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Electronics, Volume 10, Issue 18 (September-2 2021) – 137 articles

Cover Story (view full-size image): This paper combines the advantages of terahertz wave nondestructive testing, at a frequency of 0.2 Thz, with neural network machine learning and iterative threshold filtering algorithm to realize an imaging system that can accurately recognize and clearly image the inner structure of the ceramic cultural relics. Due to its low destruction, high efficiency, and high reliability, the proposed system can provide an effective scheme for nondestructive testing of ceramic cultural relics. View this paper
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20 pages, 7276 KiB  
Article
SORT-YM: An Algorithm of Multi-Object Tracking with YOLOv4-Tiny and Motion Prediction
by Han Wu, Chenjie Du, Zhongping Ji, Mingyu Gao and Zhiwei He
Electronics 2021, 10(18), 2319; https://doi.org/10.3390/electronics10182319 - 21 Sep 2021
Cited by 19 | Viewed by 4784
Abstract
Multi-object tracking (MOT) is a significant and widespread research field in image processing and computer vision. The goal of the MOT task consists in predicting the complete tracklets of multiple objects in a video sequence. There are usually many challenges that degrade the [...] Read more.
Multi-object tracking (MOT) is a significant and widespread research field in image processing and computer vision. The goal of the MOT task consists in predicting the complete tracklets of multiple objects in a video sequence. There are usually many challenges that degrade the performance of the algorithm in the tracking process, such as occlusion and similar objects. However, the existing MOT algorithms based on the tracking-by-detection paradigm struggle to accurately predict the location of the objects that they fail to track in complex scenes, leading to tracking performance decay, such as an increase in the number of ID switches and tracking drifts. To tackle those difficulties, in this study, we design a motion prediction strategy for predicting the location of occluded objects. Since the occluded objects may be legible in earlier frames, we utilize the speed and location of the objects in the past frames to predict the possible location of the occluded objects. In addition, to improve the tracking speed and further enhance the tracking robustness, we utilize efficient YOLOv4-tiny to produce the detections in the proposed algorithm. By using YOLOv4-tiny, the tracking speed of our proposed method improved significantly. The experimental results on two widely used public datasets show that our proposed approach has obvious advantages in tracking accuracy and speed compared with other comparison algorithms. Compared to the Deep SORT baseline, our proposed method has a significant improvement in tracking performance. Full article
(This article belongs to the Section Computer Science & Engineering)
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17 pages, 3288 KiB  
Article
S Band Hybrid Power Amplifier in GaN Technology with Input/Output Multi Harmonic Tuned Terminations
by Sandro Ghisotti, Stefano Pisa and Paolo Colantonio
Electronics 2021, 10(18), 2318; https://doi.org/10.3390/electronics10182318 - 21 Sep 2021
Cited by 9 | Viewed by 3628
Abstract
In this paper, the design, fabrication, and measurements of an S band multi harmonic tuned power amplifier in GaN technology is described. The amplifier has been designed by exploiting second and third harmonic tuning conditions at both input and output ports of the [...] Read more.
In this paper, the design, fabrication, and measurements of an S band multi harmonic tuned power amplifier in GaN technology is described. The amplifier has been designed by exploiting second and third harmonic tuning conditions at both input and output ports of the active device. The amplifier has been realized in a hybrid form, and characterized in terms of small and large signal performance. An operating bandwidth of 300 MHz around 3.55 GHz, with 42.3 dBm output power, 9.3 dB power gain and 53.5% power added efficiency PAE (60% drain efficiency) at 3.7 GHz are measured. Full article
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24 pages, 7507 KiB  
Article
Performance Assessment of W-Band Radiometers: Direct versus Heterodyne Detections
by Juan Pablo Pascual, Beatriz Aja, Enrique Villa, Jose Vicente Terán, Luisa de la Fuente and Eduardo Artal
Electronics 2021, 10(18), 2317; https://doi.org/10.3390/electronics10182317 - 21 Sep 2021
Cited by 1 | Viewed by 2006
Abstract
W-Band radiometers using intermediate frequency down-conversion (super-heterodyne) and direct detection are compared. Both receivers consist of two W-band low noise amplifiers and an 80-to-101 GHz filter, which conforms to the reception frequency band, in the front-end module. The back-end module of the first [...] Read more.
W-Band radiometers using intermediate frequency down-conversion (super-heterodyne) and direct detection are compared. Both receivers consist of two W-band low noise amplifiers and an 80-to-101 GHz filter, which conforms to the reception frequency band, in the front-end module. The back-end module of the first receiver comprises a subharmonic mixer, intermediate frequency (IF) amplification and a square-law detector. For direct detection, a W-Band detector replaces the mixer and the intermediate frequency detection stages. The performance of the whole receivers has been simulated requiring special techniques, based on data from the experimental characterization of each subsystem. In the super-heterodyne implementation a local oscillator at 27.1 GHz (with 8 dBm) with a x3 frequency multiplier is used, exhibiting an overall conversion gain around 48 dB, a noise figure around 4 dB, and an effective bandwidth over 10 GHz. In the direct detection scheme, slightly better noise performance is obtained, with a wider bandwidth, around 20 GHz, since there is no IF bandwidth limitation (~15 GHz), and even using the same 80-to-101 GHz filter, the detector can operate through the whole W-band. Moreover, W-band detector has higher sensitivity than the IF detector, increasing slightly the gain. In both cases, the receiver performance is characterized when a broadband noise input signal is applied. The radiometer characteristics have been obtained working as a total power radiometer and as a Dicke radiometer when an optical chopper is used to modulate the incoming signal. Combining this particular super-heterodyne or direct detection topologies and total power or Dicke modes of operation, four different cases are compared and discussed, achieving similar sensitivities, but better performances in terms of equivalent bandwidth and noise for the direct detection radiometer. It should be noted that this conclusion comes from a particular set of components, which we could consider as typical, but we cannot exclude other conclusions for different components, particularly for different mixers and detectors. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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18 pages, 447 KiB  
Article
An Adaptive Hierarchical Sliding Mode Controller for Autonomous Underwater Vehicles
by Quang Van Vu, Tuan Anh Dinh, Thien Van Nguyen, Hoang Viet Tran, Hai Xuan Le, Hung Van Pham, Thai Dinh Kim and Linh Nguyen
Electronics 2021, 10(18), 2316; https://doi.org/10.3390/electronics10182316 - 21 Sep 2021
Cited by 10 | Viewed by 2393
Abstract
The paper addresses a problem of efficiently controlling an autonomous underwater vehicle (AUV), where its typical underactuated model is considered. Due to critical uncertainties and nonlinearities in the system caused by unavoidable external disturbances such as ocean currents when it operates, it is [...] Read more.
