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Electronics, Volume 11, Issue 15 (August-1 2022) – 197 articles

Cover Story (view full-size image): Machine learning is applied in this paper to guarantee the fast convergence of the Born Iterative Method, even in the presence of strong scatterers, by assuming a single operating frequency and a reduced number of antennas in the scattering setup. In particular, the initial estimation of the dielectric profile, provided by the Born Iterative Method, is processed by a specific convolutional neural network to improve the reconstruction by a fast machine learning approach.
Numerical validations on realistic breast phantoms are illustrated, demonstrating an average error of 2.4% and an accuracy greater than 96% for all performed tests, even if considering a single operating frequency and a reduced amount of training data. View this paper
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15 pages, 329 KiB  
Article
The Transition Phenomenon of (1,0)-d-Regular (k, s)-SAT
by Zufeng Fu, Haiying Wang, Jinjiang Liu, Jincheng Zhou, Daoyun Xu and Yihai Pi
Electronics 2022, 11(15), 2475; https://doi.org/10.3390/electronics11152475 - 08 Aug 2022
Viewed by 1211
Abstract
For a d-regular (k,s)-CNF formula, a problem is to determine whether it has a (1,0)-super solution. If so, it is called (1,0)-d-regular (k,s)-SAT. A (1,0)-super solution is an assignment that satisfies [...] Read more.
For a d-regular (k,s)-CNF formula, a problem is to determine whether it has a (1,0)-super solution. If so, it is called (1,0)-d-regular (k,s)-SAT. A (1,0)-super solution is an assignment that satisfies at least two literals of each clause. When the value of any one of the variables is flipped, the (1,0)-super solution is still a solution. Super solutions have gained significant attention for their robustness. Here, a d-regular (k,s)-CNF formula is a special CNF formula with clauses of size exactly k, in which each variable appears exactly s-times, and the absolute frequency difference between positive and negative occurrences of each variable is at most a nonnegative integer d. Obviously, the structure of a d-regular (k,s)-CNF formula is much more regular than other formulas. In this paper, we certify that, for k5, there is a critical function φ(k,d) such that, if sφ(k,d), all d-regular (k,s)-CNF formulas have a (1,0)-super solution; otherwise (1,0)-d-regular (k,s)-SAT is NP-complete. By the Lopsided Local Lemma, we get an existence condition of (1,0)-super solutions and propose an algorithm to find the lower bound of φ(k,d). Full article
(This article belongs to the Section Artificial Intelligence)
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16 pages, 3846 KiB  
Article
Classification and Identification Method of Radio Fuze Target and Sweep Jamming Signals Based on Third-Order Spectrum Features
by Bing Liu, Xinhong Hao, Pengfei Qian, Xin Cai and Wen Zhou
Electronics 2022, 11(15), 2474; https://doi.org/10.3390/electronics11152474 - 08 Aug 2022
Cited by 1 | Viewed by 1308
Abstract
To overcome the problem of insufficiency of linear frequency modulation (LFM) radio fuzes against sweep-type jamming, a method is proposed to classify and identify radio fuze targets and interfering signals based on third-order spectrum features. Using the measured data of an LFM radio [...] Read more.
To overcome the problem of insufficiency of linear frequency modulation (LFM) radio fuzes against sweep-type jamming, a method is proposed to classify and identify radio fuze targets and interfering signals based on third-order spectrum features. Using the measured data of an LFM radio fuze, the third-order spectral transform is applied to the output signals of the detector end under the action of the target and several amplitude modulated sweeping interfering signals, and the amplitude mean value, third-order spectral amplitude entropy, and third-order spectral singular value entropy based on the third-order spectrum are extracted as three-dimensional features. The experimental results show that the classification and identification of targets and AM sweep-type interference using the third-order spectral features of the signal at the detector end has a high success rate, with a comprehensive identification accuracy of 98.33%. Full article
(This article belongs to the Section Circuit and Signal Processing)
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12 pages, 5931 KiB  
Article
A Study on Analysis Method for a Real-Time Neurofeedback System Using Non-Invasive Magnetoencephalography
by Kazuhiro Yagi, Yuta Shibahara, Lindsey Tate and Hiroki Tamura
Electronics 2022, 11(15), 2473; https://doi.org/10.3390/electronics11152473 - 08 Aug 2022
Viewed by 1299
Abstract
For diseases that affect brain function, such as strokes, post-onset rehabilitation plays a critical role in the wellbeing of patients. MEG is a technique with high temporal and spatial resolution that measures brain functions non-invasively, and it is widely used for clinical applications. [...] Read more.
For diseases that affect brain function, such as strokes, post-onset rehabilitation plays a critical role in the wellbeing of patients. MEG is a technique with high temporal and spatial resolution that measures brain functions non-invasively, and it is widely used for clinical applications. Without the ability to concurrently monitor patient brain activity in real-time, the most effective rehabilitation cannot occur. To address this problem, it is necessary to develop a neurofeedback system that can aid rehabilitation in real time; however, doing so requires an analysis method that is quick (less processing time means the patient can better connect the feedback to their mental state), encourages brain-injured patients towards task-necessary neural oscillations, and allows for the spatial location of those oscillation patterns to change over the course of the rehabilitation. As preliminary work to establish such an analysis method, we compared three decomposition methods for their speed and accuracy in detecting event-related synchronization (ERS) and desynchronization (ERD) in a healthy brain during a finger movement task. We investigated FastICA with 10 components, FastICA with 20 components, and spatio-spectral decomposition (SSD). The results showed that FastICA with 10 components was the most suitable for real-time monitoring due to its combination of accuracy and analysis time. Full article
(This article belongs to the Special Issue Advanced Robot and Neuroscience Technology)
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19 pages, 5051 KiB  
Article
Non-Linear Inductor Models Comparison for Switched-Mode Power Supplies Applications
by Daniele Scirè, Giuseppe Lullo and Gianpaolo Vitale
Electronics 2022, 11(15), 2472; https://doi.org/10.3390/electronics11152472 - 08 Aug 2022
Cited by 5 | Viewed by 3617
Abstract
The use of non-linear power inductors, intended as devices exploited up to a current at which the inductance is halved, is of great interest in switched-mode power supplies (SMPSs). Indeed, it allows the use of lighter and cheaper inductors improving the power density. [...] Read more.
