Electronics

18 pages, 1552 KiB

Open AccessArticle

Enhancement of E-Learning Student’s Performance Based on Ensemble Techniques

by Abdulkream A. Alsulami, Abdullah S. AL-Malaise AL-Ghamdi and Mahmoud Ragab

Electronics 2023, 12(6), 1508; https://doi.org/10.3390/electronics12061508 - 22 Mar 2023

Cited by 21 | Viewed by 2993

Educational institutions have dramatically increased in recent years, producing many graduates and postgraduates each year. One of the critical concerns of decision-makers is student performance. Educational data mining techniques are beneficial to explore uncovered data in data itself, creating a pattern to analyze [...] Read more.

Educational institutions have dramatically increased in recent years, producing many graduates and postgraduates each year. One of the critical concerns of decision-makers is student performance. Educational data mining techniques are beneficial to explore uncovered data in data itself, creating a pattern to analyze student performance. In this study, we investigate the student E-learning data that has increased significantly in the era of COVID-19. Thus, this study aims to analyze and predict student performance using information gathered from online systems. Evaluating the student E-learning data through the data mining model proposed in this study will help the decision-makers make informed and suitable decisions for their institution. The proposed model includes three traditional data mining methods, decision tree, Naive Bays, and random forest, which are further enhanced by the use of three ensemble techniques: bagging, boosting, and voting. The results demonstrated that the proposed model improved the accuracy from 0.75 to 0.77 when we used the DT method with boosting. Furthermore, the precision and recall results both improved from 0.76 to 0.78. Full article

(This article belongs to the Section Computer Science & Engineering)

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16 pages, 6093 KiB

Open AccessArticle

Near-Field Imaging of Dielectric Components Using an Array of Microwave Sensors

by Yuki Gao, Maryam Ravan and Reza K. Amineh

Electronics 2023, 12(6), 1507; https://doi.org/10.3390/electronics12061507 - 22 Mar 2023

Cited by 5 | Viewed by 2749

Abstract

Microwave imaging is a high-resolution, noninvasive, and noncontact method for detecting hidden defects, cracks, and objects with applications for testing nonmetallic components such as printed circuit boards, biomedical diagnosis, aerospace components inspection, etc. In this paper, an array of microwave sensors designed based [...] Read more.

Microwave imaging is a high-resolution, noninvasive, and noncontact method for detecting hidden defects, cracks, and objects with applications for testing nonmetallic components such as printed circuit boards, biomedical diagnosis, aerospace components inspection, etc. In this paper, an array of microwave sensors designed based on complementary split ring resonators (CSRR) are used to evaluate the hidden features in dielectric media with applications in nondestructive testing and biomedical diagnosis. In this array, each element resonates at a different frequency in the range of 1 GHz to 10 GHz. Even though the operating frequencies are not that high, the acquisition of evanescent waves in extreme proximity to the imaged object and processing them using near-field holographic imaging allows for obtaining high-resolution images. The performance of the proposed method is demonstrated through simulation and experimental results. Full article

(This article belongs to the Special Issue Applications of RF/Microwave/Millimeter-Wave/THz Imaging)

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17 pages, 13570 KiB

Open AccessReview

Review on Key Technologies and Development of Magnetic Coupling Resonant-Dynamic Wireless Power Transfer for Unmanned Ground Vehicles

by Feifan Xu, Shuguang Wei, Dong Yuan and Jiaqi Li

Electronics 2023, 12(6), 1506; https://doi.org/10.3390/electronics12061506 - 22 Mar 2023

Cited by 7 | Viewed by 2247

Abstract

With the fast development of magnetic coupling resonant-dynamic wireless power transfer (MCR-DWPT), it is more likely that high-efficiency wireless charging between unmanned ground vehicles (UGVs) will be practically realized, especially in desolate places that are far away from a city center or charging [...] Read more.

With the fast development of magnetic coupling resonant-dynamic wireless power transfer (MCR-DWPT), it is more likely that high-efficiency wireless charging between unmanned ground vehicles (UGVs) will be practically realized, especially in desolate places that are far away from a city center or charging depot and always experiencing large load fluctuations, varying operating conditions, and complex working targets. Based on this, the wireless charging of UGVs demands higher reliability and efficiency. This paper reviews the MCR-DWPT system of UGVs, and the basic structure and key technologies are introduced. Then, the key technologies, which include the coupling device design, compensation topology design, and system control strategy, are discussed in detail. After that, by considering the current research, the main challenges of the MCR-DWPT of UGVs are investigated and its developing prospects are explored. Full article

(This article belongs to the Topic Advanced Wireless Charging Technology)

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16 pages, 5072 KiB

Open AccessArticle

HTC-Grasp: A Hybrid Transformer-CNN Architecture for Robotic Grasp Detection

by Qiang Zhang, Jianwei Zhu, Xueying Sun and Mingmin Liu

Electronics 2023, 12(6), 1505; https://doi.org/10.3390/electronics12061505 - 22 Mar 2023

Cited by 13 | Viewed by 3295

Abstract

Accurately detecting suitable grasp areas for unknown objects through visual information remains a challenging task. Drawing inspiration from the success of the Vision Transformer in vision detection, the hybrid Transformer-CNN architecture for robotic grasp detection, known as HTC-Grasp, is developed to improve the [...] Read more.

Accurately detecting suitable grasp areas for unknown objects through visual information remains a challenging task. Drawing inspiration from the success of the Vision Transformer in vision detection, the hybrid Transformer-CNN architecture for robotic grasp detection, known as HTC-Grasp, is developed to improve the accuracy of grasping unknown objects. The architecture employs an external attention-based hierarchical Transformer as an encoder to effectively capture global context and correlation features across the entire dataset. Furthermore, a channel-wise attention-based CNN decoder is presented to adaptively adjust the weight of the channels in the approach, resulting in more efficient feature aggregation. The proposed method is validated on the Cornell and the Jacquard dataset, achieving an image-wise detection accuracy of 98.3% and 95.8% on each dataset, respectively. Additionally, the object-wise detection accuracy of 96.9% and 92.4% on the same datasets are achieved based on this method. A physical experiment is also performed using the Elite 6Dof robot, with a grasping accuracy rate of 93.3%, demonstrating the proposed method’s ability to grasp unknown objects in real scenarios. The results of this study indicate that the proposed method outperforms other state-of-the-art methods. Full article

(This article belongs to the Special Issue Recent Advances in Industrial Robots)

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17 pages, 817 KiB

Open AccessArticle

Query Join Order Optimization Method Based on Dynamic Double Deep Q-Network

by Lixia Ji, Runzhe Zhao, Yiping Dang, Junxiu Liu and Han Zhang

Electronics 2023, 12(6), 1504; https://doi.org/10.3390/electronics12061504 - 22 Mar 2023

Cited by 4 | Viewed by 3191

Abstract

A join order directly affects database query performance and computational overhead. Deep reinforcement learning (DRL) can explore efficient query plans while not exhausting the search space. However, the deep Q network (DQN) suffers from the overestimation of action values in query optimization, which [...] Read more.

