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arXiv 2021年

作者： Fan, Kun Zhao, Ran Cheng, Guang Shang Huang, Zhi Xiang Hu, Jun Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Chengdu611731 China

Conventional surface integral equation (SIE)-based characteristic mode formulation for the patch antenna structure with a finite substrate is susceptible to the spurious (nonphysical) modes due to the dielectric part. To avoid the contamination of spurious modes, we propose a novel generalized eigenvalue formulation based on the electric field integral equation coupled Poggio-Miller-Chang-Harrington-Wu-Tsai (EFIEPMCHWT) equation. In this formulation, the real and imaginary parts of the exterior integral operators are chosen to construct the finalized weighting matrices, to connect radiated power of the characteristic current. Compared with other SIE-based methods, this equation doesn't need additional post-processing since it can effectively avoid spurious modes. Numerical results compared with the volume-surface integral equation (VSIE) are investigated to validate the accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Microstrip antennas

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Transformer RGBT Tracking with Spatio-Temporal Multimodal Tokens

arXiv

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arXiv 2024年

作者： Sun, Dengdi Pan, Yajie Lu, Andong Li, Chenglong Luo, Bin The Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China The Anhui Provincial Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

Many RGBT tracking researches primarily focus on modal fusion design, while overlooking the effective handling of target appearance changes. While some approaches have introduced historical frames or fuse and replace initial templates to incorporate temporal information, they have the risk of disrupting the original target appearance and accumulating errors over time. To alleviate these limitations, we propose a novel Transformer RGBT tracking approach, which mixes spatio-temporal multimodal tokens from the static multimodal templates and multimodal search regions in Transformer to handle target appearance changes, for robust RGBT tracking. We introduce independent dynamic template tokens to interact with the search region, embedding temporal information to address appearance changes, while also retaining the involvement of the initial static template tokens in the joint feature extraction process to ensure the preservation of the original reliable target appearance information that prevent deviations from the target appearance caused by traditional temporal updates. We also use attention mechanisms to enhance the target features of multimodal template tokens by incorporating supplementary modal cues, and make the multimodal search region tokens interact with multimodal dynamic template tokens via attention mechanisms, which facilitates the conveyance of multimodal-enhanced target change information. Our module is inserted into the transformer backbone network and inherits joint feature extraction, search-template matching, and cross-modal interaction. Extensive experiments on three RGBT benchmark datasets show that the proposed approach maintains competitive performance compared to other state-of-the-art tracking algorithms while running at 39.1 FPS. Copyright © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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A correlation-breaking interleaving of polar codes in concatenated systems

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Science China(Information Sciences) 2021年第10期64卷 270-271页

作者： Ya MENG Liping LI Chuan ZHANG Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education of China Anhui University National Mobile Communications Research Laboratory Southeast University Purple Mountain Laboratories

Dear editor,Polar codes, along with a low complexity successive cancellation(SC) decoding, were discovered in [1] by Ar?kan. It is shown in [2] that the bit errors with the SC decoding are correlated. To improve the performance, other decoding techniques [3, 4] and concatenation schemes [5, 6] were studied. In this study, the theoretical aspects of the error correlation are investigated to improve the decoding performance of polar codes. This is the first attempt to utilize the error correlation to improve the performance of polar codes.

关键词： Information Systems and Communication Service

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Design of 0.8-3.7 GHz Broadband asymmetric multi-node directional coupler

Design of 0.8-3.7 GHz Broadband asymmetric multi-node direct...

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Ruikang Wang Bo Wu Meng Kong Jingyang Wang Yue Ma Xianliang Wu 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

ISBN: (纸本)9781665482271

In this paper, a 15 dB asymmetric broadband directional coupler for 4G and 5G communication is designed. The physical size of the coupler is $13\ \text{mm}\times 60\ \text{mm}$ . The dielectric constant is 4.4 and the thickness of single layer plate is 2 mm. The couplers operate in the 0.8-3.7 GHz band. The coupler has the advantages of bandwidth width, convenient processing and installation. ANSYS HFSS 2019 simulation results shows that in the 0.8-3.7 GHz band, the return loss (S 11 ) is more than 16.4 dB, the insertion loss (S 21 ) is from 0.14 dB to 1.18 dB, the coupling degree (S 31 ) is about 15 dB, and the isolation degree (S 41 ) is more than 29 dB. The method of multi-section coupling line cascade is adopted, to achieve the requirements of bandwidth width. The directivity of the coupler is increased by loading the branches to meet the design requirements of the 15 dB coupler.

