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IEEE International Conference on Acoustics, Speech and Signal processing

作者： Haoyi Fan Fengbin Zhang Zuoyong Li School of Computer Science and Technology Harbin University of Science and Technology Harbin China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

Anomaly detection on attributed networks aims at finding nodes whose patterns deviate significantly from the majority of reference nodes, which is pervasive in many applications such as network intrusion detection and social spammer detection. However, most existing methods neglect the complex cross-modality interactions between network structure and node attribute. In this paper, we propose a deep joint representation learning framework for anomaly detection through a dual autoencoder (AnomalyDAE), which captures the complex interactions between network structure and node attribute for high-quality embeddings. Specifically, Anoma-lyDAE consists of a structure autoencoder and an attribute autoencoder to learn both node embedding and attribute embedding jointly in latent space. Moreover, attention mechanism is employed in structure encoder to learn the importance between a node and its neighbors for an effective capturing of structure pattern, which is important to anomaly detection. Besides, by taking both the node embedding and attribute embedding as inputs of attribute decoder, the cross-modality interactions between network structure and node attribute are learned during the reconstruction of node attribute. Finally, anomalies can be detected by measuring the reconstruction errors of nodes from both the structure and attribute perspectives. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed method.

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Principled design of translation, scale, and rotation invariant variation operators for metaheuristics

arXiv

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arXiv 2021年

作者： Tian, Ye Zhang, Xingyi He, Cheng Tan, Kay Chen Jin, Yaochu Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China Guangdong Provincial Key Laboratory of Braininspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Computing The Hong Kong Polytechnic University Hong Kong Department of Computer Science University of Surrey Guildford SurreyGU2 7XH United Kingdom

In the past three decades, a large number of metaheuristics have been proposed and shown high performance in solving complex optimization problems. While most variation operators in existing metaheuristics are empirically designed, this paper aims to design new operators automatically, which are expected to be search space independent and thus exhibit robust performance on different problems. For this purpose, this work first investigates the influence of translation invariance, scale invariance, and rotation invariance on the search behavior and performance of some representative operators. Then, we deduce the generic form of translation, scale, and rotation invariant operators. Afterwards, a principled approach is proposed for the automated design of operators, which searches for highperformance operators based on the deduced generic form. The experimental results demonstrate that the operators generated by the proposed approach outperform state-of-theart ones on a variety of problems with complex landscapes and up to 1000 decision variables. © 2021, CC BY.

关键词： Heuristic algorithms

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Neural Network-Based Prescription of Chinese Herbal Medicines

Neural Network-Based Prescription of Chinese Herbal Medicine...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Wen Zhao Weikai Lu Chang'en Zhou Zuoyong Li Haoyi Fan Xuejuan Lin Zhaoyang Yang Candong Li School of Traditional Chinese Medicine Fujian University of Traditional Chinese Medicine Fuzhou China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781728194202

Objective: To develop a neural network model that recommends traditional Chinese medicine (TCM) herbal prescriptions. Methods: We constructed a new dataset of diagnosis and treatment knowledge from the Treatise on Febrile Diseases. Based on TCM's logical principles of “syndrome differentiation” and “state recognition”, a back-propagation neural network model is proposed that simulates clinical diagnosis and treatment. Results: The proposed model is a four-layer BP neural network. Experiments on the constructed dataset show that the proposed method achieved the best precision, recall, and F1-scores. Conclusion: The proposed method provides much more accurate herbal prescription recommendations than logistic regression.

关键词： Neural networks Education Clinical diagnosis information technology Logistics Diseases

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Self-Supervised Speech Denoising Using Only Noisy Audio Signals

arXiv

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arXiv 2021年

作者： Wu, Jiasong Li, Qingchun Yang, Guanyu Li, Lei Senhadji, Lotfi Shu, Huazhong LIST Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing210096 China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Southeast University Nanjing210096 China RennesF-35042 France The 28th Research Institute of China Electronics Technology Group Corporation Nanjing210007 China Univ Rennes INSERM LTSI UMR 1099 RennesF-35042 France

In traditional speech denoising tasks, clean audio signals are often used as the training target, but absolutely clean signals are collected from expensive recording equipment or in studios with the strict environments. To overcome this drawback, we propose an end-to-end self-supervised speech denoising training scheme using only noisy audio signals, named Only-Noisy Training (ONT), without extra training conditions. The proposed ONT strategy constructs training pairs only from each single noisy audio, and it contains two modules: training audio pairs generated module and speech denoising module. The first module adopts a random audio sub-sampler on each noisy audio to generate training pairs. The sub-sampled pairs are then fed into a novel complex-valued speech denoising module. Experimental results show that the proposed method not only eliminates the high dependence on clean targets of traditional audio denoising tasks, but also achieves on-par or better performance than other training strategies. Availability-ONT is available at https://***/liqingchunnnn/Only-Noisy-Training. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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Using quantum thinking to construct a musical appreciation system 2nd

Using quantum thinking to construct a musical appreciation s...

