Electronics

18 pages, 4123 KiB

Open AccessArticle

Optimal Pitch Angle Controller for DFIG-Based Wind Turbine System Using Computational Optimization Techniques

by Arsalan Khurshid, Muhammad Ali Mughal, Achraf Othman, Tawfik Al-Hadhrami, Harish Kumar, Imtinan Khurshid, Arshad and Jawad Ahmad

Electronics 2022, 11(8), 1290; https://doi.org/10.3390/electronics11081290 - 18 Apr 2022

Cited by 7 | Viewed by 2400

Abstract

With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum wind power in a wind turbine system (WTS). The pitch [...] Read more.

With the advent of high-speed and parallel computing, the applicability of computational optimization in engineering problems has increased, with greater validation than conventional methods. Pitch angle is an effective variable in extracting maximum wind power in a wind turbine system (WTS). The pitch angle controller contributes to improve the output power at different wind speeds. In this paper, the pitch angle controller with proportional (P) and proportional-integral (PI) controllers is used. The parameters of the controllers are tuned by computational optimization techniques for a doubly-fed induction generator (DFIG)-based WTS. The study is carried out on a 9 MW DFIG based WTS model in MATLAB/SIMULINK. Two computational optimization techniques: particle swarm optimization (PSO), a swarm intelligence algorithm, and a genetic algorithm (GA), an evolutionary algorithm, are applied. A multi-objective, multi-dimensional error function is defined and minimized by selecting an appropriate error criterion for each objective of the function which depicts the relative magnitude of each objective in the error function. The results of the output power flow and the dynamic response of the optimized P and PI controllers are compared with the conventional P and PI controller in three different cases. It is revealed that the PSO-based controllers performed better in comparison with both the conventional controllers and the GA-based controllers. Full article

(This article belongs to the Special Issue Cyber-Physical Security in Smart Grids: System Analysis and Control Design)

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9 pages, 2559 KiB

Open AccessArticle

Two-Path 77-GHz PA in 28-nm FD-SOI CMOS for Automotive Radar Applications

by Claudio Nocera, Giuseppe Papotto and Giuseppe Palmisano

Electronics 2022, 11(8), 1289; https://doi.org/10.3390/electronics11081289 - 18 Apr 2022

Cited by 2 | Viewed by 2038

Abstract

This paper presents a 77 GHz two path power amplifier (PA) for automotive radar applications. It was fabricated in 28-nm fully depleted silicon-on-insulator CMOS technology, which provides transistors with a transition frequency of about 270 GHz and a general-purpose low cost back-end-of-line. The [...] Read more.

This paper presents a 77 GHz two path power amplifier (PA) for automotive radar applications. It was fabricated in 28-nm fully depleted silicon-on-insulator CMOS technology, which provides transistors with a transition frequency of about 270 GHz and a general-purpose low cost back-end-of-line. The proposed PA consists of a 50 Ω input buffer followed by two power units, which are made up of a current-reuse common source driver for improved efficiency and a stacked cascode power stage for enhanced output power. A peak detector was also embedded into the PA for output power monitoring. The designed PA achieved a saturated output power as high as 17.4 dBm at 77 GHz with an excellent power added efficiency of 19%, while drawing 150 mA from a 2 V power supply. The core die size was 500 μm × 300 μm. Full article

(This article belongs to the Special Issue Millimeter-Wave-Integrated CMOS Radars and Communication Systems: Architecture and Circuit Designs)

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13 pages, 2260 KiB

Open AccessArticle

MRI Segmentation of Brain Tissue and Course Classification in Alzheimer’s Disease

by Meimei Li, Chunhai Hu, Zhen Liu and Ying Zhou

Electronics 2022, 11(8), 1288; https://doi.org/10.3390/electronics11081288 - 18 Apr 2022

Cited by 4 | Viewed by 2170

Abstract

Alzheimer’s disease (AD) is one of the most common diseases causing cognitive impairment in middle-aged and elderly people, and the high cost of the disease poses a challenge for health systems to cope with the expected increasing number of cases in the future. [...] Read more.

Alzheimer’s disease (AD) is one of the most common diseases causing cognitive impairment in middle-aged and elderly people, and the high cost of the disease poses a challenge for health systems to cope with the expected increasing number of cases in the future. With the advance of aging of the society, China has the largest number of Alzheimer’s disease patients in the world. Therefore, how to diagnose Alzheimer’s disease early and accurately and intervene positively is an urgent problem. In this paper, the improved MultiRes + UNet network is used to effectively segment the brain tissue in the preprocessing. This method expands the convolutional field by null convolution to integrate the global information, mitigates the differences between encoder–decoder features by using MultiRes block and Res path structure, greatly reducing the memory requirement, and improving its accuracy, applicability, and robustness. The non-local means the attention model is introduced to make the mapped organization categories free from noise interference. In the classification problem, this paper adopts the improved VoxCNN network model for binary classification of AD, EMCI, LMCI, and NC. Experiments showed that the model classification performance and the accuracy rate improved significantly with the combined effect of the improved MultiRes + UNet network and VoxCNN network, the binary classification accuracy was 98.35% for AD vs. NC, 89.46% for AD vs. LMCI, 83.95% for LMCI vs. EMCI, and 88.27% for EMCI vs. NC. Full article

(This article belongs to the Section Artificial Intelligence)

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33 pages, 1049 KiB

Open AccessArticle

Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Alternating Current Networks

by Andrés Alfonso Rosales Muñoz, Luis Fernando Grisales-Noreña, Jhon Montano, Oscar Danilo Montoya and Alberto-Jesus Perea-Moreno

Electronics 2022, 11(8), 1287; https://doi.org/10.3390/electronics11081287 - 18 Apr 2022

Cited by 5 | Viewed by 1800

Abstract

In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks [...] Read more.

In this paper, we solve the optimal power flow problem in alternating current networks to reduce power losses. For that purpose, we propose a master–slave methodology that combines the multiverse optimization algorithm (master stage) and the power flow method for alternating current networks based on successive approximation (slave stage). The master stage determines the level of active power to be injected by each distributed generator in the network, and the slave stage evaluates the impact of the proposed solution on each distributed generator in terms of the objective function and the constraints. For the simulations, we used the 10-, 33-, and 69-node radial test systems and the 10-node mesh test system with three levels of distributed generation penetration: 20%, 40%, and 60% of the power provided by the slack generator in a scenario without DGs. In order to validate the robustness and convergence of the proposed optimization algorithm, we compared it with four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: Particle Swarm Optimization, the Continuous Genetic Algorithm, the Black Hole Optimization algorithm, and the Ant Lion Optimization algorithm. The results obtained demonstrate that the proposed master–slave methodology can find the best solution (in terms of power loss reduction, repeatability, and technical conditions) for networks of any size while offering excellent performance in terms of computation time. Full article

(This article belongs to the Special Issue Feature Papers in Industrial Electronics)

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14 pages, 2244 KiB

Open AccessArticle

Modeling and Extended State Observer-Based Backstepping Control of Underwater Electro Hydrostatic Actuator with Pressure Compensator and External Load

by Yong Nie, Jiajia Liu, Zhenhua Lao and Zheng Chen

Electronics 2022, 11(8), 1286; https://doi.org/10.3390/electronics11081286 - 18 Apr 2022

Cited by 6 | Viewed by 2146

Abstract

Electro hydrostatic actuator (EHA) has been successfully developed for flight control applications to replace the cumbersome centralized hydraulic system. It also has excellent potential for ocean applications due to its advantages on miniaturization and energy-savings. One of the special technologies for EHA’s underwater [...] Read more.

