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arXiv 2025年

作者： Dong, Xuewen Li, Jiachen Li, Shujun You, Zhichao Qu, Qiang Kholodov, Yaroslav Shen, Yulong School of Computer Science and Technology Xidian University The Engineering Research Center of Blockchain Technology Application and Evaluation Ministry of Education China The Shaanxi Key Laboratory of Blockchain and Secure Computing Xi’an710071 China University of Kent CanterburyCT2 7NP United Kingdom Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Intelligent Transportation Systems Lab Innopolis University Innopolis Russia School of Computer Science and Technology Xidian University China The Shaanxi Key Laboratory of Network and System Security Xi’an710071 China

Recent studies show that graph neural networks (GNNs) are vulnerable to backdoor attacks. Existing backdoor attacks against GNNs use fixed-pattern triggers and lack reasonable trigger constraints, overlooking individual graph characteristics and rendering insufficient evasiveness. To tackle the above issues, we propose ABARC, the first Adaptive Backdoor Attack with Reasonable Constraints, applying to both graph-level and node-level tasks in GNNs. For graph-level tasks, we propose a subgraph backdoor attack independent of the graph’s topology. It dynamically selects trigger nodes for each target graph and modifies node features with constraints based on graph similarity, feature range, and feature type. For node-level tasks, our attack begins with an analysis of node features, followed by selecting and modifying trigger features, which are then constrained by node similarity, feature range, and feature type. Furthermore, an adaptive edge-pruning mechanism is designed to reduce the impact of neighbors on target nodes, ensuring a high attack success rate (ASR). Experimental results show that even with reasonable constraints for attack evasiveness, our attack achieves a high ASR while incurring a marginal clean accuracy drop (CAD). When combined with the state-of-the-art defense randomized smoothing (RS) method, our attack maintains an ASR over 94%, surpassing existing attacks by more than 7%. Copyright © 2025, The Authors. All rights reserved.

关键词： Graph neural networks

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Yangtze Delta Region Academy Jiaxing314019 China Beijing Institute of Technology Advanced Technology Research Institute Jinan250307 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Birmingham City University School of Computing and Digital Technology BirminghamB55JU United Kingdom Khalifa University KU 6 G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs' activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. © 1967-2012 IEEE.

关键词： Channel estimation

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A hybrid algorithm based on artificial bee colony and pigeon inspired optimization for 3D protein structure prediction

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Journal of Bionanoscience 2018年第1期12卷 100-108页

作者： Li, Ting Zhou, Changjun Wang, Bin Xiao, Boxiang Zheng, Xuedong Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian116622 China Beijing Key Laboratory of Digital Plant Beijing100097 China

With the accomplishment of the Human Genome Project, the significance of protein structure research becomes more outstanding. The prediction of protein structure is aimed at the study of amino acid molecules, and belongs to the field of Bio-Nano research. There are two kinds of methods to study protein structure: Experiment and theory. This paper adopts ab-initio prediction method which is one of theoretical methods. Based on the "thermodynamic hypothesis," there are many different models applied to the field. This paper selects 3D AB off-lattice model to solve this problem. ABC-PIO combines the characteristics of the diversity generated by artificial bee colony algorithm and the fast convergence speed of pigeon inspired optimization. At the end of this algorithm, Cauchy perturbation strategy is added to optimize the local optimum. Two functions are introduced to dynamically control two operators of the hybrid algorithm. In order to test the quality of ABC-PIO, ten real protein sequences from the Protein Data Bank have been selected. Compared with other four algorithms, the algorithm gets better result. To calculate the error between the predicted and the true protein structure RMSD is set. Comparisons are made not only in the convergence curves but also in the backbone drawings. © 2018 American Scientific Publishers.

关键词： Optimization

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

arXiv

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arXiv 2025年

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing Institute of Technology Beijing100081 China Jiaxing314019 China Advanced Technology Research Institute Beijing Institute of Technology Jinan250307 China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China School of Computing and Digital Technology Birmingham City University BirminghamB55JU United Kingdom KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs’ activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. Simulation codes are provided to reproduce the results in this article: https://***/owenwang517/tvt-2025. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implicit Variables 2nd

PreZ-DGGAN: A Drug Graph GAN Based on Pre-Learning of Implic...

引用

2nd International Conference on Applied Intelligence, ICAI 2024

作者： Liu, Yixin Fan, Yueqin Li, Zhipeng Zhang, Qinhu Big Data and Intelligent Computing Research Center Guangxi Academy of Science Nanning530007 China School of Mechanical Engineering Guangxi University Nanning530004 China Ningbo Institute of Digital Twin Eastern Institute of Technology Ningbo315201 China Institute for Regenerative Medicine Medical Innovation Center and State Key Laboratory of Cardiology School of Medicine Shanghai East Hospital Tongji University Shanghai200123 China College of Advanced Agricultural Sciences Zhejiang Agriculture and Forestry University Hangzhou311300 China

ISBN: (纸本)9789819619061

In the field of drug discovery and development, deep learning techniques have become a powerful tool to accelerate the discovery and development of new drugs. In the design and optimization of lead molecules, generative adversarial network and graph neural network are one of the prime techniques for accelerating research and development, because the former is based on the idea of two-player game to learn drug features to generate effective molecules, while the unstructured inputs of the latter are well-suited for the analysis of molecular data. Therefore, this study develops a new graph generative adversarial model, called PreZ-DGGAN, by inserting the graph neural network layer into the generative adversarial network. Within PreZ-DGGAN, the latent variable input of the generator is pre-learned by an improved graph variational autoencoder, which effectively avoids the mode collapse of the generative adversarial network, whereas the hidden layer of the discriminator is graph neural network layer, which is able to better learn the real molecules and judge the generated molecules as true or false. Experiments on two molecule datasets show that the molecules generated by PreZ-DGGAN have higher validity (100% on average) and uniqueness (91.5% on average), and the generated molecules are more diverse in structure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

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Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 221-239页

作者： Tianyuan Jia Xiangyong Chen Xiurong Yao Feng Zhao Jianlong Qiu School of Automation and Electrical Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of ShandongLinyi UniversityLinyi276005China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and School of AutomationChina University of GeosciencesWuhan430074China

Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.

