Electronics

18 pages, 1901 KiB

Open AccessArticle

Multi-Label Vulnerability Detection of Smart Contracts Based on Bi-LSTM and Attention Mechanism

by Shenyi Qian, Haohan Ning, Yaqiong He and Mengqi Chen

Electronics 2022, 11(19), 3260; https://doi.org/10.3390/electronics11193260 - 10 Oct 2022

Cited by 10 | Viewed by 3229

Smart contracts are decentralized applications running on blockchain platforms and have been widely used in a variety of scenarios in recent years. However, frequent smart contract security incidents have focused more and more attention on their security and reliability, and smart contract vulnerability [...] Read more.

Smart contracts are decentralized applications running on blockchain platforms and have been widely used in a variety of scenarios in recent years. However, frequent smart contract security incidents have focused more and more attention on their security and reliability, and smart contract vulnerability detection has become an urgent problem in blockchain security. Most of the existing methods rely on fixed rules defined by experts, which have the disadvantages of single detection type, poor scalability, and high false alarm rate. To solve the above problems, this paper proposes a method that combines Bi-LSTM and an attention mechanism for multiple vulnerability detection of smart contract opcodes. First, we preprocessed the data to convert the opcodes into a feature matrix suitable as the input of the neural network and then used the Bi-LSTM model based on the attention mechanism to classify smart contracts with multiple labels. The experimental results show that the model can detect multiple vulnerabilities at the same time, and all evaluation indicators exceeded 85%, which proves the effectiveness of the method proposed in this paper for multiple vulnerability detection tasks in smart contracts. Full article

(This article belongs to the Section Networks)

► Show Figures

Figure 1

24 pages, 2813 KiB

Open AccessArticle

ANN and SSO Algorithms for a Newly Developed Flexible Grid Trading Model

by Wei-Chang Yeh, Yu-Hsin Hsieh, Kai-Yi Hsu and Chia-Ling Huang

Electronics 2022, 11(19), 3259; https://doi.org/10.3390/electronics11193259 - 10 Oct 2022

Cited by 3 | Viewed by 3133

Abstract

In the modern era, the trading methods and strategies used in the financial market have gradually changed from traditional on-site trading to electronic remote trading, and even online automatic trading performed by pre-programmed computer programs. This is due to the conduct of trading [...] Read more.

In the modern era, the trading methods and strategies used in the financial market have gradually changed from traditional on-site trading to electronic remote trading, and even online automatic trading performed by pre-programmed computer programs. This is due to the conduct of trading automatically and self-adjustment in financial markets becoming a competitive development trend in the entire financial market, with the continuous development of network and computer computing technology. Quantitative trading aims to automatically form a fixed and quantifiable operational logic from people’s investment decisions and apply it to the financial market, which has attracted the attention of the financial market. The development of self-adjustment programming algorithms for automatically trading in financial markets has transformed to being a top priority for academic research and financial practice. Thus, a new flexible grid trading model incorporating the Simplified Swarm Optimization (SSO) algorithm for optimizing parameters for various market situations as input values and the Fully Connected Neural Network (FNN) and Long Short-Term Memory (LSTM) model for training a quantitative trading model for automatically calculating and adjusting the optimal trading parameters for trading after inputting the existing market situation are developed and studied in this work. The proposed model provides a self-adjust model to reduce investors’ effort in the trading market, obtains outperformed Return of Investment (ROI) and model robustness, and can properly control the balance between risk and return. Full article

(This article belongs to the Special Issue Feature Papers in "Networks" Section)

► Show Figures

Figure 1

14 pages, 5031 KiB

Open AccessArticle

An Application-Oriented Method Based on Cooperative Map Matching for Improving Vehicular Positioning Accuracy

by Nanhao Zhou, Wei Chen, Changzhen Li, Luyao Du, Donghua Zhang and Ming Zhang

Electronics 2022, 11(19), 3258; https://doi.org/10.3390/electronics11193258 - 10 Oct 2022

Cited by 1 | Viewed by 1673

Abstract

Accurate vehicular positioning is important for intelligent and connected vehicles (ICVs). However, in urban canyons, vehicles that rely solely on global navigation satellite system (GNSS) are susceptible to factors such as signal blocking and multi-path, reducing the positioning performance. In this paper, an [...] Read more.

Accurate vehicular positioning is important for intelligent and connected vehicles (ICVs). However, in urban canyons, vehicles that rely solely on global navigation satellite system (GNSS) are susceptible to factors such as signal blocking and multi-path, reducing the positioning performance. In this paper, an application-oriented cooperative map matching (CMM) method is proposed, and a low-cost Global Positioning System (GPS)/BeiDou navigation satellite system (BDS) integrated positioning system is designed. The road constraints of a real traffic environment, which simplifies the computational complexity and facilitates practical applications, are modeled. The positioning system is designed to collect and store the positioning data for experimental analysis. Static and dynamic experiments are conducted to verify the effectiveness of the CMM method. From the experimental results, the mean absolute error (MAE) and root mean square error (RMSE) of the positioning with CMM correction in the static experiment are reduced by 9.0% and 4.9%, respectively. In the dynamic experiment, compared with the original positioning error, the MAE is reduced by 44.2% while the RMSE is reduced by 24.3%. The results show that the proposed method can improve vehicular positioning accuracy effectively in both static and dynamic environments. Full article

(This article belongs to the Special Issue Recent Advances in Intelligent Transportation Systems)

► Show Figures

Figure 1

10 pages, 4214 KiB

Open AccessCommunication

A Five-Level RF-PWM Method with Third and Fifth Harmonic Elimination for All-Digital Transmitters

by Haoyang Fu, Qiang Zhou, Lei Zhu, Zhang Chen, Zhihu Wei and Siyu Zeng

Electronics 2022, 11(19), 3257; https://doi.org/10.3390/electronics11193257 - 10 Oct 2022

Cited by 1 | Viewed by 1641

Abstract

An appropriate pulse-coding algorithm is the key to achieving an efficient switched-mode power amplification in all-digital transmitters. A five-level RF-PWM method with third and fifth harmonic elimination is proposed to relax the requirements of the filter and to reduce the control complexity of [...] Read more.