A join order directly affects database query performance and computational overhead. Deep reinforcement learning (DRL) can explore efficient query plans while not exhausting the search space. However, the deep Q network (DQN) suffers from the overestimation of action values in query optimization, which can lead to limited query performance. In addition,

ε

-greedy exploration is not efficient enough and does not enable deep exploration. Accordingly, in this paper, we propose a dynamic double DQN (DDQN) order selection method(DDOS) for join order optimization. First, the method models the join query as a Markov decision process (MDP), then solves the DRL model by integrating the network model DQN and DDQN weighting into the DRL model’s estimation error problem in query joining, and finally improves the quality of developing query plans. And actions are selected using a dynamic progressive search strategy to improve the randomness and depth of exploration and accumulate a high information gain of exploration. The performance of the proposed method is compared with those of dynamic programming, heuristic algorithms, and DRL optimization methods based on the query set Join Order Benchmark (JOB). The experimental results show that the proposed method can effectively improve the query performance with a favorable generalization ability and robustness, and outperforms other baselines in multi-join query applications. Full article

(This article belongs to the Special Issue Advanced Techniques in Computing and Security)

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16 pages, 7425 KiB

Open AccessArticle

A Broadband Analog Predistortion Linearizer Based on GaAs MMIC for Ka-Band TWTAs

by Ting Liu, Xiaobao Su, Gang Wang, Bin Zhao, Rui Fu and Dan Zhu

Electronics 2023, 12(6), 1503; https://doi.org/10.3390/electronics12061503 - 22 Mar 2023

Cited by 4 | Viewed by 2515

Abstract

In this article, a Ka-band broadband analog predistortion (APD) microwave monolithic integrated circuit (MMIC) with independent tunability based on a 0.15 μm GaAs pHEMT process is proposed, which can be cascaded in front of traveling wave tube amplifiers (TWTAs) to improve their linearity. [...] Read more.

In this article, a Ka-band broadband analog predistortion (APD) microwave monolithic integrated circuit (MMIC) with independent tunability based on a 0.15 μm GaAs pHEMT process is proposed, which can be cascaded in front of traveling wave tube amplifiers (TWTAs) to improve their linearity. The influence of different diode sizes on the parameters of Schottky diodes is analyzed and used to design the gain and phase nonlinear branches. The broadband APD MMIC is realized based on a dual-branch vector synthesis design and nonlinear frequency adjust module (NFAM). The independent tunability and broadband characteristics of the APD MMIC are verified by simulated and measured results with an error of less than 5%. Furthermore, a Ka-band 60 W TWTA is linearized by the APD MMIC, and the gain and phase compressions are reduced from 8 dB and 50° to within 3 dB and 12°, respectively. The third-order intermodulation (C/IM3) is greater than 28 dBc and noise power ratio (NPR) is greater than 15.7 dBc at 3 dB output power backoff (OPBO) over the operating band of 25.1~27.5 GHz, indicating that the APD MMIC can improve the nonlinearity of TWTA effectively under broadband signals. Full article

(This article belongs to the Special Issue RF/Microwave Circuits for 5G and Beyond, Volume II)

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14 pages, 4746 KiB

Open AccessArticle

Long-Distance Person Detection Based on YOLOv7

by Fan Tang, Fang Yang and Xianqing Tian

Electronics 2023, 12(6), 1502; https://doi.org/10.3390/electronics12061502 - 22 Mar 2023

Cited by 37 | Viewed by 8711

Abstract

In the research field of small object detection, most object detectors have been successfully used for pedestrian detection, face recognition, lost and found, and automatic driving, among other applications, and have achieved good results. However, when general object detectors encounter challenging low-resolution images [...] Read more.

In the research field of small object detection, most object detectors have been successfully used for pedestrian detection, face recognition, lost and found, and automatic driving, among other applications, and have achieved good results. However, when general object detectors encounter challenging low-resolution images from the TinyPerson dataset, they will produce undesirable detection results because of the dense occlusion between people and different body poses. In order to solve these problems, this paper proposes a tiny object detection method TOD-YOLOv7 based on YOLOv7.First, this paper presents a reconstruction of the YOLOv7 network by adding a tiny object detection layer to enhance its detection ability. Then, we use the recursive gated convolution module to realize the interaction with the higher-order space to accelerate the model initialization process and reduce the reasoning time. Secondly, this paper proposes the integration of a coordinate attention mechanism into the YOLOv7 feature extraction network to strengthen the pedestrian object information and weaken the background information.Additionally, we leverage data augmentation techniques to improve the representation learning of the algorithm. The results show that compared with the baseline model YOLOv7, the detection accuracy of this model on the TinyPerson dataset is improved from 7.1% to 9.5%, and the detection speed reaches 208 frames per second (FPS). The algorithm of this paper is shown to achieve better detection results for tiny object detection. Full article

(This article belongs to the Special Issue Deep and Machine Learning for Image Processing: Medical and Non-medical Applications)

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13 pages, 10219 KiB

Open AccessArticle

Robust Graph Neural-Network-Based Encoder for Node and Edge Deep Anomaly Detection on Attributed Networks

by G. Victor Daniel, Kandasamy Chandrasekaran, Venkatesan Meenakshi and Prabhavathy Paneer

Electronics 2023, 12(6), 1501; https://doi.org/10.3390/electronics12061501 - 22 Mar 2023

Cited by 24 | Viewed by 3485

Abstract

The task of identifying anomalous users on attributed social networks requires the detection of users whose profile attributes and network structure significantly differ from those of the majority of the reference profiles. GNN-based models are well-suited for addressing the challenge of integrating network [...] Read more.

