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Electronics, Volume 9, Issue 11 (November 2020) – 237 articles

Cover Story (view full-size image): AlGaN/GaN MISHEMTs with low temperature epitaxy (LTE) grown AlN as the gate dielectric have successfully been demonstrated for the first time. LTE is a novel deposition method combining physical vapor deposition and chemical vapor deposition, which allows the deposition of high-quality AlN films even at a low deposition temperature of 200 °C. After a post-gate annealing at 400 °C on the MIS-diode, a low minimum LTE-AlN and GaN density of interface states (Dit) value of 5.0 × 1011 cm-2eV-1 was extracted. This low Dit enables the AlGaN/GaN MISHEMTs reported in this work to achieve good device performance comparable to MISHEMTs using other gate dielectric deposition techniques. This study indicates that LTE-AlN with optimized post-gate annealing is a viable alternate method to realize good-performance AlGaN/GaN MISHEMTs. View this paper
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Article
Quantitative Analysis of Insulator Degradation in a Single Layer Solenoid by Renormalization of the Transmission Parameter
Electronics 2020, 9(11), 1984; https://doi.org/10.3390/electronics9111984 - 23 Nov 2020
Viewed by 816
Abstract
In this paper, a novel method to quantitatively analyze insulator degradation in a single layer solenoid is proposed. The suggested method employs renormalization of scattering parameters to efficiently detect changes of permittivity in a degraded solenoid. Firstly, a transmission line model, including a [...] Read more.
In this paper, a novel method to quantitatively analyze insulator degradation in a single layer solenoid is proposed. The suggested method employs renormalization of scattering parameters to efficiently detect changes of permittivity in a degraded solenoid. Firstly, a transmission line model, including a locally degraded part in the insulator, was developed, and it was determined that the phase information of the transmission parameter was very informative to check the permittivity change in the transmission line. To check the workability of this idea in a solenoid, a 30-turn single-layer solenoid was designed and fabricated, and 51 degraded states for mimicking insulation deterioration in each turn were introduced by installing additional insulator rings, which increased local relative permittivity. The phase data of the measured transmission parameter turned out to be useful for quantifying changes of the insulator in the solenoid. To maximize the detectability, the measured scattering parameters were renormalized with different reference impedances, which was very useful for detecting degradation in the transmission parameter. In this paper, detailed procedures for quantitatively analyzing degradation of an insulator are proposed and we verify that the suggested renormalization technique is very promising for effectively evaluating the degradation of a solenoid. Full article
(This article belongs to the Section Industrial Electronics)
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Article
Adaptive and Hybrid Idle–Hard Timeout Allocation and Flow Eviction Mechanism Considering Traffic Characteristics
Electronics 2020, 9(11), 1983; https://doi.org/10.3390/electronics9111983 - 23 Nov 2020
Cited by 4 | Viewed by 910
Abstract
Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics [...] Read more.
Software-defined networking (SDN) enables flexible fine-grained networking policies by allowing the SDN controller to install packet handling rules on distributed switches. The behaviour of SDN depends on the set of forwarding entries installed at the switch flow table. The increasing number of traffics from the proliferation of the Internet of Thing (IoT) devices increase the processing load on the controller and generates an additional number of entries stored in the flow table. However, the switch flow table memory (TCAM) cannot accommodate many entries. Packets from multimedia flows are usually large in size and thus suffer processing delay and require more flow set up requests. The SDN controller may be overloaded and face some scalability problems because it supports a limited number of requests from switches. OpenFlow uses timeout configuration to manage flow setup request. The conventional fixed timeout cannot cope up with the dynamic nature of traffic flows. This paper controls the frequent flow setup requests by proposing an adaptive and hybrid idle–hard timeout allocation (AH-IHTA). The algorithm considers traffic patterns, flow table usage ratio, and returns appropriate the timeout to different flows. The performance evaluations conducted have shown a 28% and 39% reduction in the flow setup request and flow eviction, respectively. Full article
(This article belongs to the Special Issue Future Networks: New Advances and Challenges)
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Article
Comparative Performance and Assessment Study of a Current-Fed DC-DC Resonant Converter Combining Si, SiC, and GaN-Based Power Semiconductor Devices
Electronics 2020, 9(11), 1982; https://doi.org/10.3390/electronics9111982 - 23 Nov 2020
Cited by 4 | Viewed by 989
Abstract
This paper focuses on the main reasons of low efficiency in a current-fed DC-DC resonant converter applied to photovoltaic (PV) isolated systems, comparing the effects derived by the overlapping time in the gate-signals (gate-source voltage) combining silicon (Si), silicon carbide (SiC), and gallium [...] Read more.
This paper focuses on the main reasons of low efficiency in a current-fed DC-DC resonant converter applied to photovoltaic (PV) isolated systems, comparing the effects derived by the overlapping time in the gate-signals (gate-source voltage) combining silicon (Si), silicon carbide (SiC), and gallium nitride (GaN)-based power devices. The results show that unidirectional switches (metal–oxide–semiconductor field-effect transistors (MOSFETs) plus diode) present hard switching as a result of the diode preventing the MOSFET capacitance of being discharged. The effectiveness of the converter was verified with a 200-W prototype with an input voltage range of 0–30.3 V, an output voltage of 200 V, and a switching frequency of 200 kHz. The reduction losses by applying GaN versus Si and SiC technologies are 66.49% and 53.57%, respectively. Alternatively, by applying SiC versus Si devices the reduction loss is 27.84%. Finally, according to the results, 60% of losses were caused by the diodes on both switches. Full article
(This article belongs to the Special Issue Innovative Technologies in Power Converters)
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Article
Sound Coding Color to Improve Artwork Appreciation by People with Visual Impairments
Electronics 2020, 9(11), 1981; https://doi.org/10.3390/electronics9111981 - 23 Nov 2020
Cited by 11 | Viewed by 1438
Abstract
The recent development of color coding in tactile pictograms helps people with visual impairments (PVI) appreciate the visual arts. The auditory sense, in conjunction with (or possibly as an alternative to) the tactile sense, would allow PVI to perceive colors in a way [...] Read more.
