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Electronics
Journal Prestige (SJR): 0.548
Citation Impact (citeScore): 3
Number of Followers: 125  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2079-9292
Published by MDPI Homepage  [84 journals]
  • Electronics, Vol. 11, Pages 2476: Booking Public Charging: User
           Preferences and Behavior towards Public Charging Infrastructure with a
           Reservation Option

    • Authors: Michael Hardinghaus, John Erik Anderson, Claudia Nobis, Kerstin Stark, Galya Vladova
      First page: 2476
      Abstract: Electric vehicles offer a means to reduce greenhouse gas emissions in passenger transport. The availability of reliable charging infrastructure is crucial for the successful uptake of electric vehicles in dense urban areas. In a pilot project in the city of Hamburg, Germany, public charging infrastructure was equipped with a reservation option providing exclusive access for local residents and businesses. The present paper combines quantitative and qualitative methods to investigate the effects of the newly introduced neighborhood charging concept. We use a methodology combining a quantitative questionnaire survey and qualitative focus group discussions as well as analyses of charging infrastructure utilization data. Results show that inner-city charging and parking options are of key importance for (potential) users of electric vehicles. Hence, the neighborhood concept is rated very positively. Providing guaranteed charging and parking facilities is therefore likely to increase the stock of EVs. On the other hand, this could to a large extent lead to additional cars with consequential disadvantages. The study shows that openly accessible infrastructure is presently utilized much more intensely than the exclusive option. Consequentially, the concept evaluated should be part of an integrated approach managing parking and supporting efficient concepts like car sharing.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162476
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2477: A Novel Non-Isolated Step-Up DC/AC
           Inverter with Less Switches

    • Authors: Chao Chen, Tao Wu, Yixing Gu, Changli Shi
      First page: 2477
      Abstract: In order to solve the problem of leakage current and step-up voltage capability associated with the single-phase single-stage non-isolated inverter, a new topology is proposed in this paper. The proposal has the advantages of less switch components, high step-up voltage capability and no leakage current. The three operation modes are discussed and the modulation strategy is designed. Finally, the prototype of the proposed new single-phase single-stage non-isolated inverter is established. The TMS320F28335 DSP and Xilinx XC6SLX9 FPGA are used to provide the system with digital control. The experimental results show that the proposed inverter achieved the boosted ability as well as the sinusoidal output voltage, whose total harmonic distortion is well below 5%, which meets the IEEE Std. 519-2014.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162477
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2478: Coplanar Asymmetry Transformer
           Distributed Modeling for X-Band Drive Power Amplifier Design on GaN
           Process

    • Authors: Yihui Fan, Jing Wan, Zhe Yang, Shengli Zhang, Jinxiang Zhao, Gong Gao, Xiaojie Zhang, Haoyu Shen, Nan Xiao, Yuying Zhang, Yuepeng Yan, Xiaoxin Liang
      First page: 2478
      Abstract: In this paper, a methodology for designing a distributed model for coplanar asymmetry transformer on gallium nitride (GaN) process is proposed, which can accurately characterize the transformer’s feature up to a millimeter-wave band. The paper analyses a transformer-based matching circuit and proposes a practical transformer design procedure. A two stage, transformer matching based X-band power amplifier (PA) is reported here. Using the proposed transformer model and correlated transformer design procedure can sharply reduce schematic design period and optimum process time. The PA chip is designed on a 0.25 µm GaN technology process and occupies a 1.515 mm2 area. At a 28 V supply, the gain and output power of the PA reaches 15 dB and 29 dBm respectively, and the wideband matching transformer reaches 47.6% bandwidth. To the best of our knowledge, the distributed model for coplanar asymmetry transformer and transformer-based X-band MMIC PA on GaN process in this work is the first case among the reported papers.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162478
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2479: An Improved Multi-Objective Deep
           Reinforcement Learning Algorithm Based on Envelope Update

    • Authors: Can Hu, Zhengwei Zhu, Lijia Wang, Chenyang Zhu, Yanfei Yang
      First page: 2479
      Abstract: Multi-objective reinforcement learning (MORL) aims to uniformly approximate the Pareto frontier in multi-objective decision-making problems, which suffers from insufficient exploration and unstable convergence. We propose a multi-objective deep reinforcement learning algorithm (envelope with dueling structure, Noisynet, and soft update (EDNs)) to improve the ability of the agent to learn optimal multi-objective strategies. Firstly, the EDNs algorithm uses neural networks to approximate the value function and update the parameters based on the convex envelope of the solution boundary. Then, the DQN structure is replaced with the dueling structure, and the state value function is split into the dominance function and value function to make it converge faster. Secondly, the Noisynet method is used to add exploration noise to the neural network parameters to make the agent have a more efficient exploration ability. Finally, the soft update method updates the target network parameters to stabilize the training procedure. We use the DST environment as a case study, and the experimental results show that the EDNs algorithm has better stability and exploration capability than the EMODRL algorithm. In 1000 episodes, the EDNs algorithm improved the coverage by 5.39% and reduced the adaptation error by 36.87%.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162479
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2480: Phase-Based Low Power Management
           Combining CPU and GPU for Android Smartphones

    • Authors: Seung-Ryeol Ohk, YongSin Kim, Young-Jin Kim
      First page: 2480
      Abstract: Smartphones have limited battery capacity, so efficient power management is required for high-performance applications and to increase usage time. In recent years, efficient power management of smartphones has become very important as the demand for power use of smartphones has grown due to deep learning, games, virtual reality, and augmented reality applications. Existing low-power techniques of smartphones focus only on lowering power consumption without considering actual power consumption based on utilization of the central processing unit (CPU) and graphics processing unit (GPU), which are major components of smartphones. In addition, they do not take into consideration the strict use of resources within the component and what instructions are being processed to operate them. In this paper, we propose a low-power technique that manages power by calculating the actual power consumption of smartphones at execution time and classifying the detailed resource operating states of CPUs and GPUs. The proposed technique was implemented by linking the kernel and native app on a Galaxy S7 smartphone equipped with Android. In experiments with 15 workloads, the proposed technique achieves an energy reduction of 18.11% compared to the low-power technique of the interactive governor built into the Galaxy S7 with a small FPS reduction of 3.12%.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162480
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2481: A Systematic Method to Generate
           Effective STLs for the In-Field Test of CAN Bus Controllers

    • Authors: Felipe Augusto da Silva, Riccardo Cantoro, Said Hamdioui, Sandro Sartoni, Christian Sauer, Matteo Sonza Reorda
      First page: 2481
      Abstract: In order to match the strict reliability requirements mandated by regulations and standards adopted in the automotive sector, as well as other domains where safety is a major concern, the in-field testing of the most critical devices, including microcontrollers and systems on chip, is a crucial task. Since the controller area network (CAN) bus is widely used in the automotive domain, the corresponding controller ubiquitously appears in all these devices. This paper presents a generic and systematic methodology to develop an effective in-field test procedure for CAN controllers based on a functional approach (i.e., on the adoption of self-test libraries). The method can be customized to match the requirements coming from different scenarios, and allows the test engineer to maximize the achieved fault coverage in terms of structural faults in the different cases. The experimental results we gathered on a representative CAN controller model show that, given two typical testing scenarios, we are able to detect 84.28% and 87.62% of stuck-at faults, respectively, hence demonstrating the effectiveness of the proposed approach.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162481
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2482: Multi-Objective Navigation Strategy for
           Guide Robot Based on Machine Emotion

    • Authors: Dan Chen, Yuncong Ge
      First page: 2482
      Abstract: In recent years, the rapid development of robot technology means more kinds of robots appear in life and they are applied in different fields of society. Service robots are mainly used to provide convenience for human beings. Guide robots are a kind of service robot, which can replace manual instruction and guidance. However, most of the existing studies provide a preset guidance trajectory for the guiding robot, or they let the user choose the next target point for position guidance, which is a lack of intelligence. To solve the above problems, a robot navigation strategy based on machine emotion is proposed. Firstly, the machine emotion of the guide robot is established according to the user’s emotional state and environmental information. Then, the machine emotion and current location information are used to estimate the user’s intention, i.e., the most desired next target point. Finally, the classical indoor path planning method and obstacle avoidance method are employed to calculate a passable path between the target point and the current position. Simulation results show that the proposed strategy can execute different navigation strategies according to user emotion. The navigation strategy proposed in this paper has been tested on Pepper robot and received good feedback from the subjects.
      Citation: Electronics
      PubDate: 2022-08-09
      DOI: 10.3390/electronics11162482
      Issue No: Vol. 11, No. 16 (2022)
       
  • Electronics, Vol. 11, Pages 2383: A Systematic Review of
           Machine-Vision-Based Leather Surface Defect Inspection

    • Authors: Zhiqiang Chen, Jiehang Deng, Qiuqin Zhu, Hailun Wang, Yi Chen
      First page: 2383
      Abstract: Machine-vision-based surface defect inspection is one of the key technologies to realize intelligent manufacturing. This paper provides a systematic review on leather surface defect inspections based on machine vision. Leather products are regarded as the most traded products all over the world. Automatic detection, location, and recognition of leather surface defects are very important for the intelligent manufacturing of leather products, and are challenging but noteworthy tasks. This work investigates a large amount of literature related to leather surface defect inspection. In addition, we also investigate and evaluate the performance of some edge detectors and threshold detectors for leather defect detection, and the identification accuracy of the classical machine learning method SVM for leather surface defect identification. A detailed and methodical review of leather surface defect inspection with image analysis and machine learning is presented. Main challenges and future development trends are discussed for leather surface defect inspection, which can be used as a source of guidelines for designing and developing new solutions in this field.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152383
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2384: CMT-SCTP and MPTCP Multipath Transport
           Protocols: A Comprehensive Review

    • Authors: Parul Tomar, Gyanendra Kumar, Lal Pratap Verma, Varun Kumar Sharma, Dimitris Kanellopoulos, Sur Singh Rawat, Youseef Alotaibi
      First page: 2384
      Abstract: A huge amount of generated data is regularly exploding into the network by the users through smartphones, laptops, tablets, self-configured Internet-of-things (IoT) devices, and machine-to-machine (M2M) communication. In such a situation, satisfying critical quality-of-service (QoS) requirements (e.g., throughput, latency, bandwidth, and reliability) is a large challenge as a vast amount of data travels into the network. Nowadays, strict QoS requirements must be satisfied efficiently in many networked multimedia applications when intelligent multi-homed devices are used. Such devices support the concept of multi-homing. To be precise, they have multiple network interfaces that aim to connect and communicate concurrently with different networking technologies. Therefore, many multipath transport protocols are provided to multi-homed devices, which aim (1) to take advantage of several network paths at the transport layer (Layer-4) and (2) to meet the strict QoS requirements for providing low network latency, higher data rates, and increased reliability. To this end, this survey first presents the challenges/problems for supporting multipath transmission with possible solutions. Then, it reviews recent research efforts related to the concurrent multipath transmission (CMT) protocol and the multipath transmission control protocol (MPTCP). It reviews the latest research efforts by considering (1) how a multipath transport protocol operates (i.e., its functionality); (2) in what type of network; (3) what path characteristics it should consider; and (4) how it addresses various design challenges. Furthermore, it presents some lessons learned and discusses open research issues in multipath transport protocols.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152384
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2385: Secure and Efficient Message
           Authentication Scheme for 6G-Enabled VANETs

    • Authors: Longxia Liao, Junhui Zhao, Huanhuan Hu, Xiaoke Sun
      First page: 2385
      Abstract: In 6G-enabled vehicle ad hoc networks (VANETs), the messages transmitted through wireless communication face security problems such as tampering and disclosure. In this paper, to ensure the security of transmitted messages and the privacy of vehicle users, we propose an anonymous and secure message authentication (ASMA) scheme. The ASMA scheme can realize message verification and conditional privacy preservation with a lower computation overhead, and its security does not depend on a tamper-proof device (TPD). As the numbers of vehicles and applications increase in 6G-enabled VANETs, the number of messages in the network increases greatly. One-by-one verification messages in the ASMA scheme cannot meet the strict low-latency requirements. To improve the efficiency of the ASMA scheme, we investigate a proxy-vehicle-assisted batch message authentication (PVBA) scheme. In the scheme, a proxy vehicle selection algorithm is designed to choose a certain number of proxy vehicles, and the message verification tasks are completed by a roadside unit (RSU) and the proxy vehicles synchronously. Performance analysis shows that in the case of large-scale messages, the PVBA scheme has lower verification delay than related schemes, and the verification efficiency is greatly improved.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152385
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2386: Utilizing Spatio Temporal Gait Pattern
           and Quadratic SVM for Gait Recognition

    • Authors: Hajra Masood, Humera Farooq
      First page: 2386
      Abstract: This study aimed to develop a vision-based gait recognition system for person identification. Gait is the soft biometric trait recognizable from low-resolution surveillance videos, where the face and other hard biometrics are not even extractable. The gait is a cycle pattern of human body locomotion that consists of two sequential phases: swing and stance. The gait features of the complete gait cycle, referred to as gait signature, can be used for person identification. The proposed work utilizes gait dynamics for gait feature extraction. For this purpose, the spatio temporal power spectral gait features are utilized for gait dynamics captured through sub-pixel motion estimation, and they are less affected by the subject’s appearance. The spatio temporal power spectral gait features are utilized for a quadratic support vector machine classifier for gait recognition aiming for person identification. Spatio temporal power spectral preserves the spatiotemporal gait features and is adaptable for a quadratic support vector machine classifier-based gait recognition across different views and appearances. We have evaluated the gait features and support vector machine classifier-based gait recognition on a locally collected gait dataset that captures the effect of view variance in high scene depth videos. The proposed gait recognition technique achieves significant accuracy across all appearances and views.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152386
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2387: Emotion Recognition from EEG Signals
           Using Recurrent Neural Networks

    • Authors: M. Kalpana Chowdary, J. Anitha, D. Jude Hemanth
      First page: 2387
      Abstract: The application of electroencephalogram (EEG)-based emotion recognition (ER) to the brain–computer interface (BCI) has become increasingly popular over the past decade. Emotion recognition systems involve pre-processing and feature extraction, followed by classification. Deep learning has recently been used to classify emotions in BCI systems, and the results have been improved when compared to classic classification approaches. The main objective of this study is to classify the emotions from electroencephalogram signals using variant recurrent neural network architectures. Three architectures are used in this work for the recognition of emotions using EEG signals: RNN (recurrent neural network), LSTM (long short-term memory network), and GRU (gated recurrent unit). The efficiency of these networks, in terms of performance measures was confirmed by experimental data. The experiment was conducted by using the EEG Brain Wave Dataset: Feeling Emotions, and achieved an average accuracy of 95% for RNN, 97% for LSTM, and 96% for GRU for emotion detection problems.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152387
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2388: MobileUNetV3—A Combined UNet and
           MobileNetV3 Architecture for Spinal Cord Gray Matter Segmentation

    • Authors: Alhanouf Alsenan, Belgacem Ben Youssef, Haikel Alhichri
      First page: 2388
      Abstract: The inspection of gray matter (GM) tissue of the human spinal cord is a valuable tool for the diagnosis of a wide range of neurological disorders. Thus, the detection and segmentation of GM regions in magnetic resonance images (MRIs) is an important task when studying the spinal cord and its related medical conditions. This work proposes a new method for the segmentation of GM tissue in spinal cord MRIs based on deep convolutional neural network (CNNs) techniques. Our proposed method, called MobileUNetV3, has a UNet-like architecture, with the MobileNetV3 model being used as a pre-trained encoder. MobileNetV3 is light-weight and yields high accuracy compared with many other CNN architectures of similar size. It is composed of a series of blocks, which produce feature maps optimized using residual connections and squeeze-and-excitation modules. We carefully added a set of upsampling layers and skip connections to MobileNetV3 in order to build an effective UNet-like model for image segmentation. To illustrate the capabilities of the proposed method, we tested it on the spinal cord gray matter segmentation challenge dataset and compared it to a number of recent state-of-the-art methods. We obtained results that outperformed seven methods with respect to five evaluation metrics comprising the dice similarity coefficient (0.87), Jaccard index (0.78), sensitivity (87.20%), specificity (99.90%), and precision (87.96%). Based on these highly competitive results, MobileUNetV3 is an effective deep-learning model for the segmentation of GM MRIs in the spinal cord.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152388
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2389: MultiSec: A Multi-Protocol Security
           Forwarding Mechanism Based on Programmable Data Plane

