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Electronics, Volume 10, Issue 20 (October-2 2021) – 112 articles

Cover Story (view full-size image): This paper reviews, highlights, and discusses some of the common cloud computing vulnerabilities primarily related to virtualization platforms and their implementations while outsourcing services and resources to different end-users and business enterprises. Blockchain-enabled solutions are presented for virtualized cloud platforms involving both the end-users and cloud service providers (CSP) to address and solve various security and privacy-related vulnerabilities in cloud computing infrastructures. These solutions help the data center industry to improve their virtualized cloud services and resource provisioning facilities. View this paper
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12 pages, 374 KiB  
Article
State Estimation in Electric Power Systems Using an Approach Based on a Weighted Least Squares Non-Linear Programming Modeling
by Hugo A. R. Florez, Diogo Marujo, Gloria P. López, Jesús M. López-Lezama and Nicolás Muñoz-Galeano
Electronics 2021, 10(20), 2560; https://doi.org/10.3390/electronics10202560 - 19 Oct 2021
Cited by 2 | Viewed by 2892
Abstract
In this work, the state estimation problem of electric power systems is represented through a mathematical programming approach. Initially, a non-linear mathematical model based on the classical method of weighted least squares is proposed to solve the state estimation problem for comparative purposes. [...] Read more.
In this work, the state estimation problem of electric power systems is represented through a mathematical programming approach. Initially, a non-linear mathematical model based on the classical method of weighted least squares is proposed to solve the state estimation problem for comparative purposes. Due to the inherent limitations that this classical model presents when dealing with errors in the set of measurements, a new mathematical model is proposed that can be used within an iterative procedure to reduce the impact of measurement errors on the estimated results. Several tests on a didactic 5-bus power system and IEEE benchmark power test systems showed the effectiveness of the proposed approach which achieved better results than the proposed classical state estimation model. The non-linear programming models proposed in this paper are implemented in the mathematical modeling language AMPL. Additionally, to validate the results of the proposed methodologies, the power system operation points are compared with the results obtained using the Matpower simulation package. The results allowed concluding that the proposed mathematical models can be successfully applied to perform state estimation studies in power systems. Full article
(This article belongs to the Section Power Electronics)
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13 pages, 2775 KiB  
Article
Segmentation of Aorta 3D CT Images Based on 2D Convolutional Neural Networks
by Simone Bonechi, Paolo Andreini, Alessandro Mecocci, Nicola Giannelli, Franco Scarselli, Eugenio Neri, Monica Bianchini and Giovanna Maria Dimitri
Electronics 2021, 10(20), 2559; https://doi.org/10.3390/electronics10202559 - 19 Oct 2021
Cited by 12 | Viewed by 3014
Abstract
The automatic segmentation of the aorta can be extremely useful in clinical practice, allowing the diagnosis of numerous pathologies to be sped up, such as aneurysms and dissections, and allowing rapid reconstructive surgery, essential in saving patients’ lives. In recent years, the success [...] Read more.
The automatic segmentation of the aorta can be extremely useful in clinical practice, allowing the diagnosis of numerous pathologies to be sped up, such as aneurysms and dissections, and allowing rapid reconstructive surgery, essential in saving patients’ lives. In recent years, the success of Deep Learning (DL)-based decision support systems has increased their popularity in the medical field. However, their effective application is often limited by the scarcity of training data. In fact, collecting large annotated datasets is usually difficult and expensive, especially in the biomedical domain. In this paper, an automatic method for aortic segmentation, based on 2D convolutional neural networks (CNNs), using 3D CT (computed axial tomography) scans as input is presented. For this purpose, a set of 153 CT images was collected and a semi-automated approach was used to obtain their 3D annotations at the voxel level. Although less accurate, the use of a semi-supervised labeling technique instead of a full supervision proved necessary to obtain enough data in a reasonable amount of time. The 3D volume was analyzed using three 2D segmentation networks, one for each of the three CT views (axial, coronal and sagittal). Two different network architectures, U-Net and LinkNet, were used and compared. The main advantages of the proposed method lie in its ability to work with a reduced number of data even with noisy targets. In addition, analyzing 3D scans based on 2D slices allows for them to be processed even with limited computing power. The results obtained are promising and show that the neural networks employed can provide accurate segmentation of the aorta. Full article
(This article belongs to the Special Issue Neural Network Applications to Digital Signal Processing)
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14 pages, 1776 KiB  
Article
Automated Workers’ Ergonomic Risk Assessment in Manual Material Handling Using sEMG Wearable Sensors and Machine Learning
by Srimantha E. Mudiyanselage, Phuong Hoang Dat Nguyen, Mohammad Sadra Rajabi and Reza Akhavian
Electronics 2021, 10(20), 2558; https://doi.org/10.3390/electronics10202558 - 19 Oct 2021
Cited by 65 | Viewed by 5587
Abstract
Manual material handling tasks have the potential to be highly unsafe from an ergonomic viewpoint. Safety inspections to monitor body postures can help mitigate ergonomic risks of material handling. However, the real effect of awkward muscle movements, strains, and excessive forces that may [...] Read more.
Manual material handling tasks have the potential to be highly unsafe from an ergonomic viewpoint. Safety inspections to monitor body postures can help mitigate ergonomic risks of material handling. However, the real effect of awkward muscle movements, strains, and excessive forces that may result in an injury may not be identified by external cues. This paper evaluates the ability of surface electromyogram (EMG)-based systems together with machine learning algorithms to automatically detect body movements that may harm muscles in material handling. The analysis utilized a lifting equation developed by the U.S. National Institute for Occupational Safety and Health (NIOSH). This equation determines a Recommended Weight Limit, which suggests the maximum acceptable weight that a healthy worker can lift and carry, as well as a Lifting Index value to assess the risk extent. Four different machine learning models, namely Decision Tree, Support Vector Machine, K-Nearest Neighbor, and Random Forest are developed to classify the risk assessments calculated based on the NIOSH lifting equation. The sensitivity of the models to various parameters is also evaluated to find the best performance using each algorithm. Results indicate that Decision Tree models have the potential to predict the risk level with close to 99.35% accuracy. Full article
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11 pages, 3314 KiB  
Communication
Selective Disinfection Based on Directional Ultraviolet Irradiation and Artificial Intelligence
by Ben Zierdt, Taichu Shi, Thomas DeGroat, Sam Furman, Nicholas Papas, Zachary Smoot, Hong Zhang and Ben Wu
Electronics 2021, 10(20), 2557; https://doi.org/10.3390/electronics10202557 - 19 Oct 2021
Viewed by 1647
Abstract
Ultraviolet disinfection has been proven to be effective for surface sanitation. Traditional ultraviolet disinfection systems generate omnidirectional radiation, which introduces safety concerns regarding human exposure. Large scale disinfection must be performed without humans present, which limits the time efficiency of disinfection. We propose [...] Read more.
