PMU-RL) algorithm to dynamically adjust the resource utilisation of heterogeneous platforms in order to minimise power consumption. A reinforcement learning (RL) technique is applied to analyse and optimise the resource utilisation of field programmable gate array (FPGA) control state capabilities, which is built for a simulation environment with a Xilinx ZYNQ multi-processor systems-on-chip (MPSoC) board. In this study, the balance operation mode for improving power consumption and performance is established to dynamically change the programmable logic (PL) end work state. It is based on an RL algorithm that can quickly discover the optimization effect of PL on different workloads to improve energy efficiency. The results demonstrate a substantial reduction of 18% in energy consumption without affecting the application’s performance. Thus, the proposed PMU-RL technique has the potential to be considered for other heterogeneous computing platforms. Full article
(This article belongs to the Special Issue Recent Advances on Circuits and Systems for Artificial Intelligence)
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25 pages, 2972 KiB  
Article
Comparing VR- and AR-Based Try-On Systems Using Personalized Avatars
by Yuzhao Liu, Yuhan Liu, Shihui Xu, Kelvin Cheng, Soh Masuko and Jiro Tanaka
Electronics 2020, 9(11), 1814; https://doi.org/10.3390/electronics9111814 - 2 Nov 2020
Cited by 39 | Viewed by 12918
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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16 pages, 1360 KiB  
Article
RNS Number Comparator Based on a Modified Diagonal Function
by Mikhail Babenko, Maxim Deryabin, Stanislaw J. Piestrak, Piotr Patronik, Nikolay Chervyakov, Andrei Tchernykh and Arutyun Avetisyan
Electronics 2020, 9(11), 1784; https://doi.org/10.3390/electronics9111784 - 27 Oct 2020
Cited by 14 | Viewed by 3534
Abstract
Number comparison has long been recognized as one of the most fundamental non-modular arithmetic operations to be executed in a non-positional Residue Number System (RNS). In this paper, a new technique for designing comparators of RNS numbers represented in an arbitrary moduli set [...] Read more.
Number comparison has long been recognized as one of the most fundamental non-modular arithmetic operations to be executed in a non-positional Residue Number System (RNS). In this paper, a new technique for designing comparators of RNS numbers represented in an arbitrary moduli set is presented. It is based on a newly introduced modified diagonal function, whose strictly monotonic properties make it possible to replace the cumbersome operations of finding the remainder of the division by a large and awkward number with significantly simpler computations involving only a power of 2 modulus. Comparators of numbers represented in sample RNSs composed of varying numbers of moduli and offering different dynamic ranges, designed using various methods, were synthesized for the 65 nm technology. The experimental results suggest that the new circuits enjoy a delay reduction ranging from over 11% to over 75% compared to the fastest circuits designed using existing methods. Moreover, it is achieved using less hardware, the reduction of which reaches over 41%, and is accompanied by significantly reduced power-consumption, which in several cases exceeds 100%. Therefore, it seems that the presented method leads to the design of the most efficient current hardware comparators of numbers represented using a general RNS moduli set. Full article
(This article belongs to the Special Issue Approximate Computing: Design, Acceleration, Validation and Testing of Circuits, Architectures and Algorithms in Future Systems)
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