    • Authors: Zeying Liu, Pengshuai Cui, Yongji Dong, Lei Xue, Yuxiang Hu
      First page: 2389
      Abstract: With the development of network technology, various network protocols different from TCP/IP have emerged. The heterogeneous integrated network has been proposed to realize the interconnection between heterogeneous networks running different protocols. However, current protocol conversion mechanisms often can only handle a few pre-defined protocols and do not support the flexible expansion of new protocols, which cannot meet the needs of the efficient convergence of different heterogeneous networks. Addirionally, due to the lack of security mechanisms, data in the core network is confronted with the risk of stealing and tampering. Our aim is to provide a protocol-extensible protocol conversion and secure transmission integration mechanism, MultiSec, for heterogeneous converged networks. First, based on the programmable data plane, the parser is reconfigured to realize multi-protocol parsing. Furthermore, the encryption mechanism implemented in the P4 extern is proposed and unified to the data plane together with the protocol conversion mechanism. Finally, the MultiSec prototype is implemented on a programmable software switch and accelerated by a dedicated encryption card. Experiments show that MultiSec successfully realizes multi-protocol conversion and data encryption, and the system performance is significantly improved with the help of an encryption card.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152389
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2390: Toward Understanding Most of the Context
           in Document-Level Neural Machine Translation

    • Authors: Gyu-Hyeon Choi, Jong-Hun Shin, Yo-Han Lee, Young-Kil Kim
      First page: 2390
      Abstract: Considerable research has been conducted to obtain translations that reflect contextual information in documents and simultaneous interpretations. Most of the existing studies use concatenation data which merge previous and current sentences for training translation models. Although this corpus improves the performance of the model, ignoring the contextual correlation between the sentences can disturb translation performance. In this study, we introduce a simple and effective method to capture the contextual correlation of the sentence at the document level of the current sentence, thereby learning an effective contextual representation. In addition, the proposed model structure is applied to a separate residual connection network to minimize the loss of the beneficial influence of incorporating the context. The experimental results show that our methods improve the translation performance in comparison with the state-of-the-art baseline of the Transformer in various translation tasks and two benchmark machine translation tasks.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152390
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2391: Leveraging Deep Features Enhance and
           Semantic-Preserving Hashing for Image Retrieval

    • Authors: Xusheng Zhao, Jinglei Liu
      First page: 2391
      Abstract: The hash method can convert high-dimensional data into simple binary code, which has the advantages of fast speed and small storage capacity in large-scale image retrieval and is gradually being favored by an increasing number of people. However, the traditional hash method has two common shortcomings, which affect the accuracy of image retrieval. First, most of the traditional hash methods extract many irrelevant image features, resulting in partial information bias in the binary code produced by the hash method. Furthermore, the binary code made by the traditional hash method cannot maintain the semantic similarity of the image. To find solutions to these two problems, we try a new network architecture that adds a feature enhancement layer to better extract image features, remove redundant features, and express the similarity between images through contrastive loss, thereby constructing compact exact binary code. In summary, we use the relationship between labels and image features to model them, better preserve the semantic relationship and reduce redundant features, and use a contrastive loss to compare the similarity between images, using a balance loss to produce the resulting binary code. The numbers of 0s and 1s are balanced, resulting in a more compact binary code. Extensive experiments on three commonly used datasets—CIFAR-10, NUS-WIDE, and SVHN—display that our approach (DFEH) can express good performance compared with the other most advanced approaches.
      Citation: Electronics
      PubDate: 2022-07-30
      DOI: 10.3390/electronics11152391
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2392: A Modified Active-Disturbance-Rejection
           Control with Sliding Modes for an Uncertain System by Using a Novel
           Reaching Law

    • Authors: Dong Zhang, Tao Wu, Shangyao Shi, Zhen Dong
      First page: 2392
      Abstract: This article presents a modified active-disturbance-rejection control (ADRC) combined with a sliding mode control (SMC) regarding the tracking control problems for plants with unmatched uncertainty. The proposed modified active-disturbance-rejection control with sliding mode (ADRC-SM) employs a reduced-order extended state observer (ESO) for estimating various uncertainties of system in time, including unmatched and matched uncertainties. Meanwhile, a novel reaching law of SMC was designed by using the cycloid function as the main controller of ADRC, which ensures the robustness of the uncertain system. Due to the reduced-order ESO tracking and compensating for various uncertainties in the system as a total disturbance, the upper bound of the disturbance in the SMC is relaxed. The gain coefficient of the reaching law only needs to be designed to be larger than the limit of the lumped disturbance; thus, the chattering problem is greatly reduced. The designed new reaching law of the cycloid function shortens the time for the system state’s convergence to the sliding mode’s surface. The cycloid function replaces the switching function in the traditional reaching law, making the actual control input continuous and shortening the approach time. Compared with traditional ADRC-SM, the use of multiple ESOs or intelligent algorithms to approximate plant parameters can be avoided, the design is simplified, its robustness is enhanced, computational costs are reduced, and the convergence time is reduced. The controlled object with unmatched uncertainty is transformed into a system with matched uncertainty using state-space transformation, which reduces the complexity of the controller’s design. In addition, the stability analysis of the closed-loop system is carried out based on the Lyapunov method. Simulations and experiments verify that the modified ADRC-SM has the merits of fast response, small overshoot, small steady-state error, strong anti-interference competence, and high control accuracy.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152392
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2393: Federated Split Learning Model for
           Industry 5.0: A Data Poisoning Defense for Edge Computing

    • Authors: Firoz Khan, R. Lakshmana Kumar, Mustufa Haider Abidi, Seifedine Kadry, Hisham Alkhalefah, Mohamed K. Aboudaif
      First page: 2393
      Abstract: Industry 5.0 provides resource-efficient solutions compared to Industry 4.0. Edge Computing (EC) allows data analysis on edge devices. Artificial intelligence (AI) has become the focus of interest in recent years, particularly in industrial applications. The coordination of AI at the edge will significantly improve industry performance. This paper integrates AI and EC for Industry 5.0 to defend against data poisoning attacks. A hostile user or node injects fictitious training data to distort the learned model in a data poisoning attack. This research provides an effective data poisoning defense strategy to increase the learning model’s performance. This paper developed a novel data poisoning defense federated split learning, DepoisoningFSL, for edge computing. First, a defense mechanism is proposed against data poisoning attacks. Second, the optimal parameters are determined for improving the performance of the federated split learning model. Finally, the performance of the proposed work is evaluated with a real-time dataset in terms of accuracy, correlation coefficient, mean absolute error, and root mean squared error. The experimental results show that DepoisoningFSL increases the performance accuracy.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152393
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2394: Multi-Agent Deep Reinforcement
           Learning-Based Partial Task Offloading and Resource Allocation in Edge
           Computing Environment

    • Authors: Hongchang Ke, Hui Wang, Hongbin Sun
      First page: 2394
      Abstract: In the dense data communication environment of 5G wireless networks, with the dramatic increase in the amount of request computation tasks generated by intelligent wireless mobile nodes, its computation ability cannot meet the requirements of low latency and high reliability. Mobile edge computing (MEC) can utilize its servers with mighty computation power and closer to tackle the computation tasks offloaded by the wireless node (WN). The physical location of the MEC server is closer to WN, thereby meeting the requirements of low latency and high reliability. In this paper, we implement an MEC framework with multiple WNs and multiple MEC servers, which consider the randomness and divisibility of arrival request tasks from WN, the time-varying channel state between WN and MEC server, and different priorities of tasks. In the proposed MEC system, we present a decentralized multi-agent deep reinforcement learning-based partial task offloading and resource allocation algorithm (DeMADRL) to minimize the long-term weighted cost including delay cost and bandwidth cost. DeMADRL is a model-free scheme based on Double Deep Q-Learning (DDQN) and can obtain the optimal computation offloading and bandwidth allocation decision-making policy by training the neural networks. The comprehensive simulation results show that the proposed DeMADRL optimization scheme has a nice convergence and outperforms the other three baseline algorithms.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152394
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2395: Characteristic Mode Analysis of a
           Ka-Band CPW-Slot-Couple Fed Patch Antenna with Enhanced Bandwidth and Gain
           

    • Authors: Kun Deng, Fuxing Yang, Jiali Zhou, Chengqi Lai, Yucheng Wang, Ke Han
      First page: 2395
      Abstract: A Ka-band CPW-Slot-Couple (CSC) fed microstrip antenna with enhanced bandwidth and gain is presented in this paper. To simplify the feed network, the matching slots are designed at the end of the CPW. Consequently, the patch antenna is designed with a low profile, which has a size of 7.2 × 32.6 × 0.508 mm3. Characteristic mode analysis (CMA) is applied to illustrate the principle of the enhancement of the band with the form characteristic mode point of view. A slot based on inductive loading is employed on the parasitic patch to move the resonant frequency of CM3 to the resonant frequency of CM2 for enhanced bandwidth, which avoids introducing additional impedance matching networks. The measured results show that the bandwidth of the proposed monolayer antenna is 14.18% from 24.84 to 28.6 GHz and the peak gain is 7.9 dBi. Due to its attractive properties of low profile, compact configuration, wide band, and high gain, the proposed antenna could be applied to miniaturized millimeter-wave applications.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152395
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2396: A Hierarchical Random Graph Efficient
           Sampling Algorithm Based on Improved MCMC Algorithm

    • Authors: Zhixin Tie, Dingkai Zhu, Shunhe Hong, Hui Xu
      First page: 2396
      Abstract: A hierarchical random graph (HRG) model combined with a maximum likelihood approach and a Markov Chain Monte Carlo algorithm can not only be used to quantitatively describe the hierarchical organization of many real networks, but also can predict missing connections in partly known networks with high accuracy. However, the computational cost is very large when hierarchical random graphs are sampled by the Markov Chain Monte Carlo algorithm (MCMC), so that the hierarchical random graphs, which can describe the characteristics of network structure, cannot be found in a reasonable time range. This seriously limits the practicability of the model. In order to overcome this defect, an improved MCMC algorithm called two-state transitions MCMC (TST-MCMC) for efficiently sampling hierarchical random graphs is proposed in this paper. On the Markov chain composed of all possible hierarchical random graphs, TST-MCMC can generate two candidate state variables during state transition and introduce a competition mechanism to filter out the worse of the two candidate state variables. In addition, the detailed balance of Markov chain can be ensured by using Metropolis–Hastings rule. By using this method, not only can the convergence speed of Markov chain be improved, but the convergence interval of Markov chain can be narrowed as well. Three example networks are employed to verify the performance of the proposed algorithm. Experimental results show that our algorithm is more feasible and more effective than the compared schemes.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152396
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2397: Anti-Jamming Path Selection Method in a
           Wireless Communication Network Based on Dyna-Q

    • Authors: Guoliang Zhang, Yonggui Li, Yingtao Niu, Quan Zhou
      First page: 2397
      Abstract: Aiming at efficiently establishing the optimal transmission path in a wireless communication network in a malicious jamming environment, this paper proposes an anti-jamming algorithm based on Dyna-Q. Based on previous observations of the environment, the algorithm selects the optimal sequential node by searching the Q table to reduce the packet loss rate. The algorithm can accelerate the updating of the Q table based on previous experience. The Q table converges to the optimal value quickly. This is beneficial for the optimal selection of subsequent nodes. Simulation results show that the proposed algorithm has the advantage of faster convergence speed compared with the model-free reinforcement learning algorithm.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152397
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2398: Design of High−Power
           Solid−State Transformers with Grain−Oriented Electrical Steel
           Cores

    • Authors: Daniel Roger, Ewa Napieralska, Krzysztof Komeza, Piotr Napieralski
      First page: 2398
      Abstract: The paper proposes a simple structure of high−power solid−state transformers (SSTs) able to control the energy flow in critical lines of the medium−voltage (20 kV) distribution grid. With an increasing number of renewable intermittent sources connected at the nodes of the meshed distribution grid and a reduced number of nodes connected to large power plants, the distribution grid stability is more and more difficult to achieve. Control of the energy flow in critical lines can improve the stability of the distribution grid. This control can be provided by the proposed high−power SSTs operating a 20 kV with powers over 10 MW. This function is difficult to achieve with standard SST technologies that operate at high frequencies. These devices are made with expensive magnetic materials (amorphous or nanocrystalline cores) and a limited power by SST cells. The required total power is reached by assembling many SST cells. On the other hand, existing SST designs are mainly aimed at reducing the equipment’s size and it is difficult to design small objects able to operate at high voltages. The authors propose to use cores made with grain−oriented electrical steel (GOES) thin strips assembled in wound cores. Experimental results obtained, with GOES wound cores, show that the core losses are lower for a square voltage than for a sine one. This counterintuitive result is explained with an analytical calculus of eddy currents and confirmed by a non−linear time−stepping simulation. Therefore, simple converter structures, operating with rectangular voltages and low switching losses, are the best solutions. Experimental results also show that the core losses decrease with temperature. Consequently, high−power SST cells can be made with transformers whose GOES cores are hotter than coils for reducing core losses and keeping copper losses at low levels. The paper proposes an appropriate transformer mechanical structure that avoids any contact between the hot GOES wound core and the winding, with a specific cooling system and thermal insulation of the hot GOES wound core. The proposed design makes it possible to build SST cells over 1MW and full SSTs over 10 MW at moderate costs.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152398
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2399: High-Level Design Optimizations for
           Implementing Data Stream Sketch Frequency Estimators on FPGAs

    • Authors: Ali Ebrahim
      First page: 2399
      Abstract: This paper presents simple yet effective optimizations for implementing data stream frequency estimation sketch kernels using High-Level Synthesis (HLS). The paper addresses design issues common to sketches utilizing large portions of the embedded RAM resources in a Field Programmable Gate Array (FPGA). First, a solution based on Load-Store Queue (LSQ) architecture is proposed for resolving the memory dependencies associated with the hash tables in a frequency estimation sketch. Second, performance fine-tuning through high-level pragmas is explored to achieve the best possible throughput. Finally, a technique based on pre-processing the data stream in a small cache memory prior to updating the sketch is evaluated to reduce the dynamic power consumption. Using an Intel HLS compiler, a proposed optimized hardware version of the popular Count-Min sketch utilizing 80% of the embedded RAM in an Intel Arria 10 FPGA, achieved more than 3x the throughput of an unoptimized baseline implementation. Furthermore, the sketch update rate is significantly reduced when the input stream is skewed. This, in turn, minimizes the effect of high throughput on dynamic power consumption. Compared to FPGA sketches in the published literature, the presented sketch is the most well-rounded sketch in terms of features and versatility. In terms of throughput, the presented sketch is on a par with the fastest sketches fine-tuned at the Register Transfer Level (RTL).
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152399
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2400: A Deep Learning Method Based on the
           Attention Mechanism for Hardware Trojan Detection

    • Authors: Wenjing Tang, Jing Su, Jiaji He, Yuchan Gao
      First page: 2400
      Abstract: The chip manufacturing of integrated circuits requires the participation of multiple parties, which greatly increases the possibility of hardware Trojan insertion and poses a significant threat to the entire hardware device landing; however, traditional hardware Trojan detection methods require gold chips, so the detection cost is relatively high. The attention mechanism can extract data with more adequate features, which can enhance the expressiveness of the network. This paper combines an attention module with a multilayer perceptron and convolutional neural network for hardware Trojan detection based on side-channel information, and evaluates the detection results by implementing specific experiments. The results show that the proposed method significantly outperforms machine learning classification methods and network-related methods, such as SVM and KNN, in terms of accuracy, precision, recall, and F1 value. In addition, the proposed method is effective in detecting data containing one or multiple hardware Trojans, and shows high sensitivity to the size of datasets.
      Citation: Electronics
      PubDate: 2022-07-31
      DOI: 10.3390/electronics11152400
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2401: Recent Progress in Fabrication and
           Physical Properties of 2D TMDC-Based Multilayered Vertical
           Heterostructures

