IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183707

Eyal Weiss

{"title":"Advancements in Electronic Component Assembly: Real-Time AI-Driven Inspection Techniques","authors":"Eyal Weiss","doi":"10.3390/electronics13183707","DOIUrl":"https://doi.org/10.3390/electronics13183707","url":null,"abstract":"This study presents an advanced methodology for improving electronic assembly quality through real-time, inline inspection utilizing state-of-the-art artificial intelligence (AI) and deep learning technologies. The primary goal is to ensure compliance with stringent manufacturing standards, notably IPC-A-610 and IPC-J-STD-001. Employing the existing infrastructure of pick-and-place machines, this system captures high-resolution images of electronic components during the assembly process. These images are analyzed instantly by AI algorithms capable of detecting a variety of defects, including damage, corrosion, counterfeit, and structural irregularities in components and their leads. This proactive approach shifts from conventional reactive quality assurance methods by integrating real-time defect detection and strict adherence to industry standards into the assembly process. With an accuracy rate exceeding 99.5% and processing speeds of about 5 milliseconds per component, this system enables manufacturers to identify and address defects promptly, thereby significantly enhancing manufacturing quality and reliability. The implementation leverages big data analytics, analyzing over a billion components to refine detection algorithms and ensure robust performance. By pre-empting and resolving defects before they escalate, the methodology minimizes production disruptions and fosters a more efficient workflow, ultimately resulting in considerable cost reductions. This paper showcases multiple case studies of component defects, highlighting the diverse types of defects identified through AI and deep learning. These examples, combined with detailed performance metrics, provide insights into optimizing electronic component assembly processes, contributing to elevated production efficiency and quality.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids 基于信任的岛式交流微电网分布式合作控制中网络攻击的检测与缓解

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183692

Md Abu Taher, Mohd Tariq, Arif I. Sarwat

{"title":"Trust-Based Detection and Mitigation of Cyber Attacks in Distributed Cooperative Control of Islanded AC Microgrids","authors":"Md Abu Taher, Mohd Tariq, Arif I. Sarwat","doi":"10.3390/electronics13183692","DOIUrl":"https://doi.org/10.3390/electronics13183692","url":null,"abstract":"In this study, we address the challenge of detecting and mitigating cyber attacks in the distributed cooperative control of islanded AC microgrids, with a particular focus on detecting False Data Injection Attacks (FDIAs), a significant threat to the Smart Grid (SG). The SG integrates traditional power systems with communication networks, creating a complex system with numerous vulnerable links, making it a prime target for cyber attacks. These attacks can lead to the disclosure of private data, control network failures, and even blackouts. Unlike machine learning-based approaches that require extensive datasets and mathematical models dependent on accurate system modeling, our method is free from such dependencies. To enhance the microgrid’s resilience against these threats, we propose a resilient control algorithm by introducing a novel trustworthiness parameter into the traditional cooperative control algorithm. Our method evaluates the trustworthiness of distributed energy resources (DERs) based on their voltage measurements and exchanged information, using Kullback-Leibler (KL) divergence to dynamically adjust control actions. We validated our approach through simulations on both the IEEE-34 bus feeder system with eight DERs and a larger microgrid with twenty-two DERs. The results demonstrated a detection accuracy of around 100%, with millisecond range mitigation time, ensuring rapid system recovery. Additionally, our method improved system stability by up to almost 100% under attack scenarios, showcasing its effectiveness in promptly detecting attacks and maintaining system resilience. These findings highlight the potential of our approach to enhance the security and stability of microgrid systems in the face of cyber threats.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attention-Enhanced Guided Multimodal and Semi-Supervised Networks for Visual Acuity (VA) Prediction after Anti-VEGF Therapy 用于预测抗血管内皮生长因子疗法后视力 (VA) 的注意力增强型多模态和半监督引导网络

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183701

Yizhen Wang , Yaqi Wang, Xianwen Liu, Weiwei Cui, Peng Jin, Yuxia Cheng, Gangyong Jia

