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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Manni Chen Kwok L. Chung Zhining Huang Jiating Wen Yingsong Li School of Computer Science and Engineering Huizhou University Guangdong China Glorious Sun Guangdong School of Fashion Huizhou University Guangdong China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

This paper presents a hybrid method for determination of continuous dielectric properties of clothing materials. The dielectric constant and loss tangent of three types of materials are firstly investigated using open-ended coaxial probe from 0.5 to 20 GHz. The average measured values are input into the CST simulation of two CPW lines to obtain the two-port S-parameters. Finally, more reasonable yet reliable results are obtained by using two retrieval algorithms (TRACE and ABCD) for validation and comparative purposes.

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Relational-Branchformer: Novel Framework for Audio-Visual Speech Recognition

SSRN

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SSRN 2023年

作者： Xiao, Yewei Liu, Xuanming Zhu, Aosu Huang, Jian School of Information Engineering Xiangtan University Xiangtan411105 China Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan University Xiangtan411105 China

This study embraced the state-of-the-art Branchformer series architecture within the realm of automatic speech recognition, supplanting the widely utilized Conformer architecture. This substitution offers an innovative remedy tailored to audio-visual speech recognition tasks. Building upon the Branchformer architecture, enhancements were made culminating in the proposal of the Relational-Branchformer (R-Branchformer). The convolutional attention relation module was innovatively incorporated to augment the connectivity between the local and global branches by meticulously considering their interrelations and interplays. Consequently, this module facilitates the mutual embedding of local and global contextual information, ultimately leading to a substantial enhancement in model performance. Our model was grounded in the utilization of the connectionist temporal classification (CTC) loss, wherein we incorporated intermediate CTC losses between blocks. Moreover,through the reference and enhancement of the gated interlayer collaboration module, which superseded the inter CTC module, we effectively relaxed the conditional independence assumption intrinsic to the CTC model. As a consequence, this augmentation markedly bolstered the overall performance of our model. Furthermore, we proposed the audio-visual output enhancement module, which adeptly assimilates information from both audio and visual modalities to enrich the representation of audio-visual information. Consequently, the R-Branchformer model achieved remarkable word error rates of 1.7% and 1.5% on the LRS2 and LRS3 test sets, respectively, exemplifying its state-of-the-art performance in audio-visual speech recognition tasks. © 2023, The Authors. All rights reserved.

关键词： Architecture

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Robust DOA Estimation in RIS-Assisted MISO Systems

Robust DOA Estimation in RIS-Assisted MISO Systems

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Canping Yu Wudang Xiao Yingsong Li Dingcheng Zou Nikola Zlatanov Rodrigo C. de Lamare Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Innopolis Russia Centre for Telecommunications Research (CETUC) Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Gávea Brazil

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

Reconfigurable intelligent Surfaces (RIS) are recognized for their ability to actively control signal propagation, presenting a wide array of applications in 5G and the forthcoming 6G networks. In this paper, we design a RIS-assisted multi-input single-output (MISO) model and propose a corresponding direction of arrival (DOA) estimation algorithm. The proposed DOA estimation algorithm leverages the non-convex Ekblom norm to serve as the error criterion, ensuring robustness against impulsive noises, while the smoothed L1 norm is implemented as the regularization constraint to further enhance the performance of the algorithm. Distinct from prior research, the system under consideration operates with a single receive antenna, facilitating DOA estimation through the adjustment of RIS reflection coefficients, thereby markedly reducing system hardware costs. Moreover, we devise an alternating minimization strategy to obtain the optimal solution to the problem. A series of simulation results indicate that the proposed algorithm surpasses existing methods in terms of accuracy and robustness.

关键词： Wireless communication Direction-of-arrival estimation Accuracy Simulation Noise Estimation Reconfigurable intelligent surfaces

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High Common-Mode Rejection Differential Filter Based on Coupled Lines

High Common-Mode Rejection Differential Filter Based on Coup...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Zhen Liu Haoran Zhu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei China Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

In this paper, a differential bandpass filter (BPF) based on enhanced coupling line structure has been suggested in this study. Two out-of-band transmission zeros are added to the differential mode by loading the coupling line at the output terminal, which raises the rectangular coefficient of the filter. Two common mode transmission zeros in the passband are additionally provided by the open/short stub that is already loaded at the output port. To accommodate the demands of various filter performances, the location of the transmission zeros can be modified by altering the values of the coupling lines' and stubs' impedances. Finally, the passband common mode suppression might be as high as 40 dB.