The task of identifying anomalous users on attributed social networks requires the detection of users whose profile attributes and network structure significantly differ from those of the majority of the reference profiles. GNN-based models are well-suited for addressing the challenge of integrating network structure and node attributes into the learning process because they can efficiently incorporate demographic data, activity patterns, and other relevant information. Aggregate operations, such as sum or mean pooling, are utilized by Graph Neural Networks (GNNs) to combine the representations of neighboring nodes within a graph. However, these aggregate operations can cause problems in detecting anomalous nodes. There are two main issues to consider when utilizing aggregate operations in GNNs. Firstly, the presence of anomalous neighboring nodes may affect the representation of normal nodes, leading to false positives. Secondly, anomalous nodes may be overlooked as their representation is flattened during the aggregate operation, leading to false negatives. The proposed approach, AnomEn, is a robust graph neural network developed for anomaly detection. It addresses the challenges of false positives and false negatives using a weighted aggregate mechanism. This mechanism is designed to differentiate between a node’s own features and the features of its neighbors by placing greater emphasis on a node’s own features and less emphasis on its neighbors’ features. The system can preserve the node’s original characteristics, whether the node is normal or anomalous. This work proposes not only a robust graph neural network, namely, AnomEn, but also specific anomaly detection structures for nodes and edges. The proposed AnomEn method serves as the encoder in the node and edge anomaly detection architectures and was tested on multiple datasets. Experiments were conducted to validate the effectiveness of the proposed method as a graph neural network encoder. The findings demonstrated the robustness of the proposed method in detecting anomalies. The proposed method outperforms other existing methods in node anomaly detection tasks by 5.63% and edge anomaly detection tasks by 7.87%. Full article

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15 pages, 8952 KiB

Open AccessArticle

State Parameter Estimation of Intelligent Vehicles Based on an Adaptive Unscented Kalman Filter

by Yu Wang, Yushan Li and Ziliang Zhao

Electronics 2023, 12(6), 1500; https://doi.org/10.3390/electronics12061500 - 22 Mar 2023

Cited by 12 | Viewed by 2648

Abstract

The premise of vehicle intelligent decision making is to obtain vehicle motion state parameters accurately and in real-time. Several state parameters cannot be measured directly by vehicle sensors, so estimation algorithms based on filtering are effective solutions. The most representative algorithm is the [...] Read more.

The premise of vehicle intelligent decision making is to obtain vehicle motion state parameters accurately and in real-time. Several state parameters cannot be measured directly by vehicle sensors, so estimation algorithms based on filtering are effective solutions. The most representative algorithm is the Kalman filter, especially the standard unscented Kalman filter (UKF) that has been widely used in vehicle state estimation because of its superiority in dealing with nonlinear filtering problems. However, although the UKF assumes that the noise statistics of the system are known, due to the complex and changeable operating conditions, sensor aging and other factors, these noises vary. In order to realize high-precision vehicle state estimation, a noise-adaptive UKF algorithm is proposed in this article. The maximum a posteriori (MAP) algorithm is used to dynamically update the noise of the vehicle system, and it is embedded into the update step of the UKF to form an adaptive unscented Kalman filter (AUKF). The system will dynamically update the noise when noise statistics are unknown and prevent filter divergence by adjusting the mean and covariance of the estimated noise to improve accuracy. On this basis, the proposed method is verified by the joint simulation of CarSim and Matlab/Simulink, confirming that the AUKF performs better than the standard UKF in estimation accuracy and stability under different degrees of noise disturbance, and the estimation accuracy for the yaw rate, side slip angle and longitudinal velocity is improved by 20.08%, 40.98% and 89.91%, respectively. Full article

(This article belongs to the Special Issue Feature Papers in Electrical and Autonomous Vehicles)

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14 pages, 2877 KiB

Open AccessArticle

AoI-Bounded Scheduling for Industrial Wireless Sensor Networks

by Chenggen Pu, Han Yang, Ping Wang and Changjie Dong

Electronics 2023, 12(6), 1499; https://doi.org/10.3390/electronics12061499 - 22 Mar 2023

Cited by 2 | Viewed by 2277

Abstract

Age of information (AoI) is an emerging network metric that measures information freshness from an application layer perspective. It can evaluate the timeliness of information in industrial wireless sensor networks (IWSNs). Previous research has primarily focused on minimizing the long-term average AoI of [...] Read more.

Age of information (AoI) is an emerging network metric that measures information freshness from an application layer perspective. It can evaluate the timeliness of information in industrial wireless sensor networks (IWSNs). Previous research has primarily focused on minimizing the long-term average AoI of the entire system. However, in practical industrial applications, optimizing the average AoI does not guarantee that the peak AoI of each data packet is within a bounded interval. If the AoI of certain packets exceeds the predetermined threshold, it can have a significant impact on the stability of the industrial control system. Therefore, this paper studies the scheduling problem subject to a hard AoI performance requirement in IWSNs. First, we propose a low-complexity AoI-bounded scheduling algorithm for IWSNs that guarantees that the AoI of each packet is within a bounded interval. Then, we analyze the schedulability conditions of the algorithm and propose a method to decrease the peak AoI of nodes with higher AoI requirements. Finally, we present a numerical example that illustrates the proposed algorithm step by step. The results demonstrate the effectiveness of our algorithm, which can guarantee bounded AoI intervals (BAIs) for all nodes. Full article

(This article belongs to the Special Issue Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends)

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13 pages, 1586 KiB

Open AccessArticle

A Real-Time, Open-Source, IoT-like, Wearable Monitoring Platform

by Andrea Baldini, Roberto Garofalo, Enzo Pasquale Scilingo and Alberto Greco

Electronics 2023, 12(6), 1498; https://doi.org/10.3390/electronics12061498 - 22 Mar 2023

Cited by 7 | Viewed by 3970

Abstract

The spread of informatics and electronic systems capable of the real-time monitoring of multiple psychophysiological signals has continuously grown in the last few years. In this study, we propose a novel open-source wearable monitoring platform (WMP) to synchronously acquire and process multiple physiological [...] Read more.

The spread of informatics and electronic systems capable of the real-time monitoring of multiple psychophysiological signals has continuously grown in the last few years. In this study, we propose a novel open-source wearable monitoring platform (WMP) to synchronously acquire and process multiple physiological signals in a real-time fashion. Specifically, we developed an IoT-like modular and fully open-source platform composed of two main blocks that on the one hand connect multiple devices (the sensor fusion unit) and on the other hand process and store the sensors’ data through the internet (the remote storing and processing unit). To test the proposed platform and its computational performance, 15 subjects underwent an experimental protocol, in which they were exposed to rest and stressful sessions implementing the Stroop Color and Word Test (SCWT). Statistical analysis was performed to verify whether the WMP could monitor the expected variations in the subjects’ psychophysiological state induced by the SCWT. The WMP showed very good computational performance for data streaming, remote storing, and real-time processing. Moreover, the experimental results showed that the platform was reliable when capturing physiological changes coherently with the emotional salience of the SCWT. Full article

(This article belongs to the Special Issue Digital Twin Technology: New Frontiers for Personalized Healthcare)

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20 pages, 1550 KiB

Open AccessArticle

Asset Ownership Transfer and Inventory Using RFID UHF TAGS and Ethereum Blockchain NFTs

by Cesar Munoz-Ausecha, Jorge Eliecer Gómez Gómez, Juan Ruiz-Rosero and Gustavo Ramirez-Gonzalez

Electronics 2023, 12(6), 1497; https://doi.org/10.3390/electronics12061497 - 22 Mar 2023

Cited by 3 | Viewed by 3084

Abstract

In the present, many organizations grow on a daily basis, using many assets to perform their activities and generate profit. In large organizations, all of these assets must be managed, occasionally leading to challenges depending on the organization’s size. For this reason, the [...] Read more.