Electro hydrostatic actuator (EHA) has been successfully developed for flight control applications to replace the cumbersome centralized hydraulic system. It also has excellent potential for ocean applications due to its advantages on miniaturization and energy-savings. One of the special technologies for EHA’s underwater application is pressure compensation, which is used to equalize the return pressure of the hydraulic system and the seawater pressure. This paper investigates the modeling and control design of underwater EHA to improve performance, especially considering the effect of additional pressure compensator and uncertain external load. The nonlinear hydraulic model is extended by the dynamic characteristics of the pressure compensator. Two low-order extended state observers were constructed to cope with the external load fore and the effect of the pressure compensator, respectively. The backstepping methods were designed to guarantee the robust stability of the entire high-order nonlinear hydraulic system. Finally, the theoretical proving and simulation on Matlab/Simulink are conducted to demonstrate the high tracking performance of the proposed control strategy. Full article

(This article belongs to the Special Issue High Performance Control and Industrial Applications)

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17 pages, 5353 KiB

Open AccessArticle

Comparative Study of Discrete PI and PR Controller Implemented in SRG for Wind Energy Application: Theory and Experimentation

by Zeineb Touati, Manuel Pereira, Rui Esteves Araújo and Adel Khedher

Electronics 2022, 11(8), 1285; https://doi.org/10.3390/electronics11081285 - 18 Apr 2022

Cited by 9 | Viewed by 1801

Abstract

The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant [...] Read more.

The Switched Reluctance Generator (SRG) has been widely studied for Wind Energy Conversion Systems (WECS). However, a major drawback of the SRG system adopting the conventional control is the slow response of the DC link voltage controller. In this paper, a Proportional Resonant (PR) control strategy is proposed to control the output voltage of the SRG system to improve the fast response. The SRG model has a high non-linearity, which makes the design of controllers a difficult task. For this reason, the important practical engineering aspect of this work is the role played by the SRG model linearization in testing the sensitivity of the PR controller performance to specific parameter changes. The characteristics of steady-state behaviors of the SRG-based WECS under different control approaches are simulated and compared. The controller is implemented on a digital signal processor (TMS320F28379D). The experimental results are carried out using a 250 W 8/6 SRG prototype to assess the performance of the proposed control compared with the traditional Proportional Integral (PI) control strategy. The experimental results show that the PR control enhances the steady-state performance of the SR power generation system in WECS. Compared to PI control, the rise and settling times are reduced by 45% and 43%, respectively, without an overshoot. Full article

(This article belongs to the Special Issue Feature Papers in Industrial Electronics)

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17 pages, 2950 KiB

Open AccessArticle

Prediction of Content Success and Cloud-Resource Management in Internet-of-Media-Things Environments

by Yeon-Su Lee, Ye-Seul Lee, Hye-Rim Jang, Soo-Been Oh, Yong-Ik Yoon and Tai-Won Um

Electronics 2022, 11(8), 1284; https://doi.org/10.3390/electronics11081284 - 18 Apr 2022

Cited by 5 | Viewed by 1851

Abstract

In Internet-of-Media-Things (IoMT) environments, users can access and view high-quality Over-the-Top (OTT) media services anytime and anywhere. As the number of OTT platform users has increased, the original content offered by such OTT platforms has become very popular, further increasing the number of [...] Read more.

In Internet-of-Media-Things (IoMT) environments, users can access and view high-quality Over-the-Top (OTT) media services anytime and anywhere. As the number of OTT platform users has increased, the original content offered by such OTT platforms has become very popular, further increasing the number of users. Therefore, effective resource-management technology is an essential aspect for reducing service-operation costs by minimizing unused resources while securing the resources necessary to provide media services in a timely manner when the user’s resource-demand rates change rapidly. However, previous studies have investigated efficient cloud-resource allocation without considering the number of users after the release of popular content. This paper proposes a technology for predicting and allocating cloud resources in the form of a Long-Short-Term-Memory (LSTM)-based reinforcement-learning method that provides information for OTT service providers about whether users are willing to watch popular content using the Korean Bidirectional Encoder Representation from Transformer (KoBERT). Results of simulating the proposed technology verified that efficient resource allocation can be achieved by maintaining service quality while reducing cloud-resource waste depending on whether content popularity is disclosed. Full article

(This article belongs to the Special Issue Applications of Smart Internet of Things)

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19 pages, 1457 KiB

Open AccessFeature PaperArticle

Adversarial Attack and Defense: A Survey

by Hongshuo Liang, Erlu He, Yangyang Zhao, Zhe Jia and Hao Li

Electronics 2022, 11(8), 1283; https://doi.org/10.3390/electronics11081283 - 18 Apr 2022

Cited by 18 | Viewed by 8929

Abstract

In recent years, artificial intelligence technology represented by deep learning has achieved remarkable results in image recognition, semantic analysis, natural language processing and other fields. In particular, deep neural networks have been widely used in different security-sensitive tasks. Fields, such as facial payment, [...] Read more.