The recent development of color coding in tactile pictograms helps people with visual impairments (PVI) appreciate the visual arts. The auditory sense, in conjunction with (or possibly as an alternative to) the tactile sense, would allow PVI to perceive colors in a way that would be difficult to achieve with just a tactile stimulus. Sound coding colors (SCCs) can replicate three characteristics of colors, i.e., hue, chroma, and value, by matching them with three characteristics of sound, i.e., timbre, intensity, and pitch. This paper examines relationships between sound (melody) and color mediated by tactile pattern color coding and provides sound coding for hue, chroma, and value to help PVI deepen their relationship with visual art. Our two proposed SCC sets use melody to improve upon most SCC sets currently in use by adding more colors (18 colors in 6 hues). User experience and identification tests were conducted with 12 visually impaired and 8 sighted adults, and the results suggest that the SCC sets were helpful for the participants. Full article
(This article belongs to the Special Issue Multi-Sensory Interaction for Blind and Visually Impaired People)
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Article
DTaPO: Dynamic Thermal-Aware Performance Optimization for Dark Silicon Many-Core Systems
Electronics 2020, 9(11), 1980; https://doi.org/10.3390/electronics9111980 - 23 Nov 2020
Cited by 4 | Viewed by 960
Abstract
Future many-core systems need to handle high power density and chip temperature effectively. Some cores in many-core systems need to be turned off or ‘dark’ to manage chip power and thermal density. This phenomenon is also known as the dark silicon problem. This [...] Read more.
Future many-core systems need to handle high power density and chip temperature effectively. Some cores in many-core systems need to be turned off or ‘dark’ to manage chip power and thermal density. This phenomenon is also known as the dark silicon problem. This problem prevents many-core systems from utilizing and gaining improved performance from a large number of processing cores. This paper presents a dynamic thermal-aware performance optimization of dark silicon many-core systems (DTaPO) technique for optimizing dark silicon a many-core system performance under temperature constraint. The proposed technique utilizes both task migration and dynamic voltage frequency scaling (DVFS) for optimizing the performance of a many-core system while keeping system temperature in a safe operating limit. Task migration puts hot cores in low-power states and moves tasks to cooler dark cores to aggressively reduce chip temperature while maintaining high overall system performance. To reduce task migration overhead due to cold start, the source core (i.e., active core) keeps its L2 cache content during the initial migration phase. The destination core (i.e., dark core) can access it to reduce the impact of cold start misses. Moreover, the proposed technique limits tasks migration among cores that share the last level cache (LLC). In the case of major thermal violation and no cooler cores being available, DVFS is used to reduce the hot cores temperature gradually by reducing their frequency. Experimental results for different threshold temperatures show that DTaPO can keep the average system temperature below the thermal limit. Affirmatively, the execution time penalty is reduced by up to 18% compared with using only DVFS for all thermal thresholds. Moreover, the average peak temperature is reduced by up to 10.8°C. In addition, the experimental results show that DTaPO improves the system’s performance by up to 80% compared to optimal sprinting patterns (OSP) and reduces the temperature by up to 13.6°C. Full article
(This article belongs to the Special Issue High-Performance Computer Architectures and Applications)
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Article
A Study on Acer Mono Sap Integration Management System Based on Energy Harvesting Electric Device and Sap Big Data Analysis Model
Electronics 2020, 9(11), 1979; https://doi.org/10.3390/electronics9111979 - 23 Nov 2020
Cited by 2 | Viewed by 1141
Abstract
This study set out to invent an Information and Communication Technologies (ICT)-based smart Acer mono sap collection electric device to make efficient use of the labor force by reducing inefficient activities of old manual work to record sap exudation and state information. Based [...] Read more.
This study set out to invent an Information and Communication Technologies (ICT)-based smart Acer mono sap collection electric device to make efficient use of the labor force by reducing inefficient activities of old manual work to record sap exudation and state information. Based on the assumption that environmental information would have close connections with Acer mono sap exudation to reinforce the competitive edge of production in forest products, the study analyzed correlations between Acer mono sap exudation and environmental information and predicted Acer mono exudation. A smart collection of electric devices would gather data about Acer mono sap exudation per hour on outdoor temperature, humidity, conductivity, and wind direction and velocity, and was installed in four areas in the Republic of Korea, including Sancheong, Gwangyang, Geoje, and Inje. Collected data were used to analyze correlations between environmental information and Acer mono sap exudation using four different algorithms, including linear regression, Support Vector Machine (SVM), Artificial Neural Network (ANN), and random forest, to predict Acer mono sap exudation. Remarkable outcomes were obtained across all the algorithms except for linear regression, demonstrating close connections between environmental information and Acer mono sap exudation. The random forest model, which showed the most outstanding performance, was used to make a mobile app capable of providing predicted Acer mono sap exudation and collected environmental information. Full article
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Article
A Heterogeneous Inductive Power Transfer System for Electric Vehicles with Spontaneous Constant Current and Constant Voltage Output Features
Electronics 2020, 9(11), 1978; https://doi.org/10.3390/electronics9111978 - 23 Nov 2020
Cited by 4 | Viewed by 704
Abstract
An inductively coupled wireless power transfer system is proposed in this paper, which is designed to comply with the battery’s load characteristics. A loosely coupled transformer with high coupling coefficient is proposed. A heterogeneous compensation topology is proposed which is able to switch [...] Read more.
