Electronics

19 pages, 4727 KiB

Open AccessFeature PaperEditor’s ChoiceReview

A Comprehensive Study on Simulation Techniques for 5G Networks: State of the Art Results, Analysis, and Future Challenges

by Panagiotis K. Gkonis, Panagiotis T. Trakadas and Dimitra I. Kaklamani

Electronics 2020, 9(3), 468; https://doi.org/10.3390/electronics9030468 - 11 Mar 2020

Cited by 59 | Viewed by 14209

Abstract

Ιn this review article, a comprehensive study is provided regarding the latest achievements in simulation techniques and platforms for fifth generation (5G) wireless cellular networks. In this context, the calculation of a set of diverse performance metrics, such as achievable throughput in uplink [...] Read more.

Ιn this review article, a comprehensive study is provided regarding the latest achievements in simulation techniques and platforms for fifth generation (5G) wireless cellular networks. In this context, the calculation of a set of diverse performance metrics, such as achievable throughput in uplink and downlink, the mean Bit Error Rate, the number of active users, outage probability, the handover rate, delay, latency, etc., can be a computationally demanding task due to the various parameters that should be incorporated in system and link level simulations. For example, potential solutions for 5G interfaces include, among others, millimeter Wave (mmWave) transmission, massive multiple input multiple output (MIMO) architectures and non-orthogonal multiple access (NOMA). Therefore, a more accurate and realistic representation of channel coefficients and overall interference is required compared to other cellular interfaces. In addition, the increased number of highly directional beams will unavoidably lead to increased signaling burden and handovers. Moreover, until a full transition to 5G networks takes place, coexistence with currently deployed fourth generation (4G) networks will be a challenging issue for radio network planning. Finally, the potential exploitation of 5G infrastructures in future electrical smart grids in order to support high bandwidth and zero latency applications (e.g., semi or full autonomous driving) dictates the need for the development of simulation environments able to incorporate the various and diverse aspects of 5G wireless cellular networks. Full article

(This article belongs to the Section Microwave and Wireless Communications)

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23 pages, 6932 KiB

Open AccessEditor’s ChoiceArticle

Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

by Boni García, Francisco Gortázar, Micael Gallego and Andrew Hines

Electronics 2020, 9(3), 462; https://doi.org/10.3390/electronics9030462 - 10 Mar 2020

Cited by 35 | Viewed by 9665

Abstract

WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of [...] Read more.

WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of different objective Full-Reference (FR) models for video and audio in WebRTC applications. FR models calculate the video and audio quality by comparing some original media reference with the degraded signal. To compute these models, we have created an open-source benchmark in which different types of reference media inputs are sent browser to browser while simulating different kinds of network conditions in terms of packet loss and jitter. Our benchmark provides recording capabilities of the impairment WebRTC streams. Then, we use different existing FR metrics for video (VMAF, VIFp, SSIM, MS-SSIM, PSNR, PSNR-HVS, and PSNR-HVS-M) and audio (PESQ, ViSQOL, and POLQA) recordings together with their references. Moreover, we use the same recordings to carry out a subjective analysis in which real users rate the video and audio quality using a Mean Opinion Score (MOS). Finally, we calculate the correlations between the objective and subjective results to find the objective models that better correspond with the subjective outcome, which is considered the ground truth QoE. We find that some of the studied objective models, such as VMAF, VIFp, and POLQA, show a strong correlation with the subjective results in packet loss scenarios. Full article

(This article belongs to the Section Computer Science & Engineering)

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17 pages, 4103 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Efficient Opportunistic Routing Protocol for Sensor Network in Emergency Applications

by Mohammed S. Al-kahtani, Lutful Karim and Nargis Khan

Electronics 2020, 9(3), 455; https://doi.org/10.3390/electronics9030455 - 8 Mar 2020

Cited by 8 | Viewed by 3293

Abstract

Routing or forwarding information, such as the location of incidents and victims in a disaster, is significantly important for quick and accurate incident response. However, forwarding such information in disaster areas has been a challenging task for the Wireless Sensor Network as existing [...] Read more.

Routing or forwarding information, such as the location of incidents and victims in a disaster, is significantly important for quick and accurate incident response. However, forwarding such information in disaster areas has been a challenging task for the Wireless Sensor Network as existing networks are affected (destroyed or overused) the disaster. Opportunistic information forwarding can play a vital role in such circumstances. Existing opportunistic routing protocols require huge message transmissions for cluster restoration, which is not energy efficient and results in packet loss. Hence, this paper introduces an energy efficient and reliable opportunistic density cluster-based routing protocol that opportunistically transmits data using a density-clustering protocol for emergency and disaster situations. Simulation results show that the proposed protocol outperforms some existing and well-known routing protocols in terms of network energy consumption, throughput and successful data transmissions. Full article

(This article belongs to the Special Issue Crowdsensing for Wireless Communication and Networking)

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18 pages, 6308 KiB

Open AccessEditor’s ChoiceArticle

Real-Time Vehicle Detection Framework Based on the Fusion of LiDAR and Camera

by Limin Guan, Yi Chen, Guiping Wang and Xu Lei

Electronics 2020, 9(3), 451; https://doi.org/10.3390/electronics9030451 - 7 Mar 2020

Cited by 38 | Viewed by 6554

Abstract

Vehicle detection is essential for driverless systems. However, the current single sensor detection mode is no longer sufficient in complex and changing traffic environments. Therefore, this paper combines camera and light detection and ranging (LiDAR) to build a vehicle-detection framework that has the [...] Read more.

Vehicle detection is essential for driverless systems. However, the current single sensor detection mode is no longer sufficient in complex and changing traffic environments. Therefore, this paper combines camera and light detection and ranging (LiDAR) to build a vehicle-detection framework that has the characteristics of multi adaptability, high real-time capacity, and robustness. First, a multi-adaptive high-precision depth-completion method was proposed to convert the 2D LiDAR sparse depth map into a dense depth map, so that the two sensors are aligned with each other at the data level. Then, the You Only Look Once Version 3 (YOLOv3) real-time object detection model was used to detect the color image and the dense depth map. Finally, a decision-level fusion method based on bounding box fusion and improved Dempster–Shafer (D–S) evidence theory was proposed to merge the two results of the previous step and obtain the final vehicle position and distance information, which not only improves the detection accuracy but also improves the robustness of the whole framework. We evaluated our method using the KITTI dataset and the Waymo Open Dataset, and the results show the effectiveness of the proposed depth completion method and multi-sensor fusion strategy. Full article

(This article belongs to the Section Electrical and Autonomous Vehicles)

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13 pages, 5200 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Thermal Analysis of a Parallel-Configured Battery Pack (1S18P) Using 21700 Cells for a Battery-Powered Train

by Taewoo Kang, Seongyun Park, Pyeong-Yeon Lee, In-Ho Cho, Kisoo Yoo and Jonghoon Kim

Electronics 2020, 9(3), 447; https://doi.org/10.3390/electronics9030447 - 6 Mar 2020

Cited by 17 | Viewed by 7049

Abstract

In this study, the thermal behavior of a 1S18P battery pack is examined based on the power demand during train propulsion between two stations. The proposed thermal prediction model is classified into Joules heating with equivalent resistance, reversible heat, and heat dissipation. The [...] Read more.

In this study, the thermal behavior of a 1S18P battery pack is examined based on the power demand during train propulsion between two stations. The proposed thermal prediction model is classified into Joules heating with equivalent resistance, reversible heat, and heat dissipation. The equivalent resistances are determined by 5% of the state of charge intervals using the hybrid pulse power characterization test. The power demand profile during train propulsion between two stations is provided by the Korea Railroad Research Institute. An experiment is conducted to examine the 1S18P battery pack thermal behavior during the propulsion between two stations. A comparison of the simulation and experiment results validated the proposed thermal model. Full article

(This article belongs to the Special Issue Challenges of Battery Management System)

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33 pages, 18710 KiB

Open AccessFeature PaperEditor’s ChoiceReview

An Extensive Review of Multilevel Inverters Based on Their Multifaceted Structural Configuration, Triggering Methods and Applications

by Suvetha Poyyamani Sunddararaj, Shriram Srinivasarangan Rangarajan and Subashini N

Electronics 2020, 9(3), 433; https://doi.org/10.3390/electronics9030433 - 5 Mar 2020

Cited by 71 | Viewed by 7560

Abstract

Power electronic converters are used to transform one form of energy to another. They are classified into four types depending upon the nature of the input and output voltages. The inverter is one among those types; it converts direct electrical current into alternating [...] Read more.

Power electronic converters are used to transform one form of energy to another. They are classified into four types depending upon the nature of the input and output voltages. The inverter is one among those types; it converts direct electrical current into alternating electrical current at desired frequency. Conventional types of inverters are capable of producing voltage at the output terminal that can only switch between two levels. The range of output voltage generated at the output is low when they are used for high power applications. To improve the voltage profile and efficiency of the overall system, multilevel inverters (MLIs) are introduced. In multilevel inverters the voltage at the output terminal is generated from several DC voltage levels fed at its input. The generated output is more appropriate to a sine wave and the dv/dt rating is also less leading to the reduction in EMI. Though they possess many advantages compared to the conventional inverters, the structural complexity and triggering techniques involved in designing multilevel inverters are high. Many studies are being carried out in defining new topologies of MLI with reduced switch as well as with the implementation of different PWM techniques. This paper will provide an extensive review on variety of MLI configurations based on the parameters such as the number of switches, switching techniques, symmetric, asymmetric, hybrid topologies, configurations based on applications, THD and power quality. Full article

(This article belongs to the Special Issue Multilevel Converters)

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14 pages, 4479 KiB

Open AccessEditor’s ChoiceArticle

Exploring the Impact of Variability in Resistance Distributions of RRAM on the Prediction Accuracy of Deep Learning Neural Networks

by Nagaraj Lakshmana Prabhu, Desmond Loy Jia Jun, Putu Andhita Dananjaya, Wen Siang Lew, Eng Huat Toh and Nagarajan Raghavan

Electronics 2020, 9(3), 414; https://doi.org/10.3390/electronics9030414 - 29 Feb 2020

Cited by 10 | Viewed by 3814

Abstract

In this work, we explore the use of the resistive random access memory (RRAM) device as a synapse for mimicking the trained weights linking neurons in a deep learning neural network (DNN) (AlexNet). The RRAM devices were fabricated in-house and subjected to 1000 [...] Read more.

