Editorial

5 pages, 179 KiB

Open AccessEditorial

Special Issue on Application of Electronic Devices on Intelligent System

by Teen-Hang Meen and Cheng-Chien Kuo

Electronics 2021, 10(13), 1506; https://doi.org/10.3390/electronics10131506 - 22 Jun 2021

Cited by 1 | Viewed by 1124

In a modern technological society, electronic engineering and design innovations are both academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs [...] Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

Research

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30 pages, 12186 KiB

Open AccessArticle

Buck-Boost/Flyback Hybrid Converter for Solar Power System Applications

by Sheng-Yu Tseng and Jun-Hao Fan

Electronics 2021, 10(4), 414; https://doi.org/10.3390/electronics10040414 - 08 Feb 2021

Cited by 7 | Viewed by 2549

Abstract

This paper proposes a hybrid converter to supply power from solar power source to load. Since power is generated by solar power, which depends on the intensity of solar power, the power generated by the solar power does not keep at a constant [...] Read more.

This paper proposes a hybrid converter to supply power from solar power source to load. Since power is generated by solar power, which depends on the intensity of solar power, the power generated by the solar power does not keep at a constant power. Therefore, the proposed system needs a battery to balance power between solar power and load. When the proposed one uses the battery to balance powers, the proposed circuit requires a charger and discharger. To simplify the proposed converter, a buck-boost converter and flyback converter can be combined to implement the battery charging and discharging functions. With this approach, the proposed converter can be operated with zero-voltage switching (ZVS) at turn-on transition to reduce switching loss of switch when the proposed one is operated in the discharging mode. In addition, the proposed hybrid converter has several merits, which are less component counts, lighter weight, smaller size and higher conversion efficiency. As compared with the conventional counterparts with hard-switching circuit, the proposed one can increase conversion efficiency of 4% and achieve efficiency of 85% under full load condition when the proposed one is operated in the discharging mode. Experimental results which are obtained from a prototype with output voltage of 10 V and maximum output power 20 W have been implemented to verify its feasibility. It is suitable for an electronic sign indicating LED within 200 W, which is used in the night time. Full article

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18 pages, 4069 KiB

Open AccessFeature PaperArticle

Planning and Research of Distribution Feeder Automation with Decentralized Power Supply

by Yen-Chih Huang, Wen-Ching Chang, Hsuan Hsu and Cheng-Chien Kuo

Electronics 2021, 10(3), 362; https://doi.org/10.3390/electronics10030362 - 02 Feb 2021

Cited by 7 | Viewed by 2153

Abstract

The high penetration of distributed generation in distributed energy systems causes the variation of power loss and makes the power grid become more complicated, so this paper takes various types of optimal algorithms into account and simulates the feeder reconfiguration on the IEEE-33 [...] Read more.

The high penetration of distributed generation in distributed energy systems causes the variation of power loss and makes the power grid become more complicated, so this paper takes various types of optimal algorithms into account and simulates the feeder reconfiguration on the IEEE-33 system as well as the Taiwan power system. The simulation verifies linear population size reduction of successful history-based adaptive differential evolution (L-SHADE) and particle swarm optimization (PSO) fitness in different systems and provides the recommended location of distributed energy. The proposed method keeps the voltage bound of 0.95 to 1.03 p.u. of Taiwan regulation. In the IEEE-33 system, we achieved a 52.57% power loss reduction after feeder reconfiguration, and a 70.55% power loss reduction after the distributed generator was implemented and feeder reconfiguration. Under the variation of load demand and power generation of the Taiwan power system, we establish the system models by forecasting one-day load demand. Then, we propose a one-day feeder switch operation strategy by considering the switches’ operation frequency with the reduction of 83.3% manual operation and recommend feeder automation to achieve feeder power loss reduction, voltage profile improvement and get regional power grid resilient configuration. Full article

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16 pages, 1324 KiB

Open AccessArticle

Fuzzy ARTMAP-Based Fast Object Recognition for Robots Using FPGA

by Victor Lomas-Barrie, Mario Pena-Cabrera, Ismael Lopez-Juarez and Jose Luis Navarro-Gonzalez

Electronics 2021, 10(3), 361; https://doi.org/10.3390/electronics10030361 - 02 Feb 2021

Cited by 3 | Viewed by 2745

Abstract

Fast object recognition and classification is highly important when handling operations with robots. This article shows the design and implementation of an invariant recognition machine vision system to compute a descriptive vector called the Boundary Object Function (BOF) using the FuzzyARTMAP (FAM) Neural [...] Read more.

