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Volume 13
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Electronics, Volume 13, Issue 1 (January-1 2024) – 242 articles

Cover Story (view full-size image): In this paper, we propose a design strategy that is implemented to mitigate the electromagnetic interface (EMI) problems that occur in the circuitry of a dishwasher. To implement improvements, we focus on addressing conducted emissions (CE) by analyzing load impedance and core characteristics at current levels. It also describes how to incorporate a common mode (CM) core attachment design that targets the motor's resonant frequency in order to block noise at this frequency and thereby improve the radiated power (RP). Additionally, the effectiveness of the proposed improvements is verified through the modeling of the filter and a comparison of the impedance characteristics. Finally, the practicality of the mass-produced product is verified by eliminating the harness core and designing the noise filter to be miniaturized. View this paper
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17 pages, 8829 KiB  
Article
Multiple Moving Vehicles Tracking Algorithm with Attention Mechanism and Motion Model
by Jiajun Gao, Guangjie Han, Hongbo Zhu and Lyuchao Liao
Electronics 2024, 13(1), 242; https://doi.org/10.3390/electronics13010242 - 4 Jan 2024
Cited by 1 | Viewed by 2556
Abstract
With the acceleration of urbanization and the increasing demand for travel, current road traffic is experiencing rapid growth and more complex spatio-temporal logic. Vehicle tracking on roads presents several challenges, including complex scenes with frequent foreground–background transitions, fast and nonlinear vehicle movements, and [...] Read more.
With the acceleration of urbanization and the increasing demand for travel, current road traffic is experiencing rapid growth and more complex spatio-temporal logic. Vehicle tracking on roads presents several challenges, including complex scenes with frequent foreground–background transitions, fast and nonlinear vehicle movements, and the presence of numerous unavoidable low-score detection boxes. In this paper, we propose AM-Vehicle-Track, following the proven-effective paradigm of tracking by detection (TBD). At the detection stage, we introduce the lightweight channel block attention mechanism (LCBAM), facilitating the detector to concentrate more on foreground features with limited computational resources. At the tracking stage, we innovatively propose the noise-adaptive extended Kalman filter (NSA-EKF) module to extract vehicles’ motion information while considering the impact of detection confidence on observation noise when dealing with nonlinear motion. Additionally, we borrow the Byte data association method to address unavoidable low-score detection boxes, enabling secondary association to reduce ID switches. We achieve 42.2 MOTA, 51.2 IDF1, and 364 IDs on the test set of VisDrone-MOT with 72 FPS. The experimental results showcase our approach’s highly competitive performance, attaining SOTA tracking performance with a fast speed. Full article
(This article belongs to the Special Issue Computer Vision Applications for Autonomous Vehicles)
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21 pages, 8312 KiB  
Review
Active-Matrix Array Based on Thin-Film Transistors Using Emerging Materials for Application: From Lab to Industry
by Seongjae Kim and Hocheon Yoo
Electronics 2024, 13(1), 241; https://doi.org/10.3390/electronics13010241 - 4 Jan 2024
Cited by 2 | Viewed by 3124
Abstract
The active-matrix technology incorporates a transistor to exert precise control over each pixel within a pixel array, eliminating the issue of crosstalk between neighboring pixels that is prevalent in the passive-matrix approach. Consequently, the active-matrix method facilitates the realization of high-resolution arrays, and [...] Read more.
The active-matrix technology incorporates a transistor to exert precise control over each pixel within a pixel array, eliminating the issue of crosstalk between neighboring pixels that is prevalent in the passive-matrix approach. Consequently, the active-matrix method facilitates the realization of high-resolution arrays, and this inherent advantage has propelled its widespread adoption, not only in display applications but also in diverse sensor arrays from lab to industry. In this comprehensive review, we delve into instances of active-matrix arrays utilizing thin-film transistors (TFTs) that leverage emerging materials such as organic semiconductors, metal oxide semiconductors, two-dimensional materials, and carbon nanotubes (CNTs). Our examination encompasses a broad classification of active-matrix research into two main categories: (i) displays and (ii) sensors. We not only assess the performance of TFTs based on emerging materials within the active-matrix framework, but also explore the evolving trends and directions in active-matrix-based displays and sensors. Full article
(This article belongs to the Special Issue Section Collection Series: Recent Advances in Optoelectronics from Lab to Industry)
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29 pages, 2717 KiB  
Article
Emotional and Mental Nuances and Technological Approaches: Optimising Fact-Check Dissemination through Cognitive Reinforcement Technique
by Francisco S. Marcondes, Maria Araújo Barbosa, Adelino de C. O. S. Gala, José João Almeida and Paulo Novais
Electronics 2024, 13(1), 240; https://doi.org/10.3390/electronics13010240 - 4 Jan 2024
Viewed by 1478
Abstract
The issue of the dissemination of fake news has been widely addressed in the literature, but the issue of the dissemination of fact checks to debunk fake news has not received sufficient attention. Fake news is tailored to reach a wide audience, a [...] Read more.
The issue of the dissemination of fake news has been widely addressed in the literature, but the issue of the dissemination of fact checks to debunk fake news has not received sufficient attention. Fake news is tailored to reach a wide audience, a concern that, as this paper shows, does not seem to be present in fact checking. As a result, fact checking, no matter how good it is, fails in its goal of debunking fake news for the general public. This paper addresses this problem with the aim of increasing the effectiveness of the fact checking of online social media posts through the use of cognitive tools, yet grounded in ethical principles. The paper consists of a profile of the prevalence of fact checking in online social media (both from the literature and from field data) and an assessment of the extent to which engagement can be increased by using simple cognitive enhancements in the text of the post. The focus is on Snopes and X (formerly Twitter). Full article
(This article belongs to the Special Issue Advanced Architectures for Hybrid Edge Analytics Models on Adaptive Smart Areas)
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14 pages, 4397 KiB  
Article
Bidirectional Chaotic Synchronization Communication of Closed-Loop Mutually Coupled Nano-Lasers
by Xueting Zhang, Penghua Mu, Gang Guo, Xintian Liu and Pengfei He
Electronics 2024, 13(1), 239; https://doi.org/10.3390/electronics13010239 - 4 Jan 2024
Cited by 2 | Viewed by 1162
Abstract
It is well known that the dynamical characteristics of nano-lasers (NLs) have been extensively studied, but there is limited research on chaotic synchronization communication. In this paper, we propose a closed-loop system of mutually coupled NLs. Firstly, the autocorrelation function is employed to [...] Read more.
