Recent Progress on 3D NAND Flash Technologies

Journal Description

Electronics

Electronics is an international, peer-reviewed, open access journal on the science of electronics and its applications published semimonthly online by MDPI. The Polish Society of Applied Electromagnetics (PTZE) is affiliated with Electronics and their members receive a discount on article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus / SciFinder, Inspec, and many other databases.
Journal Rank: CiteScore - Q2 (Electrical and Electronic Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision provided to authors approximately 17.6 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2021).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion journals for Electronics include: Magnetism, Signals, Network and Software.

Impact Factor: 2.397 (2020) ; 5-Year Impact Factor: 2.408 (2020)

Imprint Information Journal Flyer Open Access ISSN: 2079-9292

Latest Articles

Open AccessArticle

Efficient Integration of PV Sources in Distribution Networks to Reduce Annual Investment and Operating Costs Using the Modified Arithmetic Optimization Algorithm

Oscar Danilo Montoya

Diego Armando Giral-Ramírez

and

Jesus C. Hernández

Electronics 2022, 11(11), 1680; https://doi.org/10.3390/electronics11111680 (registering DOI) - 25 May 2022

Abstract

The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the optimal siting and sizing of photovoltaic resources in medium-voltage levels is addressed from an economical point of view, where the optimization model that represents said problem corresponds to a mixed-integer nonlinear programming model. The maximum allowed size for single photovoltaic units in the distribution network is set at 2400 kW. The investment costs, energy purchase costs and maintenance costs for photovoltaic units, are considered in the objective function. Typical constraints such as power balance, generation capacities, voltage regulation, among others, are considered in the mathematical formulation. The solution of the optimization model is addressed by implementing a modified version of the Arithmetic Optimization Algorithm, which includes a new exploration and exploitation characteristic based on the best current solution in iteration t, i.e.,

x_{best}^{t}

. This improvement is based on a Gaussian distribution operator that generates new candidate solutions with the center at

x_{best}^{t}

, which are uniformly distributed. The main contribution of this research is the proposal of a new hybrid optimization algorithm to solve the exact optimization model, which is based on a combination of the Arithmetic Optimization algorithm with the Vortex Search algorithm and showed excellent numerical results in the IEEE 34-bus grid. The analysis of quantitative results allows us to conclude that the strategy proposed in this work has a greater effectiveness with respect to the General Algebraic Modeling System software solvers, as well as with metaheuristic optimizers such as Genetic Algorithms, the Newton–Metaheuristic Algorithm, and the original Arithmetic Optimization Algorithm. MATLAB was used as a simulation tool. Full article

(This article belongs to the Special Issue Power System Simulation with Renewable Power: Protection, Optimization and Control)

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Open AccessArticle

A Compact Transformer-Based E-Band CMOS Power Amplifier with Enhanced Efficiencies of 15.6% PAE_1dB and 6.5% PAE at 6 dB Power Back-Off

and

Electronics 2022, 11(11), 1679; https://doi.org/10.3390/electronics11111679 (registering DOI) - 25 May 2022

Abstract

This paper presents a compact E-band power amplifier (PA) implemented in a 40 nm CMOS process. The neutralization technique is adopted to improve reverse isolation, stability and power gain. The linearity of the PA is improved by operating the output stage in the deep class-AB region. Transformer-based matching networks (TMNs) are used for impedance transformation, and optimized for output power and efficiency. At 81 GHz, the presented PA achieves a maximum output 1 dB compressed power (P_1dB) of 11.2 dBm and a saturated output power (P_sat) of 12.7 dBm with 1 V supply. The power-added efficiencies at P_1dB (PAE_1dB) and 6 dB power back-off (PBO) are 15.6% and 6.5%, respectively. 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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Open AccessArticle

Investigations on the Potential of 5G for the Detection of Wear in Industrial Roller-Burnishing Processes

and

Electronics 2022, 11(11), 1678; https://doi.org/10.3390/electronics11111678 (registering DOI) - 25 May 2022

