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Electronics, Volume 10, Issue 11 (June-1 2021) – 145 articles

Cover Story (view full-size image): In modern industry, there is still a large number of low-added-value processes that can be automated or semi-automated with safe cooperation between robot and human operators. The European SHERLOCK project aims to integrate an autonomous industrial mobile manipulator (AIMM) to perform cooperative tasks between a robot and a human. In this paper, we report the project's tackle in a paradigmatic industrial application combining accurate autonomous navigation with deep-learning-based 3D perception for pose estimation to locate and manipulate different industrial objects in an unstructured environment. The proposed method presents a combination of different technologies fused in an AIMM that achieve the proposed objective with promising success rates in real environments. View this paper
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Review
Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview
Electronics 2021, 10(11), 1367; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111367 - 07 Jun 2021
Viewed by 528
Abstract
Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of [...] Read more.
Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification. Full article
(This article belongs to the Special Issue Compressive Optical Image Encryption)
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Article
Intelligent Security Monitoring System Based on RISC-V SoC
Electronics 2021, 10(11), 1366; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111366 - 07 Jun 2021
Viewed by 358
Abstract
With the development of the economy and society, the demand for social security and stability increases. However, traditional security systems rely too much on human resources and are affected by uncontrollable community security factors. An intelligent security monitoring system can overcome the limitations [...] Read more.
With the development of the economy and society, the demand for social security and stability increases. However, traditional security systems rely too much on human resources and are affected by uncontrollable community security factors. An intelligent security monitoring system can overcome the limitations of traditional systems and save human resources, contributing to public security. To build this system, a RISC-V SoC is first designed in this paper and implemented on the Nexys-Video Artix-7 FPGA. Then, the Linux operating system is transplanted and successfully run. Meanwhile, the driver of related hardware devices is designed independently. After that, three OpenCV-based object detection models including YOLO (You Only Look Once), Haar (Haar-like features), and LBP (Local Binary Pattern) are compared, and the LBP model is chosen to design applications. Finally, the processing speed of 1.25 s per frame is realized to detect and track moving objects. To sum up, we build an intelligent security monitoring system with real-time detection, tracking, and identification functions through hardware and software collaborative design. This paper also proposes a video downsampling technique. Based on this technique, the BRAM resource usage on the hardware side is reduced by 50% and the amount of pixel data that needs to be processed on the software side is reduced by 75%. A video downsampling technology is also proposed in this paper to achieve better video display effects under limited hardware resources. It provides conditions for future function expansion and improves the models’ processing speed. Additionally, it reduces the run time of the application and improves the system performance. Full article
(This article belongs to the Section Artificial Intelligence)
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Article
Testbed for Experimental Characterization of Indoor Visible Light Communication Channels
Electronics 2021, 10(11), 1365; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111365 - 07 Jun 2021
Viewed by 265
Abstract
In this paper, we describe an experimental testbed designed to evaluate indoor visible light communications (VLC) in realistic scenarios. The system is based on a mockup where the location and orientation of the optical receiver can be modified with precision for a static [...] Read more.
In this paper, we describe an experimental testbed designed to evaluate indoor visible light communications (VLC) in realistic scenarios. The system is based on a mockup where the location and orientation of the optical receiver can be modified with precision for a static configuration of walls and ceiling lamp arrangements. The system utilizes a timing synchronization method, which is based on evaluating the training sequence periods used for channel response estimation, which enables robust frame synchronization. In addition, an adaptive rate orthogonal frequency-division multiplexing (OFDM) scheme is used to assess the VLC performance throughout the receiver plane emulating a real communication. The preliminary results obtained with this prototype, considering a multiple-input single-output (MISO) scenario, demonstrate that reflection on walls yields a significant increase in data rates, which can be additionally improved if appropriate orientation of the receiver is implemented. However, vertical orientation upward of the optical receiver still constitutes a simple solution but efficient enough. Moreover, a good agreement between simulation and experimental results is observed, which confirms the suitability of the mockup as an experimental testbed for practical evaluation of indoor VLC systems, where system performance for different lamp arrangements and receiver designs, including multi-user communications, can be studied. Full article
(This article belongs to the Special Issue Visible Light Communications Technology and Its Applications)
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Article
Performance Tradeoff Analysis of Hybrid Signaling SWIPT Systems with Nonlinear Power Amplifiers
Electronics 2021, 10(11), 1364; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111364 - 07 Jun 2021
Viewed by 354
Abstract
Simultaneous wireless information and power transfer (SWIPT) is a promising technology to achieve wide-area energy transfer by sharing the same radio frequency (RF) signal and infrastructure of legacy wireless communication systems. To enlarge the effective range of energy transfer in practice, it is [...] Read more.
Simultaneous wireless information and power transfer (SWIPT) is a promising technology to achieve wide-area energy transfer by sharing the same radio frequency (RF) signal and infrastructure of legacy wireless communication systems. To enlarge the effective range of energy transfer in practice, it is desirable to have a hybrid signaling SWIPT scheme, which combines a high-power multitone energy signal with a low-power broadband information signal. This paper presents a systematic study on the performance of hybrid signaling SWIPT systems with memoryless nonlinear transmitter power amplifiers (PAs). Using PA efficiency and signal-to-noise-and-distortion ratio (SNDR) as the metrics to measure the efficiency of energy transfer and information transmission, respectively, we derive the tradeoff between these two metrics for two PA classes, two nonlinear PA models, and two SNDR definitions. Our results reveal insights into the fundamental performance tradeoff inherent in SWIPT systems using hybrid signaling schemes. Full article
(This article belongs to the Special Issue Wireless Power Transfer and Its Applications)
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Article
All-Dielectric Metasurface for Sensing Microcystin-LR
Electronics 2021, 10(11), 1363; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111363 - 07 Jun 2021
Viewed by 398
Abstract
Sensing Microcystin-LR (MC-LR) is an important issue for environmental monitoring, as the MC-LR is a common toxic pollutant found in freshwater bodies. The demand for sensitive detection method of MC-LR at low concentrations can be addressed by metasurface-based sensors, which are feasible and [...] Read more.