It is well known that the dynamical characteristics of nano-lasers (NLs) have been extensively studied, but there is limited research on chaotic synchronization communication. In this paper, we propose a closed-loop system of mutually coupled NLs. Firstly, the autocorrelation function is employed to evaluate the capability of the system to conceal the time-delayed signature (TDS), and then, based on this, we specifically analyze the effects of the injection strength, frequency detuning, and parameter mismatch of two NLs on the chaotic synchronization performance, as well as the bidirectional communication. The detailed studies indicate that the proposed closed-loop mutually coupled system based on NLs can achieve high-quality chaotic synchronization with a low TDS and large bandwidth. In addition, the system maintains high-quality chaotic synchronization and communication performance even under significant parameter mismatch. Full article
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15 pages, 9951 KiB  
Article
A Dual-Polarized CTS Array Antenna with Four Reconfigurable Beams for mm-Wave Wind Profile Radar
by Lei Yan, Wenbin Zou, Kaihong Zheng, Guangli Yang and Yong Luo
Electronics 2024, 13(1), 238; https://doi.org/10.3390/electronics13010238 - 4 Jan 2024
Cited by 1 | Viewed by 1662
Abstract
The wind profiler radar (WPR) system requires a dual-polarized antenna with multiple low-sidelobe and high-gain beams to facilitate the detection of weak signals reflected by atmospheric turbulence. This paper proposes a dual-polarized continuous transverse stub (CTS) K-band antenna with four reconfigurable beams, which [...] Read more.
The wind profiler radar (WPR) system requires a dual-polarized antenna with multiple low-sidelobe and high-gain beams to facilitate the detection of weak signals reflected by atmospheric turbulence. This paper proposes a dual-polarized continuous transverse stub (CTS) K-band antenna with four reconfigurable beams, which comprises a series-fed CTS array and four 1-to-14 power dividers as line source generators (LSGs) to generate a high-quality quasi-TEM wave. The CTS element incorporates a stepped transition radiation stub design and employs a short cutoff stub on the upper surface of the series-fed parallel plate waveguide (PPW) to achieve optimal impedance matching. The entire antenna is an all-metal structure with remarkably low loss, and low-cost standard fabrication processes are employed for the prototype, which achieves fast reconfigurable four-beam scanning to 15°, with a gain of 31.09 dBi and sidelobe levels below −17.6 dB. Measurement results in an anechoic chamber agree well with simulations, demonstrating the antenna’s ease of manufacture, stability, and suitability for wind profile radar applications. Full article
(This article belongs to the Special Issue Feature Papers in Microwave and Wireless Communications Section)
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61 pages, 5139 KiB  
Review
A Comprehensive Review on Matrix-Integrated Single-Stage Isolated MF/HF Converters
by Tahmin Mahmud and Hang Gao
Electronics 2024, 13(1), 237; https://doi.org/10.3390/electronics13010237 - 4 Jan 2024
Cited by 2 | Viewed by 2629
Abstract
A matrix-integrated single-stage isolated MF/HF AC-AC/DC-AC/AC-DC converter topology stands out as an innovative concept, offering a multitude of advantages including minimal output current THDs, near UPF, 4Q operation, smooth BPF capability, and increased power density leading to the converter’s enhanced efficiency, cost-effectiveness, and [...] Read more.
A matrix-integrated single-stage isolated MF/HF AC-AC/DC-AC/AC-DC converter topology stands out as an innovative concept, offering a multitude of advantages including minimal output current THDs, near UPF, 4Q operation, smooth BPF capability, and increased power density leading to the converter’s enhanced efficiency, cost-effectiveness, and reliability. These characteristics render it an exemplary choice for RE-based power conversion applications. In fact, the matrix-integrated single-stage isolated MF/HF converters have witnessed an increased adoption of RE-based grid interconnection in recent years, specifically within solar PV, WECS, grid-tied offshore WF, and FC-based applications. RE sources produce variable and intermittent AC power by nature, further necessitating conversion to a stable and grid-compatible AC voltage and frequency. This is where MCs offer distinct advantages when contrasted with the conventional indirect dual-stage VSC-based rectifier–inverter topology. In this paper, a total of 22 matrix-integrated HF isolated converter topologies are broadly explored. Our study provides a comprehensive analysis and classification of matrix-integrated isolated single-stage MF/HF AC-AC converters, DC-AC inverters, and AC-DC rectifier topologies including modified topology architectures, control method, modulation techniques along with significant applications. Within this scope, the matrix-integrated converter topologies are categorized based on their architectures and other relevant subvariants. Our primary objective of this study is to impart a clear understanding of the overarching framework and principles of the matrix-integrated single-stage isolated MF/HF converter topologies and stimulate the creation of new topologies that cater to specific requirements for grid-interconnected systems. Full article
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16 pages, 5241 KiB  
Article
YOLOv8-CB: Dense Pedestrian Detection Algorithm Based on In-Vehicle Camera
by Qiuli Liu, Haixiong Ye, Shiming Wang and Zhe Xu
Electronics 2024, 13(1), 236; https://doi.org/10.3390/electronics13010236 - 4 Jan 2024
Cited by 13 | Viewed by 5899
Abstract
Recently, the field of vehicle-mounted visual intelligence technology has witnessed a surge of interest in pedestrian detection. Existing algorithms for dense pedestrian detection at intersections face challenges such as high computational weight, complex models that are difficult to deploy, and suboptimal detection accuracy [...] Read more.