关键词： Memristor-based neural networks fixed-time synchronization mixed delays discontinuous activations adaptive control

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Acoustic scene classification by enhanced high- frequency weak signal characteristic spectrum 8

Acoustic scene classification by enhanced high- frequency we...

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8th International Conference on computing and Pattern Recognition, ICCPR 2019

作者： Hao, Wenjie Zhao, Lasheng Zhang, Qiang Key Laboratory of Advanced Design Intelligent Computing Ministry of Education Dalian University China

ISBN: (纸本)9781450376570

In the acoustic scene classification task, the method of using melspectrogram to express the acoustic scene information is widely applied. However, mel-spectrogram has defects and it ignores important information about some acoustic scenes. The paper improves the mel-spectrogram and its generation algorithm. Including: I. For the sensitivity of the acoustic scene to highfrequency acoustic signals, the paper changes the filter design method of Mel Frequency Cepstrum Coefficient (MFCC). This method preserves more high frequency information by applying the equal-height triangular filter banks and increasing the number of the filters. II. Based on the previous step, an enhancement algorithm is proposed for the problem of the lack of highfrequency weak signals in the characteristic spectrum. The algorithm performs nonlinear mapping on the mel-spectrogram, which makes the transformed high-frequency weak signal feature information more obvious. The algorithm is verified by DCASE 2018 acoustic scene classification dataset and LITIS ROUEN dataset. The experimental results demonstrate the effectiveness of the proposed algorithm. © 2019 Association for computing Machinery.

关键词： Spectrographs

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A comparative study of methodologies for designing IDSSs

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1997年第2期103卷 277-295页

作者： Blair, A Debenham, J Edwards, J Intelligent Decision Support System Laboratory Key Centre for Advanced Computing Studies School of Computing Sciences University of Technology P.O. Box 123 Broadway N.S.W. 2007 Australia

In this paper, we describe a comprehensive study conducted to understand the methodologies which are being used to design intelligent Decision Support Systems (IDSSs) and to identify the key methodological problems and benefits with using these methodologies. This comprehensive study consists of two parts. The first part is two surveys which together identify the design methodologies being used by a group of IDSS developers and how acceptable they believe their methodologies were for designing their IDSSs. The second part is a comparison of six major formal IDSS design methodologies recently published in the literature and which are not yet known to many developers. This paper is presented to assist IDSS developers in understanding what support can be gained from using existing design methodologies and hence choose the correct one for their project. Furthermore, the paper may be used by IDSS developers to compare the way that they work with the approach proposed by other developers. (C) 1997 Elsevier Science B.V.

关键词： decision support systems knowledge based systems intelligent decision support systems

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Finding Emotional Focus for Emotion Recognition at Sentence Level

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电子学报(英文版) 2013年第1期22卷 99-103页

作者： QUAN Changqin REN Fuji Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei 230009 China Faculty of Engineering The University of Tokushima Tokushima Japan

Emotion recognition at sentence level is one of the fundamental problems of textual emotion un- derstanding. Based on the observation that sentence emo- tional focus can be expressed by some clauses in this sen- tence, this paper proposes to find the emotional focus for sentence emotion recognition. For the sake of breaking through the problems brought about by depending on emo- tion lexicons, we first recognize word emotions in a sen- tence based on Maximum entropy model. And then homo- geneous Markov model is built for clause emotion recogni- tion; After that, a strategy based on emotion selection is proposed for a sentence with multiple clauses, and genetic algorithm is used for clause selection by textual feature weighting. The experimental results show that, comparing with the baseline, there are 9.1% and 3.6% improvement respectively for two different evaluations. It is demon- strated that finding emotional focus by clause selection is able to improve the performance of sentence emotion recognition significantly.

关键词：情感识别句子层面聚焦马尔可夫模型最大熵模型特征加权遗传算法

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Accelerating algorithm for biochemical reaction systems with multiple delays 17

Accelerating algorithm for biochemical reaction systems with...

引用

9th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2017

作者： Tian, Huili Zhou, Changjun Zhang, Qiang Key Laboratory of Advanced Design and Intelligent Computing Dalian University Ministry of Education Dalian China

ISBN: (纸本)9781450348799

Delay in the study of biochemical reaction system can't be ignored and the complex time delay systems are integrated to get the multiple time delayed biochemical reactions. An improved acceleration algorithm based on MD-Leaping algorithm for multidelayed biochemical reaction systems is proposed in this paper. The number of the waiting records generated during the operation of the MD-Leaping algorithm slows down its rate. We use a novel method that can reduce the size of the wait queue to add the wait records. The new algorithm greatly reduces the memory requirements without losing accuracy and runs faster. At last, this paper makes a numerical simulation analysis of a multiple time delayed model, and this case further demonstrates the accuracy and efficiency of the proposed algorithm. © 2017 Association for computing Machinery.

关键词： Stochastic systems

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