    • Authors: Qiuran Lv, Fei Chen, Yuan Xia, Weitao Su
      First page: 2401
      Abstract: Two-dimensional (2D) vertical heterojunctions (HSs), which are usually fabricated by vertically stacking two layers of transition metal dichalcogenide (TMDC), have been intensively researched during the past years. However, it is still an enormous challenge to achieve controllable preparation of the TMDC trilayer or multilayered van der Waals (vdWs) HSs, which have important effects on physical properties and device performance. In this review, we will introduce fundamental features and various fabrication methods of diverse TMDC-based multilayered vdWs HSs. This review focuses on four fabrication methods of TMDC-based multilayered vdWs HSs, such as exfoliation, chemical vapor deposition (CVD), metal-organic chemical vapor deposition (MOCVD), and pulsed laser deposition (PLD). The latest progress in vdWs HS-related novel physical phenomena are summarized, including interlayer excitons, long photocarrier lifetimes, upconversion photoluminescence, and improved photoelectrochemical catalysis. At last, current challenges and prospects in this research field are provided.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152401
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2402: Evolution of Bioamplifiers: From Vacuum
           Tubes to Highly Integrated Analog Front-Ends

    • Authors: Aleksei A. Anisimov, Alexander V. Belov, Timofei V. Sergeev, Elizaveta E. Sannikova, Oleg A. Markelov
      First page: 2402
      Abstract: The past century has seen the ongoing development of amplifiers for different electrophysiological signals to study the work of the heart. Since the vacuum tube era, engineers and designers of bioamplifiers for recording electrophysiological signals have been trying to achieve similar objectives: increasing the input impedance and common-mode rejection ratio, as well as reducing power consumption and the size of the bioamplifier. This review traces the evolution of bioamplifiers, starting from circuits on vacuum tubes and discrete transistors through circuits on operational and instrumental amplifiers, and to combined analog-digital solutions on analog front-end integrated circuits. Examples of circuits and their technical features are provided for each stage of the bioamplifier development. Special emphasis is placed on the review of modern analog front-end solutions for biopotential registration, including their generalized structural diagram and table of comparative characteristics. A detailed review of analog front-end circuit integration in various practical applications is provided, with examples of the latest achievements in the field of electrocardiogram, electroencephalogram, and electromyogram registration. The review concludes with key points and insights for the future development of the analog front-end concept applied to bioelectric signal registration.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152402
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2403: A Novel Distributed Ledger Technology
           Structure for Wireless Sensor Networks Based on IOTA Tangle

    • Authors: Hongwei Zhang, Marzia Zaman, Brian Stacey, Srinivas Sampalli
      First page: 2403
      Abstract: Wireless Sensor Networks (WSNs) consist of many wireless sensor nodes for collecting and sensing information. Distributed Ledger Technologies (DLTs) such as Blockchain allow organizations to store and share data in a decentralized, immutable, and secure way through a network of distributed peer-to-peer users or computers. The application of DLT to the Internet of Things (IoT) can improve the efficiency of information transmission and network security. IOTA Tangle is a DLT developed for IoT to process transactions. WSN is a core technology for IoT, and the two have a lot in common in terms of applications. Many solutions for IoT applications can be implemented with WSNs. However, the sensor nodes in WSNs have limited processing speed, storage capacity, communication bandwidth, and energy consumption capabilities. Therefore, a lightweight solution needs to be designed according to the characteristics of WSNs, rather than directly applying Tangle. The similarities between IoT and WSNs determine that the Tangle can be an essential reference for designing new solutions. In this paper, we propose a new DLT structure based on Tangle named Fishing Net Topology (FNT). The aim is to meet the lightweight requirements of sensor nodes in WSNs. We compared FNT with Tangle in terms of the packet network structure and algorithm and also experimentally analyzed the waste rate in the FNT network. It is concluded that FNT can be used at a reasonable Rate based on the requirement of the WSN applications, and it can significantly reduce the computation while enhancing the security of WSNs. Due to its structural stability and algorithmic simplicity, FNT outperforms Tangle in WSNs.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152403
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2404: A Fast Automatic Reconstruction Method
           for Panoramic Images Based on Cone Beam Computed Tomography

    • Authors: Jianguo Zhang, Yichuan Jiang, Fei Gao, Sheng Zhao, Fan Yang, Liang Song
      First page: 2404
      Abstract: Panoramic images have been widely used in the diagnosis of dental diseases. In the process of panoramic image reconstruction, the position of the dental arch curve usually affects the quality of display content, especially the completion level of the panoramic image. In addition, the metal implants in the patient’s mouth often lead the contrast of the panoramic image to decrease. This paper describes a method to automatically synthesize panoramic images from dental cone beam computed tomography (CBCT) data. The proposed method has two essential features: the first feature is that the method can detect the dental arch curve through axial maximum intensity projection images over different ranges, and the second feature is that our method is able to adjust the intensity distribution of the implant in critical areas, to reduce the impact of the implant on the contrast of the panoramic image. The proposed method was tested on 50 CBCT datasets; the panoramic images generated by this method were compared with images attained from three other commonly used approaches and then subjectively scored by three experienced dentists. In the comprehensive image contrast score, the method in this paper has the highest score of 11.16 ± 2.64 points. The results show that the panoramic images generated by this method have better image contrast.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152404
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2405: Research on Fingerprint and Hyperbolic
           Fusion Positioning Algorithm Based on 5G Technology

    • Authors: Zhiqiang Geng, Jie Yang, Zhiqiang Guo, Hui Cao, Lilian Leonidas
      First page: 2405
      Abstract: With the development of the Internet of Things technology, higher requirements are put forward for the positioning accuracy of objects. This paper presents an indoor fusion positioning algorithm based on the 5th Generation Mobile Communication Technology (5G), which effectively solves two problems. The first is that fingerprint positioning is susceptible to environmental changes and results in inaccurate fingerprint matching. The second is the problem of the hyperbolic positioning algorithm based on the line-of-sight fluctuating too much in complex indoor environments. This paper uses a 5G flexible subcarrier interval of Orthogonal Frequency Division Multiplexing (OFDM) to significantly reduce the time delay error of Time Of Arrival (TOA), and an improved genetic algorithm and the weighted hyperbolic algorithm are used to estimate the optimal position coordinates. In the offline database establishment stage of fingerprint positioning, the Channel State Information-reference signal (CSI-RS) of multiple-beam sets provides high-dimensional information for subsequent training and prediction. The online stage cooperates with the improved residual network model to make predictions. Finally, the positioning information and the error distribution function generated by the two positioning processes are simultaneously used as the input of the Kalman filter to obtain the precise position coordinates. The simulation results show that in complex indoor scenes where line-of-sight propagation and non-line-of-sight propagation paths are mixed, the accuracy of this method can reach below 0.82 m. Thus, the positioning accuracy is significantly improved compared with other methods, which can meet most indoor scene positioning needs.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152405
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2406: Generalized Carrier Index Differential
           

    • Authors: Mengxuan Zhang, Guixian Cheng, Bohan Yang, Cheng Yang
      First page: 2406
      Abstract: A generalized carrier index differential chaos shift keying with simultaneous wireless information and power transfer (GCI-DCSK SWIPT) scheme, is proposed, which is an improved scheme for CI-DCSK SWIPT. Compared to CI-DCSK SWIPT, GCI-DCSK SWIPT is not only more flexible in selecting both index bit number and index carrier number, but also is more practical for considering both path loss and the conversion noise generated by radio frequency (RF) band to baseband. The proposed scheme applied a time-switching manner to harvest the energy carried by the inactive carriers. Theoretical bit error rate (BER) expressions of the scheme over AWGN and multipath Rayleigh fading channels are derived, and the ratio of harvested energy to transmitted energy is derived to desecribe the probability of self-sufficiency on power supply. In addition, the frame-derived factor and the energy carried by inactive carriers are optimized to obtain better BER performance. Simulation results show that taking both path loss and conversion noise into consideration, the scheme is still self-sufficient with good BER performance. Furthermore, by adjusting the number of active carriers of GCI-DCSK SWIPT, some cases of GCI-DCSK SWIPT outperform conversion noise-aware CI-DCSK SWIPT in BER.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152406
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2407: Planning Collision-Free Robot Motions in
           a Human–Robot Shared Workspace via Mixed Reality and Sensor-Fusion
           Skeleton Tracking

    • Authors: Saverio Farsoni, Jacopo Rizzi, Giulia Nenna Ufondu, Marcello Bonfè
      First page: 2407
      Abstract: The paper describes a method for planning collision-free motions of an industrial manipulator that shares the workspace with human operators during a human–robot collaborative application with strict safety requirements. The proposed workflow exploits the advantages of mixed reality to insert real entities into a virtual scene, wherein the robot control command is computed and validated by simulating robot motions without risks for the human. The proposed motion planner relies on a sensor-fusion algorithm that improves the 3D perception of the humans inside the robot workspace. Such an algorithm merges the estimations of the pose of the human bones reconstructed by means of a pointcloud-based skeleton tracking algorithm with the orientation data acquired from wearable inertial measurement units (IMUs) supposed to be fixed to the human bones. The algorithm provides a final reconstruction of the position and of the orientation of the human bones that can be used to include the human in the virtual simulation of the robotic workcell. A dynamic motion-planning algorithm can be processed within such a mixed-reality environment, allowing the computation of a collision-free joint velocity command for the real robot.
      Citation: Electronics
      PubDate: 2022-08-01
      DOI: 10.3390/electronics11152407
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2408: A Computational Tool for Detection of
           Soft Tissue Landmarks and Cephalometric Analysis

    • Authors: Mohammad Azad, Said Elaiwat, Mohammad Khursheed Alam
      First page: 2408
      Abstract: In facial aesthetics, soft tissue landmark recognition and linear and angular measurement play a critical role in treatment planning. Visual identification and judgment by hand are time-consuming and prone to errors. As a result, user-friendly software solutions are required to assist healthcare practitioners in improving treatment planning. Our first goal in this paper is to create a computational tool that may be used to identify and save critical landmarks from patient X-ray pictures. The second goal is to create automated software that can assess the soft tissue facial profiles of patients in both linear and angular directions using the landmarks that have been identified. To boost the contrast, we employ gamma correction and a client-server web-based model to display the input images. Furthermore, we use the client-side to record landmarks in pictures and save the annotated landmarks to the database. The linear and angular measurements from the recorded landmarks are then calculated computationally and displayed to the user. Annotation and validation of 13 soft tissue landmarks were completed. The results reveal that our software accurately locates landmarks with a maximum deviation of 1.5 mm to 5 mm for the majority of landmarks. Furthermore, the linear and angular measurement variances across users are not large, indicating that the procedure is reliable.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152408
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2409: A Formulation of the Log-Logistic
           Distribution for Fading Channel Modeling

    • Authors: Iván Sánchez, Francisco Javier López-Martínez
      First page: 2409
      Abstract: In some scenarios, the log-logistic (LL) distribution is shown to provide the best fit to field measurements in the context of wireless channel modeling. However, a fading channel model based on the LL distribution has not been formulated yet. In this work, we introduce the L-distribution as a reformulation of the LL distribution for channel modeling purposes. We provide closed-form expressions for its PDF, CDF, and moments. Performance analysis of wireless communication systems operating under L-fading channels is exemplified, providing exact and asymptotic expressions for relevant metrics such as the outage probability and the average capacity. Finally, important practical aspects related to the use of the L-distribution for channel fitting purposes are discussed in two contexts: (i) millimeter-wave links with misaligned gain, and (ii) air–ground channels in unmanned aerial vehicle communications.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152409
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2410: FPGA-Based Hardware Accelerator on
           Portable Equipment for EEG Signal Patterns Recognition

    • Authors: Yu Xie, Tamás Majoros, Stefan Oniga
      First page: 2410
      Abstract: Electroencephalogram (EEG) is a recording of comprehensive reflection of physiological brain activities. Because of many reasons, however, including noises of heartbeat artifacts and muscular movements, there are complex challenges for efficient EEG signal classification. The Convolutional Neural Networks (CNN) is considered a promising tool for extracting data features. A deep neural network can detect the deeper-level features with a multilayer through nonlinear mapping. However, there are few viable deep learning algorithms applied to BCI systems. This study proposes a more effective acquisition and processing HW-SW method for EEG biosignal. First, we use a consumer-grade EEG acquisition device to record EEG signals. Short-time Fourier transform (STFT) and Continuous Wavelet Transform (CWT) methods will be used for data preprocessing. Compared with other algorithms, the CWT-CNN algorithm shows a better classification accuracy. The research result shows that the best classification accuracy of the CWT-CNN algorithm is 91.65%. On the other side, CNN inference requires many convolution operations. We further propose a lightweight CNN inference hardware accelerator framework to speed up inference calculation, and we verify and evaluate its performance. The proposed framework performs network tasks quickly and precisely while using less logical resources on the PYNQ-Z2 FPGA development board.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152410
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2411: Small-Size Algorithms for the Type-I
           Discrete Cosine Transform with Reduced Complexity

    • Authors: Miłosz Kolenderski, Aleksandr Cariow
      First page: 2411
      Abstract: Discrete cosine transforms (DCTs) are widely used in intelligent electronic systems for data storage, processing, and transmission. The popularity of using these transformations, on the one hand, is explained by their unique properties and, on the other hand, by the availability of fast algorithms that minimize the computational and hardware complexity of their implementation. The type-I DCT has so far been perhaps the least popular, and there have been practically no publications on fast algorithms for its implementation. However, at present the situation has changed; therefore, the development of effective methods for implementing this type of DCT becomes an urgent task. This article proposes several algorithmic solutions for implementing type-I DCTs. A set of type-I DCT algorithms for small lengths N=2,3,4,5,6,7,8 is presented. The effectiveness of the proposed solutions is due to the possibility of fortunate factorization of the small-size DCT-I matrices, which reduces the complexity of implementing transformations of this type.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152411
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2412: Practical Performance Analyses of 5G
           Sharing Voice Solution

    • Authors: Xiao Li, Mingshuo Wei, Weiliang Xie
      First page: 2412
      Abstract: Sharing network infrastructure is carried out by a few network operators in the world and is regarded as an effective means to accelerate the commercial 5G with seamless coverage and user experience guarantees but significantly reduced investment. Voice via IMS has been defined as the voice-bearing solution from 3rd-Generation Partnership Project (3GPP) Release 5. Release 15 pointed out that 5G still adopts the IMS-based voice service architecture. In such a background, and in the process of global 5G network evolution from non-stand-alone (NSA) to stand-alone (SA), how to bear 5G voice services in the sharing network infrastructure has quite a few technical options. This paper investigates the 5G access network sharing technical solutions and presents the voice bearer technology under different new radio (NR) evolution stages. Analysis was performed for the different stages of voice handover. Performance results from field tests are provided to verify the feasibility of the solution, and performance analysis such as end-to-end call setup delay was also carried out. From the theoretical and practical analysis, the voice over long-term evolution (VoLTE) non-back-to-home solution has a relatively short access delay in the NSA sharing stage; EPS fallback based on either handover or redirection introduces a large time delay, so EPS fallback can only be used as a transition solution in the early stage of SA sharing deployment; voice over new radio (VoNR) has the lowest access time delay and the simplest implementation solution, so it is the final voice solution for 5G SA sharing network. The comparison of different voice-bearing solutions in different network development stages provides a reference for countries around the world.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152412
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2413: Seamless Capable PV Power Generation
           System without Battery Storage for Rural Residential Load