关键词： Couplings Microwave technology Power transmission lines 5G mobile communication Simulation Millimeter wave technology Broadband communication

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VANER: Leveraging Large Language Model for Versatile and Adaptive Biomedical Named Entity Recognition 27

VANER: Leveraging Large Language Model for Versatile and Ada...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Bian, Junyi Zhai, Weiqi Huang, Xiaodi Zheng, Jiaxuan Zhu, Shanfeng School of Computer Science Fudan University Shanghai200433 China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China Ministry of Education Shanghai200433 China MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Shanghai200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai200433 China School of Computing and Mathematics Charles Sturt University AlburyNSW2640 Australia

ISBN: (纸本)9781643685489

The prevalent solution for BioNER involves using representation learning techniques combined with sequence ***, such methods are inherently task-specific, demonstrate poor generalizability, and often require a dedicated model for each *** leverage the versatile capabilities of recent large language models (LLMs), several approaches have explored generative techniques for entity ***, these approaches often fall short compared to previous sequence lab.ling *** this paper, we utilize the open-sourced LLM LLaMA2 as the backbone model, and design specific instructions to distinguish between different types of entities and *** combining the LLM's understanding of instructions with sequence lab.ling techniques, we train a model using a mix of datasets capable of extracting various types of *** that the backbone LLMs lacks specialized medical knowledge, we also integrate external entity knowledge bases and employ instruction tuning to enable the model to densely recognize curated *** parameter-efficient training model, VANER, significantly outperforms previous LLMs-based *** the first time, as an LLM-based model, VANER surpasses the majority of conventional state-of-the-art BioNER systems, achieving the highest F1 scores across three datasets. © 2024 The Authors.

关键词： lab.led data

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Molecule optimization via multi-objective evolutionary in implicit chemical space

arXiv

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arXiv 2022年

作者： Xia, Xin Su, Yansen Zheng, Chunhou Zeng, Xiangxiang The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China College of Computer Science and Electronic Engineering Hunan University China

Machine learning methods have been used to accelerate the molecule optimization process. However, efficient search for optimized molecules satisfying several properties with scarce lab.led data remains a challenge for machine learning molecule optimization. In this study, we propose MOMO, a multi-objective molecule optimization framework to address the challenge by combining learning of chemical knowledge with Pareto-based multi-objective evolutionary search. To learn chemistry, it employs a self-supervised codec to construct an implicit chemical space and acquire the continues representation of molecules. To explore the established chemical space, MOMO uses multiobjective evolution to comprehensively and efficiently search for similar molecules with multiple desirable properties. We demonstrate the high performance of MOMO on four multi-objective property and similarity optimization tasks, and illustrate the search capability of MOMO through case studies. Remarkably, our approach significantly outperforms previous approaches in optimizing three objectives simultaneously. The results show the optimization capability of MOMO, suggesting to improve the success rate of lead molecule optimization. Copyright © 2022, The Authors. All rights reserved.

关键词： Molecules

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AGMR-Net: Attention Guided Multiscale Recovery framework for stroke segmentation

arXiv

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arXiv 2022年

作者： Du, Xiuquan Ma, Kunpeng Song, Yuhui Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Anhui Hefei230601 China School of Computer Science and Technology Anhui University Anhui Hefei230601 China