Abstract

Roller burnishing represents an economical alternative to conventional surface-finishing processes, such as fine turning or honing. In contrast to the well-known wear mechanisms of chip-forming processes, the wear behavior in roller-burnishing is strongly based on the experience of the machine operators. The nature of the finishing process makes roller-burnishing very sensitive to surface defects, as it is often not possible to rework the last step in a process chain. In the present work, a prototype for a smart roller-burnishing tool with 5G communication is presented, which serves as an inline-monitoring tool to detect tool wear. A suitable metric to monitor the tool wear of the manufacturing roll is suggested, and the potentials of 5G communication for the described use-case are evaluated. Based on the signal-to-noise ratio of the process-force, a metric is found that distinguishes new rolls from worn rolls with very small defects on the micrometer scale. Using the presented approach, it was possible to distinguish the signal-to-noise ratio of a roll with very small wear marks by 3.8% on average. In the case of stronger wear marks, on the order of 20 µm, the difference increased to up to 15.6%. Full article

(This article belongs to the Special Issue 5G Technology in Smart Manufacturing)

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Open AccessArticle

Modelling a New Multifunctional High Accuracy Analogue-to-Digital Converter with an Increased Number of Inputs

and

Electronics 2022, 11(11), 1677; https://doi.org/10.3390/electronics11111677 (registering DOI) - 25 May 2022

Abstract

This paper presents a multi-input analogue-to-digital functional converter manufactured using switched capacitors. A new method of multifunctional analogue-to-digital processing was tested, which allowed the number of inputs to be increased to 10 without compromising accuracy. An algorithm was developed, and the converter’s operation was modelled based on this method. It was found that error values are not significantly affected by the number of input voltages. The value of the lowest input voltage has a decisive influence on the conversion time. The examined multi-input analogue-to-digital functional converter performs multiplication, division, exponentiation, and root extraction operations. The exponent of the power and the degree of the root corresponds to the number of inputs of the converter. Full article

(This article belongs to the Special Issue Advances on Analog-to-Digital and Digital-to-Analog Converters)

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Open AccessArticle

Empirical Study on 5G NR Cochannel Coexistence

and

Electronics 2022, 11(11), 1676; https://doi.org/10.3390/electronics11111676 (registering DOI) - 25 May 2022

Abstract

The 5G non-public network deployments for industrial applications are becoming highly interesting for industries and enterprises owing to dependable wireless performance characteristics. With an increasing trend of network deployments in local licensed and/or shared spectrum, coexistence issues naturally arise. In this article, we present our detailed empirical results on the performance impact of a 5G NR indoor non-public network from a 5G NR outdoor network operating in the same mid-band spectrum. We present experimental results on the uplink and downlink performance impact of a non-public indoor network deployed on an industrial shopfloor. Our results quantify the impact on the uplink and downlink performance characteristics based on realistic traffic loads in a non-public indoor network when using synchronized and unsynchronized Time Division Duplex (TDD) patterns, different UE deployment locations and interference levels. We also present results on mitigating interference effects through robust link adaptation techniques. We believe that this is the first article, which reports quantified 5G NR cochannel coexistence results based on a detailed and systematic study, and provides signficant insights on the cochannel coexistence behavior in realistic deployment scenarios of an industrial shopfloor. Full article

(This article belongs to the Special Issue 5G Technology in Smart Manufacturing)

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Open AccessArticle

Fuzzy Local Information and Bhattacharya-Based C-Means Clustering and Optimized Deep Learning in Spark Framework for Intrusion Detection

Brunel Elvire Bouya-Moko

Edward Kwadwo Boahen

and

Changda Wang

Electronics 2022, 11(11), 1675; https://doi.org/10.3390/electronics11111675 (registering DOI) - 25 May 2022