    • Authors: Mukul Chankaya, Ikhlaq Hussain, Hasmat Malik, Aijaz Ahmad, Majed A. Alotaibi, Fausto Pedro García Márquez
      First page: 2413
      Abstract: The presented system is a three-phase three-wire (3P–3W), seamless, capable, dual-stage PV power generation system without battery storage for rural residential loads to ensure a continuous power supply during the daytime. This system effortlessly shifts from the grid-connected (GC) mode to the standalone (SA) mode when the grid utility is unavailable. During the GC mode, a voltage source converter (VSC) is regulated by the polynomial zero-attracting least mean square (PZA-LMS) algorithm-based current control scheme. During the GC mode, the power balance is achieved at the point of common coupling (PCC) by exchanging active power with the grid, whereas the VSC delivers reactive power. Considering the low efficiency of PV power generation systems, an incremental conductance (InC)-based maximum power point tracking (MPPT) algorithm is necessary for the maximum power extraction out of a PV array. During the unavailability of the grid, the presented system operates in the SA mode, when the load is delivered with PV power only via VSC. Considering the high cost of the battery storage system (BSS), bi-directional converter, and charge control circuitry incurred by rural consumers, they were omitted from the system. Without a BSS, the InC-based MPPT is executed in the derated mode, extracting the PV power to exactly match the load demand. Without derated PV power generation operation, the load may be damaged due to excess PV power flow to the load end or the load may remain underpowered, leading to load shedding or complete disconnection. A synchronous reference frame (SRF)-based voltage control scheme is responsible for the VSC control during the SA operation of the system. The presented system performance was observed and found satisfactory during the irradiation variation, load balancing, islanding, and re-synchronization of the grid. The presented system was found to carry out harmonics suppression and active and reactive power balance at the PCC during both the GC and SA modes. The grid’s total harmonics distortion (THD) levels were shown to be kept below 5% as per the IEEE 519 standard in the GC mode.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152413
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2414: N-Versions-Based Resilient Traffic
           Control Systems

    • Authors: Abdullah Basuhail, Maher Khemakhem, Fathy Elbouraey Eassa, Junaid Mohammad Qurashi, Kamal Jambi
      First page: 2414
      Abstract: Increasing the resilience of traffic control systems is a priority for many important cities worldwide. This is due to the ever-increasing problems leading to different failures in such systems. We are witnessing the intensive introduction of new technologies that automatically manage traffic but are exposed to different kinds of attacks. There are also unpredictable increases in climatic changes and the number of cars in many cities. These factors will surely enhance the failure risks of such systems and consequently increase the damage caused by traffic jams and road accidents. In this paper, we introduce a resilient traffic control system that consists of three levels: sensor control, display, and light control. Each level has three (or more) versions and a dynamic voter. Hence, the introduced system is based on diversity and redundancy (replication), called N-versions. We propose two techniques for the introduced resilient traffic control system. The first technique uses N-versions and dynamic voters to vote between the outcomes in each level. The second technique uses N-versions, dynamic voters, and acceptance testing units. The overhead in the second technique is evidently greater than that of the first technique, but its resilience is better. A fine analytical study is conducted and shows that the first technique requires only three versions to reach the optimal results, bounded by 1/15 probability of having a faulty system. The second technique leads to better results, which can determine small probabilities.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152414
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2415: A Novel, Blind, Wideband Spectrum
           Detection under Non-Flat Spectrum and Fading Scenarios

    • Authors: Peng Shang, Decai Zou, Xue Wang, Ziyue Chu
      First page: 2415
      Abstract: In the field of radio surveillance and cognitive radio, the reception of a signal is usually made in a non-cooperative manner, which means there exists little prior information to detect the signals reliably via a traditional method. At the same time, the prevalent wideband acquisition mode will receive multiple subband signals from homogeneous or heterogeneous systems, leading to deteriorated detection performance under a non-flat spectrum and fading channel. In view of the above concerns, a novel detection algorithm based on the Gaussian hidden Markov model (HMM) is proposed so as to separate the individual sub-band signal from the wideband spectrum accurately in a low signal-to-noise ratio (SNR). The simulated communication signals with spectral fluctuation and multipath fading indicate the superiority and applicability of the proposed algorithm as compared with other detection algorithms. Our algorithm can achieve a 94% detection probability at -10 dB SNR under an additive white Gaussian noise (AWGN) channel and has a nearly ideal receiver operating characteristic (ROC) curve. When faced with a Rayleigh fading channel, it still outperforms other algorithms. The acquired real data also very its practical application with moderate computation complexity and a more stable carrier-frequency estimation.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152415
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2416: An Overview of Systolic Arrays for
           Forward and Inverse Discrete Sine Transforms and Their Exploitation in
           View of an Improved Approach

    • Authors: Doru Florin Chiper, Arcadie Cracan, Vasilica-Daniela Andries
      First page: 2416
      Abstract: This paper aims to present a unified overview of the main Very Large-Scale Integration (VLSI) implementation solutions of forward and inverse discrete sine transforms using systolic arrays. The main features of the most important solutions to implement the forward and inverse discrete sine transform (DST) using systolic arrays are presented. One of the central ideas presented in the paper is to emphasize the advantages of using regular and modular systolic array computational structures such as cyclic convolution, circular correlation, and pseudo-band correlation in the VLSI implementation of these transforms. The use of such computational structures leads to architectures well adapted to the features of VLSI technologies, with an efficient use of the hardware structures and a reduced I/O cost that helps avoiding the so-called I/O bottleneck. With the techniques presented in this review, we have developed a new VLSI implementation of the DST using systolic arrays that allow efficient hardware implementation with reduced complexity while maintaining high-speed performances. Using a new restructuring input sequence, we have been able to efficiently reformulate the computation of the forward DST transform into a special computational structure using eight short quasi-cycle convolutions that can be computed with low complexity and where some of the coefficients are identical. This leads to a hardware structure with high throughput. The new restructuring sequence is the use of the input samples in a natural order as opposed to previous solutions, leading to a significant reduction of the hardware complexity in the pre-processing stage due to avoiding a permutation stage to reverse the order. Moreover, the proposed VLSI architecture allows an efficient incorporation of the obfuscation technique with very low overheads.
      Citation: Electronics
      PubDate: 2022-08-02
      DOI: 10.3390/electronics11152416
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2417: Evaluating Intelligent Methods for
           Detecting COVID-19 Fake News on Social Media Platforms

    • Authors: Hosam Alhakami, Wajdi Alhakami, Abdullah Baz, Mohd Faizan, Mohd Waris Khan, Alka Agrawal
      First page: 2417
      Abstract: The advent of Internet-based technology has made daily life much easy than earlier days. The exponential rise in the popularity of social media platforms has not only connected people from faraway places, but has also increased communication among humans. However, in several instances, social media platforms have also been utilized for unethical and criminal activities. The propagation of fake news on social media during the ongoing COVID-19 pandemic has deteriorated the mental and physical health of people. Therefore, to control the flow of fake news regarding the novel coronavirus, several studies have been undertaken to automatically detect the fake news about COVID-19 using various intelligent techniques. However, different studies have shown different results on the performance of the predicting models. In this paper, we have evaluated several machine learning and deep learning models for the automatic detection of fake news regarding COVID-19. The experiments were carried out on two publicly available datasets, and the results were assessed using several evaluation metrics. The traditional machine learning models produced better results than the deep learning models in predicting fake news.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152417
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2418: Chinese Spam Detection Using a Hybrid
           BiGRU-CNN Network with Joint Textual and Phonetic Embedding

    • Authors: Jinliang Yao, Chenrui Wang, Chuang Hu, Xiaoxi Huang
      First page: 2418
      Abstract: The proliferation of spam in China has a negative impact on internet users’ experiences online. Existing methods for detecting spam are primarily based on machine learning. However, it has been discovered that these methods are susceptible to adversarial textual spam that has frequently been imperceptibly modified by spammers. Spammers continually modify their strategies to circumvent spam detection systems. Text with Chinese homophonic substitution may be easily understood by users according to its context. Currently, spammers widely use homophonic substitution to break down spam identification systems on the internet. To address these issues, we propose a Bidirectional Gated Recurrent Unit (BiGRU)–Text Convolutional Neural Network (TextCNN) hybrid model with joint embedding for detecting Chinese spam. Our model effectively uses phonetic information and combines the advantages of parameter sharing from TextCNN with long-term memory from BiGRU. The experimental results on real-world datasets show that our model resists homophone noise to some extent and outperforms mainstream deep learning models. We also demonstrate the generality of joint textual and phonetic embedding, which is applicable to other deep learning networks in Chinese spam detection tasks.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152418
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2419: Understanding and Controlling Band
           Alignment at the Metal/Germanium Interface for Future Electric Devices

    • Authors: Tomonori Nishimura
      First page: 2419
      Abstract: Germanium (Ge) is a promising semiconductor as an alternative channel material to enhance performance in scaled silicon (Si) field-effect transistor (FET) devices. The gate stack of Ge FETs has been much improved based on extensive research thus far, demonstrating that the performance of Ge FETs is much superior to that of Si FETs in terms of the on-state current. However, to suppress the performance degradation due to parasitic contact resistance at the metal/Ge interface in advanced nodes, the reduction of the Schottky barrier height (SBH) at the metal/Ge interface is indispensable, yet the SBH at the common metal/Ge interface is difficult to control by the work function of metal due to strong Fermi level pinning (FLP) close to the valence band edge of Ge. However, the strong FLP could be alleviated by an ultrathin interface layer or a low free-electron-density metal, which makes it possible to lower the SBH for the conduction band edge of Ge to less than 0.3 eV. The FLP alleviation is reasonably understandable by weakening the intrinsic metal-induced gap states at the metal/Ge interface and might be a key solution for designing scaled Ge n-FETs.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152419
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2420: A Flexible Semantic Ontological Model
           Framework and Its Application to Robotic Navigation in Large Dynamic
           Environments

    • Authors: Sunghyeon Joo, Sanghyeon Bae, Junhyeon Choi, Hyunjin Park, Sangwook Lee, Sujeong You, Taeyoung Uhm, Jiyoun Moon, Taeyong Kuc
      First page: 2420
      Abstract: Advanced research in robotics has allowed robots to navigate diverse environments autonomously. However, conducting complex tasks while handling unpredictable circumstances is still challenging for robots. The robots should plan the task by understanding the working environments beyond metric information and need countermeasures against various situations. In this paper, we propose a semantic navigation framework based on a Triplet Ontological Semantic Model (TOSM) to manage various conditions affecting the execution of tasks. The framework allows robots with different kinematics to perform tasks in indoor and outdoor environments. We define the TOSM-based semantic knowledge and generate a semantic map for the domains. The robots execute tasks according to their characteristics by converting inferred knowledge to Planning Domain Definition Language (PDDL). Additionally, to make the framework sustainable, we determine a policy of maintaining the map and re-planning when in unexpected situations. The various experiments on four different kinds of robots and four scenarios validate the scalability and reliability of the proposed framework.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152420
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2421: A Novel MPPT Algorithm for Photovoltaic
           Systems Based on Improved Sliding Mode Control

    • Authors: Yan Zhang, Ya-Jun Wang, Jia-Qi Yu
      First page: 2421
      Abstract: Due to the poor tracking performance and significant chattering of traditional sliding mode control in the maximum power point tracking (MPPT) algorithm, a novel MPPT algorithm based on sliding mode control for photovoltaic systems is proposed in this paper. The sliding mode control structure and new sliding mode surface of the multi-power reaching law are designed with the boost converter as the carrier of the photovoltaic system, and the sigmoid function is proposed to replace the symbolic function and saturation function in the power reaching law to improve the reaching rate and control quality of the traditional sliding mode control. Furthermore, the Liapunov function is employed to analyze the accessibility, existence and stability of the improved sliding mode control. Simulation results under dynamic and partial shading conditions show that compared with exponential sliding mode and constant speed sliding mode, the improved sliding mode control strategy can quickly track the maximum power point of photovoltaic systems under various atmospheric conditions. The proposed MPPT algorithm has stronger robustness and universality. Additionally, the efficiency of the proposed algorithm is improved by 2.3% and 5.6% as compared to the exponential sliding model control algorithm and constant velocity sliding model control algorithm. In addition, the experimental platform is constructed to further validate the feasibility and effectiveness of the proposed algorithm.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152421
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2422: Sound Based Fault Diagnosis Method Based
           on Variational Mode Decomposition and Support Vector Machine

    • Authors: Xiaojing Yin, Qiangqiang He, Hao Zhang, Ziran Qin, Bangcheng Zhang
      First page: 2422
      Abstract: In industry, it is difficult to obtain data for monitoring equipment operation, as mechanical and electrical components tend to be complicated in nature. Considering the contactless and convenient acquisition of sound signals, a method based on variational mode decomposition and support vector machine via sound signals is proposed to accurately perform fault diagnoses. Firstly, variational mode decomposition is conducted to obtain intrinsic mode functions. The fisher criterion and canonical discriminant function are applied to overcome the fault diagnosis accuracy decline caused by intrinsic mode functions with multiple features. Then, the fault features obtained from these intrinsic mode functions are chosen as the final fault features. Experiments on a car folding rearview mirror based on sound signals were used to verify the superiority and feasibility of the proposed method. To further verify the superiority of the proposed model, these final fault features were taken as the input to the following classifiers to identify fault categories: support vector machine, k-nearest neighbors, and decision tree. The model support vector machine achieved an accuracy of 95.8%, i.e., better than the 95% and 94.2% of the other two models.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152422
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2423: HFGNN-Proto: Hesitant Fuzzy Graph Neural
           Network-Based Prototypical Network for Few-Shot Text Classification

    • Authors: Xinyu Guo, Bingjie Tian, Xuedong Tian
      First page: 2423
      Abstract: Few-shot text classification aims to recognize new classes with only a few labeled text instances. Previous studies mainly utilized text semantic features to model the instance-level relation among partial samples. However, the single relation information makes it difficult for many models to address complicated natural language tasks. In this paper, we propose a novel hesitant fuzzy graph neural network (HFGNN) model that explores the multi-attribute relations between samples. We combine HFGNN with the Prototypical Network to achieve few-shot text classification. In HFGNN, multiple relations between texts, including instance-level and distribution-level relations, are discovered through dual graph neural networks and fused by hesitant fuzzy set (HFS) theory. In addition, we design a linear function that maps the fused relations to a more reasonable range in HFGNN. The final relations are used to aggregate the information of neighbor instance nodes in the graph to construct more discriminative instance features. Experimental results demonstrate that the classification accuracy of the HFGNN-based Prototypical Network (HFGNN-Proto) on the ARSC, FewRel 5-way 5-shot, and FewRel 10-way 5-shot datasets reaches 88.36%, 94.45%, and 89.40%, respectively, exceeding existing state-of-the-art few-shot learning methods.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152423
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2424: Algorithm of Computer Mainboard Quality
           Detection for Real-Time Based on QD-YOLO

    • Authors: Guangming Tu, Jiaohua Qin, Neal N. Xiong
      First page: 2424
      Abstract: Automated industrial quality detection (QD) boosts quality-detection efficiency and reduces costs. However, current quality-detection algorithms have drawbacks such as low efficiency, easily missed detections, and false detections. We propose QD-YOLO, an attention-based method to enhance quality-detection efficiency on computer mainboards. Firstly, we propose a composite attention module for the network’s backbone to highlight appropriate feature channels and improve the feature fusion structure, allowing the network to concentrate on the crucial information in the feature map. Secondly, we employ the Meta-ACON activation function to dynamically learn whether the activation function is linear or non-linear for various input data and adapt it to varied input scenarios with varying linearity. Additionally, we adopt Ghost convolution instead of ordinary convolution, using linear operations as possible to reduce the number of parameters and speed up detection. Experimental results show that our method can achieve improved real-time performance and accuracy on the self-created mainboard quality defect dataset, with a mean average precision (mAP) of 98.85% and a detection speed of 31.25 Frames Per Second (FPS). Compared with the original YOLOv5s model, the improved method improves mAP@0.5 by 2.09% and detection speed by 2.67 FPS.
      Citation: Electronics
      PubDate: 2022-08-03
      DOI: 10.3390/electronics11152424
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2425: A Tree Structure Protocol for
           Hierarchical Deterministic Latency Name Resolution System