An inductively coupled wireless power transfer system is proposed in this paper, which is designed to comply with the battery’s load characteristics. A loosely coupled transformer with high coupling coefficient is proposed. A heterogeneous compensation topology is proposed which is able to switch between constant current and constant voltage output mode according to the load resistance. The output characteristic curve agrees with the charging curve of the battery in a whole cycle. The proposed topology has a misalignment range of 300 mm where the coupling coefficient is 0.2. A 3 kW experimental platform is established to verify the theoretical analysis, and the experimental results show that the proposed loosely coupled transformer has high coupling coefficient and high power transmission efficiency (95.2% in aligned position) within a large misalignment range, which agrees with the charging scenario of the electric vehicle. Full article
(This article belongs to the Section Power Electronics)
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Article
Identification of the Use of Unauthorized Apps in the O2O Service by Combining Online Events and Offline Conditions
Electronics 2020, 9(11), 1977; https://doi.org/10.3390/electronics9111977 - 22 Nov 2020
Viewed by 862
Abstract
A model for detecting unauthorized Apps use events by combined analysis of situation information in an offline service and user behavior in an online environment is proposed. The detection and response to abnormal behavior in the O2O service environment can be focused on [...] Read more.
A model for detecting unauthorized Apps use events by combined analysis of situation information in an offline service and user behavior in an online environment is proposed. The detection and response to abnormal behavior in the O2O service environment can be focused on providers, whose decisions change dynamically based on the offline market status and conditions. However, the method for identifying the user’s tools and detecting the usage pattern of the service user were developed in the existing online service environment. Thus, in order to identify abnormal behavior in the O2O service environment, we conducted an experiment to identify the abnormal behavior of providers of smart mobility services, a representative O2O service. In the experiment, the range of normal behavior of a taxi drivers was identified, which was prepared on the basis of the test result directly executed by an expert. The optimal features were selected in order to effectively detect abnormal behavior from the event data relating to the service call acceptance behavior. In addition, by processing the collected data based on the selected features by using various machine-learning classification algorithms, we derived a detection and prediction model that is 98.28% accurate with a prediction result of more than 74% based on the F1 score. Based on these results, we expect to be able to respond to abnormal behavior that may occur in various types of O2O services. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
A Learning-Based Framework for Circuit Path Level NBTI Degradation Prediction
by and
Electronics 2020, 9(11), 1976; https://doi.org/10.3390/electronics9111976 - 22 Nov 2020
Cited by 2 | Viewed by 827
Abstract
Negative bias temperature instability (NBTI) has become one of the major causes for temporal reliability degradation of nanoscale circuits. Due to its complex dependence on operating conditions, it is a tremendous challenge to the existing timing analysis flow. In order to get the [...] Read more.
Negative bias temperature instability (NBTI) has become one of the major causes for temporal reliability degradation of nanoscale circuits. Due to its complex dependence on operating conditions, it is a tremendous challenge to the existing timing analysis flow. In order to get the accurate aged delay of the circuit, previous research mainly focused on the gate level or lower. This paper proposes a low-runtime and high-accuracy machining learning framework on the circuit path level firstly, which can be formulated as a multi-input–multioutput problem and solved using a linear regression model. A large number of worst-case path candidates from ISCAS’85, ISCAS’89, and ITC’99 benchmarks were used for training and inference in the experiment. The results show that our proposed approach achieves significant runtime speed-up with minimal loss of accuracy. Full article
(This article belongs to the Section Circuit and Signal Processing)
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Article
Electric Field Evaluation Using the Finite Element Method and Proxy Models for the Design of Stator Slots in a Permanent Magnet Synchronous Motor
Electronics 2020, 9(11), 1975; https://doi.org/10.3390/electronics9111975 - 22 Nov 2020
Cited by 11 | Viewed by 1065
Abstract
The efficiency of electric motors is being improved every day and projects with design variations can improve their performance. Among electric motors, the Permanent Magnet Synchronous Machine (PMSM) is being increasingly used, because of its growing use in electric vehicles. Simulating design variations [...] Read more.
The efficiency of electric motors is being improved every day and projects with design variations can improve their performance. Among electric motors, the Permanent Magnet Synchronous Machine (PMSM) is being increasingly used, because of its growing use in electric vehicles. Simulating design variations using the Finite Element Method (FEM) can improve PMSM design, and by optimizing the parameters based on the FEM, even better results can be achieved. The design of the PMSM stator slots must be evaluated, as conductors are accommodated and an electrical potential is applied at this location. The FEM parameters are varied, and the results can be used to build an approximate model, known as a proxy model. The proxy model can then be used in a mathematical programming problem to optimize the design of stators that have less electric field in certain regions, thus reducing the chance of developing a failure. The results of the proposed methodology show that its application is promising for machine design and can also be used for the design of other systems. Full article
(This article belongs to the Special Issue Analysis and Optimal Design Method for Electric Machine and Devices)
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Article
Two Step Random Access Latency Improvement in Congested beyond 5G Networks
Electronics 2020, 9(11), 1974; https://doi.org/10.3390/electronics9111974 - 22 Nov 2020
Cited by 3 | Viewed by 958
Abstract
It has been recently proposed to enhance the performance of random access procedure (RAP) by downsizing the current four step RAP (4s-RAP) to two step RAP (2s-RAP) in order to address ultra reliable low latency communications (URLLC) in 5G and beyond 5G wireless [...] Read more.