Recently, the field of vehicle-mounted visual intelligence technology has witnessed a surge of interest in pedestrian detection. Existing algorithms for dense pedestrian detection at intersections face challenges such as high computational weight, complex models that are difficult to deploy, and suboptimal detection accuracy for small targets and highly occluded pedestrians. To address these issues, this paper proposes an improved lightweight multi-scale pedestrian detection algorithm, YOLOv8-CB. The algorithm introduces a lightweight cascade fusion network, CFNet (cascade fusion network), and a CBAM attention module to improve the characterization of multi-scale feature semantics and location information, and it superimposes a bidirectional weighted feature fusion path BIFPN structure to fuse more effective features and improve pedestrian detection performance. It is experimentally verified that compared with the YOLOv8n algorithm, the accuracy of the improved model is increased by 2.4%, the number of model parameters is reduced by 6.45%, and the computational load is reduced by 6.74%. The inference time for a single image is 10.8 ms. The cascade fusion algorithm YOLOv8-CB has higher detection accuracy and is a lighter model for multi-scale pedestrian detection in complex scenes such as streets or intersections. This proposed algorithm presents a valuable approach for device-side pedestrian detection with limited computational resources. Full article
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2 pages, 139 KiB  
Editorial
Microwaves Go Fast: Empowering Electronics for a Brighter Future
by Giovanni Crupi
Electronics 2024, 13(1), 235; https://doi.org/10.3390/electronics13010235 - 4 Jan 2024
Viewed by 895
Abstract
Microwave wireless communication technologies have greatly evolved over the years and are nowadays experiencing tremendous growth driven by an explosive broadening of their application [...] Full article
(This article belongs to the Section Microwave and Wireless Communications)
20 pages, 1070 KiB  
Article
High-Throughput MPSoC Implementation of Sparse Bayesian Learning Algorithm
by Jinyang Wang, El-Bay Bourennane, Mahdi Madani, Jun Wang, Chao Li, Yupeng Tai, Longxu Wang, Fan Yang and Haibin Wang
Electronics 2024, 13(1), 234; https://doi.org/10.3390/electronics13010234 - 4 Jan 2024
Viewed by 1159
Abstract
In the field of sparse signal reconstruction, sparse Bayesian learning (SBL) has excellent performance, which is accompanied by extremely high computational complexity. This paper presents an efficient SBL hardware and software (HW&SW) co-implementation method using the ZYNQ series MPSoC (multiprocessor system-on-chip). Firstly, considering [...] Read more.
In the field of sparse signal reconstruction, sparse Bayesian learning (SBL) has excellent performance, which is accompanied by extremely high computational complexity. This paper presents an efficient SBL hardware and software (HW&SW) co-implementation method using the ZYNQ series MPSoC (multiprocessor system-on-chip). Firstly, considering the inherent challenges in parallelizing iterative algorithms like SBL, we propose an architecture based on the iterative calculations implemented on the PL side (FPGA) and the iteration control and input management handled by the PS side (ARM). By adopting this structure, we can take advantage of task-level pipelines on the FPGA side, effectively utilizing time and space resources. Secondly, we utilize LDL decomposition to perform the inversion of the Hermitian matrix, which not only exhibits the lowest computational complexity and requires fewer computational resources but also achieves a higher level in the parallel pipeline mechanism compared with other alternative methods. Furthermore, the algorithm conducts iterations sequentially, utilizing the parameters derived from the previous dataset as prior information for initializing the subsequent dataset’s initial values. This approach helps to reduce the number of iterations required. Finally, with the help of Vitis HLS 2022.2 and Vivado tools, we successfully accomplished the development of a hardware design language and its implementation on the ZYNQ UltraScale+ MPSoC ZCU102 platform. Meanwhile, we have solved a direction of arrival (DOA) estimation problem using horizontal line arrays to verify the practical feasibility of the method. Full article
(This article belongs to the Special Issue Artificial Intelligence in Image Processing and Computer Vision)
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18 pages, 4678 KiB  
Article
Analyzing Distance-Based Registration with Two Location Areas: A Semi-Markov Process Approach
by Jang-Hyun Baek
Electronics 2024, 13(1), 233; https://doi.org/10.3390/electronics13010233 - 4 Jan 2024
Viewed by 993
Abstract
In order to connect an incoming call to the user equipment (UE) in a mobile communication network, the location information of the UE must be always kept in the network database. Therefore, the efficiency of the location registration method of reporting new location [...] Read more.
In order to connect an incoming call to the user equipment (UE) in a mobile communication network, the location information of the UE must be always kept in the network database. Therefore, the efficiency of the location registration method of reporting new location information to a mobile communication network whenever the location information of the UE changes directly affects the performance of the radio channel, which is a limited resource in a mobile communication network. This study deals with distance-based registration (DBR). DBR does not cause the ping-pong phenomenon known to be a main problem in zone-based registration. It shows good performance when assuming a random walk mobility model. To improve the performance of the original DBR with one location area (1D), a DBR with two location areas (2D) was proposed. It is known that 2D is better than 1D in most cases. However, unlike 1D, an accurate mathematical model for 2D has not been presented in previous studies, raising questions about whether an accurate performance comparison has been performed. In this study, we present an accurate mathematical model based on the semi-Markov process for performance analysis of 2D. We compared performances of 1D and 2D using the proposed mathematical model. Various numerical results showed that 2D with two-step paging was superior to 1D in most cases. However, when simultaneous paging was applied to 2D, 1D was better than 2D in most cases. In real situations, optimal performance can be achieved by reflecting the network situation in real time and dynamically changing the operating method using a better-performing model among these two methods. Full article
(This article belongs to the Topic Electronic Communications, IOT and Big Data)
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22 pages, 5886 KiB  
Article
Civil Aeronautical Ad Hoc Network Zero-Overhead Clustering Algorithm Based on Realtime Position Information of the Aircraft
by Changyuan Luo, Lianxiang Li, Duan Li, Peisen Liu and Muhammad Saad Khan
Electronics 2024, 13(1), 232; https://doi.org/10.3390/electronics13010232 - 4 Jan 2024
Viewed by 1035
Abstract
Clustering is an important means to solve the poor scalability of aeronautical ad hoc networks (AANET). To improve the stability and performance of AANET and avoid unnecessary waste of resources caused by civil aircraft in communication, we proposed a zero-overhead clustering algorithm according [...] Read more.
Clustering is an important means to solve the poor scalability of aeronautical ad hoc networks (AANET). To improve the stability and performance of AANET and avoid unnecessary waste of resources caused by civil aircraft in communication, we proposed a zero-overhead clustering algorithm according to the real-time position of the aircraft based on the known trajectory. Firstly, the route and trajectory models are used to obtain geographical coordinates by the aircraft positioning algorithm. On this basis, the geographical cluster and cluster head region are divided in order to complete the cluster setting. Considering the aircraft maintenance cluster generation time updates, we use the communication sub-cluster generation algorithm to control the size of the cluster, and also, the flexibility of cluster hops is guaranteed by the subsidiary cluster members. The continuity of communication and the scalability of the cluster are maintained by the gateway node, thereby forming a network structure and increasing the stability of clusters. Finally, the actual route data are used to simulate the performance of the algorithm. The experimental and analytical results show that clustering and maintenance of the algorithm have zero overhead. Additionally, compared with the traditional algorithm, our proposed method can maintain a reasonable number of clusters, reduce the frequency of cluster head replacement, reduce the number of cluster members entering and leaving the cluster and avoid the loss of control of cluster heads to cluster members. So, it has important application value in the field of civil aviation. Full article
(This article belongs to the Special Issue Advances in Intelligent Systems and Networks, 2nd Edition)
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47 pages, 2225 KiB  
Review
A Survey of NOMA-Aided Cell-Free Massive MIMO Systems
by Antonio Apiyo and Jacek Izydorczyk
Electronics 2024, 13(1), 231; https://doi.org/10.3390/electronics13010231 - 4 Jan 2024
Cited by 8 | Viewed by 2694
Abstract
The Internet of Everything is leading to an increasingly connected intelligent digital world. Envisaged sixth-generation wireless networks require new solutions and technologies due to stringent network requirements. The benefits of cell-free massive MIMO (CF-mMIMO) and non-orthogonal multiple access (NOMA) have brought substantial attention [...] Read more.