    • Authors: Wei Xie, Jiali You, Jinlin Wang
      First page: 2425
      Abstract: Information-centric networking (ICN) shifts the communication model from a host-centric paradigm to an information-centric paradigm, and is promising for solving several problems on today’s Internet. For more efficient information dissemination, most ICN architectures are based on the Identifier/Locator split design. Therefore, how to map an identifier to a routable locator is an important problem for efficient data transmission. Nowadays, many new network services such as industrial control and telemedicine are highly latency-sensitive and require deterministic service response latency. To meet such requirements, name resolution with a deterministic latency guarantee is needed, but less discussed. This paper proposes a tree-based resolution system structure for deterministic latency resolution, which can support the Local Name Mapping Resolution System (LNMRS) in the new ICN network architecture—SEANet—to provide deterministic name resolution service in latency-sensitive scenarios like industrial control and telemedicine. The correctness of such a structure is the key to achieving deterministic latency resolution. To ensure the structure’s correctness in a distributed manner, a tree structure protocol based on delay measurement is also proposed for structure generation and maintenance. Simulation results show that the protocol is effective in generating a correct structure that has good performance in terms of service capability for deterministic name resolution and system scalability.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152425
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2426: High-Speed Privacy Amplification
           Algorithm Using Cellular Automate in Quantum Key Distribution

    • Authors: Yekai Lu, Enjian Bai, Xue-qin Jiang, Yun Wu
      First page: 2426
      Abstract: Privacy amplification is an important step in the post-processing of quantum communication, which plays an indispensable role in the security of quantum key distribution systems. In this paper, we propose a Cellular Automata-based privacy amplification algorithm, which improves the speed of key distribution. The proposed algorithm is characterized by block iteration to generate secure key of arbitrary length. The core of the algorithm in this paper is to use the property that Cellular Automata can generate multiple new associated random sequences at the same time to carry out bit operations for multiple negotiation keys in the meantime and calculate in turn, so as to quickly realize the compression of negotiation keys. By analyzing the final key, the proposed algorithm has the advantages of fast key generation speed and high real-time performance. At the same time, the results of the NIST randomness test and avalanche test show that the algorithm has good randomness performance.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152426
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2427: A 3DCNN-LSTM Multi-Class Temporal
           Segmentation for Hand Gesture Recognition

    • Authors: Letizia Gionfrida, Wan M. R. Rusli, Angela E. Kedgley, Anil A. Bharath
      First page: 2427
      Abstract: This paper introduces a multi-class hand gesture recognition model developed to identify a set of hand gesture sequences from two-dimensional RGB video recordings, using both the appearance and spatiotemporal parameters of consecutive frames. The classifier utilizes a convolutional-based network combined with a long-short-term memory unit. To leverage the need for a large-scale dataset, the model deploys training on a public dataset, adopting a technique known as transfer learning to fine-tune the architecture on the hand gestures of relevance. Validation curves performed over a batch size of 64 indicate an accuracy of 93.95% (±0.37) with a mean Jaccard index of 0.812 (±0.105) for 22 participants. The fine-tuned architecture illustrates the possibility of refining a model with a small set of data (113,410 fully labelled image frames) to cover previously unknown hand gestures. The main contribution of this work includes a custom hand gesture recognition network driven by monocular RGB video sequences that outperform previous temporal segmentation models, embracing a small-sized architecture that facilitates wide adoption.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152427
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2428: Research on Deep Defect Detection Method
           of Cable Lead Sealing Based on Improved Pulsed Eddy Current Excitation

    • Authors: Qianqiu Shao, Songhai Fan, Fenglian Liu
      First page: 2428
      Abstract: In order to reduce power failures caused by lead sealing defects, it is necessary to carry out nondestructive testing of cable lead sealings. However, previous studies have focused on the detection of surface and near-surface defects of lead sealings. Thus, an improved pulsed eddy current detection (IPECD) method is introduced to detect the deep defects of cable lead sealings (with depths ranging from 6 to 12 mm), and the frequency range selection principle and the optimization method of initial phase angles of different frequency components of IPECD, used to maximize the peak value of the excitation signal, are first explained in detail. Then, the detection sensitivities of the deep defects before and after the optimization are compared and analyzed based on a simulation. Finally, using the IPECD method, experiments are conducted to study the effects of the defect depth on features of the lift-off point of intersection and the zero-crossing time, enhancing the foundation for the prediction or rapid detection of the depth of lead sealing defects.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152428
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2429: Stratosphere: A Fast Virtual Circuit
           Switch Layer for Data Center Network

    • Authors: Lusha Mo, Gaofeng Lv, Baosheng Wang, Xiangrui Yang
      First page: 2429
      Abstract: The hierarchical structure of the data center network is more and more unsuitable for increasing east-west traffic from virtual machines. Reconfigurable circuit switching is utilized to reduce regional hotspots, which causes the problem of routing oscillation. We propose a stratospheric network of the data center, which combines virtual circuit switching and Tor switches. It acts as a supplement to tropospheric transmission across the hierarchical structure to alleviate global hotspots. The link of VCS (Virtual Circuit Switching) is divided into virtual channels by time division, and packets are sliced into cells to be transmitted at a specific time slot. Via the direct connection and the relaying of VCS modules, the stratospheric network could support not only the sharing of uplinks between Tor switches but also dynamical forwarding. Experiments of parameter servers demonstrate that it accelerates the transmission of data, which could provide a direct and fast path, especially for east-west traffic.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152429
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2430: Karnaugh-Veitch Maps as Minimal Formal
           Contract between Textual Requirements and Tests: A Use-Case Based
           Technical Analysis

    • Authors: Nils Henning Müllner
      First page: 2430
      Abstract: Checking that requirements written in natural language hold for a formally implemented system is a complex task. Test steps are commonly implemented manually from the requirements. This process is inherently prone to mistakes, as test cases are complex and need to be analyzed sequentially to check which input/output combinations are tested (although tools allow for explicit tracing). Utilizing Karnaugh–Veitch maps as minimal formal contract between informal requirements and implemented test steps improves this process. KV-maps provide the requirements in a computer-editable way, as they correspond to Boolean formulas. KV-maps further allow to define which test steps are relevant. With both requirements and relevance specification at hand, test steps are automatically generated. The approach is applied on a real-world industrial use-case—a train control management system. Although being generally amenable to permutation testing, the selected use-case emphasizes the potential of the method. The method successfully demonstrates its benefits and may help to disclose flaws in the current manually implemented tests.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152430
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2431: Simulating the Dispersion of the Energy
           Flux Density of the Electromagnetic Field Generated by Antennas for Mobile
           Communications

    • Authors: Raimondas Buckus, Aleksandras Chlebnikovas, Birute Strukcinskiene, Rimantas Stukas, Donatas Austys, Jacek Caban, Marcin Bogucki, Aurelija Sidlauskiene, Vaiva Seleviciene, Artūras Kilikevičius, Jonas Matijošius, Kristina Kilikevičienė, Darius Vainorius
      First page: 2431
      Abstract: The last two decades have faced a significantly increased number of telecommunication antennas emitting electromagnetic radiation in residential areas. The theoretical simulation of the dispersion of the energy flux density of the electromagnetic field has been performed applying the physical peculiarities of the waves generating electromagnetic radiation. Having evaluated studies on simulation, the visual representation of the spread of electromagnetic radiation has been carried out according to the results obtained applying the AutoCad package. A comparison of the simulated value of the energy flux density radiated from antennas for mobile telecommunications with the measured one has disclosed an overlap of 30%. The simulation of the energy flux density showed that, in the close proximity zone (under a distance of 30 m), antennas radiate values within the range 10–10,000 µW/cm2. At a distance larger than 30 m, the values of energy flux density fluctuate from 10 to 0.001 µW/cm2.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152431
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2432: A New Perspective on Traffic Flow
           Prediction: A Graph Spatial-Temporal Network with Complex Network
           Information

    • Authors: Zhiqiu Hu, Fengjing Shao, Rencheng Sun
      First page: 2432
      Abstract: Traffic flow prediction provides support for travel management, vehicle scheduling, and intelligent transportation system construction. In this work, a graph space–time network (GSTNCNI), incorporating complex network feature information, is proposed to predict future highway traffic flow time series. Firstly, a traffic complex network model using traffic big data is established, the topological features of traffic road networks are then analyzed using complex network theory, and finally, the topological features are combined with graph neural networks to explore the roles played by the topological features of 97 traffic network nodes. Consequently, six complex network properties are discussed, namely, degree centrality, clustering coefficient, closeness centrality, betweenness centrality, point intensity, and shortest average path length. This study improves the graph convolutional neural network based on the above six complex network properties and proposes a graph spatial–temporal network consisting of a combination of several complex network properties. By comparison with existing baselines containing graph convolutional neural networks, it is verified that GSTNCNI possesses high traffic flow prediction accuracy and robustness. In addition, ablation experiments are conducted for six different complex network features to verify the effect of different complex network features on the model’s prediction accuracy. Experimental analysis indicates that the model with combined multiple complex network features has a higher prediction accuracy, and its performance is improved by 31.46% on average, compared with the model containing only one complex network feature.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152432
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2433: Luminescent Downshifting Silicon Quantum
           Dots for Performance Enhancement of Polycrystalline Silicon Solar Cells

    • Authors: Qais Masaadeh, Eleni Kaplani, Yimin Chao
      First page: 2433
      Abstract: Silicon quantum dots (Si-QDs) with luminescent downshifting properties have been used for the efficiency enhancement of solar cells. In this study, Phenylacetylene-capped silicon quantum dots (PA Si-QDs) have been fabricated and applied as luminescent downshifting material on polycrystalline silicon solar cells, by dropcasting. The PA Si-QD coated solar cell samples presented an average increase in the short circuit current (Isc) of 0.75% and 1.06% for depositions of 0.15 mg and 0.01 mg on 39 mm × 39 mm pc-Si solar cells, respectively. The increase was further enhanced by full encapsulation of the sample leading to overall improved performance of about 3.4% in terms of Isc and 4.1% in terms of power output (Pm) when compared to the performance of fully encapsulated reference samples. The PA Si-QD coating achieved a reduction in specular reflectance at 377 nm of 61.8%, and in diffuse reflectance of 44.4%. The increase observed in the Isc and Pm is a promising indicator for the use of PA Si-QDs as luminescent downshifting material to improve the power conversion efficiency of pc-Si solar cells.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152433
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2434: A 1.2 V 0.4 mW 20~200 MHz DLL Based on
           Phase Detector Measuring the Delay of VCDL

    • Authors: Sang-Hyun Cho, Young-Kyun Cho
      First page: 2434
      Abstract: A delay locked loop (DLL) based on a Phase Detector, which Measures the Delay of the Voltage-controlled delay line (PD-MDV), which is tVCDL, with efficient and stable locking performance was proposed. In contrast to conventional phase detectors, the PD-MDV measures tVCDL more accurately; thus, it can always generate the correct up/down (UP/DN) pulses. The proposed technique prevents becoming stuck in the fastest operation, in which UP pulses continue to appear even when tVCDL < tREF, where tREF is the reference time, which is an input of the DLL. In the reverse case, the PD-MDV prohibits DN pulses from continuing to appear under the condition tVCDL > tREF, thereby freeing the DLL from harmonic locking and becoming stuck in the slowest operation. The proposed phase detection scheme was verified under various conditions, including process corners, temperature variations, and abrupt changes in tREF. The proposed 1.2 V, 20~200 MHz DLL with the PD-MDV was designed using the 65 nm process, with a power consumption of 0.4 mW at 200 MHz.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152434
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2435: Mammographic Classification of Breast
           Cancer Microcalcifications through Extreme Gradient Boosting

    • Authors: Haobang Liang, Jiao Li, Hejun Wu, Li Li, Xinrui Zhou, Xinhua Jiang
      First page: 2435
      Abstract: In this paper, we proposed an effective and efficient approach to the classification of breast cancer microcalcifications and evaluated the mathematical model for calcification on mammography with a large medical dataset. We employed several semi-automatic segmentation algorithms to extract 51 calcification features from mammograms, including morphologic and textural features. We adopted extreme gradient boosting (XGBoost) to classify microcalcifications. Then, we compared other machine learning techniques, including k-nearest neighbor (kNN), adaboostM1, decision tree, random decision forest (RDF), and gradient boosting decision tree (GBDT), with XGBoost. XGBoost showed the highest accuracy (90.24%) for classifying microcalcifications, and kNN demonstrated the lowest accuracy. This result demonstrates that it is essential for the classification of microcalcification to use the feature engineering method for the selection of the best composition of features. One of the contributions of this study is to present the best composition of features for efficient classification of breast cancers. This paper finds a way to select the best discriminative features as a collection to improve the accuracy. This study showed the highest accuracy (90.24%) for classifying microcalcifications with AUC = 0.89. Moreover, we highlighted the performance of various features from the dataset and found ideal parameters for classifying microcalcifications. Furthermore, we found that the XGBoost model is suitable both in theory and practice for the classification of calcifications on mammography.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152435
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2436: Cyclic Learning-Based Lightweight
           Network for Inverse Tone Mapping

    • Authors: Jiyun Park, Byung Cheol Song
      First page: 2436
      Abstract: Recent studies on inverse tone mapping (iTM) have moved toward indirect mapping, which generates a stack of low dynamic range (LDR) images with multiple exposure values (multi-EV stack) and then merges them. In order to generate multi-EV stack(s), several large-scale networks with more than 20 M parameters have been proposed, but their high dynamic range (HDR) reconstruction and multi-EV stack generation performance were not acceptable. Also, some previous methods using cycle consistency should even have trained additional networks that are not used for multi-EV stack generation, which results in large memory for training. Thus, this paper proposes novel cyclic learning based on cycle consistency to reduce the memory burden in training. In detail, we eliminated networks used only for training, so the proposed method enables efficient learning in terms of training-purpose memory. In addition, this paper presents a lightweight iTM network that dramatically reduces the network sizes of the existing networks. Actually, the proposed lightweight network requires only a small parameter size of 1/100 compared to the state-of-the-art (SOTA) method. The lightweight network contributes to the practical use of iTM. Therefore, the proposed method based on a lightweight network reliably generates a multi-EV stack. Experimental results show that the proposed method achieves quantitatively SOTA performance and is qualitatively comparable to conventional indirect iTM methods.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152436
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2437: Spectrum Sensing Based on STFT-ImpResNet
           for Cognitive Radio

    • Authors: Jianxin Gai, Linghui Zhang, Zihao Wei
      First page: 2437
      Abstract: Spectrum sensing is a crucial technology for cognitive radio. The existing spectrum sensing methods generally suffer from certain problems, such as insufficient signal feature representation, low sensing efficiency, high sensibility to noise uncertainty, and drastic degradation in deep networks. In view of these challenges, we propose a spectrum sensing method based on short-time Fourier transform and improved residual network (STFT-ImpResNet) in this work. Specifically, in STFT, the received signal is transformed into a two-dimensional time-frequency matrix which is normalized to a gray image as the input of the network. An improved residual network is designed to classify the signal samples, and a dropout layer is added to the residual block to mitigate over-fitting effectively. We conducted comprehensive evaluations on the proposed spectrum sensing method, which demonstrate that—compared with other current spectrum sensing algorithms—STFT-ImpResNet exhibits higher accuracy and lower computational complexity, as well as strong robustness to noise uncertainty, and it can meet the needs of real-time detection.
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152437
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2438: Machine Learning in Electronic and
           Biomedical Engineering

    • Authors: Claudio Turchetti, Laura Falaschetti
      First page: 2438
      Abstract: In recent years, machine learning (ML) algorithms have become of paramount importance in computer science research, both in the electronic and biomedical fields [...]
      Citation: Electronics
      PubDate: 2022-08-04
      DOI: 10.3390/electronics11152438
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2439: A Structural Framework for Assessing the
           Digital Resilience of Enterprises in the Context of the Technological
           Revolution 4.0