An appropriate pulse-coding algorithm is the key to achieving an efficient switched-mode power amplification in all-digital transmitters. A five-level RF-PWM method with third and fifth harmonic elimination is proposed to relax the requirements of the filter and to reduce the control complexity of the SMPA for all-digital transmitters. By controlling the pulse width and the center position of three-level sub-pulses, third and fifth harmonic elimination is achieved. Meanwhile, the control complexity of the SMPA is reduced by the decrease in the output-signal-level number. Finally, the feasibility of the method is verified by simulation. For the 16QAM signal with a carrier frequency of 200 MHz, the proposed method can achieve third harmonic suppression of −46.24 dBc and fifth harmonic suppression of −54.05 dBc when coding efficiency reaches 77.51%. Full article

(This article belongs to the Special Issue Signal Processing in Wireless Communications)

► Show Figures

Figure 1

13 pages, 3895 KiB

Open AccessArticle

A Compact Low-Profile Antenna for Millimeter-Wave 5G Mobile Phones

by Hidayat Ullah, Hattan F. Abutarboush, Aamir Rashid and Farooq A. Tahir

Electronics 2022, 11(19), 3256; https://doi.org/10.3390/electronics11193256 - 10 Oct 2022

Cited by 16 | Viewed by 2401

Abstract

This paper presents a very low profile and simple antenna design for dual beam and dual-band operation to be employed in future 5G mobile phones operating in the millimeter-wave bands of 26.75–30.31 and 35.83–41.22 GHz. The two distinct resonances at 28 and 38 [...] Read more.

This paper presents a very low profile and simple antenna design for dual beam and dual-band operation to be employed in future 5G mobile phones operating in the millimeter-wave bands of 26.75–30.31 and 35.83–41.22 GHz. The two distinct resonances at 28 and 38 GHz are achieved using a meta-material-based structure consisting of a closed-ring resonator (CRR) and a split-ring resonator (SRR) by co-centrically combining two planar hexagonal rings; i.e., an inner split-ring resonator (SRR) and an outer closed-ring resonator (CRR). The antenna has a high gain of 4.5 dBi. The antenna also exhibits a dual-beam radiation pattern in one of its planes. The overall antenna size is 6 × 8 mm² and is manufactured using a low-cost PCB fabrication process. The antenna’s dual-beam operation, broadband characteristics, high gain, and low profile makes it a potential candidate for future millimeter-wave mobile phones, especially in applications where space diversity is required. Full article

(This article belongs to the Special Issue Advances in Micro/mm Waves Circuits and Antennas)

► Show Figures

Figure 1

12 pages, 1343 KiB

Open AccessArticle

A Multi-Band LNA Covering 17–38 GHz in 45 nm CMOS SOI

by Fang Han, Xuzhi Liu, Chao Wang, Xiao Li, Quanwen Qi, Xiaoran Li and Zicheng Liu

Electronics 2022, 11(19), 3255; https://doi.org/10.3390/electronics11193255 - 10 Oct 2022

Cited by 3 | Viewed by 2215

Abstract

This paper presents a multi-band low-noise amplifier (LNA) in the 45-nm CMOS silicon-on-insulator (SOI) process. The LNA consists of three stages, with the differential cascode amplifier as the core structure. The first stage is mainly responsible for input matching to ensure favourable noise [...] Read more.

This paper presents a multi-band low-noise amplifier (LNA) in the 45-nm CMOS silicon-on-insulator (SOI) process. The LNA consists of three stages, with the differential cascode amplifier as the core structure. The first stage is mainly responsible for input matching to ensure favourable noise characteristics and bandwidth, while the subsequent stages increase the gain. Moreover, the LNA utilizes baluns for input/output and interstage impedance matching. Switch capacitances are added to switch the three operating bands of the LNA, which cover 17–38 GHz overall. Measurement results show that the proposed LNA achieves a gain (S21) of 23.0 dB and a noise figure (NF) of 4.0 dB. Full article

(This article belongs to the Special Issue Advanced Design of RF/Microwave Circuit)

► Show Figures

Figure 1

13 pages, 4079 KiB

Open AccessArticle

Biosensors Fabricated by Laser-Induced Metallization on DLP Composite Resin

by Ran Zhang, Qinyi Wang, Ya Chen, Chen Jiao, Fuxi Liu, Junwei Xu, Qiuwei Zhang, Jiantao Zhao, Lida Shen and Changjiang Wang

Electronics 2022, 11(19), 3254; https://doi.org/10.3390/electronics11193254 - 10 Oct 2022

Cited by 2 | Viewed by 1767

Abstract

With the growing emphasis on medical testing, people are seeking more technologies to detect indexes of the human body quickly and at a low cost. The electrochemical biosensors became a research hotspot due to their excellent properties. In this study, dicopper hydroxide phosphate [...] Read more.

With the growing emphasis on medical testing, people are seeking more technologies to detect indexes of the human body quickly and at a low cost. The electrochemical biosensors became a research hotspot due to their excellent properties. In this study, dicopper hydroxide phosphate (Cu₂(OH)PO₄) was incorporated in resin, and the resin sheets were prepared by digital light processing (DLP). The copper base points were activated on the resin sheet surface by Nd: YAG laser and then covered by the electroless copper plating and the electroless silver plating. The laser could effectively activate copper base points on the resin surface. Furthermore, silver electrodes on the detection chips could distinguish glucose solutions of different concentrations well. Finally, a novel detection kit with a three-electrode chip was designed for rapid health testing at home or in medical institutions in the future. Full article

► Show Figures

Figure 1

14 pages, 3118 KiB

Open AccessArticle

Wireless Communication Channel Scenarios: Machine-Learning-Based Identification and Performance Enhancement

by Amira Zaki, Ahmed Métwalli, Moustafa H. Aly and Waleed K. Badawi

Electronics 2022, 11(19), 3253; https://doi.org/10.3390/electronics11193253 - 10 Oct 2022

Cited by 6 | Viewed by 2276

Abstract

Wireless communication channel scenario classification is crucial for new modern wireless technologies. Reducing the time consumed by the data preprocessing phase for such identification is also essential, especially for multiple-scenario transitions in 6G. Machine learning (ML) has been used for scenario identification tasks. [...] Read more.