Ultraviolet disinfection has been proven to be effective for surface sanitation. Traditional ultraviolet disinfection systems generate omnidirectional radiation, which introduces safety concerns regarding human exposure. Large scale disinfection must be performed without humans present, which limits the time efficiency of disinfection. We propose and experimentally demonstrate a targeted ultraviolet disinfection system using a combination of robotics, lasers, and deep learning. The system uses a laser-galvo and a camera mounted on a two-axis gimbal running a custom deep learning algorithm. This allows ultraviolet radiation to be applied to any surface in the room where it is mounted, and the algorithm ensures that the laser targets the desired surfaces avoids others such as humans. Both the laser-galvo and the deep learning algorithm were tested for targeted disinfection. Full article
(This article belongs to the Special Issue Advanced Photonic Technologies for High-Speed Communications)
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9 pages, 484 KiB  
Article
Joint Diagnosis of RIS and BS for RIS-Aided Millimeter-Wave System
by Siqi Ma, Jianguo Li, Xiangyuan Bu and Jianping An
Electronics 2021, 10(20), 2556; https://doi.org/10.3390/electronics10202556 - 19 Oct 2021
Cited by 4 | Viewed by 1680
Abstract
Recently, the reconfigurable intelligent surface (RIS)-aided communication system has emerged as a promising candidate for future millimeter-wave wireless communications. Due to the short wavelength of millimeter wave, the antennas on the base station (BS) and the elements on the RIS can be densely [...] Read more.
Recently, the reconfigurable intelligent surface (RIS)-aided communication system has emerged as a promising candidate for future millimeter-wave wireless communications. Due to the short wavelength of millimeter wave, the antennas on the base station (BS) and the elements on the RIS can be densely packed. It usually causes the BS and RIS to be blocked by rain, snow, or dust, which will change the channel’s characteristics and decrease the performance of communication system. In order to solve this problem, we propose an iterative compressed sense based algorithm for joint estimating the blockage coefficients of RIS and BS. Then, for the complete blockage scenario, we propose a low complexity algorithm for estimating the blockage coefficients. Our simulation results demonstrate the superior performance of the proposed algorithm to existing ones. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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17 pages, 6159 KiB  
Article
Integration of Distributed Energy Resources and EV Fast-Charging Infrastructure in High-Speed Railway Systems
by Miad Ahmadi, Hamed Jafari Kaleybar, Morris Brenna, Francesco Castelli-Dezza and Maria Stefania Carmeli
Electronics 2021, 10(20), 2555; https://doi.org/10.3390/electronics10202555 - 19 Oct 2021
Cited by 12 | Viewed by 2511
Abstract
Low carbon emission transportation is attracting global attention where electric railway power systems (ERPS) and electric vehicles (EVs) act as a load. Besides the main utility grid, renewable energy sources (RES) including photovoltaic (PV) panels and wind turbines are implemented to supply the [...] Read more.
Low carbon emission transportation is attracting global attention where electric railway power systems (ERPS) and electric vehicles (EVs) act as a load. Besides the main utility grid, renewable energy sources (RES) including photovoltaic (PV) panels and wind turbines are implemented to supply the loads fully or partially. In this paper, a novel smart DC catenary system is proposed in which renewable sources, storage systems, and DC fast-charging stations are connected to the overhead DC catenary line of the high-speed railway power system. The generated power from renewable sources and consumed power by charging stations are processed by their dedicated DC-DC power electronics converters. Furthermore, a storage system is used as a backup system not only for the case of blackouts but also because of the intermittent nature of renewable energy sources to supply the loads continuously. The paper presents an optimal power control for various parts and a power management system (PMS) that manages the power flow from wind-PV-storage system to EV-ERPS system. The proposed system has been investigated using a real Italian Rome-Florence 3 kV high-speed line as a case study with real data of ERPS load. The EV fast-charging station power demand, wind speed, solar irradiance, and temperature were recorded for 24 h in order to provide us with realistic output data. The simulation results obtained by MATLAB/Simulink are presented to validate the effectiveness of the proposed system. Full article
(This article belongs to the Special Issue Railway Traction Power Supply)
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33 pages, 1050 KiB  
Article
Fine-Grained Implicit Sentiment in Financial News: Uncovering Hidden Bulls and Bears
by Gilles Jacobs and Véronique Hoste
Electronics 2021, 10(20), 2554; https://doi.org/10.3390/electronics10202554 - 19 Oct 2021
Cited by 6 | Viewed by 3284
Abstract
The field of sentiment analysis is currently dominated by the detection of attitudes in lexically explicit texts such as user reviews and social media posts. In objective text genres such as economic news, indirect expressions of sentiment are common. Here, a positive or [...] Read more.
The field of sentiment analysis is currently dominated by the detection of attitudes in lexically explicit texts such as user reviews and social media posts. In objective text genres such as economic news, indirect expressions of sentiment are common. Here, a positive or negative attitude toward an entity must be inferred from connotational or real-world knowledge. To capture all expressions of subjectivity, a need exists for fine-grained resources and approaches for implicit sentiment analysis. We present the SENTiVENT corpus of English business news that contains token-level annotations for target spans, polar spans, and implicit polarity (positive, negative, or neutral investor sentiment, respectively). We both directly annotate polar expressions and induce them from existing schema-based event annotations to obtain event-implied implicit sentiment tuples. This results in a large dataset of 12,400 sentiment–target tuples in 288 fully annotated articles. We validate the created resource with an inter-annotator agreement study and a series of coarse- to fine-grained supervised deep-representation-learning experiments. Agreement scores show that our annotations are of substantial quality. The coarse-grained experiments involve classifying the positive, negative, and neutral polarity of known polar expressions and, in clause-based experiments, the detection of positive, negative, neutral, and no-polarity clauses. The gold coarse-grained experiments obtain decent performance (76% accuracy and 63% macro-F1) and clause-based detection shows decreased performance (65% accuracy and 57% macro-F1) with the confusion of neutral and no-polarity. The coarse-grained results demonstrate the feasibility of implicit polarity classification as operationalized in our dataset. In the fine-grained experiments, we apply the grid tagging scheme unified model for <polar span, target span, polarity> triplet extraction, which obtains state-of-the-art performance on explicit sentiment in user reviews. We observe a drop in performance on our implicit sentiment corpus compared to the explicit benchmark (22% vs. 76% F1). We find that the current models for explicit sentiment are not directly portable to our implicit task: the larger lexical variety within implicit opinion expressions causes lexical data scarcity. We identify common errors and discuss several recommendations for implicit fine-grained sentiment analysis. Data and source code are available. Full article
(This article belongs to the Special Issue Emerging Application of Sentiment Analysis Technologies)
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26 pages, 1954 KiB  
Review
The Decreasing Hazard Rate Phenomenon: A Review of Different Models, with a Discussion of the Rationale behind Their Choice
by Elio Chiodo and Giovanni Mazzanti
Electronics 2021, 10(20), 2553; https://doi.org/10.3390/electronics10202553 - 19 Oct 2021
Cited by 2 | Viewed by 1615
Abstract
It is well known that, especially in the field of electronic components reliability studies and applications, the Exponential reliability model is by far the most adopted, although the data fostering it are few. This appears to be due partly to its simplicity (also [...] Read more.