The paper addresses a problem of efficiently controlling an autonomous underwater vehicle (AUV), where its typical underactuated model is considered. Due to critical uncertainties and nonlinearities in the system caused by unavoidable external disturbances such as ocean currents when it operates, it is paramount to robustly maintain motions of the vehicle over time as expected. Therefore, it is proposed to employ the hierarchical sliding mode control technique to design the closed-loop control scheme for the device. However, exactly determining parameters of the AUV control system is impractical since its nonlinearities and external disturbances can vary those parameters over time. Thus, it is proposed to exploit neural networks to develop an adaptive learning mechanism that allows the system to learn its parameters adaptively. More importantly, stability of the AUV system controlled by the proposed approach is theoretically proved to be guaranteed by the use of the Lyapunov theory. Effectiveness of the proposed control scheme was verified by the experiments implemented in a synthetic environment, where the obtained results are highly promising. Full article
(This article belongs to the Section Systems & Control Engineering)
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16 pages, 5648 KiB  
Article
A Compact Widely Tunable Bandpass Filter Dedicated to Preselectors
by Mirosław Magnuski, Dariusz Wójcik, Maciej Surma and Artur Noga
Electronics 2021, 10(18), 2315; https://doi.org/10.3390/electronics10182315 - 21 Sep 2021
Cited by 2 | Viewed by 3109
Abstract
This article presents a novel compact widely tunable bandpass filter. The filter consists of two resonators that are double-coupled, inductively, where the coupling inductances are elements of the input and output networks. The application of double-coupling enabled the transmission zero next to the [...] Read more.
This article presents a novel compact widely tunable bandpass filter. The filter consists of two resonators that are double-coupled, inductively, where the coupling inductances are elements of the input and output networks. The application of double-coupling enabled the transmission zero next to the upper cutoff frequency. This makes the filter useful for applications in preselector networks used in receiving systems with a low to intermediate frequency with the desired channel frequency lower than the image channel frequency. The article shows the practical realisation of the varactor-tuned example filter fabricated as a microstrip planar network of an overall size of 0.03λg × 0.045λg. The tuning range of the proposed filter is from 410 MHz to 880 MHz with the fractional bandwidth equal to 7.5–8.1% and an in-band insertion loss better than −3.4 dB. The achieved IP3 value exceeds 17.5 dBm. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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17 pages, 637 KiB  
Review
A Systematic Review of the Use of Art in Virtual Reality
by Audrey Aldridge and Cindy L. Bethel
Electronics 2021, 10(18), 2314; https://doi.org/10.3390/electronics10182314 - 20 Sep 2021
Cited by 9 | Viewed by 3692
Abstract
Brain injuries can create life-altering challenges and have the potential to leave people with permanent disabilities. Art therapy is a popular method used for treating many of the disabilities that can accompany a brain injury. In a systematic review, an assessment of how [...] Read more.
Brain injuries can create life-altering challenges and have the potential to leave people with permanent disabilities. Art therapy is a popular method used for treating many of the disabilities that can accompany a brain injury. In a systematic review, an assessment of how art is being used in virtual reality (VR) was conducted, and the feasibility of brain injury patients to participate in virtual art therapy was investigated. Studies included in this review highlight the importance of artistic subject matter, sensory stimulation, and measurable performance outcomes for assessing the effect art therapy has on motor impairment in VR. Although there are limitations to using art therapy in a virtual environment, studies show that it can feasibly be used in virtual reality for neurorehabilitation purposes. Full article
(This article belongs to the Special Issue Human Computer Interaction for Intelligent Systems)
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12 pages, 14737 KiB  
Article
Stray Flux Multi-Sensor for Stator Fault Detection in Synchronous Machines
by Miftah Irhoumah, Remus Pusca, Eric Lefèvre, David Mercier and Raphael Romary
Electronics 2021, 10(18), 2313; https://doi.org/10.3390/electronics10182313 - 20 Sep 2021
Cited by 7 | Viewed by 2143
Abstract
The aim of this paper is to detect a stator inter-turn short circuit in a synchronous machine through the analysis of the external magnetic field measured by external flux sensors. The paper exploits a methodology previously developed, based on the analysis of the [...] Read more.
The aim of this paper is to detect a stator inter-turn short circuit in a synchronous machine through the analysis of the external magnetic field measured by external flux sensors. The paper exploits a methodology previously developed, based on the analysis of the behavior with load variation of sensitive spectral lines issued from two flux sensors positioned at 180° from each other around the machine. Further developments to improve this method were made, in which more than two flux sensors were used to keep a good sensitivity for stator fault detection. The method is based on the Pearson correlation coefficient calculated from sensitive spectral lines at different load operating conditions. Fusion information with belief function is then applied to the correlation coefficients, which enable the detection of an incipient fault in any phase of the machine. The method has the advantage to be fully non-invasive and does not require knowledge of the healthy state. Full article
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16 pages, 1841 KiB  
Article
Novel Protection Coordination Scheme for Active Distribution Networks
by Muhammad Fawad Shaikh, Sunny Katyara, Zahid Hussain Khand, Madad Ali Shah, Lukasz Staszewski, Veer Bhan, Abdul Majeed, Shoaib Shaikh and Leonowicz Zbigniew
Electronics 2021, 10(18), 2312; https://doi.org/10.3390/electronics10182312 - 20 Sep 2021
Cited by 4 | Viewed by 2279
Abstract
Distribution networks are inherently radial and passive owing to the ease of operation and unidirectional power flow. Proper installation of Distributed Generators, on the one hand, makes the utility network active and mitigates certain power quality issues e.g., voltage dips, frequency deviations, losses, [...] Read more.