Wireless communication channel scenario classification is crucial for new modern wireless technologies. Reducing the time consumed by the data preprocessing phase for such identification is also essential, especially for multiple-scenario transitions in 6G. Machine learning (ML) has been used for scenario identification tasks. In this paper, the least absolute shrinkage and selection operator (LASSO) is used instead of ElasticNet in order to reduce the computational time of data preprocessing for ML. Moreover, the computational time and performance of different ML models are evaluated based on a regularization technique. The obtained results reveal that the LASSO operator achieves the same feature selection performance as ElasticNet; however, the LASSO operator consumes less computational time. The achieved run time of LASSO is 0.33 s, while the ElasticNet corresponding value is 0.67 s. The identification for each specific class for K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and k-Means and Gaussian Mixture Model (GMM) is evaluated using Receiver Operating Characteristics (ROC) curves and Area Under the Curve (AUC) scores. The KNN algorithm has the highest class-average AUC score at 0.998, compared to SVM, k-Means, and GMM with values of 0.994, 0.983, and 0.989, respectively. The GMM is the fastest algorithm among others, having the lowest classification time at 0.087 s, compared to SVM, k-Means, and GMM with values of 0.155, 0.26, and 0.087, respectively. Full article

(This article belongs to the Special Issue 5G Mobile Telecommunication Systems and Recent Advances)

► Show Figures

Figure 1

16 pages, 2509 KiB

Open AccessReview

Imperative Role of Integrating Digitalization in the Firms Finance: A Technological Perspective

by Deepa Bisht, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Aman Singh, Elisabeth Caro Montero, Neeraj Priyadarshi and Bhekisipho Twala

Electronics 2022, 11(19), 3252; https://doi.org/10.3390/electronics11193252 - 10 Oct 2022

Cited by 60 | Viewed by 7384

Abstract

Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical [...] Read more.

Financial management is a critical aspect of firms, and entails the strategic planning, direction, and control of financial endeavors. Risk assessment, fraud detection, wealth management, online transactions, customized bond scheme, customer retention, virtual assistant and so on, are a few of the critical areas where Industry 4.0 technologies intervention are highly required for managing firms' finance. It has been identified from the previous studies that they are limited studies that have addressed the significance and application of integrating of Industry 4.0 technologies such as Internet of Things (IoT), cloud computing, big data, robotic process automation (RPA), artificial intelligence (AI), Blockchain, Digital twin, and Metaverse. With the motivation from the above aspects, this study aims to discuss the role of these technologies in the area of financial management of a firm. Based up on the analysis, it has been concluded that these technologies assist to credit risk management based on real-time data; financial data analytics of risk assessment, digital finance, digital auditing, fraud detection, and AI- and IoT- based virtual assistants. This study recommended that digital technologies be deeply integrated into the financial sector to improve service quality and accessibility, as well as the creation of innovative rules that allow for healthy competition among market participants. Full article

(This article belongs to the Special Issue Recent Applications of Emerging Digital Technologies in Economy and Society)

► Show Figures

Figure 1

11 pages, 705 KiB

Open AccessFeature PaperArticle

Arrhythmia Classification and Diagnosis Based on ECG Signal: A Multi-Domain Collaborative Analysis and Decision Approach

by Hongpeng Ruan, Xueying Dai, Shengqi Chen and Xiang Qiu

Electronics 2022, 11(19), 3251; https://doi.org/10.3390/electronics11193251 - 9 Oct 2022

Cited by 4 | Viewed by 2711

Abstract

Electrocardiogram (ECG) signal plays a key role in the diagnosis of arrhythmia, which will pose a great threat to human health. As an effective feature extraction method, deep learning has shown excellent results in processing ECG signals. However, most of these methods neglect [...] Read more.

Electrocardiogram (ECG) signal plays a key role in the diagnosis of arrhythmia, which will pose a great threat to human health. As an effective feature extraction method, deep learning has shown excellent results in processing ECG signals. However, most of these methods neglect the cooperation between the multi-lead ECG series correlation and intra-series temporal patterns. In this work, a multi-domain collaborative analysis and decision approach is proposed, which makes the classification and diagnosis of arrhythmia more accurate. With this decision, we can realize the transition from the spatial domain to the spectral domain, and from the time domain to the frequency domain, and make it possible that ECG signals can be more clearly detected by convolution and sequential learning modules. Moreover, instead of the prior method, the self-attention mechanism is used to learn the relation matrix between the sequences automatically in this paper. We conduct extensive experiments on eight advanced models in the same field to demonstrate the effectiveness of our method. Full article

(This article belongs to the Special Issue Latest Theoretical and Technological Advancements in Nonlinear Adaptive Control and Decision-Making)

► Show Figures

Figure 1

10 pages, 2813 KiB

Open AccessArticle

A Non-Local Tensor Completion Algorithm Based on Weighted Tensor Nuclear Norm

by Wenzhe Wang, Jingjing Zheng, Li Zhao, Huiling Chen and Xiaoqin Zhang

Electronics 2022, 11(19), 3250; https://doi.org/10.3390/electronics11193250 - 9 Oct 2022

Cited by 4 | Viewed by 1844

Abstract

In this paper, we proposed an image inpainting algorithm, including an interpolation step and a non-local tensor completion step based on a weighted tensor nuclear norm. Specifically, the proposed algorithm adopts the triangular based linear interpolation algorithm firstly to preform the observation image. [...] Read more.

In this paper, we proposed an image inpainting algorithm, including an interpolation step and a non-local tensor completion step based on a weighted tensor nuclear norm. Specifically, the proposed algorithm adopts the triangular based linear interpolation algorithm firstly to preform the observation image. Second, we extract the non-local similar patches in the image using the patch match algorithm and rearrange them to a similar tensor. Then, we use the tensor completion algorithm based on the weighted tensor nuclear norm to recover the similar tensors. Finally, we regroup all these recovered tensors to obtain the final recovered image. From the image inpainting experiments on color RGB images, we can see that the performance of the proposed algorithm on the peak signal-to-noise ratio (PSNR) and the relative standard error (RSE) are significantly better than other image inpainting methods. Full article

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

► Show Figures

Figure 1

11 pages, 514 KiB

Open AccessArticle

Machine-Learning-Based Approach for Virtual Machine Allocation and Migration

by Suruchi Talwani, Jimmy Singla, Gauri Mathur, Navneet Malik, N. Z Jhanjhi, Mehedi Masud and Sultan Aljahdali

Electronics 2022, 11(19), 3249; https://doi.org/10.3390/electronics11193249 - 9 Oct 2022

Cited by 18 | Viewed by 2656

Abstract

Due to its ability to supply reliable, robust and scalable computational power, cloud computing is becoming increasingly popular in industry, government, and academia. High-speed networks connect both virtual and real machines in cloud computing data centres. The system’s dynamic provisioning environment depends on [...] Read more.