The use of non-linear power inductors, intended as devices exploited up to a current at which the inductance is halved, is of great interest in switched-mode power supplies (SMPSs). Indeed, it allows the use of lighter and cheaper inductors improving the power density. On the other hand, the analysis of SMPSs equipped with non-linear inductors requires appropriate modeling of the inductor reproducing the inductance versus current. This paper compares two main analytical models proposed in the literature: the former is based on a polynomial, and the latter exploits the arctangent function to reproduce the non-linearity of the inductance. Performance is compared by considering the effort of retrieving the model’s parameters, evaluating a current profile by the characteristic equation of the inductor, and exploiting the two models to simulate a switched-mode power supply. Results are given both in terms of computation time and accuracy with reference to experimental values, highlighting the pros and cons of each model. Full article
(This article belongs to the Special Issue Feature Papers in Industrial Electronics)
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21 pages, 3939 KiB  
Article
Experimental Study of Thermal and Pressure Performance of Porous Heat Sink Subjected to Al2O3-H2O Nanofluid
by Oguzhan OZBALCI, Ayla DOGAN and Meltem ASILTURK
Electronics 2022, 11(15), 2471; https://doi.org/10.3390/electronics11152471 - 08 Aug 2022
Cited by 1 | Viewed by 1708
Abstract
With the developing technology, the dimensions of electronic systems are becoming smaller, and their performance and the amount of energy they need increases. This situation causes the electronic components to heat up more and the existing cooling systems to become inadequate. In this [...] Read more.
With the developing technology, the dimensions of electronic systems are becoming smaller, and their performance and the amount of energy they need increases. This situation causes the electronic components to heat up more and the existing cooling systems to become inadequate. In this study, instead of the fins used in existing systems, 10 PPI and 40 PPI PHS were placed inside a water block, and the Al2O3-H2O nanofluid at a mass fraction of 0.1% was used as the cooling fluid. Experiments were carried out under constant heat flux of 454.54 W/m2 and 1818.18 W/m2, with volumetric flow rates varying between 100 mL/min and 800 mL/min. The heat transfer results were compared with the results obtained from the base fluid and the empty surface. The results showed that the nanofluid reduced the surface temperatures compared to the base fluid. Especially when PHSs were used together with the nanofluid, a significant increase in heat transfer occurred compared to the empty surface. The highest heat transfer was observed when both the nanofluid and 40 PPI PHS were used together. In addition, the highest thermal performance value was determined as 1.25 times compared to the empty surface when the nanofluid and 10 PPI PHS were used together. Full article
(This article belongs to the Topic Cooling Technologies and Applications)
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18 pages, 26705 KiB  
Review
Key Factors in the Implementation of Wearable Antennas for WBNs and ISM Applications: A Review WBNs and ISM Applications: A Review
by Fatimah Fawzi Hashim, Wan Nor Liza Binti Mahadi, Tariq Bin Abdul Latef and Mohamadariff Bin Othman
Electronics 2022, 11(15), 2470; https://doi.org/10.3390/electronics11152470 - 08 Aug 2022
Cited by 9 | Viewed by 2543
Abstract
The increasing usage of wireless technology has prompted the development of a new generation antenna compatible with the latest devices, with on-body antennas (wearable antennas) being one of the revolutionary applications. This modern design is relevant in technologies that require close human body [...] Read more.
The increasing usage of wireless technology has prompted the development of a new generation antenna compatible with the latest devices, with on-body antennas (wearable antennas) being one of the revolutionary applications. This modern design is relevant in technologies that require close human body contact, such as telemedicine and identification systems, due to its superior performance compared to normal antennas. Some of its finer characteristics include flexibility, reflection coefficient, bandwidth, directivity, gain, radiation, specific absorption rate (SAR), and efficiency that are anticipated to be influenced by the coupling and absorption by the human body tissues. Furthermore, improvements like band-gap structure and artificial magnetic conductors (AMC) and (DGS) are included in the wearable antenna that offers a high degree of isolation from the human body and significantly reduces SAR. In this paper, the development of on-body antennas and how they are affected by the human body were reviewed. Additionally, parameters that affect the performance of this new antenna model, such as materials and common technologies, are included as an auxiliary study for researchers to determine the factors affecting the performance of the wearable antenna and the access to a highly efficient antenna. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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16 pages, 5970 KiB  
Article
Enhancing Virtual Real-Time Monitoring of Photovoltaic Power Systems Based on the Internet of Things
by Ghedhan Boubakr, Fengshou Gu, Laith Farhan and Andrew Ball
Electronics 2022, 11(15), 2469; https://doi.org/10.3390/electronics11152469 - 08 Aug 2022
Cited by 3 | Viewed by 1685
Abstract
Solar power systems have been growing globally to replace fossil fuel-based energy and reduce greenhouse gases (GHG). In addition to panel efficiency deterioration and contamination, the produced power of photovoltaic (PV) systems is intermittent due to the dependency on weather conditions, causing reliability [...] Read more.
Solar power systems have been growing globally to replace fossil fuel-based energy and reduce greenhouse gases (GHG). In addition to panel efficiency deterioration and contamination, the produced power of photovoltaic (PV) systems is intermittent due to the dependency on weather conditions, causing reliability and resiliency issues. Monitoring system parameters can help in predicting faults in time for corrective action to be taken or preventive maintenance to be applied. However, classical monitoring approaches have two main problems: neither local nor centralized monitoring support distributed PV power systems nor provide remote access capability. Therefore, this paper presents an appraisal of a remote monitoring system of PV power generation stations by utilizing the Internet of Things (IoT) and a state-of-the-art tool for virtual supervision. The proposed system allows real-time measurements of all PV system parameters, including surrounding weather conditions, which are then available at the remote control center to check and track the PV power system. The proposed technique is composed of a set of cost-effective devices and algorithms, including a PV power conditioning unit (PCU); a sensor board for measuring the variables that influence PV energy production such as irradiance and temperature, using a communication module based on Wi-Fi for data transmission; and a maximum power point tracking (MPPT) controller for enhancing the efficiency of the PV system. For validating the proposed system, different common scenarios of PV panel conditions including different shading circumstances were considered. The results show that accurate, real-time monitoring with remote access capabilities can provide timely information for predicting and diagnosing the system condition to ensure continued stable power generation and management. Full article
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10 pages, 4392 KiB  
Article
Development and Space-Qualification of a Miniaturized CubeSat’s 2-W EDFA for Space Laser Communications
by Alberto Carrasco-Casado, Koichi Shiratama, Dimitar Kolev, Phuc V. Trinh, Femi Ishola, Tetsuharu Fuse and Morio Toyoshima
Electronics 2022, 11(15), 2468; https://doi.org/10.3390/electronics11152468 - 08 Aug 2022
Cited by 5 | Viewed by 2715
Abstract
The Japanese National Institute of Information and Communications Technology (NICT) is currently developing a high-performance laser-communication terminal for CubeSats aimed at providing a high-datarate communication solution for LEO satellites requiring transmission of large volumes of data from orbit. A key aspect of the [...] Read more.