Sensing Microcystin-LR (MC-LR) is an important issue for environmental monitoring, as the MC-LR is a common toxic pollutant found in freshwater bodies. The demand for sensitive detection method of MC-LR at low concentrations can be addressed by metasurface-based sensors, which are feasible and highly efficient. Here, we demonstrate an all-dielectric metasurface for sensing MC-LR. Its working principle is based on quasi-bound states in the continuum mode (QBIC), and it manifests a high-quality factor and high sensitivity. The dielectric metasurface can detect a small change in the refractive index of the surrounding environment with a quality factor of ~170 and a sensitivity of ~788 nm/RIU. MC-LR can be specifically identified in mixed water with a concentration limit of as low as 0.002 μg/L by a specific recognition technique for combined antigen and antibody. Furthermore, the demonstrated detection of MC-LR can be extended to the identification and monitoring of other analytes, such as viruses, and the designed dielectric metasurface can serve as a monitor platform with high sensitivity and high specific recognition capability. Full article
(This article belongs to the Section Microelectronics)
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Article
Wash Analyses of Flexible and Wearable Printed Circuits for E-Textiles and Their Prediction of Damages
Electronics 2021, 10(11), 1362; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111362 - 07 Jun 2021
Viewed by 507
Abstract
The development of specific user-based wearable smart textiles is gaining interest. The reliability and washability of e-textiles, especially electronic-based components of e-textiles, are under particular investigation nowadays. This is because e-textiles cannot be washed like normal textile products and washing electronic products is [...] Read more.
The development of specific user-based wearable smart textiles is gaining interest. The reliability and washability of e-textiles, especially electronic-based components of e-textiles, are under particular investigation nowadays. This is because e-textiles cannot be washed like normal textile products and washing electronic products is not common practice in our daily life. To adopt the e-textile products in our daily life, new standards, based on product usage, should be developed especially for flexibility and washability. The wearable motherboards are the main component for e-textile systems. They should be washing reliable and flexible for better adoption in the system. In this manuscript, flexible wearable PCBs were prepared with different conductive track widths and protected with silicone coatings. The samples were washed for 50 washing cycles in the household washing machine, and provoked damages were investigated. The PCBs were also investigated for bending tests (simulating mechanical stresses in the washing machine), and resultant damages were discussed and co-related with washing damages. The bending test was performed by bending the FPCBs at 90° over the circular rod and under the known hanging load. Full article
(This article belongs to the Collection Printed and Flexible Electronics)
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Article
AutoCoach: An Intelligent Driver Behavior Feedback Agent with Personality-Based Driver Models
Electronics 2021, 10(11), 1361; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111361 - 07 Jun 2021
Viewed by 497
Abstract
Nowadays, AI has many applications in everyday human activities such as exercise, eating, sleeping, and automobile driving. Tech companies can apply AI to identify individual behaviors (e.g., walking, eating, driving), analyze them, and offer personalized feedback to help individuals make improvements accordingly. While [...] Read more.
Nowadays, AI has many applications in everyday human activities such as exercise, eating, sleeping, and automobile driving. Tech companies can apply AI to identify individual behaviors (e.g., walking, eating, driving), analyze them, and offer personalized feedback to help individuals make improvements accordingly. While offering personalized feedback is more beneficial for drivers, most smart driver systems in the current market do not use it. This paper presents AutoCoach, an intelligent AI agent that classifies drivers’ into different driving-personality groups to offer personalized feedback. We have built a cloud-based Android application to collect, analyze and learn from a driver’s past driving data to provide personalized, constructive feedback accordingly. Our GUI interface provides real-time user feedback for both warnings and rewards for the driver. We have conducted an on-the-road pilot user study. We conducted a pilot study where drivers were asked to use different agent versions to compare personality-based feedback versus non-personality-based feedback. The study result proves our design’s feasibility and effectiveness in improving the user experience when using a personality-based driving agent, with 61% overall acceptance that it is more accurate than non-personality-based. Full article
(This article belongs to the Special Issue Applications of Next-Generation IoT)
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Article
XLNet-Caps: Personality Classification from Textual Posts
Electronics 2021, 10(11), 1360; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111360 - 07 Jun 2021
Viewed by 529
Abstract
Personality characteristics represent the behavioral characteristics of a class of people. Social networking sites have a multitude of users, and the text messages generated by them convey a person’s feelings, thoughts, and emotions at a particular time. These social texts indeed record the [...] Read more.