It is well known that, especially in the field of electronic components reliability studies and applications, the Exponential reliability model is by far the most adopted, although the data fostering it are few. This appears to be due partly to its simplicity (also in view of estimation, since it is characterized by a unique parameter), and partly because most components seem to be well represented, at least in their “useful life” time interval, by the Exponential model. This adoption is basically due to its peculiar “memory-less” property, i.e., the fact that such model possesses a constant hazard rate function, meaning that stochastic “accidents” cause the failure of the component, independently of its service time. This theoretical reason behind the choice of the Exponential model is largely prevailing over the classical statistical “goodness of fit” tests, since the high-reliability values attained by such devices does not allow the availability of an adequate number of lifetime values to be observed and analyzed in a statistical data analysis procedure. A second model also widely adopted is the Weibull model, especially if characterized by a shape parameter greater than unity, so implying an increasing hazard rate function. However, there are many cases—which can be also justified on a theoretical basis, as reviewed in this paper—in which a decreasing hazard rate function (at least for relatively large mission times) may be the best suited to describe the true model behind a given failure mechanism. The afore-mentioned theoretical basis of these apparently peculiar models is the main core of the present review article, whose aim also includes the illustration of the basic features of the main reliability models featuring an hazard rate function diminishing with time. The paper also discusses, resorting to graphical and numerical case-studies relevant to both field and simulated data, the consequences of mistaken model identification in terms of the hazard rate function behaviour, which may imply wrong maintenance actions. Full article
(This article belongs to the Section Industrial Electronics)
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26 pages, 7388 KiB  
Article
SEOUL AR: Designing a Mobile AR Tour Application for Seoul Sky Observatory in South Korea
by Soomin Shin and Yongsoon Choi
Electronics 2021, 10(20), 2552; https://doi.org/10.3390/electronics10202552 - 19 Oct 2021
Cited by 2 | Viewed by 2325
Abstract
Skyscrapers are symbols of local landmarks, and their prevalence is increasing across the world owing to recent advances in architectural technology. In Korea, the Lotte World Tower, which is now the tallest skyscraper in Seoul, was constructed in 2017. In addition, it has [...] Read more.
Skyscrapers are symbols of local landmarks, and their prevalence is increasing across the world owing to recent advances in architectural technology. In Korea, the Lotte World Tower, which is now the tallest skyscraper in Seoul, was constructed in 2017. In addition, it has an observatory deck called Seoul Sky, which is currently in operation. This study focuses on the design of Seoul AR, which is a mobile augmented reality (AR) tour application. Visitors can use Seoul AR when visiting the Seoul Sky Observatory, one of the representative landmarks of Seoul, and enjoy a 360° view of the entire landscape of Seoul in the observatory space. With Seoul AR, they can identify tourist attractions in Seoul with simple mission games. Users are also provided with information regarding the specific attraction they are viewing, as well as other information on transportation, popular restaurants, shopping places, etc., in order to increase the level of satisfaction of tourists visiting the Seoul Sky Observatory. The final design is revised through heuristic evaluation, and a study of users’ levels of satisfaction with Seoul AR is conducted through surveys completed by visitors to the Seoul Sky Observatory. Full article
(This article belongs to the Special Issue LifeXR: Concepts, Technology and Design for Everyday XR)
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2 pages, 168 KiB  
Editorial
Advanced AI Hardware Designs Based on FPGAs
by Joo-Young Kim
Electronics 2021, 10(20), 2551; https://doi.org/10.3390/electronics10202551 - 19 Oct 2021
Cited by 1 | Viewed by 1730
Abstract
Artificial intelligence (AI) and machine learning (ML) technology enable computers to run cognitive tasks such as recognition, understanding, and reasoning, which are believed to be processes that only humans are capable of, using a massive amount of data [...] Full article
(This article belongs to the Special Issue Advanced AI Hardware Designs Based on FPGAs)
24 pages, 2767 KiB  
Article
An Implementation Design of Unified Protocol Architecture for Physical Layer of LoRaWAN End-Nodes
by Jean Park and Juyeop Kim
Electronics 2021, 10(20), 2550; https://doi.org/10.3390/electronics10202550 - 19 Oct 2021
Cited by 1 | Viewed by 1886
Abstract
LoRa Wide Area Networks (LoRaWAN) can provide a connectivity service to Internet of Things (IoT) for an extremely long run-time and with low power consumption. As the LoRaWAN is extensively applied to various IoT scenarios, LoRaWAN solutions face a flexibility issue in terms [...] Read more.
LoRa Wide Area Networks (LoRaWAN) can provide a connectivity service to Internet of Things (IoT) for an extremely long run-time and with low power consumption. As the LoRaWAN is extensively applied to various IoT scenarios, LoRaWAN solutions face a flexibility issue in terms of inter-operating with various kinds of LoRa modem hardware and protocol scenarios. In this regard, we design a unified protocol architecture for LoRaWAN physical layer, which can flexibly correspond to various deployment and operational cases. The new protocol architecture includes a hardware abstraction sub-layer, which contains generalized handlers for configuring various kinds of the LoRa modem, and a physical procedure sub-layer that structurally models the physical layer procedures of the LoRaWAN based on Finite State Machine(FSM). We illustrate the flexibility of the new protocol architecture by implementing an extensive feature that enhances the packet reception ratio based on the status of preamble detection. For evaluating the new protocol architecture, we implement the LoRaWAN physical layer protocol on real-time embedded systems and conduct experiments. The experimental results show that the proposed protocol robustly transmits and receives packets and generates little amount of additional burden compared with the conventional open source protocol provided by SemTech. Full article
(This article belongs to the Special Issue Software-Defined 5G/B5G/6G Development)
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21 pages, 82066 KiB  
Article
Design and Hardware Implementation of an IGBT-Based Half-Bridge Cell for Modular Voltage Source Inverters
by Roberto Morales-Caporal, José F. Pérez-Cuapio, Haydee P. Martínez-Hernández and Raúl Cortés-Maldonado
Electronics 2021, 10(20), 2549; https://doi.org/10.3390/electronics10202549 - 19 Oct 2021
Cited by 2 | Viewed by 8963
Abstract
This article presents the design and hardware implementation of an IGBT-based half-bridge voltage source inverter (VSI) to be used as a basic cell to assemble VSIs of different topologies in modular ways. Herein, we have presented the design methodology and utilized techniques for [...] Read more.
