IEEE journal of radio frequency identification最新文献_第7页

Lens Antenna Design Tool Based on Generalized Superformula 基于广义超公式的透镜天线设计工具

IEEE journal of radio frequency identification Pub Date : 2024-03-02 DOI: 10.1109/JRFID.2024.3396333

Alberto Facchini;Francesco Paolo Chietera;Riccardo Colella;Luca Catarinucci;Pietro Bia;Luciano Mescia

{"title":"Lens Antenna Design Tool Based on Generalized Superformula","authors":"Alberto Facchini;Francesco Paolo Chietera;Riccardo Colella;Luca Catarinucci;Pietro Bia;Luciano Mescia","doi":"10.1109/JRFID.2024.3396333","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3396333","url":null,"abstract":"In this work, the design of a novel class of 3D dielectric lens antennas through the use of a lab-made electromagnetic tool is presented. The lens antenna is modeled using a generalized superformula allowing additional degree of freedom which can be exploited to obtain complex lens shapes with flat surface regions, steep sides, a non-rotational symmetry, or a modulated and aspherical surface profile. Thanks to the free parameters characterizing this formula, the lens geometry can be adjusted in a simple and analytical way. The electromagnetic tool is based on the geometrical optics and tube tracing approximations as well as the physical optics approach. In this way, the multiple wave reflections within the lens region as well as the far field outside the lens can be calculated. Moreover, an efficient synthesis procedure based on swarm intelligence has been developed and integrated in the numerical code. Thanks to this design tool it is possible to identify the lens parameters yielding the optimal antenna characteristic and a desired radiation patterns with low computational burden.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517938","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141308677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Secrecy Performance of Energy-Harvesting Backscatter Communication Network Under Different Tag Selection Schemes 不同标签选择方案下能量收集反向散射通信网络的保密性能

IEEE journal of radio frequency identification Pub Date : 2024-02-29 DOI: 10.1109/JRFID.2024.3371877

Yasin Khan;Aaqib Afzal;Ankit Dubey;Alok Saxena

引用次数: 0

Adaptive Multi-Task Learning for Multi-PAR in Real World 针对真实世界中多 PAR 的自适应多任务学习

IEEE journal of radio frequency identification Pub Date : 2024-02-29 DOI: 10.1109/JRFID.2024.3371881

Haoyun Sun;Hongwei Zhao;Weishan Zhang;Liang Xu;Hongqing Guan

{"title":"Adaptive Multi-Task Learning for Multi-PAR in Real World","authors":"Haoyun Sun;Hongwei Zhao;Weishan Zhang;Liang Xu;Hongqing Guan","doi":"10.1109/JRFID.2024.3371881","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3371881","url":null,"abstract":"Multi-pedestrian attribute recognition (Multi-PAR) is a vital task for smart city surveillance applications, which requires identifying various attributes of multiple pedestrians in a single image. However, most existing methods are limited by the complex backgrounds and the time-consuming pedestrian detection preprocessing work in real-world scenarios, and cannot achieve satisfactory accuracy and efficiency. In this paper, we present a novel end-to-end solution, named Adaptive Multi-Task Network (AMTN), which jointly performs multiple tasks and leverages an adaptive feature re-extraction (AFRE) module to optimize them. Specially, We integrate pedestrian detection into AMTN to perform PAR preprocessing, and incorporate a person re-identification (ReID) task branch to track pedestrians in video streams, thereby selecting the clearest video frames for analysis instead of every video frame to improve analysis efficiency and recognition accuracy. Moreover, we design a dynamic weight fitting loss (DWFL) function to prevent gradient explosions and balance tasks during training. We conduct extensive experiments to evaluate the accuracy and efficiency of our approach, and compare it with the state-of-the-art methods. The experimental results demonstrate that our method outperforms other state-of-the-art algorithms, achieving 1.5%-4.9% improvement in accuracy on Multi-PAR. The experiments also show that the AMTN can greatly improve the efficiency of preprocessing by saving the computation of feature extraction through basic features sharing. Compared with the state-of-the-art detection algorithm Yolov5s, it can improve the efficiency by 42%.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advanced RFID-Robot With Rotating Antennas for Smart Inventory in High-Density Shelving Systems 带旋转天线的先进 RFID 机器人，用于高密度货架系统的智能盘点

IEEE journal of radio frequency identification Pub Date : 2024-02-23 DOI: 10.1109/JRFID.2024.3369470

Andrea Motroni;Salvatore D’Avella;Alice Buffi;Paolo Tripicchio;Matteo Unetti;Glauco Cecchi;Paolo Nepa

引用次数: 0

Mitigation of Metal Body Proximity Effect in Magnetically Coupled HF RFID Systems 缓解磁耦合高频射频识别系统中的金属体接近效应

IEEE journal of radio frequency identification Pub Date : 2024-02-22 DOI: 10.1109/JRFID.2024.3368882

Somnath Mukherjee;Debidas Kundu;Ashis Khan

引用次数: 0

Multi-Class Road Target Detection Based on Multi-Gradient Flow Residual Structure 基于多梯度流残差结构的多类道路目标检测

IEEE journal of radio frequency identification Pub Date : 2024-02-21 DOI: 10.1109/JRFID.2024.3368226

Leilei Xie;Zheng Li;Fenghua Zhu

{"title":"Multi-Class Road Target Detection Based on Multi-Gradient Flow Residual Structure","authors":"Leilei Xie;Zheng Li;Fenghua Zhu","doi":"10.1109/JRFID.2024.3368226","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3368226","url":null,"abstract":"Aiming at the problem of false and missed detection due to the varied and dense target scale changes, the presence of occlusion, and insufficient light in the target detection task of complex road scenes for self-driving vehicles, an improved model YOLOv8-AUT based on YOLOv8 complex road target detection is proposed. Firstly, the MFR module is designed based on the multi-gradient flow residual structure of the attention mechanism, and the parallel gradient flow branches are added to the module to enrich the gradient flow of the model, so as to enhance the ability to extract the detailed information, and to improve the omission and misdetection of the small targets on the road. Secondly, the spatial pyramid network structure is improved using full-dimensional dynamic convolution to increase the sensory field of the model and improve the model’s ability to detect targets of different scales in complex backgrounds. Finally, the soft-NMS suppression algorithm is introduced to solve the problem of severe target leakage detection in obstacle-target dense regions. The experimental data show that on the BDD100K dataset, the improved algorithm improves the average accuracy mean by 7.7% compared with the original algorithm, mAP@0.5:0.9 by 5.7%, which proves that YOLOv8-AUT can better satisfy the demand for target detection in complex road scenarios of autonomous driving.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Thin Microwave Absorber Based on Laser-Induced Graphene Frequency Selective Surfaces 基于激光诱导石墨烯频率选择性表面的薄型微波吸收器

IEEE journal of radio frequency identification Pub Date : 2024-02-20 DOI: 10.1109/JRFID.2024.3368005

Yann Houeix;Francisco J. Romero;Francisco G. Ruiz;Diego P. Morales;Noel Rodriguez;Darine Kaddour

{"title":"Thin Microwave Absorber Based on Laser-Induced Graphene Frequency Selective Surfaces","authors":"Yann Houeix;Francisco J. Romero;Francisco G. Ruiz;Diego P. Morales;Noel Rodriguez;Darine Kaddour","doi":"10.1109/JRFID.2024.3368005","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3368005","url":null,"abstract":"This study presents a pioneering approach to fabricating single-layer Frequency Selective Surfaces (FSS) using Laser-Induced Graphene (LIG). The FSS structure proposed consists of periodic resistive patterns of LIG synthesized through a one-step laser photothermal process directly on the surface of a thin polyimide substrate. The structural and electrical properties of LIG were thoroughly investigated to develop an electrical model aiming at optimizing the design and absorbing properties. After that, a 12 mm thick LIG-FSS microwave absorber prototype was fabricated and tested under real conditions, demonstrating over 90% absorption in the frequency band from 1.69 to 2.91 GHz with a thickness of only 0.068 times the maximum wavelength \u0000<inline-formula> <tex-math>$(lambda _{mathrm{ max}})$ </tex-math></inline-formula>\u0000, demonstrating good agreement with the simulations and theoretical results. Additionally, we discuss the tunability of the frequency response of the absorber by adjusting accordingly the induced material’s properties. Finally, we also demonstrate the versatility of this approach for the fabrication of FSS structures based on alternative patterns. The findings presented in this work highlight the promising potential of sustainable microwave absorbers based on LIG-FSS structures.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10440440","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140880810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

UnstrPrompt: Large Language Model Prompt for Driving in Unstructured Scenarios UnstrPrompt：用于非结构化场景驾驶的大型语言模型提示

IEEE journal of radio frequency identification Pub Date : 2024-02-20 DOI: 10.1109/JRFID.2024.3367975

Yuchen Li;Luxi Li;Zizhang Wu;Zhenshan Bing;Zhe Xuanyuan;Alois Christian Knoll;Long Chen

{"title":"UnstrPrompt: Large Language Model Prompt for Driving in Unstructured Scenarios","authors":"Yuchen Li;Luxi Li;Zizhang Wu;Zhenshan Bing;Zhe Xuanyuan;Alois Christian Knoll;Long Chen","doi":"10.1109/JRFID.2024.3367975","DOIUrl":"https://doi.org/10.1109/JRFID.2024.3367975","url":null,"abstract":"The integration of language descriptions or prompts with Large Language Models (LLMs) into visual tasks is currently a focal point in the advancement of autonomous driving. This study has showcased notable advancements across various standard datasets. Nevertheless, the progress in integrating language prompts faces challenges in unstructured scenarios, primarily due to the limited availability of paired data. To address this challenge, we introduce a groundbreaking language prompt set called “UnstrPrompt.” This prompt set is derived from three prominent unstructured autonomous driving datasets: IDD, ORFD, and AutoMine, collectively comprising a total of 6K language descriptions. In response to the distinctive features of unstructured scenarios, we have developed a structured approach for prompt generation, encompassing three key components: scene, road, and instance. Additionally, we provide a detailed overview of the language generation process and the validation procedures. We conduct tests on segmentation tasks, and our experiments have demonstrated that text-image fusion can improve accuracy by more than 3% on unstructured data. Additionally, our description architecture outperforms the generic urban architecture by more than 0.1%. This work holds the potential to advance various aspects such as interaction and foundational models in this scenario.","PeriodicalId":73291,"journal":{"name":"IEEE journal of radio frequency identification","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Life Cycle Assessment of UHF and Chipless RFID 超高频和无芯片 RFID 生命周期评估

IEEE journal of radio frequency identification Pub Date : 2024-02-19 DOI: 10.1109/JRFID.2024.3366563

Le Quang Hieu Nguyen;Etienne Perret

引用次数: 0

A Practical Guide to Optimal Impedance Matching for UHF RFID Chip 超高频 RFID 芯片最佳阻抗匹配实用指南

IEEE journal of radio frequency identification Pub Date : 2024-02-19 DOI: 10.1109/JRFID.2024.3367452

Nicolas Barbot;Ionela Prodan;Pavel Nikitin

引用次数: 0