In this work, we explore the use of the resistive random access memory (RRAM) device as a synapse for mimicking the trained weights linking neurons in a deep learning neural network (DNN) (AlexNet). The RRAM devices were fabricated in-house and subjected to 1000 bipolar read-write cycles to measure the resistances recorded for Logic-0 and Logic-1 (we demonstrate the feasibility of achieving eight discrete resistance states in the same device depending on the RESET stop voltage). DNN simulations have been performed to compare the relative error between the output of AlexNet Layer 1 (Convolution) implemented with the standard backpropagation (BP) algorithm trained weights versus the weights that are encoded using the measured resistance distributions from RRAM. The IMAGENET dataset is used for classification purpose here. We focus only on the Layer 1 weights in the AlexNet framework with 11 × 11 × 96 filters values coded into a binary floating point and substituted with the RRAM resistance values corresponding to Logic-0 and Logic-1. The impact of variability in the resistance states of RRAM for the low and high resistance states on the accuracy of image classification is studied by formulating a look-up table (LUT) for the RRAM (from measured I-V data) and comparing the convolution computation output of AlexNet Layer 1 with the standard outputs from the BP-based pre-trained weights. This is one of the first studies dedicated to exploring the impact of RRAM device resistance variability on the prediction accuracy of a convolutional neural network (CNN) on an AlexNet platform through a framework that requires limited actual device switching test data. Full article

(This article belongs to the Special Issue Challenges and Applications of Non-volatile Memory)

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9 pages, 1408 KiB

Open AccessEditor’s ChoiceArticle

Edge Computing Robot Interface for Automatic Elderly Mental Health Care Based on Voice

by Camille Yvanoff-Frenchin, Vitor Ramos, Tarek Belabed and Carlos Valderrama

Electronics 2020, 9(3), 419; https://doi.org/10.3390/electronics9030419 - 29 Feb 2020

Cited by 10 | Viewed by 3735

Abstract

We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping to evaluate the mental health [...] Read more.

We need open platforms driven by specialists, in which queries can be created and collected for long periods and the diagnosis made based on a rigorous clinical follow-up. In this work, we developed a multi-language robot interface helping to evaluate the mental health of seniors by interacting through questions. Through the voice interface, the specialist can propose questions, as well as receive users’ answers, in text form. The robot can automatically interact with the user using the appropriate language. It can process the answers and under the guidance of a specialist, questions and answers can be oriented towards the desired therapy direction. The prototype was implemented on an embedded device meant for edge computing, thus it was able to filter environmental noise and can be placed anywhere at home. The proposed platform allows the integration of well-known open source and commercial data flow processing frameworks. The experience is now available for specialists to create queries and answers through a Web-based interface. Full article

(This article belongs to the Section Bioelectronics)

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17 pages, 7045 KiB

Open AccessEditor’s ChoiceArticle

Field Modeling the Impact of Cracks on the Electroconductivity of Thin-Film Textronic Structures

by Stanisław Pawłowski, Jolanta Plewako and Ewa Korzeniewska

Electronics 2020, 9(3), 402; https://doi.org/10.3390/electronics9030402 - 28 Feb 2020

Cited by 22 | Viewed by 2820

Abstract

Wearable electronics are produced by depositing thin electroconductive layers with low resistance on flexible substrates. In the process of producing such metallic films, as well as during their usage, structural defects may appear which affect their electrical properties. In this paper, we present [...] Read more.

Wearable electronics are produced by depositing thin electroconductive layers with low resistance on flexible substrates. In the process of producing such metallic films, as well as during their usage, structural defects may appear which affect their electrical properties. In this paper, we present analytical and numerical models for understanding phenomena related to the electrical conductivity of thin electroconductive layers. The algorithm in the numerical model is based on the boundary integral equation method. The formulas enable calculation of the potential distribution and electric field strength of the analyzed structures, and describe the impact of cracks on their electrical resistance. The validity of the proposed models was verified by experimental results. Full article

(This article belongs to the Section Microelectronics)

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24 pages, 7336 KiB

Open AccessEditor’s ChoiceArticle

A Buck-Boost Transformerless DC–DC Converter Based on IGBT Modules for Fast Charge of Electric Vehicles

by Borislav Dimitrov, Khaled Hayatleh, Steve Barker, Gordana Collier, Suleiman Sharkh and Andrew Cruden

Electronics 2020, 9(3), 397; https://doi.org/10.3390/electronics9030397 - 28 Feb 2020

Cited by 22 | Viewed by 18312

Abstract

A transformer-less Buck-Boost direct current–direct current (DC–DC) converter in use for the fast charge of electric vehicles, based on powerful high-voltage isolated gate bipolar transistor (IGBT) modules is analyzed, designed and experimentally verified. The main advantages of this topology are: simple structure on [...] Read more.

A transformer-less Buck-Boost direct current–direct current (DC–DC) converter in use for the fast charge of electric vehicles, based on powerful high-voltage isolated gate bipolar transistor (IGBT) modules is analyzed, designed and experimentally verified. The main advantages of this topology are: simple structure on the converter’s power stage; a wide range of the output voltage, capable of supporting contemporary vehicles’ on-board battery packs; efficiency; and power density accepted to be high enough for such a class of hard-switched converters. A precise estimation of the loss, dissipated in the converter’s basic modes of operation Buck, Boost, and Buck-Boost is presented. The analysis shows an approach of loss minimization, based on switching frequency reduction during the Buck-Boost operation mode. Such a technique guarantees stable thermal characteristics during the entire operation, i.e., battery charge cycle. As the Buck-Boost mode takes place when Buck and Boost modes cannot support the output voltage, operating as a combination of them, it can be considered as critically dependent on the characteristics of the semiconductors. With this, the necessary duty cycle and voltage range, determined with respect to the input-output voltages and power losses, require an additional study to be conducted. Additionally, the tolerance of the applied switching frequencies for the most versatile silicon-based powerful IGBT modules is analyzed and experimentally verified. Finally, several important characteristics, such as transients during switch-on and switch-off, IGBTs’ voltage tails, critical duty cycles, etc., are depicted experimentally with oscillograms, obtained by an experimental model. Full article

(This article belongs to the Section Electrical and Autonomous Vehicles)

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17 pages, 794 KiB

Open AccessEditor’s ChoiceArticle

Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm

by Irshad Hussain, Majid Ullah, Ibrar Ullah, Asima Bibi, Muhammad Naeem, Madhusudan Singh and Dhananjay Singh

Electronics 2020, 9(3), 406; https://doi.org/10.3390/electronics9030406 - 28 Feb 2020

Cited by 71 | Viewed by 6675

Abstract

Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the [...] Read more.

Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case. Full article

(This article belongs to the Special Issue Transforming Future Cities: Smart City)

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15 pages, 5869 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

SEEK: A Framework of Superpixel Learning with CNN Features for Unsupervised Segmentation

by Talha Ilyas, Abbas Khan, Muhammad Umraiz and Hyongsuk Kim

Electronics 2020, 9(3), 383; https://doi.org/10.3390/electronics9030383 - 25 Feb 2020

Cited by 22 | Viewed by 5836

Abstract

Supervised semantic segmentation algorithms have been a hot area of exploration recently, but now the attention is being drawn towards completely unsupervised semantic segmentation. In an unsupervised framework, neither the targets nor the ground truth labels are provided to the network. That being [...] Read more.

Supervised semantic segmentation algorithms have been a hot area of exploration recently, but now the attention is being drawn towards completely unsupervised semantic segmentation. In an unsupervised framework, neither the targets nor the ground truth labels are provided to the network. That being said, the network is unaware about any class instance or object present in the given data sample. So, we propose a convolutional neural network (CNN) based architecture for unsupervised segmentation. We used the squeeze and excitation network, due to its peculiar ability to capture the features’ interdependencies, which increases the network’s sensitivity to more salient features. We iteratively enable our CNN architecture to learn the target generated by a graph-based segmentation method, while simultaneously preventing our network from falling into the pit of over-segmentation. Along with this CNN architecture, image enhancement and refinement techniques are exploited to improve the segmentation results. Our proposed algorithm produces improved segmented regions that meet the human level segmentation results. In addition, we evaluate our approach using different metrics to show the quantitative outperformance. Full article

(This article belongs to the Special Issue Deep Neural Networks and Their Applications)

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27 pages, 5201 KiB

Open AccessEditor’s ChoiceArticle

EARL—Embodied Agent-Based Robot Control Systems Modelling Language

by Tomasz Winiarski, Maciej Węgierek, Dawid Seredyński, Wojciech Dudek, Konrad Banachowicz and Cezary Zieliński

Electronics 2020, 9(2), 379; https://doi.org/10.3390/electronics9020379 - 24 Feb 2020

Cited by 13 | Viewed by 5018

Abstract

The paper presents the Embodied Agent-based Robot control system modelling Language (EARL). EARL follows a Model-Driven Software Development approach (MDSD), which facilitates robot control system development. It is based on a mathematical method of robot controller specification, employing the concept of an Embodied [...] Read more.

The paper presents the Embodied Agent-based Robot control system modelling Language (EARL). EARL follows a Model-Driven Software Development approach (MDSD), which facilitates robot control system development. It is based on a mathematical method of robot controller specification, employing the concept of an Embodied Agent, and a graphical modelling language: System Modelling Language (SysML). It combines the ease of use of SysML with the precision of mathematical specification of certain aspects of the designed system. It makes the whole system specification effective, from the point of view of the time needed to create it, conciseness of the specification and the possibility of its analysis. By using EARL it is possible to specify systems both with fixed and variable structure. This was achieved by introducing a generalised system model and presenting particular structures of the system in terms of modelling block configurations adapted by using instances. FABRIC framework was created to support the implementation of EARL-based controllers. EARL is compatible with component based robotic middlewares (e.g., ROS and Orocos). Full article

(This article belongs to the Section Systems & Control Engineering)

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26 pages, 11344 KiB

Open AccessEditor’s ChoiceArticle

Automatic Control and Model Verification for a Small Aileron-Less Hand-Launched Solar-Powered Unmanned Aerial Vehicle

by An Guo, Zhou Zhou, Xiaoping Zhu, Xin Zhao and Yuxin Ding

Electronics 2020, 9(2), 364; https://doi.org/10.3390/electronics9020364 - 21 Feb 2020

Cited by 6 | Viewed by 3835

Abstract

This paper describes a low-cost flight control system of a small aileron-less hand-launched solar-powered unmanned aerial vehicle (UAV). In order to improve the accuracy of the whole system model and quantify the influence of each subsystem, detailed modeling of UAV energy and a [...] Read more.