Personality characteristics represent the behavioral characteristics of a class of people. Social networking sites have a multitude of users, and the text messages generated by them convey a person’s feelings, thoughts, and emotions at a particular time. These social texts indeed record the long-term psychological activities of users, which can be used for research on personality recognition. However, most of the existing deep learning models for multi-label text classification consider long-distance semantics or sequential semantics, but problems such as non-continuous semantics are rarely studied. This paper proposed a deep learning framework that combined XLNet and the capsule network for personality classification (XLNet-Caps) from textual posts. Our personality classification was based on the Big Five personality theory and used the text information generated by the same user at different times. First, we used the XLNet model to extract the emotional features from the text information at each time point, and then, the extracted features were passed through the capsule network to extract the personality features further. Experimental results showed that our model can effectively classify personality and achieve the lowest average prediction error. Full article
(This article belongs to the Special Issue Pervasive Intelligence in Information Technology)
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Article
New Indirect Tire Pressure Monitoring System Enabled by Adaptive Extended Kalman Filtering of Vehicle Suspension Systems
Electronics 2021, 10(11), 1359; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111359 - 07 Jun 2021
Viewed by 417
Abstract
This paper presents a new indirect tire pressure monitoring system (TPMS) based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested methodology is based on the explicit correlation between tire pressure and tire stiffness and is [...] Read more.
This paper presents a new indirect tire pressure monitoring system (TPMS) based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested methodology is based on the explicit correlation between tire pressure and tire stiffness and is available in real time. AEKF-UI is used to simultaneously estimate the time-varying parameter (tire stiffness) of vehicle suspension systems and the road roughness using an unknown input estimator. Simulation studies demonstrate that the proposed algorithm can simultaneously estimate tire stiffness (i.e., tire inflation pressure) variation and unknown road roughness input. The feasibility and effectiveness of the proposed estimation algorithm are verified through a laboratory-level experiment. This study offers a potential application for an alternative indirect TPMS and the estimation of unknown road roughness used for automotive controller design. Full article
(This article belongs to the Section Systems & Control Engineering)
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Article
Analysis of Random Local Descriptors in Face Recognition
Electronics 2021, 10(11), 1358; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111358 - 07 Jun 2021
Viewed by 480
Abstract
This article describes and analyzes the new feature extraction technique, Random Local Descriptor (RLD), that is used for the Permutation Coding Neural Classifier (PCNC), and compares it with Local Binary Pattern (LBP-based) feature extraction. The paper presents a model of face feature detection [...] Read more.
This article describes and analyzes the new feature extraction technique, Random Local Descriptor (RLD), that is used for the Permutation Coding Neural Classifier (PCNC), and compares it with Local Binary Pattern (LBP-based) feature extraction. The paper presents a model of face feature detection using local descriptors, and describes an improvement on the PCNC for the recognition of plane rotated and small displaced face images, as applied to three databases, i.e., ORL, FRAV3D and FEI. All databases are described along with the recognition results that were obtained. We also include a comparison of our classifier with the Support Vector Machine (SVM) and Iterative Closest Point (ICP). The ORL database was selected to compare our RLDs with LBP-based algorithms. The PCNC with the RLDs demonstrated the best recognition rate, i.e., 97.49%, in comparison with 90.49% for LBPs. For the FEI image database, we obtained the best recognition rate, i.e., 93.57%, in comparison with 66.74% for LBPs. Using the RLDs and rotating the original images for FRAV3D, we improved the recognition rate by decreasing by approximately twice the number of errors. In addition, we analyzed the influence of different RLD parameters on the quality of facial recognition. Full article
(This article belongs to the Special Issue Face Recognition Using Machine Learning)
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Review
Autonomous Haulage Systems in the Mining Industry: Cybersecurity, Communication and Safety Issues and Challenges
Electronics 2021, 10(11), 1357; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111357 - 07 Jun 2021
Viewed by 527
Abstract
The current advancement of robotics, especially in Cyber-Physical Systems (CPS), leads to a prominent combination between the mining industry and connected-embedded technologies. This progress has arisen in the form of state-of-the-art automated giant vehicles with Autonomous Haulage Systems (AHS) that can transport ore [...] Read more.
The current advancement of robotics, especially in Cyber-Physical Systems (CPS), leads to a prominent combination between the mining industry and connected-embedded technologies. This progress has arisen in the form of state-of-the-art automated giant vehicles with Autonomous Haulage Systems (AHS) that can transport ore without human intervention. Like CPS, AHS enable autonomous and/or remote control of physical systems (e.g., mining trucks). Thus, similar to CPS, AHS are also susceptible to cyber attacks such as Wi-Fi De-Auth and GPS attacks. With the use of the AHS, several mining activities have been strengthened due to increasing the efficiency of operations. Such activities require ensuring accurate data collection from which precise information about the state of the mine should be generated in a timely and consistent manner. Consequently, the presence of secure and reliable communications is crucial in making AHS mines safer, productive, and sustainable. This paper aims to identify and discuss the relation between safety of AHS in the mining environment and both cybersecurity and communication as well as highlighting their challenges and open issues. We survey the literature that addressed this aim and discuss its pros and cons and then highlight some open issues. We conclude that addressing cybersecurity issues of AHS can ensure the safety of operations in the mining environment as well as providing reliable communication, which will lead to better safety. Additionally, it was found that new communication technologies, such 5G and LTE, could be adopted in AHS-based systems for mining, but further research is needed to considered related cybersecurity issues and attacks. Full article
(This article belongs to the Special Issue Advanced Cybersecurity Services Design)
Article
Cross-Compiler Bipartite Vulnerability Search
Electronics 2021, 10(11), 1356; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111356 - 07 Jun 2021
Viewed by 488
Abstract
Open-source libraries are widely used in software development, and the functions from these libraries may contain security vulnerabilities that can provide gateways for attackers. This paper provides a function similarity technique to identify vulnerable functions in compiled programs and proposes a new technique [...] Read more.