This article presents the design and hardware implementation of an IGBT-based half-bridge voltage source inverter (VSI) to be used as a basic cell to assemble VSIs of different topologies in modular ways. Herein, we have presented the design methodology and utilized techniques for reducing stray inductances and EMI radiation on the printed circuit board, as well as the way to calculate and select the main electronic components. For the design of the circuit board, local regulations for grid interconnection and international standards were considered in order to obtain a safe and reliable electronic power cell. The developed hardware was subjected to different tests using AC electric motors as loads to validate its design. Two VSIs topologies were evaluated: a single-phase two-level full-bridge inverter and a three-phase two-level inverter. The experimental results validated the theory and demonstrated the excellent performance, reliability, and high efficiency of the developed half-bridge power cell for modular VSIs. Full article
(This article belongs to the Section Power Electronics)
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20 pages, 6516 KiB  
Article
Novel Method of Coupling Coefficient Estimation Based on the Bifurcation Phenomena in Inductive Power Transfer
by Michal Košík, Aaron D. Scher and Jiří Lettl
Electronics 2021, 10(20), 2548; https://doi.org/10.3390/electronics10202548 - 18 Oct 2021
Cited by 5 | Viewed by 2071
Abstract
Inductive power transfer (IPT) applications, such as stationary charging of electric vehicles (EVs), at least moderate coupling between the coils to achieve high efficiency, but the coefficient k typically varies between of 0.1 to 0.4, depending on the displacement of the coils according [...] Read more.
Inductive power transfer (IPT) applications, such as stationary charging of electric vehicles (EVs), at least moderate coupling between the coils to achieve high efficiency, but the coefficient k typically varies between of 0.1 to 0.4, depending on the displacement of the coils according to SAE J2954. Thus, accurate and reliable methods for estimation of k are required for positioning of the EV to achieve optimal alignment with the charging pad. Additionally, in IPT, numerous control strategies are available for regulating output power and optimizing system efficiency that require an accurate estimate of the mutual inductance or k. However, existing estimation methods tend to require detailed a-priori information of a large number of circuit parameters, or they need measurement of currents or voltages in both primary and secondary sides. This paper presents a preliminary evaluation of a novel, primary-side method to estimate k, which is based solely on the frequency response of the input phase while operating the system in bifurcation. The method does not require any additional measurements of the system parameters. The theoretical background of the method is presented together with the description of the measurement procedure. The method is experimentally verified and compared with two currently used estimation methods. According to the presented experimental evaluation, the proposed method estimates k with an error of 3.62% with respect to the reference over the evaluated range of 0.08 to 0.36. In addition, we demonstrate that the presented method is resilient to detuning. Full article
(This article belongs to the Section Power Electronics)
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16 pages, 5252 KiB  
Article
Speeding Up Velocity Consensus Control with Small World Communication Topology for Unmanned Aerial Vehicle Swarms
by Xiang Ji, Wanpeng Zhang, Shaofei Chen, Junren Luo, Lina Lu, Weilin Yuan, Zhenzhen Hu and Jing Chen
Electronics 2021, 10(20), 2547; https://doi.org/10.3390/electronics10202547 - 18 Oct 2021
Cited by 5 | Viewed by 1424
Abstract
This study addressed a problem of rapid velocity consensus within a swarm of unmanned aerial vehicles. Our analytical framework was based on tools using matrix theory and algebraic graph theory. We established connections between algebraic connectivity and the speed of converging on a [...] Read more.
This study addressed a problem of rapid velocity consensus within a swarm of unmanned aerial vehicles. Our analytical framework was based on tools using matrix theory and algebraic graph theory. We established connections between algebraic connectivity and the speed of converging on a velocity. The relationship between algebraic connectivity and communication cost was established. To deal with the trade-off among algebraic connectivity, convergence speed and communication cost, we propose a distributed small world network construction method. The small world network characteristics expedite the convergence speed toward consensus in the unmanned aerial vehicle swarm. Eventually, our method greatly sped up the consensus velocities in the unmanned aerial vehicle swarms at a lower communication cost than other methods required. Full article
(This article belongs to the Special Issue Advances in Swarm Intelligence, Data Science and Their Applications)
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12 pages, 1685 KiB  
Article
Hardware Implementation Study of Particle Tracking Algorithm on FPGAs
by Alessandro Gabrielli, Fabrizio Alfonsi, Alberto Annovi, Alessandra Camplani and Alessandro Cerri
Electronics 2021, 10(20), 2546; https://doi.org/10.3390/electronics10202546 - 18 Oct 2021
Cited by 4 | Viewed by 2168
Abstract
In recent years, the technological node used to implement FPGA devices has led to very high performance in terms of computational capacity and in some applications these can be much more efficient than CPUs or other programmable devices. The clock managers and the [...] Read more.