Abstract

Strong network connections make the risk of malicious activities emerge faster while dealing with big data. An intrusion detection system (IDS) can be utilized for alerting suitable entities when hazardous actions are occurring. Most of the techniques used to classify intrusions lack the techniques executed with big data. This paper devised an optimization-driven deep learning technique for detecting the intrusion using the Spark model. The input data is fed to the data partitioning phase wherein the partitioning of data is done using the proposed fuzzy local information and Bhattacharya-based C-means (FLIBCM). The proposed FLIBCM was devised by combining Bhattacharya distance and fuzzy local information C-Means (FLICM). The feature selection was achieved with classwise info gained to select imperative features. The data augmentation was done with oversampling to make it apposite for further processing. The detection of intrusion was done using a deep Maxout network (DMN), which was trained using the proposed student psychology water cycle caviar (SPWCC) obtained by combining the water cycle algorithm (WCA), the conditional autoregressive value at risk by regression quantiles (CAViaR), and the student psychology-based optimization algorithm (SPBO). The proposed SPWCC-based DMN offered enhanced performance with the highest accuracy of 97.6%, sensitivity of 98%, and specificity of 97%. Full article

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

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Open AccessArticle

Infrared and Visible Image Registration Based on Automatic Robust Algorithm

and

Electronics 2022, 11(11), 1674; https://doi.org/10.3390/electronics11111674 - 25 May 2022

Abstract

Image registration is the base of subsequent image processing and has been widely utilized in computer vision. Aiming at the differences in the resolution, spectrum, and viewpoint of infrared and visible images, and in order to accurately register infrared and visible images, an automatic robust infrared and visible image registration algorithm, based on a deep convolutional network, was proposed. In order to precisely search and locate the feature points, a deep convolutional network is introduced, which solves the problem that a large number of feature points can still be extracted when the pixels of the infrared image are not clear. Then, in order to achieve accurate feature point matching, a rough-to-fine matching algorithm is designed. The rough matching is obtained by location orientation scale transform Euclidean distance, and then, the fine matching is performed based on the update global optimization, and finally, the image registration is realized. Experimental results show that the proposed algorithm has better robustness and accuracy than several advanced registration algorithms. Full article

(This article belongs to the Special Issue Computer Vision Techniques: Theory and Applications)

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Open AccessArticle

Improved YOLO v5 Wheat Ear Detection Algorithm Based on Attention Mechanism

Rui Li

and

Yanpeng Wu

Electronics 2022, 11(11), 1673; https://doi.org/10.3390/electronics11111673 - 24 May 2022

Abstract

The detection and counting of wheat ears are essential for crop field management, but the adhesion and obscuration of wheat ears limit detection accuracy, with problems such as false detection, missed detection, and insufficient feature extraction capability. Previous research results have shown that most methods for detecting wheat ears are of two types: colour and texture extracted by machine learning methods or convolutional neural networks. Therefore, we proposed an improved YOLO v5 algorithm based on a shallow feature layer. There are two main core ideas: (1) to increase the perceptual field by adding quadruple down-sampling in the feature pyramid to improve the detection of small targets, and (2) introducing the CBAM attention mechanism into the neural network to solve the problem of gradient disappearance during training. CBAM is a model that includes both spatial and channel attention, and by adding this module, the feature extraction capability of the network can be improved. Finally, to make the model have better generalization ability, we proposed the Mosaic-8 data enhancement method, with adjusted loss function and modified regression formula for the target frame. The experimental results show that the improved algorithm has an mAP of 94.3%, an accuracy of 88.5%, and a recall of 98.1%. Compared with the relevant model, the improvement effect is noticeable. It shows that the model can effectively overcome the noise of the field environment to meet the practical requirements of wheat ear detection and counting. Full article

(This article belongs to the Special Issue Electronics for Agriculture)

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Open AccessFeature PaperArticle

Empirical Characterization of ReRAM Devices Using Memory Maps and a Dynamic Route Map

Rodrigo Picos

Stavros G. Stavrinides

Mohamad Moner Al Chawa

Carola de Benito

Salvador Dueñas

Helena Castan

Euripides Hatzikraniotis

and

Leon O. Chua

Electronics 2022, 11(11), 1672; https://doi.org/10.3390/electronics11111672 (registering DOI) - 24 May 2022