The Japanese National Institute of Information and Communications Technology (NICT) is currently developing a high-performance laser-communication terminal for CubeSats aimed at providing a high-datarate communication solution for LEO satellites requiring transmission of large volumes of data from orbit. A key aspect of the communication system is a high-power optical amplifier capable of providing enough gain to the transmitted signals to be able to close the link on its counterpart’s receiver with the smallest impact in terms of energy and power on the CubeSat’s platform. This manuscript describes the development of a miniaturized 2-W space-grade 2-stage erbium-doped fiber amplifier (EDFA) compatible with the CubeSat form factor, showing the best power-to-size ratio for a space-qualified EDFA to the best of the authors’ knowledge. Performance results under realistic conditions as well as full space qualification and test are presented, proving that this module can support short-duration LEO-ground downlinks as well as long-duration intersatellite links. Full article
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13 pages, 4265 KiB  
Article
Optimizing the Quantum Circuit for Solving Boolean Equations Based on Grover Search Algorithm
by Hui Liu, Fukun Li and Yilin Fan
Electronics 2022, 11(15), 2467; https://doi.org/10.3390/electronics11152467 - 08 Aug 2022
Viewed by 1906
Abstract
The solution of nonlinear Boolean equations in a binary field plays a crucial part in cryptanalysis and computational mathematics. To speed up the process of solving Boolean equations is an urgent task that needs to be addressed. In this paper, we propose a [...] Read more.
The solution of nonlinear Boolean equations in a binary field plays a crucial part in cryptanalysis and computational mathematics. To speed up the process of solving Boolean equations is an urgent task that needs to be addressed. In this paper, we propose a method for solving Boolean equations based on the Grover algorithm combined with preprocessing using classical algorithms, optimizing the quantum circuit for solving the equations, and implementing the automatic generation of quantum circuits. The method first converted Boolean equations into Boolean expressions to construct the oracle in the Grover algorithm. The quantum circuit was emulated based on the IBM Qiskit framework and then simulated the Grover algorithm on this basis. Finally, the solution of the Boolean equation was implemented. The experimental results proved the feasibility of using the Grover algorithm to solve nonlinear Boolean equations in a binary field, and the correct answer was successfully found under the conditions that the search space was 221 and three G iterations were used. The method in this paper increases the solving scale and solving speed of Boolean equations and enlarges the application area of the Grover algorithm. Full article
(This article belongs to the Special Issue Pattern Recognition and Machine Learning Applications)
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14 pages, 2982 KiB  
Article
Face-Based CNN on Triangular Mesh with Arbitrary Connectivity
by Hui Wang, Yu Guo and Zhengyou Wang
Electronics 2022, 11(15), 2466; https://doi.org/10.3390/electronics11152466 - 08 Aug 2022
Viewed by 2118
Abstract
Applying convolutional neural networks (CNNs) to triangular meshes has always been a challenging task. Because of the complex structure of the meshes, most of the existing methods apply CNNs indirectly to them, and require complex preprocessing or transformation of the meshes. In this [...] Read more.
Applying convolutional neural networks (CNNs) to triangular meshes has always been a challenging task. Because of the complex structure of the meshes, most of the existing methods apply CNNs indirectly to them, and require complex preprocessing or transformation of the meshes. In this paper, we propose a novel face-based CNN, which can be directly applied to triangular meshes with arbitrary connectivity by defining face convolution and pooling. The proposed approach takes each face of the meshes as the basic element, similar to CNNs with pixels of 2D images. First, the intrinsic features of the faces are used as the input features of the network. Second, a sort convolution operation with adjustable convolution kernel sizes is constructed to extract the face features. Third, we design an approximately uniform pooling operation by learnable face collapse, which can be applied to the meshes with arbitrary connectivity, and we directly use its inverse operation as unpooling. Extensive experiments show that the proposed approach is comparable to, or can even outperform, state-of-the-art methods in mesh classification and mesh segmentation. Full article
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12 pages, 2021 KiB  
Article
A Fully Polarity-Aware Double-Node-Upset-Resilient Latch Design
by Jung-Jin Park, Young-Min Kang, Geon-Hak Kim, Ik-Joon Chang and Jinsang Kim
Electronics 2022, 11(15), 2465; https://doi.org/10.3390/electronics11152465 - 08 Aug 2022
Cited by 3 | Viewed by 1634
Abstract
Due to aggressive scaling down, multiple-node-upset hardened design has become a major concern regarding radiation hardening. The proposed latch overcomes the architecture and performance limitations of state-of-the-art double-node-upset (DNU)-resilient latches. A novel stacked latch element is developed with multiple thresholds, regular architecture, increased [...] Read more.
Due to aggressive scaling down, multiple-node-upset hardened design has become a major concern regarding radiation hardening. The proposed latch overcomes the architecture and performance limitations of state-of-the-art double-node-upset (DNU)-resilient latches. A novel stacked latch element is developed with multiple thresholds, regular architecture, increased number of single-event upset (SEU)-insensitive nodes, low power dissipation, and high robustness. The radiation-aware layout considering layout-level issues is also proposed. Compared with state-of-the-art DNU-resilient latches, simulation results show that the proposed latch exhibits up to 92% delay and 80% power reduction in data activity ratio (DAR) of 100%. The radiation simulation using the dual-double exponential current source model shows that the proposed latch has the strongest radiation-hardening capability among the other DNU-resilient latches. Full article
(This article belongs to the Special Issue Radiation Tolerant Electronics, Volume II)
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24 pages, 869 KiB  
Article
Deadline-Aware Dynamic Task Scheduling in Edge–Cloud Collaborative Computing
by Yu Zhang, Bing Tang, Jincheng Luo and Jiaming Zhang
Electronics 2022, 11(15), 2464; https://doi.org/10.3390/electronics11152464 - 08 Aug 2022
Cited by 8 | Viewed by 2357
Abstract
In recent years, modern industry has been exploring the transition to cyber physical system (CPS)-based smart factories. As intelligent industrial detection and control technology grows in popularity, massive amounts of time-sensitive applications are generated. A cutting-edge computing paradigm called edge-cloud collaborative computing was [...] Read more.