It has been recently proposed to enhance the performance of random access procedure (RAP) by downsizing the current four step RAP (4s-RAP) to two step RAP (2s-RAP) in order to address ultra reliable low latency communications (URLLC) in 5G and beyond 5G wireless networks. 2s-RAP reduces latency and signaling overhead by manifesting only one round trip between gNB (5G base station) and the UE (user equipment). However, the low latency goal of 2s-RAP is challenged by the increase in the number of UEs in the future wireless networks. Numerous UEs competing for limited random access resources would result in frequent collisions followed by multiple random access reattempts, resulting in increased delay. In this paper, we propose novel algorithms to improve the performance of 2s-RAP in a congested environment. In the proposed algorithms, the UEs can perform RAP reattempts in either 2s-RAP or 4s-RAP based on the channel conditions such that the chances of RAP failure due to poor channels are reduced. They can also transit to 4s-RAP from the initially selected 2s-RAP in order to alleviate the congestion in 2s-RAP. The proposed algorithms are probabilistically analyzed based on collision probabilities and success rates. We employ our derived mathematical equations, as well as carry out simulation evaluations, to present the performance results effectively. Full article
(This article belongs to the Special Issue Beyond 5G Evolution)
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Article
Reverse Conduction Loss Minimization in GaN‑Based PMSM Drive
Electronics 2020, 9(11), 1973; https://doi.org/10.3390/electronics9111973 - 22 Nov 2020
Cited by 2 | Viewed by 882
Abstract
Gallium nitride (GaN) devices are becoming more popular in power semiconductor converters. Due to the absence of the freewheeling substrate diode, the reverse conduction region is used in GaN transistors to conduct the freewheeling current. However, the voltage drop across the device in [...] Read more.
Gallium nitride (GaN) devices are becoming more popular in power semiconductor converters. Due to the absence of the freewheeling substrate diode, the reverse conduction region is used in GaN transistors to conduct the freewheeling current. However, the voltage drop across the device in the reverse conduction mode is relatively high, causing additional power losses. These losses can be optimized by adequately adjusting the dead-time issued by the microcontroller. The dead-time loss minimization strategies presented in the literature have the common disadvantage that either additional hardware or specific converter data are needed for their proper operation. Therefore, this paper’s motivation is to present a novel dead-time loss minimization method for GaN-based high-frequency switching converters for electric drives that does not impose additional requirements on the hardware design phase and converter data acquisition. The method is based on optimizing the current controllers’ output with a simple perturb-and-observe tracker. The experimental results show that the proposed approach can minimize the dead-time losses over the whole drive’s operating range at the cost of only a moderate increase in software complexity. Full article
(This article belongs to the Section Power Electronics)
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Review
A Review on Deep Learning-Based Approaches for Automatic Sonar Target Recognition
Electronics 2020, 9(11), 1972; https://doi.org/10.3390/electronics9111972 - 22 Nov 2020
Cited by 28 | Viewed by 4358
Abstract
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement and study of acoustic sources in the underwater atmosphere. With [...] Read more.
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement and study of acoustic sources in the underwater atmosphere. With the rapid development in science and technology, the advancement in sonar systems has increased, resulting in a decrement in underwater casualties. The sonar signal processing and automatic target recognition using sonar signals or imagery is itself a challenging process. Meanwhile, highly advanced data-driven machine-learning and deep learning-based methods are being implemented for acquiring several types of information from underwater sound data. This paper reviews the recent sonar automatic target recognition, tracking, or detection works using deep learning algorithms. A thorough study of the available works is done, and the operating procedure, results, and other necessary details regarding the data acquisition process, the dataset used, and the information regarding hyper-parameters is presented in this article. This paper will be of great assistance for upcoming scholars to start their work on sonar automatic target recognition. Full article
(This article belongs to the Section Artificial Intelligence)
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Article
Hybrid Power System Optimization in Mission-Critical Communication
Electronics 2020, 9(11), 1971; https://doi.org/10.3390/electronics9111971 - 22 Nov 2020
Viewed by 693
Abstract
One of the common problems faced by Telecommunication (TLC) companies is the lack of power supply, usually for those appliances with scarce chances of grid connection often placed in remote zones. This issue is more and more critical if the radio network has [...] Read more.
One of the common problems faced by Telecommunication (TLC) companies is the lack of power supply, usually for those appliances with scarce chances of grid connection often placed in remote zones. This issue is more and more critical if the radio network has the specific task of guaranteeing the so-called “mission-critical communications”. This manuscript aims to propose and assess a viable solution to optimize the power supply and maintenance operations required to assure the proper functionality in such critical and remote sites. In particular, the main goals are defining a method to select the critical sites in an extensive and composite radio system and designing the hybrid power system in a way to improve the service availability and technical-economic benefits of the whole mission-critical TLC system. Finally, the proposed method and related procedures are tested and validated in a real scenario. Full article
(This article belongs to the Special Issue Emerging Technologies for Photovoltaic Solar Energy)
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Article
A Simulation Tool for Evaluating Video Streaming Architectures in Vehicular Network Scenarios
Electronics 2020, 9(11), 1970; https://doi.org/10.3390/electronics9111970 - 22 Nov 2020
Cited by 1 | Viewed by 743
Abstract
An integrated simulation tool called Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN) is presented. This framework is intended to allow users to conduct experiments related to video transmission in vehicular networks by means of simulation. Research on this topic requires the use [...] Read more.