Abstract

Memristors were proposed in the early 1970s by Leon Chua as a new electrical element linking charge to flux. Since that first introduction, these devices have positioned themselves to be considered as possible fundamental ones for the generations of electronic devices to come. In this paper, we propose a new way to investigate the effects of the electrical variables on the memristance of a device, and we successfully apply this technique to model the behavior of a TiN/Ti/HfO

_{2}

/W ReRAM structure. To do so, we initially apply the Dynamic Route Map technique in the general case to obtain an approximation to the differential equation that determines the behaviour of the device. This is performed by choosing a variable of interest and observing the evolution of its own temporal derivative versus both its value and the applied voltage. Then, according to this technique, it is possible to obtain an approach to the governing equations with no need to make any assumption about the underlying physical mechanisms, by fitting a function to this. We have used a polynomial function, which allows accurate reproduction of the observed electrical behavior of the measured devices, by integrating the resulting differential equation system. Full article

(This article belongs to the Special Issue Resistive Memory Characterization, Simulation, and Compact Modeling)

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Open AccessArticle

Real-Time Classification of Pain Level Using Zygomaticus and Corrugator EMG Features

and

Electronics 2022, 11(11), 1671; https://doi.org/10.3390/electronics11111671 (registering DOI) - 24 May 2022

Abstract

The real-time recognition of pain level is required to perform an accurate pain assessment of patients in the intensive care unit, infants, and other subjects who may not be able to communicate verbally or even express the sensation of pain. Facial expression is a key pain-related behavior that may unlock the answer to an objective pain measurement tool. In this work, a machine learning-based pain level classification system using data collected from facial electromyograms (EMG) is presented. The dataset was acquired from part of the BioVid Heat Pain database to evaluate facial expression from an EMG corrugator and EMG zygomaticus and an EMG signal processing and data analysis flow is adapted for continuous pain estimation. The extracted pain-associated facial electromyography (fEMG) features classification is performed by K-nearest neighbor (KNN) by choosing the value of k which depends on the nonlinear models. The presentation of the accuracy estimation is performed, and considerable growth in classification accuracy is noticed when the subject matter from the features is omitted from the analysis. The ML algorithm for the classification of the amount of pain experienced by patients could deliver valuable evidence for health care providers and aid treatment assessment. The proposed classification algorithm has achieved a 99.4% accuracy for classifying the pain tolerance level from the baseline (P₀ versus P₄) without the influence of a subject bias. Moreover, the result on the classification accuracy clearly shows the relevance of the proposed approach. Full article

(This article belongs to the Section Bioelectronics)

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Open AccessArticle

A 3D Image Registration Method for Laparoscopic Liver Surgery Navigation

Donghui Li

and

Monan Wang

Electronics 2022, 11(11), 1670; https://doi.org/10.3390/electronics11111670 - 24 May 2022

Abstract

At present, laparoscopic augmented reality (AR) navigation has been applied to minimally invasive abdominal surgery, which can help doctors to see the location of blood vessels and tumors in organs, so as to perform precise surgery operations. Image registration is the process of optimally mapping one or more images to the target image, and it is also the core of laparoscopic AR navigation. The key is how to shorten the registration time and optimize the registration accuracy. We have studied the three-dimensional (3D) image registration technology in laparoscopic liver surgery navigation and proposed a new registration method combining rough registration and fine registration. First, the adaptive fireworks algorithm (AFWA) is applied to rough registration, and then the optimized iterative closest point (ICP) algorithm is applied to fine registration. We proposed a method that is validated by the computed tomography (CT) dataset 3D-IRCADb-01. Experimental results show that our method is superior to other registration methods based on stochastic optimization algorithms in terms of registration time and accuracy. Full article

(This article belongs to the Special Issue Advances in Tangible and Embodied Interaction for Virtual and Augmented Reality)

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Open AccessArticle

Performance Degradation Investigation for a GaAs PHEMT High Gain MMIC PA Taking into Account the Temperature

and

Electronics 2022, 11(11), 1669; https://doi.org/10.3390/electronics11111669 - 24 May 2022