In recent years, modern industry has been exploring the transition to cyber physical system (CPS)-based smart factories. As intelligent industrial detection and control technology grows in popularity, massive amounts of time-sensitive applications are generated. A cutting-edge computing paradigm called edge-cloud collaborative computing was developed to satisfy the need of time-sensitive tasks such as smart vehicles and automatic mechanical remote control, which require substantially low latency. In edge-cloud collaborative computing, it is extremely challenging to improve task scheduling while taking into account both the dynamic changes of user requirements and the limited available resources. The current task scheduling system applies a round-robin policy to cyclically select the next server from the list of available servers, but it may not choose the best-suited server for the task. To satisfy the real-time task flow of industrial production in terms of task scheduling based on deadline and time sensitivity, we propose a hierarchical architecture for edge-cloud collaborative environments in the Industrial Internet of Things (IoT) and then simplify and mathematically formulate the time consumption of edge-cloud collaborative computing to reduce latency. Based on the above hierarchical model, we present a dynamic time-sensitive scheduling algorithm (DSOTS). After the optimization of DSOTS, the dynamic time-sensitive scheduling algorithm with greedy strategy (TSGS) that ranks server capability and job size in a hybrid and hierarchical scenario is proposed. What cannot be ignored is that we propose to employ comprehensive execution capability (CEC) to measure the performance of a server for the first time and perform effective server load balancing while satisfying the user’s requirement for tasks. In this paper, we simulate an edge-cloud collaborative computing environment to evaluate the performance of our algorithm in terms of processing time, SLA violation rate, and cost by extending the CloudSimPlus toolkit, and the experimental results are very promising. Aiming to choose a more suitable server to handle dynamically incoming tasks, our algorithm decreases the average processing time and cost by 30% and 45%, respectively, as well as the average SLA violation by 25%, when compared to existing state-of-the-art solutions. Full article
(This article belongs to the Special Issue Edge Computing for Real-Time Systems)
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20 pages, 3007 KiB  
Systematic Review
Systematic Literature Review of Models Used in the Epidemiological Analysis of Bovine Infectious Diseases
by Javier Antonio Ballesteros-Ricaurte, Ramon Fabregat, Angela Carrillo-Ramos, Carlos Parra and Martin Orlando Pulido-Medellín
Electronics 2022, 11(15), 2463; https://doi.org/10.3390/electronics11152463 - 08 Aug 2022
Viewed by 2070
Abstract
There are different bovine infectious diseases that show economic losses and social problems in various sectors of the economy. Most of the studies are focused on some diseases (for example, tuberculosis, salmonellosis, and brucellosis), but there are few studies on other diseases which [...] Read more.
There are different bovine infectious diseases that show economic losses and social problems in various sectors of the economy. Most of the studies are focused on some diseases (for example, tuberculosis, salmonellosis, and brucellosis), but there are few studies on other diseases which are not officially controlled but also have an impact on the economy. This work is a systematic literature review on models (as a theoretical scheme, generally in mathematical form) used in the epidemiological analysis of bovine infectious diseases in the dairy farming sector. In this systematic literature review, criteria were defined for cattle, models, and infectious diseases to select articles on Scopus, IEEE, Xplorer, and ACM databases. The relations between the found models (model type, function and the proposed objective in each work) and the bovine infectious diseases, and the different techniques used and the works over infectious disease in humans, are presented. The outcomes obtained in this systematic literature review provide the state-of-the-art inputs for research on models for the epidemiological analysis of infectious bovine diseases. As a consequence of these outcomes, this work also presents an approach of EiBeLec, which is an adaptive and predictive system for the bovine ecosystem, combining a prediction model that uses machine-learning techniques and an adaptive model that adapts the information presented to end users. Full article
(This article belongs to the Section Computer Science & Engineering)
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34 pages, 11532 KiB  
Review
Hardware-in-the-Loop Simulations: A Historical Overview of Engineering Challenges
by Franc Mihalič, Mitja Truntič and Alenka Hren
Electronics 2022, 11(15), 2462; https://doi.org/10.3390/electronics11152462 - 08 Aug 2022
Cited by 38 | Viewed by 11720
Abstract
The design of modern industrial products is further improved through the hardware-in-the-loop (HIL) simulation. Realistic simulation is enabled by the closed loop between the hardware under test (HUT) and real-time simulation. Such a system involves a field programmable gate array (FPGA) and digital [...] Read more.
The design of modern industrial products is further improved through the hardware-in-the-loop (HIL) simulation. Realistic simulation is enabled by the closed loop between the hardware under test (HUT) and real-time simulation. Such a system involves a field programmable gate array (FPGA) and digital signal processor (DSP). An HIL model can bypass serious damage to the real object, reduce debugging cost, and, finally, reduce the comprehensive effort during the testing. This paper provides a historical overview of HIL simulations through different engineering challenges, i.e., within automotive, power electronics systems, and different industrial drives. Various platforms, such as National Instruments, dSPACE, Typhoon HIL, or MATLAB Simulink Real-Time toolboxes and Speedgoat hardware systems, offer a powerful tool for efficient and successful investigations in different fields. Therefore, HIL simulation practice must begin already during the university’s education process to prepare the students for professional engagements in the industry, which was also verified experimentally at the end of the paper. Full article
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21 pages, 5633 KiB  
Article
Performance Metric Evaluation of Error-Tolerant Adders for 2D Image Blending
by Tanya Mendez, Subramanya G. Nayak, Vasanth Kumar P., Vijay S. R. and Vishnumurthy Kedlaya K.
Electronics 2022, 11(15), 2461; https://doi.org/10.3390/electronics11152461 - 08 Aug 2022
Cited by 4 | Viewed by 1579
Abstract
The hardware implementation of error-tolerant adders using the paradigm of approximate computing has considerably influenced the performance metrics, especially in applications that can compromise accuracy. The foundation for approximate processing is the inclusion of errors in the design to enhance the effectiveness and [...] Read more.
The hardware implementation of error-tolerant adders using the paradigm of approximate computing has considerably influenced the performance metrics, especially in applications that can compromise accuracy. The foundation for approximate processing is the inclusion of errors in the design to enhance the effectiveness and reduce the complexity. This work presents three base adders using the novel concept of error tolerance in digital VLSI design. The research is extended to construct nine variants of power and delay-efficient 16 and 32-bit error-tolerant carry select adders (CSLA). To attain optimization in power and delay, conventional CSLA is refined by substituting ripple carry adders (RCA) with the newly proposed selector unit to minimize the switching activity. The research work includes the power, area, and delay estimates of the design from synthesis using the gpdk-90 nm and gpdk-45 nm standard cell libraries. The proposed adders exhibit reduced delay, power dissipation, area, power delay product (PDP), energy delay product (EDP), and area delay product (ADP) compared to the existing approximate adders. The proposed adder is used in an image blending application. There is a significant improvement in the peak-signal-to-noise ratio (PSNR) in the blended image compared to the standard designs. Full article
(This article belongs to the Special Issue VLSI Circuits & Systems Design)
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27 pages, 4563 KiB  
Article
Multi-Method Diagnosis of CT Images for Rapid Detection of Intracranial Hemorrhages Based on Deep and Hybrid Learning
by Badiea Abdulkarem Mohammed, Ebrahim Mohammed Senan, Zeyad Ghaleb Al-Mekhlafi, Taha H. Rassem, Nasrin M. Makbol, Adwan Alownie Alanazi, Tariq S. Almurayziq, Fuad A. Ghaleb and Amer A. Sallam
Electronics 2022, 11(15), 2460; https://doi.org/10.3390/electronics11152460 - 07 Aug 2022
Cited by 18 | Viewed by 1966
Abstract
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images [...] Read more.