Fast object recognition and classification is highly important when handling operations with robots. This article shows the design and implementation of an invariant recognition machine vision system to compute a descriptive vector called the Boundary Object Function (BOF) using the FuzzyARTMAP (FAM) Neural Network. The object recognition machine is integrated in the Zybo Z7-20 module that includes reconfigurable FPGA hardware and a RISC processor. Object encoding, description and prediction is carried out rapidly compared to the processing time devoted to video capture at the camera’s frame rate. Benefiting from parallel computing, we calculated the object’s centroid and boundary points while acquiring the progressive image frame; all that was done with the intention of readying it for neural processing. The remaining time was devoted to recognising the object, this caused low latency (1.47 ms). Our test-bed also included TCP/IP communication to send/receive part location for grasping operations with an industrial robot to evaluate the approach. Results demonstrate that the hardware integration of the video sensor, image processing, descriptor generator, and the ANN classifier for cognitive decision on a single chip can increase the speed and performance of intelligent robots designed for smart manufacturing. Full article

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19 pages, 6201 KiB

Open AccessArticle

Bridgeless Boost Converter with an Interleaving Manner for PFC Applications

by Sheng-Yu Tseng and Jun-Hao Fan

Electronics 2021, 10(3), 296; https://doi.org/10.3390/electronics10030296 - 26 Jan 2021

Cited by 10 | Viewed by 3506

Abstract

Power quality is a critical issue in power systems. This paper proposes a bridgeless boost converter to increase the power factor of power systems using a utility line source for raising power quality. To reduce input and output current ripple, an interleaving manner [...] Read more.

Power quality is a critical issue in power systems. This paper proposes a bridgeless boost converter to increase the power factor of power systems using a utility line source for raising power quality. To reduce input and output current ripple, an interleaving manner is adopted in the proposed power system. When the interleaving bridgeless boost converter is used to implement power factor correction (PFC), it needs two bridgeless boost converters to process power during one switching cycle. In order to simplify the proposed bridgeless boost converter, two sets of switches in the conventional bridgeless boost one are integrated to reduce component counts. With this approach, the proposed bridgeless boost converter uses four switches to implement PFC features. Therefore, the proposed boost converter can increase conversion efficiency and decrease component counts, resulting in a higher conversion efficiency, lower cost and more simplicity for driving circuits. Finally, a prototype with a universal input voltage source (AC 90 V~265 V) under an output voltage of 400 V and a maximum output power of 1 kW has been implemented to verify the feasibility of the proposed bridgeless boost converter. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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10 pages, 1084 KiB

Open AccessArticle

Lower-Limb Electromyography Signal Analysis of Distinct Muscle Fitness Norms under Graded Exercise Intensity

by Ching-Kun Chen, Shyan-Lung Lin, Tasi-Chu Wang, Yu-Jie Lin and Chieh-Liang Wu

Electronics 2020, 9(12), 2147; https://doi.org/10.3390/electronics9122147 - 15 Dec 2020

Cited by 3 | Viewed by 2192

Abstract

Physical fitness is the overall ability of the body to adapt to the working environment and perform sporting and daily activities. The aim of this study was to analyze the correlation between muscle fitness and the electromyography (EMG) signals of lower limbs under [...] Read more.

