Electronics

15 pages, 2938 KiB

Open AccessArticle

Development of a Platform for Learning Cybersecurity Using Capturing the Flag Competitions

by Iván Ortiz-Garces, Rommel Gutierrez, David Guerra, Santiago Sanchez-Viteri and William Villegas-Ch.

Electronics 2023, 12(7), 1753; https://doi.org/10.3390/electronics12071753 - 6 Apr 2023

Cited by 3 | Viewed by 3275

Abstract

Currently, cybersecurity is a topic of great importance for society. With the increase in the use of technology and the digitization of many activities, the number of cyber threats to which individuals and organizations are exposed has increased. In addition, the COVID-19 pandemic [...] Read more.

Currently, cybersecurity is a topic of great importance for society. With the increase in the use of technology and the digitization of many activities, the number of cyber threats to which individuals and organizations are exposed has increased. In addition, the COVID-19 pandemic has accelerated the digitization of many processes, further increasing the risk of cyberattacks. One of the main causes of these problems is the lack of cyber security awareness, as many people and organizations do not have a proper understanding of cyber threats and the measures, they must take to protect themselves. As a solution to the lack of cybersecurity knowledge, this work proposes the development of a Capture the Flag platform for learning about cybersecurity. The objective is to provide a tool that allows the education of future professionals in this field and covers the existing demand for this type of specialist. The platform is made up of two sections, one for learning and the other for CTF. The first section allows teachers to contribute to the teaching of their students using challenges. The second section allows one to carry out competitions with effective results when acquiring knowledge and experience. The platform is evaluated using questionnaires and surveys to measure whether the platform fulfills its purpose. Full article

(This article belongs to the Special Issue Emerging Topics in Cybersecurity: Challenges and Solutions)

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18 pages, 1292 KiB

Open AccessArticle

Channel Estimation for High-Speed Railway Wireless Communications: A Generative Adversarial Network Approach

by Qingmiao Zhang, Hanzhi Dong and Junhui Zhao

Electronics 2023, 12(7), 1752; https://doi.org/10.3390/electronics12071752 - 6 Apr 2023

Cited by 6 | Viewed by 2864

Abstract

In high-speed railways, the wireless channel and network topology change rapidly due to the high-speed movement of trains and the constant change of the location of communication equipment. The topology is affected by channel noise, making accurate channel estimation more difficult. Therefore, the [...] Read more.

In high-speed railways, the wireless channel and network topology change rapidly due to the high-speed movement of trains and the constant change of the location of communication equipment. The topology is affected by channel noise, making accurate channel estimation more difficult. Therefore, the way to obtain accurate channel state information (CSI) is the greatest challenge. In this paper, a two-stage channel-estimation method based on generative adversarial networks (cGAN) is proposed for MIMO-OFDM systems in high-mobility scenarios. The complex channel matrix is treated as an image, and the cGAN is trained against it to generate a more realistic channel image. In addition, the noise2noise (N2N) algorithm is used to denoise the pilot signal received by the base station to improve the estimation quality. Simulation experiments have shown the proposed N2N-cGAN algorithm has better robustness. In particular, the N2N-cGAN algorithm can be adapted to the case of fewer pilot sequences. Full article

(This article belongs to the Special Issue Pattern Recognition and Machine Learning Applications)

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13 pages, 587 KiB

Open AccessArticle

MalDBA: Detection for Query-Based Malware Black-Box Adversarial Attacks

by Zixiao Kong, Jingfeng Xue, Zhenyan Liu, Yong Wang and Weijie Han

Electronics 2023, 12(7), 1751; https://doi.org/10.3390/electronics12071751 - 6 Apr 2023

Viewed by 2076

Abstract

The increasing popularity of Industry 4.0 has led to more and more security risks, and malware adversarial attacks emerge in an endless stream, posing great challenges to user data security and privacy protection. In this paper, we investigate the stateful detection method for [...] Read more.

The increasing popularity of Industry 4.0 has led to more and more security risks, and malware adversarial attacks emerge in an endless stream, posing great challenges to user data security and privacy protection. In this paper, we investigate the stateful detection method for artificial intelligence deep learning-based malware black-box attacks, i.e., determining the presence of adversarial attacks rather than detecting whether the input samples are malicious or not. To this end, we propose the MalDBA method for experiments on the VirusShare dataset. We find that query-based black-box attacks produce a series of highly similar historical query results (also known as intermediate samples). By comparing the similarity among these intermediate samples and the trend of prediction scores returned by the detector, we can detect the presence of adversarial samples in indexed samples and thus determine whether an adversarial attack has occurred, and then protect user data security and privacy. The experimental results show that the attack detection rate can reach 100%. Compared to similar studies, our method does not require heavy feature extraction tasks or image conversion and can be operated on complete PE files without requiring a strong hardware platform. Full article

(This article belongs to the Special Issue AI-Driven Network Security and Privacy)

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19 pages, 8197 KiB

Open AccessArticle

Efficient GaN-on-Si Power Amplifier Design Using Analytical and Numerical Optimization Methods for 24–30 GHz 5G Applications

by Lin Peng, Zhihao Zhang and Gary Zhang

Electronics 2023, 12(7), 1750; https://doi.org/10.3390/electronics12071750 - 6 Apr 2023

Cited by 3 | Viewed by 2769

Abstract

This paper presents the design procedure of an efficient compact monolithic microwave integrated circuit power amplifier (MMIC PA) in a 0.1 μm GaN-on-Si process for 5G millimeter-wave communication. Load/source-pull simulations were conducted to correctly create equivalent large-signal matching models for stabilized power cells [...] Read more.

This paper presents the design procedure of an efficient compact monolithic microwave integrated circuit power amplifier (MMIC PA) in a 0.1 μm GaN-on-Si process for 5G millimeter-wave communication. Load/source-pull simulations were conducted to correctly create equivalent large-signal matching models for stabilized power cells and to determine the optimal impedance domain. The shorted stub with bypass capacitors minimizes the transistor’s output reactance, simplifying the matching objective to an approximate real impedance transformation (IT). With miniaturization as the implementation guide, explicit formulas and tabulated methods based on mathematical analysis were applied to synthesize the filtering matching networks (MNs) for the input and output stages. In addition, a CAD-dependent numerical optimization approach was used for the interstage MN that needs to cope with high IT ratio and complex loads. The continuous-wave (CW) characterization for the proposed two-stage PA demonstrated 19.8 ± 0.7 dB of small-signal gain, very flat output power (P_out) and power-added efficiency (PAE) at 4 dB gain compression of 32–32.4 dBm and 34–34.6%, respectively, over 24–30 GHz, with 37.1% of peak PAE at mid-frequency. Full article

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

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14 pages, 1303 KiB

Open AccessArticle

Parallel Stochastic Computing Architecture for Computationally Intensive Applications

by Jeongeun Kim, Won Sik Jeong, Youngwoo Jeong and Seung Eun Lee

Electronics 2023, 12(7), 1749; https://doi.org/10.3390/electronics12071749 - 6 Apr 2023

Cited by 3 | Viewed by 2015

Abstract

Stochastic computing requires random number generators to generate stochastic sequences that represent probability values. In the case of an 8-bit operation, a 256-bit length of a stochastic sequence is required, which results in latency issues. In this paper, a stochastic computing architecture is [...] Read more.