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT images are one of the most important methods of diagnosing intracranial hemorrhages. CT images contain huge amounts of information, requiring a lot of experience and taking a long time for proper analysis and diagnosis. Thus, artificial intelligence techniques provide an automatic mechanism for evaluating CT images to make a diagnosis with high accuracy and help radiologists make their diagnostic decisions. In this study, CT images for rapid detection of intracranial hemorrhages are diagnosed by three proposed systems with various methodologies and materials, where each system contains more than one network. The first system is proposed by three pretrained deep learning models, which are GoogLeNet, ResNet-50 and AlexNet. The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. The third proposed system uses artificial neural networks (ANNs) based on the features of the GoogLeNet, ResNet-50 and AlexNet models, whose dimensions are reduced by a principal component analysis (PCA) algorithm, and then the low-dimensional features are combined with the features of the GLCM and LBP algorithms. All the proposed systems achieved promising results in the diagnosis of CT images for the rapid detection of intracranial hemorrhages. The ANN network based on fusion of the deep feature of AlexNet with the features of GLCM and LBP reached an accuracy of 99.3%, precision of 99.36%, sensitivity of 99.5%, specificity of 99.57% and AUC of 99.84%. Full article
(This article belongs to the Section Computer Science & Engineering)
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19 pages, 715 KiB  
Article
A Fortunate Refining Trip Recommendation Model
by Rizwan Abbas, Gehad Abdullah Amran, Ahmed A. Abdulraheem, Irshad Hussain, Rania M. Ghoniem and Ahmed A. Ewees
Electronics 2022, 11(15), 2459; https://doi.org/10.3390/electronics11152459 - 07 Aug 2022
Cited by 2 | Viewed by 1692
Abstract
Personalized travel recommendations propose locations of interest (LOIs) for users. The LOI sequence suggestion is more complicated than a single LOI recommendation. Only a few studies have considered LOI sequence recommendations. Creating a reliable succession of LOIs is difficult. The two LOIs that [...] Read more.
Personalized travel recommendations propose locations of interest (LOIs) for users. The LOI sequence suggestion is more complicated than a single LOI recommendation. Only a few studies have considered LOI sequence recommendations. Creating a reliable succession of LOIs is difficult. The two LOIs that follow each other should not be identical or from the same category. It is vital to examine the types of subsequent LOIs when designing a sequence of LOIs. Another issue is that providing precise and accurate location recommendations bores users. It can be tedious and monotonous to look at the same types of LOIs repeatedly. Users may want to change their plans in the middle of a trip. The trip must be dynamic rather than static. To address these concerns in the recommendations, organize a customized journey by looking for continuity, implications, innovation, and surprising (i.e., high levels of amusement) LOIs. We use LOI-likeness and category differences between subsequent LOIs to build sequential LOIs. In our travel recommendations, we leveraged luck and dynamicity. We suggest a fortunate refining trip recommendation (FRTR) to address the issues of identifying and rating user pleasure. An algorithm oof compelling recommendation should offer what we are likely to enjoy and provide spontaneous yet objective components to maintain an open doorway to new worlds and discoveries. In addition, two advanced novel estimations are presented to examine the recommended precision of a sequence of LOIs: regulated precision (RP) and pattern precision (PP). They consider the consistency and order of the LOIs. We tested our strategy using data from a real-world dataset and user journey records from Foursquare dataset. We show that our system outperforms other recommendation algorithms to meet the travel interests of users. Full article
(This article belongs to the Section Computer Science & Engineering)
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15 pages, 694 KiB  
Article
Improved Belief Propagation List Decoding for Polar Codes
by Huan Li, Jingxuan Huang and Ce Sun
Electronics 2022, 11(15), 2458; https://doi.org/10.3390/electronics11152458 - 07 Aug 2022
Cited by 1 | Viewed by 2009
Abstract
Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the 5G communication systems. Belief propagation (BP) decoding of polar codes has advantages of low decoding latency and high parallelism but achieves worse bit error ratio (BER) [...] Read more.
Polar codes have become the channel coding scheme for control channel of enhanced mobile broadband in the 5G communication systems. Belief propagation (BP) decoding of polar codes has advantages of low decoding latency and high parallelism but achieves worse bit error ratio (BER) performance compared with the successive cancellation list (SCL) decoding scheme. In this paper, an improved BP list (IBPL) decoding algorithm is proposed with comparable BER performance to SCL algoritm. Firstly, the optimal permuted factor graph is analyzed for polar codes, which improves the performance of the BP decoder without path extension. Furthermore, based on the optimal graph, the bit metric and decoding path metric are proposed to extend and prune the decoding path. The proposed IBPL decoder is focused on not only the permutation of polar codes but also the reliabilities of decoded codewords during each iteration of BP decoding, which has a more accurate decoding path list. The simulation results show that the proposed IBPL decoder improves the BER performance compared with the original BP decoder significantly, and can approach the performance of the SCL decoder at low signal to noise ratio regions. Full article
(This article belongs to the Special Issue Multirate and Multicarrier Communication)
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13 pages, 2414 KiB  
Article
Dim and Small Target Tracking Using an Improved Particle Filter Based on Adaptive Feature Fusion
by Youhui Huo, Yaohong Chen, Hongbo Zhang, Haifeng Zhang and Hao Wang
Electronics 2022, 11(15), 2457; https://doi.org/10.3390/electronics11152457 - 07 Aug 2022
Cited by 4 | Viewed by 1575
Abstract
Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of particle diversity caused by resampling, lead [...] Read more.