Physical fitness is the overall ability of the body to adapt to the working environment and perform sporting and daily activities. The aim of this study was to analyze the correlation between muscle fitness and the electromyography (EMG) signals of lower limbs under varying exercise intensity. The standing long jump was used as a test task for assessing the power of the lower limb muscles. Participants were university freshmen who belonged to the top 20%, middle 20%, and bottom 20% groups in terms of physical fitness norms. The EMG signals of the participants’ lower limbs while they performed squats were collected under four exercise intensities of repetitions maximum (RM): no load, 8RM, 18RM, and 28RM; the features of the signals were extracted using time-domain and frequency-domain analysis. Statistical analysis was also performed. The top and bottom groups exhibited significant differences time-domain indicators mean absolute value (MAV) and average amplitude change (AAC) in the low-intensity exercise (28RM). The MAV, variance of EMG (VAR), root mean square (RMS), and AAC were significantly different between the top and bottom groups in the three graded intensities (8RM, 18RM, and 28RM). The mean frequency (MNF) and median frequency (MDF), which are frequency-domain indicators, were significantly different between the top and bottom groups in the low-intensity (28RM) and moderate-intensity (18RM) exercises. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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15 pages, 6031 KiB

Open AccessArticle

Hot Carrier Stress Sensing Bulk Current for 28 nm Stacked High-k nMOSFETs

by Chii-Wen Chen, Mu-Chun Wang, Cheng-Hsun-Tony Chang, Wei-Lun Chu, Shun-Ping Sung and Wen-How Lan

Electronics 2020, 9(12), 2095; https://doi.org/10.3390/electronics9122095 - 08 Dec 2020

Cited by 6 | Viewed by 5502

Abstract

This work primarily focuses on the degradation degree of bulk current (I_B) for 28 nm stacked high-k (HK) n-channel metal–oxide–semiconductor field-effect transistors (MOSFETs), sensed and stressed with the channel-hot-carrier test and the drain-avalanche-hot-carrier test, and uses a lifetime model to [...] Read more.

This work primarily focuses on the degradation degree of bulk current (I_B) for 28 nm stacked high-k (HK) n-channel metal–oxide–semiconductor field-effect transistors (MOSFETs), sensed and stressed with the channel-hot-carrier test and the drain-avalanche-hot-carrier test, and uses a lifetime model to extract the lifetime of the tested devices. The results show that when I_B reaches its maximum, the ratio of V_GS/V_DS values at this point, in the meanwhile, gradually increases in the tested devices from the long-channel to the short ones, not just located at one-third to one half. The possible ratiocination is due to the ON-current (I_DS), in which the short-channel devices provide larger I_DS impacting the drain junction and generating more hole carriers at the surface channel near the drain site. In addition, the decrease in I_B after hot-carrier stress is not only the increment in threshold voltage V_T inducing the decrease in I_DS, but also the increment in the recombination rate due to the mechanism of diffusion current. Ultimately, the device lifetime uses Berkley’s model to extract the slope parameter m of the lifetime model. Previous studies have reported m-values ranging from 2.9 to 3.3, but in this case, approximately 1.1. This possibly means that the critical energy of the generated interface state becomes smaller, as is the barrier height of the HK dielectric to the conventional silicon dioxide as the gate oxide. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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13 pages, 10803 KiB

Open AccessArticle

Q-Factor Performance of 28 nm-Node High-K Gate Dielectric under DPN Treatment at Different Annealing Temperatures

by Chii-Wen Chen, Shea-Jue Wang, Wen-Ching Hsieh, Jian-Ming Chen, Te Jong, Wen-How Lan and Mu-Chun Wang

Electronics 2020, 9(12), 2086; https://doi.org/10.3390/electronics9122086 - 07 Dec 2020

Cited by 10 | Viewed by 2405

Abstract

Q-factor is a reasonable index to investigate the integrity of circuits or devices in terms of their energy or charge storage capabilities. We use this figure of merit to explore the deposition quality of nano-node high-k gate dielectrics by decoupled-plasma nitridation at [...] Read more.