Stochastic computing requires random number generators to generate stochastic sequences that represent probability values. In the case of an 8-bit operation, a 256-bit length of a stochastic sequence is required, which results in latency issues. In this paper, a stochastic computing architecture is proposed to address the latency issue by employing parallel linear feedback shift registers (LFSRs). The proposed architecture reduces the latency in the stochastic sequence generation process without losing accuracy. In addition, the proposed architecture achieves area efficiency by reducing 69% of flip-flops and 70.4% of LUTs compared to architecture employing shared LFSRs, and 74% of flip-flops and 58% of LUTs compared to the architecture applying multiple LFSRs with the same computational time. Full article

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15 pages, 503 KiB

Open AccessArticle

A Unified Approach to Nested and Non-Nested Slots for Spoken Language Understanding

by Xue Wan, Wensheng Zhang, Mengxing Huang, Siling Feng and Yuanyuan Wu

Electronics 2023, 12(7), 1748; https://doi.org/10.3390/electronics12071748 - 6 Apr 2023

Cited by 2 | Viewed by 1545

Abstract

As chatbots become more popular, multi-intent spoken language understanding (SLU) has received unprecedented attention. Multi-intent SLU, which primarily comprises the two subtasks of multiple intent detection (ID) and slot filling (SF), has the potential for widespread implementation. The two primary issues with the [...] Read more.

As chatbots become more popular, multi-intent spoken language understanding (SLU) has received unprecedented attention. Multi-intent SLU, which primarily comprises the two subtasks of multiple intent detection (ID) and slot filling (SF), has the potential for widespread implementation. The two primary issues with the current approaches are as follows: (1) They cannot solve the problem of slot nesting; (2) The performance and inference rate of the model are not high enough. To address these issues, we suggest a multi-intent joint model based on global pointers to handle nested and non-nested slots. Firstly, we constructed a multi-dimensional type-slot label interaction network (MTLN) for subsequent intent decoding to enhance the implicit correlation between intents and slots, which allows for more adequate information about each other. Secondly, the global pointer network (GP) was introduced, which not only deals with nested and non-nested slots and slot incoherence but also has a faster inference rate and better performance than the baseline model. On two multi-intent datasets, the proposed model achieves state-of-the-art results on MixATIS with 1.6% improvement of intent Acc, 0.1% improvement of slot F1 values, 3.1% improvement of sentence Acc values, and 1.2%, 1.1% and 4.5% performance improvements on MixSNIPS, respectively. Meanwhile, the inference rate is also improved. Full article

(This article belongs to the Topic Machine and Deep Learning)

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22 pages, 8715 KiB

Open AccessArticle

9.9 µW, 140 dB DR, and 93.27 dB SNDR, Double Sampling ΔΣ Modulator Using High Swing Inverter-Based Amplifier for Digital Hearing Aids

by Shima Alizadeh Zanjani, Abumoslem Jannesari and Pooya Torkzadeh

Electronics 2023, 12(7), 1747; https://doi.org/10.3390/electronics12071747 - 6 Apr 2023

Viewed by 1898

Abstract

In this paper, an ultra-low-power second-order, single-bit discrete-time (DT) double sampling ΔΣ modulator was proposed for hearing aid applications. In portable biomedical devices that are permanently used such as hearing aids, short battery lifetime and power dissipation are considerable issues. In a typical [...] Read more.

In this paper, an ultra-low-power second-order, single-bit discrete-time (DT) double sampling ΔΣ modulator was proposed for hearing aid applications. In portable biomedical devices that are permanently used such as hearing aids, short battery lifetime and power dissipation are considerable issues. In a typical delta–sigma modulator, the most power-consuming parts are the operational transconductance amplifiers (OTAs), and their elimination without loss of efficiency is now challenging. This proposed modulator includes an ultra-low-power self-biased inverter-based amplifier with swing enhancement instead of power-hungry OTAs. Low voltage amplifier design reduces output swing voltage, affecting delta–sigma modulator efficiency and decreasing the signal-to-noise and distortion ratio (SNDR) and dynamic range (DR) values. In this article, the proposed amplifier’s source and tail transistors were biased in the sub-threshold region, increasing the output swing voltage significantly and leading to desired properties for a hearing aid modulator. The proposed amplifier peak-to-peak swing voltage was approximately 1.01 V at a 1 V power supply. In addition, the proposed modulator design used a standard 180 nm CMOS technology, which obtained 140 dB DR and 93.27 dB SNDR for a 10 kHz signal bandwidth with an oversampling ratio (OSR) of 128. Finally, the modulator’s effective chip area was 0.02 mm² and consumed only about 9.9 µW, while the figure of merit (FOM_W) and FOMs achieved 1.31 fJ/step and 183.31, respectively. Full article

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15 pages, 4263 KiB

Open AccessArticle

A Current Spectrum-Based Algorithm for Fault Detection of Electrical Machines Using Low-Power Data Acquisition Devices

by Bilal Asad, Hadi Ashraf Raja, Toomas Vaimann, Ants Kallaste, Raimondas Pomarnacki and Van Khang Hyunh

Electronics 2023, 12(7), 1746; https://doi.org/10.3390/electronics12071746 - 6 Apr 2023

Cited by 2 | Viewed by 2089

Abstract

An algorithm to improve the resolution of the frequency spectrum by detecting the number of complete cycles, removing any fractional components of the signal, signal discontinuities, and interpolating the signal for fault diagnostics of electrical machines using low-power data acquisition cards is proposed [...] Read more.