Particle filters have been widely used in dim and small target tracking, which plays a significant role in navigation applications. However, their characteristics, such as difficulty of expressing features for dim and small targets and lack of particle diversity caused by resampling, lead to a considerable negative impact on tracking performance. In the present paper, we propose an improved resampling particle filter algorithm based on adaptive multi-feature fusion to address the drawbacks of particle filters for dim and small target tracking and improve the tracking performance. We first establish an observation model based on the adaptive fusion of the features of the weighted grayscale intensity, edge information, and wavelet transform. We then generate new particles based on residual resampling by combining the target position in the previous frame and the particles in the current frame with higher weights, with the tracking accuracy and particle diversity improving simultaneously. The experimental results demonstrate that our proposed method achieves a high tracking performance with a distance accuracy of 77.2% and a running speed of 106 fps, respectively, meaning that it will have a promising prospect in dim and small target tracking applications. Full article
(This article belongs to the Topic Computer Vision and Image Processing)
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11 pages, 888 KiB  
Article
Classification of Atrial Fibrillation and Congestive Heart Failure Using Convolutional Neural Network with Electrocardiogram
by Yunendah Nur Fu’adah and Ki Moo Lim
Electronics 2022, 11(15), 2456; https://doi.org/10.3390/electronics11152456 - 07 Aug 2022
Cited by 2 | Viewed by 1751
Abstract
Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing electrocardiogram (ECG) signals. However, manual diagnosis [...] Read more.
Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing electrocardiogram (ECG) signals. However, manual diagnosis is complex, owing to the various characteristics of ECG signals. An accurate classification system for AF and CHF has the potential to save patient lives. Therefore, this study proposed an ECG signal classification system for AF and CHF using a one-dimensional convolutional neural network (1-D CNN) to provide a robust classification system performance. This study used ECG signal recording of AF, CHF, and NSR, which can be accessed on the Physionet website. A total of 5600 ECG signal segments were obtained from 56 subjects, divided into train sets from 42 subjects (N = 4200 ECG segments), and test sets from 14 subjects (N = 1400). We applied for leave-one-out cross-validation in training to select the best model. The proposed 1-D CNN algorithm successfully classified raw data of ECG signals into normal sinus rhythm (NSR), AF, and CHF by providing the highest classification accuracy of 99.643%, f1-score, recall, and precision of 0.996, respectively, with an AUC score of 0.999. The results showed that the proposed method extracted the ECG signal information directly without needing several preprocessing steps and feature extraction methods that potentially reduce the information contained in the ECG signals. Furthermore, the proposed method outperformed previous studies in classifying AF, CHF, and NSR. Therefore, this approach can be considered as an adjunct for medical personnel to diagnose AF, CHF, and NSR. Full article
(This article belongs to the Section Bioelectronics)
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25 pages, 642 KiB  
Article
Response Time and Intrinsic Information Quality as Criteria for the Selection of Low-Cost Sensors for Use in Mobile Weather Stations
by Agnieszka Chodorek, Robert Ryszard Chodorek and Paweł Sitek
Electronics 2022, 11(15), 2448; https://doi.org/10.3390/electronics11152448 - 07 Aug 2022
Cited by 2 | Viewed by 1374
Abstract
Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost [...] Read more.
Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, i.e., the two-stage selection of sensors, carried out on the basis of both the literature (pre-selection) and experiments (actual selection). We formulated the criteria of the sensor selection for the needs of the sources of weather information: the major one, which is the fast response time of a sensor in a cyber-physical subsystem and two minor ones, which are based on the intrinsic information quality dimensions related to measurement information. These criteria were tested by using a set of twelve weather sensors from different manufacturers. Results show that the two-stage sensor selection allows us to choose the least energy consuming (due to the major criterion) and the most accurate (due to the minor criteria) set of weather sensors, and is able to replace some methods of sensor selection reported in the literature. The proposed method is, however, more versatile and can be used to select any sensors with a response time comparable to electric ones, and for the application of low-cost sensors that are not related to weather stations. Full article
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11 pages, 2914 KiB  
Article
Maintaining Effective Node Chain Connectivity in the Network with Transmission Power of Self-Arranged AdHoc Routing in Cluster Scenario
by Kiruthiga Devi Murugavel, Parthasarathy Ramadass, Rakesh Kumar Mahendran, Arfat Ahmad Khan, Mohd Anul Haq, Sultan Alharby and Ahmed Alhussen
Electronics 2022, 11(15), 2455; https://doi.org/10.3390/electronics11152455 - 06 Aug 2022
Cited by 2 | Viewed by 1353
Abstract
Mobile Ad hoc Networks (MANETs) are intended to work without a fixed framework and provide dependable interchanges to ground vehicles, boats, airplanes, or people and structure a self-mending process that will empower persistent correspondences in any event, when at least one of its [...] Read more.
Mobile Ad hoc Networks (MANETs) are intended to work without a fixed framework and provide dependable interchanges to ground vehicles, boats, airplanes, or people and structure a self-mending process that will empower persistent correspondences in any event, when at least one of its nodes are debilitated or briefly expelled from the system. Notwithstanding, MANETs demonstrate themselves to be progressively harder to create for enormous systems with hundreds or thousands more nodes than initially envisioned. In our proposed technique, the node switches its communication mode depending on the connectivity of the adjacent nodes. The transmission power of each node will be calculated with the help of two major scenarios i.e., tree scenario and zone scenario. The autonomous clustering of the nodes among the tree and the zone scenario will be channelized by a comparison of the transmission power (residual energy) among the nodes. The inter and the intra communication of the node is also discussed in the paper. The result will be carried out by the simulation work in various perspectives, such as checking the percentage level of malicious nodes, traffic density, transmission power, and the longevity of nodes. Full article
(This article belongs to the Section Networks)
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14 pages, 5842 KiB  
Article
Textile Bandwidth-Enhanced Coupled-Mode Substrate-Integrated Cavity Antenna with Slot
by Jie Cui, Feng-Xue Liu, Xiaopeng Shen, Lei Zhao and Hongsheng Yin
Electronics 2022, 11(15), 2454; https://doi.org/10.3390/electronics11152454 - 06 Aug 2022
Cited by 3 | Viewed by 1217
Abstract
A textile bandwidth-enhanced coupled-mode substrate-integrated cavity antenna with a slot is presented. The original coupled-mode substrate-integrated cavity antenna is of two close resonances for the odd and even coupled modes, and a rectangular slot is added on the top layer to introduce a [...] Read more.