The Internet of Everything is leading to an increasingly connected intelligent digital world. Envisaged sixth-generation wireless networks require new solutions and technologies due to stringent network requirements. The benefits of cell-free massive MIMO (CF-mMIMO) and non-orthogonal multiple access (NOMA) have brought substantial attention to these approaches as potential technologies for future networks. In CF-mMIMO, numerous distributed access points are linked to a central processing unit, which allocates the same time-frequency resources to a smaller group of users. On the other hand, NOMA can support more users than its orthogonal counterparts by utilizing non-orthogonal resource allocation. This paper provides a comprehensive review and survey of NOMA-aided CF-mMIMO (CF-mMIMO-NOMA). Specifically, we present a comprehensive review of massive MIMO, CF-mMIMO, and NOMA. We then present a state-of-the-art research review of CF-mMIMO-NOMA. Finally, we discuss the challenges and potential of combining CF-mMIMO-NOMA with other enabling technologies to enhance performance. Full article
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14 pages, 913 KiB  
Article
FOLD: Low-Level Image Enhancement for Low-Light Object Detection Based on FPGA MPSoC
by Xiang Li, Zeyu Li, Lirong Zhou and Zhao Huang
Electronics 2024, 13(1), 230; https://doi.org/10.3390/electronics13010230 - 4 Jan 2024
Cited by 1 | Viewed by 1913
Abstract
Object detection has a wide range of applications as the most fundamental and challenging task in computer vision. However, the image quality problems such as low brightness, low contrast, and high noise in low-light scenes cause significant degradation of object detection performance. To [...] Read more.
Object detection has a wide range of applications as the most fundamental and challenging task in computer vision. However, the image quality problems such as low brightness, low contrast, and high noise in low-light scenes cause significant degradation of object detection performance. To address this, this paper focuses on object detection algorithms in low-light scenarios, carries out exploration and research from the aspects of low-light image enhancement and object detection, and proposes low-level image enhancement for low-light object detection based on the FPGA MPSoC method. On the one hand, the low-light dataset is expanded and the YOLOv3 object detection model is trained based on the low-order image enhancement technique, which improves the detection performance of the model in low-light scenarios; on the other hand, the model is deployed on the MPSoC board to achieve an edge object detection system, which improves the detection efficiency. Finally, validation experiments are conducted on the publicly available low-light object detection dataset and the ZU3EG-AXU3EGB MPSoC board, and the results show that the method in this paper can effectively improve the detection accuracy and efficiency. Full article
(This article belongs to the Section Computer Science & Engineering)
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18 pages, 8189 KiB  
Article
Deep-Learning-Based Seismic-Signal P-Wave First-Arrival Picking Detection Using Spectrogram Images
by Sugi Choi, Bohee Lee, Junkyeong Kim and Haiyoung Jung
Electronics 2024, 13(1), 229; https://doi.org/10.3390/electronics13010229 - 4 Jan 2024
Cited by 2 | Viewed by 2005
Abstract
The accurate detection of P-wave FAP (First-Arrival Picking) in seismic signals is crucial across various industrial domains, including coal and oil exploration, tunnel construction, hydraulic fracturing, and earthquake early warning systems. At present, P-wave FAP detection relies on manual identification by experts and [...] Read more.
The accurate detection of P-wave FAP (First-Arrival Picking) in seismic signals is crucial across various industrial domains, including coal and oil exploration, tunnel construction, hydraulic fracturing, and earthquake early warning systems. At present, P-wave FAP detection relies on manual identification by experts and automated methods using Short-Term Average to Long-Term Average algorithms. However, these approaches encounter significant performance challenges, especially in the presence of real-time background noise. To overcome this limitation, this study proposes a novel P-wave FAP detection method that employs the U-Net model and incorporates spectrogram transformation techniques for seismic signals. Seismic signals, similar to those encountered in South Korea, were generated using the stochastic model simulation program. Synthesized WGN (White Gaussian Noise) was added to replicate background noise. The resulting signals were transformed into 2D spectrogram images and used as input data for the U-Net model, ensuring precise P-wave FAP detection. In the experimental result, it demonstrated strong performance metrics, achieving an MSE of 0.0031 and an MAE of 0.0177, and an RMSE of 0.0195. Additionally, it exhibited precise FAP detection capabilities in image prediction. The developed U-Net-based model exhibited exceptional performance in accurately detecting P-wave FAP in seismic signals with varying amplitudes. Through the developed model, we aim to contribute to the advancement of microseismic monitoring technology used in various industrial fields. Full article
(This article belongs to the Special Issue AI in Disaster, Crisis, and Emergency Management)
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13 pages, 2704 KiB  
Article
Research on Guide Star Distribution of Sub-Arcsecond Attitude Determination for Microsatellites Reusing Scientific Cameras
by Qin Lin, Peng Qiu, Sibo Zhang and Chao Wang
Electronics 2024, 13(1), 228; https://doi.org/10.3390/electronics13010228 - 4 Jan 2024
Viewed by 908
Abstract
Onboard scientific cameras are reused in attitude determination to meet the sub-arcsecond attitude determination accuracy requirements of microsatellites. This approach does not require an additional payload for microsatellites. It involves reusing high-quality optical lenses from the scientific camera and utilizing the peripheral high-quality [...] Read more.