In recent years, artificial intelligence technology represented by deep learning has achieved remarkable results in image recognition, semantic analysis, natural language processing and other fields. In particular, deep neural networks have been widely used in different security-sensitive tasks. Fields, such as facial payment, smart medical and autonomous driving, which accelerate the construction of smart cities. Meanwhile, in order to fully unleash the potential of edge big data, there is an urgent need to push the AI frontier to the network edge. Edge AI, the combination of artificial intelligence and edge computing, supports the deployment of deep learning algorithms to edge devices that generate data, and has become a key driver of smart city development. However, the latest research shows that deep neural networks are vulnerable to attacks from adversarial example and output wrong results. This type of attack is called adversarial attack, which greatly limits the promotion of deep neural networks in tasks with extremely high security requirements. Due to the influence of adversarial attacks, researchers have also begun to pay attention to the research in the field of adversarial defense. In the game process of adversarial attacks and defense technologies, both attack and defense technologies have been developed rapidly. This article first introduces the principles and characteristics of adversarial attacks, and summarizes and analyzes the adversarial example generation methods in recent years. Then, it introduces the adversarial example defense technology in detail from the three directions of model, data, and additional network. Finally, combined with the current status of adversarial example generation and defense technology development, put forward challenges and prospects in this field. Full article

(This article belongs to the Special Issue Edge Computing for Urban Internet of Things)

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22 pages, 3167 KiB

Open AccessArticle

An RG-FLAT-CRF Model for Named Entity Recognition of Chinese Electronic Clinical Records

by Jiakang Li, Ruixia Liu, Changfang Chen, Shuwang Zhou, Xiaoyi Shang and Yinglong Wang

Electronics 2022, 11(8), 1282; https://doi.org/10.3390/electronics11081282 - 18 Apr 2022

Cited by 7 | Viewed by 2127

Abstract

The goal of Clinical Named Entity Recognition (CNER) is to identify clinical terms from medical records, which is of great importance for subsequent clinical research. Most of the current Chinese CNER models use a single set of features that do not consider the [...] Read more.

The goal of Clinical Named Entity Recognition (CNER) is to identify clinical terms from medical records, which is of great importance for subsequent clinical research. Most of the current Chinese CNER models use a single set of features that do not consider the linguistic characteristics of the Chinese language, e.g., they do not use both word and character features, and they lack morphological information and specialized lexical information on Chinese characters in the medical field. We propose a RoBerta Glyce-Flat Lattice Transformer-CRF (RG-FLAT-CRF) model to address this problem. The model uses a convolutional neural network to discern the morphological information hidden in Chinese characters, and a pre-trained model to obtain vectors with medical features. The different vectors are stitched together to form a multi-feature vector. To use lexical information and avoid the problem of word separation errors, the model uses a lattice structure to add lexical information associated with each word, which can be used to avoid the problem of word separation errors. The RG-FLAT-CRF model scored 95.61%, 85.17%, and 91.2% for F1 on the CCKS 2017, 2019, and 2020 datasets, respectively. We used statistical tests to compare with other models. The results show that most p-values less than 0.05 are statistically significant. Full article

(This article belongs to the Special Issue Knowledge Engineering and Data Mining)

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28 pages, 7778 KiB

Open AccessArticle

A Socio-Inspired Methodology and Model for Advanced and Opportunistic Interactions between Industrial IoT Objects

by Rim Kilani, Ahmed Zouinkhi, Eddy Bajic and Mohamed Naceur Abdelkrim

Electronics 2022, 11(8), 1281; https://doi.org/10.3390/electronics11081281 - 18 Apr 2022

Cited by 6 | Viewed by 1400

Abstract

The concept of the Internet of Things (IoT) is widely discussed. IoT is one of the emerging technologies that have caught the attention of many researchers. The increase in the number of exchanges of services between heterogeneous or homogeneous connected objects with the [...] Read more.

The concept of the Internet of Things (IoT) is widely discussed. IoT is one of the emerging technologies that have caught the attention of many researchers. The increase in the number of exchanges of services between heterogeneous or homogeneous connected objects with the integration of social networking concepts gives rise to the concept of the Social Internet of Things (SIoT). The SIoT concept contributes to the evolution of interactions between industrial objects by improving deterministic mechanisms towards intelligent interactions. The integration of the SIoT concept into the Industrial Internet of Things (IIoT) gives rise to the Social Internet of Industrial Things (SIoIT) and plays an important role in improving system performance in Industry 4.0. In this article, we propose an innovative methodology and a model of socio-inspired interaction between industrial communicating objects inspired by sociological approaches. Thanks to this model, socialized industrial communicating objects form a community of objects, autonomously and dynamically, by exchanging messages to know each other perfectly, and service requests between objects are executed adaptively according to the principles of social interaction governed by socio-inspired strategies and conditions. The model is implemented, tested and validated in a Netlogo multi-agent system simulation environment. Full article

(This article belongs to the Special Issue Recent Advances in Internet of Things and Emerging Social Internet of Things: Vision, Challenges, and Trends)

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5 pages, 187 KiB

Open AccessEditorial

Advances in Sustainable Smart Cities and Territories

by Juan M. Corchado and Saber Trabelsi

Electronics 2022, 11(8), 1280; https://doi.org/10.3390/electronics11081280 - 18 Apr 2022

Cited by 4 | Viewed by 1348

Abstract

The smart city concept refers to the implementation of disruptive technologies in the urban environment, with the aim of creating an optimal citizen experience [...] Full article

(This article belongs to the Special Issue Advances in Sustainable Smart Cities and Territories)

13 pages, 7177 KiB

Open AccessArticle

The Development of 170 GHz, 1 MW Gyrotron for Fusion Application

by Yichi Zhang, Xu Zeng, Ming Bai, Ming Jin, Wenteng Hao, Dongshuo Gao, Qiao Liu and Jinjun Feng

Electronics 2022, 11(8), 1279; https://doi.org/10.3390/electronics11081279 - 18 Apr 2022

Cited by 4 | Viewed by 1867

Abstract

This paper presents the overall conceptual design of a 170 GHz, 1 MW gyrotron for plasma heating applications in thermonuclear fusion reactors. The operating mode is carefully selected with consideration of mode competition. The TE_25,10 mode is determined as the operating mode [...] Read more.

This paper presents the overall conceptual design of a 170 GHz, 1 MW gyrotron for plasma heating applications in thermonuclear fusion reactors. The operating mode is carefully selected with consideration of mode competition. The TE_25,10 mode is determined as the operating mode in the present study. A weakly tapered conventional resonator is used for the study of the RF behavior, and multimode calculations are carried out for power and efficiencies. The optimized structure of the beam tunnel can further attenuate low-frequency oscillation. The design studies of a triode-type magnetic injection gun, quasi-optical mode converter, and single-disc sapphire window are also described. In addition, novel cold test methods which can effectively validate assembles are designed. In 2021, a prototype gyrotron was fabricated to validate the electronic–optic system and RF system. The current results obtained support an output power of 210 kW and efficiency of 15.9% through an initial low-power experiment. On the basis of the optimized design, an industrial prototype gyrotron is under fabrication as the heating source for the thermonuclear experimental reactor. Full article

(This article belongs to the Section Microelectronics)

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13 pages, 733 KiB

Open AccessArticle

Smart Mobile Learning Success Model for Higher Educational Institutions in the Context of the COVID-19 Pandemic

by Mohammed Amin Almaiah, Sarra Ayouni, Fahima Hajjej, Abdalwali Lutfi, Omar Almomani and Ali Bani Awad

Electronics 2022, 11(8), 1278; https://doi.org/10.3390/electronics11081278 - 18 Apr 2022

Cited by 49 | Viewed by 4305

Abstract

Smart mobile learning (M-learning) applications have shown several new benefits for higher educational institutions during the COVID-19 pandemic, during which such applications were used to support distance learning. Therefore, this study aims to examine the most important drivers influencing the adoption of M-learning [...] Read more.