An algorithm to improve the resolution of the frequency spectrum by detecting the number of complete cycles, removing any fractional components of the signal, signal discontinuities, and interpolating the signal for fault diagnostics of electrical machines using low-power data acquisition cards is proposed in this paper. Smart sensor-based low-power data acquisition and processing devices such as Arduino cards are becoming common due to the growing trend of the Internet of Things (IoT), cloud computation, and other Industry 4.0 standards. For predictive maintenance, the fault representing frequencies at the incipient stage are very difficult to detect due to their small amplitude and the leakage of powerful frequency components into other parts of the spectrum. For this purpose, offline advanced signal processing techniques are used that cannot be performed in small signal processing devices due to the required computational time, complexity, and memory. Hence, in this paper, an algorithm is proposed that can improve the spectrum resolution without complex advanced signal processing techniques and is suitable for low-power signal processing devices. The results both from the simulation and practical environment are presented. Full article

(This article belongs to the Special Issue Advanced Fault Detection, Diagnosis and Prognosis in a Context of Renewable Power Generation)

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13 pages, 4183 KiB

Open AccessArticle

Thangka Sketch Colorization Based on Multi-Level Adaptive-Instance-Normalized Color Fusion and Skip Connection Attention

by Hang Li, Jie Fang, Ying Jia, Liqi Ji, Xin Chen and Nianyi Wang

Electronics 2023, 12(7), 1745; https://doi.org/10.3390/electronics12071745 - 6 Apr 2023

Cited by 2 | Viewed by 1895

Abstract

Thangka is an important intangible cultural heritage of Tibet. Due to the complexity, and time-consuming nature of the Thangka painting technique, this technique is currently facing the risk of being lost. It is important to preserve the art of Thangka through digital painting [...] Read more.

Thangka is an important intangible cultural heritage of Tibet. Due to the complexity, and time-consuming nature of the Thangka painting technique, this technique is currently facing the risk of being lost. It is important to preserve the art of Thangka through digital painting methods. Machine learning-based auto-sketch colorization is one of the vital steps for digital Thangka painting. However, existing learning-based sketch colorization methods face two challenges in solving the problem of colorizing Thangka: (1) the extremely rich colors of the Thangka make it difficult to color accurately with existing algorithms, and (2) the line density of the Thangka brings extreme challenges for algorithms to define what semantic information the lines imply. To resolve these problems, we propose a Thangka sketch colorization method based on multi-level adaptive-instance-normalized color fusion (MACF) and skip connection attention (SCA). The proposed method consists of two parts: (1) a multi-level adaptive-instance-normalized color fusion (MACF) to fuse sketch feature and color feature; and (2) a skip connection attention (SCA) mechanism to distinguish the semantic information implied by the sketch lines. Experiments on colorizing Thangka sketches show that our method works well on two small datasets—the Danbooru 2019 dataset and the Thangka dataset. Our approach can generate exquisite Thangka. Full article

(This article belongs to the Topic Computer Vision and Image Processing)

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18 pages, 18651 KiB

Open AccessArticle

Remaining Useful Life Prediction for a Catenary, Utilizing Bayesian Optimization of Stacking

by Li Liu, Zhihui Zhang, Zhijian Qu and Adrian Bell

Electronics 2023, 12(7), 1744; https://doi.org/10.3390/electronics12071744 - 6 Apr 2023

Cited by 3 | Viewed by 1661

Abstract

This article addresses the problem that the remaining useful life (RUL) prediction accuracy for a high-speed rail catenary is not accurate enough, leading to costly and time-consuming periodic planned and reactive maintenance costs. A new method for predicting the RUL of a catenary [...] Read more.

This article addresses the problem that the remaining useful life (RUL) prediction accuracy for a high-speed rail catenary is not accurate enough, leading to costly and time-consuming periodic planned and reactive maintenance costs. A new method for predicting the RUL of a catenary is proposed based on the Bayesian optimization stacking ensemble learning method. Taking the uplink and downlink catenary data of a high-speed railway line as an example, the preprocessed historical maintenance and maintenance data are input into the integrated prediction model of Bayesian hyperparameter optimization for training, and the root mean square error (RMSE) of the final optimized RUL prediction result is 0.068, with an R-square (R²) of 0.957, and a mean absolute error (MAE) of 0.053. The calculation example results show that the improved stacking ensemble algorithm improves the RMSE by 28.42%, 30.61% and 32.67% when compared with the extreme gradient boosting (XGBoost), support vector machine (SVM) and random forests (RF) algorithms, respectively. The improved accuracy prediction lays the foundation for targeted equipment maintenance and system maintenance performed before the catenary system fails, thus potentially saving both planned and reactive maintenance costs and time. Full article

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19 pages, 513 KiB

Open AccessArticle

Survivability Analysis of Unmanned Aerial Vehicle Network based on Dynamic Weighted Clustering Algorithm with Dual Cluster Heads

by Yujing Zhang, Zhiqun Hu, Zhifei Wang, Xiangming Wen and Zhaoming Lu

Electronics 2023, 12(7), 1743; https://doi.org/10.3390/electronics12071743 - 6 Apr 2023

Cited by 1 | Viewed by 1639

Abstract

The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic [...] Read more.

The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic weighted clustering algorithm with dual cluster heads (DWCA-DCH) in this paper to deploy the UAV network. To trade off communication efficiency and lifetime, the selection of prime and backup cluster heads is designed by synthetically considering communication quality and remaining energy of the UAV. Furthermore, a survivability analysis method based on Markov process (SAM-MP) is constructed to analyze the survivability performance of the proposed UAV network based on DWCA-DCH when the UAV node suffers from energy exhausting or accidents. The simulation results show that the survivability and stability of the UAV cluster ad hoc network based on DWCA-DCH proposed in this paper is improved by about 35% compared with the single cluster head network. Full article

(This article belongs to the Special Issue Advanced Technologies in Unmanned Aerial Vehicles)

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17 pages, 2222 KiB

Open AccessArticle

DNCL: Hybrid DOA Estimation and NMDS Cooperative Multi-Target Localization for RFID

by Yuting Li, Yongtao Ma, Chenglong Tian, Dianfei Su and Bo Yang

Electronics 2023, 12(7), 1742; https://doi.org/10.3390/electronics12071742 - 6 Apr 2023

Cited by 1 | Viewed by 1852

Abstract

Passive radio frequency identification (RFID) tags have been widely used in logistics, supply chain, warehousing, and other fields. However, for RFID-based automatic inventory management in warehouses, the deployment of current methods is more complex, and the localization range still has some limitations. This [...] Read more.