An integrated simulation tool called Video Delivery Simulation Framework over Vehicular Networks (VDSF-VN) is presented. This framework is intended to allow users to conduct experiments related to video transmission in vehicular networks by means of simulation. Research on this topic requires the use of many independent tools, such as traffic and network simulators, intermediate frameworks, video encoders and decoders, converters, platform-dependent scripting languages, data visualisation packages and spreadsheets, and some other tasks are performed manually. The lack of tools necessary to carry out all these tasks in an integrated and efficient way formed the motivation for the development of the VDSF-VN framework. It is managed via two user-friendly applications, GatcomSUMO and GatcomVideo, which allow all the necessary tasks to be accomplished. The first is primarily used to build the network scenario and set up the traffic flows, whereas the second involves the delivery process of the whole video, encoding/decoding video, running simulations, and processing all the experimental results to automatically provide the requested figures, tables and reports. This multiplatform framework is intended to fill the existing gap in this field, and has been successfully used in several experimental tests of vehicular networks. Full article
(This article belongs to the Special Issue Multimedia Content Delivery over Mobile Networks)
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Article
A Reference-Guided Double Pipeline Face Image Completion Network
Electronics 2020, 9(11), 1969; https://doi.org/10.3390/electronics9111969 - 22 Nov 2020
Viewed by 1134
Abstract
The existing face image completion approaches cannot be utilized to rationally complete damaged face images where their identity information is completely lost due to being obscured by center masks. Hence, in this paper, a reference-guided double-pipeline face image completion network (RG-DP-FICN) is designed [...] Read more.
The existing face image completion approaches cannot be utilized to rationally complete damaged face images where their identity information is completely lost due to being obscured by center masks. Hence, in this paper, a reference-guided double-pipeline face image completion network (RG-DP-FICN) is designed within the framework of the generative adversarial network (GAN) completing the identity information of damaged images utilizing reference images with the same identity as damaged images. To reasonably integrate the identity information of reference images into completed images, the reference image is decoupled into identity features (e.g., the contour of eyes, eyebrows, nose) and pose features (e.g., the orientation of face and the positions of the facial features), and then the resulting identity features are fused with posture features of damaged images. Specifically, a lightweight identity predictor is used to extract the pose features; an identity extraction module is designed to compress and globally extract the identity features of the reference images, and an identity transfer module is proposed to effectively fuse identity and pose features by performing identity rendering on different receptive fields. Furthermore, quantitative and qualitative evaluations are conducted on a public dataset CelebA-HQ. Compared to the state-of-the-art methods, the evaluation metrics peak signal-to-noise ratio (PSNR), structure similarity index (SSIM) and L1 loss are improved by 2.22 dB, 0.033 and 0.79%, respectively. The results indicate that RG-DP-FICN can generate completed images with reasonable identity, with superior completion effect compared to existing completion approaches. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
A Power Efficient Frequency Divider With 55 GHz Self-Oscillating Frequency in SiGe BiCMOS
Electronics 2020, 9(11), 1968; https://doi.org/10.3390/electronics9111968 - 21 Nov 2020
Cited by 3 | Viewed by 946
Abstract
A power efficient static frequency divider in commercial 55 nm SiGe BiCMOS technology is reported. A standard Current Mode Logic (CML)-based architecture is adopted, and optimization of layout, biasing and transistor sizes allows achieving a maximum input frequency of 63 GHz and a [...] Read more.
A power efficient static frequency divider in commercial 55 nm SiGe BiCMOS technology is reported. A standard Current Mode Logic (CML)-based architecture is adopted, and optimization of layout, biasing and transistor sizes allows achieving a maximum input frequency of 63 GHz and a self-oscillating frequency of 55 GHz, while consuming 23.7 mW from a 3 V supply. This results in high efficiency with respect to other static frequency dividers in BiCMOS technology presented in the literature. The divider topology does not use inductors, thus optimizing the area footprint: the divider core occupies 60 × 65 μm2 on silicon. Full article
(This article belongs to the Section Microelectronics)
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Article
Subthreshold Characteristics of AlGaN/GaN MIS-FinFETs with Controlling Threshold Voltages
Electronics 2020, 9(11), 1967; https://doi.org/10.3390/electronics9111967 - 21 Nov 2020
Cited by 1 | Viewed by 766
Abstract
AlGaN/GaN metal-insulator-semiconductor field-effect transistors with fin structures (AlGaN/GaN MIS-FinFETs) were fabricated and characterized by changing fin width and using different dielectric layers. The FinFET with 20 nm-thick SiO2 dielectric layer exhibits a very small subthreshold swing (SS) of 56 mV/decade. However, the [...] Read more.
AlGaN/GaN metal-insulator-semiconductor field-effect transistors with fin structures (AlGaN/GaN MIS-FinFETs) were fabricated and characterized by changing fin width and using different dielectric layers. The FinFET with 20 nm-thick SiO2 dielectric layer exhibits a very small subthreshold swing (SS) of 56 mV/decade. However, the threshold voltage of the device is too low to ensure low off-state leakage current (at the gate voltage of 0 V), even though the fin width of the device is reduced to 30 nm, which would not meet the requirement for low standby power consumption. On the other hand, the FinFET with a 10 nm-thick Al2O3 dielectric layer and a much wider fin width of 100 nm shows normally-off operation with a threshold voltage of 0.8 V, SS of 63 mV/dec, and very low off-state current of 1 nA/mm. When the fin width is reduced to 40 nm, the threshold voltage of the FinFET is increased to 2.3 V and the SS is decreased to 52 mV/decade. These excellent switching performances convince us that the FinFETs might be promising either for low voltage logic or for efficient power switching applications. The observed SS values, which are smaller than the theoretical Boltzmann limit (60 mV/decade), can be explained by the concept of the voltage-dependent effective channel width. Full article
(This article belongs to the Section Microelectronics)
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Communication
Does Deep Learning Work Well for Categorical Datasets with Mainly Nominal Attributes?