    • Authors: Anca Mehedintu, Georgeta Soava
      First page: 2439
      Abstract: This research aims to develop a conceptual model to establish the influence of digital core investment and digital innovation on digital resilience at the enterprise level. The data were collected through a questionnaire-based survey of managers and IT specialists of companies. The analysis was performed using structural equation modeling with SPSS Statistics and Amos software. Based on the literature review, the study identifies the main factors that can ensure digital resilience and assesses their impact on Romania’s private and public companies. The research results confirm the hypotheses presented in the article, emphasizing that digital resilience is the result of the collaboration of several factors with different effects, determined by using Industry 4.0 technologies. Thus, digital core and digital innovation investments help improve digital resilience. Moreover, digital core investments have a positive impact on the digital resilience of enterprises, mediated by digital innovation investments. The study’s novelty consists in the realization of a model of interconnected analysis of several variables specific to digital and innovative technologies to ensure the resilience framework at the company level. The research offers valuable results which can be used by companies in Romania or other European Union countries to ensure their digital resilience.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152439
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2440: An Efficient Design of High Step-Up
           Switched Z-Source (HS-SZSC) DC-DC Converter for Grid-Connected Inverters

    • Authors: Rahul Kumar, Ramani Kannan, Narinderjit Singh Sawaran Singh, Ghulam E. Mustafa Abro, Nirbhay Mathur, Maveeya Baba
      First page: 2440
      Abstract: With the increasing trend in the energy demand, power networks are transitioning from conventional generation systems to renewable energy sources (RESs). The energy is harvested from these RESs and fed to grid-connected inverters (GCIs), as the output power of major sources (e.g., solar and fuel cell) is mainly DC. However, owing to the lower output voltage of renewable RESs, power converters play a vital role in two-stage power systems for enhancing its lower value to a higher value. The basic requirement for the GCI is to maintain the constant output voltage for which it is essential to have a constant input voltage. Therefore, high gain and efficient power boost converters are required for a robust and reliable two-stage power system. This paper investigates the performance of an efficient model of a high step-up switched Z-source DC-DC converter (HS-SZSC) for grid-connected 3-phase H-bridge inverter applications. The proposed design achieves high voltage gain and eliminates the problems of circuit complexity by utilizing a smaller number of components, which makes it cost effective and highly efficient. The working principle is discussed in detail. To validate the proposed model, the performance of the conventional Z-source converter (ZSC) and proposed HS-SZSC employed with GCI is analyzed and compared for both normal and transient states through MATLAB simulations. The HS-SZSC with an open- and closed-loop system is tested at different loads (AC), representing varying power factor conditions, and results verify the suitability of the proposed design for grid-connected inverters. Lastly, another model is presented to resolve the issue of grid islanding in GCIs.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152440
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2441: A Reinforcement Learning-Based Routing
           for Real-Time Multimedia Traffic Transmission over Software-Defined
           Networking

    • Authors: Mohammed Al Jameel, Triantafyllos Kanakis, Scott Turner, Ali Al-Sherbaz, Wesam S. Bhaya
      First page: 2441
      Abstract: Recently, video streaming services consumption has grown massively and is foreseen to increase even more in the future. The tremendous traffic usage has negatively impacted the network’s quality of service due to network congestion and end-to-end customers’ satisfaction represented by the quality of experience, especially during evening peak hours. This paper introduces an intelligent multimedia framework that aims to optimise the network’s quality of service and users’ quality of experience by taking into account the integration of Software-Defined Networking and Reinforcement Learning, which enables exploring, learning, and exploiting potential paths for video streaming flows. Moreover, an objective study was conducted to assess video streaming for various realistic network environments and under low and high traffic loads to obtain two quality of experience metrics; video multimethod assessment fusion and structural similarity index measure. The experimental results validate the effectiveness of the proposed solution strategy, which demonstrated better viewing quality by achieving better customers’ quality of experience, higher throughput and lower data loss compared with the currently existing solutions.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152441
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2442: The Effects of Corporate Social
           Responsibility (CSR) on Consumer Behaviour in Online Commerce: The Case of
           Cosmetics during the COVID-19 Pandemics

    • Authors: Ion Popa, Luminița Nicolescu, Simona Cătălina Ștefan, Ștefan Cătălin Popa
      First page: 2442
      Abstract: Corporate social responsibility (CSR) is a trend that manifests on a global level. The positive effects of CSR initiatives depend on the reaction of stakeholders, among which customers represent an important category. The purpose of this paper was to analyse the impact that CSR initiatives of cosmetics companies have on customer behaviour in both the short-term (buying intention) and the long-term (client loyalty) in the case of electronic commerce. Starting from the existing literature, the conceptual model proposed different dimensions of CSR as influencers (legal and ethical, philanthropic and community services, respect for environment, respect for consumers), and as mediators, which were considered as the brand trust and the competitive advantage of the company. The research method used was quantitative with the empirical data being collected from 1265 actual and potential consumers of cosmetic products. The hypotheses were tested using the partial least squares structural equation modelling (PLS-SEM). The main findings illustrated positive relationships between CSR and both buying intention and client loyalty, as the two facets of consumer behaviour. The interpretation is that CSR activities can increase both the consumer intentions to buy cosmetics products provided by CSR-involved companies, and increase the long-term customer loyalty for these companies. The research also provided evidence for a strong mediation effect of brand trust for both sides of customer behaviour. This illustrates that when brand trust is higher the effect of CSR initiatives on customer behaviour increases. The paper includes theoretical and practical contributions associated to the results of the research.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152442
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2443: Methods of Intelligent Control in
           Mechatronics and Robotic Engineering: A Survey

    • Authors: Iuliia Zaitceva, Boris Andrievsky
      First page: 2443
      Abstract: Artificial intelligence is becoming an increasingly popular tool in more and more areas of technology. New challenges in control systems design and application are related to increased productivity, control flexibility, and processing of big data. Some kinds of systems require autonomy in real-time decision-making, while the other ones may serve as an essential factor in human-robot interaction and human influences on system performance. Naturally, the complex tasks of controlling technical systems require new modern solutions, but there remains an inextricable link between control theory and artificial intelligence. The first part of the present survey is devoted to the main intelligent control methods in technical systems. Among them, modern methods of adaptive and optimal control, fuzzy logic, and machine learning are considered. In its second part, the crucial achievements in intelligent control applications in robotic and mechatronic systems over the past decade are considered. The references are structured according to the type of such common control problems as stabilization, controller tuning, identification, parametric optimization, iterative learning, and prediction. In the conclusion, the main problems and tendencies toward intelligent control methods improvement are outlined.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152443
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2444: A Novel Seismocardiogram Mathematical
           Model for Simplified Adjustment of Adaptive Filter

    • Authors: Gediminas Uskovas, Algimantas Valinevicius, Mindaugas Zilys, Dangirutis Navikas, Michal Frivaldsky, Michal Prauzek, Jaromir Konecny, Darius Andriukaitis
      First page: 2444
      Abstract: Nonclinical measurements of a seismocardiogram (SCG) can diagnose cardiovascular disease (CVD) at an early stage, when a critical condition has not been reached, and prevents unplanned hospitalization. However, researchers are restricted when it comes to investigating the benefits of SCG signals for moving patients, because the public database does not contain such SCG signals. The analysis of a mathematical model of the seismocardiogram allows the simulation of the heart with cardiovascular disease. Additionally, the developed mathematical model of SCG does not totally replace the real cardio mechanical vibration of the heart. As a result, a seismocardiogram signal of 60 beats per min (bpm) was generated based on the main values of the main artefacts, their duration and acceleration. The resulting signal was processed by finite impulse response (FIR), infinitive impulse response (IRR), and four adaptive filters to obtain optimal signal processing settings. Meanwhile, the optimal filter settings were used to manage the real SCG signals of slowly moving or resting. Therefore, it is possible to validate measured SCG signals and perform advanced scientific research of seismocardiogram. Furthermore, the proposed mathematical model could enable electronic systems to measure the seismocardiogram with more accurate and reliable signal processing, allowing the extraction of more useful artefacts from the SCG signal during any activity.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152444
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2445: Image Denoising Based on GAN with
           Optimization Algorithm

    • Authors: Min-Ling Zhu, Liang-Liang Zhao, Li Xiao
      First page: 2445
      Abstract: Image denoising has been a knotty issue in the computer vision field, although the developing deep learning technology has brought remarkable improvements in image denoising. Denoising networks based on deep learning technology still face some problems, such as in their accuracy and robustness. This paper constructs a robust denoising network based on a generative adversarial network (GAN). Since the neural network has the phenomena of gradient dispersion and feature disappearance, the global residual is added to the autoencoder in the generator network, to extract and learn the features of the input image, so as to ensure the stability of the network. On this basis, we proposed an optimization algorithm (OA), to train and optimize the mean and variance of noise on each node of the generator. Then the robustness of the denoising network was improved through back propagation. Experimental results showed that the model’s denoising effect is remarkable. The accuracy of the proposed model was over 99% in the MNIST data set and over 90% in the CIFAR10 data set. The peak signal to noise ratio (PSNR) and structural similarity (SSIM) values of the proposed model were better than the state-of-the-art models in the BDS500 data set. Moreover, an anti-interference test of the model showed that the defense capacities of both the fast gradient sign method (FGSM) and project gradient descent (PGD) attacks were significantly improved, with PSNR and SSIM values decreased by less than 2%.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152445
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2446: Position Distribution Matters: A
           Graph-based Binary Function Similarity Analysis Method

    • Authors: Zulie Pan, Taiyan Wang, Lu Yu, Yintong Yan
      First page: 2446
      Abstract: Binary function similarity analysis evaluates the similarity of functions at the binary level to aid program analysis, which is popular in many fields, such as vulnerability detection, binary clone detection, and malware detection. Graph-based methods have relatively good performance in practice, but currently, they cannot capture similarity in the aspect of the graph position distribution and lose information in graph processing, which leads to low accuracy. This paper presents PDM, a graph-based method to increase the accuracy of binary function similarity detection, by considering position distribution information. First, an enhanced Attributed Control Flow Graph (ACFG+) of a function is constructed based on a control flow graph, assisted by the instruction embedding technique and data flow analysis. Then, ACFG+ is fed to a graph embedding model using the CapsGNN and DiffPool mechanisms, to enrich information in graph processing by considering the position distribution. The model outputs the corresponding embedding vector, and we can calculate the similarity between different function embeddings using the cosine distance. Similarity detection is completed in the Siamese network. Experiments show that compared with VulSeeker and PalmTree+VulSeeker, PDM can stably obtain three-times and two-times higher accuracy, respectively, in binary function similarity detection and can detect up to six-times more results in vulnerability detection. When comparing with some state-of-the-art tools, PDM has comparable Top-5, Top-10, and Top-20 ranking results with respect to BinDiff, Diaphora, and Kam1n0 and significant advantages in the Top-50, Top-100, and Top-200 detection results.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152446
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2447: Study of Breakdown Voltage Stability of
           Gas-Filled Surge Arresters in the Presence of Gamma Radiation

    • Authors: Emilija Živanović, Marija Živković, Sandra Veljković
      First page: 2447
      Abstract: The results presented in this article relate to the study of the impact of gamma radiation on the breakdown voltage of gas-filled surge arrester manufactured by CITEL, Littelfuse and EPCOS at an operating voltage of 230 V. Radium was considered as a source of gamma radiation in this research. The stability of breakdown voltage as well as the reliability of gas-filled surge arresters of different manufacturers were investigated using different statistical methods. This gas component operation was based on processes that lead to electrical breakdown and discharge in gas. The breakdown voltage has a stochastic nature, and it is a subject of certain distribution. One thousand voltage measurements of breakdown voltage were carried out for each value of the voltage increase rate, from 1 V/s up to 10 V/s, with and without the presence of additional gamma radiation. The detailed statistical analysis of the obtained experimental data was performed for both cases for all three GFSA types. Moreover, the cumulative distribution functions of breakdown voltage were presented with the applied Weibull distribution fit. The coefficient of correlation as well as Pearson χ2 test showed the strength of the relationship between the experimental distribution functions and the Weibull distribution fits. The values of the Weibull distribution coefficients for all voltage increase rates and for all components were also analyzed with and without gamma radiation.
      Citation: Electronics
      PubDate: 2022-08-05
      DOI: 10.3390/electronics11152447
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2448: Response Time and Intrinsic Information
           Quality as Criteria for the Selection of Low-Cost Sensors for Use in
           Mobile Weather Stations

    • Authors: Agnieszka Chodorek, Robert Ryszard Chodorek, Paweł Sitek
      First page: 2448
      Abstract: Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, i.e., the two-stage selection of sensors, carried out on the basis of both the literature (pre-selection) and experiments (actual selection). We formulated the criteria of the sensor selection for the needs of the sources of weather information: the major one, which is the fast response time of a sensor in a cyber-physical subsystem and two minor ones, which are based on the intrinsic information quality dimensions related to measurement information. These criteria were tested by using a set of twelve weather sensors from different manufacturers. Results show that the two-stage sensor selection allows us to choose the least energy consuming (due to the major criterion) and the most accurate (due to the minor criteria) set of weather sensors, and is able to replace some methods of sensor selection reported in the literature. The proposed method is, however, more versatile and can be used to select any sensors with a response time comparable to electric ones, and for the application of low-cost sensors that are not related to weather stations.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152448
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2449: Task-Space Cooperative Tracking Control
           for Networked Uncalibrated Multiple Euler-Lagrange Systems

    • Authors: Zhuoqun Zhao, Jiang Wang, Hui Zhao
      First page: 2449
      Abstract: Task-space cooperative tracking control of the networked multiple Euler-Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler-Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and uncertainties. First, in order to weaken the influence of the uncertainty of kinematic and dynamic parameters on the control error of the system, the product of the Jacobian matrix and the generalized spatial velocity are linearly parameterized; thus, the unknown parameters are separated from known parameters. The online estimation of uncertain parameters is realized by designing parameters and by proposing new adaptive laws for the dynamic and kinematic parameters. Furthermore, to describe the transmission of time-varying delay errors among networked agents, a new error term is introduced, obtained by adding the observation error and tracking error, and the coefficient of the network mutual coupling term related to the time-varying delay rate is added with reference to the generalized space velocity and task-space velocity of the Lagrange systems. In the end, the influence of the time-varying delay on the cooperative tracking control error of the networked multiple Euler-Lagrange systems is eliminated. With the help of Lyapunov stability theory, the tracking errors and synchronization errors of this system are calculated by introducing the Lyapunov-Krasovskii functional; the asymptotic convergence results rigorously prove the stability of the adaptive cooperative control systems. The simulation results verify the excellent performance of the controller.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152449
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2450: A Compact mmWave MIMO Antenna for Future
           Wireless Networks

    • Authors: Muhammad Imran Khan, Sarmadullah Khan, Saad Hassan Kiani, Naser Ojaroudi Ojaroudi Parchin, Khalid Mahmood, Umair Rafique, Muhammad Mansoor Qadir
      First page: 2450
      Abstract: This article presents a four-element multiple-input multiple-output (MIMO) antenna design for next-generation millimeter-wave (mmWave) communication systems. The single antenna element of the MIMO systems consists of a T-shaped and plow-shaped patch radiator designed on an ultra-thin Rogers RT/Duroid 5880 substrate. The dimensions of the single antenna are 10 × 12 mm2. The MIMO system is designed by placing four elements in a polarization diversity configuration whose overall dimensions are 24 × 24 mm2. From the measured results, it is observed that the MIMO antenna provides 9.23 GHz impedance bandwidth ranging from 22.43 to 31.66 GHz. In addition, without the utilization of any decoupling network, a minimum isolation of 25 dB is achieved between adjacent MIMO elements. Furthermore, the proposed MIMO antenna system is fabricated, and it is noted that the simulated results are in good agreement with the measured results. Through the achieved results, it can be said that the proposed MIMO antenna system can be used in 5G mmWave radio frequency (RF) front-ends.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152450
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2451: Design and Simulation of a Novel
           Single-Chip Integrated MEMS Accelerometer Gyroscope