Smart mobile learning (M-learning) applications have shown several new benefits for higher educational institutions during the COVID-19 pandemic, during which such applications were used to support distance learning. Therefore, this study aims to examine the most important drivers influencing the adoption of M-learning by using the technology acceptance model (TAM). The structural equation modelling (SEM) method was used to test the hypotheses in the proposed model. Data were collected via online questionnaires from 520 undergraduate and postgraduate students at four universities in Saudi Arabia. Partial least squares (PLS)–SEM was used to analyse the data. The findings indicated that M-learning acceptance is influenced by three main factors, namely, awareness, IT infrastructure (ITI), and top management support. This research contributes to the body of knowledge on M-learning acceptance practices. Likewise, it may help to facilitate and promote the acceptance of M-learning among students in Saudi universities. Full article

(This article belongs to the Special Issue The Effects of the COVID-19 Pandemic on the Digital Competence of Educators)

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25 pages, 8451 KiB

Open AccessArticle

Integrated Yaw Stability Control of Electric Vehicle Equipped with Front/Rear Steer-by-Wire Systems and Four In-Wheel Motors

by Younghoon Seo, Kwanghyun Cho and Kanghyun Nam

Electronics 2022, 11(8), 1277; https://doi.org/10.3390/electronics11081277 - 18 Apr 2022

Cited by 3 | Viewed by 2638

Abstract

This paper presents the integrated motion control method for an electric vehicle (EV) equipped with a front/rear steer-by-wire (SbW) system and four in-wheel motor (IWM). The proposed integrated motion control method aims to maintain stable cornering. To maintain vehicle agility and stability, the [...] Read more.

This paper presents the integrated motion control method for an electric vehicle (EV) equipped with a front/rear steer-by-wire (SbW) system and four in-wheel motor (IWM). The proposed integrated motion control method aims to maintain stable cornering. To maintain vehicle agility and stability, the lateral force and yaw rate commands of the vehicle are generated by referring to the neutral steering characteristics. The driver’s driving force command, the lateral force command based on the bicycle model, and the yaw moment generated by the high-level controller are distributed into the driving force of each wheel and the lateral force of the front and rear wheels by the yaw moment distribution. Finally, the distributed forces are directly controlled by a low-level controller. To directly control the forces, a driving force observer and a lateral force observer were introduced via driving force estimation in the IWMs and rack force estimation in the SbW system. The control performance is verified through computer simulations. Full article

(This article belongs to the Special Issue Advances in Control for Electric Vehicle)

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27 pages, 14271 KiB

Open AccessArticle

In-Depth Evaluation of the Impact of National-Level DNS Filtering on DNS Resolvers over Space and Time

by Yanan Cheng, Yali Liu, Chao Li, Zhaoxin Zhang, Ning Li and Yuejin Du

Electronics 2022, 11(8), 1276; https://doi.org/10.3390/electronics11081276 - 18 Apr 2022

Cited by 1 | Viewed by 12050

Abstract

DNS filtering is the practice of blocking access to certain sites for a specific purpose, often content-based filtering. Unlike previous studies that focused on the behavior of national-level DNS filtering itself (e.g., location of filtering devices), we demonstrate and evaluate in depth the [...] Read more.

DNS filtering is the practice of blocking access to certain sites for a specific purpose, often content-based filtering. Unlike previous studies that focused on the behavior of national-level DNS filtering itself (e.g., location of filtering devices), we demonstrate and evaluate in depth the impact of DNS filtering on different types (public, ISP, and open) of DNS resolvers in the censored networks. In particular, we actively send DNS queries for 83 well-selected domain names to three types of DNS resolvers and keep track of the resolvers’ responses changing over time and space in China. Here, we present the results of our system running for 40 days, during which we obtained a total of 1.7 billion DNS records. Using these collected data, we found that specific DNS resolvers are unaffected by DNS filtering devices and can respond with the correct IP addresses for particular blocked domains. Furthermore, we revealed that three factors should be considered to evaluate the impact of a country-level DNS filtering mechanism: DNS resolver, client location, and blocked domain. Finally, we propose and implement a system to identify the correct IP addresses of blocked domain names in censored networks based on the characteristics of country-level DNS filtering. Full article

(This article belongs to the Section Networks)

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14 pages, 1556 KiB

Open AccessArticle

AI Ekphrasis: Multi-Modal Learning with Foundation Models for Fine-Grained Poetry Retrieval

by Muhammad Shahid Jabbar, Jitae Shin and Jun-Dong Cho

Electronics 2022, 11(8), 1275; https://doi.org/10.3390/electronics11081275 - 18 Apr 2022

Cited by 1 | Viewed by 2159

Abstract

Artificial intelligence research in natural language processing in the context of poetry struggles with the recognition of holistic content such as poetic symbolism, metaphor, and other fine-grained attributes. Given these challenges, multi-modal image–poetry reasoning and retrieval remain largely unexplored. Our recent accessibility study [...] Read more.

Artificial intelligence research in natural language processing in the context of poetry struggles with the recognition of holistic content such as poetic symbolism, metaphor, and other fine-grained attributes. Given these challenges, multi-modal image–poetry reasoning and retrieval remain largely unexplored. Our recent accessibility study indicates that poetry is an effective medium to convey visual artwork attributes for improved artwork appreciation of people with visual impairments. We, therefore, introduce a deep learning approach for the automatic retrieval of poetry suitable to the input images. The recent state-of-the-art CLIP provides a way for multi-modal visual and text features matched using cosine similarity. However, it lacks shared cross-modality attention features to model fine-grained relationships. The proposed approach in this work takes advantage of strong pre-training of the CLIP model and overcomes its limitations by introducing shared attention parameters to better model the fine-grained relationship between both modalities. We test and compare our proposed approach using the expertly annotated MiltiM-Poem dataset, which is considered the largest public image–poetry pair dataset for English poetry. The proposed approach aims to solve the problems of image-based attribute recognition and automatic retrieval for fine-grained poetic verses. The test results reflect that the shared attention parameters alleviate fine-grained attribute recognition, and the proposed approach is a significant step towards automatic multi-modal retrieval for improved artwork appreciation of people with visual impairments. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: Recent Advances in Computer Science & Engineering)

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11 pages, 3041 KiB

Open AccessArticle

Theory and Experiment of Pulse Wave Rectifier with High Efficiency

by Bozhong Xiao and Xuexia Yang

Electronics 2022, 11(8), 1274; https://doi.org/10.3390/electronics11081274 - 17 Apr 2022

Cited by 1 | Viewed by 1475

Abstract

In this paper, the pulse wave (PW) rectifier of the Schottky diode is theoretically analyzed using the microwave equivalent circuit. It is found that the duty cycle of PW is inversely proportional to the load resistance of the rectifier when the amplitude of [...] Read more.