In the present, many organizations grow on a daily basis, using many assets to perform their activities and generate profit. In large organizations, all of these assets must be managed, occasionally leading to challenges depending on the organization’s size. For this reason, the role of asset custodian is needed. This role entails assigning the fixed assets to one person for their care, maintenance, and safekeeping. In this process, it is necessary to update information in the central system, leading to further administrative processes, which, in the majority of cases, are carried out through traditional methods. This involves time to obtain wet signatures, a great deal of paperwork, and time for the person or people in charge to update the information. Due to these reasons, the process can be updated partially or entirely to use digital means in order to solve the mentioned inconveniences. This paper presents a proof-of-concept system to offer a modernized and practical solution to this problem using the advantages of blockchain technology, and speeding up the process by using assets identified with UHF RFID technology to permit the reading of many tags that can be embedded and hidden with no need for line-of-sight, allowing fast ownership transfer, using smart contracts in the Ethereum private blockchain. Full article

(This article belongs to the Special Issue Blockchain Technology and Distributed Applications (DApps))

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22 pages, 2018 KiB

Open AccessArticle

DC-Link Ripple Reduction for Parallel Inverter Systems by a Novel Formulation Using Multiple Space Vector-Based Interleaving Schemes

by Akbar Ali Khan, Nauman Ahmad Zaffar and Muhammad Jahangir Ikram

Electronics 2023, 12(6), 1496; https://doi.org/10.3390/electronics12061496 - 22 Mar 2023

Cited by 4 | Viewed by 2860

Abstract

This paper proposes an analytical formulation-based minimization of DC link current ripples for interleaved parallel inverter systems. Parallel inverter systems find applications in multiple fields. The interleaved superposition of the DC link currents in these systems can potentially be adjusted to mitigate the [...] Read more.

This paper proposes an analytical formulation-based minimization of DC link current ripples for interleaved parallel inverter systems. Parallel inverter systems find applications in multiple fields. The interleaved superposition of the DC link currents in these systems can potentially be adjusted to mitigate the overall harmonics consequently reducing the DC link capacitor size. To this end, a widely used approach in the literature is the Fourier analysis based on interleaving focusing on dominant harmonic mitigation. However, it leaves room for a generic analytical mechanism to provide time shifts leading to an optimal reduction in DC-link ripples. The goal of this work is to target this optimal reduction by utilizing an analytical mechanism. The paper presents an alternate way of DC-link formulation in terms of the piece-wise sinusoids of inverter output currents for space vector modulation-based systems. The formulation is then used to numerically optimize the interleaved shifts for minimum ripples. Moreover, in addition to the traditional concept of fixed time interleaving, a contemporary concept of sequence-based interleaving is utilized, which is anticipated to have more flexibility in the implementation and additional switching synchronism with PWM rectifiers for back–back converters. Therefore, the sequence interleaving has also been utilized in conjunction with the proposed ripple reduction methodology. Further, an underexplored area of using the combined impact of sequence and time interleaving has also been applied in this work. These interleaving methods are shown to provide significantly improved DC-link ripple mitigation, as compared to existing methods, using numerical assessment followed by simulations and experimental evaluation. Full article

(This article belongs to the Special Issue Selected Papers from Young Researchers in Energy Systems and Management)

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18 pages, 3190 KiB

Open AccessArticle

Statistical Characteristics of Differential Communication Scheme Based on Chaotic Radio Pulses

by Alexander Dmitriev, Anton Ryzhov and Christian Sierra-Teran

Electronics 2023, 12(6), 1495; https://doi.org/10.3390/electronics12061495 - 22 Mar 2023

Cited by 1 | Viewed by 1716

Abstract

The aim of this paper is to analyze statistical characteristics of the new differential communication scheme based on chaotic radio pulses in the presence of additive white noise (Gaussian) and using various distributions of instantaneous values of the chaotic signal. The characteristic feature [...] Read more.

The aim of this paper is to analyze statistical characteristics of the new differential communication scheme based on chaotic radio pulses in the presence of additive white noise (Gaussian) and using various distributions of instantaneous values of the chaotic signal. The characteristic feature of the presented scheme is the usage of significantly shorter time delays compared to the classical differential chaotic shift keying (DCSK) scheme. In order to investigate noise immunity of the direct chaotic differential communication (DC²) scheme, numerical statistical simulation is performed in terms of the bit error probability (BER) of the transmitted information. Then, the results of this simulation are compared to the results of analytical research. It is shown that due to the inherent internal noises of the scheme, the bit error probability (BER) for arbitrarily large values of the ratio of the signal energy to the Gaussian noise spectral density (E_b/N₀) is higher than 10⁻³ for the values of processing gain K < 30 for any distribution of instantaneous values of the chaotic signal. With the increase of the K values, there is a rapid decrease in BER in a system with a channel without white noise. Numeric simulation is performed, which verifies and clarifies the analytical estimates obtained earlier regarding the bit error probabilities as functions of processing gain and ratio of the signal energy to the Gaussian noise spectral density. The minimum values of E_b/N₀ are obtained, which provide necessary error probabilities with the processing gain set. It is shown that with a high processing gain (K > 30), the communication scheme considered here operates effectively both in a channel without fluctuation noises and in a channel with additive white Gaussian noise. The statistical characteristics of the proposed scheme do not depend on the choice of a particular distribution of instantaneous values of the chaotic signal. Taking into account that the scheme uses short delays, which do not depend on the processing gain of the used signal and are easily implemented, for example, on fragments of a high-frequency cable, the results obtained show good prospects for its implementation in a physical experiment. Full article

(This article belongs to the Special Issue Electronic Systems with Dynamic Chaos: Design and Applications)

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18 pages, 3116 KiB

Open AccessArticle

RSP-DST: Revisable State Prediction for Dialogue State Tracking

by Qianyu Li, Wensheng Zhang, Mengxing Huang, Siling Feng and Yuanyuan Wu

Electronics 2023, 12(6), 1494; https://doi.org/10.3390/electronics12061494 - 22 Mar 2023

Cited by 2 | Viewed by 2156

Abstract

Task-oriented dialogue systems depend on dialogue state tracking to keep track of the intentions of users in the course of conversations. Although recent models in dialogue state tracking exhibit good performance, the errors in predicting the value of each slot at the current [...] Read more.