Onboard scientific cameras are reused in attitude determination to meet the sub-arcsecond attitude determination accuracy requirements of microsatellites. This approach does not require an additional payload for microsatellites. It involves reusing high-quality optical lenses from the scientific camera and utilizing the peripheral high-quality imaging areas of its square-shaped detector. Separate detectors are placed within these areas as attitude determination detectors to obtain star patterns for closed-loop attitude determination, thereby achieving high-precision attitude determination for microsatellites. The star patterns obtained using this method may pose specific issues due to the relative positions of stars. Through an analysis of the theoretical model that examines the relationship between attitude determination accuracy and the main influencing factors, it is indicated that guide star distribution is one of the main, complex factors determining attitude determination accuracy. A further simulation analysis was conducted on the specific impact of two guide star distribution characteristics—namely, the coverage of guide stars in the attitude determination areas and the proportion of the average field of view occupied by the guide star triangles to the total field of view of the attitude determination areas—on attitude determination accuracy. This study concludes that when the measurement error of the guide stars is bigger than the attitude determination accuracy requirement for its area configuration, four attitude determination areas should be configured. Four attitude determination areas should be prioritized when the measurement error is equal to or smaller than the attitude determination accuracy requirement, followed by the option to configure three attitude determination areas or two symmetric attitude determination areas. When selecting guide stars for star pattern recognition, the guide stars should cover the attitude determination areas as much as possible, and guide stars with a higher proportion of the average field of view occupied by the guide star triangles to the total field of view should be chosen. Finally, experimental validation was conducted using star patterns from dense star fields and sparse star fields. The research results provide an important reference for the optimization of attitude determination area configuration, navigation star catalog construction, and star pattern recognition algorithm research for microsatellites equipped with scientific cameras. Full article
(This article belongs to the Special Issue Recent Advances in Autonomous Navigation)
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17 pages, 3604 KiB  
Article
Signal Processing from the Radiation Detector of the Radiometric Density Meter Using the Low-Pass Infinite Impulse Response Filter in the Measurement Path in the Coal Enrichment Process Control System
by Jarosław Joostberens, Aurelia Rybak, Aleksandra Rybak and Paulina Gwoździk
Electronics 2024, 13(1), 227; https://doi.org/10.3390/electronics13010227 - 4 Jan 2024
Viewed by 972
Abstract
One of the most common coal preparations is enrichment in a jig using a float regulation system. The latest solutions propose to compensate for significant measurement errors of the float by introducing a radiometric density meter operating on the principle of gamma radiation [...] Read more.
One of the most common coal preparations is enrichment in a jig using a float regulation system. The latest solutions propose to compensate for significant measurement errors of the float by introducing a radiometric density meter operating on the principle of gamma radiation absorption into the bottom product discharge zone of the jig. The signal from the radiometric density meter detector is in the form of a sequence of pulses with a Poisson time distribution, which are counted by a counter, as a form of digital low-pass filter. The requirement to maintain accuracy at an appropriate level forces the measurement time to be extended, which worsens the dynamic properties. Changes in the density of the coal–water medium have an unsteady, cyclical course, resulting from the principle of operation of the jig. The research goal was to develop an algorithm for processing the signal from the radiation detector using an IIR filter in the measurement path in a way that ensures optimization of the dynamic properties of the radiometric density meter operating in the control system of the coal enrichment process in the jig. For this purpose, a low-pass IIR filter was introduced into the measurement path to process the signal from the pulse counter. The identified course of the medium density for one cycle (the first) served as a reference signal. A first-order IIR filter was proposed, with a constant parameter selected on the basis of the reference signal and a parameter depending on the time derivative of the identified density of the medium. The mean squared error MSE was adopted as an indicator for assessing the dynamic properties of the radiometric density meter. The results of simulation tests showed that introducing an IIR filter into the measurement path gives better results in terms of the adopted criterion than using a counter with a constant measurement time. The best results (MSE = 2.05 × 10−4) were obtained using an IIR filter with a parameter that is a linear function of the derivative of the medium density over time, determined for one air pulsation cycle and applied in four subsequent cycles. These results were obtained for an adaptive first-order filter with a variable parameter a from the designated range from 0.833 to 0.999, for a measurement time of 2 ms. Full article
(This article belongs to the Special Issue Modeling and Optimization of Energy Efficiency in the Light of Energy Security)
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8 pages, 165 KiB  
Editorial
Recent Advances in Intelligent Data Analysis and Its Applications
by Chao Zhang, Wentao Li, Huiyan Zhang and Tao Zhan
Electronics 2024, 13(1), 226; https://doi.org/10.3390/electronics13010226 - 4 Jan 2024
Viewed by 3344
Abstract
In the current rapidly evolving technological landscape, marked by transformative advancements such as cloud computing, the Internet of Things (IoT), and industrial internet, the complexity of data analysis tasks is escalating across the socio-economic spectrum [...] Full article
(This article belongs to the Special Issue Advances in Intelligent Data Analysis and Its Applications)
16 pages, 2987 KiB  
Article
Grid-Based Non-Uniform Probabilistic Roadmap-Based AGV Path Planning in Narrow Passages and Complex Environments
by Yaozhe Zhou, Yujun Lu and Liye Lv
Electronics 2024, 13(1), 225; https://doi.org/10.3390/electronics13010225 - 4 Jan 2024
Cited by 1 | Viewed by 1390
Abstract
In this paper, we propose a Grid-based Non-uniform Probability Density Sampling Probabilistic Roadmap algorithm (GN-PRM) in response to the challenges of difficult sampling in narrow passages and low-probability map generation in traditional Probabilistic Roadmap algorithms (PRM). The improved algorithm incorporates grid-based processing for [...] Read more.
In this paper, we propose a Grid-based Non-uniform Probability Density Sampling Probabilistic Roadmap algorithm (GN-PRM) in response to the challenges of difficult sampling in narrow passages and low-probability map generation in traditional Probabilistic Roadmap algorithms (PRM). The improved algorithm incorporates grid-based processing for map segmentation, employing non-uniform probability density sampling based on the different attributes of each block to enhance sampling probability in narrow passages. Additionally, considering the computational cost and frequent ineffective searches in traditional PRM algorithms during pathfinding, this paper optimizes the time required for query route planning by altering connection strategies to improve the algorithm’s runtime. Finally, the simulation results indicate that, with a reduction of over 50% in undirected line segments and a reduction of over 85% in runtime, the GN-PRM algorithm achieves a 100% success rate in complex planning scenarios with a sampling point value of K = 500. In comparison, the traditional PRM algorithm has a success rate of no more than 10%, with a sampling point value of K = 500. Full article
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12 pages, 2309 KiB  
Article
Effect of Proton Irradiation on Complementary Metal Oxide Semiconductor (CMOS) Single-Photon Avalanche Diodes
by Mingzhu Xun, Yudong Li, Jie Feng, Chengfa He, Mingyu Liu and Qi Guo
Electronics 2024, 13(1), 224; https://doi.org/10.3390/electronics13010224 - 4 Jan 2024
Cited by 1 | Viewed by 1388
Abstract
The effects of proton irradiation on CMOS Single-Photon Avalanche Diodes (SPADs) are investigated in this article. The I–V characteristics, dark count rate (DCR), and photon detection probability (PDP) of the CMOS SPADs were measured under 30 MeV and 52 MeV proton irradiations. Two [...] Read more.