关键词： Band-pass filters Couplings Radio frequency Conferences Loading Microwave circuits Filtering theory

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Relational-Branchformer：一种新的视听语音识别框架

SSRN

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SSRN 2023年

作者： Xiao, Yewei Liu, Xuanming Zhu, Aosu Huang, Jian School of Information Engineering Xiangtan University Xiangtan411105 China Key Laboratory of Intelligent Computing &Information Processing Ministry of Education Xiangtan University Xiangtan411105 China

This study adopts the state-of-the-art Branchformer series architecture in the field of automatic speech recognition (ASR) as a replacement for the previously popular Conformer architecture, providing a novel solution for audio-visual speech recognition tasks. Building upon this foundation, we improve the Branchformer architecture and propose the R-Branchformer (Relational-Branchformer) architecture. The introduction of the CARM (Convolutional Attention Relation Module)enhances the connectivity between the local and global branches by considering their relationships and interactions, facilitating mutual embedding of local and global contextual information, ultimately boosting model performance. Our model is based on the Connectionist Temporal Classification (CTC) loss, and we incorporate intermediate CTC losses between blocks. Moreover, by referencing and improving the GIC (Gated Interlayer Collaboration) module to replace the Inter CTC module, we further relax the conditional independence assumption of the CTC model, resulting in enhanced model performance. Furthermore, we propose the Audio-Visual Output Enhancement (AVOE) module, which effectively assimilates information from both audio and visual modalities to enrich the representation of audio-visual information. As a result, our R-Branchformer model achieves remarkable Word Error Rates (WERs) of 1.7% and 1.5% on the LRS2 and LRS3 test sets, respectively, showcasing its state-of-the-art performance in audio-visual speech recognition tasks. © 2023, The Authors. All rights reserved.

关键词： Architecture

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A further study on the mass formula for linear codes with prescribed hull dimension

arXiv

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arXiv 2024年

作者： Li, Shitao Shi, Minjia Li, Yang Ling, San Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Mathematical Sciences Anhui University Hefei230601 China School of Mathematics Hefei University of Technology Hefei230601 China School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore

Finding a mass formula for a given class of linear codes is a fundamental problem in combinatorics and coding theory. In this paper, we consider the action of the unitary (resp. symplectic) group on the set of all Hermitian (resp. symplectic) linear complementary dual (LCD) codes, prove that all Hermitian (resp. symplectic) LCD codes are on a unique orbit under this action, and determine the formula for the size of the orbit. Based on this, we develop a general technique to obtain a closed mass formula for linear codes with prescribed Hermitian (resp. symplectic) hull dimension, and further obtain some asymptotic results. Copyright © 2024, The Authors. All rights reserved.

关键词： Hulls (ship)

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A Multimodal Knowledge Representation Method for Fake News Detection

A Multimodal Knowledge Representation Method for Fake News D...

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Computer, Control and Robotics (ICCCR), International Conference on

作者： Fanhao Zeng Jiaxin Yao Yijie Xu Yanhua Liu Fujian Key Laboratory of Network Computing and Intelligent Information Processing College of Computer and Data Science Fuzhou University Engineering Research Center of Big Data Intelligence Ministry of Education (Fuzhou University) Fuzhou China

ISBN: (数字)9798350373141

ISBN: (纸本)9798350373158

To address the key challenge encountered in fake news detection, i.e., multimodal data is difficult to be effectively semantically represented due to its intrinsic heterogeneity, this paper proposes a multimodal knowledge representation method for fake news detection. First, visual feature extraction is performed for fake news image data, the relevant images are sliced into multiple blocks, and then visual modal features are obtained by linear projection layer mapping. This simplifies the feature extraction process and reduces the computational cost, which helps to improve the fake news recognition performance. Second, to meet the actual fake news detection needs, a long text representation method based on topic words is investigated for the text data in fake news. Finally, the multimodal representation of the same fake news data is optimized by establishing a connection between two different modalities, visual and text, and inputting it into a BiLSTM-Attention based network to achieve the fusion of multimodal features. The experiment selects the same fake news data of EANN model and uses four classical classification methods to verify the effect of knowledge representation and compare it with the fusion model ViLT which is not optimized for long text. The experiment proves that the accuracy rate of fake news detection using the multimodal representation proposed in this paper is improved by 7.4% compared to the EANN model, and by 9.3% compared to the ViLT representation.