Due to its ability to supply reliable, robust and scalable computational power, cloud computing is becoming increasingly popular in industry, government, and academia. High-speed networks connect both virtual and real machines in cloud computing data centres. The system’s dynamic provisioning environment depends on the requirements of end-user computer resources. Hence, the operational costs of a particular data center are relatively high. To meet service level agreements (SLAs), it is essential to assign an appropriate maximum number of resources. Virtualization is a fundamental technology used in cloud computing. It assists cloud providers to manage data centre resources effectively, and, hence, improves resource usage by creating several virtualmachine (VM) instances. Furthermore, VMs can be dynamically integrated into a few physical nodes based on current resource requirements using live migration, while meeting SLAs. As a result, unoptimised and inefficient VM consolidation can reduce performance when an application is exposed to varying workloads. This paper introduces a new machine-learning-based approach for dynamically integrating VMs based on adaptive predictions of usage thresholds to achieve acceptable service level agreement (SLAs) standards. Dynamic data was generated during runtime to validate the efficiency of the proposed technique compared with other machine learning algorithms. Full article

(This article belongs to the Special Issue Intelligent Distributed Resource Allocation in Wireless Sensor Networks (WSNs))

► Show Figures

Figure 1

22 pages, 26716 KiB

Open AccessArticle

JN-Logo: A Logo Database for Aesthetic Visual Analysis

by Nannan Tian, Yuan Liu and Ziruo Sun

Electronics 2022, 11(19), 3248; https://doi.org/10.3390/electronics11193248 - 9 Oct 2022

Cited by 1 | Viewed by 2403

Abstract

Data are an important part of machine learning. In recent years, it has become increasingly common for researchers to study artificial intelligence-aided design, and rich design materials are needed to provide data support for related work. Existing aesthetic visual analysis databases contain mainly [...] Read more.

Data are an important part of machine learning. In recent years, it has become increasingly common for researchers to study artificial intelligence-aided design, and rich design materials are needed to provide data support for related work. Existing aesthetic visual analysis databases contain mainly photographs and works of art. There is no true logo database, and there are few public and high-quality design material databases. Facing these challenges, this paper introduces a larger-scale logo database named JN-Logo. JN-Logo provides 14,917 logo images from three well-known websites around the world and uses the votes of 150 graduate students. JN-Logo provides three types of annotation: aesthetic, style and semantic. JN-Logo’s scoring system includes 6 scoring points, 6 style labels and 11 semantic descriptions. Aesthetic annotations are divided into 0–5 points to evaluate the visual aesthetics of a logo image: the worst is 0 points; the best is 5 points. We demonstrate five advantages of the JN-Logo database: logo images as data objects, rich human annotations, quality scores for image aesthetics, style attribute labels and semantic description of style. We establish a baseline for JN-Logo to measure the effectiveness of its performance on algorithmic models of people’s choices of logo images. We compare existing traditional handcrafted and deep-learned features in both the aesthetic scoring task and the style-labeling task, showing the advantages of deep learning features. In the logo attribute classification task, the EfficientNet _B1 model achieved the best results, reaching an accuracy of 0.524. Finally, we describe two applications of JN-Logo: generating logo design style and similarity retrieval of logo content. The database of this article will eventually be made public. Full article

► Show Figures

Figure 1

14 pages, 4596 KiB

Open AccessArticle

Collaborative Accurate Vehicle Positioning Based on Global Navigation Satellite System and Vehicle Network Communication

by Haixu Yang, Jichao Hong, Lingjun Wei, Xun Gong and Xiaoming Xu

Electronics 2022, 11(19), 3247; https://doi.org/10.3390/electronics11193247 - 9 Oct 2022

Cited by 7 | Viewed by 3111

Abstract

Intelligence is a direction of development for vehicles and transportation. Accurate vehicle positioning plays a vital role in intelligent driving and transportation. In the case of obstruction or too few satellites, the positioning capability of the Global navigation satellite system (GNSS) will be [...] Read more.

Intelligence is a direction of development for vehicles and transportation. Accurate vehicle positioning plays a vital role in intelligent driving and transportation. In the case of obstruction or too few satellites, the positioning capability of the Global navigation satellite system (GNSS) will be significantly reduced. To eliminate the effect of unlocalization due to missing GNSS signals, a collaborative multi-vehicle localization scheme based on GNSS and vehicle networks is proposed. The vehicle first estimates the location based on GNSS positioning information and then shares this information with the environmental vehicles through vehicle network communication. The vehicle further integrates the relative position of the ambient vehicle observed by the radar with the ambient vehicle position information obtained by communication. A smaller error estimate of the position of self-vehicle and environmental vehicles is obtained by correcting the positioning of self-vehicle and environmental vehicles. The proposed method is validated by simulating multi-vehicle motion scenarios in both lane change and straight-ahead scenarios. The root-mean-square error of the co-location method is below 0.5 m. The results demonstrate that the combined vehicle network communication approach has higher accuracy than single GNSS positioning in both scenarios. Full article

(This article belongs to the Special Issue Emerging Scientific and Technical Challenges and Developments in Key Power Electronics and Mechanical Engineering)

► Show Figures

Figure 1

14 pages, 19432 KiB

Open AccessArticle

A High Phase Detection Density and Low Space Complexity Mueller-Muller Phase Detector for DB PAM-4 Wireline Receiver

by Jinwang Zhang, Fangxu Lv, Jianjun Shi, Zixiang Tang and Dongbin Lv

Electronics 2022, 11(19), 3246; https://doi.org/10.3390/electronics11193246 - 9 Oct 2022

Viewed by 2336

Abstract

A Mueller-Muller Phase Detector (MM PD) technology based on duo-binary four-level pulse amplitude modulation (DB PAM-4) with low complexity and high phase-detection density is presented. The proposed low complexity includes low phase-detection complexity and low space complexity of data processing. The waveform sifting [...] Read more.

A Mueller-Muller Phase Detector (MM PD) technology based on duo-binary four-level pulse amplitude modulation (DB PAM-4) with low complexity and high phase-detection density is presented. The proposed low complexity includes low phase-detection complexity and low space complexity of data processing. The waveform sifting technology simplifies 175 specific waveform changes into five fuzzy waveform change trends, reducing the complexity of subsequent phase detection. By making the data sample before the waveform sifting, the data bit width is reduced from 8 bit to 3 bit, which realizes data dimensionality reduction, greatly reduces the scale of subsequent auxiliary data, reduces the number of basic devices by 13.7%, and reduces the spatial complexity of data processing. The coherent coding of DB PAM-4 combined with waveform sifting increases the phase-detection density from 50% to 65% and improves both phase-detection density and phase-detection gain by 30%, and improves the jitter tolerance. Through the simulation of the clock and data recovery (CDR) model built by Cadence, the fast locking capability of CDR is verified. Full article

(This article belongs to the Section Microelectronics)

► Show Figures

Figure 1

11 pages, 5054 KiB

Open AccessArticle

Compact 8 × 8 MIMO Antenna Design for 5G Terminals

by Haifu Zhang, Li-Xin Guo, Pengfei Wang and Hao Lu

Electronics 2022, 11(19), 3245; https://doi.org/10.3390/electronics11193245 - 9 Oct 2022

Cited by 6 | Viewed by 2017

Abstract

In this paper, a compact 8 × 8 MIMO antenna design for 5G terminals is proposed. The 8 × 8 MIMO antenna consists of two quad-element antenna pairs, each of which includes two symmetrical T-shaped monopole mode elements and two symmetrical edge-coupled fed [...] Read more.