{"title":"Attention-Enhanced Guided Multimodal and Semi-Supervised Networks for Visual Acuity (VA) Prediction after Anti-VEGF Therapy","authors":"Yizhen Wang , Yaqi Wang, Xianwen Liu, Weiwei Cui, Peng Jin, Yuxia Cheng, Gangyong Jia","doi":"10.3390/electronics13183701","DOIUrl":"https://doi.org/10.3390/electronics13183701","url":null,"abstract":"The development of telemedicine technology has provided new avenues for the diagnosis and treatment of patients with DME, especially after anti-vascular endothelial growth factor (VEGF) therapy, and accurate prediction of patients’ visual acuity (VA) is important for optimizing follow-up treatment plans. However, current automated prediction methods often require human intervention and have poor interpretability, making it difficult to be widely applied in telemedicine scenarios. Therefore, an efficient, automated prediction model with good interpretability is urgently needed to improve the treatment outcomes of DME patients in telemedicine settings. In this study, we propose a multimodal algorithm based on a semi-supervised learning framework, which aims to combine optical coherence tomography (OCT) images and clinical data to automatically predict the VA values of patients after anti-VEGF treatment. Our approach first performs retinal segmentation of OCT images via a semi-supervised learning framework, which in turn extracts key biomarkers such as central retinal thickness (CST). Subsequently, these features are combined with the patient’s clinical data and fed into a multimodal learning algorithm for VA prediction. Our model performed well in the Asia Pacific Tele-Ophthalmology Society (APTOS) Big Data Competition, earning fifth place in the overall score and third place in VA prediction accuracy. Retinal segmentation achieved an accuracy of 99.03 ± 0.19% on the HZO dataset. This multimodal algorithmic framework is important in the context of telemedicine, especially for the treatment of DME patients.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Low-Power, High-Resolution Analog Front-End Circuit for Carbon-Based SWIR Photodetector 用于碳基 SWIR 光电探测器的低功耗、高分辨率模拟前端电路

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183708

Yuyan Zhang, Zhifeng Chen, Wenli Liao, Weirong Xi, Chengying Chen, Jianhua Jiang

{"title":"A Low-Power, High-Resolution Analog Front-End Circuit for Carbon-Based SWIR Photodetector","authors":"Yuyan Zhang, Zhifeng Chen, Wenli Liao, Weirong Xi, Chengying Chen, Jianhua Jiang","doi":"10.3390/electronics13183708","DOIUrl":"https://doi.org/10.3390/electronics13183708","url":null,"abstract":"Carbon nanotube field-effect transistors (CNT-FETs) have shown great promise in infrared image detection due to their high mobility, low cost, and compatibility with silicon-based technologies. This paper presents the design and simulation of a column-level analog front-end (AFE) circuit tailored for carbon-based short-wave infrared (SWIR) photodetectors. The AFE integrates a Capacitor Trans-impedance Amplifier (CTIA) for current-to-voltage conversion, coupled with Correlated Double Sampling (CDS) for noise reduction and operational amplifier offset suppression. A 10-bit/125 kHz Successive Approximation analog-to-digital converter (SAR ADC) completes the signal processing chain, achieving rail-to-rail input/output with minimized component count. Fabricated using 0.18 μm CMOS technology, the AFE demonstrates a high signal-to-noise ratio (SNR) of 59.27 dB and an Effective Number of Bits (ENOB) of 9.35, with a detectable current range from 500 pA to 100.5 nA and a total power consumption of 7.5 mW. These results confirm the suitability of the proposed AFE for high-precision, low-power SWIR detection systems, with potential applications in medical imaging, night vision, and autonomous driving systems.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Routing Using Fuzzy Logic for URLLC in 5G Networks Based on Software-Defined Networking 基于软件定义网络的 5G 网络中使用模糊逻辑进行 URLLC 的动态路由选择