Distribution networks are inherently radial and passive owing to the ease of operation and unidirectional power flow. Proper installation of Distributed Generators, on the one hand, makes the utility network active and mitigates certain power quality issues e.g., voltage dips, frequency deviations, losses, etc., but on the other hand, it disturbs the optimal coordination among existing protection devices e.g., over-current relays. In order to maintain the desired selectivity level, such that the primary and backup relays are synchronized against different contingencies, it necessitates design of intelligent and promising protection schemes to distinguish between the upstream and downstream power flows. This research proposes exploiting phase angle jump, an overlooked voltage sag parameter, to add directional element to digital over-current relays with inverse time characteristics. The decision on the direction of current is made on the basis of polarity of phase angle jump together with the impedance angle of the system. The proposed scheme at first is evaluated on a test system in a simulated environment under symmetrical and unsymmetrical faults and, secondly, as a proof of the concept, it is verified in real-time on a laboratory setup using a Power Hardware-in-loop (PHIL) system. Moreover, a comparative analysis is made with other state-of-the-art techniques to evaluate the performance and robustness of the proposed approach. Full article
(This article belongs to the Special Issue Environment and Electrical Engineering-Edition 2021)
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14 pages, 37603 KiB  
Article
A High Bandwidth-Power Efficiency, Low THD2,3 Driver Amplifier with Dual-Loop Active Frequency Compensation for High-Speed Applications
by Ximing Fu, Kamal El-Sankary and Yadong Yin
Electronics 2021, 10(18), 2311; https://doi.org/10.3390/electronics10182311 - 20 Sep 2021
Viewed by 1913
Abstract
This paper presents a driver amplifier with high bandwidth-power efficiency, high capacitor-driving capacity, and low total harmonic distortion (THD). One complementary differential pair composed of self-cascode transistors is incorporated to obtain a full input voltage swing. Flipped voltage follower (FVF) buffers are applied [...] Read more.
This paper presents a driver amplifier with high bandwidth-power efficiency, high capacitor-driving capacity, and low total harmonic distortion (THD). One complementary differential pair composed of self-cascode transistors is incorporated to obtain a full input voltage swing. Flipped voltage follower (FVF) buffers are applied as second stage to drive the last class-AB output stage. Moreover, a dual-loop active-feedback frequency compensation (DLAFC) is presented, which can stabilize the proposed multistage amplifier and keep the dominant pole on high frequency to obtain high-frequency total harmonic distortion (THD) suppression. To achieve a low-frequency phase margin protection (PMP), one left half-plane (LHP) zero is introduced to compensate for the nondominant pole caused by the load capacitor. Meanwhile, two high-frequency LHP zeros are injected to achieve high-frequency phase margin boosting (PMB) and reduce the amplifier’s settling time and integration area. This proposed amplifier is implemented in a standard DBH 0.18 μm 5 V CMOS process, and it achieves over 115-dB DC gain, 150–300 MHz GBW under 0–100 p load capacitors, ultra-high THD2,3 suppression ranges from 100 kHz to 10 MHz under 1–2 V output swing, and over 250 V/μs average slew rate, by only dissipating 12.5 mW at 5 V power supply. Full article
(This article belongs to the Section Circuit and Signal Processing)
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12 pages, 3313 KiB  
Article
Ext4 and XFS File System Forensic Framework Based on TSK
by Hyungchan Kim, Sungbum Kim, Yeonghun Shin, Wooyeon Jo, Seokjun Lee and Taeshik Shon
Electronics 2021, 10(18), 2310; https://doi.org/10.3390/electronics10182310 - 20 Sep 2021
Cited by 5 | Viewed by 4762
Abstract
Recently, the number of Internet of Things (IoT) devices, such as artificial intelligence (AI) speakers and smartwatches, using a Linux-based file system has increased. Moreover, these devices are connected to the Internet and generate vast amounts of data. To efficiently manage these generated [...] Read more.
Recently, the number of Internet of Things (IoT) devices, such as artificial intelligence (AI) speakers and smartwatches, using a Linux-based file system has increased. Moreover, these devices are connected to the Internet and generate vast amounts of data. To efficiently manage these generated data and improve the processing speed, the function is improved by updating the file system version or using new file systems, such as an Extended File System (XFS), B-tree file system (Btrfs), or Flash-Friendly File System (F2FS). However, in the process of updating the existing file system, the metadata structure may be changed or the analysis of the newly released file system may be insufficient, making it impossible for existing commercial tools to extract and restore deleted files. In an actual forensic investigation, when deleted files become unrecoverable, important clues may be missed, making it difficult to identify the culprit. Accordingly, a framework for extracting and recovering files based on The Sleuth Kit (TSK) is proposed by deriving the metadata changed in Ext4 file system journal checksum v3 and XFS file system v5. Thereafter, by comparing the accuracy and recovery rate of the proposed framework with existing commercial tools using the experimental dataset, we conclude that sustained research on file systems should be conducted from the perspective of forensics. Full article
(This article belongs to the Special Issue Applied AI-Based Platform Technology and Application)
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13 pages, 2492 KiB  
Article
High-Speed Column Driver IC Having Buffer Amplifier with Embedded Isolation Switch and Compact Adaptive Biasing for Flat-Panel Displays
by Hyoung-Rae Kim, Chang-Ho An and Bai-Sun Kong
Electronics 2021, 10(18), 2309; https://doi.org/10.3390/electronics10182309 - 20 Sep 2021
Cited by 2 | Viewed by 3625
Abstract
A high-speed column driver IC with an area-efficient high-slew-rate buffer amplifier is proposed for use in a large-sized, high-resolution TFT-LCD panel application. In the proposed architecture, explicit isolation switches have been embedded into the buffer amplifier resulting in a fast settling response. The [...] Read more.
A high-speed column driver IC with an area-efficient high-slew-rate buffer amplifier is proposed for use in a large-sized, high-resolution TFT-LCD panel application. In the proposed architecture, explicit isolation switches have been embedded into the buffer amplifier resulting in a fast settling response. The amplifier also has a structure that adjusts the tail current of the input stage using a very compact adaptive biasing. The proposed column driver IC, having the proposed buffer amplifier for driving a 55-inch 4K ultra-high-definition (UHD) TV panel, was fabricated in a 0.18-μm 1.8-V low-voltage, 1.2-μm 9-V medium-voltage, and 1.6-μm 18-V high-voltage CMOS process. The performance evaluation results indicated that 90% and 99.9% falling settling times were improved from 1.947 µs to 0.710 µs (63.5% improvement) and 4.131 µs to 2.406 µs (41.7% improvement), respectively. They also indicated that the layout size of the proposed buffer amplifier was reduced from 5580 μm2 to 4402 μm2 (21.1% reduction). Full article
(This article belongs to the Section Circuit and Signal Processing)
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19 pages, 4797 KiB  
Article
Parameter Estimation of Modified Double-Diode and Triple-Diode Photovoltaic Models Based on Wild Horse Optimizer
by Abdelhady Ramadan, Salah Kamel, Ibrahim B. M. Taha and Marcos Tostado-Véliz
Electronics 2021, 10(18), 2308; https://doi.org/10.3390/electronics10182308 - 19 Sep 2021
Cited by 28 | Viewed by 2978
Abstract
The increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems [...] Read more.
The increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems facing those in charge of manufacturing these systems, which makes it interesting to many researchers. The difficulty in estimating the efficiency of PV is due to the high non-linear current–voltage characteristics and power–voltage characteristics. In addition, the absence of ample efficiency information in the manufacturers’ datasheets has led to the development of an effective electrical mathematical equivalent model necessary to simulate the PV module. In this paper, an application for an optimization algorithm named Wild Horse Optimizer (WHO) is proposed to extract the parameters of a double-diode PV model (DDM), modified double-diode PV model (MDDM), triple-diode PV model (TDM), and modified triple-diode PV model (MTDM). This study focuses on two main objectives. The first concerns comparing the original models (DDM and TDM) and their modification (MDDM and MTDM). The second concerns the algorithm behavior with the optimization problem and comparing this behavior with other recent algorithms. The evaluation process uses different methods, such as Root Mean Square Error (RMSE) for accuracy and statistical analysis for robustness. Based on the results obtained by the WHO, the estimated parameters using the WHO are more accurate than those obtained by the other studied optimization algorithms; furthermore, the MDDM and MTDM modifications enhanced the original DDM and TDM efficiencies. Full article
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24 pages, 21140 KiB  
Article
Modeling of Occupancy-Based Energy Consumption in a Campus Building Using Embedded Devices and IoT Technology
by Aryuanto Soetedjo and Sotyohadi Sotyohadi
Electronics 2021, 10(18), 2307; https://doi.org/10.3390/electronics10182307 - 19 Sep 2021
Cited by 3 | Viewed by 2046
Abstract
Since occupancy affects energy consumption, it is common to model and simulate occupancy using simulation software. One drawback of simulation software is that it cannot provide data transmission information from the sensors, which is essential for real-time energy monitoring systems. This paper proposes [...] Read more.
Since occupancy affects energy consumption, it is common to model and simulate occupancy using simulation software. One drawback of simulation software is that it cannot provide data transmission information from the sensors, which is essential for real-time energy monitoring systems. This paper proposes an approach to integrating an occupancy model and a real-time monitoring system for real-time modeling. The integration was performed by implementing a model on embedded devices and employing an IoT-based real-time monitoring application. The experimental results showed that the proposed approach effectively configured and monitored the model using a smartphone. Moreover, the data generated by the model were stored in an IoT cloud server for monitoring and further analysis. The evaluation result showed that the model ran perfectly in real-time embedded devices. The assessment of the IoT data transmission performances yielded a maximum latency of 9.0348 s, jitter of 0.9829 s, inter-arrival time of 5.5085 s, and packet loss of 10.8%, which are adequate for real-time modeling of occupancy-based energy consumption. Full article
(This article belongs to the Section Networks)
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17 pages, 1393 KiB  
Article
Read Reference Calibration and Tracking for Non-Volatile Flash Memories
by Johann-Philipp Thiers, Daniel Nicolas Bailon, Jürgen Freudenberger and Jianjie Lu
Electronics 2021, 10(18), 2306; https://doi.org/10.3390/electronics10182306 - 19 Sep 2021
Cited by 4 | Viewed by 2338
Abstract
The performance and reliability of nonvolatile NAND flash memories deteriorate as the number of program/erase cycles grows. The reliability also suffers from cell-to-cell interference, long data retention time, and read disturb. These processes effect the read threshold voltages. The aging of the cells [...] Read more.
The performance and reliability of nonvolatile NAND flash memories deteriorate as the number of program/erase cycles grows. The reliability also suffers from cell-to-cell interference, long data retention time, and read disturb. These processes effect the read threshold voltages. The aging of the cells causes voltage shifts which lead to high bit error rates (BER) with fixed predefined read thresholds. This work proposes two methods that aim on minimizing the BER by adjusting the read thresholds. Both methods utilize the number of errors detected in the codeword of an error correction code. It is demonstrated that the observed number of errors is a good measure for the voltage shifts and is utilized for the initial calibration of the read thresholds. The second approach is a gradual channel estimation method that utilizes the asymmetrical error probabilities for the one-to-zero and zero-to-one errors that are caused by threshold calibration errors. Both methods are investigated utilizing the mutual information between the optimal read voltage and the measured error values. Numerical results obtained from flash measurements show that these methods reduce the BER of NAND flash memories significantly. Full article
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24 pages, 2001 KiB  
Review
Challenges in Application of Petri Nets in Manufacturing Systems
by Iwona Grobelna and Andrei Karatkevich
Electronics 2021, 10(18), 2305; https://doi.org/10.3390/electronics10182305 - 19 Sep 2021
Cited by 22 | Viewed by 5142
Abstract
Petri nets are a useful mathematical formalism for specification of manufacturing systems, supported by various analysis and verification methods. The progress made in automating control systems and the widespread use of Industry 4.0 pose a number of challenges to their application, starting from [...] Read more.
Petri nets are a useful mathematical formalism for specification of manufacturing systems, supported by various analysis and verification methods. The progress made in automating control systems and the widespread use of Industry 4.0 pose a number of challenges to their application, starting from the education at university level and ending with modelling of real case studies. The paper aims to present and analyse the most relevant challenges and opportunities related to the use of Petri nets as a modelling technique of manufacturing systems. The review of the literature is primarily based on the years 2019–2020 to reflect the current state of the art. The newest approaches to deadlock prevention and recovering, but also other important analysis problems and difficulties in modelling real industrial processes are discussed. Trends for the future are also identified. Full article
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10 pages, 1491 KiB  
Article
Bioinspired Auditory Model for Vowel Recognition
by Viviana Abad Peraza, José Manuel Ferrández Vicente and Ernesto Arturo Martínez Rams
Electronics 2021, 10(18), 2304; https://doi.org/10.3390/electronics10182304 - 18 Sep 2021
Cited by 1 | Viewed by 1407
Abstract
In this work, a bioinspired or neuromorphic model to replicate the vowel recognition process for an auditory system is presented. A bioinspired peripheral and central auditory system model is implemented and a neuromorphic higher auditory system model based on artificial neuronal nets for [...] Read more.