    • Authors: Yang Gao, Lin Meng, Jinwu Tong, Zhihu Ruan, Jia Jia
      First page: 2451
      Abstract: This paper presents the design and simulation of a single-chip integrated MEMS accelerometer gyroscope by integrating a Coriolis vibratory ring gyroscope and a differential resonant accelerometer into one single-chip structure, measuring both the acceleration and the angular velocity (or the angle). At the same time, it has the advantages of small volume, low cost, and high precision based on the characteristics of a ring gyroscope and resonant accelerometer. The proposed structure consists of a microring gyroscope and a MEMS resonant accelerometer. Tthe accelerometer is located inside the gyroscope and the two structures are concentric. The operating mechanisms of the ring gyroscope and the resonant accelerometer are first introduced. Then, the whole structure of the proposed single-chip integrated accelerometer gyroscope is presented, and the structural components are introduced in detail. Modal analysis shows the resonant frequencies of upper and lower DETFs in resonant accelerometer are 28,944.8 Hz and 28,948.0 Hz, and the resonant frequencies of the ring gyroscope (n=2) are 15,768.5 Hz and 15,770.3 Hz, respectively. The scale factor of the resonant accelerometer is calculated as 83.5 Hz/g by the analysis of the input–output characteristic. Finally, the thermal analysis fully demonstrates that the single-chip integrated accelerometer gyroscope has excellent immunity to temperature change.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152451
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2452: Compiler Optimization Parameter
           Selection Method Based on Ensemble Learning

    • Authors: Hui Liu, Jinlong Xu, Sen Chen, Te Guo
      First page: 2452
      Abstract: Iterative compilation based on machine learning can effectively predict a program’s compiler optimization parameters. Although having some limits, such as the low efficiency of optimization parameter search and prediction accuracy, machine learning-based solutions have been a frontier research field in the field of iterative compilation and have gained increasing attention. The research challenges are focused on learning algorithm selection, optimal parameter search, and program feature representation. For the existing problems, we propose an ensemble learning-based optimization parameter selection (ELOPS) method for the compiler. First, in order to further improve the optimization parameter search efficiency and accuracy, we proposed a multi-objective particle swarm optimization (PSO) algorithm to determine the optimal compiler parameters of the program. Second, we extracted the mixed features of the program through the feature-class relevance method, rather than using static or dynamic features alone. Finally, as the existing research usually uses a separate machine learning algorithm to build prediction models, an ensemble learning model using program features and optimization parameters was constructed to effectively predict compiler optimization parameters of the new program. Using standard performance evaluation corporation 2006 (SPEC2006) and NAS parallel benchmark (NPB) benchmarks as well as some typical scientific computing programs, we compared ELOPS with the existing methods. The experimental results showed that we can respectively achieve 1.29× and 1.26× speedup when using our method on two platforms, which are better results than those of existing methods.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152452
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2453: Dynamic Modeling and Simulation of a
           Four-Wheel Skid-Steer Mobile Robot Using Linear Graphs

    • Authors: Eric McCormick, Haoxiang Lang, Clarence W. de de Silva
      First page: 2453
      Abstract: This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a four-wheel skid-steer mobile robotic system. An LG representation of the system is proposed, and the accompanying state-space model of the dynamics of a mobile robot system is evaluated using the associated LGtheory MATLAB toolbox, which was developed in our lab. A genetic algorithm (GA)-based parameter estimation method is employed to determine the system parameters, which leads to a very accurate simulation of the model. The developed model is then evaluated and validated by comparing the simulated LG model trajectory with the trajectory of an ROS Gazebo-simulated robot and experimental data obtained from the physical robotic system. The obtained results demonstrate that the proposed LG model, combined with the GA parameter estimation process, produces a highly accurate method of modeling and simulating a mobile robotic system.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152453
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2454: Textile Bandwidth-Enhanced Coupled-Mode
           Substrate-Integrated Cavity Antenna with Slot

    • Authors: Jie Cui, Feng-Xue Liu, Xiaopeng Shen, Lei Zhao, Hongsheng Yin
      First page: 2454
      Abstract: A textile bandwidth-enhanced coupled-mode substrate-integrated cavity antenna with a slot is presented. The original coupled-mode substrate-integrated cavity antenna is of two close resonances for the odd and even coupled modes, and a rectangular slot is added on the top layer to introduce a third resonance. Parameters are optimized to merge the bands of the three resonances to realize a widened −10 dB impedance band to cover the Medical Body Area Network band, 2.45 GHz Industrial Scientific Medical band and Long-Term Evolution Band7. The proposed antenna can operate in a −10 dB impedance band of 2.32–2.69 GHz with a 14.9% fractional bandwidth according to the measurements on a fabricated prototype. Simulation and measurement results illustrate the robustness of the proposed textile antenna in the vicinity of the human body and cylindrical bending conditions. In addition, the simulated specific absorption rate of the antenna radiation in the human body is lower than the IEEE and EN limits.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152454
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2455: Maintaining Effective Node Chain
           Connectivity in the Network with Transmission Power of Self-Arranged AdHoc
           Routing in Cluster Scenario

    • Authors: Kiruthiga Devi Murugavel, Parthasarathy Ramadass, Rakesh Kumar Mahendran, Arfat Ahmad Khan, Mohd Anul Haq, Sultan Alharby, Ahmed Alhussen
      First page: 2455
      Abstract: Mobile Ad hoc Networks (MANETs) are intended to work without a fixed framework and provide dependable interchanges to ground vehicles, boats, airplanes, or people and structure a self-mending process that will empower persistent correspondences in any event, when at least one of its nodes are debilitated or briefly expelled from the system. Notwithstanding, MANETs demonstrate themselves to be progressively harder to create for enormous systems with hundreds or thousands more nodes than initially envisioned. In our proposed technique, the node switches its communication mode depending on the connectivity of the adjacent nodes. The transmission power of each node will be calculated with the help of two major scenarios i.e., tree scenario and zone scenario. The autonomous clustering of the nodes among the tree and the zone scenario will be channelized by a comparison of the transmission power (residual energy) among the nodes. The inter and the intra communication of the node is also discussed in the paper. The result will be carried out by the simulation work in various perspectives, such as checking the percentage level of malicious nodes, traffic density, transmission power, and the longevity of nodes.
      Citation: Electronics
      PubDate: 2022-08-06
      DOI: 10.3390/electronics11152455
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2456: Classification of Atrial Fibrillation
           and Congestive Heart Failure Using Convolutional Neural Network with
           Electrocardiogram

    • Authors: Yunendah Nur Fu’adah, Ki Moo Lim
      First page: 2456
      Abstract: Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing electrocardiogram (ECG) signals. However, manual diagnosis is complex, owing to the various characteristics of ECG signals. An accurate classification system for AF and CHF has the potential to save patient lives. Therefore, this study proposed an ECG signal classification system for AF and CHF using a one-dimensional convolutional neural network (1-D CNN) to provide a robust classification system performance. This study used ECG signal recording of AF, CHF, and NSR, which can be accessed on the Physionet website. A total of 5600 ECG signal segments were obtained from 56 subjects, divided into train sets from 42 subjects (N = 4200 ECG segments), and test sets from 14 subjects (N = 1400). We applied for leave-one-out cross-validation in training to select the best model. The proposed 1-D CNN algorithm successfully classified raw data of ECG signals into normal sinus rhythm (NSR), AF, and CHF by providing the highest classification accuracy of 99.643%, f1-score, recall, and precision of 0.996, respectively, with an AUC score of 0.999. The results showed that the proposed method extracted the ECG signal information directly without needing several preprocessing steps and feature extraction methods that potentially reduce the information contained in the ECG signals. Furthermore, the proposed method outperformed previous studies in classifying AF, CHF, and NSR. Therefore, this approach can be considered as an adjunct for medical personnel to diagnose AF, CHF, and NSR.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152456
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2457: Dim and Small Target Tracking Using an
           Improved Particle Filter Based on Adaptive Feature Fusion

    • Authors: Youhui Huo, Yaohong Chen, Hongbo Zhang, Haifeng Zhang, Hao Wang
      First page: 2457
      Abstract: Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of particle diversity caused by resampling, lead to a considerable negative impact on tracking performance. In the present paper, we propose an improved resampling particle filter algorithm based on adaptive multi-feature fusion to address the drawbacks of particle filters for dim and small target tracking and improve the tracking performance. We first establish an observation model based on the adaptive fusion of the features of the weighted grayscale intensity, edge information, and wavelet transform. We then generate new particles based on residual resampling by combining the target position in the previous frame and the particles in the current frame with higher weights, with the tracking accuracy and particle diversity improving simultaneously. The experimental results demonstrate that our proposed method achieves a high tracking performance with a distance accuracy of 77.2% and a running speed of 106 fps, respectively, meaning that it will have a promising prospect in dim and small target tracking applications.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152457
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2458: Improved Belief Propagation List
           Decoding for Polar Codes

    • Authors: Huan Li, Jingxuan Huang, Ce Sun
      First page: 2458
      Abstract: Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the 5G communication systems. Belief propagation (BP) decoding of polar codes has advantages of low decoding latency and high parallelism but achieves worse bit error ratio (BER) performance compared with the successive cancellation list (SCL) decoding scheme. In this paper, an improved BP list (IBPL) decoding algorithm is proposed with comparable BER performance to SCL algoritm. Firstly, the optimal permuted factor graph is analyzed for polar codes, which improves the performance of the BP decoder without path extension. Furthermore, based on the optimal graph, the bit metric and decoding path metric are proposed to extend and prune the decoding path. The proposed IBPL decoder is focused on not only the permutation of polar codes but also the reliabilities of decoded codewords during each iteration of BP decoding, which has a more accurate decoding path list. The simulation results show that the proposed IBPL decoder improves the BER performance compared with the original BP decoder significantly, and can approach the performance of the SCL decoder at low signal to noise ratio regions.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152458
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2459: A Fortunate Refining Trip Recommendation
           Model

    • Authors: Rizwan Abbas, Gehad Abdullah Amran, Ahmed A. Abdulraheem, Irshad Hussain, Rania M. Ghoniem, Ahmed A. Ewees
      First page: 2459
      Abstract: Personalized travel recommendations propose locations of interest (LOIs) for users. The LOI sequence suggestion is more complicated than a single LOI recommendation. Only a few studies have considered LOI sequence recommendations. Creating a reliable succession of LOIs is difficult. The two LOIs that follow each other should not be identical or from the same category. It is vital to examine the types of subsequent LOIs when designing a sequence of LOIs. Another issue is that providing precise and accurate location recommendations bores users. It can be tedious and monotonous to look at the same types of LOIs repeatedly. Users may want to change their plans in the middle of a trip. The trip must be dynamic rather than static. To address these concerns in the recommendations, organize a customized journey by looking for continuity, implications, innovation, and surprising (i.e., high levels of amusement) LOIs. We use LOI-likeness and category differences between subsequent LOIs to build sequential LOIs. In our travel recommendations, we leveraged luck and dynamicity. We suggest a fortunate refining trip recommendation (FRTR) to address the issues of identifying and rating user pleasure. An algorithm oof compelling recommendation should offer what we are likely to enjoy and provide spontaneous yet objective components to maintain an open doorway to new worlds and discoveries. In addition, two advanced novel estimations are presented to examine the recommended precision of a sequence of LOIs: regulated precision (RP) and pattern precision (PP). They consider the consistency and order of the LOIs. We tested our strategy using data from a real-world dataset and user journey records from Foursquare dataset. We show that our system outperforms other recommendation algorithms to meet the travel interests of users.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152459
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2460: Multi-Method Diagnosis of CT Images for
           Rapid Detection of Intracranial Hemorrhages Based on Deep and Hybrid
           Learning

    • Authors: Badiea Abdulkarem Mohammed, Ebrahim Mohammed Senan, Zeyad Ghaleb Al-Mekhlafi, Taha H. Rassem, Nasrin M. Makbol, Adwan Alownie Alanazi, Tariq S. Almurayziq, Fuad A. Ghaleb, Amer A. Sallam
      First page: 2460
      Abstract: Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions. In this study, CT images for rapid detection of intracranial hemorrhages are diagnosed by three proposed systems with various methodologies and materials, where each system contains more than one network. The first system is proposed by three pretrained deep learning models, which are GoogLeNet, ResNet-50 and AlexNet. The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. All the proposed systems achieved promising results in the diagnosis of CT images for the rapid detection of intracranial hemorrhages. The ANN network based on fusion of the deep feature of AlexNet with the features of GLCM and LBP reached an accuracy of 99.3%, precision of 99.36%, sensitivity of 99.5%, specificity of 99.57% and AUC of 99.84%.
      Citation: Electronics
      PubDate: 2022-08-07
      DOI: 10.3390/electronics11152460
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2461: Performance Metric Evaluation of
           Error-Tolerant Adders for 2D Image Blending

    • Authors: Tanya Mendez, Subramanya G. Nayak, Vasanth Kumar P., Vijay S. R., Vishnumurthy Kedlaya K.
      First page: 2461
      Abstract: The hardware implementation of error-tolerant adders using the paradigm of approximate computing has considerably influenced the performance metrics, especially in applications that can compromise accuracy. The foundation for approximate processing is the inclusion of errors in the design to enhance the effectiveness and reduce the complexity. This work presents three base adders using the novel concept of error tolerance in digital VLSI design. The research is extended to construct nine variants of power and delay-efficient 16 and 32-bit error-tolerant carry select adders (CSLA). To attain optimization in power and delay, conventional CSLA is refined by substituting ripple carry adders (RCA) with the newly proposed selector unit to minimize the switching activity. The research work includes the power, area, and delay estimates of the design from synthesis using the gpdk-90 nm and gpdk-45 nm standard cell libraries. The proposed adders exhibit reduced delay, power dissipation, area, power delay product (PDP), energy delay product (EDP), and area delay product (ADP) compared to the existing approximate adders. The proposed adder is used in an image blending application. There is a significant improvement in the peak-signal-to-noise ratio (PSNR) in the blended image compared to the standard designs.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152461
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2462: Hardware-in-the-Loop Simulations: A
           Historical Overview of Engineering Challenges

    • Authors: Franc Mihalič, Mitja Truntič, Alenka Hren
      First page: 2462
      Abstract: The design of modern industrial products is further improved through the hardware-in-the-loop (HIL) simulation. Realistic simulation is enabled by the closed loop between the hardware under test (HUT) and real-time simulation. Such a system involves a field programmable gate array (FPGA) and digital signal processor (DSP). An HIL model can bypass serious damage to the real object, reduce debugging cost, and, finally, reduce the comprehensive effort during the testing. This paper provides a historical overview of HIL simulations through different engineering challenges, i.e., within automotive, power electronics systems, and different industrial drives. Various platforms, such as National Instruments, dSPACE, Typhoon HIL, or MATLAB Simulink Real-Time toolboxes and Speedgoat hardware systems, offer a powerful tool for efficient and successful investigations in different fields. Therefore, HIL simulation practice must begin already during the university’s education process to prepare the students for professional engagements in the industry, which was also verified experimentally at the end of the paper.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152462
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2463: Systematic Literature Review of Models
           Used in the Epidemiological Analysis of Bovine Infectious Diseases