Open-source libraries are widely used in software development, and the functions from these libraries may contain security vulnerabilities that can provide gateways for attackers. This paper provides a function similarity technique to identify vulnerable functions in compiled programs and proposes a new technique called Cross-Compiler Bipartite Vulnerability Search (CCBVS). CCBVS uses a novel training process, and bipartite matching to filter SVM model false positives to improve the quality of similar function identification. This research uses debug symbols in programs compiled from open-source software products to generate the ground truth. This automatic extraction of ground truth allows experimentation with a wide range of programs. The results presented in the paper show that an SVM model trained on a wide variety of programs compiled for Windows and Linux, x86 and Intel 64 architectures can be used to predict function similarity and that the use of bipartite matching substantially improves the function similarity matching performance. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
Factors for the Automation of the Creation of Virtual Reality Experiences to Raise Awareness of Occupational Hazards on Construction Sites
Electronics 2021, 10(11), 1355; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111355 - 06 Jun 2021
Viewed by 581
Abstract
Two of the differential characteristics of the AECO sector (architecture, engineering, construction and operation) are barriers for the mass creation of training materials for its workers. On the one hand, the workplace is unique and changing over time; on the other, the aging [...] Read more.
Two of the differential characteristics of the AECO sector (architecture, engineering, construction and operation) are barriers for the mass creation of training materials for its workers. On the one hand, the workplace is unique and changing over time; on the other, the aging trend of its workers and the unattractive nature of the industry for new generations of professionals. These two problems can be tackled by virtual reality technologies, which allow the agile creation of all kinds of scenarios, while their current technology may be attractive to young people and intuitive for everyone. This work shows the results of an investigation that seeks to provide automated tools based on virtual reality experiences to support learning in occupational risk prevention. This objective is part of the development of a culture for prevention, which allows the treatment of the human factor, with all its complexity and casuistry. The proposal includes the development of a process and tools that allow replicating the specific scenario where the work will be carried out, incorporating risks and probable incidents, systematically establishing cause-effect relationships, incorporating a narrative (storytelling) that provides emotional meaning to users and Lastly, the creation of a workflow that facilitates the agile development of these virtual reality experiences for each specific work. Full article
(This article belongs to the Section Computer Science & Engineering)
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Article
Characterization and Study of the Primitive Dynamic Movements Required to Bi-Manipulate a Box
Electronics 2021, 10(11), 1354; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111354 - 06 Jun 2021
Viewed by 463
Abstract
Automating the action of finding the opening side of a box is not possible if the robot is not capable of reaching and evaluating all of its sides. To achieve this goal, in this paper, three different movement strategies to bi-manipulate a box [...] Read more.
Automating the action of finding the opening side of a box is not possible if the robot is not capable of reaching and evaluating all of its sides. To achieve this goal, in this paper, three different movement strategies to bi-manipulate a box are studied: overturning, lifting, and spinning it over a surface. First of all, the dynamics involved in each of the three movement strategies are studied using physics equations. Then, a set of experiments are conducted to determine if the real response of the humanoid robot, TEO, to a box is consistent with the expected answer based on theoretical calculus. After the dynamics validation, the information on the forces and the position in the end effectors is used to characterize these movements and create its primitives. These primitive movements will be used in the future to design a hybrid position–force control in order to adapt the movements to different kinds of boxes. The structure of this control is also presented in this paper. Full article
(This article belongs to the Special Issue Advances in Robotic Mobile Manipulation)
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Article
Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery
Electronics 2021, 10(11), 1353; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111353 - 06 Jun 2021
Viewed by 521
Abstract
Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) [...] Read more.
Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) has been identified as one of the most promising tools, as is the generation of advanced multivariable models that integrate environmental and internal-battery information. In this article, we describe an algorithm that automatically identifies a battery-equivalent electrochemical model based on electroscopic impedance data. This algorithm allows in operando monitoring of variations in the equivalent circuit parameters that will be used to further estimate variations in the state of health (SoH) and state of charge (SoC) of the battery based on a correlation with experimental aging data corresponding to states of failure or degradation. In the current work, the authors propose a two-step parameter identification algorithm. The first consists of a rough differential evolution algorithm-based identification. The second is based on the Nelder–Mead Simplex search method, which gives a fine parameter estimation. These algorithm results were compared with those of the commercially available Z-view, an equivalent circuit tool estimation that requires expert human input. Full article
(This article belongs to the Special Issue Theory and Applications of Fuzzy Systems and Neural Networks)
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Article
ATMP-CA: Optimising Mixed-Criticality Systems Considering Criticality Arithmetic
Electronics 2021, 10(11), 1352; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111352 - 06 Jun 2021
Viewed by 442
Abstract
Many safety-critical systems use criticality arithmetic, an informal practice of implementing a higher-criticality function by combining several lower-criticality redundant components or tasks. This lowers the cost of development, but existing mixed-criticality schedulers may act incorrectly as they lack the knowledge that the lower-criticality [...] Read more.
Many safety-critical systems use criticality arithmetic, an informal practice of implementing a higher-criticality function by combining several lower-criticality redundant components or tasks. This lowers the cost of development, but existing mixed-criticality schedulers may act incorrectly as they lack the knowledge that the lower-criticality tasks are operating together to implement a single higher-criticality function. In this paper, we propose a solution to this problem by presenting a mixed-criticality mid-term scheduler that considers where criticality arithmetic is used in the system. As this scheduler, which we term ATMP-CA, is a mid-term scheduler, it changes the configuration of the system when needed based on the recent history of deadline misses. We present the results from a series of experiments that show that ATMP-CA’s operation provides a smoother degradation of service compared with reference schedulers that do not consider the use of criticality arithmetic. Full article
(This article belongs to the Special Issue Emerging Advances for Cyber-Physical Systems)
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Article
Active Balun with Center-Tapped Inductor and Double-Balanced Gilbert Mixer for GNSS Applications
Electronics 2021, 10(11), 1351; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111351 - 05 Jun 2021
Viewed by 523
Abstract
A new 1.575 GHz active balun with a classic double-balanced Gilbert mixer for global navigation satellite systems is proposed herein. A simple, low-noise amplifier architecture is used with a center-tapped inductor to generate a differential signal equal in amplitude and shifted in phase [...] Read more.