In this work, a bioinspired or neuromorphic model to replicate the vowel recognition process for an auditory system is presented. A bioinspired peripheral and central auditory system model is implemented and a neuromorphic higher auditory system model based on artificial neuronal nets for vowel recognition is proposed. For their verification, ten Hispanic Spanish language-speaking adults (five males and five females) were used. With the proposed bioinspired model based on artificial neuronal nets it is possible to recognize with high levels of accuracy and sensibility the vowels phonemes of speech signals and the assessment of cochlear implant stimulation strategies in terms of vowel recognition. Full article
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15 pages, 17605 KiB  
Article
Towards Realization of a Low-Voltage Class-AB VCII with High Current Drive Capability
by Leila Safari, Gianluca Barile, Vincenzo Stornelli, Shahram Minaei and Giuseppe Ferri
Electronics 2021, 10(18), 2303; https://doi.org/10.3390/electronics10182303 - 18 Sep 2021
Cited by 6 | Viewed by 2095
Abstract
In this paper, the implementation of a low-voltage class AB second generation voltage conveyor (VCII) with high current drive capability is presented. Simple realization and good overall performance are the main features of the proposed circuit. Proper solutions and techniques were used to [...] Read more.
In this paper, the implementation of a low-voltage class AB second generation voltage conveyor (VCII) with high current drive capability is presented. Simple realization and good overall performance are the main features of the proposed circuit. Proper solutions and techniques were used to achieve high signal swing and high linearity at Y, X and Z ports of VCII as well as low-voltage operation. The operation of the proposed VCII was verified through SPICE simulations based on TSMC 0.18 µm CMOS technology parameters and a supply voltage of ±0.9 V. The small signal impedance values were 973 Ω, 120 kΩ and 217 Ω at Y, X and Z ports, respectively. The maximum current at the X port was ±10 mA with maximum total harmonic distortion (THD) of 2.4% at a frequency of 1 MHz. Considering a bias current (IB) of 29 µA and output current at the X port (IX) of 10 mA, the current drive capability (IX/IB) of about 345 was achieved at the X port. The voltage swing at the Z port was (−0.4, 0.4) V. The THD value at the Z port for an input signal with 0.8 V peak-to-peak value and frequency of 1 MHz was 3.9%. The total power consumption was 0.393 µW. Full article
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15 pages, 2494 KiB  
Article
A Novel Flip-List-Enabled Belief Propagation Decoder for Polar Codes
by Qasim Jan, Shahid Hussain, Muhammad Furqan, Zhiwen Pan, Nan Liu and Xiaohu You
Electronics 2021, 10(18), 2302; https://doi.org/10.3390/electronics10182302 - 18 Sep 2021
Cited by 4 | Viewed by 2283
Abstract
Due to the design principle of parallel processing, belief propagation (BP) decoding is attractive, and it provides good error-correction performance compared with successive cancellation (SC) decoding. However, its error-correction performance is still inferior to that of successive cancellation list (SCL) decoding. Consequently, this [...] Read more.
Due to the design principle of parallel processing, belief propagation (BP) decoding is attractive, and it provides good error-correction performance compared with successive cancellation (SC) decoding. However, its error-correction performance is still inferior to that of successive cancellation list (SCL) decoding. Consequently, this paper proposes a novel flip-list- (FL)-enabled belief propagation (BP) method to improve the error-correction performance of BP decoding for polar codes with low computational complexity. The proposed technique identifies the vulnerable channel log-likelihood ratio (LLR) that deteriorates the BP decoding result. The FL is utilized to efficiently identify the erroneous channel LLRs and correct them for the next BP decoding attempt. The preprocessed channel LLR through FL improves the error-correction performance with minimal flipping attempts and reduces the computational complexity. The proposed technique was compared with the state-of-the-art BP, i.e., BP bit-flip (BP-BF), generalized BP-flip (GBPF), cyclic redundancy check (CRC)-aided (CA-SCL) decoding, and ordered statistic decoding (OSD), algorithms. Simulation results showed that the FL-BP had an excellent block error rate (BLER) performance gain up to 0.7 dB compared with BP, BP-BF, and GBPF decoder. Besides, the computational complexity was reduced considerably in the high signal-to-noise ratio (SNR) regime compared with the BP-BF and GBPF decoding methods. Full article
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24 pages, 4413 KiB  
Article
Space Imaging Sensor Power Supply Filtering: Improving EMC Margin Assessment with Clustering and Sensitivity Analyses
by Laurent Patier and Sébastien Lalléchère
Electronics 2021, 10(18), 2301; https://doi.org/10.3390/electronics10182301 - 18 Sep 2021
Cited by 1 | Viewed by 1768
Abstract
This work is dedicated to the assessment of the filtering performances of an optoelectronic sensor for space applications. Particular care is taken concerning the power supply subsystem (here voltage shifter integrated circuit), which is part of the electromagnetic compatibility (EMC) compliance of an [...] Read more.
This work is dedicated to the assessment of the filtering performances of an optoelectronic sensor for space applications. Particular care is taken concerning the power supply subsystem (here voltage shifter integrated circuit), which is part of the electromagnetic compatibility (EMC) compliance of an imaging equipment embedded on spacecrafts. The proposed methodology aims at two major targets: First, evaluating the Filter Effectiveness (FE) subject concerning varying parameters (including filter topology, parasitic effects and source/load impedance variations); second, quantifying the relative importance of representative equivalent electrical components through sensitivity analyses (nominal and parasitic values). The latter point is of utmost importance considering the expected versatility of such systems, such as manufacturing tolerances, for instance. Nominal values and/or components are often badly defined for confidentiality reasons, lack of knowledge or pure ignorance of inputs. An analytical deterministic formulation (here through the transfer matrix approach) is proposed and completed with an original stochastic strategy (Reduced Order Clustering, ROC). This ensures the reliable assessment of both statistical filter performances and most influential parameters, jointly with computational resources saving relatively to brute force Monte Carlo simulations. Full article
(This article belongs to the Special Issue Electromagnetic Interference and Compatibility, Volume II)
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23 pages, 758 KiB  
Article
Extensible Chatbot Architecture Using Metamodels of Natural Language Understanding
by Rade Matic, Milos Kabiljo, Miodrag Zivkovic and Milan Cabarkapa
Electronics 2021, 10(18), 2300; https://doi.org/10.3390/electronics10182300 - 18 Sep 2021
Cited by 13 | Viewed by 8817
Abstract
In recent years, gradual improvements in communication and connectivity technologies have enabled new technical possibilities for the adoption of chatbots across diverse sectors such as customer services, trade, and marketing. The chatbot is a platform that uses natural language processing, a subset of [...] Read more.