    • Authors: Javier Antonio Ballesteros-Ricaurte, Ramon Fabregat, Angela Carrillo-Ramos, Carlos Parra, Martin Orlando Pulido-Medellín
      First page: 2463
      Abstract: There are different bovine infectious diseases that show economic losses and social problems in various sectors of the economy. Most of the studies are focused on some diseases (for example, tuberculosis, salmonellosis, and brucellosis), but there are few studies on other diseases which are not officially controlled but also have an impact on the economy. This work is a systematic literature review on models (as a theoretical scheme, generally in mathematical form) used in the epidemiological analysis of bovine infectious diseases in the dairy farming sector. In this systematic literature review, criteria were defined for cattle, models, and infectious diseases to select articles on Scopus, IEEE, Xplorer, and ACM databases. The relations between the found models (model type, function and the proposed objective in each work) and the bovine infectious diseases, and the different techniques used and the works over infectious disease in humans, are presented. The outcomes obtained in this systematic literature review provide the state-of-the-art inputs for research on models for the epidemiological analysis of infectious bovine diseases. As a consequence of these outcomes, this work also presents an approach of EiBeLec, which is an adaptive and predictive system for the bovine ecosystem, combining a prediction model that uses machine-learning techniques and an adaptive model that adapts the information presented to end users.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152463
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2464: Deadline-Aware Dynamic Task Scheduling
           in Edge–Cloud Collaborative Computing

    • Authors: Yu Zhang, Bing Tang, Jincheng Luo, Jiaming Zhang
      First page: 2464
      Abstract: In recent years, modern industry has been exploring the transition to cyber physical system (CPS)-based smart factories. As intelligent industrial detection and control technology grows in popularity, massive amounts of time-sensitive applications are generated. A cutting-edge computing paradigm called edge-cloud collaborative computing was developed to satisfy the need of time-sensitive tasks such as smart vehicles and automatic mechanical remote control, which require substantially low latency. In edge-cloud collaborative computing, it is extremely challenging to improve task scheduling while taking into account both the dynamic changes of user requirements and the limited available resources. The current task scheduling system applies a round-robin policy to cyclically select the next server from the list of available servers, but it may not choose the best-suited server for the task. To satisfy the real-time task flow of industrial production in terms of task scheduling based on deadline and time sensitivity, we propose a hierarchical architecture for edge-cloud collaborative environments in the Industrial Internet of Things (IoT) and then simplify and mathematically formulate the time consumption of edge-cloud collaborative computing to reduce latency. Based on the above hierarchical model, we present a dynamic time-sensitive scheduling algorithm (DSOTS). After the optimization of DSOTS, the dynamic time-sensitive scheduling algorithm with greedy strategy (TSGS) that ranks server capability and job size in a hybrid and hierarchical scenario is proposed. What cannot be ignored is that we propose to employ comprehensive execution capability (CEC) to measure the performance of a server for the first time and perform effective server load balancing while satisfying the user’s requirement for tasks. In this paper, we simulate an edge-cloud collaborative computing environment to evaluate the performance of our algorithm in terms of processing time, SLA violation rate, and cost by extending the CloudSimPlus toolkit, and the experimental results are very promising. Aiming to choose a more suitable server to handle dynamically incoming tasks, our algorithm decreases the average processing time and cost by 30% and 45%, respectively, as well as the average SLA violation by 25%, when compared to existing state-of-the-art solutions.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152464
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2465: A Fully Polarity-Aware
           Double-Node-Upset-Resilient Latch Design

    • Authors: Jung-Jin Park, Young-Min Kang, Geon-Hak Kim, Ik-Joon Chang, Jinsang Kim
      First page: 2465
      Abstract: Due to aggressive scaling down, multiple-node-upset hardened design has become a major concern regarding radiation hardening. The proposed latch overcomes the architecture and performance limitations of state-of-the-art double-node-upset (DNU)-resilient latches. A novel stacked latch element is developed with multiple thresholds, regular architecture, increased number of single-event upset (SEU)-insensitive nodes, low power dissipation, and high robustness. The radiation-aware layout considering layout-level issues is also proposed. Compared with state-of-the-art DNU-resilient latches, simulation results show that the proposed latch exhibits up to 92% delay and 80% power reduction in data activity ratio (DAR) of 100%. The radiation simulation using the dual-double exponential current source model shows that the proposed latch has the strongest radiation-hardening capability among the other DNU-resilient latches.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152465
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2466: Face-Based CNN on Triangular Mesh with
           Arbitrary Connectivity

    • Authors: Hui Wang, Yu Guo, Zhengyou Wang
      First page: 2466
      Abstract: Applying convolutional neural networks (CNNs) to triangular meshes has always been a challenging task. Because of the complex structure of the meshes, most of the existing methods apply CNNs indirectly to them, and require complex preprocessing or transformation of the meshes. In this paper, we propose a novel face-based CNN, which can be directly applied to triangular meshes with arbitrary connectivity by defining face convolution and pooling. The proposed approach takes each face of the meshes as the basic element, similar to CNNs with pixels of 2D images. First, the intrinsic features of the faces are used as the input features of the network. Second, a sort convolution operation with adjustable convolution kernel sizes is constructed to extract the face features. Third, we design an approximately uniform pooling operation by learnable face collapse, which can be applied to the meshes with arbitrary connectivity, and we directly use its inverse operation as unpooling. Extensive experiments show that the proposed approach is comparable to, or can even outperform, state-of-the-art methods in mesh classification and mesh segmentation.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152466
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2467: Optimizing the Quantum Circuit for
           Solving Boolean Equations Based on Grover Search Algorithm

    • Authors: Hui Liu, Fukun Li, Yilin Fan
      First page: 2467
      Abstract: The solution of nonlinear Boolean equations in a binary field plays a crucial part in cryptanalysis and computational mathematics. To speed up the process of solving Boolean equations is an urgent task that needs to be addressed. In this paper, we propose a method for solving Boolean equations based on the Grover algorithm combined with preprocessing using classical algorithms, optimizing the quantum circuit for solving the equations, and implementing the automatic generation of quantum circuits. The method first converted Boolean equations into Boolean expressions to construct the oracle in the Grover algorithm. The quantum circuit was emulated based on the IBM Qiskit framework and then simulated the Grover algorithm on this basis. Finally, the solution of the Boolean equation was implemented. The experimental results proved the feasibility of using the Grover algorithm to solve nonlinear Boolean equations in a binary field, and the correct answer was successfully found under the conditions that the search space was 221 and three G iterations were used. The method in this paper increases the solving scale and solving speed of Boolean equations and enlarges the application area of the Grover algorithm.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152467
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2468: Development and Space-Qualification of a
           Miniaturized CubeSat’s 2-W EDFA for Space Laser Communications

    • Authors: Alberto Carrasco-Casado, Koichi Shiratama, Dimitar Kolev, Phuc V. Trinh, Femi Ishola, Tetsuharu Fuse, Morio Toyoshima
      First page: 2468
      Abstract: The Japanese National Institute of Information and Communications Technology (NICT) is currently developing a high-performance laser-communication terminal for CubeSats aimed at providing a high-datarate communication solution for LEO satellites requiring transmission of large volumes of data from orbit. A key aspect of the communication system is a high-power optical amplifier capable of providing enough gain to the transmitted signals to be able to close the link on its counterpart’s receiver with the smallest impact in terms of energy and power on the CubeSat’s platform. This manuscript describes the development of a miniaturized 2-W space-grade 2-stage erbium-doped fiber amplifier (EDFA) compatible with the CubeSat form factor, showing the best power-to-size ratio for a space-qualified EDFA to the best of the authors’ knowledge. Performance results under realistic conditions as well as full space qualification and test are presented, proving that this module can support short-duration LEO-ground downlinks as well as long-duration intersatellite links.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152468
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2469: Enhancing Virtual Real-Time Monitoring
           of Photovoltaic Power Systems Based on the Internet of Things

    • Authors: Ghedhan Boubakr, Fengshou Gu, Laith Farhan, Andrew Ball
      First page: 2469
      Abstract: Solar power systems have been growing globally to replace fossil fuel-based energy and reduce greenhouse gases (GHG). In addition to panel efficiency deterioration and contamination, the produced power of photovoltaic (PV) systems is intermittent due to the dependency on weather conditions, causing reliability and resiliency issues. Monitoring system parameters can help in predicting faults in time for corrective action to be taken or preventive maintenance to be applied. However, classical monitoring approaches have two main problems: neither local nor centralized monitoring support distributed PV power systems nor provide remote access capability. Therefore, this paper presents an appraisal of a remote monitoring system of PV power generation stations by utilizing the Internet of Things (IoT) and a state-of-the-art tool for virtual supervision. The proposed system allows real-time measurements of all PV system parameters, including surrounding weather conditions, which are then available at the remote control center to check and track the PV power system. The proposed technique is composed of a set of cost-effective devices and algorithms, including a PV power conditioning unit (PCU); a sensor board for measuring the variables that influence PV energy production such as irradiance and temperature, using a communication module based on Wi-Fi for data transmission; and a maximum power point tracking (MPPT) controller for enhancing the efficiency of the PV system. For validating the proposed system, different common scenarios of PV panel conditions including different shading circumstances were considered. The results show that accurate, real-time monitoring with remote access capabilities can provide timely information for predicting and diagnosing the system condition to ensure continued stable power generation and management.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152469
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2470: Key Factors in the Implementation of
           Wearable Antennas for WBNs and ISM Applications: A Review WBNs and ISM
           Applications: A Review

    • Authors: Fatimah Fawzi Hashim, Wan Nor Liza Binti Mahadi, Tariq Bin Abdul Latef, Mohamadariff Bin Othman
      First page: 2470
      Abstract: The increasing usage of wireless technology has prompted the development of a new generation antenna compatible with the latest devices, with on-body antennas (wearable antennas) being one of the revolutionary applications. This modern design is relevant in technologies that require close human body contact, such as telemedicine and identification systems, due to its superior performance compared to normal antennas. Some of its finer characteristics include flexibility, reflection coefficient, bandwidth, directivity, gain, radiation, specific absorption rate (SAR), and efficiency that are anticipated to be influenced by the coupling and absorption by the human body tissues. Furthermore, improvements like band-gap structure and artificial magnetic conductors (AMC) and (DGS) are included in the wearable antenna that offers a high degree of isolation from the human body and significantly reduces SAR. In this paper, the development of on-body antennas and how they are affected by the human body were reviewed. Additionally, parameters that affect the performance of this new antenna model, such as materials and common technologies, are included as an auxiliary study for researchers to determine the factors affecting the performance of the wearable antenna and the access to a highly efficient antenna.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152470
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2471: Experimental Study of Thermal and
           

    • Authors: Oguzhan OZBALCI, Ayla DOGAN, Meltem ASILTURK
      First page: 2471
      Abstract: With the developing technology, the dimensions of electronic systems are becoming smaller, and their performance and the amount of energy they need increases. This situation causes the electronic components to heat up more and the existing cooling systems to become inadequate. In this study, instead of the fins used in existing systems, 10 PPI and 40 PPI PHS were placed inside a water block, and the Al2O3-H2O nanofluid at a mass fraction of 0.1% was used as the cooling fluid. Experiments were carried out under constant heat flux of 454.54 W/m2 and 1818.18 W/m2, with volumetric flow rates varying between 100 mL/min and 800 mL/min. The heat transfer results were compared with the results obtained from the base fluid and the empty surface. The results showed that the nanofluid reduced the surface temperatures compared to the base fluid. Especially when PHSs were used together with the nanofluid, a significant increase in heat transfer occurred compared to the empty surface. The highest heat transfer was observed when both the nanofluid and 40 PPI PHS were used together. In addition, the highest thermal performance value was determined as 1.25 times compared to the empty surface when the nanofluid and 10 PPI PHS were used together.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152471
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2472: Non-Linear Inductor Models Comparison
           for Switched-Mode Power Supplies Applications

    • Authors: Daniele Scirè, Giuseppe Lullo, Gianpaolo Vitale
      First page: 2472
      Abstract: The use of non-linear power inductors, intended as devices exploited up to a current at which the inductance is halved, is of great interest in switched-mode power supplies (SMPSs). Indeed, it allows the use of lighter and cheaper inductors improving the power density. On the other hand, the analysis of SMPSs equipped with non-linear inductors requires appropriate modeling of the inductor reproducing the inductance versus current. This paper compares two main analytical models proposed in the literature: the former is based on a polynomial, and the latter exploits the arctangent function to reproduce the non-linearity of the inductance. Performance is compared by considering the effort of retrieving the model’s parameters, evaluating a current profile by the characteristic equation of the inductor, and exploiting the two models to simulate a switched-mode power supply. Results are given both in terms of computation time and accuracy with reference to experimental values, highlighting the pros and cons of each model.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152472
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2473: A Study on Analysis Method for a
           Real-Time Neurofeedback System Using Non-Invasive Magnetoencephalography

    • Authors: Kazuhiro Yagi, Yuta Shibahara, Lindsey Tate, Hiroki Tamura
      First page: 2473
      Abstract: For diseases that affect brain function, such as strokes, post-onset rehabilitation plays a critical role in the wellbeing of patients. MEG is a technique with high temporal and spatial resolution that measures brain functions non-invasively, and it is widely used for clinical applications. Without the ability to concurrently monitor patient brain activity in real-time, the most effective rehabilitation cannot occur. To address this problem, it is necessary to develop a neurofeedback system that can aid rehabilitation in real time; however, doing so requires an analysis method that is quick (less processing time means the patient can better connect the feedback to their mental state), encourages brain-injured patients towards task-necessary neural oscillations, and allows for the spatial location of those oscillation patterns to change over the course of the rehabilitation. As preliminary work to establish such an analysis method, we compared three decomposition methods for their speed and accuracy in detecting event-related synchronization (ERS) and desynchronization (ERD) in a healthy brain during a finger movement task. We investigated FastICA with 10 components, FastICA with 20 components, and spatio-spectral decomposition (SSD). The results showed that FastICA with 10 components was the most suitable for real-time monitoring due to its combination of accuracy and analysis time.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152473
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2474: Classification and Identification Method
           of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order
           Spectrum Features

    • Authors: Bing Liu, Xinhong Hao, Pengfei Qian, Xin Cai, Wen Zhou
      First page: 2474
      Abstract: To overcome the problem of insufficiency of linear frequency modulation (LFM) radio fuzes against sweep-type jamming, a method is proposed to classify and identify radio fuze targets and interfering signals based on third-order spectrum features. Using the measured data of an LFM radio fuze, the third-order spectral transform is applied to the output signals of the detector end under the action of the target and several amplitude modulated sweeping interfering signals, and the amplitude mean value, third-order spectral amplitude entropy, and third-order spectral singular value entropy based on the third-order spectrum are extracted as three-dimensional features. The experimental results show that the classification and identification of targets and AM sweep-type interference using the third-order spectral features of the signal at the detector end has a high success rate, with a comprehensive identification accuracy of 98.33%.
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152474
      Issue No: Vol. 11, No. 15 (2022)
       
  • Electronics, Vol. 11, Pages 2475: The Transition Phenomenon of
           (1,0)-d-Regular (k, s)-SAT

    • Authors: Zufeng Fu, Haiying Wang, Jinjiang Liu, Jincheng Zhou, Daoyun Xu, Yihai Pi
      First page: 2475
      Abstract: For a d-regular (k,s)-CNF formula, a problem is to determine whether it has a (1,0)-super solution. If so, it is called (1,0)-d-regular (k,s)-SAT. A (1,0)-super solution is an assignment that satisfies at least two literals of each clause. When the value of any one of the variables is flipped, the (1,0)-super solution is still a solution. Super solutions have gained significant attention for their robustness. Here, a d-regular (k,s)-CNF formula is a special CNF formula with clauses of size exactly k, in which each variable appears exactly s-times, and the absolute frequency difference between positive and negative occurrences of each variable is at most a nonnegative integer d. Obviously, the structure of a d-regular (k,s)-CNF formula is much more regular than other formulas. In this paper, we certify that, for k≥5, there is a critical function φ(k,d) such that, if s≤φ(k,d), all d-regular (k,s)-CNF formulas have a (1,0)-super solution; otherwise (1,0)-d-regular (k,s)-SAT is NP-complete. By the Lopsided Local Lemma, we get an existence condition of (1,0)-super solutions and propose an algorithm to find the lower bound of φ(k,d).
      Citation: Electronics
      PubDate: 2022-08-08
      DOI: 10.3390/electronics11152475
      Issue No: Vol. 11, No. 15 (2022)
       
 
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