The effects of proton irradiation on CMOS Single-Photon Avalanche Diodes (SPADs) are investigated in this article. The I–V characteristics, dark count rate (DCR), and photon detection probability (PDP) of the CMOS SPADs were measured under 30 MeV and 52 MeV proton irradiations. Two types of SPAD, with and without shallow trench isolation (STI), were designed. According to the experimental results, the leakage current, breakdown voltage, and PDP did not change after irradiation at a DDD of 2.82 × 108 MeV/g, but the DCR increased significantly at five different higher voltages. The DCR increased by 506 cps at an excess voltage of 2 V and 10,846 cps at 10 V after 30 MeV proton irradiation. A γ irradiation was conducted with a TID of 10 krad (Si). The DCR after the γ irradiation increased from 256 cps to 336 cps at an excess voltage of 10 V. The comparison of the DCR after proton and γ-ray irradiation with two structures of SPAD indicates that the major increase in the DCR was due to the depletion region defects caused by proton displacement damage rather than the Si-SiO2 interface trap generated by ionization. Full article
(This article belongs to the Special Issue Radiation Effects of Advanced Electronic Devices and Circuits)
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17 pages, 607 KiB  
Article
A Time-Sensitive Graph Neural Network for Session-Based New Item Recommendation
by Luzhi Wang and Di Jin
Electronics 2024, 13(1), 223; https://doi.org/10.3390/electronics13010223 - 3 Jan 2024
Cited by 3 | Viewed by 1615
Abstract
Session-based recommendation plays an important role in daily life and exists in many scenarios, such as online shopping websites and streaming media platforms. Recently, some works have focused on using graph neural networks (GNNs) to recommend new items in session-based scenarios. However, these [...] Read more.
Session-based recommendation plays an important role in daily life and exists in many scenarios, such as online shopping websites and streaming media platforms. Recently, some works have focused on using graph neural networks (GNNs) to recommend new items in session-based scenarios. However, these methods have encountered several limitations. First, existing methods typically ignore the impact of items’ visited time in constructing session graphs, resulting in a departure from real-world recommendation dynamics. Second, sessions are often sparse, making it challenging for GNNs to learn valuable item embedding and user preferences. Third, the existing methods usually overemphasize the impact of the last item on user preferences, neglecting their interest in multiple items in a session. To address these issues, we introduce a time-sensitive graph neural network for new item recommendation in session-based scenarios, namely, TSGNN. Specifically, TSGNN provides a novel time-sensitive session graph constructing technique to solve the first problem. For the second problem, TSGNN introduces graph augmentation and contrastive learning into it. To solve the third problem, TSGNN designs a time-aware attention mechanism to accurately discern user preferences. By evaluating the compatibility between user preferences and candidate new item embeddings, our method recommends items with high relevance scores for users. Comparative experiments demonstrate the superiority of TSGNN over state-of-the-art (SOTA) methods. Full article
(This article belongs to the Special Issue Intelligent Big Data Analysis for High-Dimensional Internet of Things)
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21 pages, 6926 KiB  
Article
An Accurate and Invertible Sketch for Super Spread Detection
by Zheng Zhang, Jie Lu, Quan Ren, Ziyong Li, Yuxiang Hu and Hongchang Chen
Electronics 2024, 13(1), 222; https://doi.org/10.3390/electronics13010222 - 3 Jan 2024
Viewed by 1223
Abstract
Super spread detection has been widely applied in network management, recommender systems, and cyberspace security. It is more complicated than heavy hitter owing to the requirement of duplicate removal. Accurately detecting a super spread in real-time with small memory demands remains a nontrivial [...] Read more.
Super spread detection has been widely applied in network management, recommender systems, and cyberspace security. It is more complicated than heavy hitter owing to the requirement of duplicate removal. Accurately detecting a super spread in real-time with small memory demands remains a nontrivial yet challenging issue. The previous work either had low accuracy or incurred heavy memory overhead and could not provide a precise cardinality estimation. This paper designed an invertible sketch for super spread detection with small memory demands and high accuracy. It introduces a power-weakening increment strategy that creates an environment encouraging sufficient competition at the early stages of discriminating a super spread and amplifying the comparative dominance to maintain accuracy. Extensive experiments have been performed based on actual Internet traffic traces and recommender system datasets. The trace-driven evaluation demonstrates that our sketch actualizes higher accuracy in super spread detection than state-of-the-art sketches. The super spread cardinality estimation error is 2.6–19.6 times lower than that of the previous algorithms. Full article
(This article belongs to the Special Issue Theories and Technologies of Network, Data and Information Security)
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17 pages, 2272 KiB  
Article
Semi-Supervised Object Detection with Multi-Scale Regularization and Bounding Box Re-Prediction
by Yeqin Shao, Chang Lv, Ruowei Zhang, He Yin, Meiqin Che, Guoqing Yang and Quan Jiang
Electronics 2024, 13(1), 221; https://doi.org/10.3390/electronics13010221 - 3 Jan 2024
Cited by 1 | Viewed by 1488
Abstract
Semi-supervised object detection has become a hot topic in recent years, but there are still some challenges regarding false detection, duplicate detection, and inaccurate localization. This paper presents a semi-supervised object detection method with multi-scale regularization and bounding box re-prediction. Specifically, to improve [...] Read more.