In recent years, the technological node used to implement FPGA devices has led to very high performance in terms of computational capacity and in some applications these can be much more efficient than CPUs or other programmable devices. The clock managers and the enormous versatility of communication technology through digital transceivers place FPGAs in a prime position for many applications. For example, from real-time medical image analysis to high energy physics particle trajectory recognition, where computation time can be crucial, the benefits of using frontier FPGA capabilities are even more relevant. This paper shows an example of FPGA hardware implementation, via a firmware design, of a complex analytical algorithm: The Hough transform. This is a mathematical spatial transformation used here to facilitate on-the-fly recognition of the trajectories of ionising particles as they pass through the so-called tracker apparatus within high-energy physics detectors. This is a general study to demonstrate that this technique is not only implementable via software-based systems, but can also be exploited using consumer hardware devices. In this context the latter are known as hardware accelerators. In this article in particular, the Xilinx UltraScale+ FPGA is investigated as it belongs to one of the frontier family devices on the market. These FPGAs make it possible to reach high-speed clock frequencies at the expense of acceptable energy consumption thanks to the 14 nm technological node used by the vendor. These devices feature a huge number of gates, high-bandwidth memories, transceivers and other high-performance electronics in a single chip, enabling the design of large, complex and scalable architectures. In particular the Xilinx Alveo U250 has been investigated. A target frequency of 250 MHz and a total latency of 30 clock periods have been achieved using only the 17 ÷ 53% of LUTs, the 8 ÷ 12% of DSPs, the 1 ÷ 3% of Block Rams and a Flip Flop occupancy range of 9 ÷ 28%. Full article
(This article belongs to the Special Issue VLSI Circuits & Systems Design)
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13 pages, 17897 KiB  
Article
Conception and Simulation of a 2-Then-1-Bit/Cycle Noise-Shaping SAR ADC
by Kihyun Kim, Sein Oh and Hyungil Chae
Electronics 2021, 10(20), 2545; https://doi.org/10.3390/electronics10202545 - 18 Oct 2021
Cited by 2 | Viewed by 2065
Abstract
A 2-then-1-bit/cycle noise-shaping successive-approximation register (SAR) analog-to-digital converter (ADC) for high sampling rate and high resolution is presented. The conversion consists of two phases of a coarse 2-bit/cycle SAR conversion for high speed and a fine 1-bit/cycle noise-shaping SAR conversion for high accuracy. [...] Read more.
A 2-then-1-bit/cycle noise-shaping successive-approximation register (SAR) analog-to-digital converter (ADC) for high sampling rate and high resolution is presented. The conversion consists of two phases of a coarse 2-bit/cycle SAR conversion for high speed and a fine 1-bit/cycle noise-shaping SAR conversion for high accuracy. The coarse conversion is performed by both voltage and time comparison for low power consumption. A redundancy after the coarse conversion corrects the error caused by a jitter noise during the time comparison. Additionally, a mismatch error between signal and reference paths is eliminated with the help of a tail-current-sharing comparator. The proposed ADC was designed in a 28 nm CMOS process, and the simulation result shows a 68.2 dB signal-to-noise distortion (SNDR) for a sampling rate of 480 MS/s and a bandwidth of 60 MHz with good energy efficiency. Full article
(This article belongs to the Section Circuit and Signal Processing)
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17 pages, 775 KiB  
Article
Adaptive Fading Extended Kalman Filtering for Mobile Robot Localization Using a Doppler–Azimuth Radar
by Bin Li, Yanyang Lu and Hamid Reza Karimi
Electronics 2021, 10(20), 2544; https://doi.org/10.3390/electronics10202544 - 18 Oct 2021
Cited by 5 | Viewed by 1598
Abstract
In this paper, the localization problem of a mobile robot equipped with a Doppler–azimuth radar (D–AR) is investigated in the environment with multiple landmarks. For the type (2,0) robot kinematic model, the unknown modeling errors are generally aroused by the inaccurate odometer measurement. [...] Read more.
In this paper, the localization problem of a mobile robot equipped with a Doppler–azimuth radar (D–AR) is investigated in the environment with multiple landmarks. For the type (2,0) robot kinematic model, the unknown modeling errors are generally aroused by the inaccurate odometer measurement. Meanwhile, the inaccurate odometer measurement can also give rise to a type of unknown bias for the D–AR measurement. For reducing the influence induced by modeling errors on the localization performance and enhancing the practicability of the developed robot localization algorithm, an adaptive fading extended Kalman filter (AFEKF)-based robot localization scheme is proposed. First, the robot kinematic model and the D–AR measurement model are modified by considering the impact caused by the inaccurate odometer measurement. Subsequently, in the frame of adaptive fading extended Kalman filtering, the way to the addressed robot localization problem with unknown biases is sought out and the stability of the developed AFEKF-based localization algorithm is also discussed. Finally, in order to testify the feasibility of the AFEKF-based localization scheme, three different kinds of modeling errors are considered and the comparative simulations are conducted with the conventional EKF. From the comparative simulation results, it can be seen that the average localization error under the developed AFEKF-based localization scheme is [0.0245 m0.0224 m0.0039 rad]T and the average localization errors using the conventional EKF are [1.0405 m2.2700 m0.1782 rad]T, [0.4963 m0.3482 m0.0254 rad]T and [0.2774 m0.3897 m0.0353 rad]T, respectively, under the three cases of the constant bias, the white Gaussian stochastic bias and the bounded uncertainty bias. Full article
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26 pages, 27568 KiB  
Article
Three-Port Series-Resonant DC/DC Converter for Automotive Charging Applications
by Jannik Schäfer and Johann Walter Kolar
Electronics 2021, 10(20), 2543; https://doi.org/10.3390/electronics10202543 - 18 Oct 2021
Cited by 12 | Viewed by 3356
Abstract
In the energy distribution grid of electric vehicles (EVs), multiple different voltage potentials need to be interconnected, to allow arbitrary power flow between the various energy sources and the different electrical loads. However, between the different potentials, galvanic isolation is absolutely necessary, either [...] Read more.
In the energy distribution grid of electric vehicles (EVs), multiple different voltage potentials need to be interconnected, to allow arbitrary power flow between the various energy sources and the different electrical loads. However, between the different potentials, galvanic isolation is absolutely necessary, either due to safety reasons and/or due to different grounding schemes. This paper presents an isolated three-port DC/DC converter topology, which, in combination with an upstream PFC rectifier, can be used as combined EV charger for interconnecting the single-phase AC mains, the high-voltage (HV) battery and the low-voltage (LV) bus in EVs. The proposed topology comprises two synergetically controlled and magnetically coupled converter parts, namely, a series-resonant converter between the PFC-sided DC-link capacitor and the HV battery, as well as a phase-shifted full-bridge circuit equivalent in the LV port, and is mainly characterized by simplicity in terms of control and circuit complexity. For this converter, a simple soft switching modulation scheme is proposed and comprehensively analyzed, in consideration of all parasitic components of a real converter implementation. Based on this analysis, the design of a 3.6 kW, 500 V/500 V/15 V prototype is discussed, striving for the highest possible power density and as low as possible manufacturing costs, by using PCB-integrated windings for all magnetic components. The hardware demonstrator achieves a measured full-load efficiency in charge mode of 96.5% for nominal operating conditions and a power density of 16.4  kWL−1. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
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20 pages, 9311 KiB  
Article
SPSO Based Optimal Integration of DGs in Local Distribution Systems under Extreme Load Growth for Smart Cities
by Mian Rizwan, Muhammad Waseem, Rehan Liaqat, Intisar Ali Sajjad, Udaya Dampage, Saleh H. Salmen, Sami Al Obaid, Mohamed A. Mohamed and Andres Annuk
Electronics 2021, 10(20), 2542; https://doi.org/10.3390/electronics10202542 - 18 Oct 2021
Cited by 26 | Viewed by 2688
Abstract
Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of [...] Read more.
