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Electronics, Volume 10, Issue 10 (May-2 2021) – 93 articles

Cover Story (view full-size image): The brain–computer interface (BCI) is a promising technology where a user can control a robot or computer by thinking and without using movements. Generally, different principles are applied to BCI depending on the application because the strengths and weaknesses vary according to each BCI method. Therefore, BCI should be able to predict a user state for applying suitable principles to the system. In this paper, we developed BCI technology that predicts a user state using functional connectivity of the brain and a convolutional neural network. The mean accuracy for user state classification was 88.25 ± 2.34%. BCI is an essential technology for applying suitable principles to the BCI system according to the user state. View this paper.
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Article
A Novel Multilevel Controller
Electronics 2021, 10(10), 1222; https://doi.org/10.3390/electronics10101222 - 20 May 2021
Viewed by 398
Abstract
Active power filter is an important means to improve power quality, and power topology is an important part of active power filter. Therefore, the research on power topology has important practical value. This paper proposes a simple-structure topology that employs eight switching power [...] Read more.
Active power filter is an important means to improve power quality, and power topology is an important part of active power filter. Therefore, the research on power topology has important practical value. This paper proposes a simple-structure topology that employs eight switching power devices, two capacitors, and eight diodes to realize nine-level voltage output. The proposed topology can effectively reduce the volume and weight of the device and achieve multilevel output. Simultaneously, a compound control strategy, consisting of integrated phase voltage control and cell capacitance voltage control, is proposed for unit voltage equalization control. Finally, taking the three-phase active power filter as the research object, simulation and experimental verification are carried out with the proposed topology. The results show that the proposed topology and control scheme are feasible, and in the case of sudden load change, the fluctuation of capacitor voltage V1 is less than 3 V, the fluctuation of capacitor voltage V2 is less than 1 V, and the THD (Total Harmonic Distortion) of the phase current is well suppressed to 3.84%. Full article
(This article belongs to the Section Power Electronics)
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Article
Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies
Electronics 2021, 10(10), 1221; https://doi.org/10.3390/electronics10101221 - 20 May 2021
Viewed by 385
Abstract
Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps [...] Read more.
Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow. Full article
(This article belongs to the Special Issue Autonomous Navigation Systems: Design, Control and Applications)
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Article
Cybersafety Approach to Cybersecurity Analysis and Mitigation for Mobility-as-a-Service and Internet of Vehicles
Electronics 2021, 10(10), 1220; https://doi.org/10.3390/electronics10101220 - 20 May 2021
Viewed by 418
Abstract
Urban mobility is in the midst of a revolution, driven by the convergence of technologies such as artificial intelligence, on-demand ride services, and Internet-connected and self-driving vehicles. Technological advancements often lead to new hazards. Coupled with the increased levels of automation and connectivity [...] Read more.
Urban mobility is in the midst of a revolution, driven by the convergence of technologies such as artificial intelligence, on-demand ride services, and Internet-connected and self-driving vehicles. Technological advancements often lead to new hazards. Coupled with the increased levels of automation and connectivity in the new generation of autonomous vehicles, cybersecurity is emerging as a key threat affecting these vehicles. Traditional hazard analysis methods treat safety and security in isolation and are limited in their ability to account for interactions among organizational, sociotechnical, human, and technical components. In response to these challenges, the cybersafety method, based on System Theoretic Process Analysis (STPA and STPA-Sec), was developed to meet the growing need to holistically analyze complex sociotechnical systems. We applied cybersafety to coanalyze safety and security hazards, as well as identify mitigation requirements. The results were compared with another promising method known as Combined Harm Analysis of Safety and Security for Information Systems (CHASSIS). Both methods were applied to the Mobility-as-a-Service (MaaS) and Internet of Vehicles (IoV) use cases, focusing on over-the-air software updates feature. Overall, cybersafety identified additional hazards and more effective requirements compared to CHASSIS. In particular, cybersafety demonstrated the ability to identify hazards due to unsafe/unsecure interactions among sociotechnical components. This research also suggested using CHASSIS methods for information lifecycle analysis to complement and generate additional considerations for cybersafety. Finally, results from both methods were backtested against a past cyber hack on a vehicular system, and we found that recommendations from cybersafety were likely to mitigate the risks of the incident. Full article
(This article belongs to the Special Issue Recent Advances in Internet of Vehicles)
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Review
Approaches towards Blockchain Innovation: A Survey and Future Directions
Electronics 2021, 10(10), 1219; https://doi.org/10.3390/electronics10101219 - 20 May 2021
Viewed by 459
Abstract
A blockchain is a decentralized peer to peer platform which provides security services based on some key concepts, namely authentication, confidentiality, integrity and authorization. It is the process of recording and keeping track of the resources without the intervention of a centralized authority. [...] Read more.