Passive radio frequency identification (RFID) tags have been widely used in logistics, supply chain, warehousing, and other fields. However, for RFID-based automatic inventory management in warehouses, the deployment of current methods is more complex, and the localization range still has some limitations. This paper proposes DNCL, which is a hybrid passive RFID localization scheme based on direction-of-arrival (DOA) estimation and nonmetric multidimensional scaling (NMDS) to achieve spatial coordinate localization of tagged objects on shelves or racks using a single antenna for simple 1D scanning. DNCL uses antenna dynamic scanning to generate a virtual antenna array for the dynamic information capture of tags in the scene, which helps eliminate the phase shift produced by ambient noise. We apply the angle profile linear model to identify the characteristics of each tag and introduce the NMDS algorithm to improve the robustness of the scheme through the fixed layout of the reference tags, which can reliably estimate the coordinates of the tagged objects in the space. This paper realizes a prototype system and validated its practical performance in real complex situationse by COTS RFID devices. The results indicate that DNCL can achieve high accuracy for the localization of passive tags in free space. Full article

(This article belongs to the Special Issue RFID Technology and Its Applications)

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15 pages, 2255 KiB

Open AccessArticle

Response Surface Method for Reliability Analysis Based on Iteratively-Reweighted-Least-Square Extreme Learning Machines

by Yanjun Ou, Yeting Wu, Jun Cheng, Yangyang Chen and Wei Zhao

Electronics 2023, 12(7), 1741; https://doi.org/10.3390/electronics12071741 - 6 Apr 2023

Cited by 3 | Viewed by 1229

Abstract

A response surface method for reliability analysis based on iteratively-reweighted-least-square extreme learning machines (IRLS-ELM) is explored in this paper, in which, highly nonlinear implicit performance functions of structures are approximated by the IRLS-ELM. Monte Carlo simulation is then carried out on the approximate [...] Read more.

A response surface method for reliability analysis based on iteratively-reweighted-least-square extreme learning machines (IRLS-ELM) is explored in this paper, in which, highly nonlinear implicit performance functions of structures are approximated by the IRLS-ELM. Monte Carlo simulation is then carried out on the approximate IRLS-ELM for structural reliability analysis. Some numerical examples are given to illustrate the proposed method. The effects of parameters involved in the IRLS-ELM on accuracy in reliability analysis are respectively discussed. The results exhibit that a proper number of samples and neurons in hidden layer nodes, an appropriate regularization parameter, and the number of iterations for reweighting are of important assurance to obtain reasonable precision in estimating structural failure probability. Full article

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13 pages, 5172 KiB

Open AccessArticle

Long Distance Military Fiber-Optic Polarization Sensor Improved by an Optical Amplifier

by Martin Kyselak, Jiri Vavra, Karel Slavicek, David Grenar and Lucie Hudcova

Electronics 2023, 12(7), 1740; https://doi.org/10.3390/electronics12071740 - 6 Apr 2023

Cited by 4 | Viewed by 2009

Abstract

The ever-increasing demands for the use of fiber-optic sensors powered by long optical fibers is forcing developers to solve problems associated with powering these remote sensors. Due to their non-electric character, these sensors are suitable for many uses, including military applications. The Army [...] Read more.

The ever-increasing demands for the use of fiber-optic sensors powered by long optical fibers is forcing developers to solve problems associated with powering these remote sensors. Due to their non-electric character, these sensors are suitable for many uses, including military applications. The Army of the Czech Republic is very interested in this type of optical fiber sensor as it fulfils the significant prerequisites for use in military areas. However, the army’s requirements are challenging because they require long supply cables in which there is significant attenuation of optical power. At the same time, there is a need for high sensitivity. The subject of our research team’s work was to use amplifiers to power these sensors. The army already uses this type of sensor for short distances as it cannot ignite a gas mixture with an explosive concentration and thus meet the strict requirements of the explosion-poof standard. The novelty of our research lies in the discovered measurement technique that allows the sensors to be powered remotely and in the saving of optical fibers by utilizing duplex communication with a circulator. Furthermore, the research presents an innovative approach to the optimization of the entire sensor by using a bidirectional, sensory, polarization-maintaining optical fiber. The proposed sensor was first verified in laboratory conditions at the Optoelectronics Laboratory of the University of Defense in Brno, and further tests were carried out in the military training areas of Boletice and Březina in the Czech Republic, which is a member of North Atlantic Treaty Organization. Full article

(This article belongs to the Special Issue Advances in Optical Fiber Amplifiers: Techniques and Applications to Laser-Based Global Connectivity)

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14 pages, 2300 KiB

Open AccessArticle

Energy-Constrained UAV Data Acquisition in Wireless Sensor Networks with the Age of Information

by Jinxuan Xiong, Zhimin Li, Hongzhi Li, Lin Tang and Shaohong Zhong

Electronics 2023, 12(7), 1739; https://doi.org/10.3390/electronics12071739 - 6 Apr 2023

Cited by 3 | Viewed by 1573

Abstract

This paper considers a wireless sensor network (WSN) assisted by the unmanned aerial vehicle (UAV) in the Internet of Things (IoT). The UAV departs from the data center to the ground node to collect sensor node data as a relay. Under the constraints [...] Read more.

This paper considers a wireless sensor network (WSN) assisted by the unmanned aerial vehicle (UAV) in the Internet of Things (IoT). The UAV departs from the data center to the ground node to collect sensor node data as a relay. Under the constraints of battery energy, the UAV will travel to and from the data center repeatedly and transmit the collected sensor node data. The freshness of the node data received by the data center is measured by the Age of Information (AoI) as a performance metric. A genetic algorithm is used to plan the flight trajectory of the UAV. To ensure the data’s integrity and accuracy in a single sensor node, the UAV continuously collects sensor node data when the distance from the sensor node is less than the minimum acquisition distance. Through simulation experiments, we analyzed the influence of changing acquisition distance, the initial battery capacity, acquisition success probability, and transmission power on the peak age of information and the average age of information. Full article

(This article belongs to the Special Issue AI Technologies and Smart City)

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18 pages, 8071 KiB

Open AccessArticle

A Face Detector with Adaptive Feature Fusion in Classroom Environment

by Cheng Sun, Pei Wen, Shiwen Zhang, Xingjin Wu, Jin Zhang and Hongfang Gong

Electronics 2023, 12(7), 1738; https://doi.org/10.3390/electronics12071738 - 6 Apr 2023

Cited by 2 | Viewed by 2088

Abstract

Face detection in the classroom environment is the basis for student face recognition, sensorless attendance, and concentration analysis. Due to equipment, lighting, and the uncontrollability of students in an unconstrained environment, images include many moving faces, occluded faces, and extremely small faces in [...] Read more.