Renewable energy-based distributed generators (DGs) are gaining more penetration in modern grids to meet the growing demand for electrical energy. The anticipated techno-economic benefits of these eco-friendly resources require their judicious and properly sized allocation in distribution networks (DNs). The preeminent objective of this research is to determine the sizing and optimal placing of DGs in the condensed DN of a smart city. The placing and sizing problem is modeled as an optimization problem to reduce the distribution loss without violating the technical constraints. The formulated model is solved for a radial distribution system with a non-uniformly distributed load utilizing the selective particle swarm optimization (SPSO) algorithm. The intended technique decreases the power loss and perfects the voltage profile at the system’s nodes. MATLAB is used for the simulation, and the obtained results are also validated by the Electrical Transient Analysis Program (ETAP). Results show that placing optimally sized DGs at optimal system nodes offers a considerable decline in power loss with an improved voltage profile at the network’s nodes. Distribution system operators can utilize the proposed technique to realize the reliable operation of overloaded urban networks. Full article
(This article belongs to the Special Issue Operation and Control of Power Systems)
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16 pages, 7645 KiB  
Article
Modeling and Analysis of PV System with Fuzzy Logic MPPT Technique for a DC Microgrid under Variable Atmospheric Conditions
by Vasantharaj Subramanian, Vairavasundaram Indragandhi, Ramya Kuppusamy and Yuvaraja Teekaraman
Electronics 2021, 10(20), 2541; https://doi.org/10.3390/electronics10202541 - 18 Oct 2021
Cited by 20 | Viewed by 3048
Abstract
Due to the easiness of setup and great energy efficiency, direct current (DC) microgrids (MGs) have become more common. Solar photovoltaic (PV) and fuel cell (FC) systems drive the DC MG. Under varying irradiance and temperature, this work proposes a fuzzy logic controller [...] Read more.
Due to the easiness of setup and great energy efficiency, direct current (DC) microgrids (MGs) have become more common. Solar photovoltaic (PV) and fuel cell (FC) systems drive the DC MG. Under varying irradiance and temperature, this work proposes a fuzzy logic controller (FLC) based maximum power point tracking (MPPT) approach deployed to PV panel and FC generated boost converter. PV panels must be operated at their maximum power point (MPP) to enhance efficiency and shorten the system’s payback period. There are different kinds of MPPT approaches for using PV panels at that moment. Still, the FLC-based MPPT approach was chosen in this study because it responds instantaneously to environmental changes and is unaffected by circuit parameter changes. Similarly, this research proposes a better design strategy for FLC systems. It will improve the system reliability and stability of the response of the system. An FLC evaluates PV and FC via DC–DC boost converters to obtain this enhanced response time and accuracy. Full article
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16 pages, 4954 KiB  
Article
Using a Flexible IoT Architecture and Sequential AI Model to Recognize and Predict the Production Activities in the Labor-Intensive Manufacturing Site
by Cadmus Yuan, Chic-Chang Wang, Ming-Lun Chang, Wen-Ting Lin, Po-An Lin, Chang-Chi Lee and Zhe-Luen Tsui
Electronics 2021, 10(20), 2540; https://doi.org/10.3390/electronics10202540 - 18 Oct 2021
Cited by 1 | Viewed by 1878
Abstract
Under the pressures of global market uncertainty and rapid production changes, the labor-intensive industries demand instant manufacturing site information and accurate production forecasting. This research applies sensor modules with noise reduction, information abstracting, and wireless transmission functions to form a flexible internet of [...] Read more.
Under the pressures of global market uncertainty and rapid production changes, the labor-intensive industries demand instant manufacturing site information and accurate production forecasting. This research applies sensor modules with noise reduction, information abstracting, and wireless transmission functions to form a flexible internet of things (IoT) architecture for acquiring field information. Moreover, AI models are used to reveal human activities and predict the output of a group of workstations. The IoT architecture has been implemented in the actual shoe making site. Although there is a 5% missing data issue due to network transmission, neural network models can successfully convert the IoT data to machine utilization. By analyzing the field data, the actual collaboration among the worker team can be revealed. Furthermore, a sequential AI model is applied to learn to capture the characteristics of the team working. This AI model only requires training by 15 min of IoT data, then it can predict the current and next few days’ productions within 10% error. This research confirms that implementing the IoT architecture and applying the AI model enables instant manufacturing monitoring of labor-intensive manufacturing sites and accurate production forecasting. Full article
(This article belongs to the Special Issue AI for Embedded Systems)
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14 pages, 27248 KiB  
Article
3D Face Recognition Based on an Attention Mechanism and Sparse Loss Function
by Hongyan Zou and Xinyan Sun
Electronics 2021, 10(20), 2539; https://doi.org/10.3390/electronics10202539 - 18 Oct 2021
Cited by 10 | Viewed by 2057
Abstract
Face recognition is one of the essential applications in computer vision, while current face recognition technology is mainly based on 2D images without depth information, which are easily affected by illumination and facial expressions. This paper presents a fast face recognition algorithm combining [...] Read more.
Face recognition is one of the essential applications in computer vision, while current face recognition technology is mainly based on 2D images without depth information, which are easily affected by illumination and facial expressions. This paper presents a fast face recognition algorithm combining 3D point cloud face data with deep learning, focusing on key part of face for recognition with an attention mechanism, and reducing the coding space by the sparse loss function. First, an attention mechanism-based convolutional neural network was constructed to extract facial features to avoid expressions and illumination interference. Second, a Siamese network was trained with a sparse loss function to minimize the face coding space and enhance the separability of the face features. With the FRGC face dataset, the experimental results show that the proposed method could achieve the recognition accuracy of 95.33%. Full article
(This article belongs to the Section Artificial Intelligence)
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18 pages, 4956 KiB  
Article
Self-Detection of Early Breast Cancer Application with Infrared Camera and Deep Learning
by Mohammed Abdulla Salim Al Husaini, Mohamed Hadi Habaebi, Teddy Surya Gunawan and Md Rafiqul Islam
Electronics 2021, 10(20), 2538; https://doi.org/10.3390/electronics10202538 - 18 Oct 2021
Cited by 9 | Viewed by 3713
Abstract
Breast cancer is the most common cause of death in women around the world. A new tool has been adopted based on thermal imaging, deep convolutional networks, health applications on smartphones, and cloud computing for early detection of breast cancer. The development of [...] Read more.