关键词： Digital control Visualization Accuracy Knowledge representation Machine learning Feature extraction Data models

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A Metasurface-Based Wideband High Isolation Circularly Polarized Antenna For 5G MIMO Millimeter-Wave Systems

A Metasurface-Based Wideband High Isolation Circularly Polar...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Hui Zhu Haoran Zhu Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei China Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

A wideband high isolation circularly polarized antenna for 5G MIMO millimeter-wave systems is presented in this paper. The presented antenna exhibits wideband characteristics due to the resonance of surface waves along the metasurface. The circularly polarized preliminary bandwidth is achieved by truncated corner patches when the truncation can be adjusted to implement the phase and amplitude values of the two quadrature modes. The port isolation is improved by the resonance of double-layer microstrip lines in the frequency. The size of the antenna is 17.8×17.8×1.02 mm 3 , the impedance bandwidth is 30.4% (23.29-31.66 GHz) and the 3-dB axial ratio bandwidth is 20.5% (24.47-30.12 GHz). In addition, the port isolation of the presented antenna is higher than 25 dB, and the peak gain is 8.4 dB. Therefore, the given antenna has the advantages of wideband, circularly polarized and high isolation.

关键词： Microwave antennas Surface impedance 5G mobile communication Surface waves Metasurfaces Broadband antennas Impedance

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Lifetime Prediction of Topcon Modules Based on Accelerated Damp Heat Life Tests

SSRN

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SSRN 2025年

作者： Ren, Xingang Duan, Junwei Yang, Lixia Xu, Tao Yu, Yuanjie Chen, Zhiliang Lv, Ruirui Ye, Feihong Wang, Gang Ahmed, Rida Jiang, Hao Yang, Lixia Huang, Zhixiang Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei230601 China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230601 China CSI Cells Co. Ltd. Suzhou215129 China Anhui University of Chinese Medicine China Hong Kong Polytechnic University Hong Kong

Tunnel Oxide Passivation Contacts (TOPCon) solar cells have achieved high efficiency and become mainstream product in the global photovoltaic (PV) market. However, their long-term reliability, especially under high-temperature and high-humidity conditions, lacks sufficient field validation, and there is a lack of lifetime prediction models for TOPCon modules. To address this, we developed a robust accelerated aging model by integrating an improved Peck model with a sigmoidal degradation function, incorporating internal humidity and temperature as critical factors. The model employs a particle swarm optimization (PSO) algorithm to calibrate activation energy and humidity sensitivity parameters, enabling precise degradation trajectory simulation. Validated through a "fitting + testing" framework, the model achieves high accuracy (RMSE = 0.7%) in predicting power degradation under Damp Heat (DH), Highly Accelerated Stress Test (HAST), and modified Pressure Cooker Test (mPCT) conditions. Accelerated aging tests reveal that DH-induced degradation primarily reduces fill factor (FF) due to finger corrosion, with minimal impact on Voc and Isc. Experimental validation using a non-commercial corrosion-sensitive BOM combination shows that polyolefin elastomer (POE)-encapsulated modules exhibit superior corrosion resistance, projecting a service lifetime 23 years longer than EVA/EVA encapsulation in high-humidity regions like Hainan. This work bridges the gap in TOPCon module lifetime prediction under extreme environments, offering actionable insights for optimizing encapsulation materials and enhancing reliability. The model provides a scalable framework for evaluating module performance under site-specific climatic conditions, accelerating the development of durable PV technologies. © 2025, The Authors. All rights reserved.

关键词： Corrosion resistance

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Multi-Object Localization and Irrelevant-Semantic Separation for Nuclei Segmentation in Histopathology Images 48

Multi-Object Localization and Irrelevant-Semantic Separation...

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48th IEEE International Conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Tang, Ya Ye, Xiongjun Li, Xuanya Chen, Zhineng Xiangtan University Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan411105 China Chinese Academy of Medical Sciences Peking Union Medical College National Cancer Center Cancer Hospital Beijing100021 China Baidu Inc. Beijing100085 China Fudan University School of Computer Science Shanghai200438 China

ISBN: (纸本)9781728163277

Automated segmentation of nuclei in histopathology images is critical for cancer diagnosis and prognosis. Due to the high variability of nuclei morphology, numerous nuclei overlapping, and the wide existence of nuclei clusters, this task still remains challenging. In this paper, we propose an effective nuclei segmentation method for histopathology images based on a novel neural network for multi-object localization and irrelevant-semantic separation (MI-Net), which includes a multi-object localization module (MOLM), a deep boundary awareness module (DBAM), and an irrelevant semantic separation module (ISSM). Specifically, the MOLM is used to calibrate features to capture more comprehensive information about the location of nuclei. It alleviates the problem of cell adhesion in histopathology images. The DBAM is intended to extract boundary information and solve the blurred boundary problem effectively. The ISSM is used to separate foreground features from background features and effectively address the problem of complex backgrounds in histopathology images. It also solves the low contrast problem between the target objects and the background. We evaluate MI-Net on the famous MoNuSeg dataset and compare it with ten state-of-the-art methods. MI-Net surpasses the best-performed method by margins from 1.12% to 2.29% over standard evaluation metrics, showing its effectiveness on nuclei segmentation. © 2023 IEEE.

关键词： Semantics

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