In recent years, gradual improvements in communication and connectivity technologies have enabled new technical possibilities for the adoption of chatbots across diverse sectors such as customer services, trade, and marketing. The chatbot is a platform that uses natural language processing, a subset of artificial intelligence, to find the right answer to all users’ questions and solve their problems. Advanced chatbot architecture that is extensible, scalable, and supports different services for natural language understanding (NLU) and communication channels for interactions of users has been proposed. The paper describes overall chatbot architecture and provides corresponding metamodels as well as rules for mapping between the proposed and two commonly used NLU metamodels. The proposed architecture could be easily extended with new NLU services and communication channels. Finally, two implementations of the proposed chatbot architecture are briefly demonstrated in the case study of “ADA” and “COVID-19 Info Serbia”. Full article
(This article belongs to the Special Issue Human Activity Recognition and Machine Learning)
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20 pages, 3454 KiB  
Article
Minimization of Torque Ripple in the Brushless DC Motor Using Constrained Cuckoo Search Algorithm
by Łukasz Knypiński, Sebastian Kuroczycki and Fausto Pedro García Márquez
Electronics 2021, 10(18), 2299; https://doi.org/10.3390/electronics10182299 - 18 Sep 2021
Cited by 17 | Viewed by 2417
Abstract
This paper presents the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC). The optimization algorithm was created based on the cuckoo’s reproductive behavior. The lumped-parameters mathematical model of [...] Read more.
This paper presents the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC). The optimization algorithm was created based on the cuckoo’s reproductive behavior. The lumped-parameters mathematical model of the BLDC motor was developed. The values of self-inductances, mutual inductances, and back-electromotive force waveforms applied in the mathematical model were calculated by the use of the finite element method. The optimization algorithm was developed in Python 3.8. The CS algorithm was coupled with the static penalty function. During the optimization process, the shape of the voltage supplying the stator windings was determined to minimize the commutation torque ripple. Selected results of computer simulation are presented and discussed. Full article
(This article belongs to the Special Issue Environment and Electrical Engineering-Edition 2021)
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17 pages, 6969 KiB  
Article
Applying a Genetic Algorithm to a m-TSP: Case Study of a Decision Support System for Optimizing a Beverage Logistics Vehicles Routing Problem
by David E. Gomes, Maria Inês D. Iglésias, Ana P. Proença, Tânia M. Lima and Pedro D. Gaspar
Electronics 2021, 10(18), 2298; https://doi.org/10.3390/electronics10182298 - 18 Sep 2021
Cited by 10 | Viewed by 3743
Abstract
Route optimization has become an increasing problem in the transportation and logistics sector within the development of smart cities. This article aims to demonstrate the implementation of a genetic algorithm adapted to a Vehicle Route Problem (VRP) in a company based in the [...] Read more.
Route optimization has become an increasing problem in the transportation and logistics sector within the development of smart cities. This article aims to demonstrate the implementation of a genetic algorithm adapted to a Vehicle Route Problem (VRP) in a company based in the city of Covilhã (Portugal). Basing the entire approach to this problem on the characteristic assumptions of the Multiple Traveling Salesman Problem (m-TSP) approach, an optimization of the daily routes for the workers assigned to distribution, divided into three zones: North, South and Central, was performed. A critical approach to the returned routes based on the adaptation to the geography of the Zones was performed. From a comparison with the data provided by the company, it is predicted by the application of a genetic algorithm to the m-TSP, that there will be a reduction of 618 km per week of the total distance traveled. This result has a huge impact in several forms: clients are visited in time, promoting provider-client relations; reduction of the fixed costs with fuel; promotion of environmental sustainability by the reduction of logistic routes. All these improvements and optimizations can be thought of as contributions to foster smart cities. Full article
(This article belongs to the Special Issue Emerging Trends, Issues and Challenges in Smart Cities)
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19 pages, 3811 KiB  
Article
Impact of Novel Image Preprocessing Techniques on Retinal Vessel Segmentation
by Toufique A. Soomro, Ahmed Ali, Nisar Ahmed Jandan, Ahmed J. Afifi, Muhammad Irfan, Samar Alqhtani, Adam Glowacz, Ali Alqahtani, Ryszard Tadeusiewicz, Eliasz Kantoch and Lihong Zheng
Electronics 2021, 10(18), 2297; https://doi.org/10.3390/electronics10182297 - 18 Sep 2021
Cited by 5 | Viewed by 3227
Abstract
Segmentation of retinal vessels plays a crucial role in detecting many eye diseases, and its reliable computerized implementation is becoming essential for automated retinal disease screening systems. A large number of retinal vessel segmentation algorithms are available, but these methods improve accuracy levels. [...] Read more.
Segmentation of retinal vessels plays a crucial role in detecting many eye diseases, and its reliable computerized implementation is becoming essential for automated retinal disease screening systems. A large number of retinal vessel segmentation algorithms are available, but these methods improve accuracy levels. Their sensitivity remains low due to the lack of proper segmentation of low contrast vessels, and this low contrast requires more attention in this segmentation process. In this paper, we have proposed new preprocessing steps for the precise extraction of retinal blood vessels. These proposed preprocessing steps are also tested on other existing algorithms to observe their impact. There are two steps to our suggested module for segmenting retinal blood vessels. The first step involves implementing and validating the preprocessing module. The second step applies these preprocessing stages to our proposed binarization steps to extract retinal blood vessels. The proposed preprocessing phase uses the traditional image-processing method to provide a much-improved segmented vessel image. Our binarization steps contained the image coherence technique for the retinal blood vessels. The proposed method gives good performance on a database accessible to the public named DRIVE and STARE. The novelty of this proposed method is that it is an unsupervised method and offers an accuracy of around 96% and sensitivity of 81% while outperforming existing approaches. Due to new tactics at each step of the proposed process, this blood vessel segmentation application is suitable for computer analysis of retinal images, such as automated screening for the early diagnosis of eye disease. Full article
(This article belongs to the Special Issue Novel Technologies on Image and Signal Processing)
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17 pages, 1646 KiB  
Article
Unsupervised Object Segmentation Based on Bi-Partitioning Image Model Integrated with Classification
by Hyun-Tae Choi and Byung-Woo Hong
Electronics 2021, 10(18), 2296; https://doi.org/10.3390/electronics10182296 - 18 Sep 2021
Cited by 1 | Viewed by 1677
Abstract
The development of convolutional neural networks for deep learning has significantly contributed to image classification and segmentation areas. For high performance in supervised image segmentation, we need many ground-truth data. However, high costs are required to make these data, so unsupervised manners are [...] Read more.