Abstract

In order to comprehensively grasp the performance changes for the monolithic microwave integrated circuit (MMIC), this paper proposes that the complete temperature reliability tests for a 2.4–4.4 GHz gallium arsenide (GaAs) pseudomorphic high electron mobility transistor (pHEMT) high gain power amplifier (PA) should be investigated. The performance for this MMIC PA at different temperatures has been presented effectively. The results shown that the direct current (DC) characteristics, small-signal gain (S21), and radio frequency (RF) output characteristics for this MMIC PA decrease and the output third-order intersection point (OIP3) increases with the rising temperature. The main factor influencing the performance is analyzed in detail. For further applications of this MMIC PA, several measures can be utilized to remedy the performance degradation. This paper can provide significant engineer guidance for the reliability design of RF microwave circuits. Full article

(This article belongs to the Section Microelectronics)

Open AccessArticle

Compact CMOS Wideband Instrumentation Amplifiers for Multi-Frequency Bioimpedance Measurement: A Design Procedure

and

Juan Francisco Duque-Carrillo

Electronics 2022, 11(11), 1668; https://doi.org/10.3390/electronics11111668 (registering DOI) - 24 May 2022

Abstract

The design of an instrumentation amplifier (IA), based on indirect current feedback and suited to electrical bioimpedance spectroscopy, is presented. The IA consists of two transconductors and a summing stage, featuring a single-stage configuration process that allows the maximum achievable bandwidth to be extended. The transconductors are linearized by means of resistive source degeneration, whereas the use of super source followers allows a reduction in the values of the source degeneration resistors. This fact leads to a decrease in the overall noise and the silicon area, thus resulting in a compact implementation. A thorough analysis of the proposed solution, accompanied by a design procedure and verified by means of electrical simulations, is also provided. Two versions of the IA, i.e., a single-ended (SE) and a pseudo-differential (PD) structure, were designed and fabricated using 180 nm CMOS technology to operate with a 1.8 V supply. The experimental results, including a BW of 5.2 MHz/8.0 MHz, a CMRR higher than 72 dB/80 dB, a DC current consumption of 139.0

μ

A/219.3

μ

A and a silicon area equal to 0.0173 mm

^{2}

/0.0291 mm

^{2}

for the SE/PD implementation, validate the suitability of the approach. Full article

(This article belongs to the Section Microelectronics)

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Open AccessArticle

Broadband Dynamic Phasor Measurement Method for Harmonic Detection

Yufu Guo

Hang Xu

and

Aobing Chi

Electronics 2022, 11(11), 1667; https://doi.org/10.3390/electronics11111667 - 24 May 2022

Abstract

A large number of nonlinear loads and distributed energy sources are connected to the power system, leading to the generation of broadband dynamic signals including inter-harmonics and decaying DC (DDC) components. This causes deterioration of power quality and errors during power measurement. Therefore, effective phasor estimation methods are needed for accurate monitoring and effective analysis of harmonics and interharmonic phasors. For this purpose, an algorithm is proposed in this paper that is implemented in two parts. The first part is based on the least square method in order to obtain accurate DDC component. In the second part, a Taylor–Fourier model of broadband dynamic harmonic phasor is established. The regularization optimization problem of the sparse acquisition model is solved by harmonic vector estimation method. Finally, the piecewise Split-Bregman Iterative (SBI) framework is used to obtain the estimated value of the harmonic phasor measurement and to realize the reconstruction of the original signal. Through simulation and performance test, the proposed algorithm significantly improves the accuracy of the phasor measurement and estimation, and can provide a reliable theoretical basis for the PMU measurement. Full article

(This article belongs to the Topic Smart Grids: Electrical Power Networks and Communication Systems)

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Open AccessArticle

Prototype of 5G Integrated with TSN for Edge-Controlled Mobile Robotics

Pierre Kehl

Junaid Ansari

Mohammad Hossein Jafari

and

Electronics 2022, 11(11), 1666; https://doi.org/10.3390/electronics11111666 - 24 May 2022