This paper describes a low-cost flight control system of a small aileron-less hand-launched solar-powered unmanned aerial vehicle (UAV). In order to improve the accuracy of the whole system model and quantify the influence of each subsystem, detailed modeling of UAV energy and a control system including a solar model, engine, energy storage, sensors, state estimation, control law, and actuator module are established in accordance with the experiment and component principles. A whole system numerical simulation combined with the 6 degree-of-freedom (DOF) simulation model is constructed based on the typical mission route, and the parameter precision sequence and energy balance are obtained. Then, a hardware-in-the-loop (HIL) experiment scheme based on the Stewart platform (SP) is proposed, and three modes of acceleration, angular velocity, and attitude are designed to verify the control system through the inner and boundary states of the flight envelope. The whole system scheme is verified by flight tests at different altitudes, and the aerodynamic force coefficient and sensor error are corrected by flight data. With the increase of altitude, the cruise power increases from 47 W to 78 W, the trajectory tracking precision increases from 23 m to 44 m, the sensor measurement noise increases, and the bias decreases. Full article

(This article belongs to the Special Issue Autonomous Vehicles Technology)

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22 pages, 8149 KiB

Open AccessEditor’s ChoiceArticle

Realization of the Sensorless Permanent Magnet Synchronous Motor Drive Control System with an Intelligent Controller

by Hung-Khong Hoai, Seng-Chi Chen and Hoang Than

Electronics 2020, 9(2), 365; https://doi.org/10.3390/electronics9020365 - 21 Feb 2020

Cited by 32 | Viewed by 8460

Abstract

This paper presents the sensorless control algorithm for a permanent magnet synchronous motor (PMSM) drive system with the estimator and the intelligent controller. The estimator is constructed on the novel sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate [...] Read more.

This paper presents the sensorless control algorithm for a permanent magnet synchronous motor (PMSM) drive system with the estimator and the intelligent controller. The estimator is constructed on the novel sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the position and speed of the rotor. The intelligent controller is a radial basis function neural network (RBFNN)-based self-tuning PID (Proportional-Integral-Derivative) controller, applied to the velocity control loop of the PMSM drive control system to adapt strongly to dynamic characteristics during the operation with an external load. The I-f startup strategy is adopted to accelerate the motor from standstill, then switches to the sensorless mode smoothly. The control algorithm program is based on MATLAB and can be executed in simulations and experiments. The control system performance is verified on an experimental platform with various speeds and the dynamic load, in which the specified I-f startup mode and sensorless mode, inspected by tracking response and speed regulation. The simulation and experimental results demonstrate that the proposed method has worked successfully. The motor control system has smooth switching, good tracking response, and robustness against disturbance. Full article

(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)

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17 pages, 12191 KiB

Open AccessEditor’s ChoiceArticle

Novel Design and Adaptive Fuzzy Control of a Lower-Limb Elderly Rehabilitation

by Xin Zhang, Jiehao Li, Salih Ertug Ovur, Ziyang Chen, Xiangnan Li, Zhenhuan Hu and Yingbai Hu

Electronics 2020, 9(2), 343; https://doi.org/10.3390/electronics9020343 - 17 Feb 2020

Cited by 20 | Viewed by 3881

Abstract

Design and control of a lower-limb exoskeleton rehabilitation of the elderly are the main challenge for health care in the past decades. In order to satisfy the requirements of the elderly or disabled users, this paper presents a novel design and adaptive fuzzy [...] Read more.

Design and control of a lower-limb exoskeleton rehabilitation of the elderly are the main challenge for health care in the past decades. In order to satisfy the requirements of the elderly or disabled users, this paper presents a novel design and adaptive fuzzy control of lower-limb empowered rehabilitation, namely MOVING UP. Different from other rehabilitation devices, this article considers active rehabilitation training devices. Firstly, a novel product design method based on user experience is proposed for the lower-limb elderly exoskeleton rehabilitation. At the same time, in order to achieve a stable operation control for the assistant rehabilitation system, an adaptive fuzzy control scheme is discussed. Finally, the feasibility of the design and control method is validated with a detailed simulation study and the human-interaction test. With the booming demand in the global market for the assistive lower-limb exoskeleton, the methodology developed in this paper will bring more research and manufacturing interests. Full article

(This article belongs to the Section Systems & Control Engineering)

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14 pages, 5053 KiB

Open AccessEditor’s ChoiceArticle

Efficient Systolic-Array Redundancy Architecture for Offline/Online Repair

by Keewon Cho, Ingeol Lee, Hyeonchan Lim and Sungho Kang

Electronics 2020, 9(2), 338; https://doi.org/10.3390/electronics9020338 - 15 Feb 2020

Cited by 5 | Viewed by 10187

Abstract

Neural-network computing has revolutionized the field of machine learning. The systolic-array architecture is a widely used architecture for neural-network computing acceleration that was adopted by Google in its Tensor Processing Unit (TPU). To ensure the correct operation of the neural network, the reliability [...] Read more.

Neural-network computing has revolutionized the field of machine learning. The systolic-array architecture is a widely used architecture for neural-network computing acceleration that was adopted by Google in its Tensor Processing Unit (TPU). To ensure the correct operation of the neural network, the reliability of the systolic-array architecture should be guaranteed. This paper proposes an efficient systolic-array redundancy architecture that is based on systolic-array partitioning and rearranging connections of the systolic-array elements. The proposed architecture allows both offline and online repair with an extended redundancy architecture and programmable fuses and can ensure reliability even in an online situation, for which the previous fault-tolerant schemes have not been considered. Full article

(This article belongs to the Special Issue Hardware and Architecture Ⅱ)

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15 pages, 3279 KiB

Open AccessEditor’s ChoiceArticle

Bidirectional Short-Circuit Current Blocker for DC Microgrid Based on Solid-State Circuit Breaker

by Lujun Wang, Boyu Feng, Yu Wang, Tiezhou Wu and Huipin Lin

Electronics 2020, 9(2), 306; https://doi.org/10.3390/electronics9020306 - 10 Feb 2020

Cited by 39 | Viewed by 5589

Abstract

In order to solve the imminent problem in that the traditional protection strategy cannot meet time requirements, together with the fact that the rotational inertia of a DC microgrid is small and short-circuit fault develops rapidly, a bidirectional short-circuit current blocker (BSCCB) based [...] Read more.

In order to solve the imminent problem in that the traditional protection strategy cannot meet time requirements, together with the fact that the rotational inertia of a DC microgrid is small and short-circuit fault develops rapidly, a bidirectional short-circuit current blocker (BSCCB) based on solid-state circuit breaker for a DC microgrid is proposed. Firstly, the bidirectional current blocking circuit structure is proposed based on the analysis of key components. Then, a top-level differential protection strategy is developed based on the aforementioned proposal. Finally, the performance of the blocking circuit is simulated and verified by experiments. The results show that the proposed method can block short-circuit current within 4 ms, and the response speed of the protection strategy is very fast compared with previous approaches. BSCCB also has reclosing, bidirectional blocking and energy releasing functions. The current blocker proposed in this paper can be reused multiple times and has a promising future in low-voltage DC microgrid application. Full article

(This article belongs to the Section Power Electronics)

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18 pages, 1183 KiB

Open AccessEditor’s ChoiceArticle

Fuzzy Analytic Hierarchy Process-Based Mobile Robot Path Planning

by Changwon Kim, Yeesock Kim and Hak Yi

Electronics 2020, 9(2), 290; https://doi.org/10.3390/electronics9020290 - 8 Feb 2020

Cited by 26 | Viewed by 4105

Abstract

This study presents a new path planning method based on Fuzzy Analytic Hierarchy Process (FAHP) for a mobile robot to be effectively operated through a multi-objective decision making problem. Unlike typical AHP, the proposed FAHP has a difference in using triangulation fuzzy number [...] Read more.

This study presents a new path planning method based on Fuzzy Analytic Hierarchy Process (FAHP) for a mobile robot to be effectively operated through a multi-objective decision making problem. Unlike typical AHP, the proposed FAHP has a difference in using triangulation fuzzy number based extent analysis to derive weight vectors among the considerations. FAHP framework for finding the optimal position in this study is defined with the highest level (goal), middle level (objectives), and the lowest level (alternatives). It analytically selects an optimal position as a sub-goal among points on the sensing boundary of the mobile robot considering the three objectives: the travel distance to the target, robot’s rotation, and safety against collision between obstacles. Alternative solutions are evaluated by quantifying the relative importance for the objectives. Comparative results obtained from the artificial potential field, AHP, and FAHP simulations show that FAHP is much preferable for mobile robot’s path planning than typical AHP. Full article

(This article belongs to the Special Issue Sensor-Based Navigation and Control with Applications)

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12 pages, 7362 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Design and Implementation of a Digital Dual Orthogonal Outputs Chaotic Oscillator

by Yves Berviller, Etienne Tisserand, Philippe Poure and Hassan Rabah

Electronics 2020, 9(2), 264; https://doi.org/10.3390/electronics9020264 - 5 Feb 2020

Cited by 1 | Viewed by 4436

Abstract

Discrete time dynamical chaotic systems obey a set of recurrence equations involving one or more variables. Many chaotic maps have been proposed. None that simultaneously provides two sine–cosine outputs has stationary mean and standard deviation, or is quite robust with respect to the [...] Read more.