A new 1.575 GHz active balun with a classic double-balanced Gilbert mixer for global navigation satellite systems is proposed herein. A simple, low-noise amplifier architecture is used with a center-tapped inductor to generate a differential signal equal in amplitude and shifted in phase by 180°. The main advantage of the proposed circuit is that the phase shift between the outputs is always equal to 180°, with an accuracy of ±5°, and the gain difference between the balun outputs does not change by more than 1.5 dB. This phase shift and gain difference between the outputs are also preserved for all process corners, as well as temperature and voltage supply variations. In the balun design, a band calibration system based on a switchable capacitor bank is proposed. The balun and mixer were designed with a 110 nm CMOS process, consuming only a 2.24 mA current from a 1.5 V supply. The measured noise figure and conversion gain of the balun and mixer were, respectively, NF = 7.7 dB and GC = 25.8 dB in the band of interest. Full article
(This article belongs to the Special Issue RF/Mm-Wave Circuits Design and Applications)
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Article
Analyzing and Visualizing Deep Neural Networks for Speech Recognition with Saliency-Adjusted Neuron Activation Profiles
Electronics 2021, 10(11), 1350; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111350 - 05 Jun 2021
Viewed by 518
Abstract
Deep Learning-based Automatic Speech Recognition (ASR) models are very successful, but hard to interpret. To gain a better understanding of how Artificial Neural Networks (ANNs) accomplish their tasks, several introspection methods have been proposed. However, established introspection techniques are mostly designed for computer [...] Read more.
Deep Learning-based Automatic Speech Recognition (ASR) models are very successful, but hard to interpret. To gain a better understanding of how Artificial Neural Networks (ANNs) accomplish their tasks, several introspection methods have been proposed. However, established introspection techniques are mostly designed for computer vision tasks and rely on the data being visually interpretable, which limits their usefulness for understanding speech recognition models. To overcome this limitation, we developed a novel neuroscience-inspired technique for visualizing and understanding ANNs, called Saliency-Adjusted Neuron Activation Profiles (SNAPs). SNAPs are a flexible framework to analyze and visualize Deep Neural Networks that does not depend on visually interpretable data. In this work, we demonstrate how to utilize SNAPs for understanding fully-convolutional ASR models. This includes visualizing acoustic concepts learned by the model and the comparative analysis of their representations in the model layers. Full article
(This article belongs to the Special Issue Machine Learning Applied to Music/Audio Signal Processing)
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Article
Stochastic Restoration of Heavily Compressed Musical Audio Using Generative Adversarial Networks
Electronics 2021, 10(11), 1349; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111349 - 05 Jun 2021
Viewed by 607
Abstract
Lossy audio codecs compress (and decompress) digital audio streams by removing information that tends to be inaudible in human perception. Under high compression rates, such codecs may introduce a variety of impairments in the audio signal. Many works have tackled the problem of [...] Read more.
Lossy audio codecs compress (and decompress) digital audio streams by removing information that tends to be inaudible in human perception. Under high compression rates, such codecs may introduce a variety of impairments in the audio signal. Many works have tackled the problem of audio enhancement and compression artifact removal using deep-learning techniques. However, only a few works tackle the restoration of heavily compressed audio signals in the musical domain. In such a scenario, there is no unique solution for the restoration of the original signal. Therefore, in this study, we test a stochastic generator of a Generative Adversarial Network (GAN) architecture for this task. Such a stochastic generator, conditioned on highly compressed musical audio signals, could one day generate outputs indistinguishable from high-quality releases. Therefore, the present study may yield insights into more efficient musical data storage and transmission. We train stochastic and deterministic generators on MP3-compressed audio signals with 16, 32, and 64 kbit/s. We perform an extensive evaluation of the different experiments utilizing objective metrics and listening tests. We find that the models can improve the quality of the audio signals over the MP3 versions for 16 and 32 kbit/s and that the stochastic generators are capable of generating outputs that are closer to the original signals than those of the deterministic generators. Full article
(This article belongs to the Special Issue Machine Learning Applied to Music/Audio Signal Processing)
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Review
Sentiment Analysis for Fake News Detection
Electronics 2021, 10(11), 1348; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111348 - 05 Jun 2021
Viewed by 857
Abstract
In recent years, we have witnessed a rise in fake news, i.e., provably false pieces of information created with the intention of deception. The dissemination of this type of news poses a serious threat to cohesion and social well-being, since it fosters political [...] Read more.