Face detection in the classroom environment is the basis for student face recognition, sensorless attendance, and concentration analysis. Due to equipment, lighting, and the uncontrollability of students in an unconstrained environment, images include many moving faces, occluded faces, and extremely small faces in a classroom environment. Since the image sent to the detector will be resized to a smaller size, the face information extracted by the detector is very limited. This seriously affects the accuracy of face detection. Therefore, this paper proposes an adaptive fusion-based YOLOv5 method for face detection in classroom environments. First, a very small face detection layer in YOLOv5 is added to enhance the YOLOv5 baseline, and an adaptive fusion backbone network based on multi-scale features is proposed, which has the ability to feature fusion and rich feature information. Second, the adaptive spatial feature fusion strategy is applied to the network, considering the face location information and semantic information. Finally, a face dataset Classroom-Face in the classroom environment is creatively proposed, and it is verified with our method. The experimental results show that, compared with YOLOv5 or other traditional algorithms, our algorithm portrays better performance in WIDER-FACE Dataset and Classroom-Face dataset. Full article

(This article belongs to the Special Issue Deep Learning in Computer Vision and Image Processing)

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15 pages, 2487 KiB

Open AccessArticle

Root Mirror Sites Identification and Service Area Analysis

by Jiachen Wang, Zhiping Li, Zhaoxin Zhang, Jian Chen, Chao Li and Yanan Cheng

Electronics 2023, 12(7), 1737; https://doi.org/10.3390/electronics12071737 - 5 Apr 2023

Cited by 1 | Viewed by 1935

Abstract

The operation of today’s Internet can only be achieved with the domain name system (DNS), and the essential part of the DNS is the root servers. Adding anycast mirrors has been used to maintain the security of root servers, but many problems accompany [...] Read more.

The operation of today’s Internet can only be achieved with the domain name system (DNS), and the essential part of the DNS is the root servers. Adding anycast mirrors has been used to maintain the security of root servers, but many problems accompany this technique. In this paper, we used 36198 probe points deployed worldwide to probe 1160 root mirror sites and analyzed the data with root mirrors’ identification and localization (RMIL). RMIL is a method to identify and locate root mirrors. It contains probing and analyzing the network services ID (NSID) and traceroute data to identify and locate root mirror sites. Using this method, 821 (70.78% of the total) sites were accurately identified and located, and city-level localization was achieved for 281 other sites. Finally, the identification results were used in the service area analysis. The analysis contained multiple dimensions: locations, autonomous system numbers (ASN), internet service providers (ISP), and IPV4 prefixes. As such, we helped identify and locate root mirror sites more precisely and discover which ones have a greater service area in different dimensions. Full article

(This article belongs to the Topic Cyber Security and Critical Infrastructures)

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17 pages, 2052 KiB

Open AccessArticle

Improved Repetitive Control for an LCL-Type Grid-Tied Inverter with Frequency Adaptive Capability in Microgrids

by Hongwei Zhang, Qiangsong Zhao, Shuanghong Wang and Xuebin Yue

Electronics 2023, 12(7), 1736; https://doi.org/10.3390/electronics12071736 - 5 Apr 2023

Cited by 1 | Viewed by 1861

Abstract

Repetitive control (RC), which can track any periodic signal with a known integer period with zero steady-state error, is widely used for current control of grid-tied inverters in microgrids. However, the inherent one fundamental period time delay, leads to poor dynamic performance. Furthermore, [...] Read more.

Repetitive control (RC), which can track any periodic signal with a known integer period with zero steady-state error, is widely used for current control of grid-tied inverters in microgrids. However, the inherent one fundamental period time delay, leads to poor dynamic performance. Furthermore, the performance of conventional RC (CRC) will degrade when operating at a high variation grid frequency. Therefore, this paper proposes a frequency adaptive improved RC (FA-IRC) for grid-tied inverters. The improved RC (IRC) consists of a repetitive controller with a modified internal model filter, plus a proportional controller. In comparison to the CRC, the IRC has a good dynamic response, because it provides a higher gain and a wider bandwidth at the resonant frequency. Moreover, to achieve the frequency adaptability of the IRC, a fractional delay, based on a finite impulse response (FIR) filter, is built into the IRC system, to ensure that the resonant frequency of the IRC is approximately equal to the actual grid frequency and harmonic frequency. Stability analysis and characteristic analysis of the FA-IRC system are reported in this paper. Simulations are conducted, to demonstrate the validity of the proposed method. Full article

(This article belongs to the Topic Power System Dynamics and Stability)

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19 pages, 18389 KiB

Open AccessArticle

Summarization of Videos with the Signature Transform

by J. de Curtò, I. de Zarzà, Gemma Roig and Carlos T. Calafate

Electronics 2023, 12(7), 1735; https://doi.org/10.3390/electronics12071735 - 5 Apr 2023

Cited by 8 | Viewed by 1893

Abstract

This manuscript presents a new benchmark for assessing the quality of visual summaries without the need for human annotators. It is based on the Signature Transform, specifically focusing on the RMSE and the MAE Signature and Log-Signature metrics, and builds upon the assumption [...] Read more.

This manuscript presents a new benchmark for assessing the quality of visual summaries without the need for human annotators. It is based on the Signature Transform, specifically focusing on the RMSE and the MAE Signature and Log-Signature metrics, and builds upon the assumption that uniform random sampling can offer accurate summarization capabilities. We provide a new dataset comprising videos from Youtube and their corresponding automatic audio transcriptions. Firstly, we introduce a preliminary baseline for automatic video summarization, which has at its core a Vision Transformer, an image–text model pre-trained with Contrastive Language–Image Pre-training (CLIP), as well as a module of object detection. Following that, we propose an accurate technique grounded in the harmonic components captured by the Signature Transform, which delivers compelling accuracy. The analytical measures are extensively evaluated, and we conclude that they strongly correlate with the notion of a good summary. Full article

(This article belongs to the Special Issue Advanced Technologies for Image/Video Quality Assessment)

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21 pages, 3518 KiB

Open AccessArticle

Fault Segment Location for MV Distribution System Based on the Characteristic Voltage of LV Side

by Dehai Zhang, Wenhai Zhang, Changzhi Wang and Xianyong Xiao

Electronics 2023, 12(7), 1734; https://doi.org/10.3390/electronics12071734 - 5 Apr 2023

Cited by 3 | Viewed by 1869

Abstract

The voltage and current measurement of the medium-voltage (MV) side are used for the traditional fault location method, which leads to a high installation cost of the measurement and complicated post-operational and maintenance work. A fault location method is proposed based on the [...] Read more.