Electronics 2020, 9(11), 1966; https://doi.org/10.3390/electronics9111966 - 21 Nov 2020
Cited by 1 | Viewed by 1075
Abstract
Given the complexity of real-world datasets, it is difficult to present data structures using existing deep learning (DL) models. Most research to date has concentrated on datasets with only one type of attribute: categorical or numerical. Categorical data are common in datasets such [...] Read more.
Given the complexity of real-world datasets, it is difficult to present data structures using existing deep learning (DL) models. Most research to date has concentrated on datasets with only one type of attribute: categorical or numerical. Categorical data are common in datasets such as the German (-categorical) credit scoring dataset, which contains numerical, ordinal, and nominal attributes. The heterogeneous structure of this dataset makes very high accuracy difficult to achieve. DL-based methods have achieved high accuracy (99.68%) for the Wisconsin Breast Cancer Dataset, whereas DL-inspired methods have achieved high accuracy (97.39%) for the Australian credit dataset. However, to our knowledge, no such method has been proposed to classify the German credit dataset. This study aimed to provide new insights into the reasons why DL-based and DL-inspired classifiers do not work well for categorical datasets, mainly consisting of nominal attributes. We also discuss the problems associated with using nominal attributes to design high-performance classifiers. Considering the expanded utility of DL, this study's findings should aid in the development of a new type of DL that can handle categorical datasets consisting of mainly nominal attributes, which are commonly used in risk evaluation, finance, banking, and marketing. Full article
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Article
A Hybrid DC–DC Quadrupler Boost Converter for Photovoltaic Panels Integration into a DC Distribution System
Electronics 2020, 9(11), 1965; https://doi.org/10.3390/electronics9111965 - 20 Nov 2020
Cited by 1 | Viewed by 1095
Abstract
This paper presents a non-isolated DC–DC boost topology with a high-voltage-gain ratio for renewable energy applications. The presented converter is suitable for converting the voltage from low-voltage sources, such as photovoltaic panels, to higher voltage levels. The proposed converter consists of a multiphase [...] Read more.
This paper presents a non-isolated DC–DC boost topology with a high-voltage-gain ratio for renewable energy applications. The presented converter is suitable for converting the voltage from low-voltage sources, such as photovoltaic panels, to higher voltage levels. The proposed converter consists of a multiphase boost stage with an interleaving switching technique and a voltage multiplier cell to provide a voltage level at a reduced duty cycle. The interleaved boost stage consists of two legs and can be either fed from single or multiple voltage sources with the ability to control each source separately. The voltage multiplier cell can increase the voltage level by charging and discharging the capacitors. Several advantages are associated with the converter, such as reduced voltage stress on semiconductor elements and a scalable structure, where the number of voltage multiplier cells can be increased. The inductors in the interleaved boost stage share the input current equally, which reduces the conduction loss in the inductors. The input and the output of the converter share the same ground, and all active switches are low-side, which means no feedback or signal isolation is required. The theory of operation and steady-state analysis of the converter operating in the continuous conduction mode is presented. Components selections and efficiency analysis are presented and validated by comparative analysis and simulation results. A 0.195 kW experimental prototype was designed and implemented to convert the voltage from 20 V input source to 400 V output load, at 50 kHz. The test results show a high-performance of the converter as the maximum efficiency point is above 97%. Full article
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Article
Design and Optimization of Coupling Coils for Bidirectional Wireless Charging System of Unmanned Aerial Vehicle
Electronics 2020, 9(11), 1964; https://doi.org/10.3390/electronics9111964 - 20 Nov 2020
Cited by 3 | Viewed by 859
Abstract
To solve the battery power supply problem with wireless sensor networks (WSNs), a novel bidirectional wireless charging system is proposed, in which an unmanned aerial vehicle (UAV) can fly to the WSNs to charge sensors through high-frequency wireless power transfer (WPT) and also [...] Read more.
To solve the battery power supply problem with wireless sensor networks (WSNs), a novel bidirectional wireless charging system is proposed, in which an unmanned aerial vehicle (UAV) can fly to the WSNs to charge sensors through high-frequency wireless power transfer (WPT) and also obtain energy for its own battery in the same way. To improve the performance of the UAV bidirectional wireless charging system, a lightweight design is adopted to increase its loading capacity and working time. Moreover, the radii and the numbers of turns and pitches of coupling coils were designed and optimized on the basis of simulations and experiments. Experimental results show that the weight of optimized UAV coil was reduced by 34.45%. The power transfer efficiency (PTE) of the UAV coil to sensor coil increased from 60.2% to 74.4% at a transmission distance of 15 cm, while that of the ground transmitting coil to UAV coil increased from 65.2% to 90.1% at 10 cm. Full article
(This article belongs to the Special Issue Wireless Power Transfer and Its Applications)
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Article
Integrating Enhanced Sparse Autoencoder-Based Artificial Neural Network Technique and Softmax Regression for Medical Diagnosis
Electronics 2020, 9(11), 1963; https://doi.org/10.3390/electronics9111963 - 20 Nov 2020
Cited by 12 | Viewed by 1019
Abstract
In recent times, several machine learning models have been built to aid in the prediction of diverse diseases and to minimize diagnostic errors made by clinicians. However, since most medical datasets seem to be imbalanced, conventional machine learning algorithms tend to underperform when [...] Read more.