Task-oriented dialogue systems depend on dialogue state tracking to keep track of the intentions of users in the course of conversations. Although recent models in dialogue state tracking exhibit good performance, the errors in predicting the value of each slot at the current dialogue turn of these models are easily carried over to the next turn, and unlikely to be revised in the next turn, resulting in error propagation. In this paper, we propose a revisable state prediction for dialogue state tracking, which constructs a two-stage slot value prediction process composed of an original prediction and a revising prediction. The original prediction process jointly models the previous dialogue state and dialogue context to predict the original dialogue state of the current dialogue turn. Then, in order to avoid the errors existing in the original dialogue state continuing to the next dialogue turn, a revising prediction process utilizes the dialogue context to revise errors, alleviating the error propagation. Experiments are conducted on MultiWOZ 2.0, MultiWOZ 2.1, and MultiWOZ 2.4 and results indicate that our model outperforms previous state-of-the-art works, achieving new state-of-the-art performances with 56.35, 58.09, and 75.65% joint goal accuracy, respectively, which has a significant improvement (2.15, 1.73, and 2.03%) over the previous best results. Full article

(This article belongs to the Special Issue Advances in Artificial Intelligence, Machine Learning and Deep Learning Application)

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17 pages, 16477 KiB

Open AccessArticle

Electromagnetic Characteristics and Capacity Analysis of a Radial–Axial Hybrid Magnetic Bearing with Two Different Radial Stators

by Mengyao Wu and Huangqiu Zhu

Electronics 2023, 12(6), 1493; https://doi.org/10.3390/electronics12061493 - 22 Mar 2023

Cited by 2 | Viewed by 1686

Abstract

Compared with the widely used four-pole magnetic bearings, three-pole magnetic bearings are driven by a three-phase power inverter and have advantages pertaining to their small volume, low costs, and low power losses. However, the asymmetric structure of the three-pole bearings presents disadvantages in [...] Read more.

Compared with the widely used four-pole magnetic bearings, three-pole magnetic bearings are driven by a three-phase power inverter and have advantages pertaining to their small volume, low costs, and low power losses. However, the asymmetric structure of the three-pole bearings presents disadvantages in terms of their strong nonlinearity and couplings among the suspension forces of the control currents and displacements. The radial–axial hybrid magnetic bearing (RAHMB) with six-pole bearings is proposed to solve this problem. Firstly, the structure and working principle of the RAHMB are introduced. Secondly, the mathematical models of the RAHMB are established, and in order to obtain the radial capacity, the maximum suspension forces of the three-pole and six-pole RAHMBs are theoretically analyzed. Thirdly, the nonlinearity and couplings of the suspension forces with the control currents and displacements are analyzed. The radial capacity of the three-pole and six-pole RAHMB is 74.6 N and 83.6 N, respectively, which is an increase of 12.0%. Finally, the experiment results prove that the nonlinearity and couplings of the six-pole RAHMB are smaller than the nonlinearity and couplings of the three-pole RAHMB, and the maximum radial capacity of the three-pole and six-pole RAHMB is 84.1 N and 94.8 N, respectively, which is an increase of 12.7%. The simulation results are basically consistent with the experimental results, indicating the correctness of the theoretical analysis. Full article

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33 pages, 19490 KiB

Open AccessArticle

Practical Implementation of an Analogue and Digital Electronics System for a Modular Cosmic Ray Detector—MCORD

by Marcin Bielewicz, Aleksandr Bancer, Andrzej Dziedzic, Jaroslaw Grzyb, Elzbieta Jaworska, Grzegorz Kasprowicz, Michal Kiecana, Piotr Kolasinski, Michal Kuc, Michal Kuklewski, Marcin Pietrzak, Krzysztof Pozniak, Maciej Sitek, Mikolaj Sowinski, Łukasz Świderski, Agnieszka Syntfeld-Kazuch, Jaroslaw Szewinski and Wojciech Marek Zabołotny

Electronics 2023, 12(6), 1492; https://doi.org/10.3390/electronics12061492 - 22 Mar 2023

Cited by 2 | Viewed by 2292

Abstract

A Modular COsmic Ray Detector (MCORD) was prepared for use in various physics experiments. MCORD detectors can be used in laboratory measurements or can become a part of large measurement sets. MCORD can be used as a muon detector, a veto system, or [...] Read more.

A Modular COsmic Ray Detector (MCORD) was prepared for use in various physics experiments. MCORD detectors can be used in laboratory measurements or can become a part of large measurement sets. MCORD can be used as a muon detector, a veto system, or a tool supporting the testing and calibration of other detectors. MCORD can also work as a stand-alone device for scientific and commercial purposes. The basic element of MCORD is one section consisting of eight oblong scintillators with a double-sided light reading performed by silicon photomultipliers (SiPMs). This work presents a practical description of testing, calibration, and programming of analogue and digital electronics modules. The characterisation and calibration methods of the analogue front-end electronic modules, the obtained results, and their implementation into an operating system are presented. In addition, we describe the development environment and the procedures used to prepare our kit for practical use. The architecture of the FPGAs is also presented with a description of their programming as a data-collecting system in a simple coincidence circuit. We also present the possibilities of extending the data analysis system for large experiments. Full article

(This article belongs to the Special Issue Electronics for Radiation Imaging, High Energy Physics and Plasma Experiments)

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23 pages, 8712 KiB

Open AccessArticle

System-Level Consideration and Multiphysics Design of Propulsion Motor for Fully Electrified Battery Powered Car Ferry Propulsion System

by Vu-Khanh Tran, Sarbajit Paul, Jae-Woon Lee, Jae-Hak Choi, Pil-Wan Han and Yon-Do Chun

Electronics 2023, 12(6), 1491; https://doi.org/10.3390/electronics12061491 - 22 Mar 2023

Cited by 2 | Viewed by 2777

Abstract

The Korean government is facing growing concern over the increasing levels of fine dust. A significant contribution to this problem comes from coastal vessels. To mitigate this, an electric ship propulsion system has been proposed as a solution to reduce air pollution. The [...] Read more.