In recent years, we have witnessed a rise in fake news, i.e., provably false pieces of information created with the intention of deception. The dissemination of this type of news poses a serious threat to cohesion and social well-being, since it fosters political polarization and the distrust of people with respect to their leaders. The huge amount of news that is disseminated through social media makes manual verification unfeasible, which has promoted the design and implementation of automatic systems for fake news detection. The creators of fake news use various stylistic tricks to promote the success of their creations, with one of them being to excite the sentiments of the recipients. This has led to sentiment analysis, the part of text analytics in charge of determining the polarity and strength of sentiments expressed in a text, to be used in fake news detection approaches, either as a basis of the system or as a complementary element. In this article, we study the different uses of sentiment analysis in the detection of fake news, with a discussion of the most relevant elements and shortcomings, and the requirements that should be met in the near future, such as multilingualism, explainability, mitigation of biases, or treatment of multimedia elements. Full article
(This article belongs to the Special Issue Emerging Application of Sentiment Analysis Technologies)
Article
Behavioral Analysis and Immunity Design of the RO-Based TRNG under Electromagnetic Interference
Electronics 2021, 10(11), 1347; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111347 - 04 Jun 2021
Viewed by 517
Abstract
True random-number generators based on ring oscillators (RO-based TRNG) are widely used in the field of information encryption because of their simple structure and compatibility with CMOS technology. However, radiated or conducted electromagnetic interference can dramatically deteriorate the randomness of the output bitstream [...] Read more.
True random-number generators based on ring oscillators (RO-based TRNG) are widely used in the field of information encryption because of their simple structure and compatibility with CMOS technology. However, radiated or conducted electromagnetic interference can dramatically deteriorate the randomness of the output bitstream of the RO-based TRNG, which poses a great threat to security. Traditional research focuses on the innovation of the means of attack and the detection of circuit states. There is a lack of research on the interference mechanism and anti-interference countermeasures. In this paper, the response of the RO array to electromagnetic interference was analyzed, and the concept of synchronous locking was proposed to describe the locking scene of multiple ROs. On the basis of synchronous locking, the RF immunity of the RO-based TRNG was modeled, which can explain the degradation mechanism of bitstream randomness under RFI. Moreover, the design method of gate-delay differentiation is presented to improve the RF immunity of the RO-based TRNG at a low cost. Both transistor-level simulation and board-level measurement proved the rationality of this scheme. Full article
(This article belongs to the Section Microelectronics)
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Article
An Active and Passive Reputation Method for Secure Wideband Spectrum Sensing Based on Blockchain
Electronics 2021, 10(11), 1346; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111346 - 04 Jun 2021
Viewed by 552
Abstract
Spectrum is a kind of non-reproducible scarce strategic resource. A secure wideband spectrum sensing technology provides the possibility for the next generation of ultra-dense, ultra-large-capacity communications to realize the shared utilization of spectrum resources. However, for the open collaborative sensing in cognitive radio [...] Read more.
Spectrum is a kind of non-reproducible scarce strategic resource. A secure wideband spectrum sensing technology provides the possibility for the next generation of ultra-dense, ultra-large-capacity communications to realize the shared utilization of spectrum resources. However, for the open collaborative sensing in cognitive radio networks, the collusion attacks of malicious users greatly affect the accuracy of the sensing results and the security of the entire network. To address this problem, this paper proposes a weighted fusion decision algorithm by using the blockchain technology. The proposed algorithm divides the single-node reputation into active reputation and passive reputation. Through the proposed token threshold concept, the active reputation is set to increase the malicious cost of the node; the passive reputation of the node is determined according to the historical data and recent performance of the blockchain. The final node weight is obtained by considering both kinds of reputation. The proposed scheme can build a trust-free platform for the cognitive radio collaborative networks. Compared with the traditional equal-gain combination algorithm and the centralized sensing algorithm based on the beta reputation system, the simulation results show that the proposed algorithm can obtain reliable sensing results with a lower number of assistants and sampling rate, and can effectively resist malicious users’ collusion attacks. Therefore, the security and the accuracy of cooperative spectrum sensing can be significantly improved in cognitive radio networks. Full article
(This article belongs to the Special Issue Cognitive Radio Applications in Wireless Communication System)
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Article
Machine Learning-Assisted Man Overboard Detection Using Radars
Electronics 2021, 10(11), 1345; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111345 - 04 Jun 2021
Viewed by 628
Abstract
One of the most crucial emergencies that require instant action to be taken during traveling across water is the so-called man overboard (MOB). Thus, constant monitoring equipment needs to be installed for the fast notice and detection of the victim to be rescued, [...] Read more.
One of the most crucial emergencies that require instant action to be taken during traveling across water is the so-called man overboard (MOB). Thus, constant monitoring equipment needs to be installed for the fast notice and detection of the victim to be rescued, if an incident happens. Despite the fact that different installations such as radar sensors, thermal cameras etc., can be handy, a combination of these could be beneficial yet it would increase the complexity. Nevertheless, the full potential may be not reached yet. The key component to what needs to be done in order to achieve the utmost accuracy is artificial intelligence (AI). That is, with the aid of AI, one can deploy an automated surveillance system capable of making its own humanlike decisions regarding such incidents like MOB. To achieve this, fully organized real-time cooperation among the concerned system components is essential. The latter holds since in such dynamically changing operational environments like these, information must be distributed fast, errorless and reliably to the decision center. This study aims to analyze and demonstrate the outcome of an integrated sensor-based system that utilizes AI, implemented for ship incidents. Different machine learning algorithms were used where each one of them made use of information that originated from a cluster of radar sensors located remotely. In particular, the deployed system’s objective is to detect human motion so it can be used to protect against potentially fateful events during ship voyages. Full article
(This article belongs to the Section Artificial Intelligence)
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Article
Precise Reactive Power-Voltage Droop Control of Parallel Virtual Synchronous Generators That Considers Line Impedance
Electronics 2021, 10(11), 1344; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111344 - 03 Jun 2021
Cited by 1 | Viewed by 446
Abstract
Problems such as high power coupling, low distribution accuracy, and insufficient reactive power-voltage droop accuracy occur when distributed generators are operated in parallel due to the influence of line impedance. The precise control of output reactive power and voltage is difficult to achieve [...] Read more.