Abstract

The digitization of industries enables a rapid transformation from mass production to individualized manufacturing. Communication plays an essential role in this digital transformation; in particular, wireless communication enables a high degree of flexibility, dynamic interactions, and mobility support in production systems. This paper presents an implementation of a 5G system with Time-Sensitive Networking (TSN) and analyzes a typical industrial use case involving cloud-controlled mobile robots. A prototype setup integrating 5G in a TSN network has been completed to evaluate the 5G-TSN performance for industrial applications. The integrated 5G and TSN prototype has been evaluated with over the air tests in an industrial shopfloor using TSN features of traffic shaping and scheduling. Full article

(This article belongs to the Special Issue 5G Technology in Smart Manufacturing)

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Open AccessArticle

Tuning Bolometric Parameters of Sierpinski Fractal Antenna-Coupled Uncracked/Cracked SWCNT Films by Thermoelectric Characterization at UHF Frequencies

Gustavo Vera-Reveles

José Vulfrano González-Fernández

Juan Francisco Castillo-León

Francisco Javier González

Ramón Díaz de León-Zapata

Ariel Benjamín de la Rosa-Zapata

Norma Orocio-Castro

and

Jorge Simón

Electronics 2022, 11(11), 1665; https://doi.org/10.3390/electronics11111665 - 24 May 2022

Abstract

In this work, the bolometric parameters of Sierpinski fractal antenna-coupled SWCNT semi-metallic films are obtained by thermoelectric characterization, this in order to find out the performance as bolometer. The method was based on an experimental setup considering a line-of-sight wireless link between two identical planar fractal antennas, infrared thermography, and electrical resistance measurements. The experimental setup considered the antennas resonant frequencies. Both the transmitting and receiving antenna were third-iteration Sierpinski fractal dipoles designed to work at UHF frequencies. Films made either of cracked or uncracked SWCNT films were each separately coupled to the receiving fractal antenna. Measurements showed that the receiving antenna that was impinged with radiation at UHF frequencies coming from the transmitting antenna, experienced as it was expected an induction of electric current, the induced current flowed through the film producing a temperature change, which in turn caused changes in the radiated heat of the film, as well as changes in the electrical resistance known as Temperature Coefficient of Resistance TCR. The maximum value of TCR for uncracked SWCNT films was −3.6%K⁻¹, higher than the one observed for cracked SWCNT films which exhibited a maximum value of −1.46%K⁻¹. Measurements for conversion of incident radiation to electrical signals known as the Voltage Responsivity ℜ_v, exhibited values of 9.4 mV/W and 1.4 mV/W for uncracked SWCNT films and cracked SWCNT films, respectively. Full article

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

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Graphical abstract

Open AccessArticle

Design of 2.5D Miniaturized Broadband Absorber for Ultrahigh-Frequency Band

and

Electronics 2022, 11(10), 1664; https://doi.org/10.3390/electronics11101664 - 23 May 2022

Abstract

A broadband metamaterial absorber (MA) structure for Ultrahigh-Frequency (UHF) band was proposed, and the miniaturization of the unit was realized by combining the method of bending metal wires and loading metal vias. The size of the unit cell is 0.040 λ_L × 0.040 λ_L × 0.075 λ_L (λ_L is the wavelength corresponding to the lowest frequency of 0.5 GHz). The simulation results show that the bandwidth of the MA is from 0.50 GHz to 1.33 GHz, and the relative bandwidth is 90.7%. Polarization insensitivity of the MA was realized through assembling a 2 × 2 orthogonal array. TE and TM polarizations maintain more than 80% of the absorptance in the range of 40° at oblique incidence. The consistency of full-wave simulation, circuit simulation and measured results is high, which verifies the broadband absorption characteristics of the proposed MA. Full article

(This article belongs to the Section Circuit and Signal Processing)

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Open AccessArticle

Automatic Weight Prediction System for Korean Cattle Using Bayesian Ridge Algorithm on RGB-D Image

and

Electronics 2022, 11(10), 1663; https://doi.org/10.3390/electronics11101663 - 23 May 2022