The Korean government is facing growing concern over the increasing levels of fine dust. A significant contribution to this problem comes from coastal vessels. To mitigate this, an electric ship propulsion system has been proposed as a solution to reduce air pollution. The application of a fully electric propulsion system in a ship is challenging due to size, capacity limitations, and the cost investment of the battery system. To address the challenges of battery limitation and initial investment costs, the development and supply of removable battery supply systems (RBSSs) for fully electrified battery powered (F-EBP) car ferries are studied. A permanent magnet synchronous motor (PMSM) for the F-EBP car ferry using a roll-on/roll-off-type RBSS is developed in this work. Firstly, the concept of the F-EBP car ferry is discussed, and the specifications of the electric car ferry propulsion system are provided. Secondly, motor design and electromagnetic analysis are performed using finite-element analysis (FEA), where the heat sources including copper loss, core loss, and PM loss are calculated. Mechanical loss is also considered. Finally, a thermal network of the motor is built considering the lumped-parameter model. The results of the thermal analysis indicate that the motor operates within the safe region and can perform well in rated working conditions. Full article

(This article belongs to the Special Issue Electromechanical Actuators and Sensors Targeting Mechatronics in the Smart Industry)

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14 pages, 6333 KiB

Open AccessArticle

Two-Stage Generator Network for High-Quality Image Inpainting in Future Internet

by Peng Zhao, Dan Zhang, Shengling Geng and Mingquan Zhou

Electronics 2023, 12(6), 1490; https://doi.org/10.3390/electronics12061490 - 22 Mar 2023

Viewed by 2139

Abstract

Sharpness is an important factor for image inpainting in future Internet, but the massive model parameters involved may produce insufficient edge consistency and reduce image quality. In this paper, we propose a two-stage transformer-based high-resolution image inpainting method to address this issue. This [...] Read more.

Sharpness is an important factor for image inpainting in future Internet, but the massive model parameters involved may produce insufficient edge consistency and reduce image quality. In this paper, we propose a two-stage transformer-based high-resolution image inpainting method to address this issue. This model consists of a coarse and a fine generator network. A self-attention mechanism is introduced to guide the transformation of higher-order semantics across the network layers, accelerate the forward propagation and reduce the computational cost. An adaptive multi-head attention mechanism is applied to the fine network to control the input of the features in order to reduce the redundant computations during training. The pyramid and perception are fused as the loss function of the generator network to improve the efficiency of the model. The comparison with Pennet, GapNet and Partial show the significance of the proposed method in reducing parameter scale and improving the resolution and texture details of the inpainted image. Full article

(This article belongs to the Topic Future Internet Architecture: Difficulties and Opportunities)

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17 pages, 730 KiB

Open AccessArticle

A Novel Data Partitioning Method for Active Privacy Protection Applied to Medical Records

by Nawaf Alharbe, Abeer Aljohani and Mohamed Ali Rakrouki

Electronics 2023, 12(6), 1489; https://doi.org/10.3390/electronics12061489 - 22 Mar 2023

Cited by 3 | Viewed by 2136

Abstract

In recent years, cloud computing has attracted extensive attention from industry and academia due to its convenience and ubiquity. As a new Internet-based IT service model, cloud computing has brought revolutionary changes to traditional computing and storage services. More and more individual users [...] Read more.

In recent years, cloud computing has attracted extensive attention from industry and academia due to its convenience and ubiquity. As a new Internet-based IT service model, cloud computing has brought revolutionary changes to traditional computing and storage services. More and more individual users and enterprises are willing to deploy their own data and applications on the cloud platform, but the accompanying security issues have also become an obstacle to the development of cloud computing. Multi-tenancy and virtualization technologies are the main reasons why cloud computing faces many security problems. Through the virtualization of storage resources, multi-tenant data are generally stored as shared physical storage resources. To distinguish the data of different tenants, labels are generally used to distinguish them. However, this simple label cannot resist the attack of a potential malicious tenant, and data still has the risk of leakage. Based on this, this paper proposed a data partitioning method in a multi-tenant scenario to prevent privacy leakage of user data. We demonstrate the use of the proposed approach in protecting patient data in medical records in health informatics. Experiments show that the proposed algorithm can partition the attributes more fine-grained and effectively protect the sensitive information in the data. Full article

(This article belongs to the Section Artificial Intelligence)

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18 pages, 2230 KiB

Open AccessArticle

Nonlinear Simulation and Performance Characterisation of an Adaptive Model Predictive Control Method for Booster Separation and Re-Entry

by Joseph Chai and Erkan Kayacan

Electronics 2023, 12(6), 1488; https://doi.org/10.3390/electronics12061488 - 21 Mar 2023

Viewed by 1633

Abstract

This paper evaluates the

L_{1}

adaptive model predictive control (AMPC-

L_{1}

) method in terms of its control performance and computational load. The control performance is assessed on the basis of the nonlinear simulation of a fly-back booster conducting stage separation [...] Read more.

This paper evaluates the

L_{1}

adaptive model predictive control (AMPC-

L_{1}

) method in terms of its control performance and computational load. The control performance is assessed on the basis of the nonlinear simulation of a fly-back booster conducting stage separation and re-entry, and compared to baseline nonadaptive MPC and as a pole placement controller in both longitudinal and lateral control tasks. Simulation results show that AMPC-

L_{1}

exhibits superior control performance under nominal conditions, and aerodynamic and guidance law uncertainties. The computational load of AMPC-

L_{1}

is also evaluated on an embedded platform to demonstrate that AMPC-

L_{1}

preserves the efficiency properties of AMPC while improving its performance. Full article

(This article belongs to the Special Issue Advanced Nonlinear and Learning-Based Control Techniques for Complex Dynamical Systems)

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14 pages, 2088 KiB

Open AccessArticle

NS-GAAFET Compact Modeling: Technological Challenges in Sub-3-nm Circuit Performance

by Fabrizio Mo, Chiara Elfi Spano, Yuri Ardesi, Massimo Ruo Roch, Gianluca Piccinini and Marco Vacca

Electronics 2023, 12(6), 1487; https://doi.org/10.3390/electronics12061487 - 21 Mar 2023

Cited by 7 | Viewed by 5086

Abstract

NanoSheet-Gate-All-Around-FETs (NS-GAAFETs) are commonly recognized as the future technology to push the digital node scaling into the sub-3 nm range. NS-GAAFETs are expected to replace FinFETs in a few years, as they provide highly electrostatic gate control thanks to the GAA structure, with [...] Read more.