Discrete time dynamical chaotic systems obey a set of recurrence equations involving one or more variables. Many chaotic maps have been proposed. None that simultaneously provides two sine–cosine outputs has stationary mean and standard deviation, or is quite robust with respect to the data format used in the hardware implementation. Here, we propose a chaotic oscillator based on a complex phasor whose angular argument evolves according to a geometric progression that is independent of the instantaneous amplitude. In order to maintain the oscillations, the phasor magnitude is normalized at each iteration using an approximation factor. The statistical characteristics of this oscillator are stationary in the short term, and do not depend on the initial conditions. The mean and standard deviation of the two orthogonal sequences quickly approach 0 and

1 / \sqrt{2}

, respectively. The resulting distribution is similar to that of a digital sine with a constant angular step. We also present an FPGA architecture and its implementation results. This oscillator can be used in modulation schemes, such as the chaotic shift keying one or for data and image encryption. Finally, we show an original application that exploits the orthogonality of the two chaotic signals for the simultaneous encryption of two digital images. Full article

(This article belongs to the Special Issue Multidimensional Digital Signal Processing)

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16 pages, 7713 KiB

Open AccessEditor’s ChoiceArticle

Early Detection of Diabetic Retinopathy Using PCA-Firefly Based Deep Learning Model

by Thippa Reddy Gadekallu, Neelu Khare, Sweta Bhattacharya, Saurabh Singh, Praveen Kumar Reddy Maddikunta, In-Ho Ra and Mamoun Alazab

Electronics 2020, 9(2), 274; https://doi.org/10.3390/electronics9020274 - 5 Feb 2020

Cited by 268 | Viewed by 14452

Abstract

Diabetic Retinopathy is a major cause of vision loss and blindness affecting millions of people across the globe. Although there are established screening methods - fluorescein angiography and optical coherence tomography for detection of the disease but in majority of the cases, the [...] Read more.

Diabetic Retinopathy is a major cause of vision loss and blindness affecting millions of people across the globe. Although there are established screening methods - fluorescein angiography and optical coherence tomography for detection of the disease but in majority of the cases, the patients remain ignorant and fail to undertake such tests at an appropriate time. The early detection of the disease plays an extremely important role in preventing vision loss which is the consequence of diabetes mellitus remaining untreated among patients for a prolonged time period. Various machine learning and deep learning approaches have been implemented on diabetic retinopathy dataset for classification and prediction of the disease but majority of them have neglected the aspect of data pre-processing and dimensionality reduction, leading to biased results. The dataset used in the present study is a diabetes retinopathy dataset collected from the UCI machine learning repository. At its inceptions, the raw dataset is normalized using the Standardscalar technique and then Principal Component Analysis (PCA) is used to extract the most significant features in the dataset. Further, Firefly algorithm is implemented for dimensionality reduction. This reduced dataset is fed into a Deep Neural Network Model for classification. The results generated from the model is evaluated against the prevalent machine learning models and the results justify the superiority of the proposed model in terms of Accuracy, Precision, Recall, Sensitivity and Specificity. Full article

(This article belongs to the Special Issue Deep Neural Networks and Their Applications)

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15 pages, 14204 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A New CPW-Fed Diversity Antenna for MIMO 5G Smartphones

by Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Yasir I. A. Al-Yasir, Ahmed M. Abdulkhaleq, Mohammad Patwary and Raed A. Abd-Alhameed

Electronics 2020, 9(2), 261; https://doi.org/10.3390/electronics9020261 - 4 Feb 2020

Cited by 61 | Viewed by 5067

Abstract

In this study, a new coplanar waveguide (CPW)-fed diversity antenna design is introduced for multiple-input–multiple-output (MIMO) smartphone applications. The diversity antenna is composed of a double-fed CPW-fed antenna with a pair of modified T-ring radiators. The antenna is designed to cover the frequency [...] Read more.

In this study, a new coplanar waveguide (CPW)-fed diversity antenna design is introduced for multiple-input–multiple-output (MIMO) smartphone applications. The diversity antenna is composed of a double-fed CPW-fed antenna with a pair of modified T-ring radiators. The antenna is designed to cover the frequency spectrum of commercial sub-6 GHz 5G communication (3.4–3.8 and 3.8–4.2 GHz). It also provides high isolation, better than −16 dB, without an additional decoupling structure. It offers good potential to be deployed in future smartphones. Therefore, the characteristics and performance of an 8-port 5G smartphone antenna were investigated using four pairs of the proposed diversity antennas. Due to the compact size and also the placement of the elements, the presented CPW-fed smartphone antenna array design occupies a very small part of the smartphone board. Its operation band spans from 3.4 to 4.4 GHz. The simulated results agree well with measured results, and the performance of the smartphone antenna design in the presence of a user is given in this paper as well. The proposed MIMO design provides not only sufficient radiation coverage supporting different sides of the mainboard but also polarization diversity. Full article

(This article belongs to the Special Issue Recent Technical Developments in Energy-Efficient 5G Mobile Cells)

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18 pages, 2953 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Complex Bianisotropy Effect on the Propagation Constant of a Shielded Multilayered Coplanar Waveguide Using Improved Full Generalized Exponential Matrix Technique

by Djamel Sayad, Chemseddine Zebiri, Issa Elfergani, Jonathan Rodriguez, Hasan Abobaker, Atta Ullah, Raed Abd-Alhameed, Ifiok Otung and Fatiha Benabdelaziz

Electronics 2020, 9(2), 243; https://doi.org/10.3390/electronics9020243 - 2 Feb 2020

Cited by 11 | Viewed by 3232

Abstract

A theoretical study of the electromagnetic propagation in a complex medium suspended multilayer coplanar waveguide (CPW) is presented. The study is based on the generalized exponential matrix technique (GEMT) combined with Galerkin’s spectral method of moments applied to a CPW printed on a [...] Read more.

A theoretical study of the electromagnetic propagation in a complex medium suspended multilayer coplanar waveguide (CPW) is presented. The study is based on the generalized exponential matrix technique (GEMT) combined with Galerkin’s spectral method of moments applied to a CPW printed on a bianisotropic medium. The analytical formulation is based on a Full-GEMT, a method that avoids usual procedures of heavy and tedious mathematical expressions in the development of calculations and uses matrix-based mathematical expressions instead. These particularities are exploited to develop a mathematical model for the characterization of wave propagation in a three-layer shielded suspended CPW structure. This study is based on the development of mathematical formulations in full compact matrix-based expressions resulting in Green’s functions in a matrix form. The implemented method incorporates a new accelerating procedure developed in the GEMT which provides an initial value used to speed up searching for the exact solution in the principal computation code. This helped us to obtain accurate solutions with tolerable computing time. Good agreements have been achieved with the literature in terms of accuracy and rapid convergence. The results for different cases of bianisotropy have been investigated, and particularly, the effect on the dispersion characteristics is presented and compared with the isotropic case. Full article

(This article belongs to the Special Issue Recent Technical Developments in Energy-Efficient 5G Mobile Cells)

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18 pages, 4138 KiB

Open AccessEditor’s ChoiceArticle

Method of Moments Based on Equivalent Periodic Problem and FFT with NURBS Surfaces for Analysis of Multilayer Periodic Structures

by Rafael Florencio, Álvaro Somolinos, Iván González and Felipe Cátedra

Electronics 2020, 9(2), 234; https://doi.org/10.3390/electronics9020234 - 31 Jan 2020

Cited by 3 | Viewed by 2819

Abstract

In this paper, an efficient technique of computation of method of moments (MM) matrix entries for multilayer periodic structures with NURBS surface and Bézier patches modelling is proposed. An approximation in terms of constant pulses of generalized rooftop basis functions (BFs) defined on [...] Read more.

In this paper, an efficient technique of computation of method of moments (MM) matrix entries for multilayer periodic structures with NURBS surface and Bézier patches modelling is proposed. An approximation in terms of constant pulses of generalized rooftop basis functions (BFs) defined on Bézier patches is proposed. This approximation leads discrete convolutions instead of usual continuous convolution between Green’s functions and BFs obtained by the direct mixed potential integral equation (MPIE) approach. An equivalent periodic problem (EPP) which contains the original problem is proposed to transform the discrete convolutions in discrete cyclic convolutions. The resultant discrete cyclic convolutions are computed by efficiently using the Fast Fourier Transform (FFT) procedure. The performance of the proposed method and direct computation of the MM entries are compared for phases of reflection coefficient. The proposed method is between 9 and 50 times faster than the direct computation for phase errors less than 1 deg. The proposed method exhibits a behaviour of CPU time consumption of O(N_bLog10N_b) as the number N_b of BFs increases. This behaviour provides significant CPU time savings with respect to the expected behaviour of O(N_b²) provided by the direct computation of the MM matrix entries. Full article

(This article belongs to the Special Issue Numerical Methods and Measurements in Antennas and Propagation)

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28 pages, 3735 KiB

Open AccessEditor’s ChoiceArticle

On Implementing Optimal Energy Management for EREV Using Distance Constrained Adaptive Real-Time Dynamic Programming

by Aman V. Kalia and Brian C. Fabien

Electronics 2020, 9(2), 228; https://doi.org/10.3390/electronics9020228 - 30 Jan 2020

Cited by 13 | Viewed by 4681

Abstract

Extended range electric vehicles (EREVs) operate both as an electric vehicle (EV) and as a hybrid electric vehicle (HEV). As a hybrid, the on-board range extender (REx) system provides additional energy to increase the feasible driving range. In this paper, we evaluate an [...] Read more.

Extended range electric vehicles (EREVs) operate both as an electric vehicle (EV) and as a hybrid electric vehicle (HEV). As a hybrid, the on-board range extender (REx) system provides additional energy to increase the feasible driving range. In this paper, we evaluate an experimental research EREV based on the 2016 Chevrolet Camaro platform for optimal energy management control. We use model-in-loop and software-in-loop environments to validate the data-driven power loss model of the research vehicle. A discussion on the limitations of conventional energy management control algorithms is presented. We then propose our algorithm derived from adaptive real-time dynamic programming (ARTDP) with a distance constraint for energy consumption optimization. To achieve a near real-time functionality, the algorithm recomputes optimal parameters by monitoring the energy storage system’s (ESS) state of charge deviations from the previously computed optimal trajectory. The proposed algorithm is adaptable to variability resulting from driving behavior or system limitations while maintaining the target driving range. The net energy consumption evaluation shows a maximum improvement of 9.8% over the conventional charge depleting/charge sustaining (CD/CS) algorithm used in EREVs. Thus, our proposed algorithm shows adaptability and fault tolerance while being close to the global optimal solution. Full article

(This article belongs to the Special Issue Optimization-Based Energy Management Strategy for Hybrid-Electric Vehicles)

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26 pages, 1505 KiB

Open AccessEditor’s ChoiceReview

The Mechanical Effects Influencing on the Design of RF MEMS Switches

by Igor E. Lysenko, Alexey V. Tkachenko, Olga A. Ezhova, Boris G. Konoplev, Eugeny A. Ryndin and Elena V. Sherova

Electronics 2020, 9(2), 207; https://doi.org/10.3390/electronics9020207 - 22 Jan 2020

Cited by 17 | Viewed by 5703

Abstract

Radio-frequency switches manufactured by microelectromechanical systems technology are now widely used in aerospace systems and other mobile installations for various purposes. In these operating conditions, these devices are often exposed to intense mechanical environmental influences that have a strong impact on their operation. [...] Read more.