A blockchain is a decentralized peer to peer platform which provides security services based on some key concepts, namely authentication, confidentiality, integrity and authorization. It is the process of recording and keeping track of the resources without the intervention of a centralized authority. This paper provides an overview of blockchains, the structure of blockchains, consensus algorithms, etc., It compares the algorithms based on their utility and limitations. Though blockchains provide secure communication, there are some minimal data leaks which are discussed. Various security issues in blockchains are discussed such as denial of service attacks, etc., In addition to security, some other blockchain challenges are presented like scalability, reliability, interoperability, privacy and consensus mechanisms for integration with AI, IoT and edge computing. This paper also explains about the importance of blockchains in the fields of smart healthcare, smart grid, and smart financial systems. Overall, this paper gives the glimpse of various protocols, algorithms, applications, challenges and opportunities that are found in the blockchain domain. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
Anomaly Detection Based on Temporal Behavior Monitoring in Programmable Logic Controllers
Electronics 2021, 10(10), 1218; https://doi.org/10.3390/electronics10101218 - 20 May 2021
Viewed by 419
Abstract
As Programmable Logic Controllers (PLCs) are increasingly connected and integrated into the industrial Internet of things, cybersecurity threats to PLCs are also increasing. Adversaries can perform a denial of service (DoS) attack based on the transmission of a large number of network packets, [...] Read more.
As Programmable Logic Controllers (PLCs) are increasingly connected and integrated into the industrial Internet of things, cybersecurity threats to PLCs are also increasing. Adversaries can perform a denial of service (DoS) attack based on the transmission of a large number of network packets, and a control-logic injection attack through sophisticated packet transmission. We propose an approach to detecting and defending against attacks that exploit security vulnerabilities in a PLC system. In order to protect against indiscriminate packet transmission attacks that exploit uncontrolled resource consumption vulnerabilities, an abnormal temporal behavior detection method is proposed that monitors the CPU usage of tasks. If a temporal anomaly is detected, the proposed approach tries to detect control-flow anomalies by examining the sequences of function calls, then detects stack-based buffer overflow attacks. The proposed method is implemented in a water tank control system for evaluation purposes. The experimental results show that the proposed method can improve the security of the system by detecting anomalies in temporal behavior with little system overhead. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
Integral Sliding Control Approach for Generalized Cyclic Pursuit Formation Maintenance
Electronics 2021, 10(10), 1217; https://doi.org/10.3390/electronics10101217 - 20 May 2021
Viewed by 302
Abstract
This paper is concerned with the formation maintenance of a group of autonomous agents under generalized cyclic pursuit (GCP) law. The described pattern for agents under such formation is epicycle-like. For a network of agents to achieve such a formation, marginal stability of [...] Read more.
This paper is concerned with the formation maintenance of a group of autonomous agents under generalized cyclic pursuit (GCP) law. The described pattern for agents under such formation is epicycle-like. For a network of agents to achieve such a formation, marginal stability of the overall network is required. The desired marginal stability of the network relies on each agents’ gain values, and uncertainties in these gains can occur. Previous studies have used fixed gains, we enhance the stability of the gains via a dynamic approach using an integral sliding controller (ISC). An ISC can ensure sliding behavior of the gains throughout the entire response, and it is shown that the gains are robust toward variations and thus make the network keep its marginal stability and its formation. Full article
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Review
Review on Generative Adversarial Networks: Focusing on Computer Vision and Its Applications
Electronics 2021, 10(10), 1216; https://doi.org/10.3390/electronics10101216 - 20 May 2021
Viewed by 394
Abstract
The emergence of deep learning model GAN (Generative Adversarial Networks) is an important turning point in generative modeling. GAN is more powerful in feature and expression learning compared to machine learning-based generative model algorithms. Nowadays, it is also used to generate non-image data, [...] Read more.
The emergence of deep learning model GAN (Generative Adversarial Networks) is an important turning point in generative modeling. GAN is more powerful in feature and expression learning compared to machine learning-based generative model algorithms. Nowadays, it is also used to generate non-image data, such as voice and natural language. Typical technologies include BERT (Bidirectional Encoder Representations from Transformers), GPT-3 (Generative Pretrained Transformer-3), and MuseNet. GAN differs from the machine learning-based generative model and the objective function. Training is conducted by two networks: generator and discriminator. The generator converts random noise into a true-to-life image, whereas the discriminator distinguishes whether the input image is real or synthetic. As the training continues, the generator learns more sophisticated synthesis techniques, and the discriminator grows into a more accurate differentiator. GAN has problems, such as mode collapse, training instability, and lack of evaluation matrix, and many researchers have tried to solve these problems. For example, solutions such as one-sided label smoothing, instance normalization, and minibatch discrimination have been proposed. The field of application has also expanded. This paper provides an overview of GAN and application solutions for computer vision and artificial intelligence healthcare field researchers. The structure and principle of operation of GAN, the core models of GAN proposed to date, and the theory of GAN were analyzed. Application examples of GAN such as image classification and regression, image synthesis and inpainting, image-to-image translation, super-resolution and point registration were then presented. The discussion tackled GAN’s problems and solutions, and the future research direction was finally proposed. Full article
(This article belongs to the Special Issue Electronic Solutions for Artificial Intelligence Healthcare Volume II)
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Article
A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach
Electronics 2021, 10(10), 1215; https://doi.org/10.3390/electronics10101215 - 20 May 2021
Viewed by 647
Abstract
In this era of big data, the amount of video content has dramatically increased with an exponential broadening of video streaming services. Hence, it has become very strenuous for end-users to search for their desired videos. Therefore, to attain an accurate and robust [...] Read more.