In this paper, a compact 8 × 8 MIMO antenna design for 5G terminals is proposed. The 8 × 8 MIMO antenna consists of two quad-element antenna pairs, each of which includes two symmetrical T-shaped monopole mode elements and two symmetrical edge-coupled fed dipole mode elements. The size of the quad-element antenna is 38 × 7 × 0.8 mm³. T-shaped monopoles are decoupled by parasitic elements, and dipoles are decoupled by grounding strips. Meanwhile, both T-shaped monopoles and dipoles are also decoupled by the orthogonal mode. The results show that the operating frequency band of each antenna element meets the requirement of 3.4–3.6 GHz, the reflection coefficient is less than −6 dB, and the isolation between any antenna element is more than 10 dB. The antenna radiation efficiency is over 50% in the entire operating frequency band for the 8 × 8 MIMO system. Full article

(This article belongs to the Special Issue Wideband and Multiband Antennas for Wireless Applications)

► Show Figures

Figure 1

22 pages, 5745 KiB

Open AccessReview

The Class D Audio Power Amplifier: A Review

by Shangming Mei, Yihua Hu, Hui Xu and Huiqing Wen

Electronics 2022, 11(19), 3244; https://doi.org/10.3390/electronics11193244 - 9 Oct 2022

Cited by 8 | Viewed by 14100 | Correction

Abstract

Class D power amplifiers, one of the most critical devices for application in sound systems, face severe challenges due to the increasing requirement of smartphones, digital television, digital sound, and other terminals. The audio power amplifier has developed from a transistor amplifier to [...] Read more.

Class D power amplifiers, one of the most critical devices for application in sound systems, face severe challenges due to the increasing requirement of smartphones, digital television, digital sound, and other terminals. The audio power amplifier has developed from a transistor amplifier to a field-effect tube amplifier, and digital amplifiers have made significant progress in circuit technology, components, and ideological understanding. The stumbling blocks for a successful power amplifier are low power efficiency and a high distortion rate. Therefore, Class D audio amplifiers are becoming necessary for smartphones and terminals due to their power efficiency. However, the switching nature and intrinsic worst linearity of Class D amplifiers compared to linear amplifiers make it hard to dominate the market for high-quality speakers. The breakthrough arrived with the GaN device, which is appropriate for fast-switching and high-power-density power electronics switching elements compared with traditional Si devices, thus, reducing power electronic systems’ weight, power consumption, and cost. GaN devices allow Class D audio amplifiers to have high fidelity and efficiency. This paper analyzes and discusses the topological structure and characteristics and makes a judgment that Class D amplifiers based on GaN amplifiers are the future development direction of audio amplifiers. Full article

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

► Show Figures

Figure 1

20 pages, 1176 KiB

Open AccessArticle

A Cuckoo Filter-Based Name Resolution and Routing Method in Information-Centric Networking

by Wenhan Lian, Yang Li, Jinlin Wang and Jiali You

Electronics 2022, 11(19), 3243; https://doi.org/10.3390/electronics11193243 - 9 Oct 2022

Cited by 1 | Viewed by 1742

Abstract

Information-centric networking (ICN) is a new network architecture that routes content based on names to improve transmission performance. Therefore, the efficiency of name resolution and routing becomes a critical issue in ICN. The bloom filter-based routing scheme has gained significant attention for its [...] Read more.

Information-centric networking (ICN) is a new network architecture that routes content based on names to improve transmission performance. Therefore, the efficiency of name resolution and routing becomes a critical issue in ICN. The bloom filter-based routing scheme has gained significant attention for its ability to improve the memory efficiency of routing nodes in the network, but it cannot handle the movement or deletion of content and has a high false positive rate, which increases bandwidth consumption. In this paper, we propose a cuckoo filter-based name resolution and routing method where resolution requests are forwarded through a hierarchical network structure to the node closest to the content copy as much as possible to minimize latency. This method achieves reliable content removal and allows summaries of content to be exchanged between nodes for resolution error correction and information synchronization based on a modified cuckoo filter. The simulation results show that our method can effectively reduce the number of false positives, and it can reduce the additional overhead caused by processing false positives for a large-scale network by 50% compared with the bloom filter-based scheme. Full article

(This article belongs to the Section Networks)

► Show Figures

Figure 1

16 pages, 4283 KiB

Open AccessArticle

Short-Term Load Forecasting with an Ensemble Model Based on 1D-UCNN and Bi-LSTM

by Wenhao Chen, Guangjie Han, Hongbo Zhu and Lyuchao Liao

Electronics 2022, 11(19), 3242; https://doi.org/10.3390/electronics11193242 - 9 Oct 2022

Cited by 5 | Viewed by 1907

Abstract

Short-term load forecasting (STLF), especially for regional aggregate load forecasting, is essential in smart grid operation and control. However, the existing CNN-based methods cannot efficiently extract the essential features from the electricity load. The reason is that the basic requirement of using CNNs [...] Read more.

Short-term load forecasting (STLF), especially for regional aggregate load forecasting, is essential in smart grid operation and control. However, the existing CNN-based methods cannot efficiently extract the essential features from the electricity load. The reason is that the basic requirement of using CNNs is space invariance, which is not satisfied by the actual electricity data. In addition, the existing models cannot extract the multi-scale input features by representing the tendency of the electricity load, resulting in a reduction in the forecasting performance. As a solution, this paper proposes a novel ensemble model, which is a four-stage framework composed of a feature extraction module, a densely connected residual block (DCRB), a bidirectional long short-term memory layer (Bi-LSTM), and ensemble thinking. The model first extracts the basic and derived features from raw data using the feature extraction module. The derived features comprise hourly average temperature and electricity load features, which can capture huge randomness and trend characteristics in electricity load. The DCRB can effectively extract the essential features from the above multi-scale input data compared with CNN-based models. The experiment results show that the proposed method can provide higher forecasting performance than the existing models, by almost 0.9–3.5%. Full article

► Show Figures

Figure 1

25 pages, 5232 KiB

Open AccessArticle

AIBot: A Novel Botnet Capable of Performing Distributed Artificial Intelligence Computing

by Hao Zhao, Hui Shu, Yuyao Huang and Ju Yang

Electronics 2022, 11(19), 3241; https://doi.org/10.3390/electronics11193241 - 9 Oct 2022

Viewed by 3201

Abstract

As an infrastructure platform for launching large-scale cyber attacks, botnets are one of the biggest threats to cyberspace security today. With the development of network technology and changes in the network environment, network attack intelligence has become a trend, and botnet designers are [...] Read more.