The voltage and current measurement of the medium-voltage (MV) side are used for the traditional fault location method, which leads to a high installation cost of the measurement and complicated post-operational and maintenance work. A fault location method is proposed based on the distributed measurement at the low-voltage (LV) side. On the analysis of voltage distribution rules and the influence of the distribution transformer on voltage transmission, obvious differences are found in the variation of voltage (phase voltage and sequence voltage) at the LV side for different faults—specifically, the detection sensitivity of the voltage to different faults varies. Therefore, a fault location method for the MV distribution network based on characteristic voltage at the LV side is proposed. Firstly, the characteristic voltage is selected adaptively according to the fault type. The suspected fault path is then determined by the characteristic voltage amplitude of measuring points. Finally, the fault segment is located via the characteristic current of each segment. This method can be applied in combination with the widely used LV measurement equipment such as the power consumption information acquisition system and the intelligent fusion terminal to acquire LV side voltage without adding new measurement devices. The distribution difference of the characteristic voltage at the LV side is applied for accurate fault finding, which is an economical and practical new idea for the fault location of the distribution network. The correctness and effectiveness of the method were verified by the simulation of the IEEE 34 system built in PSCAD/EMTDC and a real distribution network. Full article

(This article belongs to the Special Issue Advancement of Fault Detection and Fault-Tolerant Control with Applications)

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15 pages, 3466 KiB

Open AccessArticle

A New Generation of Fast and Low-Memory Smart Digital/Geometrical Beamforming MIMO Antenna

by Kandasamy Pirapaharan, W. H. Sasinda C. Prabhashana, S. P. Pramuka Medaranga, Paul R. P. Hoole and Xavier Fernando

Electronics 2023, 12(7), 1733; https://doi.org/10.3390/electronics12071733 - 5 Apr 2023

Cited by 7 | Viewed by 2312

Abstract

Smart multiple-input multiple-output (MIMO) antennas with advanced signal processing algorithms are necessary in future wireless networks, such as 6G and beyond, for accurate space division multiplexing and beamforming. Such a MIMO antenna will yield better network coverage and tracking. This paper presents a [...] Read more.

Smart multiple-input multiple-output (MIMO) antennas with advanced signal processing algorithms are necessary in future wireless networks, such as 6G and beyond, for accurate space division multiplexing and beamforming. Such a MIMO antenna will yield better network coverage and tracking. This paper presents a smart MIMO antenna configuration with a highly innovative beamforming technique using several nonlinear configurations of dipole arrays. Phase delay factors are optimized at the transmitter to form a single beam and then to steer the beam towards a particular direction. A number of phase shifters are added in order to obtain maximum directional gain. This configuration also significantly increases the power gain of the MIMO antenna at a low cost and with operational simplicity. The paper also demonstrates how the beam width and beamsteering can be effectively controlled. Wolfram Mathematica software was used to generate the three-dimensional radiated beam patterns of the transmitter antenna. There are two approaches to configure the receiver antenna. In the first approach, the received signal magnitude is maximized by aligning the contribution of all elements of the receiver antenna to the same phase. With this approach, the field gain of the proposed system is 25.52 (14.07 dBi). The signal processing gain at the receiver is 64 (18.06 dBi). Therefore, the overall power gain for this proposed new digital/geometrical smart MIMO system is 32.13 dBi. In the second approach, the receiver beam is directed towards the transmitter by optimizing the phase delay coefficients of the receiver. Here, the overall gain of the system is found to be 134.56 (21.28 dBi). Even though the system gain in the second approach is lower, it has the advantage of low interference at the receiver side. Full article

(This article belongs to the Special Issue State-of-the-Art of Smart MIMO Antennas)

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13 pages, 5352 KiB

Open AccessArticle

Research on Detection and Recognition Technology of a Visible and Infrared Dim and Small Target Based on Deep Learning

by Yuxing Dong, Yan Li and Zhen Li

Electronics 2023, 12(7), 1732; https://doi.org/10.3390/electronics12071732 - 5 Apr 2023

Cited by 1 | Viewed by 1745

Abstract

With the increasing trend towards informatization and intelligence in modern warfare, high-intensity and continuous reconnaissance activities are becoming increasingly common in battlefield environments via airborne, vehicle, UAV, satellite and other platforms. Visible and infrared images are preferred due to their high resolution, strong [...] Read more.

With the increasing trend towards informatization and intelligence in modern warfare, high-intensity and continuous reconnaissance activities are becoming increasingly common in battlefield environments via airborne, vehicle, UAV, satellite and other platforms. Visible and infrared images are preferred due to their high resolution, strong contrast, rich texture details and color features, and strong information expression ability. However, the quality of imaging is easily affected by environmental factors, making it crucial to quickly and accurately filter useful information from massive image data. To this end, super-resolution image preprocessing can improve the detection performance of UAV, and reduce false detection and missed detection of targets. Additionally, super-resolution reconstruction results in high-quality images that can be used to expand UAV datasets and enhance the UAV characteristics, thereby enabling the enhancement of small targets. In response to the challenge of “low-slow small” UAV targets at long distances, we propose a multi-scale fusion super-resolution reconstruction (MFSRCNN) algorithm based on the fast super-resolution reconstruction (FSRCNN) algorithm and multi-scale fusion. Our experiments confirm the feasibility of the algorithm in reconstructing detailed information of the UAV target. On average, the MFSRCNN reconstruction time is 0.028 s, with the average confidence before and after reconstruction being 80.73% and 86.59%, respectively, resulting in an average increase of 6.72%. Full article

(This article belongs to the Section Artificial Intelligence)

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15 pages, 349 KiB

Open AccessArticle

An Instruction-Driven Batch-Based High-Performance Resource-Efficient LSTM Accelerator on FPGA

by Ning Mao, Haigang Yang and Zhihong Huang

Electronics 2023, 12(7), 1731; https://doi.org/10.3390/electronics12071731 - 5 Apr 2023

Cited by 1 | Viewed by 1951

Abstract

In recent years, long short-term memory (LSTM) has been used in many speech recognition tasks, due to its excellent performance. Due to a large amount of calculation and complex data dependencies of LSTM, it is often not so efficient to deploy on the [...] Read more.