Semi-supervised object detection has become a hot topic in recent years, but there are still some challenges regarding false detection, duplicate detection, and inaccurate localization. This paper presents a semi-supervised object detection method with multi-scale regularization and bounding box re-prediction. Specifically, to improve the generalization of the two-stage object detector and to make consistent predictions related to the image and its down-sampled counterpart, a novel multi-scale regularization loss is proposed for the region proposal network and the region-of-interest head. Then, in addition to using the classification probabilities of the pseudo-labels to exploit the unlabeled data, this paper proposes a novel bounding box re-prediction strategy to re-predict the bounding boxes of the pseudo-labels in the unlabeled images and select the pseudo-labels with reliable bounding boxes (location coordinates) to improve the model’s localization accuracy based on its unsupervised localization loss. Experiments on the public MS COCO and Pascal VOC show that our proposed method achieves a competitive detection performance compared to other state-of-the-art methods. Furthermore, our method offers a multi-scale regularization strategy and a reliably located pseudo-label screening strategy, both of which facilitate the development of semi-supervised object detection techniques and boost the object detection performance in autonomous driving, industrial inspection, and agriculture automation. Full article
(This article belongs to the Section Artificial Intelligence)
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27 pages, 5536 KiB  
Article
Multi-Modal Contrastive Learning for LiDAR Point Cloud Rail-Obstacle Detection in Complex Weather
by Lu Wen, Yongliang Peng, Miao Lin, Nan Gan and Rongqing Tan
Electronics 2024, 13(1), 220; https://doi.org/10.3390/electronics13010220 - 3 Jan 2024
Cited by 5 | Viewed by 2411
Abstract
Obstacle intrusion is a serious threat to the safety of railway traffic. LiDAR point cloud 3D semantic segmentation (3DSS) provides a new method for unmanned rail-obstacle detection. However, the inevitable degradation of model performance occurs in complex weather and hinders its practical application. [...] Read more.
Obstacle intrusion is a serious threat to the safety of railway traffic. LiDAR point cloud 3D semantic segmentation (3DSS) provides a new method for unmanned rail-obstacle detection. However, the inevitable degradation of model performance occurs in complex weather and hinders its practical application. In this paper, a multi-modal contrastive learning (CL) strategy, named DHT-CL, is proposed to improve point cloud 3DSS in complex weather for rail-obstacle detection. DHT-CL is a camera and LiDAR sensor fusion strategy specifically designed for complex weather and obstacle detection tasks, without the need for image input during the inference stage. We first demonstrate how the sensor fusion method is more robust under rainy and snowy conditions, and then we design a Dual-Helix Transformer (DHT) to extract deeper cross-modal information through a neighborhood attention mechanism. Then, an obstacle anomaly-aware cross-modal discrimination loss is constructed for collaborative optimization that adapts to the anomaly identification task. Experimental results on a complex weather railway dataset show that with an mIoU of 87.38%, the proposed DHT-CL strategy achieves better performance compared to other high-performance models from the autonomous driving dataset, SemanticKITTI. The qualitative results show that DHT-CL achieves higher accuracy in clear weather and reduces false alarms in rainy and snowy weather. Full article
(This article belongs to the Special Issue Advanced Technologies in Intelligent Transportation Systems)
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18 pages, 4222 KiB  
Article
The Prescribed-Time Sliding Mode Control for Underactuated Bridge Crane
by Yin’an Feng, Hao Zhang and Chan Gu
Electronics 2024, 13(1), 219; https://doi.org/10.3390/electronics13010219 - 3 Jan 2024
Cited by 3 | Viewed by 1216
Abstract
In this article, a prescribed-time sliding mode controller is proposed for the design of the positioning and anti-swing time of the underactuated bridge crane under different initial conditions. Compared with the existing crane positioning and anti-swing controller, the controller can directly specify the [...] Read more.
In this article, a prescribed-time sliding mode controller is proposed for the design of the positioning and anti-swing time of the underactuated bridge crane under different initial conditions. Compared with the existing crane positioning and anti-swing controller, the controller can directly specify the positioning and anti-swing time of the bridge crane system through the controller parameters. Firstly, in order to solve the underdrive problem of the bridge crane system, the crane system model is transformed by constructing composite variables; secondly, a new prescribed-time convergence rate and a new prescribed-time sliding mode surface are designed to ensure that the state of the bridge crane system can converge within the prescribed time; finally, the Lyapunov stability analysis and simulation results show that the designed controller can enable the crane to position and anti-swing within the prescribed time. Full article
(This article belongs to the Special Issue High Performance Control and Industrial Applications)
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14 pages, 5127 KiB  
Article
Contextual Rule-Based System for Brightness Energy Management in Buildings
by Vasco Ferreira, Tiago Pinto and José Baptista
Electronics 2024, 13(1), 218; https://doi.org/10.3390/electronics13010218 - 3 Jan 2024
Viewed by 964
Abstract
The increase in renewable generation of a distributed nature has brought significant new challenges to power and energy system management and operation. Self-consumption in buildings is widespread, and with it rises the need for novel, adaptive and intelligent building energy management systems. Although [...] Read more.
The increase in renewable generation of a distributed nature has brought significant new challenges to power and energy system management and operation. Self-consumption in buildings is widespread, and with it rises the need for novel, adaptive and intelligent building energy management systems. Although there is already extensive research and development work regarding building energy management solutions, the capabilities for adaptation and contextualization of decisions are still limited. Consequently, this paper proposes a novel contextual rule-based system for energy management in buildings, which incorporates a contextual dimension that enables the adaptability of the system according to diverse contextual situations and the presence of multiple users with different preferences. Results of a case study based on real data show that the contextualization of the energy management process can maintain energy costs as low as possible, while respecting user preferences and guaranteeing their comfort. Full article
(This article belongs to the Special Issue Section Collection Series: New Horizons and Recent Advances in Power Electronics)
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14 pages, 5322 KiB  
Article
How to Accurately Determine the Ohmic Contact Properties on n-Type 4H-SiC
by Clément Berger, Daniel Alquier and Jean-François Michaud
Electronics 2024, 13(1), 217; https://doi.org/10.3390/electronics13010217 - 3 Jan 2024
Cited by 1 | Viewed by 2449
Abstract
The electrical properties of ohmic contacts are classically investigated by using the transfer length method (TLM). In the literature, the TLM patterns are fabricated onto different substrate configurations, especially directly onto the 4H-SiC wafers. But, due to the high doping level of commercial [...] Read more.
The electrical properties of ohmic contacts are classically investigated by using the transfer length method (TLM). In the literature, the TLM patterns are fabricated onto different substrate configurations, especially directly onto the 4H-SiC wafers. But, due to the high doping level of commercial substrates, the current is not confined close to the contact and, in this case, the specific contact resistance (SCR) value is overestimated. In this article, we propose, by the means of simulations, to investigate the influence of the layer under the contact towards the estimation of the SCR. The simulation results highlight that, for an accurate determination of the SCR values, an isolation layer between the contact and the silicon carbide substrate is mandatory. Thus, we have determined the characteristics (doping level and thickness) of a suitable isolation layer compatible with SCR values ranging from 10−3 to 10−6 Ω·cm2. Full article
(This article belongs to the Topic Modeling, Fabrication, and Characterization of Semiconductor Materials and Devices)
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17 pages, 530 KiB  
Article
ASKAT: Aspect Sentiment Knowledge Graph Attention Network for Recommendation
by Yachao Cui, Peng Zhou, Hongli Yu, Pengfei Sun, Han Cao and Pei Yang
Electronics 2024, 13(1), 216; https://doi.org/10.3390/electronics13010216 - 3 Jan 2024
Cited by 1 | Viewed by 1543
Abstract
In modern online life, recommender systems can help us filter unimportant information. Researchers of recommendation algorithms usually utilize historical interaction data to mine potential user preferences. However, most existing methods use rating data to mine user interest preferences, ignoring rich textual information such [...] Read more.