Q-factor is a reasonable index to investigate the integrity of circuits or devices in terms of their energy or charge storage capabilities. We use this figure of merit to explore the deposition quality of nano-node high-k gate dielectrics by decoupled-plasma nitridation at different temperatures with a fixed nitrogen concentration. This is very important in radio-frequency applications. From the point of view of the Q-factor, the device treated at a higher annealing temperature clearly demonstrates a better Q-factor value. Another interesting observation is the appearance of two troughs in the Q-V_GS characteristics, which are strongly related to either the series parasitic capacitance, the tunneling effect, or both. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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13 pages, 4303 KiB

Open AccessArticle

Automated and Intelligent System for Monitoring Swimming Pool Safety Based on the IoT and Transfer Learning

by Aziz Alotaibi

Electronics 2020, 9(12), 2082; https://doi.org/10.3390/electronics9122082 - 06 Dec 2020

Cited by 12 | Viewed by 5139

Abstract

Recently, integrating the Internet of Things (IoT) and computer vision has been utilized in swimming pool automated surveillance systems. Several studies have been proposed to overcome off-time surveillance drowning incidents based on using a sequence of videos to track human motion and position. [...] Read more.

Recently, integrating the Internet of Things (IoT) and computer vision has been utilized in swimming pool automated surveillance systems. Several studies have been proposed to overcome off-time surveillance drowning incidents based on using a sequence of videos to track human motion and position. This paper proposes an efficient and reliable detection system that utilizes a single image to detect and classify drowning objects, to prevent drowning incidents. The proposed system utilizes the IoT and transfer learning to provide an intelligent and automated solution for off-time monitoring swimming pool safety. In addition, a specialized transfer-learning-based model utilizing a model pretrained on “ImageNet”, which can extract the most useful and complex features of the captured image to differentiate between humans, animals, and other objects, has been proposed. The proposed system aims to reduce human intervention by processing and sending the classification results to the owner’s mobile device. The performance of the specialized model is evaluated by using a prototype experiment that achieves higher accuracy, sensitivity, and precision, as compared to other deep learning algorithms. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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23 pages, 10195 KiB

Open AccessArticle

A Non-Dissipative Equalizer with Fast Energy Transfer Based on Adaptive Balancing Current Control

by Shun-Chung Wang, Chun-Yu Liu and Yi-Hua Liu

Electronics 2020, 9(12), 1990; https://doi.org/10.3390/electronics9121990 - 24 Nov 2020

Cited by 5 | Viewed by 1885

Abstract

In this study, an active inductive equalizer with fast energy transfer based on adaptive balancing current control is proposed to rapidly equilibrate lithium-ion battery packs. A multiphase structure of equalizer formed by many specific parallel converter legs (PCLs) with bidirectional energy conversion serves [...] Read more.

In this study, an active inductive equalizer with fast energy transfer based on adaptive balancing current control is proposed to rapidly equilibrate lithium-ion battery packs. A multiphase structure of equalizer formed by many specific parallel converter legs (PCLs) with bidirectional energy conversion serves as the power transfer stage to make the charge shuttle back and forth between the cell and sub-pack or sub-pack and sub-pack more flexible and efficient. This article focuses on dealing with the problem of slow balancing rate, which inherently arises from the reduction of balancing current as the voltage difference between the cells or sub-packs decreases, especially in the later period of equalization. An adaptive varied-duty-cycle (AVDC) algorithm is put forward here to accelerate the balance process. The devised method has taken the battery nonlinear behavior and the nonideality of circuit component into consideration and can adaptively modulate the duty cycle with the change of voltage differences to maintain balancing current nearly constant in the whole equilibrating procedure. Test results derived from simulations and experiments are provided to demonstrate the validity and effectiveness of the equalizer prototype constructed. Comparing with the conventional fixed duty cycle (FDC) method, the improvements of 68.3% and 8.3% in terms of balance time and efficiency have been achieved. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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17 pages, 7982 KiB

Open AccessArticle

Frequency Occurrence Plot-Based Convolutional Neural Network for Motor Fault Diagnosis

by Eduardo Jr Piedad, Yu-Tung Chen, Hong-Chan Chang and Cheng-Chien Kuo

Electronics 2020, 9(10), 1711; https://doi.org/10.3390/electronics9101711 - 18 Oct 2020

Cited by 20 | Viewed by 3093

Abstract

A novel motor fault diagnosis using only motor current signature is developed using a frequency occurrence plot-based convolutional neural network (FOP-CNN). In this study, a healthy motor and four identical motors with synthetically applied fault conditions—bearing axis deviation, stator coil inter-turn short circuiting, [...] Read more.