In recent times, several machine learning models have been built to aid in the prediction of diverse diseases and to minimize diagnostic errors made by clinicians. However, since most medical datasets seem to be imbalanced, conventional machine learning algorithms tend to underperform when trained with such data, especially in the prediction of the minority class. To address this challenge and proffer a robust model for the prediction of diseases, this paper introduces an approach that comprises of feature learning and classification stages that integrate an enhanced sparse autoencoder (SAE) and Softmax regression, respectively. In the SAE network, sparsity is achieved by penalizing the weights of the network, unlike conventional SAEs that penalize the activations within the hidden layers. For the classification task, the Softmax classifier is further optimized to achieve excellent performance. Hence, the proposed approach has the advantage of effective feature learning and robust classification performance. When employed for the prediction of three diseases, the proposed method obtained test accuracies of 98%, 97%, and 91% for chronic kidney disease, cervical cancer, and heart disease, respectively, which shows superior performance compared to other machine learning algorithms. The proposed approach also achieves comparable performance with other methods available in the recent literature. Full article
(This article belongs to the Special Issue Computational Intelligence in Healthcare)
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Article
Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading
Electronics 2020, 9(11), 1962; https://doi.org/10.3390/electronics9111962 - 20 Nov 2020
Cited by 35 | Viewed by 1404
Abstract
The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV [...] Read more.
The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique. Full article
(This article belongs to the Section Systems & Control Engineering)
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Article
Cache-Enabled Data Rate Maximization for Solar-Powered UAV Communication Systems
Electronics 2020, 9(11), 1961; https://doi.org/10.3390/electronics9111961 - 20 Nov 2020
Viewed by 773
Abstract
Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited [...] Read more.
Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited to cache data from the LS and then serve GUs’ requests to handle the issue of unavailable or damaged links from the LS to the GUs. The UAV can harvest solar energy for its operation. We investigate joint cache scheduling and power allocation schemes by using the non-orthogonal multiple access (NOMA) technique to maximize the long-term downlink rate. Two scenarios for the network are taken into account. In the first, the harvested energy distribution of the GUs is assumed to be known, and we propose a partially observable Markov decision process framework such that the UAV can allocate optimal transmission power for each GU based on proper content caching over each flight period. In the second scenario where the UAV does not know the environment’s dynamics in advance, an actor-critic-based scheme is proposed to achieve a solution by learning with a dynamic environment. Afterwards, the simulation results verify the effectiveness of the proposed methods, compared to baseline approaches. Full article
(This article belongs to the Special Issue Wireless Network Protocols and Performance Evaluation)
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Article
Cognitive Association in Interactive Evolutionary Design Process for Product Styling and Application to SUV Design
Electronics 2020, 9(11), 1960; https://doi.org/10.3390/electronics9111960 - 20 Nov 2020
Cited by 4 | Viewed by 766
Abstract
In recent years, intelligent design technology that is based on interactive evolutionary algorithms, namely interactive evolutionary design (IED) systems, has received extensive attention in the computer science, design, and other related literature. However, due to the complexity of design problems and the limitation [...] Read more.
In recent years, intelligent design technology that is based on interactive evolutionary algorithms, namely interactive evolutionary design (IED) systems, has received extensive attention in the computer science, design, and other related literature. However, due to the complexity of design problems and the limitation of human cognitive ability, IED faces several challenges in actual design applications. With the aim to address these problems in the IED, this paper deconstructs the IED of the product styling from the perspective of the cognitive association of the users, and proposes a corresponding cognitive intervention method that is based on the association of information. We built databases of the perceptual evaluation results of typical cases and coded profiles of the typical cases, combined with the corresponding interaction process, to improve the efficiency of creating associations between dissimilar information in the early stages of evolution. Besides, in order to simplify the process of creating associations between similar information, this paper proposes a clustering model of similar information based on explicit and implicit distances. The proposed method is then applied to the evolutionary design of an SUV. The experimental results show that the proposed method reduces the initial and total evaluation time. Therefore, the proposed method improves users’ ability to understand the complex design tasks of IED for product styling, optimizing the interactive evaluation process by guiding designers to efficiently create the cognitive association of information, and increases the effectiveness of adopting IED to solve actual design problems about product styling. Full article
(This article belongs to the Special Issue Smart Processing for Systems under Uncertainty or Perturbation)
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Article
Adaptive Protection for Microgrid with Distributed Energy Resources
Electronics 2020, 9(11), 1959; https://doi.org/10.3390/electronics9111959 - 20 Nov 2020
Cited by 11 | Viewed by 1125
Abstract
The microgrid includes a distribution system with low voltage, controllable load, and distributed energy resources (DER). The DERs have been increased in the recent power network to address global environmental concerns, which creates challenges in faults, synchronization, inertia control, etc. As the technologies [...] Read more.
The microgrid includes a distribution system with low voltage, controllable load, and distributed energy resources (DER). The DERs have been increased in the recent power network to address global environmental concerns, which creates challenges in faults, synchronization, inertia control, etc. As the technologies are getting advanced day by day, the past technology becomes obsolete. The internet of things (IoT) and artificial intelligence (AI) are the most discussed topics to obtain solutions for the challenges. One of the proposed solutions is adaptive overcurrent protection, as it can be used for any grid. In this paper, an algorithm is developed for the adaptive overcurrent relay protection to overcome the challenges of the microgrid with distributed energy resources. Then, the solutions obtained from the adaptive overcurrent protection algorithm network simulation are compared to the traditional overcurrent protection algorithm using the four key points such as selectivity, reliability, sensitivity, and speed to have a good performance in the power network. All the simulation studies are done in the electrical transient analyzer program (ETAP) software environment. Simulation results validate the performance of the proposed algorithm for adaptive protection using the IEEE-9 bus system with a microgrid. Full article
(This article belongs to the Section Power Electronics)
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Article
A Low-Power Memory-in-Pixel Circuit for Liquid Crystal Displays Comprising Low-Temperature Poly-Silicon and Oxide Thin-Film Transistors
Electronics 2020, 9(11), 1958; https://doi.org/10.3390/electronics9111958 - 19 Nov 2020
Cited by 3 | Viewed by 1165
Abstract
In this paper, a new pixel structure using low-temperature polycrystalline silicon and oxide (LTPO) thin-film transistors (TFTs) for low-power liquid crystal displays (LCDs) is proposed. The extremely low off-state current of oxide semiconductor TFTs enables the proposed circuit to operate at a very [...] Read more.