In this era of big data, the amount of video content has dramatically increased with an exponential broadening of video streaming services. Hence, it has become very strenuous for end-users to search for their desired videos. Therefore, to attain an accurate and robust clustering of information, a hybrid algorithm was used to introduce a recommender engine with collaborative filtering using Apache Spark and machine learning (ML) libraries. In this study, we implemented a movie recommendation system based on a collaborative filtering approach using the alternating least squared (ALS) model to predict the best-rated movies. Our proposed system uses the last search data of a user regarding movie category and references this to instruct the recommender engine, thereby making a list of predictions for top ratings. The proposed study used a model-based approach of matrix factorization, the ALS algorithm along with a collaborative filtering technique, which solved the cold start, sparse, and scalability problems. In particular, we performed experimental analysis and successfully obtained minimum root mean squared errors (oRMSEs) of 0.8959 to 0.97613, approximately. Moreover, our proposed movie recommendation system showed an accuracy of 97% and predicted the top 1000 ratings for movies. Full article
(This article belongs to the Special Issue Big Data Privacy-Preservation)
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Article
Singing Voice Detection in Opera Recordings: A Case Study on Robustness and Generalization
Electronics 2021, 10(10), 1214; https://doi.org/10.3390/electronics10101214 - 20 May 2021
Viewed by 291
Abstract
Automatically detecting the presence of singing in music audio recordings is a central task within music information retrieval. While modern machine-learning systems produce high-quality results on this task, the reported experiments are usually limited to popular music and the trained systems often overfit [...] Read more.
Automatically detecting the presence of singing in music audio recordings is a central task within music information retrieval. While modern machine-learning systems produce high-quality results on this task, the reported experiments are usually limited to popular music and the trained systems often overfit to confounding factors. In this paper, we aim to gain a deeper understanding of such machine-learning methods and investigate their robustness in a challenging opera scenario. To this end, we compare two state-of-the-art methods for singing voice detection based on supervised learning: A traditional approach relying on hand-crafted features with a random forest classifier, as well as a deep-learning approach relying on convolutional neural networks. To evaluate these algorithms, we make use of a cross-version dataset comprising 16 recorded performances (versions) of Richard Wagner’s four-opera cycle Der Ring des Nibelungen. This scenario allows us to systematically investigate generalization to unseen versions, musical works, or both. In particular, we study the trained systems’ robustness depending on the acoustic and musical variety, as well as the overall size of the training dataset. Our experiments show that both systems can robustly detect singing voice in opera recordings even when trained on relatively small datasets with little variety. Full article
(This article belongs to the Special Issue Machine Learning Applied to Music/Audio Signal Processing)
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Article
Transmission Analysis in Human Body Communication for Head-Mounted Wearable Devices
Electronics 2021, 10(10), 1213; https://doi.org/10.3390/electronics10101213 - 19 May 2021
Viewed by 346
Abstract
As society ages, wireless body area networks (WBANs) are expected to increasingly improve the quality of life of the elderly and disabled. One promising WBAN technology is human body communication (HBC), which utilizes part of the human body as a transmission medium. Communication [...] Read more.
As society ages, wireless body area networks (WBANs) are expected to increasingly improve the quality of life of the elderly and disabled. One promising WBAN technology is human body communication (HBC), which utilizes part of the human body as a transmission medium. Communication between head-mounted wearable devices, such as hearing aids, is a potential HBC application. To clarify the HBC transmission mechanism between head-mounted wearable devices, this study analyzes the input impedance characteristics of the transceiver electrodes, transmission characteristics, and electric field distributions around and through a detailed head model. The investigation was performed via an electromagnetic field simulation. The signal frequency had less effect on the transmission characteristics and electric field distributions at 10, 20, and 30 MHz. However, the transmission mechanism between the head-mounted wearable devices was influenced by the number of electrodes in the transceiver. Moreover, the transmission characteristics between two-electrode transceivers were improved by impedance matching. Finally, the availability of the proposed system was evaluated from power consumption and human safety perspectives. Full article
(This article belongs to the Special Issue Antennas for Wearable and Implantable Applications)
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Article
Design of a Charge Pump Circuit and System with Input Impedance Modulation for a Flexible-Type Thermoelectric Generator with High-Output Impedance
Electronics 2021, 10(10), 1212; https://doi.org/10.3390/electronics10101212 - 19 May 2021
Viewed by 354
Abstract
This paper describes a charge pump system for a flexible thermoelectric generator (TEG). Even though the TEG has high-output impedance, the system controls the input voltage to keep it higher than the minimum operating voltage by modulating the input impedance of the charge [...] Read more.