A novel motor fault diagnosis using only motor current signature is developed using a frequency occurrence plot-based convolutional neural network (FOP-CNN). In this study, a healthy motor and four identical motors with synthetically applied fault conditions—bearing axis deviation, stator coil inter-turn short circuiting, a broken rotor strip, and outer bearing ring damage—are tested. A set of 150 three-second sampling stator current signals from each motor fault condition are taken under five artificial coupling loads (0, 25%, 50%, 75% and 100%). The sampling signals are collected and processed into frequency occurrence plots (FOPs) which later serve as CNN inputs. This is done first by transforming the time series signals into its frequency spectra then convert these into two-dimensional FOPs. Fivefold stratified sampling cross-validation is performed. When motor load variations are considered as input labels, FOP-CNN predicts motor fault conditions with a 92.37% classification accuracy. It precisely classifies and recalls bearing axis deviation fault and healthy conditions with 99.92% and 96.13% f-scores, respectively. When motor loading variations are not used as input data labels, FOP-CNN still satisfactorily predicts motor condition with an 80.25% overall accuracy. FOP-CNN serves as a new feature extraction technique for time series input signals such as vibration sensors, thermocouples, and acoustics. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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21 pages, 7852 KiB

Open AccessArticle

FPGA Acceleration of CNNs-Based Malware Traffic Classification

by Lin Zhang, Bing Li, Yong Liu, Xia Zhao, Yazhou Wang and Jiaxin Wu

Electronics 2020, 9(10), 1631; https://doi.org/10.3390/electronics9101631 - 03 Oct 2020

Cited by 7 | Viewed by 3049

Abstract

With the rapid development of the Internet, malware traffic is seriously endangering the security of cyberspace. Convolutional neural networks (CNNs)-based malware traffic classification can automatically learn features from raw traffic, avoiding the inaccuracy of hand-design traffic features. Through the experiments and comparisons of [...] Read more.

With the rapid development of the Internet, malware traffic is seriously endangering the security of cyberspace. Convolutional neural networks (CNNs)-based malware traffic classification can automatically learn features from raw traffic, avoiding the inaccuracy of hand-design traffic features. Through the experiments and comparisons of LeNet, AlexNet, VGGNet, and ResNet, it is found that LeNet has good and stable classification ability for malware traffic and normal traffic. Then, a field programmable gate array (FPGA) accelerator for CNNs-based malware traffic classification is designed, which consists of a parameterized hardware accelerator and a fully automatic software framework. By fully exploring the parallelism between CNN layers, parallel computation and pipeline optimization are used in the hardware design to achieve high performance. Simultaneously, runtime reconfigurability is implemented by using a global register list. By encapsulating the underlying driver, a three-layer software framework is provided for users to deploy their pre-trained models. Finally, a typical CNNs-based malware traffic classification model was selected to test and verify the hardware accelerator. The typical application system can classify each traffic image from the test dataset in 18.97 μs with the accuracy of 99.77%, and the throughput of the system is 411.83 Mbps. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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16 pages, 648 KiB

Open AccessArticle

Posit Arithmetic Hardware Implementations with The Minimum Cost Divider and SquareRoot

by Feibao Xiao, Feng Liang, Bin Wu, Junzhe Liang, Shuting Cheng and Guohe Zhang

Electronics 2020, 9(10), 1622; https://doi.org/10.3390/electronics9101622 - 02 Oct 2020

Cited by 12 | Viewed by 3277

Abstract

As a substitute for the IEEE 754-2008 floating-point standard, Posit, a new kind of number system for floating-point numbers, was put forward recently. Hitherto, some studies have proven that Posit is a better floating-point style than IEEE 754-2008 in some fields. However, most [...] Read more.