Problems such as high power coupling, low distribution accuracy, and insufficient reactive power-voltage droop accuracy occur when distributed generators are operated in parallel due to the influence of line impedance. The precise control of output reactive power and voltage is difficult to achieve using traditional virtual synchronous generator (VSG) control. Taking this into consideration, this study proposes a virtual synchronous generator reactive power-voltage integrated control strategy that considers line parameters to solve this problem. First, the impedance voltage drop of the line is compensated for in accordance with local information control to ensure the consistency of the control voltage in parallel operation of distributed generators and to realize the precise droop control of reactive power and the voltage of the point of common coupling (UPCC). Second, virtual negative impedance control is added to change the equivalent output impedance characteristics of the system and achieve power decoupling. On this basis, the active frequency and reactive voltage decoupling control effect of the improved control strategy is quantified and analyzed using the relative gain matrix. The accuracy of reactive power distribution and droop control is theoretically derived and analyzed by establishing a small-signal model of a two-machine parallel system. Finally, the accuracy and effectiveness of the proposed integrated control strategy are verified via a simulation model and an experimental platform for parallel operation. Results show that the proposed integrated control strategy can effectively solve the problems of power decoupling and accurate distribution, reduce system loop current, and realize accurate reactive power-voltage droop. Compared with the traditional VSG control strategy, the dynamic deviation of UPCC is reduced by at least 40% when a large-scale load disturbance occurs. Full article
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Article
CioSy: A Collaborative Blockchain-Based Insurance System
Electronics 2021, 10(11), 1343; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111343 - 03 Jun 2021
Viewed by 564
Abstract
The insurance industry is heavily dependent on several processes executed among multiple entities, such as insurer, insured, and third-party services. The increasingly competitive environment is pushing insurance companies to use advanced technologies to address multiple challenges, namely lack of trust, lack of transparency, [...] Read more.
The insurance industry is heavily dependent on several processes executed among multiple entities, such as insurer, insured, and third-party services. The increasingly competitive environment is pushing insurance companies to use advanced technologies to address multiple challenges, namely lack of trust, lack of transparency, and economic instability. To this end, blockchain is used as an emerging technology that enables transparent and secure data storage and transmission. In this paper, we propose CioSy, a collaborative blockchain-based insurance system for monitoring and processing the insurance transactions. To the best of our knowledge, the existing approaches do not consider collaborative insurance to achieve an automated, transparent, and tamper-proof solution. CioSy aims at automating the insurance policy processing, claim handling, and payment using smart contracts. For validation purposes, an experimental prototype is developed on Ethereum blockchain. Our experimental results show that the proposed approach is both feasible and economical in terms of time and cost. Full article
(This article belongs to the Special Issue Blockchain-Based Technology for Mobile Application)
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Article
Thermal Analyses of Reactor under High-Power and High-Frequency Square Wave Voltage Based on Improved Thermal Network Model
Electronics 2021, 10(11), 1342; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111342 - 03 Jun 2021
Viewed by 406
Abstract
In order to quickly calculate the stable temperature of a reactor driven by high-frequency and high-power pulse voltage, an improved thermal network model suitable for a reactor under this condition is established in this paper. In power electronic equipment, the maximum temperature of [...] Read more.
In order to quickly calculate the stable temperature of a reactor driven by high-frequency and high-power pulse voltage, an improved thermal network model suitable for a reactor under this condition is established in this paper. In power electronic equipment, the maximum temperature of the reactor is usually concentrated in its internal core. Moreover, with the increasing demand of high-power density in power electronic devices, the structure design of the reactor is more compact, and the internal magnetic field will affect the accuracy of the temperature-measuring device. Therefore, it is difficult to measure the internal temperature rise of the reactor directly. However, its stable operating temperature could be analyzed by the thermal network modeling methods and heat transfer analysis tool. Therefore, a convenient and accurate thermal network model of the reactor under high-frequency and high-power square wave voltage is established by considering the equivalent thermal resistance of the winding, the three-dimensional geometrical effect of the core and the effect of the high-frequency repeated pulse stress on the thermal penetration depth. Additionally, the internal temperature of the reactor can be obtained through the external temperature in terms of the presented model. To verify the feasibility of the thermal network model, the corresponding multiphysical field finite element simulation and the reactor temperature measurement platform is built. The simulation and experimental results show that the proposed thermal network model has a high precision and fast calculation speed, and it is an effective tool for thermal analysis of the reactor. Full article
(This article belongs to the Special Issue Thermal Management of Electronic Packaging)
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Article
Botnet Attack Detection Using Local Global Best Bat Algorithm for Industrial Internet of Things
Electronics 2021, 10(11), 1341; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111341 - 03 Jun 2021
Viewed by 546
Abstract
The need for timely identification of Distributed Denial-of-Service (DDoS) attacks in the Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT devices deployed rapidly grows globally and the volume of such attacks rises to unprecedented levels. [...] Read more.