This paper describes a charge pump system for a flexible thermoelectric generator (TEG). Even though the TEG has high-output impedance, the system controls the input voltage to keep it higher than the minimum operating voltage by modulating the input impedance of the charge pump using two-phase operation with low- and high-input impedance modes. The average input impedance can be matched with the output impedance of the TEG. How the system can be designed is also described in detail. A design demonstration was performed for the TEG with 400 Ω. The fabricated system was also measured with a flexible-type TEG based on carbon nanotubes. Even with an output impedance of 1.4 kΩ, the system converted thermal energy into electric power of 30 μW at 2.5 V to the following sensor ICs. Full article
(This article belongs to the Special Issue Energy Harvesting and Energy Storage Systems)
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Article
Mitigating Children’s Pain and Anxiety during Blood Draw Using Social Robots
Electronics 2021, 10(10), 1211; https://doi.org/10.3390/electronics10101211 - 19 May 2021
Viewed by 548
Abstract
Young pediatric patients who undergo venipuncture or capillary blood sampling often experience high levels of pain and anxiety. This often results in distressed young patients and their parents, increased treatment times, and a higher workload for healthcare professionals. Social robots are a new [...] Read more.
Young pediatric patients who undergo venipuncture or capillary blood sampling often experience high levels of pain and anxiety. This often results in distressed young patients and their parents, increased treatment times, and a higher workload for healthcare professionals. Social robots are a new and promising tool to mitigate children’s pain and anxiety. This study aims to purposefully design and test a social robot for mitigating stress and anxiety during blood draw of children. We first programmed a social robot based on the requirements expressed by experienced healthcare professionals during focus group sessions. Next, we designed a randomized controlled experiment in which the social robot was applied as a distraction method to measure its capacity to mitigate pain and anxiety in children during blood draw in a children’s hospital setting. Children who interacted with the robot showed significantly lower levels of anxiety before actual blood collection, compared to children who received regular medical treatment. Children in the middle classes of primary school (aged 6–9) seemed especially sensitive to the robot’s ability to mitigate pain and anxiety before blood draw. Children’s parents overall expressed strong positive attitudes toward the use and effectiveness of the social robot for mitigating pain and anxiety. The results of this study demonstrate that social robots can be considered a new and effective tool for lowering children’s anxiety prior to the distressing medical procedure of blood collection. Full article
(This article belongs to the Special Issue Human Computer Interaction and Its Future)
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Article
Backstepping Predictive Control of Hybrid Microgrids Interconnected by Neutral Point Clamped Converters
Electronics 2021, 10(10), 1210; https://doi.org/10.3390/electronics10101210 - 19 May 2021
Viewed by 311
Abstract
In this work, DC and AC parts of hybrid microgrids are interconnected by a neutral point clamped—NPC converter controlled using a new backstepping predictive (BP) method. The NPC converter is controlled to operate in the DC microgrid voltage control mode or in the [...] Read more.
In this work, DC and AC parts of hybrid microgrids are interconnected by a neutral point clamped—NPC converter controlled using a new backstepping predictive (BP) method. The NPC converter is controlled to operate in the DC microgrid voltage control mode or in the AC microgrid power control mode. The novel backstepping predictive controller is designed using the dq state space dynamic model of the NPC converter connected to the hybrid microgrid. The designed BP controller regulates the DC voltage or AC injected power, balances the capacitor voltages, controls the AC currents, and enforces the near unity power factor. Simulation (MATLAB/Simulink) and experimental (laboratory prototype) results show that the converter can regulate the DC voltage in the DC microgrid interconnection point, by adjusting the AC power conversion to compensate variations on the loads or on the distributed renewable energy sources in the DC microgrid. AC currents are sinusoidal with low harmonic distortion. The obtained BP controller is faster at balancing capacitor voltages than PWM (pulse width modulation) control with carrier offset. The fast AC power response allows the converter to be used as a primary frequency regulator of the AC microgrid. This research is appropriate for power and voltage control in hybrid microgrids with renewable energy. Full article
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Article
Mitigation of the Effects of Network Outage on Video QoE Using a Sender Buffer
Electronics 2021, 10(10), 1209; https://doi.org/10.3390/electronics10101209 - 19 May 2021
Viewed by 253
Abstract
With the growth of multimedia applications and the mobile Internet, quality sense and quality expectation of the end-user are rising rapidly. A small notable distortion in the multimedia applications may degrade the degree of delight of the user, who is very considerate of [...] Read more.
With the growth of multimedia applications and the mobile Internet, quality sense and quality expectation of the end-user are rising rapidly. A small notable distortion in the multimedia applications may degrade the degree of delight of the user, who is very considerate of the video Quality of Experience (QoE). During live streaming, a network outage may result in video freezes and video jumps. To dampen the impact of a network outage on the video QoE, we propose the use of a well-sized sender buffer. We present the concept, derive key analytical relations, and perform a set of subjective tests. Based on those, we report a significant enhancement of user ratings due to the proposed sender buffer in the presence of network outages. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
Is There a Predisposition towards the Use of New Technologies within the Traffic Field of Emerging Countries? The Case of the Dominican Republic
Electronics 2021, 10(10), 1208; https://doi.org/10.3390/electronics10101208 - 19 May 2021
Viewed by 268
Abstract
Technological devices are becoming more and more integrated in the management and control of traffic in big cities. The population perceives the benefits provided by these systems, and, therefore, citizens usually have a favorable opinion of them. However, emerging countries, which have fewer [...] Read more.