In modern online life, recommender systems can help us filter unimportant information. Researchers of recommendation algorithms usually utilize historical interaction data to mine potential user preferences. However, most existing methods use rating data to mine user interest preferences, ignoring rich textual information such as reviews. Although some researchers have attempted to combine ratings and reviews for recommendation, we believe the following shortcomings still exist. First, existing methods are overly dependent on the accuracy of external sentiment analysis tools. Second, existing methods do not fully utilize the features extracted from reviews. Further, existing methods focus only on the aspects that users like, while ignoring the aspects that users dislike, and they cannot completely model users’ true preferences. To address the above issues, in this paper, we propose a recommendation model based on the aspect of the sentiment knowledge graph attention network (ASKAT). We first use the improved aspect-based sentiment analysis algorithm to extract aspectual sentiment features from reviews. Then, to overcome the difficulty in underutilizing the information extracted from the comments, we build aspects of sentiment-enhanced collaborative knowledge mapping. After that, we propose a new graph attention network that uses sentiment-aware attention mechanisms to aggregate neighbour information. Finally, our experimental results on three datasets, Movie, Amazon book, and Yelp, show that our model consistently outperforms the baseline model in two recommendation scenarios, click-through-rate prediction and Top-k recommendation. Compared with other models, the method shows significant improvement in both recommendation accuracy and personalised recommendation effectiveness. Full article
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15 pages, 9600 KiB  
Article
Cybersecurity in Supply Chain Systems: The Farm-to-Fork Use Case
by Helen C. Leligou, Alexandra Lakka, Panagiotis A. Karkazis, Joao Pita Costa, Eva Marin Tordera, Henrique Manuel Dinis Santos and Antonio Alvarez Romero
Electronics 2024, 13(1), 215; https://doi.org/10.3390/electronics13010215 - 3 Jan 2024
Cited by 1 | Viewed by 1528
Abstract
Modern supply chains comprise an increasing number of actors which deploy different information technology systems that capture information of a diverse nature and diverse sources (from sensors to order information). While the benefits of the automatic exchange of information between these systems have [...] Read more.
Modern supply chains comprise an increasing number of actors which deploy different information technology systems that capture information of a diverse nature and diverse sources (from sensors to order information). While the benefits of the automatic exchange of information between these systems have been recognized and have led to their interconnection, protecting the whole supply chain from potential attacks is a challenging issue given the attack proliferation reported in the literature. In this paper, we present the FISHY platform, which anticipates protecting the whole supply chain from potential attacks by (a) adopting novel technologies and approaches including machine learning-based tools to detect security threats and recommend mitigation policies and (b) employing blockchain-based tools to provide evidence of the captured events and suggested policies. This platform is also easily expandable to protect against additional attacks in the future. We experiment with this platform in the farm-to-fork supply chain to prove its operation and capabilities. The results show that the FISHY platform can effectively be used to protect the supply chain and offers high flexibility to its users. Full article
(This article belongs to the Special Issue Security and Privacy in Networks and Multimedia)
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11 pages, 443 KiB  
Article
Dual-Safety Knowledge Graph Completion for Process Industry
by Lingzhi Wang, Haotian Li, Wei Wang, Guodong Xin and Yuliang Wei
Electronics 2024, 13(1), 214; https://doi.org/10.3390/electronics13010214 - 3 Jan 2024
Viewed by 1498
Abstract
With the rise of Industry 4.0, control systems have taken on increasing importance in industrial processes, and ensuring their security has become a pressing issue. While recent research has focused on cybersecurity threats, the security risks inherent to industrial processes themselves have been [...] Read more.
With the rise of Industry 4.0, control systems have taken on increasing importance in industrial processes, and ensuring their security has become a pressing issue. While recent research has focused on cybersecurity threats, the security risks inherent to industrial processes themselves have been overlooked. Additionally, existing tools cannot simultaneously analyze both cyber vulnerabilities and processes anomaly in industrial settings. This paper aims to address these issues through two main contributions. First, we develop a knowledge graph to integrate information on security risks across cybersecurity and industrial processes, providing a foundation for comprehensively assessing threats. Second, we apply the link prediction task to the knowledge graph, introducing an embedding-based approach to unveil previously undiscovered knowledge. Our experiments demonstrate that the proposed method exhibits comparable performance on link prediction and is capable of mining valuable and diverse potential risks in industrial processes. Full article
(This article belongs to the Topic AI and Data-Driven Advancements in Industry 4.0)
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18 pages, 2334 KiB  
Article
How to Design and Evaluate mHealth Apps? A Case Study of a Mobile Personal Health Record App
by Guyeop Kim, Dongwook Hwang, Jaehyun Park, Hyun K. Kim and Eui-Seok Hwang
Electronics 2024, 13(1), 213; https://doi.org/10.3390/electronics13010213 - 3 Jan 2024
Cited by 2 | Viewed by 2713
Abstract
The rapid growth of the mHealth market has led to the development of several tools to evaluate user experience. However, there is a lack of universal tools specifically designed for this emerging technology. This study was conducted with the aim of developing and [...] Read more.
The rapid growth of the mHealth market has led to the development of several tools to evaluate user experience. However, there is a lack of universal tools specifically designed for this emerging technology. This study was conducted with the aim of developing and verifying a user experience evaluation scale for mHealth apps based on factors proposed in previous research. The initial draft of the tool was created following a comprehensive review of existing questionnaires related to mHealth app evaluation. The validity of this scale was then tested through exploratory and confirmatory factor analysis. The results of the factor analysis led to the derivation of 16 items, which were conceptually mapped to five factors: ease of use and satisfaction, information architecture, usefulness, ease of information, and aesthetics. A case study was also conducted to improve mHealth apps concerning personal health records using this scale. In conclusion, the developed user experience evaluation scale for mHealth apps can provide comprehensive user feedback and contribute to the improvement of these apps. Full article
(This article belongs to the Special Issue Human-Computer Interactions in E-health)
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