Breast cancer is the most common cause of death in women around the world. A new tool has been adopted based on thermal imaging, deep convolutional networks, health applications on smartphones, and cloud computing for early detection of breast cancer. The development of the smart app included the use of Mastology Research with the Infrared Image DMR-IR database and the training of the modified version of deep convolutional neural network model inception V4 (MV4). In addition to designing the application in a graphical user interface and linking it with the AirDroid application to send thermal images from the smartphone to the cloud and to retrieve the suggestive diagnostic result from the cloud server to the smartphone. Moreover, to verify the proper operation of the app, a set of thermal images was sent from the smartphone to the cloud server from different distances and image acquisition procedures to verify the quality of the images. Four effects on the thermal image were applied: Blur, Shaken, Tilted, and Flipping were added to the images to verify the detection accuracy. After conducting repeated experiments, the classification results of early detection of breast cancer, generated from the MV4, illustrated high accuracy performance. The response time achieved after the successful transfer of diagnostic results from the smartphone to the cloud and back to the smartphone via the AirDroid application is six seconds. The results show that the quality of thermal images did not affect by different distances and methods except in one method when compressing thermal images by 5%, 15%, and 26%. The results indicate 1% as maximum detection accuracy when compressing thermal images by 5%, 15%, and 26%. In addition, the results indicate detection accuracy increased in Blurry images and Shaken images by 0.0002%, while diagnostic accuracy decreased to nearly 11% in Tilted images. Early detection of breast cancer using a thermal camera, deep convolutional neural network, cloud computing, and health applications of smartphones are valuable and reliable complementary tools for radiologists to reduce mortality rates. Full article
(This article belongs to the Section Bioelectronics)
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16 pages, 3593 KiB  
Article
Designing the Calibration Process of Weigh-In-Motion Systems
by Janusz Gajda, Ryszard Sroka and Piotr Burnos
Electronics 2021, 10(20), 2537; https://doi.org/10.3390/electronics10202537 - 18 Oct 2021
Cited by 2 | Viewed by 2208
Abstract
Weigh-In-Motion (WIM) systems provide information on the state of road traffic and are used in activities undertaken as part of traffic supervision and management, enforcement of applicable regulations, and in the design of road infrastructure. The further development of such systems is aimed [...] Read more.
Weigh-In-Motion (WIM) systems provide information on the state of road traffic and are used in activities undertaken as part of traffic supervision and management, enforcement of applicable regulations, and in the design of road infrastructure. The further development of such systems is aimed at increasing their measurement accuracy, operational reliability, and their resistance to disturbing environmental factors. Increasing the accuracy of measurement can be achieved both through actions taken in the hardware layer (technology of load sensors, the number of sensors and their arrangement, technology used in the construction of the pavement, selection of the system location), as well as by implementing better system calibration algorithms and algorithms for pre-processing measurement data. In this paper, we focus on the issue of WIM system calibration. We believe that through the correct selection of the calibration algorithm, it is possible to significantly increase the accuracy of vehicle weighing in WIM systems, from a practical point of view. The simulation and experimental studies we conducted confirmed this hypothesis. Full article
(This article belongs to the Special Issue Signal Processing and Data Fusion in Measurement Systems)
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14 pages, 973 KiB  
Article
Optimal Beamforming for IRS-Assisted SWIPT System with an Energy-Harvesting Eavesdropper
by Zhixiang Deng and Yan Pan
Electronics 2021, 10(20), 2536; https://doi.org/10.3390/electronics10202536 - 18 Oct 2021
Cited by 7 | Viewed by 1625
Abstract
In this paper, we study a simultaneous wireless information and power transfer (SWIPT) system aided by the intelligent reflecting surface (IRS) technology, where an AP transmits confidential information to the legitimate information receiver (IR) in the presence of an energy harvesting (EH) receiver [...] Read more.
In this paper, we study a simultaneous wireless information and power transfer (SWIPT) system aided by the intelligent reflecting surface (IRS) technology, where an AP transmits confidential information to the legitimate information receiver (IR) in the presence of an energy harvesting (EH) receiver that could be a potential eavesdropper. We aim to maximize the secrecy rate at the legitimate IR by jointly optimizing the information beamforming vector and the energy transfer beamforming vector at the access point (AP), and the phase shift matrix at the IRS, subject to the minimum harvested power required by the EH receiver. The semi-definite relaxation (SDR) approach and the alternating optimization (AO) method are proposed to convert the original non-convex optimization problem to a series of semi-definite programs (SDPs), which are solved iteratively. Numerical results show that the achievable secrecy rate of the proposed IRS-assisted SWIPT system is higher than that of the SWIPT system without the assistance of the IRS. Full article
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10 pages, 3827 KiB  
Article
Fabrication of Planar Heating Chuck Using Nichrome Thin Film as Heating Element for PECVD Equipment
by Dong-Hyeok Im, Tae-Woong Yoon, Woo-Sig Min and Sang-Jeen Hong
Electronics 2021, 10(20), 2535; https://doi.org/10.3390/electronics10202535 - 18 Oct 2021
Cited by 2 | Viewed by 3059
Abstract
Improving semiconductor equipment and components is an important goal of semiconductor manufacture. Especially during the deposition process, the temperature of the wafer must be precisely controlled to form a uniform thin film. In the conventional plasma-enhanced chemical vapor deposition (PECVD) chuck, heating rate, [...] Read more.
Improving semiconductor equipment and components is an important goal of semiconductor manufacture. Especially during the deposition process, the temperature of the wafer must be precisely controlled to form a uniform thin film. In the conventional plasma-enhanced chemical vapor deposition (PECVD) chuck, heating rate, and temperature uniformity are limited by the spiral pattern and volume of the heating element. To overcome the structural limitation of the heating element of conventional chuck, we tried to develop the planar heating chuck (PHC), a 6-inch PECVD chuck with a planar heating element based on NiCr thin film that would be a good candidate for rapidly and uniformly heating. The time for the temperature elevation from room temperature to 330 °C was 398 s. In a performance evaluation, the fabricated PHC successfully completed a SiO2 PECVD process. Full article
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14 pages, 345 KiB  
Article
Malware Detection Based on Graph Attention Networks for Intelligent Transportation Systems
by Cagatay Catal, Hakan Gunduz and Alper Ozcan
Electronics 2021, 10(20), 2534; https://doi.org/10.3390/electronics10202534 - 18 Oct 2021
Cited by 14 | Viewed by 3466
Abstract
Intelligent Transportation Systems (ITS) aim to make transportation smarter, safer, reliable, and environmentally friendly without detrimentally affecting the service quality. ITS can face security issues due to their complex, dynamic, and non-linear properties. One of the most critical security problems is attacks that [...] Read more.
