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

作者： Sipei Min Canping Yu Liping Li Yingsong Li Nikola Zlatanov Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Russia

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

This paper aims to investigate the ability of reconfigurable intelligent surfaces (RIS) damaged in multi-user environments to eliminate interference. Our research found that even if the RIS is damaged, interference can still be eliminated in the absence of a direct path and when the number of RIS is sufficient. In order to solve interference cancellation, we adopted the alternating projection algorithm, which ensures local convergence and good convergence speed.

关键词： Base stations Interference cancellation Reconfigurable intelligent surfaces Information and communication technology Projection algorithms Convergence

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Pattern Reconfigurable MIMO Antenna Based on Characteristic Mode Theory 4

Pattern Reconfigurable MIMO Antenna Based on Characteristic ...

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Tian, Minmin Cheng, G.S. Sun, Y.T. Huang, Z.X. Auhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

ISBN: (纸本)9781733509619

A pattern reconfigurable dual-port multiple-input multiple-output (MIMO) antenna system utilizing Characteristic mode theory is proposed at 2.45GHz. By using the selective incentives of four characteristic modes, six pairs of balanced inductive exciter (BIEs) and the antenna are integrated to realize the selective incentives of the four patterns. In the feeder network, by changing the state of the PIN diode, the two ports realize selective incentive to obtain four working states. The test results show that the pattern reconfiguration technique is reliable and can be used in other types of structures. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： MIMO systems

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A Simple Broadband Slotted Circularly Polarization Antenna

A Simple Broadband Slotted Circularly Polarization Antenna

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2023 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2023

作者： Wang, Lihua Li, Yingsong Huang, Zhixiang Loh, Tian Hong Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China National Physical Laboratory Electromagnetic and Eletrochemical Technologies Department Middlesex United Kingdom

ISBN: (纸本)9798350336740

A simple broadband slotted circularly-polarized (CP) antenna (SBS-CP) is presented, which mainly consists of a ground structure with a modified slot and an asymmetric feeding structure. The two structures can give different CP characteristics in low and high frequencies. By etching rectangular slots in the ground structure, the coupling effect between feeding and ground structure will be improved and the bandwidth will be broadened. By modeling and optimizing the antenna, the proposed antenna impedance bandwidth (IBW) and axial ratio bandwidth (ARBW) are 113% (2.08~7.46 GHz) and 97% (2.5~7.24 GHz), respectively. © 2023 IEEE.

关键词： Slot antennas

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A Novel Compact On-Chip Millimeter-Wave Band-Pass Filter with GaAs pHEMT Technology 13

A Novel Compact On-Chip Millimeter-Wave Band-Pass Filter wit...

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13th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2021

作者： Wang, Wen-Tao Zhu, Hao-Ran Sun, Yu-Fa Huang, Zhi-Xiang Wu, Xian-Liang Anhui University Key Laboratory Of Intelligent Computing And Signal Processing Ministry Of Education Hefei230039 China

ISBN: (纸本)9781665434379

In this paper, a compact and high selectivity millimeter wave on-chip band-pass filter using GaAs pHEMT technology is proposed. A compact lumped element unit, which consists of a series LC resonator and an extra capacitor, is used to produce a transmission zero near the pass-band without occupying much area. The proposed filter consists two of the proposed resonators. An additional series resonator is grounded to produce a transmission zero. The area of the proposed filter is only 0.816×0.607mm2. The presented filter is worked on 25.5 GHz, the 3-dB bandwidth is 21.5 GHz to 29.5GHz. The insertion loss is around 1.1dB, and the return loss is better than 17dB. © 2021 IEEE.

关键词： Bandpass filters

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A miniaturized double-sided UWB-MIMO antenna with four-notched band

A miniaturized double-sided UWB-MIMO antenna with four-notch...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Qitao Chen Yufa Sun Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University HeFei China

A $\boldsymbol{40}\times\boldsymbol{40}\times \boldsymbol{1.6}\mathbf{mm}^{3}$ ultra-wideband MIMO antenna is proposed in this paper. The antenna realizes four-notched band characteristics by embedding different types of slits in the radiating element. The antenna has good UWB performance, with four-band rejection to avoid interference caused by four narrow frequency bands WiMAX(3.3-3.8GHz), WLAN(S.1-S.8GHz), INSAT(6.7-7.3GHz) and ITV 8GHz (8.13-8.38GHz). It achieves better than - 15dB of isolation, and impedance bandwidth from 3.06-15.5GHz.