In this paper, the pulse wave (PW) rectifier of the Schottky diode is theoretically analyzed using the microwave equivalent circuit. It is found that the duty cycle of PW is inversely proportional to the load resistance of the rectifier when the amplitude of the input pulse is the same. Therefore, a stable high-efficiency rectifier can be designed by changing the value of the load resistance when the duty cycles are different. A grounded coplanar waveguide (GCPW) rectifier for the pulse wave is designed to verify this rule. The rectifier is simulated by ADS software and verified by the measurements. When the duty cycle of PW varies from 0.01 to 1 and the input pulse amplitude is stable at the operation frequency of 2.38 GHz, the measured rectifying efficiency can be maintained at the peak efficiency of 76.1% by adjusting the load resistance. However, when the input signal of the rectifier is the continuous wave (CW), the rectifying efficiency is only 3.9% at the same input power amplitude. The proposed rectifier has a simple structure so that it can obtain a high efficiency and has a compact size of 0.22λ₀ × 0.11λ₀. It can be a good candidate for simultaneous wireless information and power transmission (SWIPT) for low-power electronic devices in the Internet of Things (IoT). Full article

(This article belongs to the Section Microwave and Wireless Communications)

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9 pages, 1844 KiB

Open AccessArticle

Lattice Relaxation Forward Negative Coulomb Drag in Hopping Regime

by Dongyang Liu, Jiawei Wang, Chong Bi, Mengmeng Li, Nianduan Lu, Zhekai Chen and Ling Li

Electronics 2022, 11(8), 1273; https://doi.org/10.3390/electronics11081273 - 17 Apr 2022

Cited by 2 | Viewed by 1430

Abstract

Quasi-particle formed by electron and the dressed deformed lattice is important to accurately interpret the properties of various disordered/amorphous materials. However, a unified understanding of the drag effect, in particular the negative Coulomb drag in hopping systems, remains an open challenge. This work [...] Read more.

Quasi-particle formed by electron and the dressed deformed lattice is important to accurately interpret the properties of various disordered/amorphous materials. However, a unified understanding of the drag effect, in particular the negative Coulomb drag in hopping systems, remains an open challenge. This work proposes a theoretic framework to account for both positive and negative Coulomb drag in dual-1D-hopping systems by considering both the electron-electron correlation and the electron-phonon correlation. It is found that lattice relaxation in the active line of the hopping system may give rise to an inverse energetic pumping force in the passive line, causing negative Coulomb drag. The mobility of the negative coulomb drag can approach the scale of 10⁻⁵cm²V⁻¹s⁻¹, especially at low temperature, high carrier-density, and narrow inter-spacing separation. More intriguingly, the positive drag could be recovered by varying the energy fluctuation and suppressing the electron-phonon interactions, but with a much lower magnitude. Our work could serve as a universal model for the Coulomb drag effect in the hopping system. Full article

(This article belongs to the Section Electronic Materials)

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16 pages, 21145 KiB

Open AccessArticle

Channel-Attention-Enhanced LSTM Neural Network Decoder and Equalizer for RSE-Based Optical Camera Communications

by Peng Ling, Maolin Li and Weipeng Guan

Electronics 2022, 11(8), 1272; https://doi.org/10.3390/electronics11081272 - 17 Apr 2022

Cited by 4 | Viewed by 1941

Abstract

In an RGB-LED-based optical camera communication system, it is an essential goal to have better performance in the data rate and BER. However, in a higher symbol rate, due to the conventional sampling algorithm, the deterioration of transmission performance brought by the inter-symbol [...] Read more.

In an RGB-LED-based optical camera communication system, it is an essential goal to have better performance in the data rate and BER. However, in a higher symbol rate, due to the conventional sampling algorithm, the deterioration of transmission performance brought by the inter-symbol interference and inter-channel interference is significant. Innovatively, in this paper, the sub-image obtained by a captured frame of received video is encoded by a channel-attention-Net-based encoder to generate a descriptor without existing sampling methods. Moreover, we propose an LSTM-based equalizer to decode the descriptor and mitigate transmission performance deterioration. Utilizing the long-short-term memory of an LSTM unit, an equalizer not only can reduce bit error rates but also increase the data rate. The experimental results show that at a symbol rate of 46 kbaud/s, a record-high data rate at 44.03 kbit/s is achieved under random data transmission while still meeting the pre-forward error correction requirement. Full article

(This article belongs to the Section Microwave and Wireless Communications)

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11 pages, 3927 KiB

Open AccessArticle

A 1.8 V Low-Power Low-Noise High Tunable Gain TIA for CMOS Integrated Optoelectronic Biomedical Applications

by Guido Di Patrizio Stanchieri, Andrea De Marcellis, Graziano Battisti, Marco Faccio, Elia Palange and Ulkuhan Guler

Electronics 2022, 11(8), 1271; https://doi.org/10.3390/electronics11081271 - 17 Apr 2022

Cited by 9 | Viewed by 2250

Abstract

This paper reports on a novel solution for a transimpedance amplifier (TIA) specifically designed as an analog conditioning circuit for low-voltage, low-power, wearable, portable and implantable optoelectronic integrated sensor systems in biomedical applications. The growing use of sensors in all fields of industry, [...] Read more.