The development of convolutional neural networks for deep learning has significantly contributed to image classification and segmentation areas. For high performance in supervised image segmentation, we need many ground-truth data. However, high costs are required to make these data, so unsupervised manners are actively being studied. The Mumford–Shah and Chan–Vese models are well-known unsupervised image segmentation models. However, the Mumford–Shah model and the Chan–Vese model cannot separate the foreground and background of the image because they are based on pixel intensities. In this paper, we propose a weakly supervised model for image segmentation based on the segmentation models (Mumford–Shah model and Chan–Vese model) and classification. The segmentation model (i.e., Mumford–Shah model or Chan–Vese model) is to find a base image mask for classification, and the classification network uses the mask from the segmentation models. With the classifcation network, the output mask of the segmentation model changes in the direction of increasing the performance of the classification network. In addition, the mask can distinguish the foreground and background of images naturally. Our experiment shows that our segmentation model, integrated with a classifier, can segment the input image to the foreground and the background only with the image’s class label, which is the image-level label. Full article
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22 pages, 26012 KiB  
Article
OATCR: Outdoor Autonomous Trash-Collecting Robot Design Using YOLOv4-Tiny
by Medhasvi Kulshreshtha, Sushma S. Chandra, Princy Randhawa, Georgios Tsaramirsis, Adil Khadidos and Alaa O. Khadidos
Electronics 2021, 10(18), 2292; https://doi.org/10.3390/electronics10182292 - 18 Sep 2021
Cited by 23 | Viewed by 12205
Abstract
This paper proposed an innovative mechanical design using the Rocker-bogie mechanism for resilient Trash-Collecting Robots. Mask-RCNN, YOLOV4, and YOLOv4-tiny were experimented on and analyzed for trash detection. The Trash-Collecting Robot was developed to be completely autonomous as it was able to detect trash, [...] Read more.
This paper proposed an innovative mechanical design using the Rocker-bogie mechanism for resilient Trash-Collecting Robots. Mask-RCNN, YOLOV4, and YOLOv4-tiny were experimented on and analyzed for trash detection. The Trash-Collecting Robot was developed to be completely autonomous as it was able to detect trash, move towards it, and pick it up while avoiding any obstacles along the way. Sensors including a camera, ultrasonic sensor, and GPS module played an imperative role in automation. The brain of the Robot, namely, Raspberry Pi and Arduino, processed the data from the sensors and performed path-planning and consequent motion of the robot through actuation of motors. Three models for object detection were tested for potential use in the robot: Mask-RCNN, YOLOv4, and YOLOv4-tiny. Mask-RCNN achieved an average precision (mAP) of over 83% and detection time (DT) of 3973.29 ms, YOLOv4 achieved 97.1% (mAP) and 32.76 DT, and YOLOv4-tiny achieved 95.2% and 5.21 ms DT. The YOLOv4-tiny was selected as it offered a very similar mAP to YOLOv4, but with a much lower DT. The design was simulated on different terrains and behaved as expected. Full article
(This article belongs to the Section Systems & Control Engineering)
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17 pages, 4576 KiB  
Article
Optimization of Energy Consumption Based on Traffic Light Constraints and Dynamic Programming
by Jiaming Xing, Liang Chu and Chong Guo
Electronics 2021, 10(18), 2295; https://doi.org/10.3390/electronics10182295 - 17 Sep 2021
Cited by 2 | Viewed by 2399
Abstract
Traffic lights are an important part of urban roads. They improve traffic conditions but bring about a limitation of driving speed in the space–time domain for vehicles. In this paper, a traffic light model based on a vehicle–road cooperative system is built. The [...] Read more.
Traffic lights are an important part of urban roads. They improve traffic conditions but bring about a limitation of driving speed in the space–time domain for vehicles. In this paper, a traffic light model based on a vehicle–road cooperative system is built. The model provides the vehicle with speed constraints when passing the green light in the time–space domain. A global-optimization-based energy management strategy based on dynamic programming (DP) is constructed with the constraints. The simulations are performed for two driving situations of different signal phases with the electric vehicle driven by a single power source. Compared with the traditional fixed speed driving strategy and green light optimal speed advisory (GLOSA) system, the energy management strategy proposed in this paper is able to control operating points of the motor to be distributed in more efficiency areas. A higher economy is achieved from simulation results. Full article
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20 pages, 3501 KiB  
Article
Unsupervised Neural Networks for Identification of Aging Conditions in Li-Ion Batteries
by Pablo Pastor-Flores, Bonifacio Martín-del-Brío, Antonio Bono-Nuez, Iván Sanz-Gorrachategui and Carlos Bernal-Ruiz
Electronics 2021, 10(18), 2294; https://doi.org/10.3390/electronics10182294 - 17 Sep 2021
Cited by 2 | Viewed by 1823
Abstract
This paper explores a new methodology based on data-driven approaches to identify and track degradation processes in Li-ion batteries. Our goal is to study if it is possible to differentiate the state of degradation of cells that present similar aging in terms of [...] Read more.