Abstract

Weighting the Hanwoo (Korean cattle) is very important for Korean beef producers when selling the Hanwoo at the right time. Recently, research is being conducted on the automatic prediction of the weight of Hanwoo only through images with the achievement of research using deep learning and image recognition. In this paper, we propose a method for the automatic weight prediction of Hanwoo using the Bayesian ridge algorithm on RGB-D images. The proposed system consists of three parts: segmentation, extraction of features, and estimation of the weight of Korean cattle from a given RGB-D image. The first step is to segment the Hanwoo area from a given RGB-D image using depth information and color information, respectively, and then combine them to perform optimal segmentation. Additionally, we correct the posture using ellipse fitting on segmented body image. The second step is to extract features for weight prediction from the segmented Hanwoo image. We extracted three features: size, shape, and gradients. The third step is to find the optimal machine learning model by comparing eight types of well-known machine learning models. In this step, we compared each model with the aim of finding an efficient model that is lightweight and can be used in an embedded system in the real field. To evaluate the performance of the proposed weight prediction system, we collected 353 RGB-D images from livestock farms in Wonju, Gangwon-do in Korea. In the experimental results, random forest showed the best performance, and the Bayesian ridge model is the second best in MSE or the coefficient of determination. However, we suggest that the Bayesian ridge model is the most optimal model in the aspect of time complexity and space complexity. Finally, it is expected that the proposed system will be casually used to determine the shipping time of Hanwoo in wild farms for a portable commercial device. Full article

(This article belongs to the Collection Predictive and Learning Control in Engineering Applications)

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Open AccessArticle

Secure Virtual Network Embedding Algorithms for a Software-Defined Network Considering Differences in Resource Value

Ling Shen

Muqing Wu

and

Min Zhao

Electronics 2022, 11(10), 1662; https://doi.org/10.3390/electronics11101662 - 23 May 2022

Abstract

Software-defined networking (SDN) and network virtualization (NV) are key technologies for future networks, which allow telecommunication service providers (TSPs) to share network resources with users in a flexible manner. Since TSPs have limited virtualized network resources, it is critical to develop effective virtual network embedding (VNE) algorithms for an SDN network to improve resource utilization. However, most existing VNE algorithms ignore the security issues of SDN networks, which may be subject to malicious attacks due to their openness feature. Therefore, it is necessary to develop secure VNE (SVNE) for SDN networks. In this paper, we researched the relationship between resource value and node security-level, and we found that there are differences in the resource value of different nodes. Based on this analysis, we define the evaluation indicators considering differences in resource value for the SVNE problem. Then, we present a mixed-integer linear program (MILP) model to minimize the cost of SVNE. As the formulated optimization problem cannot be solved conveniently, we design two node-ranking approaches to rank physical and virtual nodes, respectively, and we propose two novel SVNE algorithms based on the node ranking approaches. Finally, simulation results reveal that our proposed algorithm is superior to other typical algorithms. Full article

(This article belongs to the Special Issue New Frontiers in Edge Computing for Internet of Things)

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Open AccessReview

Recent Trends in AI-Based Intelligent Sensing

Dushantha Nalin K. Jayakody

Chathuranga M. Wijerathna Basnayaka

and

Ammar Muthanna

Electronics 2022, 11(10), 1661; https://doi.org/10.3390/electronics11101661 - 23 May 2022

Abstract

In recent years, intelligent sensing has gained significant attention because of its autonomous decision-making ability to solve complex problems. Today, smart sensors complement and enhance the capabilities of human beings and have been widely embraced in numerous application areas. Artificial intelligence (AI) has made astounding growth in domains of natural language processing, machine learning (ML), and computer vision. The methods based on AI enable a computer to learn and monitor activities by sensing the source of information in a real-time environment. The combination of these two technologies provides a promising solution in intelligent sensing. This survey provides a comprehensive summary of recent research on AI-based algorithms for intelligent sensing. This work also presents a comparative analysis of algorithms, models, influential parameters, available datasets, applications and projects in the area of intelligent sensing. Furthermore, we present a taxonomy of AI models along with the cutting edge approaches. Finally, we highlight challenges and open issues, followed by the future research directions pertaining to this exciting and fast-moving field. Full article

(This article belongs to the Topic Artificial Intelligence in Sensors)

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