关键词： Antenna measurements Bandwidth Interference Size measurement Ultra wideband antennas Impedance Antennas

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Uncertainty-aware Superpoint Graph Transformer for Weakly Supervised 3D Semantic Segmentation

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IEEE Transactions on Fuzzy Systems 2025年第6期33卷 1899-1912页

作者： Fan, Yan Wang, Yu Zhu, Pengfei Hui, Le Xie, Jin Hu, Qinghua Tianjin University College of Intelligence and Computing Tianjin300350 China Ministry of Education of the People's Republic of China Engineering Research Center of City Intelligence and Digital Governance China Haihe Laboratory of Itai Tianjin China Northwestern Polytechnical University School of Electronics and Information Shaanxi Key Laboratory of Information Acquisition and Processing China Nanjing University of Science and Technology Pca Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

Weakly supervised 3D semantic segmentation has successfully mitigated the labor-intensive and time-consuming task of annotating 3D point clouds. However, reliably utilizing the minimal point-wise annotations for unlabeled data in complex and large-scale scenes is still challenging, such as only 20 points labeled in 2 million points. To tackle this challenge, we propose a new Uncertainty-aware Superpoint Graph Transformer (UaSGT) framework that utilizes minimal annotations for unlabeled data learning through reliable long-range supervision propagation from labeled superpoints to unlabeled superpoints. First, we propose a superpoint graph transformer to achieve long-range supervision propagation along the attention-based fuzzy subsets defined on superpoints. The attention-based fuzzy subset measures the membership of unlabeled superpoints to clusters centered on labeled superpoints. Second, we employ an uncertainty-aware membership rectification technique on the fuzzy subset to ensure reliable propagation among superpoints within the same category. This technique integrates an uncertainty prediction module to mask the influence of unreliable membership and a spatial prior refinement module to reduce uncertainty in intra-class membership degrees. Finally, experimental results on two large-scale benchmarks S3DIS and ScanNet-V2 demonstrate the superiority of our approach compared to the state-of-the-art with at least 90% annotation reduction, and our method also achieves comparable performance to fully supervised methods with less than 0.1% labeled points. Our code is available at https://***/fanyan0411/UaSGT. © 2025 IEEE.

关键词： Semantic Segmentation

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Trajectory diffusion for objectgoal navigation 24

Trajectory diffusion for objectgoal navigation

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Proceedings of the 38th International Conference on Neural Information processing Systems

作者： Xinyao Yu Sixian Zhang Xinhang Song Xiaorong Qin Shuqiang Jiang Key Lab of Intelligent Information Processing Laboratory of the Chinese Academy of Sciences (CAS) Institute of Computing Technology Beijing and University of Chinese Academy of Sciences Beijing Key Lab of Intelligent Information Processing Laboratory of the Chinese Academy of Sciences (CAS) Institute of Computing Technology Beijing and University of Chinese Academy of Sciences Beijing and Institute of Intelligent Computing Technology Suzhou CAS

ISBN: (纸本)9798331314385

Object goal navigation requires an agent to navigate to a specified object in an unseen environment based on visual observations and user-specified goals. Human decision-making in navigation is sequential, planning a most likely sequence of actions toward the goal. However, existing ObjectNav methods, both end-to-end learning methods and modular methods, rely on single-step planning. They output the next action based on the current model input, which easily overlooks temporal consistency and leads to myopic planning. To this end, we aim to learn sequence planning for ObjectNav. Specifically, we propose trajectory diffusion to learn the distribution of trajectory sequences conditioned on the current observation and the goal. We utilize DDPM and automatically collected optimal trajectory segments to train the trajectory diffusion. Once the trajectory diffusion model is trained, it can generate a temporally coherent sequence of future trajectory for agent based on its current observations. Experimental results on the Gibson and MP3D datasets demonstrate that the generated trajectories effectively guide the agent, resulting in more accurate and efficient navigation. The code is available at https://***/sx-zhang/***.