Radio-frequency switches manufactured by microelectromechanical systems technology are now widely used in aerospace systems and other mobile installations for various purposes. In these operating conditions, these devices are often exposed to intense mechanical environmental influences that have a strong impact on their operation. These negative effects can lead to unwanted short-circuit or open-circuit in the radio-frequency transmission line or to irreversible damage to structural elements. Such a violation in the operation of radio-frequency microelectromechanical switches leads to errors and improper functioning of the electronic equipment in which they are integrated. Thus, this review is devoted to the analysis of the origin of these negative intense mechanical effects of the environment, their classification, and analysis, as well as a review of methods to reduce or prevent their negative impact on the design of radio-frequency microelectromechanical switches. Full article

(This article belongs to the Special Issue Progress in MEMS/NEMS Devices)

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18 pages, 1588 KiB

Open AccessEditor’s ChoiceArticle

Hybrid Intrusion Detection System Based on the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support Vector Machine

by Ansam Khraisat, Iqbal Gondal, Peter Vamplew, Joarder Kamruzzaman and Ammar Alazab

Electronics 2020, 9(1), 173; https://doi.org/10.3390/electronics9010173 - 17 Jan 2020

Cited by 137 | Viewed by 13257

Abstract

Cyberttacks are becoming increasingly sophisticated, necessitating the efficient intrusion detection mechanisms to monitor computer resources and generate reports on anomalous or suspicious activities. Many Intrusion Detection Systems (IDSs) use a single classifier for identifying intrusions. Single classifier IDSs are unable to achieve high [...] Read more.

Cyberttacks are becoming increasingly sophisticated, necessitating the efficient intrusion detection mechanisms to monitor computer resources and generate reports on anomalous or suspicious activities. Many Intrusion Detection Systems (IDSs) use a single classifier for identifying intrusions. Single classifier IDSs are unable to achieve high accuracy and low false alarm rates due to polymorphic, metamorphic, and zero-day behaviors of malware. In this paper, a Hybrid IDS (HIDS) is proposed by combining the C5 decision tree classifier and One Class Support Vector Machine (OC-SVM). HIDS combines the strengths of SIDS) and Anomaly-based Intrusion Detection System (AIDS). The SIDS was developed based on the C5.0 Decision tree classifier and AIDS was developed based on the one-class Support Vector Machine (SVM). This framework aims to identify both the well-known intrusions and zero-day attacks with high detection accuracy and low false-alarm rates. The proposed HIDS is evaluated using the benchmark datasets, namely, Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) and Australian Defence Force Academy (ADFA) datasets. Studies show that the performance of HIDS is enhanced, compared to SIDS and AIDS in terms of detection rate and low false-alarm rates. Full article

(This article belongs to the Special Issue Machine Learning Techniques for Intelligent Intrusion Detection Systems)

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14 pages, 5000 KiB

Open AccessEditor’s ChoiceArticle

Application of a Stub-Loaded Square Ring Resonator for Wideband Bandpass Filter Design

by Ping Zhang, Liqin Liu, Deli Chen, Min-Hang Weng and Ru-Yuan Yang

Electronics 2020, 9(1), 176; https://doi.org/10.3390/electronics9010176 - 17 Jan 2020

Cited by 20 | Viewed by 3851

Abstract

In this paper, a stub-loaded square ring resonator (SLSRR) is analyzed and applied to design a very simple and compact wideband bandpass filter structure. Resonant modes dependent on the structure parameters of the SLSRR are analyzed first, and then the first two modes [...] Read more.

In this paper, a stub-loaded square ring resonator (SLSRR) is analyzed and applied to design a very simple and compact wideband bandpass filter structure. Resonant modes dependent on the structure parameters of the SLSRR are analyzed first, and then the first two modes are used to achieve a required passband. The input and output terminals are supplied with high impedance and strong coupling to provide sufficient coupling energy. Two wideband filter examples are designed, manufactured, and measured using the SLSRRs. The first filter is a wideband filter with a wide upper stopband, and the second filter is a dual wideband filter with a notched stopband between two passbands. The two filter examples are designed, fabricated, and measured to verify the design concept and present the advantages of easy design and a simple and compact structure. Full article

(This article belongs to the Special Issue RF/Mm-Wave Circuits Design and Applications)

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14 pages, 2705 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Design and Validation of 100 nm GaN-On-Si Ka-Band LNA Based on Custom Noise and Small Signal Models

by Lorenzo Pace, Sergio Colangeli, Walter Ciccognani, Patrick Ettore Longhi, Ernesto Limiti, Remy Leblanc, Marziale Feudale and Fabio Vitobello

Electronics 2020, 9(1), 150; https://doi.org/10.3390/electronics9010150 - 13 Jan 2020

Cited by 24 | Viewed by 4653

Abstract

In this paper a GaN-on-Si MMIC Low-Noise Amplifier (LNA) working in the Ka-band is shown. The chosen technology for the design is a 100 nm gate length HEMT provided by OMMIC foundry. Both small-signal and noise models had been previously extracted by the [...] Read more.

In this paper a GaN-on-Si MMIC Low-Noise Amplifier (LNA) working in the Ka-band is shown. The chosen technology for the design is a 100 nm gate length HEMT provided by OMMIC foundry. Both small-signal and noise models had been previously extracted by the means of an extensive measurement campaign, and were then employed in the design of the presented LNA. The amplifier presents an average noise figure of 2.4 dB, a 30 dB average gain value, and input/output matching higher than 10 dB in the whole 34–37.5 Ghz design band, while non-linear measurements testify a minimum output 1 dB compression point of 23 dBm in the specific 35–36.5 GHz target band. This shows the suitability of the chosen technology for low-noise applications. Full article

(This article belongs to the Section Microelectronics)

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19 pages, 3531 KiB

Open AccessEditor’s ChoiceArticle

Towards a Lightweight Detection System for Cyber Attacks in the IoT Environment Using Corresponding Features

by Yan Naung Soe, Yaokai Feng, Paulus Insap Santosa, Rudy Hartanto and Kouichi Sakurai

Electronics 2020, 9(1), 144; https://doi.org/10.3390/electronics9010144 - 11 Jan 2020

Cited by 85 | Viewed by 6933

Abstract

The application of a large number of Internet of Things (IoT) devices makes our life more convenient and industries more efficient. However, it also makes cyber-attacks much easier to occur because so many IoT devices are deployed and most of them do not [...] Read more.

The application of a large number of Internet of Things (IoT) devices makes our life more convenient and industries more efficient. However, it also makes cyber-attacks much easier to occur because so many IoT devices are deployed and most of them do not have enough resources (i.e., computation and storage capacity) to carry out ordinary intrusion detection systems (IDSs). In this study, a lightweight machine learning-based IDS using a new feature selection algorithm is designed and implemented on Raspberry Pi, and its performance is verified using a public dataset collected from an IoT environment. To make the system lightweight, we propose a new algorithm for feature selection, called the correlated-set thresholding on gain-ratio (CST-GR) algorithm, to select really necessary features. Because the feature selection is conducted on three specific kinds of cyber-attacks, the number of selected features can be significantly reduced, which makes the classifiers very small and fast. Thus, our detection system is lightweight enough to be implemented and carried out in a Raspberry Pi system. More importantly, as the really necessary features corresponding to each kind of attack are exploited, good detection performance can be expected. The performance of our proposal is examined in detail with different machine learning algorithms, in order to learn which of them is the best option for our system. The experiment results indicate that the new feature selection algorithm can select only very few features for each kind of attack. Thus, the detection system is lightweight enough to be implemented in the Raspberry Pi environment with almost no sacrifice on detection performance. Full article

(This article belongs to the Section Networks)

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17 pages, 3543 KiB

Open AccessEditor’s ChoiceArticle

Deep Learning-Based Stacked Denoising and Autoencoder for ECG Heartbeat Classification

by Siti Nurmaini, Annisa Darmawahyuni, Akhmad Noviar Sakti Mukti, Muhammad Naufal Rachmatullah, Firdaus Firdaus and Bambang Tutuko

Electronics 2020, 9(1), 135; https://doi.org/10.3390/electronics9010135 - 10 Jan 2020

Cited by 99 | Viewed by 10478

Abstract

The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds of noise. Such noise may cause deformation on the ECG heartbeat waveform, leading to cardiologists’ mislabeling or misinterpreting heartbeats due [...] Read more.

The electrocardiogram (ECG) is a widely used, noninvasive test for analyzing arrhythmia. However, the ECG signal is prone to contamination by different kinds of noise. Such noise may cause deformation on the ECG heartbeat waveform, leading to cardiologists’ mislabeling or misinterpreting heartbeats due to varying types of artifacts and interference. To address this problem, some previous studies propose a computerized technique based on machine learning (ML) to distinguish between normal and abnormal heartbeats. Unfortunately, ML works on a handcrafted, feature-based approach and lacks feature representation. To overcome such drawbacks, deep learning (DL) is proposed in the pre-training and fine-tuning phases to produce an automated feature representation for multi-class classification of arrhythmia conditions. In the pre-training phase, stacked denoising autoencoders (DAEs) and autoencoders (AEs) are used for feature learning; in the fine-tuning phase, deep neural networks (DNNs) are implemented as a classifier. To the best of our knowledge, this research is the first to implement stacked autoencoders by using DAEs and AEs for feature learning in DL. Physionet’s well-known MIT-BIH Arrhythmia Database, as well as the MIT-BIH Noise Stress Test Database (NSTDB). Only four records are used from the NSTDB dataset: 118 24 dB, 118 −6 dB, 119 24 dB, and 119 −6 dB, with two levels of signal-to-noise ratio (SNRs) at 24 dB and −6 dB. In the validation process, six models are compared to select the best DL model. For all fine-tuned hyperparameters, the best model of ECG heartbeat classification achieves an accuracy, sensitivity, specificity, precision, and F1-score of 99.34%, 93.83%, 99.57%, 89.81%, and 91.44%, respectively. As the results demonstrate, the proposed DL model can extract high-level features not only from the training data but also from unseen data. Such a model has good application prospects in clinical practice. Full article

(This article belongs to the Special Issue Sensing and Signal Processing in Smart Healthcare)

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16 pages, 1709 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Novel Extensions to Enhance Scalability and Reliability of the IEEE 802.15.4-DSME Protocol

by Filippo Battaglia, Mario Collotta, Luca Leonardi, Lucia Lo Bello and Gaetano Patti

Electronics 2020, 9(1), 126; https://doi.org/10.3390/electronics9010126 - 9 Jan 2020

Cited by 17 | Viewed by 3292

Abstract

The Deterministic and Synchronous Multichannel Extension (DSME) of the IEEE 802.15.4 standard was designed to fulfill the requirements of commercial and industrial applications. DSME overcomes the IEEE 802.15.4 limitation on the maximum number of Guaranteed Time Slots (GTS) in a superframe and it [...] Read more.