In recent years, long short-term memory (LSTM) has been used in many speech recognition tasks, due to its excellent performance. Due to a large amount of calculation and complex data dependencies of LSTM, it is often not so efficient to deploy on the field-programmable gate array (FPGA) platform. This paper proposes an LSTM accelerator, driven by a specific instruction set. The accelerator consists of a matrix multiplication unit and a post-processing unit. The matrix multiplication unit uses staggered timing of read data to reduce register usage. The post-processing unit can complete various calculations with only a small amount of digital signal processing (DSP) slices, through resource sharing, and at the same time, the memory footprint is reduced, through the well-designed data flow design. The accelerator is batch-based and capable of computing data from multiple users simultaneously. Since the calculation process of LSTM is divided into a sequence of instructions, it is feasible to execute multi-layer LSTM networks as well as large-scale LSTM networks. Experimental results show that our accelerator can achieve a performance of 2036 GOPS at 16-bit data precision, while having higher hardware utilization compared to previous work. Full article

(This article belongs to the Special Issue Applications Enabled by FPGA-Based Technology)

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24 pages, 9129 KiB

Open AccessArticle

A New Three-Way Incremental Naive Bayes Classifier

by Zhiwei Yang, Jing Ren, Zichi Zhang, Yuqing Sun, Chunying Zhang, Mengyao Wang and Liya Wang

Electronics 2023, 12(7), 1730; https://doi.org/10.3390/electronics12071730 - 5 Apr 2023

Cited by 5 | Viewed by 2827

Abstract

Aiming at the problems of the dynamic increase in data in real life and that the naive Bayes (NB) classifier only accepts or rejects the sample processing results, resulting in a high error rate when dealing with uncertain data, this paper combines three-way [...] Read more.

Aiming at the problems of the dynamic increase in data in real life and that the naive Bayes (NB) classifier only accepts or rejects the sample processing results, resulting in a high error rate when dealing with uncertain data, this paper combines three-way decision and incremental learning, and a new three-way incremental naive Bayes classifier (3WD-INB) is proposed. First, the NB classifier is established, and the distribution fitting is carried out according to the minimum residual sum of squares (RSS) for continuous data, so that 3WD-INB can process both discrete data and continuous data, then carry out an incremental learning operation, select the samples with higher data quality according to the confidence of the samples in the incremental training set for incremental learning, solve the problem of data dynamics and filter the poor samples. Then we construct the 3WD-INB classifier and determine the classification rules of the positive, negative and boundary domains of the 3WD-INB classifier, so that the three-way classification of samples can be realized and better decisions can be made when dealing with uncertain data. Finally, five discrete data and five continuous data are selected for comparative experimental analysis with traditional classification methods. The results show that 3WD-INB has high accuracy and recall rate on different types of datasets, and the classification performance is also relatively stable. Full article

(This article belongs to the Section Artificial Intelligence)

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20 pages, 3616 KiB

Open AccessArticle

An Electric Vehicle Assisted Charging Mechanism for Unmanned Aerial Vehicles

by Chenn-Jung Huang, Kai-Wen Hu and Hao-Wen Cheng

Electronics 2023, 12(7), 1729; https://doi.org/10.3390/electronics12071729 - 5 Apr 2023

Cited by 1 | Viewed by 1722

Abstract

The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered [...] Read more.

The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles (EVs) that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, unmanned aerial vehicles (UAVs) have also gradually and more recently been widely used for military and civilian purposes. The recent literature estimated that UAVs will become the major means of transport for goods delivery services before 2040, and the development of passenger UAVs will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping, and charging stations to refill the battery of UAVs. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of UAVs. It may even be very possible that a large number of UAVs need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of UAVs. Although studies have proposed the method of that employing moving EVs along with wireless charging technology in order to provide electricity to UAVs with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options should be provided to fit the individual need of each UAV. In view of this, this work attempts to meet the mission characteristics and needs of various UAVs by providing an adaptive flight path and charging plan attached to individual UAVs, as well as reducing the power load of the renewable power generation during the peak period. We ran a series of simulations for the proposed flight path and charging mechanism to evaluate its performance. The simulation results revealed that the solutions proposed in this work can be used by UAV operators to fit the needs of each individual UAV. Full article

(This article belongs to the Special Issue Electric Vehicles Integration and Control in Smart Grids)

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14 pages, 3057 KiB

Open AccessArticle

Design of a Compact Ultra-Wideband Microstrip Bandpass Filter

by Chen Li, Zhong-Hua Ma, Jia-Xiang Chen, Meng-Nan Wang and Jian-Mei Huang

Electronics 2023, 12(7), 1728; https://doi.org/10.3390/electronics12071728 - 5 Apr 2023

Cited by 17 | Viewed by 3590

Abstract

A compact ultra-wideband bandpass filter based on a multilayer printed circuit board (MPCB) structure is proposed in this paper. RO4450F prepreg is used to bond three RO4350B dielectric substrates with different thicknesses in the MPCB structure. The upper surfaces of the three dielectric [...] Read more.

A compact ultra-wideband bandpass filter based on a multilayer printed circuit board (MPCB) structure is proposed in this paper. RO4450F prepreg is used to bond three RO4350B dielectric substrates with different thicknesses in the MPCB structure. The upper surfaces of the three dielectric substrates are respectively provided with copper-coated structures with different patterns. The blind holes and the defected ground structure (DGS) are added to the MPCB of an ultra-wideband bandpass filter. Two groups of loaded quarter-wavelength terminal-open stubs introduce two transmission zeros, which improves the roll-off rates and stopband characteristics, while simple DGS composed of rectangular slots introduces two resonance points in the passband to improve the return loss. Simulation and measurement are consistent. The insertion loss at the center frequency of 12.795 GHz is 0.58 dB and the fractional bandwidth of 3 dB is 40.33% from 10.215 GHz to 15.375 GHz. This bandpass filter can be widely used in wireless and satellite communication. Full article

(This article belongs to the Special Issue Microwave Devices: Analysis, Design, and Application)

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15 pages, 1475 KiB

Open AccessReview

Improving Humanization through Metaverse-Related Technologies: A Systematic Review

by Maria Gonzalez-Moreno, Paula Andrade-Pino, Carlos Monfort-Vinuesa, Antonio Piñas-Mesa and Esther Rincon

Electronics 2023, 12(7), 1727; https://doi.org/10.3390/electronics12071727 - 5 Apr 2023

Cited by 8 | Viewed by 3242

Abstract

While there is an increasing awareness regarding the culture of humanization, which is strongly needed in the healthcare environment, little knowledge has been provided in relation to accurate strategies to teach humanization skills to healthcare undergraduate students, as well as to healthcare professionals. [...] Read more.