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183694

Yan-Jing Wu, Menq-Chyun Chen, Wen-Shyang Hwang, Ming-Hua Cheng

{"title":"Dynamic Routing Using Fuzzy Logic for URLLC in 5G Networks Based on Software-Defined Networking","authors":"Yan-Jing Wu, Menq-Chyun Chen, Wen-Shyang Hwang, Ming-Hua Cheng","doi":"10.3390/electronics13183694","DOIUrl":"https://doi.org/10.3390/electronics13183694","url":null,"abstract":"Software-defined networking (SDN) is an emerging networking technology with a central point, called the controller, on the control plane. This controller communicates with the application and data planes. In fifth-generation (5G) mobile wireless networks and beyond, specific levels of service quality are defined for different traffic types. Ultra-reliable low-latency communication (URLLC) is one of the key services in 5G. This paper presents a fuzzy logic (FL)-based dynamic routing (FLDR) mechanism with congestion avoidance for URLLC on SDN-based 5G networks. By periodically monitoring the network status and making forwarding decisions on the basis of fuzzy inference rules, the FLDR mechanism not only can reroute in real time, but also can cope with network status uncertainty owing to FL’s fault tolerance capabilities. Three input parameters, normalized throughput, packet delay, and link utilization, were employed as crisp inputs to the FL control system because they had a more accurate correlation with the network performance measures we studied. The crisp output of the FL control system, i.e., path weight, and a predefined threshold of packet loss ratio on a path were applied to make routing decisions. We evaluated the performance of the proposed FLDR mechanism on the Mininet simulator by installing three additional modules, topology discovery, monitoring, and rerouting with FL, on the traditional control plane of SDN. The superiority of the proposed FLDR over the other existing FL-based routing schemes was demonstrated using three performance measures, system throughput, packet loss rate, and packet delay versus traffic load in the system.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel 10-Watt-Level High-Power Microwave Rectifier with an Inverse Class-F Harmonic Network for Microwave Power Transmission 用于微波功率传输的新型 10 瓦级大功率微波整流器与反 F 类谐波网络

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183705

Jing Peng, Shouhao Wang, Xiaoning Li, Ke Wang

引用次数: 0

A Deep Reinforcement Learning Method Based on a Transformer Model for the Flexible Job Shop Scheduling Problem 基于变压器模型的深度强化学习法，用于灵活的作业车间调度问题

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183696

Shuai Xu, Yanwu Li, Qiuyang Li

{"title":"A Deep Reinforcement Learning Method Based on a Transformer Model for the Flexible Job Shop Scheduling Problem","authors":"Shuai Xu, Yanwu Li, Qiuyang Li","doi":"10.3390/electronics13183696","DOIUrl":"https://doi.org/10.3390/electronics13183696","url":null,"abstract":"The flexible job shop scheduling problem (FJSSP), which can significantly enhance production efficiency, is a mathematical optimization problem widely applied in modern manufacturing industries. However, due to its NP-hard nature, finding an optimal solution for all scenarios within a reasonable time frame faces serious challenges. This paper proposes a solution that transforms the FJSSP into a Markov Decision Process (MDP) and employs deep reinforcement learning (DRL) techniques for resolution. First, we represent the state features of the scheduling environment using seven feature vectors and utilize a transformer encoder as a feature extraction module to effectively capture the relationships between state features and enhance representation capability. Second, based on the features of the jobs and machines, we design 16 composite dispatching rules from multiple dimensions, including the job completion rate, processing time, waiting time, and manufacturing resource utilization, to achieve flexible and efficient scheduling decisions. Furthermore, we project an intuitive and dense reward function with the objective of minimizing the total idle time of machines. Finally, to verify the performance and feasibility of the algorithm, we evaluate the proposed policy model on the Brandimarte, Hurink, and Dauzere datasets. Our experimental results demonstrate that the proposed framework consistently outperforms traditional dispatching rules, surpasses metaheuristic methods on larger-scale instances, and exceeds the performance of existing DRL-based scheduling methods across most datasets.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Evaluation of UDP-Based Data Transmission with Acknowledgment for Various Network Topologies in IoT Environments 物联网环境中基于 UDP 的数据传输（带确认）的性能评估（适用于各种网络拓扑结构

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183697

Bereket Endale Bekele, Krzysztof Tokarz, Nebiyat Yilikal Gebeyehu, Bolesław Pochopień, Dariusz Mrozek