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A Joint Learning Sentiment Analysis Method Incorporating Emoji-Augmentation 8

A Joint Learning Sentiment Analysis Method Incorporating Emo...

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8th IEEE International Conference on Cloud computing and Intelligence Systems, CCIS 2022

作者： Chen, Jie Luo, Luping Ji, Bojing Zhao, Shu Zhang, Yanping Anhui University The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology China Chizhou University School of Big Data and Artificial Intelligence China

ISBN: (纸本)9781665477352

Social media is the platform for most people to share their opinions, emojis are also widely used to express moods, emotions, and feelings on social media. There have been many researched on emojis and sentiment analysis. However, existing methods mainly face two limitations. First, since deep learning relies on large amounts of labeled data, the training samples of emoji are not enough to achieve the training effect. Second, they consider the sentiment of emojis and texts separately, not fully exploring the impact of emojis on the sentiment polarity of texts. In this paper, we propose a joint learning sentiment analysis method incorporating emoji-augmentation, and the method has two advantages compared with the existing work. First, We optimize the easy data augmentation method so that the newly generated sentences can also preserve the semantic information of emojis, which relieves the problem of insufficient training data with emojis. Second, it fuses emojis and text features to allow the model to better learn the mutual emotional semantics between text and emojis, jointly training emojis and words to obtain the sentence representations containing more semantic information of both emojis and text. Our experimental results show that the proposed method can significantly improve the performance compared with several baselines on two datasets. © 2022 IEEE.

关键词： Sentiment analysis

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Optimizing Antenna Design through AI Integration: A Concise Review

Optimizing Antenna Design through AI Integration: A Concise ...

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

作者： Xiaotian Liu Kwok L. Chung Wenbiao Li Ruihong Li Shuwei Huang Yingsong Li School of Computer Science and Engineering Huizhou University Huizhou China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

The integration of artificial intelligence with antenna design and optimization represents a promising research frontier. This paper provides a concise overview of current research, emphasizing the computational cost challenges associated with implementing machine learning in antenna design and optimization. It explores the advantages and limitations of utilizing the Kriging model and the Surrogate-assisted Differential Evolution Algorithm (SADEA) series to tackle these cost constraints.

关键词： Microwave antennas Technological innovation Analytical models Reviews Computational modeling Machine learning Transforms

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Balancing property optimization and constraint satisfaction for constrained multi-property molecular optimization

arXiv

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arXiv 2024年

作者： Xia, Xin Zhang, Yajie Zeng, Xiangxiang Zhang, Xingyi Zheng, Chunhou Su, Yansen The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China College of Computer Science and Electronic Engineering Hunan University Changsha410012 China

Molecular optimization, which aims to discover improved molecules from a vast chemical search space, is a critical step in chemical development. Various artificial intelligence technologies have demonstrated high effectiveness and efficiency on molecular optimization tasks. However, few of these technologies focus on balancing property optimization with constraint satisfaction, making it difficult to obtain high-quality molecules that not only possess desirable properties but also meet various constraints. To address this issue, we propose a constrained multi-property molecular optimization framework (CMOMO), which is a flexible and efficient method to simultaneously optimize multiple molecular properties while satisfying several druglike constraints. CMOMO improves multiple properties of molecules with constraints based on dynamic cooperative optimization, which dynamically handles the constraints across various scenarios. Besides, CMOMO evaluates multiple properties within discrete chemical spaces cooperatively with the evolution of molecules within an implicit molecular space to guide the evolutionary search. Experimental results show the superior performance of the proposed CMOMO over five state-of-the-art molecular optimization methods on two benchmark tasks of simultaneously optimizing multiple non-biological activity properties while satisfying two structural constraints. Furthermore, the practical applicability of CMOMO is verified on two practical tasks, where it identified a collection of candidate ligands of β2-adrenoceptor GPCR and candidate inhibitors of glycogen synthase kinase-3β with high properties and under drug-like constraints. Copyright © 2024, The Authors. All rights reserved.

关键词： Constrained optimization

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