This paper explores a new methodology based on data-driven approaches to identify and track degradation processes in Li-ion batteries. Our goal is to study if it is possible to differentiate the state of degradation of cells that present similar aging in terms of overall parameters (similar remaining capacity, state of health or internal resistance), but that have had different applications or conditions of use (different discharge currents, depth of discharges, temperatures, etc.). For this purpose, this study proposed to analyze voltage waveforms of cells obtained in cycling tests by using an unsupervised neural network, the Self-Organizing Map (SOM). In this work, a laboratory dataset of real Li-ion cells was used, and the SOM algorithm processed battery cell features, thus carrying out smart sensing of the battery. It was shown that our methodology differentiates the previous conditions of use (history) of a cell, complementing conventional metrics such as the state of health, which could be useful for the growing second-life market because it allows for determining more precisely the state of disease of a battery and assesses its suitability for a specific application. Full article
(This article belongs to the Special Issue Machine Learning and Smart Sensing)
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22 pages, 3814 KiB  
Article
Implementation of an Autonomous Overtaking System Based on Time to Lane Crossing Estimation and Model Predictive Control
by Yu-Chen Lin, Chun-Liang Lin, Shih-Ting Huang and Cheng-Hsuan Kuo
Electronics 2021, 10(18), 2293; https://doi.org/10.3390/electronics10182293 - 17 Sep 2021
Cited by 6 | Viewed by 2911
Abstract
According to statistics, the majority of accidents are attributed to driver negligence, especially when a driver intends to lane change or to overtake another vehicle, which is most likely to cause accidents. In addition, overtaking is one of the most difficult and complex [...] Read more.
According to statistics, the majority of accidents are attributed to driver negligence, especially when a driver intends to lane change or to overtake another vehicle, which is most likely to cause accidents. In addition, overtaking is one of the most difficult and complex functions for the development of autonomous driving technologies because of the dynamic and complicated task involved in the control strategy and electronic control systems, such as steering, throttle, and brake control. This paper proposes a safe overtaking maneuver procedure for an autonomous vehicle based on time to lane crossing (TLC) estimation and the model predictive control scheme. As overtaking is one of the most complex maneuvers that require both lane keeping and lane changing, a vision-based lane-detection system is used to estimate TLC to make a timely and accurate decision about whether to overtake or remain within the lane. Next, to maintain the minimal safe distance and to choose the best timing to overtake, the successive linearization-based model predictive control is employed to derive an optimal vehicle controller, such as throttle, brake, and steering angle control. Simultaneously, it can make certain that the longitudinal acceleration and steering velocity are maintained under constraints to maintain driving safety. Finally, the proposed system is validated by real-world experiments performed on a prototype electric golf cart and executed in real-time on the automotive embedded hardware with limited computational power. In addition, communication between the sensors and actuators as well as the vehicle control unit (VCU) are based on the controller area network (CAN) bus to realize vehicle control and data collection. The experiments demonstrate the ability of the proposed overtaking decision and control strategy to handle a variety of driving scenarios, including a lane-following function when a relative yaw angle exists and an overtaking function when the approaching vehicle has a different lateral velocity. Full article
(This article belongs to the Special Issue Intelligent Systems and Control Application in Autonomous Vehicle)
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32 pages, 710 KiB  
Article
Custom Memory Design for Logic-in-Memory: Drawbacks and Improvements over Conventional Memories
by Fabrizio Ottati, Giovanna Turvani, Guido Masera and Marco Vacca
Electronics 2021, 10(18), 2291; https://doi.org/10.3390/electronics10182291 - 17 Sep 2021
Cited by 2 | Viewed by 3049
Abstract
The speed of modern digital systems is severely limited by memory latency (the “Memory Wall” problem). Data exchange between Logic and Memory is also responsible for a large part of the system energy consumption. Logic-in-Memory (LiM) represents an attractive solution to this problem. [...] Read more.
The speed of modern digital systems is severely limited by memory latency (the “Memory Wall” problem). Data exchange between Logic and Memory is also responsible for a large part of the system energy consumption. Logic-in-Memory (LiM) represents an attractive solution to this problem. By performing part of the computations directly inside the memory the system speed can be improved while reducing its energy consumption. LiM solutions that offer the major boost in performance are based on the modification of the memory cell. However, what is the cost of such modifications? How do these impact the memory array performance? In this work, this question is addressed by analysing a LiM memory array implementing an algorithm for the maximum/minimum value computation. The memory array is designed at physical level using the FreePDK 45nm CMOS process, with three memory cell variants, and its performance is compared to SRAM and CAM memories. Results highlight that read and write operations performance is worsened but in-memory operations result to be very efficient: a 55.26% reduction in the energy-delay product is measured for the AND operation with respect to the SRAM read one. Therefore, the LiM approach represents a very promising solution for low-density and high-performance memories. Full article
(This article belongs to the Special Issue Computing-in-Memory Devices and Systems)
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9 pages, 3309 KiB  
Article
Highly Stable Inverted CdSe/ZnS-Based Light-Emitting Diodes by Nonvacuum Technique ZTO as the Electron-Transport Layer
by Sajid Hussain, Fawad Saeed, Ahmad Raza, Abida Parveen, Ali Asghar, Nasrud Din, Zhang Chao, Jing Chen, Qasim Khan and Wei Lei
Electronics 2021, 10(18), 2290; https://doi.org/10.3390/electronics10182290 - 17 Sep 2021
Cited by 4 | Viewed by 2616
Abstract
CdSe/ZnS quantum dots (QDs) have attracted great consideration from investigators owing to their excellent photo-physical characteristics and application in quantum dot light-emitting diodes (QD-LEDs). The CdSe/ZnS-based inverted QD-LEDs structure uses high-quality semiconductors electron transport layers (ETLs), a multilayered hole transporting layers (HTLs). In [...] Read more.
CdSe/ZnS quantum dots (QDs) have attracted great consideration from investigators owing to their excellent photo-physical characteristics and application in quantum dot light-emitting diodes (QD-LEDs). The CdSe/ZnS-based inverted QD-LEDs structure uses high-quality semiconductors electron transport layers (ETLs), a multilayered hole transporting layers (HTLs). In QD-LED, designing a device structure with a minimum energy barrier between adjacent layers is very important to achieve high efficiency. A high mobility polymer of poly (9,9-dioctylfluorene-co-N-(4-(3-methylpropyl)) diphenylamine (TFB) was doped with 4,4′-bis-(carbazole-9-yl) biphenyl (CBP) with deep energy level to produce composite TFB:CBP holes to solve energy mismatch (HTL). In addition, we also improved the QD-LED device structure by using zinc tin oxide (ZTO) as ETL to improve device efficiency. The device turn-on voltage Vt (1 cd m−2) with ZTO ETL reduced from 2.4 V to 1.9 V significantly. Furthermore, invert structure devices exhibit luminance of 4296 cd m−2, current-efficiency (CE) of 7.36 cd A−1, and external-quantum efficiency (EQE) of 3.97%. For the QD-LED based on ZTO, the device efficiency is improved by 1.7 times. Full article
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