Technological devices are becoming more and more integrated in the management and control of traffic in big cities. The population perceives the benefits provided by these systems, and, therefore, citizens usually have a favorable opinion of them. However, emerging countries, which have fewer available infrastructures, could present a certain lack of trust. The objective of this work is to detect the level of knowledge and predisposition towards the use of new technologies in the transportation field of the Dominican Republic. For this study, the National Survey on Mobility was administered to a sample of Dominican citizens, proportional to the ONE census and to sex, age and province. The knowledge of ITS topics, as well as the use of mobile applications for mobility, are scarce; however, there was a significant increase that can be observed in only one year. Moreover, technology is, in general, positively assessed for what concerns the improvement of the traffic field, even though there is a lack of predisposition to provide one’s personal data, which is necessary for these devices. The process of technological development in the country must be backed up by laws that protect the citizens’ privacy. Thus, technologies that can improve road safety, mobility and sustainability can be implemented in the country. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
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Editorial
Autonomous Vehicles Technological Trends
Electronics 2021, 10(10), 1207; https://doi.org/10.3390/electronics10101207 - 19 May 2021
Viewed by 312
Abstract
One of the technologies widely considered to be the most promising for reducing a number of traffic-related problems, including traffic jams, safety within and outside of cities, among others, is the autonomous vehicle [...] Full article
(This article belongs to the Special Issue Autonomous Vehicles Technology)
Article
Application of Logistic Regression Algorithm in the Interpretation of Dissolved Gas Analysis for Power Transformers
Electronics 2021, 10(10), 1206; https://doi.org/10.3390/electronics10101206 - 19 May 2021
Viewed by 276
Abstract
Dissolved gas analysis (DGA) is one of the regular routine tests accepted by worldwide utilities to detect power transformer incipient faults. While the DGA measurement has fully matured since the development of offline and online sensors, interpretation of the DGA results still calls [...] Read more.
Dissolved gas analysis (DGA) is one of the regular routine tests accepted by worldwide utilities to detect power transformer incipient faults. While the DGA measurement has fully matured since the development of offline and online sensors, interpretation of the DGA results still calls for advanced approaches to automate and standardize the process. Current industry practice relies on various interpretation techniques that are reported to be inconsistent and, in some cases, unreliable. This paper presents a new application for the advanced logistic regression algorithm to improve the reliability of the DGA interpretation process. In this regard, regularized logistic regression is used to improve the accuracy of the DGA interpretation process. Results reveal the superior features of the proposed logistic regression approach over the conventional and artificial intelligence techniques presented in the literature. Full article
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Article
Strong-Weak Feature Alignment for 3D Object Detection
Electronics 2021, 10(10), 1205; https://doi.org/10.3390/electronics10101205 - 18 May 2021
Viewed by 302
Abstract
Object detection in 3D point clouds is still a challenging task in autonomous driving. Due to the inherent occlusion and density changes of the point cloud, the data distribution of the same object will change dramatically. Especially, the incomplete data with sparsity or [...] Read more.
Object detection in 3D point clouds is still a challenging task in autonomous driving. Due to the inherent occlusion and density changes of the point cloud, the data distribution of the same object will change dramatically. Especially, the incomplete data with sparsity or occlusion can not represent the complete characteristics of the object. In this paper, we proposed a novel strong–weak feature alignment algorithm between complete and incomplete objects for 3D object detection, which explores the correlations within the data. It is an end-to-end adaptive network that does not require additional data and can be easily applied to other object detection networks. Through a complete object feature extractor, we achieve a robust feature representation of the object. It serves as a guarding feature to help the incomplete object feature generator to generate effective features. The strong–weak feature alignment algorithm reduces the gap between different states of the same object and enhances the ability to represent the incomplete object. The proposed adaptation framework is validated on the KITTI object benchmark and gets about 6% improvement in detection average precision on 3D moderate difficulty compared to the basic model. The results show that our adaptation method improves the detection performance of incomplete 3D objects. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
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Article
Solid-State DC Circuit Breakers and Their Comparison in Modular Multilevel Converter Based-HVDC Transmission System
Electronics 2021, 10(10), 1204; https://doi.org/10.3390/electronics10101204 - 18 May 2021
Viewed by 672
Abstract
This paper proposes a new and surge-less solid-state direct current (DC) circuit breaker in a high-voltage direct current (HVDC) transmission system to clear the short-circuit fault. The main purpose is the fast interruption and surge-voltage and over-current suppression capability analysis of the breaker [...] Read more.