NanoSheet-Gate-All-Around-FETs (NS-GAAFETs) are commonly recognized as the future technology to push the digital node scaling into the sub-3 nm range. NS-GAAFETs are expected to replace FinFETs in a few years, as they provide highly electrostatic gate control thanks to the GAA structure, with four sides of the NS channel entirely enveloped by the gate. At the same time, the NS rectangular cross-section is demonstrated to be effective in its driving strength thanks to its high saturation current, tunable through the NS width used as a design parameter. In this work, we develop a NS-GAAFET compact model and we use it to link peculiar single-device parameters to digital circuit performance. In particular, we use the well-known BSIM-CMG core solver for multigate transistors as a starting point and develop an ad hoc resistive and capacitive network to model the NS-GAAFET geometrical and physical structure. Then, we employ the developed model to design and optimize a digital inverter and a five-stage ring oscillator, which we use as a performance benchmark for the NS-GAAFET technology. Through Cadence Virtuoso SPICE simulations, we investigate the digital NS-GAAFET performance for both high-performance and low-power nodes, according to the average future node present in the International Roadmap for Devices and Systems. We focus our analysis on the main different technological parameters with regard to FinFET, i.e., the inner and outer spacers. Our results highlight that in future technological nodes, the choice of alternative low-K dielectric materials for the NS spacers will assume increasing importance, being as relevant, or even more relevant, than photolithographic alignment and resolution at the sub-nm scale. Full article

(This article belongs to the Special Issue Advances in RF, Analog, and Mixed Signal Circuits)

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15 pages, 685 KiB

Open AccessEditor’s ChoiceArticle

Knowledge-Guided Prompt Learning for Few-Shot Text Classification

by Liangguo Wang, Ruoyu Chen and Li Li

Electronics 2023, 12(6), 1486; https://doi.org/10.3390/electronics12061486 - 21 Mar 2023

Cited by 7 | Viewed by 5530

Abstract

Recently, prompt-based learning has shown impressive performance on various natural language processing tasks in few-shot scenarios. The previous study of knowledge probing showed that the success of prompt learning contributes to the implicit knowledge stored in pre-trained language models. However, how this implicit [...] Read more.

Recently, prompt-based learning has shown impressive performance on various natural language processing tasks in few-shot scenarios. The previous study of knowledge probing showed that the success of prompt learning contributes to the implicit knowledge stored in pre-trained language models. However, how this implicit knowledge helps solve downstream tasks remains unclear. In this work, we propose a knowledge-guided prompt learning method that can reveal relevant knowledge for text classification. Specifically, a knowledge prompting template and two multi-task frameworks were designed, respectively. The experiments demonstrated the superiority of combining knowledge and prompt learning in few-shot text classification. Full article

(This article belongs to the Special Issue Natural Language Processing and Information Retrieval)

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19 pages, 2296 KiB

Open AccessEditor’s ChoiceArticle

Integration of Farm Financial Accounting and Farm Management Information Systems for Better Sustainability Reporting

by Krijn Poppe, Hans Vrolijk and Ivor Bosloper

Electronics 2023, 12(6), 1485; https://doi.org/10.3390/electronics12061485 - 21 Mar 2023

Cited by 13 | Viewed by 8734

Abstract

Farmers face an increasing administrative burden as agricultural policies and certification systems of trade partners ask for more sustainability reporting. Several indicator frameworks have been developed to measure sustainability, but they often lack empirical operationalization and are not always measured at the farm [...] Read more.

Farmers face an increasing administrative burden as agricultural policies and certification systems of trade partners ask for more sustainability reporting. Several indicator frameworks have been developed to measure sustainability, but they often lack empirical operationalization and are not always measured at the farm level. The research gap we address in this paper is the empirical link between the data needs for sustainability reporting and the developments in data management at the farm level. Family farms do not collect much data for internal management, but external demand for sustainability data can partly be fulfilled by reorganizing data management in the farm office. The Farm Financial Accounts (FFAs) and Farm Management Information Systems (FMISs) are the main data sources in the farm office. They originate from the same source of note-taking by farmers but became separated when formalized and computerized. Nearly all European farms have a bank account and must keep financial accounts (e.g., for Value-Added Tax or income tax) that can be audited. Financial accounts are not designed for environmental accounting or calculating sustainability metrics but provide a wealth of information to make assessments on these subjects. FMISs are much less frequently used but collect more technical and fine-grained data at crop or enterprise level for different fields. FMISs are also strong in integrating sensor and satellite data. Integrating data availability and workflows of FFAs and FMISs makes sustainability reporting less cumbersome regarding data entry and adds valuable data to environmental accounts. This paper applies a design science approach to design an artifact, a dashboard for sustainability reporting based on the integration of information flows from farm financial accounting systems and farm management information systems. The design developed in this paper illustrates that if invoices were digitized, most data-gathering needed for external sustainability reporting would automatically be done when the invoices is paid by a bank transfer. Data on the use of inputs and production could be added with procedures as in current FMISs, but with less data entry, fewer risks of differences in outcomes, and possibilities of cross-checking the results. Full article

(This article belongs to the Special Issue The Role of Digital Technologies in Sustainability Accounting and Reporting)

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26 pages, 3084 KiB

Open AccessArticle

A Blockchained AutoML Network Traffic Analyzer to Industrial Cyber Defense and Protection

by Alexandros Papanikolaou, Aggelos Alevizopoulos, Christos Ilioudis, Konstantinos Demertzis and Konstantinos Rantos

Electronics 2023, 12(6), 1484; https://doi.org/10.3390/electronics12061484 - 21 Mar 2023

Cited by 3 | Viewed by 3474

Abstract

Network traffic analysis can raise privacy concerns due to its ability to reveal sensitive information about individuals and organizations. This paper proposes a privacy-preserving Block-chained AutoML Network Traffic Analyzer (BANTA). The system securely stores network traffic logs in a decentralized manner, providing transparency [...] Read more.

Network traffic analysis can raise privacy concerns due to its ability to reveal sensitive information about individuals and organizations. This paper proposes a privacy-preserving Block-chained AutoML Network Traffic Analyzer (BANTA). The system securely stores network traffic logs in a decentralized manner, providing transparency and security. Differential privacy algorithms protect sensitive information in the network flow logs while allowing administrators to analyze network traffic without the risk of leakages. The BANTA uses blockchain technology, where smart contracts automate the process of network traffic analysis, and a multi-signature system ensures the system’s security, safety, and reliability. The proposed approach was evaluated using a real-world network traffic dataset. The results demonstrate the system’s high accuracy and real-time anomaly detection capabilities, which makes it well-suited for scalable cybersecurity operations. The system’s privacy protection, decentralized storage, automation, multi-signature system, and real-world effectiveness ensure that the organization’s data is private, secure, and effectively protected from cyber threats, which are the most vexing issue of modern cyber-physical systems. Full article

(This article belongs to the Special Issue Advances in Cryptography and Blockchain for Securing Modern Smart Communications)

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4 pages, 159 KiB

Open AccessEditorial

AICAS—PAST, PRESENT, AND FUTURE

by Valeri Mladenov

Electronics 2023, 12(6), 1483; https://doi.org/10.3390/electronics12061483 - 21 Mar 2023

Cited by 2 | Viewed by 1383

Abstract

Artificial intelligence circuits and systems (AICAS) are electronic circuits and systems designed to solve artificial intelligence (AI) problems and perform tasks [...] Full article

(This article belongs to the Section Artificial Intelligence Circuits and Systems (AICAS))

27 pages, 11262 KiB

Open AccessFeature PaperArticle

Theoretical and Experimental Comparative Analysis of Finite Control Set Model Predictive Control Strategies

by Breno Ventorim Comarella, Daniel Carletti, Imene Yahyaoui and Lucas Frizera Encarnação

Electronics 2023, 12(6), 1482; https://doi.org/10.3390/electronics12061482 - 21 Mar 2023

Cited by 9 | Viewed by 2468

Abstract

This research paper studies and highlights the features of the most popular finite control set model predictive control (FCS-MPC) strategies available in the state of the art, which are the optimal switching vector (OSV-MPC), modulated model predictive control (M2PC), and optimal switching sequence [...] Read more.