The Deterministic and Synchronous Multichannel Extension (DSME) of the IEEE 802.15.4 standard was designed to fulfill the requirements of commercial and industrial applications. DSME overcomes the IEEE 802.15.4 limitation on the maximum number of Guaranteed Time Slots (GTS) in a superframe and it also exploits channel diversity to increase the communication reliability. However, DSME suffers from scalability problems, as its multi-superframe structure does not efficiently handle GTS in networks with a high number of nodes and periodic flows. This paper proposes the enhanceD DSME (D-DSME), which consists of two extensions that improve the DSME scalability and reliability exploiting a GTS within the multi-superframe to accommodate multiple flows or multiple retransmissions of the same flow. The paper describes the proposed extensions and the performance results of both OMNeT simulations and experiments with real devices implementing the D-DSME. Full article

(This article belongs to the Special Issue Emerging Trends in Industrial Communication)

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10 pages, 2326 KiB

Open AccessEditor’s ChoiceArticle

Numerical Analysis on Effective Mass and Traps Density Dependence of Electrical Characteristics of a-IGZO Thin-Film Transistors

by Jihwan Park, Do-Kyung Kim, Jun-Ik Park, In Man Kang, Jaewon Jang, Hyeok Kim, Philippe Lang and Jin-Hyuk Bae

Electronics 2020, 9(1), 119; https://doi.org/10.3390/electronics9010119 - 8 Jan 2020

Cited by 14 | Viewed by 9143

Abstract

We have investigated the effect of electron effective mass (m_e*) and tail acceptor-like edge traps density (N_TA) on the electrical characteristics of amorphous-InGaZnO (a-IGZO) thin-film transistors (TFTs) through numerical simulation. To examine the credibility of our simulation, [...] Read more.

We have investigated the effect of electron effective mass (m_e*) and tail acceptor-like edge traps density (N_TA) on the electrical characteristics of amorphous-InGaZnO (a-IGZO) thin-film transistors (TFTs) through numerical simulation. To examine the credibility of our simulation, we found that by adjusting m_e* to 0.34 of the free electron mass (m_o), we can preferentially derive the experimentally obtained electrical properties of conventional a-IGZO TFTs through our simulation. Our initial simulation considered the effect of m_e* on the electrical characteristics independent of N_TA. We varied the m_e* value while not changing the other variables related to traps density not dependent on it. As m_e* was incremented to 0.44 m_o, the field-effect mobility (µ_fe) and the on-state current (I_on) decreased due to the higher sub-gap scattering based on electron capture behavior. However, the threshold voltage (V_th) was not significantly changed due to fixed effective acceptor-like traps (N_TA). In reality, since the magnitude of N_TA was affected by the magnitude of m_e*, we controlled m_e* together with N_TA value as a secondary simulation. As the magnitude of both m_e* and N_TA increased, µ_fe and Ion deceased showing the same phenomena as the first simulation. The magnitude of V_th was higher when compared to the first simulation due to the lower conductivity in the channel. In this regard, our simulation methods showed that controlling m_e* and N_TA simultaneously would be expected to predict and optimize the electrical characteristics of a-IGZO TFTs more precisely. Full article

(This article belongs to the Section Semiconductor Devices)

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15 pages, 2107 KiB

Open AccessEditor’s ChoiceArticle

An Automatic Diagnosis of Arrhythmias Using a Combination of CNN and LSTM Technology

by Zhenyu Zheng, Zhencheng Chen, Fangrong Hu, Jianming Zhu, Qunfeng Tang and Yongbo Liang

Electronics 2020, 9(1), 121; https://doi.org/10.3390/electronics9010121 - 8 Jan 2020

Cited by 71 | Viewed by 5642

Abstract

Electrocardiogram (ECG) signal evaluation is routinely used in clinics as a significant diagnostic method for detecting arrhythmia. However, it is very labor intensive to externally evaluate ECG signals, due to their small amplitude. Using automated detection and classification methods in the clinic can [...] Read more.

Electrocardiogram (ECG) signal evaluation is routinely used in clinics as a significant diagnostic method for detecting arrhythmia. However, it is very labor intensive to externally evaluate ECG signals, due to their small amplitude. Using automated detection and classification methods in the clinic can assist doctors in making accurate and expeditious diagnoses of diseases. In this study, we developed a classification method for arrhythmia based on the combination of a convolutional neural network and long short-term memory, which was then used to diagnose eight ECG signals, including a normal sinus rhythm. The ECG data of the experiment were derived from the MIT-BIH arrhythmia database. The experimental method mainly consisted of two parts. The input data of the model were two-dimensional grayscale images converted from one-dimensional signals, and detection and classification of the input data was carried out using the combined model. The advantage of this method is that it does not require performing feature extraction or noise filtering on the ECG signal. The experimental results showed that the implemented method demonstrated high classification performance in terms of accuracy, specificity, and sensitivity equal to 99.01%, 99.57%, and 97.67%, respectively. Our proposed model can assist doctors in accurately detecting arrhythmia during routine ECG screening. Full article

(This article belongs to the Section Bioelectronics)

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19 pages, 3999 KiB

Open AccessEditor’s ChoiceCommunication

Floating Car Data Adaptive Traffic Signals: A Description of the First Real-Time Experiment with “Connected” Vehicles

by Vittorio Astarita, Vincenzo Pasquale Giofré, Demetrio Carmine Festa, Giuseppe Guido and Alessandro Vitale

Electronics 2020, 9(1), 114; https://doi.org/10.3390/electronics9010114 - 7 Jan 2020

Cited by 21 | Viewed by 6899

Abstract

The future of traffic management will be based on “connected” and “autonomous” vehicles. With connected vehicles it is possible to gather real-time information. The main potential application of this information is in real-time adaptive traffic signal control. Despite the feasibility of using Floating [...] Read more.

The future of traffic management will be based on “connected” and “autonomous” vehicles. With connected vehicles it is possible to gather real-time information. The main potential application of this information is in real-time adaptive traffic signal control. Despite the feasibility of using Floating Car Data (FCD), for signal control, there have been practically no real experiments with all “connected” vehicles to regulate traffic signals in real-time. Most of the research in this field has been carried out with simulations. The purpose of this study is to present a dedicated system that was implemented in the first experiment of an FCD-based adaptive traffic signal. For the first time in the history of traffic management, a traffic signal has been regulated in real time with real “connected” vehicles. This paper describes the entire path of software and system development that has allowed us to make the steps from just simulation test to a real on-field implementation. Results of the experiments carried out with the presented system prove the feasibility of FCD adaptive traffic signals with commonly-used technologies and also establishes a test-bed that may help others to develop better regulation algorithms for these kinds of new “connected” intersections. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems (ITS))

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16 pages, 3041 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Mobilities in Network Topology and Simulation Reproducibility of Sightseeing Vehicle Detected by Low-Power Wide-Area Positioning System

by Keigo Yamamoto, Jun Yoshida, Shigeyuki Miyagi, Shinsuke Minami, Daisuke Minami and Osamu Sakai

Electronics 2020, 9(1), 116; https://doi.org/10.3390/electronics9010116 - 7 Jan 2020

Cited by 3 | Viewed by 2775

Abstract

Vehicle mobilities for passengers in a city’s downtown area or in the countryside are significant points to characterize their functions and outputs. We focus on commercial sightseeing vehicles in a Japanese city where many tourists enjoy sightseeing. Such mobilities and their visualizations make [...] Read more.

Vehicle mobilities for passengers in a city’s downtown area or in the countryside are significant points to characterize their functions and outputs. We focus on commercial sightseeing vehicles in a Japanese city where many tourists enjoy sightseeing. Such mobilities and their visualizations make tourist activities smoother and richer. We design and install a low-power, wide-area positioning system on a rickshaw, which is a human-pulled, two- or three-wheeled cart, and monitor its mobility in Hikone City. All the spatial locations, which are recorded in a time sequence on a cloud server, are currently available as open data on the internet. We analyze such sequential data using graph topology, which reflects the information of corresponding geographical maps, and reproduce it in cyberspace using an agent-based model with similar probabilities to the accumulated rickshaw records from one spatial node to another. Although the numerical results of the agent traced in a simulated city are partially consistent with the rickshaw’s record, we identify some significant differences. We conclude that the rickshaw’s mobility observed at the actual sightseeing sites is partially in the random motion; some cases are strongly biased by memory routes. Such non-randomness in the rickshaw’s mobility indicates the existence of specific features in tourism sources that are identified for each sightseeing activity and affected by local sightseeing resources. Full article

(This article belongs to the Section Networks)

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18 pages, 11088 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Interference of Spread-Spectrum EMI and Digital Data Links under Narrowband Resonant Coupling

by Paolo Stefano Crovetti and Francesco Musolino

Electronics 2020, 9(1), 60; https://doi.org/10.3390/electronics9010060 - 1 Jan 2020

Cited by 15 | Viewed by 4196

Abstract

In this paper, the effects of electromagnetic interference (EMI) coupled to a radio-frequency (RF) communication channel by resonant mechanisms are investigated and described in the framework of Shannon information theory in terms of an equivalent channel capacity loss so that to analyze and [...] Read more.