As a substitute for the IEEE 754-2008 floating-point standard, Posit, a new kind of number system for floating-point numbers, was put forward recently. Hitherto, some studies have proven that Posit is a better floating-point style than IEEE 754-2008 in some fields. However, most of these studies presented the advantages of Posit from the arithmetical aspect, but none of them suggested it had a better hardware implementation than that of IEEE 754-2008. In this paper, we propose several hardware implementations that contain the Posit adder/subtractor, multiplier, divider, and square root. Our goal is to achieve an arbitrary Posit format and exploit the minimum circuit area, which is required in embedded devices. To implement the minimum circuit area for the divider and square root, the alternating addition and subtraction method is used rather than the Newton–Raphson method. Compared with other works, the area of our divider is about 0.2×–0.7× (FPGA). Furthermore, this paper provides the synthesis results for each critical module with the Xilinx Virtex-7 FPGA VC709 platform. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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9 pages, 1928 KiB

Open AccessArticle

Lung Nodule Classification Using Taguchi-Based Convolutional Neural Networks for Computer Tomography Images

by Cheng-Jian Lin and Yu-Chi Li

Electronics 2020, 9(7), 1066; https://doi.org/10.3390/electronics9071066 - 29 Jun 2020

Cited by 20 | Viewed by 6500

Abstract

Lung cancer occurs in the lungs, trachea, or bronchi. This cancer is often caused by malignant nodules. These cancer cells spread uncontrollably to other organs of the body and pose a threat to life. An accurate assessment of disease severity is critical to [...] Read more.

Lung cancer occurs in the lungs, trachea, or bronchi. This cancer is often caused by malignant nodules. These cancer cells spread uncontrollably to other organs of the body and pose a threat to life. An accurate assessment of disease severity is critical to determining the optimal treatment approach. In this study, a Taguchi-based convolutional neural network (CNN) was proposed for classifying nodules into malignant or benign. For setting parameters in a CNN, most users adopt trial and error to determine structural parameters. This study used the Taguchi method for selecting preliminary factors. The orthogonal table design is used in the Taguchi method. The final optimal parameter combination was determined, as were the most significant parameters. To verify the proposed method, the lung image database consortium data set from the National Cancer Institute was used for analysis. The database contains a total of 16,471 images, including 11,139 malignant nodule images. The experimental results demonstrated that the proposed method with the optimal parameter combination obtained an accuracy of 99.6%. Full article

(This article belongs to the Special Issue Application of Electronic Devices on Intelligent System)

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14 pages, 6016 KiB

Open AccessArticle

A Segmentation Enhancement Method for the Low-Contrast and Narrow-Banded Substances in CBCT Images

by Lam Dao-Ngoc, Ching-Feng Liu and Yi-Chun Du

Electronics 2020, 9(6), 974; https://doi.org/10.3390/electronics9060974 - 11 Jun 2020

Cited by 3 | Viewed by 2276

Abstract

Due to its low contrast, narrow banded, and emerged to the output imaging attribute scale, facial skin tissue is difficult to extract from dental cone-beam computed tomography (CBCT) reconstructions. Furthermore, there is a challenge of balancing the indication and patient-specific factors and imaging [...] Read more.

Due to its low contrast, narrow banded, and emerged to the output imaging attribute scale, facial skin tissue is difficult to extract from dental cone-beam computed tomography (CBCT) reconstructions. Furthermore, there is a challenge of balancing the indication and patient-specific factors and imaging dosage to make it both safe and diagnostically effective for successful treatment planning. These issues make a new frontier for facial skin and soft tissue diagnostic applications driven by sparse dental and low-dose CBCT data. In this study, a new segmentation enhancement method for low-contrast and narrow-banded substances is proposed based on our previous work on selective anatomy analysis iterative reconstruction (SA2IR). The purpose of the proposed method is to segment facial skin tissue based on combinatorial optimization and previously known facial soft tissue structure anatomy. Our results using this method indicated that the skin thickness was much more easily and more quickly identified than with conventional ultrasonic scanning methods. This method holds the potential to be an assisting tool for studying linage of anthropometrics, forensics, human archaeology, and some narrow medico-dental applications. Full article

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