As an infrastructure platform for launching large-scale cyber attacks, botnets are one of the biggest threats to cyberspace security today. With the development of network technology and changes in the network environment, network attack intelligence has become a trend, and botnet designers are also committed to developing more destructive intelligent botnets. The feasibility of implementing distributed intelligent computing based on botnet node resources is analyzed with regard to the aspects of program size, communication traffic and resource occupancy. AIBot, a botnet model that can perform intelligent computation in a distributed manner, is proposed from the attacker’s perspective, which hierarchically deploys distributed neural network models in the botnet, thereby organizing nodes to collaboratively perform intelligent computation tasks. AIBot enables the distributed execution of intelligent computing tasks on a cluster of bot nodes by decomposing the computational load of a deep neural network model. A general algorithm for the distributed deployment of neural networks in AIBot is proposed, and the overall operational framework for AIBot is given. Two classical neural network models, CNN and RNN, are used as examples to illustrate specific schemes for deploying and running distributed intelligent computing in AIBot. Experimental scenarios were constructed to experimentally validate and briefly evaluate the performance of the two AIBot attack modes, and the overall efficiency of AIBot was evaluated in terms of execution time. This paper studies new forms of botnet attack techniques from a predictive perspective, aiming to increase defenders’ understanding of potential botnet threats, in order to propose effective defense strategies and improve the botnet defense system. Full article

(This article belongs to the Special Issue New Trends in Information Security)

► Show Figures

Figure 1

14 pages, 405 KiB

Open AccessArticle

Machine Learning to Predict Pre-Eclampsia and Intrauterine Growth Restriction in Pregnant Women

by Lola Gómez-Jemes, Andreea Madalina Oprescu, Ángel Chimenea-Toscano, Lutgardo García-Díaz and María del Carmen Romero-Ternero

Electronics 2022, 11(19), 3240; https://doi.org/10.3390/electronics11193240 - 9 Oct 2022

Cited by 10 | Viewed by 3094

Abstract

The use of artificial intelligence in healthcare in general and in obstetrics and gynecology in particular has great potential. Specifically, machine learning methods could help improve the health and well-being of pregnant women, closely monitoring their health parameters during pregnancy, or reducing maternal [...] Read more.

The use of artificial intelligence in healthcare in general and in obstetrics and gynecology in particular has great potential. Specifically, machine learning methods could help improve the health and well-being of pregnant women, closely monitoring their health parameters during pregnancy, or reducing maternal and perinatal morbidity and mortality with early detection of pathologies. In this work, we propose a machine learning model to predict risk events in pregnancy, in particular the prediction of pre-eclampsia and intrauterine growth restriction, using Doppler measures of the uterine artery, sFlt-1, and PlGF values. For this purpose, we used a public dataset from a study carried out by the University Medical Center of Ljubljana, in which data were collected from 95 pregnant women with pre-eclampsia and intrauterine growth restriction. We adopted a multi-label approach to accomplish the prediction task. Different classifiers were evaluated and compared. The performance of each model was tested in terms of accuracy, precision, recall, F1 score, Hamming loss, and AUC-ROC. On the basis of these parameters, a variation of the decision tree classifier was found to be the best performing model. Our model had a robust recall metric (0.89) and an AUC ROC metric (0.87), taking into account the size of the data and the unbalance of the class. Full article

(This article belongs to the Section Artificial Intelligence)

► Show Figures

Figure 1

16 pages, 4780 KiB

Open AccessArticle

Data Driven SVBRDF Estimation Using Deep Embedded Clustering

by Yong Hwi Kim and Kwan H. Lee

Electronics 2022, 11(19), 3239; https://doi.org/10.3390/electronics11193239 - 9 Oct 2022

Cited by 1 | Viewed by 1407

Abstract

Photo-realistic representation in user-specified view and lighting conditions is a challenging but high-demand technology in the digital transformation of cultural heritages. Despite recent advances in neural renderings, it is still necessary to capture high-quality surface reflectance from photography in a controlled environment for [...] Read more.

Photo-realistic representation in user-specified view and lighting conditions is a challenging but high-demand technology in the digital transformation of cultural heritages. Despite recent advances in neural renderings, it is still necessary to capture high-quality surface reflectance from photography in a controlled environment for real-time applications such as VR/AR and digital arts. In this paper, we present a deep embedding clustering network for spatially-varying bidirectional reflectance distribution function (SVBRDF) estimation. Our network is designed to simultaneously update the reflectance basis and its linear manifold in the spatial domain of SVBRDF. We show that our dual update scheme excels in optimizing the rendering loss in terms of the convergence speed and visual quality compared to the current iterative SVBRDF update methods. Full article

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

► Show Figures

Graphical abstract

18 pages, 1809 KiB

Open AccessArticle

LASNet: A Light-Weight Asymmetric Spatial Feature Network for Real-Time Semantic Segmentation

by Yu Chen, Weida Zhan, Yichun Jiang, Depeng Zhu, Renzhong Guo and Xiaoyu Xu

Electronics 2022, 11(19), 3238; https://doi.org/10.3390/electronics11193238 - 9 Oct 2022

Cited by 4 | Viewed by 1835

Abstract

In recent years, deep learning models have achieved great success in the field of semantic segmentation, which achieve satisfactory performance by introducing a large number of parameters. However, this achievement usually leads to high computational complexity, which seriously limits the deployment of semantic [...] Read more.

In recent years, deep learning models have achieved great success in the field of semantic segmentation, which achieve satisfactory performance by introducing a large number of parameters. However, this achievement usually leads to high computational complexity, which seriously limits the deployment of semantic segmented applications on mobile devices with limited computing and storage resources. To address this problem, we propose a lightweight asymmetric spatial feature network (LASNet) for real-time semantic segmentation. We consider the network parameters, inference speed, and performance to design the structure of LASNet, which can make the LASNet applied to embedded devices and mobile devices better. In the encoding part of LASNet, we propose the LAS module, which retains and utilize spatial information. This module uses a combination of asymmetric convolution, group convolution, and dual-stream structure to reduce the number of network parameters and maintain strong feature extraction ability. In the decoding part of LASNet, we propose the multivariate concatenate module to reuse the shallow features, which can improve the segmentation accuracy and maintain a high inference speed. Our network attains precise real-time segmentation results in a wide range of experiments. Without additional processing and pre-training, LASNet achieves 70.99% mIoU and 110.93 FPS inference speed in the CityScapes dataset with only 0.8 M model parameters. Full article

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

► Show Figures

Figure 1

19 pages, 11609 KiB

Open AccessFeature PaperArticle

QCA-Based PIPO and SIPO Shift Registers Using Cost-Optimized and Energy-Efficient D Flip Flop

by Naira Nafees, Suhaib Ahmed, Vipan Kakkar, Ali Newaz Bahar, Khan A. Wahid and Akira Otsuki

Electronics 2022, 11(19), 3237; https://doi.org/10.3390/electronics11193237 - 8 Oct 2022

Cited by 8 | Viewed by 2995

Abstract

With the growing use of quantum-dot cellular automata (QCA) nanotechnology, digital circuits designed at the Nanoscale have a number of advantages over CMOS devices, including the lower utilization of power, increased processing speed of the circuit, and higher density. There are several flip [...] Read more.