This paper reports on a novel solution for a transimpedance amplifier (TIA) specifically designed as an analog conditioning circuit for low-voltage, low-power, wearable, portable and implantable optoelectronic integrated sensor systems in biomedical applications. The growing use of sensors in all fields of industry, biomedicine, agriculture, environment analysis, workplace security and safety, needs the development of small sensors with a reduced number of electronic components to be easily integrated in the standard CMOS technology. Especially in biomedicine applications, reduced size sensor systems with small power consumption are of paramount importance to make them non-invasive, comfortable tools for patients to be continuously monitored even with personalized therapeutics and/or that can find autonomous level of life using prosthetics. The proposed new TIA architecture has been designed at transistor level in TSMC 0.18 μm standard CMOS technology with the aim to operate with nanoampere input pulsed currents that can be generated, for example, by Si photodiodes in optical sensor systems. The designed solution operates at 1.8 V single supply voltage with a maximum power consumption of about 36.1 μW and provides a high variable gain up to about 124 dBΩ (with fine- and coarse-tuning capabilities) showing wide bandwidth up to about 1.15 MHz and low-noise characteristics with a minimum noise floor level down to about 0.39 pA/

\sqrt{Hz}

. The overall circuit is described in detail, and its main characteristics and performances have been analyzed by performing accurate post-layout simulations. Full article

(This article belongs to the Special Issue Circuits and Optoelectronics for Point-of-Care Medical Devices)

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8 pages, 2306 KiB

Open AccessArticle

Very Low-Noise Figure HTSC RF Front-End

by Eldad Holdengreber, Moshe Mizrahi, Noy Citron, Shmuel E. Schacham and Eliyahu Farber

Electronics 2022, 11(8), 1270; https://doi.org/10.3390/electronics11081270 - 17 Apr 2022

Cited by 1 | Viewed by 1671

Abstract

A very low noise figure radio frequency (RF) front-end for the cellular realm is presented. The front-end is composed of two planar YBCO high critical temperature superconductor (HTSC) bandpass filters (BPFs) and a low temperature, low noise amplifier. Using advanced HTSC growth techniques, [...] Read more.

A very low noise figure radio frequency (RF) front-end for the cellular realm is presented. The front-end is composed of two planar YBCO high critical temperature superconductor (HTSC) bandpass filters (BPFs) and a low temperature, low noise amplifier. Using advanced HTSC growth techniques, 8-pole hairpin BPFs are implemented in a YBCO thin film grown on both sides of a sapphire substrate. The front-end is designed and implemented based on the optimal configuration of the filters derived from advanced electromagnetic simulations. Measured performance at 77 K shows a high-frequency response and very low losses, with an insertion loss of 0.15 dB and a rejection ratio of −93 dBc. The integration of HTSC filters with the low noise amplifier results in a system with superior performance, with a low noise figure of around 0.5 dB. Low insertion loss and the compact dimensions of the filter, along with low total system noise, make the designed superconducting RF front-end highly attractive for radio receivers. Full article

(This article belongs to the Section Microwave and Wireless Communications)

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22 pages, 1094 KiB

Open AccessArticle

Assessing the Effects of the COVID-19 Pandemic on M-Commerce Adoption: An Adapted UTAUT2 Approach

by Simona Vinerean, Camelia Budac, Lia Alexandra Baltador and Dan-Cristian Dabija

Electronics 2022, 11(8), 1269; https://doi.org/10.3390/electronics11081269 - 17 Apr 2022

Cited by 89 | Viewed by 6568

Abstract

The COVID-19 pandemic has impacted consumers’ lives and their shopping patterns, leading them towards mobile commerce. To address current shopping circumstances, an adapted UTAUT2 model aims to integrate trust and perceptions of the effects of the COVID-19 pandemic on consumers’ behavioral intention to [...] Read more.

The COVID-19 pandemic has impacted consumers’ lives and their shopping patterns, leading them towards mobile commerce. To address current shopping circumstances, an adapted UTAUT2 model aims to integrate trust and perceptions of the effects of the COVID-19 pandemic on consumers’ behavioral intention to rely on m-commerce during this period. The study proposes a research model which is investigated with the help of structural equation modelling in AMOS. Using the framework of a cross-sectional study, data were collected from an emerging market in Romania, where internet speed ranks 4th worldwide and where the yearly increase in internet and social media users is approximately 10%. By using confirmatory factor analysis and structural equation modelling, the research validates the applicability of UTAUT2 in examining consumers’ behavioral intent of using m-commerce during a pandemic. Hedonic motivation is the strongest predictor of consumers’ behavioral intentions to continue using m-commerce. The findings contribute to understandings of consumers’ behavior with m-commerce in an emerging market, extending knowledge based on the adapted UTAUT2 model and allowing for comprehension of the key role of trust and social influences in affecting consumers’ perceptions of the COVID-19 outbreak in relation to shopping patterns. Full article

(This article belongs to the Special Issue Impact of COVID-19 on Multimedia Transformation)

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18 pages, 1376 KiB

Open AccessArticle

Evaluation of Production of Digital Twins Based on Blockchain Technology

by Nada A. Nabeeh, Mohamed Abdel-Basset, Abduallah Gamal and Victor Chang

Electronics 2022, 11(8), 1268; https://doi.org/10.3390/electronics11081268 - 17 Apr 2022

Cited by 14 | Viewed by 2845

Abstract

A blockchain, as a form of distributed ledger technology, represents the unanimity of replication, synchronization, and sharing of data among various geographical sites. Blockchains have demonstrated impressive and effective applications throughout many aspects of the business. Blockchain technology can lead to the advent [...] Read more.

A blockchain, as a form of distributed ledger technology, represents the unanimity of replication, synchronization, and sharing of data among various geographical sites. Blockchains have demonstrated impressive and effective applications throughout many aspects of the business. Blockchain technology can lead to the advent of the construction of Digital Twins (DTs). DTs involve the real representation of physical devices digitally as a virtual representation of both elements and dynamics prior to the building and deployment of actual devices. DT products can be built using blockchain-based technology in order to achieve sustainability. The technology of DT is one of the emerging novel technologies of Industry 4.0, along with artificial intelligence (AI) and the Internet of Things (IoT). Therefore, the present study adopts intelligent decision-making techniques to conduct a biased analysis of the drivers, barriers, and risks involved in applying blockchain technologies to the sustainable production of DTs. The proposed model illustrates the use of neutrosophic theory to handle the uncertain conditions of real-life situations and the indeterminate cases evolved in decision-makers’ judgments and perspectives. In addition, the model applies the analysis of Multi-criteria Decision Making (MCDM) methods through the use of ordered weighted averaging (OWA) and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to achieve optimal rankings for DT production providers based on consistent weighted decision-maker’s judgments in order to maintain and to assure sustainability. An empirical study is applied to the uncertain environment to aid decision-makers in achieving ideal decisions for DT providers with respect to various DT challenges, promoting sustainability and determining the best service providers. The Monte Carlo simulation method is used to illustrate, predict, and forecast the importance of the weights of decision-makers’ judgments as well as the direct impact on the sustainability of DT production. Full article

(This article belongs to the Special Issue Advances in Industrial IoT, Big Data and Supply Chain)

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14 pages, 5715 KiB

Open AccessArticle

On the Reuse of a Matching Network for IoT Devices Operating at 900 MHz Embedding Antenna Boosters

by Jaime Gui, Aurora Andújar and Jaume Anguera

Electronics 2022, 11(8), 1267; https://doi.org/10.3390/electronics11081267 - 17 Apr 2022

Cited by 1 | Viewed by 2366

Abstract

The Internet of Things (IoT) is evolving rapidly, enabling more new applications than ever before. Some radio systems in the IoT space used to connect things with things operate at the 863–928 MHz frequency band (e.g., LoRa, ISM). IoT wireless devices at 900 [...] Read more.