This research paper studies and highlights the features of the most popular finite control set model predictive control (FCS-MPC) strategies available in the state of the art, which are the optimal switching vector (OSV-MPC), modulated model predictive control (M2PC), and optimal switching sequence (OSS-MPC) methods. Thus, these strategies are studied experimentally by analyzing the transient and steady state performance using a grid tie conventional three-phase two-level voltage source inverter (VSI) with inductive output filter in a Typhoon HIL real-time simulator (RTS) with a Texas Instruments F28379D digital signal processor (DSP). Hence, quantitative indicators, such as the maximum tracking error, the mean absolute error, the settling time, the total harmonic distortion, the switching frequency spectrum, the switching pattern, and the computational burden are compared with the aim to deduce the best strategy for each criteria. Full article

(This article belongs to the Special Issue Advances in Model Predictive Control for Power Electronics)

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21 pages, 2220 KiB

Open AccessArticle

STATCOM Switching Technique Based on a Finite-State Machine

by César Contreras, Juan C. Quirós, Inmaculada Casaucao, Alicia Triviño, Eliseo Villagrasa and José A. Aguado

Electronics 2023, 12(6), 1481; https://doi.org/10.3390/electronics12061481 - 21 Mar 2023

Viewed by 2063

Abstract

The Voltage Source Converter (VSC) is the basis of STATCOMs and other power systems. It is composed of a three-phase inverter in which the activation of the switching devices must be controlled to generate the intended signals. The control technique used to switch [...] Read more.

The Voltage Source Converter (VSC) is the basis of STATCOMs and other power systems. It is composed of a three-phase inverter in which the activation of the switching devices must be controlled to generate the intended signals. The control technique used to switch the power devices affects the performance of the converter in terms of harmonic distortion mainly. Although some complex modulation techniques have been proposed in the related literature, local controllers opt for simpler methods as they provide robustness and they ease the implementation. In this paper, we propose a simple but effective technique to switch the transistors of a three-phase inverter with a Space Vector Modulation (SVM) supported by a Finite-State Machine (FSM). With this model, the switching technique can be easily implemented in low-cost microcontrollers with reduced memory and computational resources if code optimisation is performed. With an electrical analysis, we have designed a low-pass band filter adequate for the proposed switching technique. In a laboratory prototype, the performance of this proposal is evaluated under static and dynamic conditions. When compared with other control techniques (classical SVM and PWM), we conclude that a similar harmonic distortion is achieved. Full article

(This article belongs to the Topic Power Electronics Converters)

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13 pages, 2112 KiB

Open AccessArticle

MFSR: Light Field Images Spatial Super Resolution Model Integrated with Multiple Features

by Jianfei Zhou and Hongbing Wang

Electronics 2023, 12(6), 1480; https://doi.org/10.3390/electronics12061480 - 21 Mar 2023

Viewed by 2311

Abstract

Light Field (LF) cameras can capture angular and spatial information simultaneously, making them suitable for a wide range of applications such as refocusing, disparity estimation, and virtual reality. However, the limited spatial resolution of the LF images hinders their applicability. In order to [...] Read more.

Light Field (LF) cameras can capture angular and spatial information simultaneously, making them suitable for a wide range of applications such as refocusing, disparity estimation, and virtual reality. However, the limited spatial resolution of the LF images hinders their applicability. In order to address this issue, we propose an end-to-end learning-based light field super-resolution (LFSR) model called MFSR, which integrates multiple features, including spatial, angular, epipolar plane images (EPI), and global features. These features are extracted separately from the LF image and then fused together to obtain a comprehensive feature using the Feature Extract Block (FE Block) iteratively. Gradient loss is added into the loss function to ensure that the MFSR has good performance for LF images with rich texture. Experimental results on synthetic and real-world datasets demonstrate that the proposed method outperforms other state-of-the-art methods, with a peak signal-to-noise ratio (PSNR) improvement of 0.208 dB and 0.274 dB on average for the 2× and 4× super-resolution tasks, and structural similarity (SSIM) of both improvements of 0.01 on average. Full article

(This article belongs to the Special Issue Deep Learning in Computer Vision and Image Processing)

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24 pages, 3473 KiB

Open AccessReview

Blockchain-Based New Business Models: A Systematic Review

by Hamed Taherdoost and Mitra Madanchian

Electronics 2023, 12(6), 1479; https://doi.org/10.3390/electronics12061479 - 21 Mar 2023

Cited by 22 | Viewed by 20637

Abstract

The role of blockchain in new business model development requires greater focus because the technology is still in its infancy. Thus, there has been little research on the effects of the various blockchain networks (such as public, private, and consortium). This finding prompted [...] Read more.

The role of blockchain in new business model development requires greater focus because the technology is still in its infancy. Thus, there has been little research on the effects of the various blockchain networks (such as public, private, and consortium). This finding prompted a thorough investigation of new blockchain-based business models created between 2012 and 2022 to close this gap. This review’s focus is on journals, and duplicate articles have been removed. Works based on interviews, articles in press, non-English articles, reviews, conferences, book chapters, dissertations, and monographs are also not included. Seventy-five papers from the past ten years are included in this evaluation. This study examines the current state of new blockchain-based business models. Additionally, the implications and applications in the related literature have been investigated. These findings highlight numerous open research questions and promising new directions for investigation, which will likely be helpful to academics and professionals. The business strategies built on blockchain are currently on a path with a rapid upward trajectory. Blockchain technology offers businesses numerous chances to modify and develop new company models. By changing the conventional framework, blockchain innovation leads to the development of new methods for developing company models. The supportive potential of blockchain technologies such as NFT and P2E is increasingly being coupled with the development of new corporate projects and the modification of current business models. Since this field of study is still fairly new, researchers will have fresh opportunities to analyze its characteristics. Full article

(This article belongs to the Special Issue Advancement in Blockchain Technology and Applications)

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