{"title":"Performance Evaluation of UDP-Based Data Transmission with Acknowledgment for Various Network Topologies in IoT Environments","authors":"Bereket Endale Bekele, Krzysztof Tokarz, Nebiyat Yilikal Gebeyehu, Bolesław Pochopień, Dariusz Mrozek","doi":"10.3390/electronics13183697","DOIUrl":"https://doi.org/10.3390/electronics13183697","url":null,"abstract":"The rapid expansion of Internet-of-Things (IoT) applications necessitates a thorough understanding of network configurations to address unique challenges across various use cases. This paper presents an in-depth analysis of three IoT network topologies: linear chain, structured tree, and dynamic transition networks, each designed to meet the specific requirements of industrial automation, home automation, and environmental monitoring. Key performance metrics, including round-trip time (RTT), server processing time (SPT), and power consumption, are evaluated through both simulation and hardware experiments. Additionally, this study introduces an enhanced UDP protocol featuring an acknowledgment mechanism and a power consumption evaluation, aiming to improve data transmission reliability over the standard UDP protocol. Packet loss is specifically measured in hardware experiments to compare the performance of standard and enhanced UDP protocols. The findings show that the enhanced UDP significantly reduces packet loss compared to the standard UDP, enhancing data delivery reliability across dynamic and structured networks, though it comes at the cost of slightly higher power consumption due to additional processing. For network topology performance, the linear chain topology provides stable processing but higher RTT, making it suitable for applications such as tunnel monitoring; the structured tree topology offers low energy consumption and fast communication, ideal for home automation; and the dynamic transition network, suited for industrial Automated Guided Vehicles (AGVs), encounters challenges with adaptive routing. These insights guide the optimization of communication protocols and network configurations for more efficient and reliable IoT deployments.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Light-Weight Self-Supervised Infrared Image Perception Enhancement Method 一种轻量级自监督红外图像感知增强方法

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183695

Yifan Xiao, Zhilong Zhang, Zhouli Li

{"title":"A Light-Weight Self-Supervised Infrared Image Perception Enhancement Method","authors":"Yifan Xiao, Zhilong Zhang, Zhouli Li","doi":"10.3390/electronics13183695","DOIUrl":"https://doi.org/10.3390/electronics13183695","url":null,"abstract":"Convolutional Neural Networks (CNNs) have achieved remarkable results in the field of infrared image enhancement. However, the research on the visual perception mechanism and the objective evaluation indicators for enhanced infrared images is still not in-depth enough. To make the subjective and objective evaluation more consistent, this paper uses a perceptual metric to evaluate the enhancement effect of infrared images. The perceptual metric mimics the early conversion process of the human visual system and uses the normalized Laplacian pyramid distance (NLPD) between the enhanced image and the original scene radiance to evaluate the image enhancement effect. Based on this, this paper designs an infrared image-enhancement algorithm that is more conducive to human visual perception. The algorithm uses a lightweight Fully Convolutional Network (FCN), with NLPD as the similarity measure, and trains the network in a self-supervised manner by minimizing the NLPD between the enhanced image and the original scene radiance to achieve infrared image enhancement. The experimental results show that the infrared image enhancement method in this paper outperforms existing methods in terms of visual perception quality, and due to the use of a lightweight network, it is also the fastest enhancement method currently.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

AUTOSAR-Compatible Level-4 Virtual ECU for the Verification of the Target Binary for Cloud-Native Development 用于验证云原生开发目标二进制文件的 AUTOSAR 兼容 Level-4 虚拟 ECU

IF 2.9 3区工程技术

Electronics Pub Date : 2024-09-18 DOI: 10.3390/electronics13183704

Hyeongrae Kim, Junho Kwak, Jeonghun Cho

{"title":"AUTOSAR-Compatible Level-4 Virtual ECU for the Verification of the Target Binary for Cloud-Native Development","authors":"Hyeongrae Kim, Junho Kwak, Jeonghun Cho","doi":"10.3390/electronics13183704","DOIUrl":"https://doi.org/10.3390/electronics13183704","url":null,"abstract":"The rapid evolution of automotive software necessitates efficient and accurate development and verification processes. This study proposes a virtual electronic control unit (vECU) that allows for precise software testing without the need for hardware, thereby reducing developmental costs and enabling cloud-native development. The software was configured and built on a Hyundai Autoever AUTomotive Open System Architecture (AUTOSAR) classic platform, Mobilgene, and Renode was used for high-fidelity emulations. Custom peripherals in C# were implemented for the FlexTimer, system clock generator, and analog-to-digital converter to ensure the proper functionality of the vECU. Renode’s GNU debugger server function facilitates detailed software debugging in a cloud environment, further accelerating the developmental cycle. Additionally, automated testing was implemented using a vECU tester to enable the verification of the vECU. Performance evaluations demonstrated that the vECU’s execution order and timing of tasks and runnable entities closely matched those of the actual ECU. The vECU tester also enabled fast and accurate verification. These findings confirm the potential of the AUTOSAR-compatible Level-4 vECU to replace hardware in development processes. Future efforts will focus on extending capabilities to emulate a broader range of hardware components and complex system integration scenarios, supporting more diverse research and development efforts.","PeriodicalId":11646,"journal":{"name":"Electronics","volume":null,"pages":null},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Electronics最新文献