While there is an increasing awareness regarding the culture of humanization, which is strongly needed in the healthcare environment, little knowledge has been provided in relation to accurate strategies to teach humanization skills to healthcare undergraduate students, as well as to healthcare professionals. Furthermore, the usefulness of new technologies to improve humanization skills has hardly been addressed so far in the scientific literature, including promising strategies such as Metaverse-related technologies. Presumably, this is the first systematic review focused on the efficacy of Metaverse-related technologies to increase the acquisition of humanization skills in the healthcare environment. The purpose of this study was to review the scientific studies published in the last decade to answer the following two questions: (1) are Metaverse-related technologies useful in enhancing humanization skills in the healthcare environment? (2) What are the advantages and disadvantages that should be addressed to successfully develop Metaverse-related technologies in the healthcare sector? We conducted a systematic review of the peer-reviewed literature from EBSCO, Ovid, PubMed, Scopus, and Web of Science (WOS), following the PRISMA statements and using the following keywords: “humanization + Metaverse”; “humanization + mixed reality”; “humanization + extended reality”; “humanization + augmented reality”; “humanization + virtual reality”; “humanization + app”; “humanization + telemedicine”; “humanization + digital health”; “humanization + eHealth”; “humanization + telehealth”; “humanization + web-based”; “humanization + website”; “humanization + digital”; “humanization + online”; and “humanization + internet”. Studies published from 2012 to the present, written in the English language, were reviewed. A total of 505 records were obtained, of which three were selected based on the inclusion and exclusion criteria. The results will be helpful in developing new strategies to improve humanization skills in the health sphere. Full article

(This article belongs to the Special Issue Metaverse and Digital Twins)

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16 pages, 3685 KiB

Open AccessArticle

Efficient Strategies for Computing Euler Number of a 3D Binary Image

by Bin Yao, Haochen He, Shiying Kang, Yuyan Chao and Lifeng He

Electronics 2023, 12(7), 1726; https://doi.org/10.3390/electronics12071726 - 5 Apr 2023

Cited by 1 | Viewed by 1519

Abstract

As an important topological property for a 3D binary image, the Euler number can be computed by finding specific a voxel block with 2 × 2 × 2 voxels, named the voxel pattern, in the image. In this paper, we introduce three strategies [...] Read more.

As an important topological property for a 3D binary image, the Euler number can be computed by finding specific a voxel block with 2 × 2 × 2 voxels, named the voxel pattern, in the image. In this paper, we introduce three strategies for enhancing the efficiency of a voxel-pattern-based Euler number computing algorithm used for 3D binary images. The first strategy is taking advantage of the voxel information acquired during computation to avoid accessing voxels repeatedly. This can reduce the average number of accessed voxels from 8 to 4 for processing a voxel pattern. Therefore, the efficiency of computation will be improved. The second strategy is scanning every two rows and processing two voxel patterns simultaneously in each scan. In this strategy, only three voxels need to be accessed when a voxel pattern is processed. The last strategy is determining the voxel accessing order in the processing voxel pattern and unifying the processing of the voxel patterns that have identical Euler number increments to one group in the computation. Although this strategy can theoretically reduce the average number of voxels accessed from 8 to 4.25 for processing a voxel pattern, it is more efficient than the above two strategies for moderate- and high-density 3D binary images. Experimental results demonstrated that the three algorithms with each of our proposed three strategies exhibit greater efficiency compared to the conventional Euler number computing algorithm based on finding specific voxel patterns in the image. Full article

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

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13 pages, 1148 KiB

Open AccessArticle

Detection of Inferior Vena Cava in Ultrasound Scans through a Deep Learning Model

by Piero Policastro, Giovanni Chiarion, Francesco Ponzio, Leonardo Ermini, Stefania Civera, Stefano Albani, Giuseppe Musumeci, Silvestro Roatta and Luca Mesin

Electronics 2023, 12(7), 1725; https://doi.org/10.3390/electronics12071725 - 5 Apr 2023

Cited by 3 | Viewed by 2035

Abstract

Ultrasound (US) scans of inferior vena cava (IVC) are widely adopted by healthcare providers to assess patients’ volume status. Unfortunately, this technique is extremely operator dependent. Recently, new techniques have been introduced to extract stable and objective information from US images by automatic [...] Read more.

Ultrasound (US) scans of inferior vena cava (IVC) are widely adopted by healthcare providers to assess patients’ volume status. Unfortunately, this technique is extremely operator dependent. Recently, new techniques have been introduced to extract stable and objective information from US images by automatic IVC edge tracking. However, these methods require prior interaction with the operator, which leads to a waste of time and still makes the technique partially subjective. In this paper, two deep learning methods, YOLO (You only look once) v4 and YOLO v4 tiny networks, commonly used for fast object detection, are applied to identify the location of the IVC and to recognise the either long or short axis view of the US scan. The output of these algorithms can be used to remove operator dependency, to reduce the time required to start an IVC analysis, and to automatically recover the vein if it is lost for a few frames during acquisition. The two networks were trained with frames extracted from 18 subjects, labeled by 4 operators. In addition, they were also trained on a linear combination of two frames that extracted information on both tissue anatomy and movement. We observed similar accuracy of the two models in preliminary tests on the entire dataset, so that YOLO v4 tiny (showing much lower computational cost) was selected for additional cross-validation in which training and test frames were taken from different subjects. The classification accuracy was approximately 88% when using original frames, but it reached 95% when pairs of frames were processed to also include information on tissue movements, indicating the importance of accounting for tissue motion to improve the accuracy of our IVC detector. Full article

(This article belongs to the Special Issue New Technologies for Biomedical Circuits and Systems)

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8 pages, 286 KiB

Open AccessArticle

Approximating Max Function in Fully Homomorphic Encryption

by Hyunjun Lee, Jina Choi and Younho Lee

Electronics 2023, 12(7), 1724; https://doi.org/10.3390/electronics12071724 - 4 Apr 2023

Viewed by 2063

Abstract

This study focuses on efficiently finding the location of the maximum value for large-scale values encrypted by the CKKS (Cheon—Kim—Kim–Song) method. To find the maximum value,

log M + 1

comparison operations and

log M

rotation operations, and

2 log M + 3

[...] Read more.

This study focuses on efficiently finding the location of the maximum value for large-scale values encrypted by the CKKS (Cheon—Kim—Kim–Song) method. To find the maximum value,

log M + 1

comparison operations and

log M

rotation operations, and

2 log M + 3

additions and

2 log M + 1

multiplications are required. However, there is no known way to find a k-approximate maximum value, i.e., a value with the same most significant k-bits as the maximum value. In this study, when the value range of all data in each slot in the ciphertext is [0, 1], we propose a method for finding all slot positions of values whose most significant k-bits match the maximum value. The proposed method can find all slots from the input ciphertexts where their values have the same most significant k-bits as the maximum value by performing

2 k

comparison operations,

(4 k + 2)

multiplications,

(6 k + 2 k log M + 3)

additions, and

2 k log M

rotation operations. Through experiments and complexity analysis, we show that the proposed method is more efficient than the existing method of finding all locations where the k MSB is equal to the maximum value. The result of this can be applied to various privacy-preserving applications in various environments, such as IoT devices. Full article

(This article belongs to the Special Issue Data Driven Security)

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