A textile bandwidth-enhanced coupled-mode substrate-integrated cavity antenna with a slot is presented. The original coupled-mode substrate-integrated cavity antenna is of two close resonances for the odd and even coupled modes, and a rectangular slot is added on the top layer to introduce a third resonance. Parameters are optimized to merge the bands of the three resonances to realize a widened −10 dB impedance band to cover the Medical Body Area Network band, 2.45 GHz Industrial Scientific Medical band and Long-Term Evolution Band7. The proposed antenna can operate in a −10 dB impedance band of 2.32–2.69 GHz with a 14.9% fractional bandwidth according to the measurements on a fabricated prototype. Simulation and measurement results illustrate the robustness of the proposed textile antenna in the vicinity of the human body and cylindrical bending conditions. In addition, the simulated specific absorption rate of the antenna radiation in the human body is lower than the IEEE and EN limits. Full article
(This article belongs to the Section Microwave and Wireless Communications)
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16 pages, 6862 KiB  
Article
Dynamic Modeling and Simulation of a Four-Wheel Skid-Steer Mobile Robot Using Linear Graphs
by Eric McCormick, Haoxiang Lang and Clarence W. de Silva
Electronics 2022, 11(15), 2453; https://doi.org/10.3390/electronics11152453 - 06 Aug 2022
Cited by 3 | Viewed by 2756
Abstract
This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a four-wheel skid-steer mobile robotic system. An LG representation of the system is proposed, and the accompanying state-space model of the dynamics [...] Read more.
This paper presents the application of the concepts and approaches of linear graph (LG) theory in the modeling and simulation of a four-wheel skid-steer mobile robotic system. An LG representation of the system is proposed, and the accompanying state-space model of the dynamics of a mobile robot system is evaluated using the associated LGtheory MATLAB toolbox, which was developed in our lab. A genetic algorithm (GA)-based parameter estimation method is employed to determine the system parameters, which leads to a very accurate simulation of the model. The developed model is then evaluated and validated by comparing the simulated LG model trajectory with the trajectory of an ROS Gazebo-simulated robot and experimental data obtained from the physical robotic system. The obtained results demonstrate that the proposed LG model, combined with the GA parameter estimation process, produces a highly accurate method of modeling and simulating a mobile robotic system. Full article
(This article belongs to the Special Issue Smart Sensing, Monitoring, and Control in Industry 4.0)
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26 pages, 3446 KiB  
Article
Compiler Optimization Parameter Selection Method Based on Ensemble Learning
by Hui Liu, Jinlong Xu, Sen Chen and Te Guo
Electronics 2022, 11(15), 2452; https://doi.org/10.3390/electronics11152452 - 06 Aug 2022
Cited by 1 | Viewed by 2357
Abstract
Iterative compilation based on machine learning can effectively predict a program’s compiler optimization parameters. Although having some limits, such as the low efficiency of optimization parameter search and prediction accuracy, machine learning-based solutions have been a frontier research field in the field of [...] Read more.
Iterative compilation based on machine learning can effectively predict a program’s compiler optimization parameters. Although having some limits, such as the low efficiency of optimization parameter search and prediction accuracy, machine learning-based solutions have been a frontier research field in the field of iterative compilation and have gained increasing attention. The research challenges are focused on learning algorithm selection, optimal parameter search, and program feature representation. For the existing problems, we propose an ensemble learning-based optimization parameter selection (ELOPS) method for the compiler. First, in order to further improve the optimization parameter search efficiency and accuracy, we proposed a multi-objective particle swarm optimization (PSO) algorithm to determine the optimal compiler parameters of the program. Second, we extracted the mixed features of the program through the feature-class relevance method, rather than using static or dynamic features alone. Finally, as the existing research usually uses a separate machine learning algorithm to build prediction models, an ensemble learning model using program features and optimization parameters was constructed to effectively predict compiler optimization parameters of the new program. Using standard performance evaluation corporation 2006 (SPEC2006) and NAS parallel benchmark (NPB) benchmarks as well as some typical scientific computing programs, we compared ELOPS with the existing methods. The experimental results showed that we can respectively achieve 1.29× and 1.26× speedup when using our method on two platforms, which are better results than those of existing methods. Full article
(This article belongs to the Special Issue Pattern Recognition and Machine Learning Applications)
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14 pages, 5249 KiB  
Article
Design and Simulation of a Novel Single-Chip Integrated MEMS Accelerometer Gyroscope
by Yang Gao, Lin Meng, Jinwu Tong, Zhihu Ruan and Jia Jia
Electronics 2022, 11(15), 2451; https://doi.org/10.3390/electronics11152451 - 06 Aug 2022
Viewed by 1627
Abstract
This paper presents the design and simulation of a single-chip integrated MEMS accelerometer gyroscope by integrating a Coriolis vibratory ring gyroscope and a differential resonant accelerometer into one single-chip structure, measuring both the acceleration and the angular velocity (or the angle). At the [...] Read more.
This paper presents the design and simulation of a single-chip integrated MEMS accelerometer gyroscope by integrating a Coriolis vibratory ring gyroscope and a differential resonant accelerometer into one single-chip structure, measuring both the acceleration and the angular velocity (or the angle). At the same time, it has the advantages of small volume, low cost, and high precision based on the characteristics of a ring gyroscope and resonant accelerometer. The proposed structure consists of a microring gyroscope and a MEMS resonant accelerometer. Tthe accelerometer is located inside the gyroscope and the two structures are concentric. The operating mechanisms of the ring gyroscope and the resonant accelerometer are first introduced. Then, the whole structure of the proposed single-chip integrated accelerometer gyroscope is presented, and the structural components are introduced in detail. Modal analysis shows the resonant frequencies of upper and lower DETFs in resonant accelerometer are 28,944.8 Hz and 28,948.0 Hz, and the resonant frequencies of the ring gyroscope (n=2) are 15,768.5 Hz and 15,770.3 Hz, respectively. The scale factor of the resonant accelerometer is calculated as 83.5 Hz/g by the analysis of the input–output characteristic. Finally, the thermal analysis fully demonstrates that the single-chip integrated accelerometer gyroscope has excellent immunity to temperature change. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Transportation Systems)
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13 pages, 1961 KiB  
Article
A Compact mmWave MIMO Antenna for Future Wireless Networks
by Muhammad Imran Khan, Sarmadullah Khan, Saad Hassan Kiani, Naser Ojaroudi Parchin, Khalid Mahmood, Umair Rafique and Muhammad Mansoor Qadir
Electronics 2022, 11(15), 2450; https://doi.org/10.3390/electronics11152450 - 06 Aug 2022
Cited by 11 | Viewed by 2454
Abstract
This article presents a four-element multiple-input multiple-output (MIMO) antenna design for next-generation millimeter-wave (mmWave) communication systems. The single antenna element of the MIMO systems consists of a T-shaped and plow-shaped patch radiator designed on an ultra-thin Rogers RT/Duroid 5880 substrate. The dimensions of [...] Read more.