In this paper, a new pixel structure using low-temperature polycrystalline silicon and oxide (LTPO) thin-film transistors (TFTs) for low-power liquid crystal displays (LCDs) is proposed. The extremely low off-state current of oxide semiconductor TFTs enables the proposed circuit to operate at a very low frame frequency of 1/60 Hz, so that the power consumption can be significantly reduced. In addition, the low-temperature polycrystalline silicon TFTs with high reliability directly drive pixels, which can achieve stable and flicker-free LCDs. The proposed circuit is fabricated using the LTPO TFT backplane and successfully verified by simulation and measurement results. The measurement results prove that the proposed circuit operates well without further programming for 60 s, and the power consumption in the panel (except backlight power) can be reduced to 0.02% of that of conventional LCD. Full article
(This article belongs to the Section Semiconductor Devices)
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Article
Unsupervised Adversarial Defense through Tandem Deep Image Priors
Electronics 2020, 9(11), 1957; https://doi.org/10.3390/electronics9111957 - 19 Nov 2020
Cited by 3 | Viewed by 820
Abstract
Deep neural networks are vulnerable to the adversarial example synthesized by adding imperceptible perturbations to the original image but can fool the classifier to provide wrong prediction outputs. This paper proposes an image restoration approach which provides a strong defense mechanism to provide [...] Read more.
Deep neural networks are vulnerable to the adversarial example synthesized by adding imperceptible perturbations to the original image but can fool the classifier to provide wrong prediction outputs. This paper proposes an image restoration approach which provides a strong defense mechanism to provide robustness against adversarial attacks. We show that the unsupervised image restoration framework, deep image prior, can effectively eliminate the influence of adversarial perturbations. The proposed method uses multiple deep image prior networks called tandem deep image priors to recover the original image from adversarial example. Tandem deep image priors contain two deep image prior networks. The first network captures the main information of images and the second network recovers original image based on the prior information provided by the first network. The proposed method reduces the number of iterations originally required by deep image prior network and does not require adjusting the classifier or pre-training. It can be combined with other defensive methods. Our experiments show that the proposed method surprisingly achieves higher classification accuracy on ImageNet against a wide variety of adversarial attacks than previous state-of-the-art defense methods. Full article
(This article belongs to the Section Artificial Intelligence)
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Article
A New Card-Linked Loyalty Program: Estimated and Anticipated Benefits for Payment Transaction Parties
Electronics 2020, 9(11), 1956; https://doi.org/10.3390/electronics9111956 - 19 Nov 2020
Viewed by 1167
Abstract
Electronic card payments are getting more and more popular, mainly because of their simplicity, convenience, processing time and high level of security. The fact that a single payment card is issued for a particular cardholder makes it possible to link a card to [...] Read more.
Electronic card payments are getting more and more popular, mainly because of their simplicity, convenience, processing time and high level of security. The fact that a single payment card is issued for a particular cardholder makes it possible to link a card to various services. In this paper, we investigated a usage of a payment card in the loyalty program that incorporates our Contextual Risk Management System (CRMS) to assure a novel intangible reward: Shorter transaction processing time. In the beginning, we emphasize the importance of soft benefits in modern loyalty programs and recall the risk management algorithms and the reputation system that has been used in the CRMS. Then, using an extensive dataset of 2.5 million payment transaction traces (collected within a year from 68 terminals) we estimate potential benefits for merchants and cardholders and try to predict an effect of this system for the future. We also discuss the impact of this system on the real and user-perceived security level. Full article
(This article belongs to the Special Issue Cybersecurity and Mobility in 5G and Beyond)
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Article
Connecting Discourse and Domain Models in Discourse Analysis through Ontological Proxies
Electronics 2020, 9(11), 1955; https://doi.org/10.3390/electronics9111955 - 19 Nov 2020
Viewed by 961
Abstract
Argumentation-oriented discourse analysis usually focuses on what is being said and how, following the text under analysis quite literally, and paying little attention to the things in the world to which the text refers. However, to perform argumentation-oriented discourse analysis, one must assume [...] Read more.
Argumentation-oriented discourse analysis usually focuses on what is being said and how, following the text under analysis quite literally, and paying little attention to the things in the world to which the text refers. However, to perform argumentation-oriented discourse analysis, one must assume certain conceptualisations by the speaker in order to interpret and reconstruct propositions and argumentation structures. These conceptualisations are rarely captured as a product of the analysis process. In this paper, we argue that considering the ontology to which a discourse refers as well as the text itself provides a richer and more useful representation of the discourse and its argumentation structures, facilitates intertextual analysis, and improves understandability of the analysis products. To this end, we propose the notion of ontological proxies, i.e., conceptual artefacts that connect elements in the argumentation structure to the associated ontology elements. Full article
(This article belongs to the Special Issue Hybrid Methods for Natural Language Processing)
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