Intelligent Transportation Systems (ITS) aim to make transportation smarter, safer, reliable, and environmentally friendly without detrimentally affecting the service quality. ITS can face security issues due to their complex, dynamic, and non-linear properties. One of the most critical security problems is attacks that damage the infrastructure of the entire ITS. Attackers can inject malware code that triggers dangerous actions such as information theft and unwanted system moves. The main objective of this study is to improve the performance of malware detection models using Graph Attention Networks. To detect malware attacks addressing ITS, a Graph Attention Network (GAN)-based framework is proposed in this study. The inputs to this framework are the Application Programming Interface (API)-call graphs obtained from malware and benign Android apk files. During the graph creation, network metrics and the Node2Vec model are utilized to generate the node features. A GAN-based model is combined with different types of node features during the experiments and the performance is compared against Graph Convolutional Network (GCN). Experimental results demonstrated that the integration of the GAN and Node2Vec models provides the best performance in terms of F-measure and accuracy parameters and, also, the use of an attention mechanism in GAN improves the performance. Furthermore, node features generated with Node2Vec resulted in a 3% increase in classification accuracy compared to the features generated with network metrics. Full article
(This article belongs to the Special Issue Security & Privacy in Intelligent Transportation Systems)
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18 pages, 4038 KiB  
Article
Low-Latency Hardware Implementation of High-Precision Hyperbolic Functions Sinhx and Coshx Based on Improved CORDIC Algorithm
by Wenjia Fu, Jincheng Xia, Xu Lin, Ming Liu and Mingjiang Wang
Electronics 2021, 10(20), 2533; https://doi.org/10.3390/electronics10202533 - 17 Oct 2021
Cited by 13 | Viewed by 2084
Abstract
CORDIC algorithm is used for low-cost hardware implementation to calculate transcendental functions. This paper proposes a low-latency high-precision architecture for the computation of hyperbolic functions sinhx and coshx based on an improved CORDIC algorithm, that is, the QH-CORDIC. The principle, structure, [...] Read more.
CORDIC algorithm is used for low-cost hardware implementation to calculate transcendental functions. This paper proposes a low-latency high-precision architecture for the computation of hyperbolic functions sinhx and coshx based on an improved CORDIC algorithm, that is, the QH-CORDIC. The principle, structure, and range of convergence of the QH-CORDIC are discussed, and the hardware circuit architecture of functions sinhx and coshx using the QH-CORDIC is plotted in this paper. The proposed architecture is implemented using an FPGA device, showing that it has 75% and 50% latency overhead over the two latest prior works. In the synthesis using TSMC 65 nm standard cell library, ASIC implementation results show that the proposed architecture is also superior to the two latest prior works in terms of total time (latency × period), ATP (area × total time), total energy (power × total time), energy efficiency (total energy/efficient bits), and area efficiency (efficient bits/area/total time). Comparison of related works indicates that it is much more favorable for the proposed architecture to perform high-precision floating-point computations on functions sinhx and coshx than the LUT method, stochastic computing, and other CORDIC algorithms. Full article
(This article belongs to the Section Computer Science & Engineering)
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19 pages, 1521 KiB  
Article
Self-Assessment of Soft Skills of University Teachers from Countries with a Low Level of Digital Competence
by Álvaro Antón-Sancho, Diego Vergara and Pablo Fernández-Arias
Electronics 2021, 10(20), 2532; https://doi.org/10.3390/electronics10202532 - 17 Oct 2021
Cited by 29 | Viewed by 3811
Abstract
The lockdown of March and April 2020 as a consequence of the COVID-19 pandemic has forced relevant changes in the educational environment in a very short period of time, making it necessary to suspend in-person instruction and generating the need to implement virtual [...] Read more.
The lockdown of March and April 2020 as a consequence of the COVID-19 pandemic has forced relevant changes in the educational environment in a very short period of time, making it necessary to suspend in-person instruction and generating the need to implement virtual learning mechanisms. In a future post-COVID-19 hybrid educational model, it will be necessary for university teachers to acquire an optimal degree of digital competence, as a combination of different competencies, namely, (i) technical, (ii) digital, and (iii) soft. Soft skills have been shown to have a decisive influence on the development of digital competence. The aim of this study was to analyze the degree of acquisition of soft skills in Latin American university teachers whose countries are less digitally developed. For this purpose, the countries with the lowest Global Innovation Index (GII) were selected: (i) Panama; (ii) Peru; (iii) Argentina; (iv) El Salvador; (v) Ecuador; (vi) Paraguay; (vii) Honduras; and (viii) Bolivia. To achieve this objective, it was necessary to develop a questionnaire on the self-concept of soft skills, based on the soft skills included in the Bochum Inventory of Personality and Competences (BIP). Results obtained from statistical analysis of the data collected from a sample of 219 participants show that university teachers are sufficiently prepared, in terms of their soft skills, for the increase in digital competence required as a result of the COVID-19 crisis, despite the low level of digital development in their respective countries. Full article
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13 pages, 4134 KiB  
Article
Estimation of Tire Mileage and Wear Using Measurement Data
by Wei-Hsuan Chang, Rong-Terng Juang, Min-Hsiang Huang and Min-Feng Sung
Electronics 2021, 10(20), 2531; https://doi.org/10.3390/electronics10202531 - 17 Oct 2021
Cited by 1 | Viewed by 3255
Abstract
Tire mileage and wear provide important information for vehicle applications. There are more and more studies discussing intelligent tires, but few focus on the role of tire mileage and wear. The conventional tire pressure monitoring system (TPMS) is one of the intelligent tire [...] Read more.
Tire mileage and wear provide important information for vehicle applications. There are more and more studies discussing intelligent tires, but few focus on the role of tire mileage and wear. The conventional tire pressure monitoring system (TPMS) is one of the intelligent tire applications, but there has been no significant advancement in recent years in this regard. In order to increase the additional functions of intelligent tire applications, we propose a method that estimates the mileage and wear information of tires. The proposed method uses a three-axis sensor and a Hall sensor to implement the function. The proposed method also has a low power design to reduce the power consumption of the Hall sensor. The experimental results show the trend of tire wear status, rendering this method effective. This method also requires more accurate mileage information to support tire wear estimation. This experiment found that the correct rate of the proposed mileage estimation method is 99.4% and provides sufficient and correct mileage information for tire wear methods. If this method is used in autonomous vehicle applications, the autonomous control strategy algorithm has more conditions to plan the control strategy. The strategy system processes more meticulous control that increases the safety of autonomous vehicles. Full article
(This article belongs to the Special Issue Automotive Electronics)
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