This article presents a four-element multiple-input multiple-output (MIMO) antenna design for next-generation millimeter-wave (mmWave) communication systems. The single antenna element of the MIMO systems consists of a T-shaped and plow-shaped patch radiator designed on an ultra-thin Rogers RT/Duroid 5880 substrate. The dimensions of the single antenna are 10 × 12 mm2. The MIMO system is designed by placing four elements in a polarization diversity configuration whose overall dimensions are 24 × 24 mm2. From the measured results, it is observed that the MIMO antenna provides 9.23 GHz impedance bandwidth ranging from 22.43 to 31.66 GHz. In addition, without the utilization of any decoupling network, a minimum isolation of 25 dB is achieved between adjacent MIMO elements. Furthermore, the proposed MIMO antenna system is fabricated, and it is noted that the simulated results are in good agreement with the measured results. Through the achieved results, it can be said that the proposed MIMO antenna system can be used in 5G mmWave radio frequency (RF) front-ends. Full article
(This article belongs to the Special Issue Antenna Designs for 5G/IoT and Space Applications)
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14 pages, 2470 KiB  
Article
Task-Space Cooperative Tracking Control for Networked Uncalibrated Multiple Euler–Lagrange Systems
by Zhuoqun Zhao, Jiang Wang and Hui Zhao
Electronics 2022, 11(15), 2449; https://doi.org/10.3390/electronics11152449 - 06 Aug 2022
Cited by 1 | Viewed by 1018
Abstract
Task-space cooperative tracking control of the networked multiple Euler–Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler–Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and [...] Read more.
Task-space cooperative tracking control of the networked multiple Euler–Lagrange systems is studied in this paper. On the basis of establishing kinematic and dynamic modeling of a Euler–Lagrange system, an innovative task-space coordination controller is designed to deal with the time-varying communicating delays and uncertainties. First, in order to weaken the influence of the uncertainty of kinematic and dynamic parameters on the control error of the system, the product of the Jacobian matrix and the generalized spatial velocity are linearly parameterized; thus, the unknown parameters are separated from known parameters. The online estimation of uncertain parameters is realized by designing parameters and by proposing new adaptive laws for the dynamic and kinematic parameters. Furthermore, to describe the transmission of time-varying delay errors among networked agents, a new error term is introduced, obtained by adding the observation error and tracking error, and the coefficient of the network mutual coupling term related to the time-varying delay rate is added with reference to the generalized space velocity and task-space velocity of the Lagrange systems. In the end, the influence of the time-varying delay on the cooperative tracking control error of the networked multiple Euler–Lagrange systems is eliminated. With the help of Lyapunov stability theory, the tracking errors and synchronization errors of this system are calculated by introducing the Lyapunov–Krasovskii functional; the asymptotic convergence results rigorously prove the stability of the adaptive cooperative control systems. The simulation results verify the excellent performance of the controller. Full article
(This article belongs to the Special Issue Real-Time Control of Embedded Systems)
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15 pages, 4549 KiB  
Article
Study of Breakdown Voltage Stability of Gas-Filled Surge Arresters in the Presence of Gamma Radiation
by Emilija Živanović, Marija Živković and Sandra Veljković
Electronics 2022, 11(15), 2447; https://doi.org/10.3390/electronics11152447 - 05 Aug 2022
Cited by 8 | Viewed by 1565
Abstract
The results presented in this article relate to the study of the impact of gamma radiation on the breakdown voltage of gas-filled surge arrester manufactured by CITEL, Littelfuse and EPCOS at an operating voltage of 230 V. Radium was considered as a source [...] Read more.
The results presented in this article relate to the study of the impact of gamma radiation on the breakdown voltage of gas-filled surge arrester manufactured by CITEL, Littelfuse and EPCOS at an operating voltage of 230 V. Radium was considered as a source of gamma radiation in this research. The stability of breakdown voltage as well as the reliability of gas-filled surge arresters of different manufacturers were investigated using different statistical methods. This gas component operation was based on processes that lead to electrical breakdown and discharge in gas. The breakdown voltage has a stochastic nature, and it is a subject of certain distribution. One thousand voltage measurements of breakdown voltage were carried out for each value of the voltage increase rate, from 1 V/s up to 10 V/s, with and without the presence of additional gamma radiation. The detailed statistical analysis of the obtained experimental data was performed for both cases for all three GFSA types. Moreover, the cumulative distribution functions of breakdown voltage were presented with the applied Weibull distribution fit. The coefficient of correlation as well as Pearson χ2 test showed the strength of the relationship between the experimental distribution functions and the Weibull distribution fits. The values of the Weibull distribution coefficients for all voltage increase rates and for all components were also analyzed with and without gamma radiation. Full article
(This article belongs to the Special Issue Advances in Micro- and Nano-Electronics)
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17 pages, 1663 KiB  
Article
Position Distribution Matters: A Graph-Based Binary Function Similarity Analysis Method
by Zulie Pan, Taiyan Wang, Lu Yu and Yintong Yan
Electronics 2022, 11(15), 2446; https://doi.org/10.3390/electronics11152446 - 05 Aug 2022
Viewed by 2098
Abstract
Binary function similarity analysis evaluates the similarity of functions at the binary level to aid program analysis, which is popular in many fields, such as vulnerability detection, binary clone detection, and malware detection. Graph-based methods have relatively good performance in practice, but currently, [...] Read more.
Binary function similarity analysis evaluates the similarity of functions at the binary level to aid program analysis, which is popular in many fields, such as vulnerability detection, binary clone detection, and malware detection. Graph-based methods have relatively good performance in practice, but currently, they cannot capture similarity in the aspect of the graph position distribution and lose information in graph processing, which leads to low accuracy. This paper presents PDM, a graph-based method to increase the accuracy of binary function similarity detection, by considering position distribution information. First, an enhanced Attributed Control Flow Graph (ACFG+) of a function is constructed based on a control flow graph, assisted by the instruction embedding technique and data flow analysis. Then, ACFG+ is fed to a graph embedding model using the CapsGNN and DiffPool mechanisms, to enrich information in graph processing by considering the position distribution. The model outputs the corresponding embedding vector, and we can calculate the similarity between different function embeddings using the cosine distance. Similarity detection is completed in the Siamese network. Experiments show that compared with VulSeeker and PalmTree+VulSeeker, PDM can stably obtain three-times and two-times higher accuracy, respectively, in binary function similarity detection and can detect up to six-times more results in vulnerability detection. When comparing with some state-of-the-art tools, PDM has comparable Top-5, Top-10, and Top-20 ranking results with respect to BinDiff, Diaphora, and Kam1n0 and significant advantages in the Top-50, Top-100, and Top-200 detection results. Full article
(This article belongs to the Special Issue AI in Cybersecurity)
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