This paper proposes a new and surge-less solid-state direct current (DC) circuit breaker in a high-voltage direct current (HVDC) transmission system to clear the short-circuit fault. The main purpose is the fast interruption and surge-voltage and over-current suppression capability analysis of the breaker during the fault. The breaker is equipped with series insulated-gate bipolar transistor (IGBT) switches to mitigate the stress of high voltage on the switches. Instead of conventional metal oxide varistor (MOV), the resistance–capacitance freewheeling diodes branch is used to bypass the high fault current and repress the over-voltage across the circuit breaker. The topology and different operation modes of the proposed breaker are discussed. In addition, to verify the effectiveness of the proposed circuit breaker, it is compared with two other types of surge-less solid-state DC circuit breakers in terms of surge-voltage and over-current suppression. For this purpose, MATLAB Simulink simulation software is used. The system is designed for the transmission of 20 MW power over a 120 km distance where the voltage of the transmission line is 220 kV. The results show that the fault current is interrupted in a very short time and the surge-voltage and over-current across the proposed breaker are considerably reduced compared to other topologies. Full article
(This article belongs to the Special Issue Multifaceted Applications of Power Electronics)
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Article
High-Frequency and High-Voltage Asymmetric Bipolar Pulse Generator for Electroporation Based Technologies and Therapies
Electronics 2021, 10(10), 1203; https://doi.org/10.3390/electronics10101203 - 18 May 2021
Viewed by 310
Abstract
Currently, in high-frequency electroporation, much progress has been made but limited to research groups with custom-made laboratory prototype electroporators. According to the review of electroporators and economic evaluations, there is still an area of pulse parameters that needs to be investigated. The development [...] Read more.
Currently, in high-frequency electroporation, much progress has been made but limited to research groups with custom-made laboratory prototype electroporators. According to the review of electroporators and economic evaluations, there is still an area of pulse parameters that needs to be investigated. The development of an asymmetric bipolar pulse generator with a maximum voltage of 4 kV and minimum duration time of a few hundred nanoseconds, would enable in vivo evaluation of biological effects of high-frequency electroporation pulses. Herein, from a series of most commonly used drivers and optical isolations in high-voltage pulse generators the one with optimal characteristics was used. In addition, the circuit topology of the developed device is described in detail. The developed device is able to generate 4 kV pulses, with theoretical 131 A maximal current and 200 ns minimal pulse duration, the maximal pulse repetition rate is 2 MHz and the burst maximal repetition rate is 1 MHz. The device was tested in vivo. The effectiveness of electrochemotherapy of high-frequency electroporation pulses is compared to “classical” electrochemotherapy pulses. In vivo electrochemotherapy with high-frequency electroporation pulses was at least as effective as with “classical” well-established electric pulses, resulting in 86% and 50% complete responses, respectively. In contrast to previous reports, however, muscle contractions were comparable between the two protocols. Full article
(This article belongs to the Section Bioelectronics)
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Article
Mechanism Analysis of Dynamic On-State Resistance Degradation for a Commercial GaN HEMT Using Double Pulse Test
Electronics 2021, 10(10), 1202; https://doi.org/10.3390/electronics10101202 - 18 May 2021
Viewed by 369
Abstract
The dynamic on-resistance (RON) behavior of one commercial GaN HEMT device with p-GaN gate is investigated under hard-switching conditions. The non-monotonic performance of dynamic RON with off-state voltage ranging from 50 to 400 V is ascribed to the “leaky dielectric” [...] Read more.
The dynamic on-resistance (RON) behavior of one commercial GaN HEMT device with p-GaN gate is investigated under hard-switching conditions. The non-monotonic performance of dynamic RON with off-state voltage ranging from 50 to 400 V is ascribed to the “leaky dielectric” model. The highest normalized RON value of 1.22 appears at 150 and 200 V. The gradual increase and following maximum of dynamic RON are found when the device is exposed to a stress voltage for an extended stress time under 100 and 200 V, which is due to a much longer trapping time compared to detrapping time related to deep acceptors and donors. No obvious RON degradation, thanks to the suppressed trapping effect, is observed at higher VDS. From the multi-pulse test, the dynamic RON is seen to be insensitive to the frequency. It is demonstrated that the leakage, especially under source and drain contact, is a key issue in the dynamic resistance degradation. Full article
(This article belongs to the Special Issue GaN-Based Power Electronic Devices and Their Applications)
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Article
Bone Metastasis Detection in the Chest and Pelvis from a Whole-Body Bone Scan Using Deep Learning and a Small Dataset
Electronics 2021, 10(10), 1201; https://doi.org/10.3390/electronics10101201 - 18 May 2021
Viewed by 278
Abstract
The aim of this study was to establish an early diagnostic system for the identification of the bone metastasis of prostate cancer in whole-body bone scan images by using a deep convolutional neural network (D-CNN). The developed system exhibited satisfactory performance for a [...] Read more.
The aim of this study was to establish an early diagnostic system for the identification of the bone metastasis of prostate cancer in whole-body bone scan images by using a deep convolutional neural network (D-CNN). The developed system exhibited satisfactory performance for a small dataset containing 205 cases, 100 of which were of bone metastasis. The sensitivity and precision for bone metastasis detection and classification in the chest were 0.82 ± 0.08 and 0.70 ± 0.11, respectively. The sensitivity and specificity for bone metastasis classification in the pelvis were 0.87 ± 0.12 and 0.81 ± 0.11, respectively. We propose the use of hard example mining for increasing the sensitivity and precision of the chest D-CNN. The developed system has the potential to provide a prediagnostic report for physicians’ final decisions. Full article
(This article belongs to the Special Issue Precision Healthcare-Oriented Artificial Intelligence)
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Article
A Novel Low Power Method of Combining Saliency and Segmentation for Mobile Displays
Electronics 2021, 10(10), 1200; https://doi.org/10.3390/electronics10101200 - 18 May 2021
Viewed by 250
Abstract
Saliency, which means the area human vision is concentrated, can be used in many applications, such as enemy detection in solider goggles and person detection in an auto-driving car. In recent years, saliency is obtained instead of human eyes using a model in [...] Read more.