The need for timely identification of Distributed Denial-of-Service (DDoS) attacks in the Internet of Things (IoT) has become critical in minimizing security risks as the number of IoT devices deployed rapidly grows globally and the volume of such attacks rises to unprecedented levels. Instant detection facilitates network security by speeding up warning and disconnection from the network of infected IoT devices, thereby preventing the botnet from propagating and thereby stopping additional attacks. Several methods have been developed for detecting botnet attacks, such as Swarm Intelligence (SI) and Evolutionary Computing (EC)-based algorithms. In this study, we propose a Local-Global best Bat Algorithm for Neural Networks (LGBA-NN) to select both feature subsets and hyperparameters for efficient detection of botnet attacks, inferred from 9 commercial IoT devices infected by two botnets: Gafgyt and Mirai. The proposed Bat Algorithm (BA) adopted the local-global best-based inertia weight to update the bat’s velocity in the swarm. To tackle with swarm diversity of BA, we proposed Gaussian distribution used in the population initialization. Furthermore, the local search mechanism was followed by the Gaussian density function and local-global best function to achieve better exploration during each generation. Enhanced BA was further employed for neural network hyperparameter tuning and weight optimization to classify ten different botnet attacks with an additional one benign target class. The proposed LGBA-NN algorithm was tested on an N-BaIoT data set with extensive real traffic data with benign and malicious target classes. The performance of LGBA-NN was compared with several recent advanced approaches such as weight optimization using Particle Swarm Optimization (PSO-NN) and BA-NN. The experimental results revealed the superiority of LGBA-NN with 90% accuracy over other variants, i.e., BA-NN (85.5% accuracy) and PSO-NN (85.2% accuracy) in multi-class botnet attack detection. Full article
(This article belongs to the Special Issue Design of Intelligent Intrusion Detection Systems)
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Article
A Novel Single-Switch Single-Stage LED Driver with Power Factor Correction and Current Balancing Capability
Electronics 2021, 10(11), 1340; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111340 - 03 Jun 2021
Viewed by 494
Abstract
A novel single-switch single-stage high power factor LED driver is proposed by integrating a flyback converter, a buck–boost converter and a current balance circuit. Only an active switch and a corresponding control circuit are used. The LED power can be adjusted by the [...] Read more.
A novel single-switch single-stage high power factor LED driver is proposed by integrating a flyback converter, a buck–boost converter and a current balance circuit. Only an active switch and a corresponding control circuit are used. The LED power can be adjusted by the control scheme of pulse–width modulation (PWM). The flyback converter performs the function of power factor correction (PFC), which is operated at discontinuous-current mode (DCM) to achieve unity power factor and low total current harmonic distortion (THDi). The buck–boost converter regulates the dc-link voltage to obtain smooth dc voltage for the LED. The current–balance circuit applies the principle of ampere-second balance of capacitors to obtain equal current in each LED string. The steady-state analyses for different operation modes is provided, and the mathematical equations for designing component parameters are conducted. Finally, a 90-W prototype circuit with three LED strings was built and tested. Experimental results show that the current in each LED string is indeed consistent. High power factor and low THDi can be achieved. LED power is regulated from 100% to 25% rated power. Satisfactory performance has proved the feasibility of this circuit. Full article
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Article
The Evaluation of an Asymptotic Solution to the Sommerfeld Radiation Problem Using an Efficient Method for the Calculation of Sommerfeld Integrals in the Spectral Domain
Electronics 2021, 10(11), 1339; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111339 - 02 Jun 2021
Viewed by 485
Abstract
A recently developed high-frequency asymptotic solution for the famous “Sommerfeld radiation problem” is revisited. The solution is based on an analysis performed in the spectral domain, through which a compact asymptotic formula describes the behavior of the EM field, which emanates from a [...] Read more.
A recently developed high-frequency asymptotic solution for the famous “Sommerfeld radiation problem” is revisited. The solution is based on an analysis performed in the spectral domain, through which a compact asymptotic formula describes the behavior of the EM field, which emanates from a vertical Hertzian radiating dipole, located above flat, lossy ground. The paper is divided into two parts. We first demonstrate an efficient technique for the accurate numerical calculation of the well-known Sommerfeld integrals. The results are compared against alternative calculation approaches and validated with the corresponding Norton figures for the surface wave. In the second part, we introduce the asymptotic solution and investigate its performance; we compare the solution with the accurate numerical evaluation for the received EM field and with a more basic asymptotic solution to the given problem, obtained via the application of the Stationary Phase Method. Simulations for various frequencies, distances, altitudes, and ground characteristics are illustrated and inferences for the applicability of the solution are made. Finally, special cases leading to analytical field expressions close as well as far from the interface are examined. Full article
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Article
Body Size Measurement Using a Smartphone
Electronics 2021, 10(11), 1338; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10111338 - 02 Jun 2021
Viewed by 493
Abstract
Measuring body sizes accurately and rapidly for optimal garment fit detection has been a challenge for fashion retailers. Especially for apparel e-commerce, there is an increasing need for digital and convenient ways to obtain body measurements to provide their customers with correct-fitting products. [...] Read more.
Measuring body sizes accurately and rapidly for optimal garment fit detection has been a challenge for fashion retailers. Especially for apparel e-commerce, there is an increasing need for digital and convenient ways to obtain body measurements to provide their customers with correct-fitting products. However, the currently available methods depend on cumbersome and complex 3D reconstruction-based approaches. In this paper, we propose a novel smartphone-based body size measurement method that does not require any additional objects of a known size as a reference when acquiring a subject’s body image using a smartphone. The novelty of our proposed method is that it acquires measurement positions using body proportions and machine learning techniques, and it performs 3D reconstruction of the body using measurements obtained from two silhouette images. We applied our proposed method to measure body sizes (i.e., waist, lower hip, and thigh circumferences) of males and females for selecting well-fitted pants. The experimental results show that our proposed method gives an accuracy of 95.59% on average when estimating the size of the waist, lower hip, and thigh circumferences. Our proposed method is expected to solve issues with digital body measurements and provide a convenient garment fit detection solution for online shopping. Full article
(This article belongs to the Special Issue Smart Bioelectronics and Wearable Systems)
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