The Internet of Things (IoT) is evolving rapidly, enabling more new applications than ever before. Some radio systems in the IoT space used to connect things with things operate at the 863–928 MHz frequency band (e.g., LoRa, ISM). IoT wireless devices at 900 MHz need an efficient antenna to send data into the cloud, and ensure range and long battery life. Moreover, the antenna should be easy to use across different device sizes. In this regard, antenna booster technology is proposed, which relies on a tiny element called an antenna booster, able to excite radiation currents on the ground plane of the IoT device. The antenna booster in this paper is only 12 mm × 3 mm × 2.4 mm (height), representing only ~λ/30 at 863 MHz. Such an antenna booster is reactive across the 863–928 MHz frequency range and, thus, a matching network is needed. The paper first proposes a matching network on a 120 mm × 60 mm ground plane. Afterward, an analysis is carried out to find the set of different ground plane sizes where the same matching network as the one used for the 120 mm × 60 mm ground plane can be reused, ensuring an S₁₁ < −6 dB. The goal is to find a map representing a cluster of ground planes where the same antenna system can be used (the same antenna booster and the same matching network) to simplify the design of IoT devices embedding antenna boosters. The analysis is addressed using MoM (Method of Moments) electromagnetic software (IE3D) and validated through measurements. Results indicate that a broad set of device sizes can reuse the same matching network with the same antenna booster, thus, simplifying and accelerating the design of IoT devices since no adjustment is needed on the antenna system. Full article

(This article belongs to the Special Issue Ubiquitous Sensor Networks)

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15 pages, 10120 KiB

Open AccessArticle

A Five Convolutional Layer Deep Convolutional Neural Network for Plant Leaf Disease Detection

by J. Arun Pandian, K. Kanchanadevi, V. Dhilip Kumar, Elżbieta Jasińska, Radomír Goňo, Zbigniew Leonowicz and Michał Jasiński

Electronics 2022, 11(8), 1266; https://doi.org/10.3390/electronics11081266 - 16 Apr 2022

Cited by 32 | Viewed by 3193

Abstract

In this research, we proposed a Deep Convolutional Neural Network (DCNN) model for image-based plant leaf disease identification using data augmentation and hyperparameter optimization techniques. The DCNN model was trained on an augmented dataset of over 240,000 images of different healthy and diseased [...] Read more.

In this research, we proposed a Deep Convolutional Neural Network (DCNN) model for image-based plant leaf disease identification using data augmentation and hyperparameter optimization techniques. The DCNN model was trained on an augmented dataset of over 240,000 images of different healthy and diseased plant leaves and backgrounds. Five image augmentation techniques were used: Generative Adversarial Network, Neural Style Transfer, Principal Component Analysis, Color Augmentation, and Position Augmentation. The random search technique was used to optimize the hyperparameters of the proposed DCNN model. This research shows the significance of choosing a suitable number of layers and filters in DCNN development. Moreover, the experimental outcomes illustrate the importance of data augmentation techniques and hyperparameter optimization techniques. The performance of the proposed DCNN was calculated using different performance metrics such as classification accuracy, precision, recall, and F1-Score. The experimental results show that the proposed DCNN model achieves an average classification accuracy of 98.41% on the test dataset. Moreover, the overall performance of the proposed DCNN model was better than that of advanced transfer learning and machine learning techniques. The proposed DCNN model is useful in the identification of plant leaf diseases. Full article

(This article belongs to the Special Issue New Technological Advancements and Applications of Deep Learning)

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20 pages, 2084 KiB

Open AccessArticle

A Countermeasure Approach for Brute-Force Timing Attacks on Cache Privacy in Named Data Networking Architectures

by Ertugrul Dogruluk, Joaquim Macedo and Antonio Costa

Electronics 2022, 11(8), 1265; https://doi.org/10.3390/electronics11081265 - 16 Apr 2022

Cited by 4 | Viewed by 2178

Abstract

One key feature of named data networks (NDN) is supporting in-network caching to increase the content distribution for today’s Internet needs. However, previously cached contents may be threatened by side-channel timing measurements/attacks. For example, one adversary can identify previously cached contents by distinguishing [...] Read more.

One key feature of named data networks (NDN) is supporting in-network caching to increase the content distribution for today’s Internet needs. However, previously cached contents may be threatened by side-channel timing measurements/attacks. For example, one adversary can identify previously cached contents by distinguishing between uncached and cached contents from the in-network caching node, namely the edge NDN router. The attacks can be mitigated by the previously proposed methods effectively. However, these countermeasures may be against the NDN paradigm, affecting the content distribution performance. This work studied the side-channel timing attack on streaming over NDN applications and proposed a capable approach to mitigate it. Firstly, a recent side-channel timing attack, designated by brute-force, was implemented on ndnSIM using the AT&T network topology. Then, a multi-level countermeasure method, designated by detection and defense (DaD), is proposed to mitigate this attack. Simulation results showed that DaD distinguishes between legitimate and adversary nodes. During the attack, the proposed DaD multi-level approach achieved the minimum cache hit ratio (≈0.7%) compared to traditional countermeasures (≈4.1% in probabilistic and ≈3.7% in freshness) without compromising legitimate requests. Full article

(This article belongs to the Special Issue Advanced Security Protection Mechanism in Networks)

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27 pages, 1358 KiB

Open AccessArticle

Bagged Tree and ResNet-Based Joint End-to-End Fast CTU Partition Decision Algorithm for Video Intra Coding

by Yixiao Li, Lixiang Li, Yuan Fang, Haipeng Peng and Nam Ling

Electronics 2022, 11(8), 1264; https://doi.org/10.3390/electronics11081264 - 16 Apr 2022

Cited by 8 | Viewed by 1836

Abstract

Video coding standards, such as high-efficiency video coding (HEVC), versatile video coding (VVC), and AOMedia video 2 (AV2), achieve an optimal encoding performance by traversing all possible combinations of coding unit (CU) partition and selecting the combination with the minimum coding cost. It [...] Read more.