Saliency, which means the area human vision is concentrated, can be used in many applications, such as enemy detection in solider goggles and person detection in an auto-driving car. In recent years, saliency is obtained instead of human eyes using a model in an automated way in HMD (Head Mounted Display), smartphones, and VR (Virtual Reality) devices based on mobile displays; however, such a mobile device needs too much power to maintain saliency on a mobile display. Therefore, low power saliency methods have been important. CURA tried to power down, according to the saliency level, while keeping human visual satisfaction. But it still has some artifacts due to the difference in brightness at the boundary of the region divided by saliency. In this paper, we propose a new segmentation-based saliency-aware low power approach to minimize the artifacts. Unlike CURA, our work considers visual perceptuality and power management at the saliency level and at the segmented region level for each saliency. Through experiments, our work achieves low power in each region divided by saliency and in the segmented regions in each saliency region, while maintaining human visual satisfaction for saliency. In addition, it maintains good image distortion quality while removing artifacts efficiently. Full article
(This article belongs to the Special Issue Design and Implementation of Efficient Future Memory Systems)
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Article
A Novel Energy-Efficiency Optimization Approach Based on Driving Patterns Styles and Experimental Tests for Electric Vehicles
Electronics 2021, 10(10), 1199; https://doi.org/10.3390/electronics10101199 - 18 May 2021
Viewed by 750
Abstract
This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the [...] Read more.
This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the differential drive. The electrical inverter model and the power-train efficiency are established by lookup tables determined by power tests in a dynamometric bank. The optimization problem is focused on maximizing energy-efficiency between the wheel power and battery pack, not only to maintain but also to improve its value by modifying the state of charge (SOC). The solution is found by means of a Particle Swarm Optimization (PSO) algorithm. The optimizer simulation results validate the increasing efficiency with the speed setpoint variations, and also show that the battery SOC is improved. The best results are obtained when the speed variation is between 5% and 6%. Full article
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Article
VO2 Carbon Nanotube Composite Memristor-Based Cellular Neural Network Pattern Formation
Electronics 2021, 10(10), 1198; https://doi.org/10.3390/electronics10101198 - 18 May 2021
Viewed by 299
Abstract
A cellular neural network (CNN) based on a VO2 carbon nanotube memristor is proposed in this paper. The device is modeled by SPICE at first, and then the cell dynamic characteristics based on the device are analyzed. It is pointed out that [...] Read more.
A cellular neural network (CNN) based on a VO2 carbon nanotube memristor is proposed in this paper. The device is modeled by SPICE at first, and then the cell dynamic characteristics based on the device are analyzed. It is pointed out that only when the cell is at the sharp edge of chaos can the cell be successfully awakened after the CNN is formed. In this paper, we give the example of a 5 × 5 CNN, set specific initial conditions and observe the formed pattern. Because the generated patterns are affected by the initial conditions, the cell power supply can be pre-programmed to obtain specific patterns, which can be applied to the future information processing system based on complex space–time patterns, especially in the field of computer vision. Full article
(This article belongs to the Special Issue Memristive Devices and Systems: Modelling, Properties & Applications)
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Article
Phase-Based Accurate Power Modeling for Mobile Application Processors
Electronics 2021, 10(10), 1197; https://doi.org/10.3390/electronics10101197 - 17 May 2021
Viewed by 319
Abstract
Modern mobile application processors are required to execute heavier workloads while the battery capacity is rarely increased. This trend leads to the need for a power model that can analyze the power consumed by CPU and GPU at run-time, which are the key [...] Read more.
Modern mobile application processors are required to execute heavier workloads while the battery capacity is rarely increased. This trend leads to the need for a power model that can analyze the power consumed by CPU and GPU at run-time, which are the key components of the application processor in terms of power savings. We propose novel CPU and GPU power models based on the phases using performance monitoring counters for smartphones. Our phase-based power models employ combined per-phase power modeling methods to achieve more accurate power consumption estimations, unlike existing power models. The proposed CPU power model shows estimation errors of 2.51% for ARM Cortex A-53 and 1.97% for Samsung M1 on average, and the proposed GPU power model shows an average error of 8.92% for the Mali-T880. In addition, we integrate proposed CPU and GPU models with the latest display power model into a holistic power model. Our holistic power model can estimate the smartphone′s total power consumption with an error of 6.36% on average while running nine 3D game benchmarks, improving the error rate by about 56% compared with the latest prior model. Full article
(This article belongs to the Special Issue Design and Implementation of Efficient Future Memory Systems)
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Article
Metamaterial Impedance Matching Network for Ambient RF-Energy Harvesting Operating at 2.4 GHz and 5 GHz
Electronics 2021, 10(10), 1196; https://doi.org/10.3390/electronics10101196 - 17 May 2021
Viewed by 340
Abstract
This paper points out the viability of the utilization of metamaterial transmission lines as a multifrequency impedance matching network, improving RF-Energy Harvesting systems operating around 2.4 GHz and 5 GHz. Metamaterial transmission lines introduce additional degrees of freedom in the transmission line design, [...] Read more.