With the growing use of quantum-dot cellular automata (QCA) nanotechnology, digital circuits designed at the Nanoscale have a number of advantages over CMOS devices, including the lower utilization of power, increased processing speed of the circuit, and higher density. There are several flip flop designs proposed in the literature with their realization in the QCA technology. However, the majority of these designs suffer from large cell counts, large area utilization, and latency, which leads to the high cost of the circuits. To address this, this work performed a literature survey of the D flip flop (DFF) designs and complex sequential circuits that can be designed from it. A new design of D flip flop was proposed in this work and to assess the performance of the proposed QCA design, an in-depth comparison with existing designs was performed. Further, sequential circuits such as parallel-in-parallel-out (PIPO) and serial-in-parallel-out (SIPO) shift registers were designed using the flip flop design that was put forward. A comprehensive evaluation of the energy dissipation of all presented fundamental flip-flop circuits and other sequential circuits was also performed using the QCAPro tool, and their energy dissipation maps were also obtained. The suggested designs showed lower power dissipation and were cost-efficient, making them suitable for designing higher-power circuits. Full article

(This article belongs to the Special Issue Resource Sustainability for Energy and Electronics)

► Show Figures

Figure 1

37 pages, 16318 KiB

Open AccessArticle

An Optimal Control Approach for Enhancing Transients Stability and Resilience in Super Smart Grids

by Turki Alsuwian, Abdul Basit, Arslan Ahmed Amin, Muhammad Adnan and Mansoor Ali

Electronics 2022, 11(19), 3236; https://doi.org/10.3390/electronics11193236 - 8 Oct 2022

Cited by 8 | Viewed by 1898

Abstract

Super smart grids (SSGs) are a wide area transmission network that mainly uses renewable energy resources (RERs), contributing to the reduction of greenhouse gas (GHGs) emissions and supporting the power infrastructure of multiple countries. The SSGs comprise two-way communication between the loads and [...] Read more.

Super smart grids (SSGs) are a wide area transmission network that mainly uses renewable energy resources (RERs), contributing to the reduction of greenhouse gas (GHGs) emissions and supporting the power infrastructure of multiple countries. The SSGs comprise two-way communication between the loads and sources of different countries, and these loads can be mostly served with numerous types of RERs tied with the grids. The RERs will play a pivotal role in the development of future grids and the generation of electricity. However, the main challenge to tackle in these RERs is that they are intermittent in nature. Due to intermittency in these RERs, transient stability issues have become one of the critical research challenges in SSGs. These stability issues are escalated and become more difficult to handle if a network is vulnerable to an arising of different kinds of faults. To address these problems, multiple approaches to enhance transient stability already exist in the current literature. After reviewing the literature, flexible alternating current transmission systems (FACTS) devices proved more promising in improving transient stability. Among FACTSdevices, UPFC is a versatile FACTS device, which provides complete stability to power system networks in the form of series and shunt compensations. Considering this scenario, a hypothetical network for SSGs is designed in this research work based on the interconnection between two countries, i.e., Denmark and Norway, to address the transient stability issues in SSGs. The complete probabilistic model of the system is also designed to enhance the stability of the system. The results clearly showed that the insertion of UPFC is an effective technique to enhance the transient stability and resilience of the power system networks as compared to other purposed techniques in the literature. The main contribution of this paper is that extensive simulation studies employing accurate RERs models are used to analyze and investigate various problems arising due to the integration of many clusters of RERs in SSGs. Full article

(This article belongs to the Topic Distributed Generation and Storage in Power Systems)

► Show Figures

Figure 1

24 pages, 6726 KiB

Open AccessArticle

Design and Implementation of Low Noise Amplifier Operating at 868 MHz for Duty Cycled Wake-Up Receiver Front-End

by Ilef Ketata, Sarah Ouerghemmi, Ahmed Fakhfakh and Faouzi Derbel

Electronics 2022, 11(19), 3235; https://doi.org/10.3390/electronics11193235 - 8 Oct 2022

Cited by 13 | Viewed by 6258

Abstract

The integration of wireless communication, e.g., in real- or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, quality of service, and reliability. The improvement of wireless sensor networks (WSN) performance starts by enhancing the capabilities of each sensor [...] Read more.

The integration of wireless communication, e.g., in real- or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, quality of service, and reliability. The improvement of wireless sensor networks (WSN) performance starts by enhancing the capabilities of each sensor node. To minimize latencies without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works since they can be always-on or power-gated with short latencies by a power consumption in the range of some microwatts. Compared to standard receiver technologies, they are usually characterized by drawbacks in terms of sensitivity. To overcome the limitation of the sensitivity of WuRxs, a design of a low noise amplifier (LNA) with several design specifications is required. The challenging task of the LNA design is to provide equitable trade-off performances such as gain, power consumption, the noise figure, stability, linearity, and impedance matching. The design of fast settling LNA for a duty-cycled WuRx front-end operating at a 868 MHz frequency band is investigated in this work. The paper details the trade-offs between design challenges and illustrates practical considerations for the simulation and implementation of a radio frequency (RF) circuit. The implemented LNA competes with many commercialized designs where it reaches single-stage 12 dB gain at a 1.8 V voltage supply and consumes only a 1.6 mA current. The obtained results could be made tunable by working with off-the-shelf components for different wake-up based application exigencies. Full article

(This article belongs to the Special Issue Wireless Sensors Networks in the IoT Era: Advanced Technologies, Recent Challenges, Smart Applications & Future Prospects)

► Show Figures

Figure 1

16 pages, 10970 KiB

Open AccessArticle

Penetration Estimation in SEM, EDAX Dental Imaging Systems for Desensitization Application

by Prawin Angel Michael, Pamela Dharmaraj, Rajasekaran Meenal, Francisxavier Thomas Josh, Jeyaraj Jency Joseph, Kulandaisamy Gerard Joe Nigel and Jude Hemanth

Electronics 2022, 11(19), 3234; https://doi.org/10.3390/electronics11193234 - 8 Oct 2022

Viewed by 1594

Abstract

Background: In the dental field, many people undergo an extreme fear of injections, which is referred to as trypanophobia. The medical procedures that involve injections in the dental field to create numbness raises a certain level of discomfort to all of the patients [...] Read more.