Video coding standards, such as high-efficiency video coding (HEVC), versatile video coding (VVC), and AOMedia video 2 (AV2), achieve an optimal encoding performance by traversing all possible combinations of coding unit (CU) partition and selecting the combination with the minimum coding cost. It is still necessary to further reduce the encoding time of HEVC, because HEVC is one of the most widely used coding standards. In HEVC, the process of searching for the best performance is the source of most of the encoding complexity. To reduce the complexity of the coding block partition in HEVC, a new end-to-end fast algorithm is presented to aid the partition structure decisions of the coding tree unit (CTU) in intra coding. In the proposed method, the partition structure decision problem of a CTU is solved by a novel two-stage strategy. In the first stage, a bagged tree model is employed to predict the splitting of a CTU. In the second stage, the partition problem of a 32 × 32-sized CU is modeled as a 17-output classification task for the first time, so that it can be solved by a single prediction. To achieve a high prediction accuracy, a residual network (ResNet) with 34 layers is employed. Jointly using bagged tree and ResNet, the proposed fast CTU partition algorithm is able to generate the partition quad-tree structure of a CTU through an end-to-end prediction process, which abandons the traditional scheme of making multiple decisions at various depth levels. In addition, several datasets are used in this paper to lay the foundation for high prediction accuracy. Compared with the original HM16.7 encoder, the experimental results show that the proposed algorithm can reduce the encoding time by 60.29% on average, while the Bjøntegaard delta rate (BD-rate) loss is as low as 2.03%, which outperforms the results of most of the state-of-the-art approaches in the field of fast intra CU partition. Full article

(This article belongs to the Special Issue Multimedia Content Analysis, Management and Retrieval: Trends and Challenges)

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15 pages, 3298 KiB

Open AccessArticle

Low-Dimensional-Approximate Model Based Improved Fuzzy Non-Singular Terminal Sliding Mode Control for Rigid-Flexible Manipulators

by Lisha Xu, Xiaoshan Qian, Rong Hu, Yi Zhang and Hua Deng

Electronics 2022, 11(8), 1263; https://doi.org/10.3390/electronics11081263 - 16 Apr 2022

Cited by 5 | Viewed by 1490

Abstract

The dynamic characteristics of rigid-flexible manipulators involve complex rigid-flexible coupling phenomena, which essentially comprise a nonlinear distributed parameter system with infinite degrees of freedom. Consequently, it results in challenges to the manipulator’s precise positioning. This study combined a state feedback module and a [...] Read more.

The dynamic characteristics of rigid-flexible manipulators involve complex rigid-flexible coupling phenomena, which essentially comprise a nonlinear distributed parameter system with infinite degrees of freedom. Consequently, it results in challenges to the manipulator’s precise positioning. This study combined a state feedback module and a fuzzy non-singular terminal sliding mode to suppress vibration and deformation. Using the improved fuzzy strategy and non-singular terminal sliding mode control, an adaptive dynamic supplementary control law is proposed. The results based on MATLAB simulation and a built hardware experiment show that this method is effective and superior. While realizing the accurate positioning of the end of the manipulator, the vibration of the end of the flexible arm is significantly suppressed. This method has a high tracking performance, which enables accurate positioning of the manipulator terminal and provides strong robustness under the action of bounded external interference. Full article

(This article belongs to the Special Issue Advanced Research in Electromagnetic Devices for Electric Vehicles)

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19 pages, 3610 KiB

Open AccessFeature PaperArticle

Overview of Prospects for Service-Aware Radio Access towards 6G Networks

by Zixiao Zhao, Qinghe Du, Dawei Wang, Xiao Tang and Houbing Song

Electronics 2022, 11(8), 1262; https://doi.org/10.3390/electronics11081262 - 16 Apr 2022

Cited by 17 | Viewed by 3138

Abstract

The integration of space–air–ground–sea networking in 6G, which is expected to not only achieve seamless coverage but also offer service-aware access and transmission, has introduced many new challenges for current mobile communications systems. Service awareness requires the 6G network to be aware of [...] Read more.

The integration of space–air–ground–sea networking in 6G, which is expected to not only achieve seamless coverage but also offer service-aware access and transmission, has introduced many new challenges for current mobile communications systems. Service awareness requires the 6G network to be aware of the demands of a diverse range of services as well as the occupation, utilization, and variation of network resources, which will enable the capability of deriving more intelligent and effective solutions for complicated heterogeneous resource configuration. Following this trend, this article investigates potential techniques that may improve service-aware radio access using the heterogeneous 6G network. We start with a discussion on the evolution of cloud-based RAN architectures from 5G to 6G, and then we present an intelligent radio access network (RAN) architecture for the integrated 6G network, which targets balancing the computation loads and fronthaul burden and achieving service-awareness for heterogeneous and distributed requests from users. In order for the service-aware access and transmissions to be equipped for future heterogeneous 6G networks, we analyze the challenges and potential solutions for the heterogeneous resource configuration, including a tightly coupled cross-layer design, resource service-aware sensing and allocation, transmission over multiple radio access technologies (RAT), and user socialization for cloud extension. Finally, we briefly explore some promising and crucial research topics on service-aware radio access for 6G networks. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)

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25 pages, 1619 KiB

Open AccessArticle

Mapping Processing Elements of Custom Virtual CGRAs onto Reconfigurable Partitions

by Zbigniew Mudza and Rafał Kiełbik

Electronics 2022, 11(8), 1261; https://doi.org/10.3390/electronics11081261 - 16 Apr 2022

Viewed by 1629

Abstract

FPGAs can provide application-specific acceleration for computationally demanding tasks. However, they are rarely considered general-purpose platforms due to low productivity of software development and long reconfiguration time. These problems can be mitigated by implementing a coarser overlay atop the FPGA fabric. Combining this [...] Read more.

FPGAs can provide application-specific acceleration for computationally demanding tasks. However, they are rarely considered general-purpose platforms due to low productivity of software development and long reconfiguration time. These problems can be mitigated by implementing a coarser overlay atop the FPGA fabric. Combining this approach with partial reconfiguration allows for the modification of individual processing elements (PEs) of the virtual architecture without altering the rest of the system. Module relocation can be used to share implementation details between functionally equivalent PEs that use identical sets of resources, thus eliminating redundant placement and routing runs. Proper floorplanning is crucial for virtual Coarse-Grained Reconfigurable Architectures (CGRAs) with relocatable PEs considering their tendency to use nearest-neighbor connection patterns. It requires solving two problems—finding identical regions in the FPGA fabric and assigning individual partitions to certain locations. This article presents minor improvements of a state-of-the-art solution for the first and proposes a novel technique for solving the other. The proposed automated floorplanner uses modified breadth-first search with direction-based penalties to create initial floorplan consistent with geometry of logical array, then improves the result with 2-opt local optimization. Compared to simulated annealing solutions, the proposed approach allows for the reduction in the floorplanning time by two to three orders of magnitude without compromising the quality of the results. Full article

(This article belongs to the Special Issue Applications of FPGAs and Reconfigurable Computing: Current Trends and Future Perspectives)

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Electronics, Volume 11, Issue 8 (April-2 2022) – 125 articles

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