Automatic and accurate lesion segmentation is critical for clinically estimating the lesion statuses of stroke diseases and developing appropriate diagnostic systems. Although existing methods have achieved remarkable results, further adoption of the models is hindered by: (1) inter-class indistinction, the normal brain tissue resembles the lesion in appearance. (2) intra-class inconsistency, large variability exists between different areas of the lesion. To solve these challenges in stroke segmentation, we propose a novel method, namely Attention Guided Multiscale Recovery framework (AGMR-Net) in this paper. Firstly, a coarse-grained patch attention module in the encoding is adopted to get a patch-based coarse-grained attention map in a multi-stage explicitly supervised way, enabling target spatial context saliency representation with a patch-based weighting technique that eliminates the effect of intra-class inconsistency. Secondly, to obtain a more detailed boundary partitioning to solve the challenge of the inter-class indistinction, a newly designed cross-dimensional feature fusion module is used to capture global contextual information to further guide the selective aggregation of 2D and 3D features, which can compensate for the lack of boundary learning capability of 2D convolution. Lastly, in the decoding stage, an innovative designed multi-scale deconvolution upsampling instead of linear interpolation enhances the recovery of target space and boundary information. The AGMR-Net is evaluated on the open dataset Anatomical Tracings of Lesions-After-Stroke (ATLAS), achieving the highest dice similarity coefficient (DSC) score of 0.594, Hausdorff distance of 27.005 mm, and average symmetry surface distance of 7.137 mm, which demonstrate that our proposed method outperforms other state-of-the-art methods and has great potential in the diagnosis of stroke. Copyright © 2022, The Authors. All rights reserved.

关键词： Recovery

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Research on solving time-dependent Schrodinger equation for higher-order FDTD based on spatial filtering

Research on solving time-dependent Schrodinger equation for ...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Wenjie Ding Guoda Xie Zhixiang Huang Education of Anhui Province. Anhui Province Key Laboratory of Target Recognition and Feature Extraction (Luan Anhui 237000 China) Ministry of Education. the Key Laboratory of Intelligent Computing and Signal Processing Hefei China Key Laboratory of Electromagnetic Environmental Sensing (Hefei 230601 China) Anhui Province Anhui University Anhui university Hefei China

Combining the spatial filtering (SF) technique with FDTD(2, q) method (2 and q denote the temporal differential order and spatial differential order, respectively), a novel SF-FDTD(2, q) method with more relaxed Courant-Friedrichs-Lewy (CFL) condition is proposed and used for solving 3D time-dependent Schrödinger equation. Then, the correctness of the SF-FDTD(2, $q$ ) method is validated by calculating eigenfrequencies of the 3D quantum well model.

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Transient Electro-thermal and Bandgap Narrowing Analysis of the bipolar transistor

Transient Electro-thermal and Bandgap Narrowing Analysis of ...

引用

International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Hui Xiao Xingang Ren Yeqiang Yan Zhixiang Huang Xianliang Wu Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan China Engineering Technology Research Center of Specific Power Devices with Novel Semiconductor Materials Chizhou Anhui Province China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

Given the bandgap narrowing (BGN) effect caused by heavy doping of the bipolar transistor and the self-heating effect (SHE) in the practical work environment, a transient electro-thermal and bandgap narrowing model is proposed in this paper, which is based on the Slotboom model and the modification of the drift-diffusion equation based on semiconductor equations and the heat conduction equation. The transient characteristics of the bipolar transistor in amplification mode are simulated using the differential method, and the results show that the terminal current of the bipolar transistor decreases after considering the SHE and the BGN effect. The model developed and the results obtained in this work can provide some reference significance for the optimization of the amplification characteristics of the bipolar transistor.

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Efficient CDI-FDTD Method for Modelling Graphene-Based Structures

Efficient CDI-FDTD Method for Modelling Graphene-Based Struc...

引用

International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jiale Liu Guoda Xie Zhixiang Huang Education of Anhui Province. Anhui Province Key Laboratory of Target Recognition and Feature Extraction Luan Anhui China Ministry of Education. the Key Laboratory of Intelligent Computing and Signal Processing Hefei China Anhui Province Anhui University. Key Laboratory of Electromagnetic Environmental Sensing Hefei China Anhui university Hefei China

This paper presents a novel approach for calculating graphene-based structures in the complying divergence implicit finite-difference time-domain (CDI-FDTD) method. To begin, the differential iteration formula of graphene structure in the CDI-FDTD method is derived utilizing the auxiliary-differential-equation (ADE) method. Next, the transmission characteristics of an infinite graphene sheet in an open space are investigated by conducting simulation analyses within the CDI-FDTD framework, considering various magnetostatic or electrostatic biases. Finally, the simulation results were compared with analytical solutions and the results obtained from traditional FDTD methods, confirming the unconditional stability and reliability of the proposed method.

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