Background: In the dental field, many people undergo an extreme fear of injections, which is referred to as trypanophobia. The medical procedures that involve injections in the dental field to create numbness raises a certain level of discomfort to all of the patients to an extent that the patients avoid treating their teeth or show an anxious or avoidance behavior. Hence, needle phobia is one of the more common phobias amongst people but was not officially recognized as a phobia in dentistry for a long time. In rural areas, some patients, mainly elderly people, might go away without treating their damaged tooth due to fear of injections. Aim: Thus, setting this as the major point of consideration, the researchers have put forth a new concept of dental treatment of creating desensitization without injections rather by adopting a new concept as “iontophoresis”, which causes the ions of specific charges to penetrate the semipermeable membrane, which helps in performing surgeries in the dental field. In the present manuscript, the ‘iontophoresis’ method, along with the imaging systems, was adopted and 45 tooth samples were taken and tested with four different ionic gels that are used in the dental field, and the results were analyzed using the imaging systems of SEM and EDAX for clear analysis. Results: The results through these imaging systems show that the ions have penetrated the tooth, which causes a desensitizing effect in the tooth and makes it numb, so that dental operations can be performed easier and with more perfection. The process of performing dental surgery with a needless process is that the patient to be treated by the dentist is exposed to a gel with electrodes wherein the ions penetrate the tooth, which causes numbness. Conclusion: The incorporation of needle-free injection through the concept of iontophoresis and imaging systems in the dental field introduces a new era in the field of dentistry, making the process simple. Full article

(This article belongs to the Section Industrial Electronics)

► Show Figures

Figure 1

10 pages, 1802 KiB

Open AccessArticle

Downlink MIMO-NOMA System for 6G Internet of Things

by Weiliang Xie, Xue Ding, Bowen Cai, Xiao Li and Mingshuo Wei

Electronics 2022, 11(19), 3233; https://doi.org/10.3390/electronics11193233 - 8 Oct 2022

Cited by 4 | Viewed by 2157

Abstract

This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA [...] Read more.

This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA system based on downlink simultaneous wireless information and power transfer (SWIPT) assistance. To improve the overall performance, we employ machine learning to optimize user-pairing and radio resource allocation. At the end of the paper, the simulation results are obtained, which fully prove that the MIMO-NOMA system constructed in this paper is correct in theory and can be realized in practice. Full article

(This article belongs to the Special Issue Applications, Trends and Development for 5G/6G and beyond Wireless Communication Systems)

► Show Figures

Figure 1

11 pages, 10340 KiB

Open AccessFeature PaperArticle

Electromagnetic Effective-Degree-of-Freedom Limit of a MIMO System in 2-D Inhomogeneous Environment

by Shuai S. A. Yuan, Zi He, Sheng Sun, Xiaoming Chen, Chongwen Huang and Wei E. I. Sha

Electronics 2022, 11(19), 3232; https://doi.org/10.3390/electronics11193232 - 8 Oct 2022

Cited by 5 | Viewed by 2455

Abstract

Compared with a single-input-single-output (SISO) wireless communication system, the benefit of multiple-input-multiple-output (MIMO) technology originates from its extra degree of freedom (DOF), also referred to as scattering channels or spatial electromagnetic (EM) modes, brought by spatial multiplexing. When the physical sizes of transmitting [...] Read more.

Compared with a single-input-single-output (SISO) wireless communication system, the benefit of multiple-input-multiple-output (MIMO) technology originates from its extra degree of freedom (DOF), also referred to as scattering channels or spatial electromagnetic (EM) modes, brought by spatial multiplexing. When the physical sizes of transmitting and receiving arrays are fixed and there are sufficient antennas (typically with half-wavelength spacings), the DOF limit is only dependent on the propagating environment. Analytical methods can be used to estimate this limit in free space, and some approximate models are adopted in stochastic environments, such as Clarke’s model and Ray-tracing methods. However, this DOF limit in a certain inhomogeneous environment has not been well discussed with rigorous full-wave numerical methods. In this work, volume integral equation (VIE) is implemented for investigating the limit of MIMO effective degree of freedom (EDOF) in three representative two-dimensional (2-D) inhomogeneous environments. Moreover, we clarify the relation between the performance of a MIMO system and the scattering characteristics of its propagating environment. Full article

(This article belongs to the Special Issue Recent Advancements and Applications of Computational Electromagnetics)

► Show Figures

Figure 1

17 pages, 3377 KiB

Open AccessArticle

Evaluating the Efficiency of Connected and Automated Buses Platooning in Mixed Traffic Environment

by Suyong Park, Sanghyeon Nam, Gokul S. Sankar and Kyoungseok Han

Electronics 2022, 11(19), 3231; https://doi.org/10.3390/electronics11193231 - 8 Oct 2022

Cited by 4 | Viewed by 1870

Abstract

Due to the battery capacity limitation of battery electric vehicles (BEVs), the importance of minimizing energy consumption has been increasing in recent years. In the mean time, for improving vehicle energy efficiency, platooning has attracted attention of several automakers. Using the connected and [...] Read more.

Due to the battery capacity limitation of battery electric vehicles (BEVs), the importance of minimizing energy consumption has been increasing in recent years. In the mean time, for improving vehicle energy efficiency, platooning has attracted attention of several automakers. Using the connected and automated vehicles (CAVs) technology, platooning can achieve a longer driving range while preserving a closer distance from the preceding vehicle, resulting in the minimization of the aerodynamic force. However, undesired behaviors of human-driven vehicles (HVs) in the platooning group can prohibit the maximization of the energy efficiency. In this paper, we developed a speed planner based on the model predictive control (MPC) to minimize the total platooning energy consumption, and HVs were programmed to maintain a long enough distance from the preceding vehicle to avoid collision. The simulations were performed to determine how HV influences the efficiencies of the platooning group, which is composed of CAVs and HVs together, in several scenarios including the different positions and numbers of the HVs. Test results show that the CAVs planned by our approach reduces energy consumption by about 4% or more than 4% compared to that of the HVs. Full article

(This article belongs to the Special Issue Advances in Autonomous Control Systems and Their Applications)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Electronics, Volume 11, Issue 19 (October-1 2022) – 286 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI