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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Yunshuai Gao Yingsong Li Luyu Zhao Zhixiang Huang Eugene Sinkevich Vladimir Mordachev Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China EMC R and D laboratory Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

A novel miniaturized and low-profile FSS is presented for electromagnetic shielding, which consists of a layer of metal patch and a layer of dielectric substrate, resulting in a small unit and low profile with a thickness of only $0.0054\lambda$ , where $\lambda$ corresponds to the resonant frequency of the first operating band. Additionally, the folded structure not only reduces the unit size but also creates two stop bands, corresponding to around 7.7GHz and 16.7GHz. There is a low-insertion passband between the stopbands, which has a bandwdith of 2G Hz wide. The created FSS allows for signal transmission within the passband while it suppresses unrelated signals incident from both sides.

关键词： Wireless communication Conferences Dielectric substrates Resonant frequency Metals Interference Electromagnetic compatibility

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Research and Implementation of Chinese Resume Named Entity Recognition Method Based on BLDC 4

Research and Implementation of Chinese Resume Named Entity R...

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4th International Conference on Image processing and intelligent Control, IPIC 2024

作者： Chen, Min Wei, Bin Yu, Hongzhi Wan, Fucheng Feng, Yulin Lu, Baoqing Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Key Laboratory of Minzu Languages and Cultures Intelligent Information Processing Northwest Minzu University Gansu Province Gansu Lanzhou730000 China Lanzhou Technology and Business College Lanzhou China

ISBN: (纸本)9781510682313

Aiming at the semantic complexity and the difficulty of capturing long-distance dependencies in the task of named entity recognition in Chinese resume text, a BLDC (BERT-BiLSTM-Dense-CRF)-based named entity recognition method for Chinese resumes is investigated. The model first uses the pre-trained BERT-Base-Chinese model to obtain the semantic information of the text, then learns the contextual information of the sequence through the BiLSTM layer, followed by mapping the output of BiLSTM to the label space through the Dense layer, and finally uses the CRF layer to consider the dependencies between the labels for sequence annotation. Experimental results on public datasets show that the method outperforms other models in terms of precision, recall, and F1 value, and effectively improves the performance of named entity recognition in Chinese resume text. © 2024 SPIE.

关键词： Semantics

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An Optimization Method Based on Deep Learning for Electromagnetic Inverse Scattering Problems

An Optimization Method Based on Deep Learning for Electromag...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Wangchao Hu Guoda Xie Jinpeng Dai Guilin Hou Xiang Li Zhixiang Huang The Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China Education of Anhui Province Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China Key Laboratory of Electromagnetic Environmental Sensing Anhui Province Anhui University Hefei China Anhui University Hefei China

ISBN: (数字)9798350355581

ISBN: (纸本)9798350355598

In this paper, a deep learning optimization method combining U-net model and cycle generative adversarial network (Cycle-GAN) is proposed to efficiently solve the electromagnetic inverse scattering (EMIS) problems. Firstly, a U-net model is used to obtain a rough preliminary reconstruction. Through down-sampling and up-sampling processes, the basic features of the object are extracted and reconstructed from the measured scattered field, providing a coarse dielectric parameter distribution. Then, a Cycle-GAN model further refines the output of the U-net. The Cycle-GAN model, through its adversarial training mechanism involving a generator and a discriminator, enhances the details of the preliminary reconstruction, resulting in a finely detailed dielectric parameter distribution his method improves the problem of rough results obtained by using U-net method alone, and can effectively solve and optimize EMIS problems.

关键词： Deep learning Inverse problems Computational modeling Electromagnetic interference Electromagnetic scattering Optimization methods Feature extraction Dielectric measurement Electromagnetics Image reconstruction

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A Microwave Sensor for Detection of Water Adulteration and Spoilage in Milk Based on Split-Ring Resonator

A Microwave Sensor for Detection of Water Adulteration and S...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Shuying Ding Yingsong Li Zhixiang Huang Eugene Sinkevich Vladimir Mordachev Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China EMC R and D Laboratory Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

The paper introduces a microwave sensor based on split-ring resonators (SRR) for detecting the moisture content and spoilage of milk. This sensor is characterized by its simple structure and high sensitivity, utilizing SRR to enhance the local electric field intensity of the electromagnetic field. By measuring the transmission characteristics of microwave signals, it can accurately detect the moisture content and spoilage of milk samples. The sensor operates at a frequency of 6 GHz and has dimensions of 30×25×1.6 mm³. The study establishes the relationship between resonance frequency and water content in milk through simulated data, which provides an effective method for monitoring milk quality and holds potential applications in the food industry, contributing significantly to ensuring food safety.

关键词： Microwave measurement Microwave integrated circuits Dairy products Sensitivity Resonant frequency Moisture Microwave sensors

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Few-Shot Object Detection Based on Generalized Features 2

Few-Shot Object Detection Based on Generalized Features

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2nd International Conference on Artificial Intelligence and intelligent Information processing, AIIIP 2023

作者： Chen, Qiuqin Ke, Xiao College of Computer and Data Science Fuzhou University Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou350116 China Key Laboratory of Spatial Data Mining & Information Sharing Ministry of Education Fuzhou Fuzhou350003 China

ISBN: (纸本)9798350371451

Few-shot object detection aims to rapidly detect novel classes of objects using a minimal number of annotated instances. Compared to methods such as meta-learning, few-shot object detection based on transfer learning can achieve better performance. However, when training on base-class datasets, the model gradually improves its detection performance on base classes but does not enhance its generalization. A base-class model lacking generalization tends to result in lower detection performance for novel classes during fine-tuning. To address the aforementioned issues, this paper tackles the problem from two aspects: firstly, we introduce the Confusion-Dropblock Module (CDM) to perturb the model's features, thus enhancing feature generalization. Secondly, we incorporate Deformable Convolution Modules to mitigate the impact of object shapes and sizes on detection performance, thereby improving overall detection performance. Experimental results on the COCO dataset demonstrate the effectiveness of the proposed algorithm, outperforming the compared methods. © 2023 IEEE.

关键词： Object detection

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Enhanced Breakdown Voltage of p-GaN HEMT with a Lateral Gradient in Barrier Layer Component

Enhanced Breakdown Voltage of p-GaN HEMT with a Lateral Grad...

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IEEE International Workshop on Radio-Frequency Integration Technology (RFIT)

作者： Wei Zhi Xingang Ren Hui Wang Shubin Zhao Gang Wang Shuping He Zhixiang Huang Xianliang Wu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China Anhui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei China

ISBN: (数字)9798331541095

ISBN: (纸本)9798331541101

In this paper, an optimized enhanced-mode p-GaN high electron mobility transistor (p-GaN HEMT) is proposed, in which the barrier layer is set into a composite structure with a lateral gradient of Aluminum component (LGC) from the drain edge under the gate towards both source and drain, respectively. By leveraging the polarization effects from different heterojunctions, a two-dimensional electron gas (2DEG) with gradually changing density is formed laterally in the channel layer, which more precisely modulates the electric field distribution in the gate-drain region, enhances the voltage resistance of it, and reduces leakage current, thereby enhancing the breakdown voltage of the device and improving the output performance. The breakdown voltage of the proposed optimized LGC-HEMT under simulation is 716.73V, which is 13.1 % higher than that of the conventional p-GaN HEMT (633.64V), while the specific on-resistance $(\mathrm{R}_{\mathrm{o}\mathrm{n},\mathrm{s}\mathrm{p}})$ is only 1.34 $m\Omega\cdot cm^{2}$ , and the Baliga's figure of merit (BFOM) changes from 216.42 to 382.68 $MW/cm^2$ , which is 76.82% higher, hinting at the promising potential of the proposed HEMT.

关键词： Resistance Radio frequency Performance evaluation Breakdown voltage HEMTs Logic gates Impact ionization Leakage currents MODFETs Electric fields

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An ultra-wideband high-isolation dual-port MIMO antenna design

An ultra-wideband high-isolation dual-port MIMO antenna desi...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Shuangqing Cao Minquan Li Zhenfa Zi Zhonghui Li Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China School of Physics and Materials Engineering Hefei Normal University Hefei China

ISBN: (数字)9798350355581

ISBN: (纸本)9798350355598

In this paper, an antenna for ultra-wideband multiple-input and multiple-output (UWB-MIMO) is designed. The design comprises two hexagonal monopole antennas. In order to achieve ultra-wideband characteristics and mitigate the coupling, a stepped microstrip line structure for impedance matching and T-shaped defective ground structure are employed, which optimizes the broadband characteristics and achieves high isolation characteristics. The antenna achieves a wide impedance bandwidth of 3.5 GHz to 13.9 GHz (relative bandwidth of 119%). Furthermore, the isolation between the two feed ports of the antenna exceeds 18 dB, the envelope correlation coefficient (ECC) is less than 0.012, and it exhibits favorable radiation characteristics.

关键词： Correlation coefficient Time-frequency analysis Impedance matching Bandwidth Microstrip antennas Ultra wideband antennas Envelope detectors Impedance Microstrip Gain

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An Empirical Study on Neural Networks Pruning: Trimming for Reducing Memory or Workload

An Empirical Study on Neural Networks Pruning: Trimming for ...

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Data-driven Optimization of Complex Systems (DOCS), International Conference on

作者： Kaiwen Xiao Xiaodong Cai Ke Xu School of Artificial Intelligence Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei China

Most of existing studies on neural network pruning only consider memory-based pruning strategies. However pruning for computational workload is often more important in hardware deployments due to a greater focus on model computation reductions. In addition, most pruning schemes restore model accuracy during pruning at the expense of adding hyperparameters, extending training time and training complexity. This work proposes a statistical-based globally soft iterative pruning scheme. With little extra calculation, an extremely sparse model can be obtained without additional hyperparameters and extended training time. Moreover, this work proposes the concept of computational intensity to balance model memory and computational workload during pruning. Focusing on memory orientated pruning, we can achieve $\mathbf{303}\times, \mathbf{100}\times$ and $\mathbf{25}\times$ parameter compression on LeNet-5 (MNIST), VGG (CIFAR-10) and AlexNet (ImageNet) models, respectively. In particular, combined with cluster quantization, the LeNet-5 model parameters can be compressed to $\mathbf{3232}\times$ . Focusing on workload orientated pruning, we can reduce the computation by $\mathbf{7}.\mathbf{6}\times$ on the AlexNet model, without accuracy loss, significantly higher than prior work. In addition, in order to verify the versatility of the pruning method, we also migrate the pruning task to the object detection and implement $\mathbf{10}\times$ parameter compression and $\mathbf{2}.\mathbf{8}\times$ computation compression for YOLOv2 with reduced mAP within 1%.

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Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

arXiv

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arXiv 2023年

作者： Yang, Shangshang Yu, Xiaoshan Tian, Ye Yan, Xueming Ma, Haiping Zhang, Xingyi Anhui University China Guangdong University of Foreign Studies China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education China

Transformer has achieved excellent performance in the knowledge tracing (KT) task, but they are criticized for the manually selected input features for fusion and the defect of single global context modelling to directly capture students’ forgetting behavior in KT, when the related records are distant from the current record in terms of time. To address the issues, this paper first considers adding convolution operations to the Transformer to enhance its local context modelling ability used for students’ forgetting behavior, then proposes an evolutionary neural architecture search approach to automate the input feature selection and automatically determine where to apply which operation for achieving the balancing of the local/global context modelling. In the search space design, the original global path containing the attention module in Transformer is replaced with the sum of a global path and a local path that could contain different convolutions, and the selection of input features is also considered. To search the best architecture, we employ an effective evolutionary algorithm to explore the search space and also suggest a search space reduction strategy to accelerate the convergence of the algorithm. Experimental results on the two largest and most challenging education.datasets demonstrate the effectiveness of the architecture found by the proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolution

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A Dual-passbands FSS with Wide Angular Stability and High Polarization Stability for 5G and EMC Pulse Shielding

A Dual-passbands FSS with Wide Angular Stability and High Po...

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International Workshop on Antenna Technology: Small Antennas and Novel Metamaterials, iWAT

作者： Yunshuai Gao Yingsong Li Luyu Zhao Zhixiang Huang Eugene Sinkevich Vladimir Mordachev Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China EMC R&D Laboratory Belarusian State University of Informatics and Radioelectronics Minsk Belarus

ISBN: (数字)9798350314755

ISBN: (纸本)9798350314762

An excellent frequency selective surface (FSS) with capacitance loading and multi-layer structure is proposed, primarily for application in the sub-6 and shielding. The proposed FSS has two different operational passbands to cover the frequencies located at 3.68 GHz and 5.85 GHz, respectively, which is also a multi-layered unit consisting of three metal layers and two dielectric layers. The unit size is 0.125λ, and the unit profile is 0.075λ, where λ corresponds to the resonance frequency of the first operating band. By adjusting the structural dimensions and parameters, the operating bands can be well-tuned. Simulation results demonstrate favorable polarization stability and angular stability, making it good for pulse shielding.

关键词： Frequency selective surfaces Simulation Capacitors Loading Resonant frequency Metals Interference

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