In this paper, the effects of electromagnetic interference (EMI) coupled to a radio-frequency (RF) communication channel by resonant mechanisms are investigated and described in the framework of Shannon information theory in terms of an equivalent channel capacity loss so that to analyze and compare the effects of non-modulated and random Spread Spectrum (SS) modulated EMI. The analysis reveals a higher EMI-induced capacity loss for SS-modulated compared to non modulated EMI under practical values of the quality factor Q, while a modest improvement in the worst case capacity loss is observed only for impractical values of Q. Simulations on a 4-quadrature amplitude modulation (4-QAM) digital link featuring Turbo coding under EMI resonant coupling reveal that SS-modulated EMI gives rise to higher bit error rate (BER) at lower EMI power compared non-modulated EMI in the presence of resonant coupling for practical values of Q, thus suggesting a worse interfering potential of SS-modulated EMI. Full article

(This article belongs to the Special Issue Electromagnetic Interference and Compatibility)

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13 pages, 4935 KiB

Open AccessEditor’s ChoiceArticle

4-Port MIMO Antenna with Defected Ground Structure for 5G Millimeter Wave Applications

by Mahnoor Khalid, Syeda Iffat Naqvi, Niamat Hussain, MuhibUr Rahman, Fawad, Seyed Sajad Mirjavadi, Muhammad Jamil Khan and Yasar Amin

Electronics 2020, 9(1), 71; https://doi.org/10.3390/electronics9010071 - 1 Jan 2020

Cited by 285 | Viewed by 13326

Abstract

We present a 4-port Multiple-Input-Multiple-Output (MIMO) antenna array operating in the mm-wave band for 5G applications. An identical two-element array excited by the feed network based on a T-junction power combiner/divider is introduced in the reported paper. The array elements are rectangular-shaped slotted [...] Read more.

We present a 4-port Multiple-Input-Multiple-Output (MIMO) antenna array operating in the mm-wave band for 5G applications. An identical two-element array excited by the feed network based on a T-junction power combiner/divider is introduced in the reported paper. The array elements are rectangular-shaped slotted patch antennas, while the ground plane is made defected with rectangular, circular, and a zigzag-shaped slotted structure to enhance the radiation characteristics of the antenna. To validate the performance, the MIMO structure is fabricated and measured. The simulated and measured results are in good coherence. The proposed structure can operate in a 25.5–29.6 GHz frequency band supporting the impending mm-wave 5G applications. Moreover, the peak gain attained for the operating frequency band is 8.3 dBi. Additionally, to obtain high isolation between antenna elements, the polarization diversity is employed between the adjacent radiators, resulting in a low Envelope Correlation Coefficient (ECC). Other MIMO performance metrics such as the Channel Capacity Loss (CCL), Mean Effective Gain (MEG), and Diversity gain (DG) of the proposed structure are analyzed, and the results indicate the suitability of the design as a potential contender for imminent mm-wave 5G MIMO applications. Full article

(This article belongs to the Special Issue Antennas and Propagation Aspects for Emerging Wireless Communication Technologies)

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16 pages, 3904 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Common Mode Voltage Elimination for Quasi-Switch Boost T-Type Inverter Based on SVM Technique

by Duc-Tri Do, Minh-Khai Nguyen, Van-Thuyen Ngo, Thanh-Hai Quach and Vinh-Thanh Tran

Electronics 2020, 9(1), 76; https://doi.org/10.3390/electronics9010076 - 1 Jan 2020

Cited by 15 | Viewed by 3505

Abstract

In this paper, the effect of common-mode voltage generated in the three-level quasi-switched boost T-type inverter is minimized by applying the proposed space-vector modulation technique, which uses only medium vectors and zero vector to synthesize the reference vector. The switching sequence is selected [...] Read more.

In this paper, the effect of common-mode voltage generated in the three-level quasi-switched boost T-type inverter is minimized by applying the proposed space-vector modulation technique, which uses only medium vectors and zero vector to synthesize the reference vector. The switching sequence is selected smoothly for inserting the shoot-through state for the inverter branch. The shoot-through vector is added within the zero vector in order to not affect the active vectors as well as the output voltage. In addition, the shoot-through control signal of active switches of the impedance network is generated to ensure that its phase is shifted 90 degrees compared to shoot through the signal of the inverter leg, which provides an improvement in reducing the inductor current ripple and enhancing the voltage gain. The effectiveness of the proposed method is verified through simulation and experimental results. In addition, the superiority of the proposed scheme is demonstrated by comparing it to the conventional pulse-width modulation technique. Full article

(This article belongs to the Special Issue Power Converters in Power Electronics)

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14 pages, 10153 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Low-Speed Performance Improvement of Direct Torque Control for Induction Motor Drives Fed by Three-Level NPC Inverter

by Samer Saleh Hakami, Ibrahim Mohd Alsofyani and Kyo-Beum Lee

Electronics 2020, 9(1), 77; https://doi.org/10.3390/electronics9010077 - 1 Jan 2020

Cited by 11 | Viewed by 3672

Abstract

Classical direct torque control (DTC) is considered one of the simplest and fastest control algorithms in motor drives. However, it produces high torque and flux ripples due to the implementation of the three-level hysteresis torque regulator (HTR). Although, increasing the level of HTR [...] Read more.

Classical direct torque control (DTC) is considered one of the simplest and fastest control algorithms in motor drives. However, it produces high torque and flux ripples due to the implementation of the three-level hysteresis torque regulator (HTR). Although, increasing the level of HTR and utilizing multilevel inverters has a great contribution in torque and flux ripples reduction, stator flux magnitude of induction motor (IM) droops at every switching sector transition, particularly at low-speed operation. This problem occurs due to the utilization of a zero voltage vector, where the domination of stator resistance is very high. A simple flux regulation strategy (SFRS) is applied for low-speed operation for DTC of IM. The proposed DTC-SFRS modifies the output status of the five-level HTR depending on the flux error, torque error, and stator flux position. This method regulates the stator flux for both forward and reverse rotational directions of IM with retaining the basic structure of classical DTC. By using the proposed algorithm, the stator flux is regulated, hence pure sinusoidal current waveform is achieved, which results in lower total harmonics distortion (THD). The effectiveness of the proposed DTC-SFRS is verified through simulation and experimental results. Full article

(This article belongs to the Special Issue High Power Electric Traction Systems)

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16 pages, 4395 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Development of a Compact, IoT-Enabled Electronic Nose for Breath Analysis

by Akira Tiele, Alfian Wicaksono, Sai Kiran Ayyala and James A. Covington

Electronics 2020, 9(1), 84; https://doi.org/10.3390/electronics9010084 - 1 Jan 2020

Cited by 48 | Viewed by 8286

Abstract

In this paper, we report on an in-house developed electronic nose (E-nose) for use with breath analysis. The unit consists of an array of 10 micro-electro-mechanical systems (MEMS) metal oxide (MOX) gas sensors produced by seven manufacturers. Breath sampling of end-tidal breath is [...] Read more.

In this paper, we report on an in-house developed electronic nose (E-nose) for use with breath analysis. The unit consists of an array of 10 micro-electro-mechanical systems (MEMS) metal oxide (MOX) gas sensors produced by seven manufacturers. Breath sampling of end-tidal breath is achieved using a heated sample tube, capable of monitoring sampling-related parameters, such as carbon dioxide (CO₂), humidity, and temperature. A simple mobile app was developed to receive real-time data from the device, using Wi-Fi communication. The system has been tested using chemical standards and exhaled breath samples from healthy volunteers, before and after taking a peppermint capsule. Results from chemical testing indicate that we can separate chemical standards (acetone, isopropanol and 1-propanol) and different concentrations of isobutylene. The analysis of exhaled breath samples demonstrate that we can distinguish between pre- and post-consumption of peppermint capsules; area under the curve (AUC): 0.81, sensitivity: 0.83 (0.59–0.96), specificity: 0.72 (0.47–0.90), p-value: <0.001. The functionality of the developed device has been demonstrated with the testing of chemical standards and a simplified breath study using peppermint capsules. It is our intention to deploy this system in a UK hospital in an upcoming breath research study. Full article

(This article belongs to the Special Issue Design and Application of Biomedical Circuits and Systems)

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18 pages, 3546 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Face–Iris Multimodal Biometric Identification System

by Basma Ammour, Larbi Boubchir, Toufik Bouden and Messaoud Ramdani

Electronics 2020, 9(1), 85; https://doi.org/10.3390/electronics9010085 - 1 Jan 2020

Cited by 68 | Viewed by 8711

Abstract

Multimodal biometrics technology has recently gained interest due to its capacity to overcome certain inherent limitations of the single biometric modalities and to improve the overall recognition rate. A common biometric recognition system consists of sensing, feature extraction, and matching modules. The robustness [...] Read more.

Multimodal biometrics technology has recently gained interest due to its capacity to overcome certain inherent limitations of the single biometric modalities and to improve the overall recognition rate. A common biometric recognition system consists of sensing, feature extraction, and matching modules. The robustness of the system depends much more on the reliability to extract relevant information from the single biometric traits. This paper proposes a new feature extraction technique for a multimodal biometric system using face–iris traits. The iris feature extraction is carried out using an efficient multi-resolution 2D Log-Gabor filter to capture textural information in different scales and orientations. On the other hand, the facial features are computed using the powerful method of singular spectrum analysis (SSA) in conjunction with the wavelet transform. SSA aims at expanding signals or images into interpretable and physically meaningful components. In this study, SSA is applied and combined with the normal inverse Gaussian (NIG) statistical features derived from wavelet transform. The fusion process of relevant features from the two modalities are combined at a hybrid fusion level. The evaluation process is performed on a chimeric database and consists of Olivetti research laboratory (ORL) and face recognition technology (FERET) for face and Chinese academy of science institute of automation (CASIA) v3.0 iris image database (CASIA V3) interval for iris. Experimental results show the robustness. Full article

(This article belongs to the Special Issue Recent Advances in Biometrics and its Applications)

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28 pages, 9694 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Design of an Intrinsically Safe Series-Series Compensation WPT System for Automotive LiDAR

by Luiz A. Lisboa Cardoso, Vítor Monteiro, José Gabriel Pinto, Miguel Nogueira, Adérito Abreu, José A. Afonso and João L. Afonso

Electronics 2020, 9(1), 86; https://doi.org/10.3390/electronics9010086 - 1 Jan 2020

Cited by 2 | Viewed by 3481

Abstract

The earliest and simplest impedance compensation technique used in inductive wireless power transfer (WPT) design is the series-series (SS) compensation circuit, which uses capacitors in series with both primary and secondary coils of an air-gapped transformer. Despite of its simplicity at the resonant [...] Read more.