This paper points out the viability of the utilization of metamaterial transmission lines as a multifrequency impedance matching network, improving RF-Energy Harvesting systems operating around 2.4 GHz and 5 GHz. Metamaterial transmission lines introduce additional degrees of freedom in the transmission line design, providing the possibility to match the impedance in multiple bands. The impedance matching structure has been designed and optimized using ADS simulator to match the input impedance of a four-diode-bridge rectifier connected to an energy management system. The proposed Metamaterial Impedance Matching Network (MIMN) has been fabricated using standard PCB technologies and tested in a full operative ambient RF-Energy Harvesting System obtaining a DC output voltage of 1.8 V in a 6.8 mF supercapacitor. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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Article
Estimating Software Development Efforts Using a Random Forest-Based Stacked Ensemble Approach
Electronics 2021, 10(10), 1195; https://doi.org/10.3390/electronics10101195 - 17 May 2021
Viewed by 304
Abstract
Software Project Estimation is a challenging and important activity in developing software projects. Software Project Estimation includes Software Time Estimation, Software Resource Estimation, Software Cost Estimation, and Software Effort Estimation. Software Effort Estimation focuses on predicting the number of hours of work (effort [...] Read more.
Software Project Estimation is a challenging and important activity in developing software projects. Software Project Estimation includes Software Time Estimation, Software Resource Estimation, Software Cost Estimation, and Software Effort Estimation. Software Effort Estimation focuses on predicting the number of hours of work (effort in terms of person-hours or person-months) required to develop or maintain a software application. It is difficult to forecast effort during the initial stages of software development. Various machine learning and deep learning models have been developed to predict the effort estimation. In this paper, single model approaches and ensemble approaches were considered for estimation. Ensemble techniques are the combination of several single models. Ensemble techniques considered for estimation were averaging, weighted averaging, bagging, boosting, and stacking. Various stacking models considered and evaluated were stacking using a generalized linear model, stacking using decision tree, stacking using a support vector machine, and stacking using random forest. Datasets considered for estimation were Albrecht, China, Desharnais, Kemerer, Kitchenham, Maxwell, and Cocomo81. Evaluation measures used were mean absolute error, root mean squared error, and R-squared. The results proved that the proposed stacking using random forest provides the best results compared with single model approaches using the machine or deep learning algorithms and other ensemble techniques. Full article
(This article belongs to the Section Artificial Intelligence)
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Article
Grover on PIPO
Electronics 2021, 10(10), 1194; https://doi.org/10.3390/electronics10101194 - 17 May 2021
Viewed by 348
Abstract
The emergence of quantum computers is threatening the security of cryptography through various quantum algorithms. Among them, the Grover search algorithm is known to be efficient in accelerating brute force attacks on block cipher algorithms. To utilize the Grover’s algorithm for brute force [...] Read more.
The emergence of quantum computers is threatening the security of cryptography through various quantum algorithms. Among them, the Grover search algorithm is known to be efficient in accelerating brute force attacks on block cipher algorithms. To utilize the Grover’s algorithm for brute force attacks, block ciphers must be implemented in quantum circuits. In this paper, we present optimized quantum circuits of the SPN (Substitution Permutation Network) structured lightweight block cipher, namely the PIPO block cipher. In particular, the compact design of quantum circuits for the 8-bit Sbox is investigated. These optimization techniques are used to implement other cryptographic operations as quantum circuits. Finally, we evaluate quantum resources of Grover search algorithm for the PIPO block cipher in ProejctQ, a quantum simulator provided by IBM. Full article
(This article belongs to the Special Issue Recent Trends and Applications in Cybersecurity)
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Article
UAVs Path Planning under a Bi-Objective Optimization Framework for Smart Cities
Electronics 2021, 10(10), 1193; https://doi.org/10.3390/electronics10101193 - 17 May 2021
Viewed by 273
Abstract
Unmanned aerial vehicles (UAVs) have been used extensively for search and rescue operations, surveillance, disaster monitoring, attacking terrorists, etc. due to their growing advantages of low-cost, high maneuverability, and easy deployability. This study proposes a mixed-integer programming model under a multi-objective optimization framework [...] Read more.
Unmanned aerial vehicles (UAVs) have been used extensively for search and rescue operations, surveillance, disaster monitoring, attacking terrorists, etc. due to their growing advantages of low-cost, high maneuverability, and easy deployability. This study proposes a mixed-integer programming model under a multi-objective optimization framework to design trajectories that enable a set of UAVs to execute surveillance tasks. The first objective maximizes the cumulative probability of target detection to aim for mission planning success. The second objective ensures minimization of cumulative path length to provide a higher resource utilization goal. A two-step variable neighborhood search (VNS) algorithm is offered, which addresses the combinatorial optimization issue for determining the near-optimal sequence for cell visiting to reach the target. Numerical experiments and simulation results are evaluated in numerous benchmark instances. Results demonstrate that the proposed approach can favorably support practical deployability purposes. Full article
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