The earliest and simplest impedance compensation technique used in inductive wireless power transfer (WPT) design is the series-series (SS) compensation circuit, which uses capacitors in series with both primary and secondary coils of an air-gapped transformer. Despite of its simplicity at the resonant condition, this configuration exhibits a major sensitivity to variations of the load attached to the secondary, especially when higher coupling coefficients are used in the design. In the extreme situation that the secondary coil is left at open circuit, the current at the primary coil may increase above the safety limits for either the power converter driving the primary coil or the components in the primary circuit, including the coil itself. An approach often used to minimize this problem is detuning, but this also reduces the electrical efficiency of the power transfer. In low power, fixed-distance stationary WPT, a fair trade-off between efficiency and safety must be verified. This paper aims to consolidate a simple design procedure for such a SS-compensation, exemplifying its use in the prototype of a WPT system for automotive light detection and ranging (LiDAR) equipment. The guidelines herein provided should equally apply to other low power applications. Full article

(This article belongs to the Section Power Electronics)

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9 pages, 3402 KiB

Open AccessEditor’s ChoiceArticle

A Compact 3.3–3.5 GHz Filter Based on Modified Composite Right-/Left-Handed Resonator Units

by Shanwen Hu, Yunqing Hu, Haiyu Zheng, Weiguang Zhu, Yiting Gao and Xiaodong Zhang

Electronics 2020, 9(1), 1; https://doi.org/10.3390/electronics9010001 - 18 Dec 2019

Cited by 11 | Viewed by 4207

Abstract

In the RF (Radio Frequency) front-end of a communication system, bandpass filters (BPFs) are used to send passband signals and reject stopband signals. Substrate-integrated waveguides (SIW) are widely used in RF filter designs due to their low loss and low cost and the [...] Read more.

In the RF (Radio Frequency) front-end of a communication system, bandpass filters (BPFs) are used to send passband signals and reject stopband signals. Substrate-integrated waveguides (SIW) are widely used in RF filter designs due to their low loss and low cost and the flexibility of their integration properties. However, SIW filters under 6 GHz are still too large to meet the requirement of portable communication devices due to their long wavelength. In this paper, a very compact fully integrated SIW filter is proposed and designed with RT6010 dielectric material to meet the small size requirement of portable devices for next-generation sub-6 G applications. The proposed filter contains two sawtooth-shaped composite right-/left-handed (CRLH) resonator units, instead of traditional rectangular-shaped CRLH resonator units, which makes the filter more compact and cost effective. The filter is designed and fabricated on an RT6010 substrate, with a size of only 10 mm × 7.4 mm. The measurement results illustrated that the proposed BPF shows a passband covering the frequency range of 3.25–3.45 GHz; the minimum passband insertion loss is only 2.4 dB; the stopband rejection is better than −20 dB throughout the frequencies below 3.0 GHz and above 3.8 GHz; S11 is as low as −37 dB at 3.35 GHz; and the group delay variation is only 1.4 ns throughout the operation bandwidth. Full article

(This article belongs to the Special Issue RF/Mm-Wave Circuits Design and Applications)

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18 pages, 5456 KiB

Open AccessEditor’s ChoiceArticle

A Deep Learning-Based Scatter Correction of Simulated X-ray Images

by Heesin Lee and Joonwhoan Lee

Electronics 2019, 8(9), 944; https://doi.org/10.3390/electronics8090944 - 27 Aug 2019

Cited by 30 | Viewed by 6959

Abstract

X-ray scattering significantly limits image quality. Conventional strategies for scatter reduction based on physical equipment or measurements inevitably increase the dose to improve the image quality. In addition, scatter reduction based on a computational algorithm could take a large amount of time. We [...] Read more.

X-ray scattering significantly limits image quality. Conventional strategies for scatter reduction based on physical equipment or measurements inevitably increase the dose to improve the image quality. In addition, scatter reduction based on a computational algorithm could take a large amount of time. We propose a deep learning-based scatter correction method, which adopts a convolutional neural network (CNN) for restoration of degraded images. Because it is hard to obtain real data from an X-ray imaging system for training the network, Monte Carlo (MC) simulation was performed to generate the training data. For simulating X-ray images of a human chest, a cone beam CT (CBCT) was designed and modeled as an example. Then, pairs of simulated images, which correspond to scattered and scatter-free images, respectively, were obtained from the model with different doses. The scatter components, calculated by taking the differences of the pairs, were used as targets to train the weight parameters of the CNN. Compared with the MC-based iterative method, the proposed one shows better results in projected images, with as much as 58.5% reduction in root-mean-square error (RMSE), and 18.1% and 3.4% increases in peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), on average, respectively. Full article

(This article belongs to the Special Issue Deep Neural Networks and Their Applications)

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20 pages, 36563 KiB

Open AccessEditor’s ChoiceArticle

Fallen People Detection Capabilities Using Assistive Robot

by Saturnino Maldonado-Bascón, Cristian Iglesias-Iglesias, Pilar Martín-Martín and Sergio Lafuente-Arroyo

Electronics 2019, 8(9), 915; https://doi.org/10.3390/electronics8090915 - 21 Aug 2019

Cited by 39 | Viewed by 7385

Abstract

One of the main problems in the elderly population and for people with functional disabilities is falling when they are not supervised. Therefore, there is a need for monitoring systems with fall detection functionality. Mobile robots are a good solution for keeping the [...] Read more.

One of the main problems in the elderly population and for people with functional disabilities is falling when they are not supervised. Therefore, there is a need for monitoring systems with fall detection functionality. Mobile robots are a good solution for keeping the person in sight when compared to static-view sensors. Mobile-patrol robots can be used for a group of people and systems are less intrusive than ones based on mobile robots. In this paper, we propose a novel vision-based solution for fall detection based on a mobile-patrol robot that can correct its position in case of doubt. The overall approach can be formulated as an end-to-end solution based on two stages: person detection and fall classification. Deep learning-based computer vision is used for person detection and fall classification is done by using a learning-based Support Vector Machine (SVM) classifier. This approach mainly fulfills the following design requirements—simple to apply, adaptable, high performance, independent of person size, clothes, or the environment, low cost and real-time computing. Important to highlight is the ability to distinguish between a simple resting position and a real fall scene. One of the main contributions of this paper is the input feature vector to the SVM-based classifier. We evaluated the robustness of the approach using a realistic public dataset proposed in this paper called the Fallen Person Dataset (FPDS), with 2062 images and 1072 falls. The results obtained from different experiments indicate that the system has a high success rate in fall classification (precision of 100% and recall of 99.74%). Training the algorithm using our Fallen Person Dataset (FPDS) and testing it with other datasets showed that the algorithm is independent of the camera setup. Full article

(This article belongs to the Special Issue Machine Learning Techniques for Assistive Robotics)

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18 pages, 3513 KiB

Open AccessEditor’s ChoiceArticle

Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting

by Renzhuo Wan, Shuping Mei, Jun Wang, Min Liu and Fan Yang

Electronics 2019, 8(8), 876; https://doi.org/10.3390/electronics8080876 - 7 Aug 2019

Cited by 242 | Viewed by 24568

Abstract

Multivariable time series prediction has been widely studied in power energy, aerology, meteorology, finance, transportation, etc. Traditional modeling methods have complex patterns and are inefficient to capture long-term multivariate dependencies of data for desired forecasting accuracy. To address such concerns, various deep learning [...] Read more.

Multivariable time series prediction has been widely studied in power energy, aerology, meteorology, finance, transportation, etc. Traditional modeling methods have complex patterns and are inefficient to capture long-term multivariate dependencies of data for desired forecasting accuracy. To address such concerns, various deep learning models based on Recurrent Neural Network (RNN) and Convolutional Neural Network (CNN) methods are proposed. To improve the prediction accuracy and minimize the multivariate time series data dependence for aperiodic data, in this article, Beijing PM2.5 and ISO-NE Dataset are analyzed by a novel Multivariate Temporal Convolution Network (M-TCN) model. In this model, multi-variable time series prediction is constructed as a sequence-to-sequence scenario for non-periodic datasets. The multichannel residual blocks in parallel with asymmetric structure based on deep convolution neural network is proposed. The results are compared with rich competitive algorithms of long short term memory (LSTM), convolutional LSTM (ConvLSTM), Temporal Convolution Network (TCN) and Multivariate Attention LSTM-FCN (MALSTM-FCN), which indicate significant improvement of prediction accuracy, robust and generalization of our model. Full article

(This article belongs to the Special Issue Deep Learning Applications with Practical Measured Results in Electronics Industries)

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34 pages, 364 KiB

Open AccessEditor’s ChoiceReview

Machine Learning Interpretability: A Survey on Methods and Metrics

by Diogo V. Carvalho, Eduardo M. Pereira and Jaime S. Cardoso

Electronics 2019, 8(8), 832; https://doi.org/10.3390/electronics8080832 - 26 Jul 2019

Cited by 1007 | Viewed by 59164

Abstract

Machine learning systems are becoming increasingly ubiquitous. These systems’s adoption has been expanding, accelerating the shift towards a more algorithmic society, meaning that algorithmically informed decisions have greater potential for significant social impact. However, most of these accurate decision support systems remain complex [...] Read more.

Machine learning systems are becoming increasingly ubiquitous. These systems’s adoption has been expanding, accelerating the shift towards a more algorithmic society, meaning that algorithmically informed decisions have greater potential for significant social impact. However, most of these accurate decision support systems remain complex black boxes, meaning their internal logic and inner workings are hidden to the user and even experts cannot fully understand the rationale behind their predictions. Moreover, new regulations and highly regulated domains have made the audit and verifiability of decisions mandatory, increasing the demand for the ability to question, understand, and trust machine learning systems, for which interpretability is indispensable. The research community has recognized this interpretability problem and focused on developing both interpretable models and explanation methods over the past few years. However, the emergence of these methods shows there is no consensus on how to assess the explanation quality. Which are the most suitable metrics to assess the quality of an explanation? The aim of this article is to provide a review of the current state of the research field on machine learning interpretability while focusing on the societal impact and on the developed methods and metrics. Furthermore, a complete literature review is presented in order to identify future directions of work on this field. Full article

(This article belongs to the Section Artificial Intelligence)

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