引用

2nd International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2018

作者： Peng, Mei Gangyi, Ding Qiankun, Jin Fuquan, Zhang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (纸本)9783030045845

With the richness of material and cultural life, participating in music activities and enjoying music works has become an indispensable activity in people’s leisure time. The rich emotions in music have different performances according to individual differences. After the composers create the music, the performer’s deductive processing and then the emotion is sublimated by the viewers finally. This paper proposes a new emotional system for basic emotional joy, anger, sadness, joy, etc., and interprets the superposition state of emotional expression in detail. The paper believes that the generation of consciousness and the resonance of thinking are precisely the result of the quantum collapse of mutual entanglement. © Springer Nature Switzerland AG 2019.

关键词： Music

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Augmented reality-based pre-visualization for film making 2nd

Augmented reality-based pre-visualization for film making

引用

2nd International Conference on Smart Vehicular technology, Transportation, Communication and Applications, VTCA 2018

作者： Xue, Tong Ding, Gangyi Zhang, Fuquan School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

ISBN: (纸本)9783030045845

With the development of the augmented reality technologies, wearing devices such as Microsoft Hololens and Google glass become highly popular recently. In this paper, we proposed a novel augmented reality application that helps the film directors to complete and facilitate their film rehearsal process. We simulated a design space to provide film directors with a high-fidelity visual-audio experience. The directors wearing the hololens are allowed to observe the synthesized virtual-reality space in which they can recognize the whole design space, prefabricated boxes, and modify the space by defined gestures. Feedbacks from directors indicate the proposed tool is effective and the preliminary experimental results agree with our observations. In general, our research offers the guidelines for novel film rehearsal tactics. © Springer Nature Switzerland AG 2019.

关键词： Visualization

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Unified Framework for Oculomotor Nerve Reconstruction: Tractography-Based Anatomical Assessment

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Journal of Neuroimaging 2025年第3期35卷

作者： Jiahao Huang Qingrun Zeng Ye Wu Jiawei Zhang Mengjun Li Lei Xie Mingchu Li Yuanjing Feng Institute of Information Processing and Automation College of Information Engineering Zhejiang University of Technology Hangzhou China Zhejiang Provincial United Key Laboratory of Embedded Systems Hangzhou China School of Computer Science and Technology Nanjing University of Science and Technology Nanjing China Department of Radiology Second Xiangya Hospital Central South University Changsha China Department of Neurosurgery Capital Medical University Xuanwu Hospital Beijing China

Background and Purpose The oculomotor nerve (OCN) innervates the eye muscles and can be affected by inflammatory, compressive, and pathological conditions. Diffusion MRI (dMRI) tractography shows the potential ability to describe the trajectory of the OCN. However, reconstruction of the OCN in the cavernous sinus is still challenging due to the complex tissue environment at the skull base. Methods In this study, we integrated anatomical knowledge to propose a unified framework for OCN tractography, using 45 dMRI datasets from the Human Connectome Project subjects aged 22–36 years and data from four neurosurgical patients aged 41–53 years with visual behavior disorders. We first employed automatically labeled direct and indirect anatomical landmarks as reference locations for individualized tractography. Next, we compared five widely used cranial nerve reconstruction algorithms to assess the most suitable method for OCN reconstruction. Finally, we tested the combination of the unified framework and the optimized tractography method in tumor patients. Results We found that unscented Kalman filter (UKF)-2T and probabilistic tractography outperformed other methods in OCN fiber tractography, owing to their “step-by-step” fiber direction computation and multidirectional consideration, respectively. In neurosurgical patients, UKF-2T effectively reconstructed OCN fibers around lesions. Conclusion Our study provides valuable insights for researchers and clinicians in the diagnosis and treatment of OCN-related diseases and neurosurgeries.

关键词： diffusion magnetic resonance imaging Human Connectome Project neurosurgery oculomotor nerve tractography

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Beamforming Design and Association Scheme for Multi-RIS Multi-User mmWave Systems Through Graph Neural Networks

arXiv

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arXiv 2025年

作者： Liu, Mengbing Huang, Chongwen Alhammadi, Ahmed Di Renzo, Marco Debbah, Mérouane Yuen, Chau School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Technology Innovation Institute Masdar City Abu Dhabi United Arab Emirates Université Paris-Saclay CNRS CentraleSupélec Laboratoire des Signaux et Systèmes 3 Rue Joliot-Curie Gif-sur-Yvette91192 France King’s College London Centre for Telecommunications Research Department of Engineering LondonWC2R 2LS United Kingdom KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France

Reconfigurable intelligent surface (RIS) is emerging as a promising technology for next-generation wireless communication networks, offering a variety of merits such as the ability to tailor the communication environment. Moreover, deploying multiple RISs helps mitigate severe signal blocking between the base station (BS) and users, providing a practical and efficient solution to enhance the service coverage. However, fully reaping the potential of a multi-RIS aided communication system requires solving a non-convex optimization problem. This challenge motivates the adoption of learning-based methods for determining the optimal policy. In this paper, we introduce a novel heterogeneous graph neural network (GNN) to effectively leverage the graph topology of a wireless communication environment. Specifically, we design an association scheme that selects a suitable RIS for each user. Then, we maximize the weighted sum rate (WSR) of all the users by iteratively optimizing the RIS association scheme, and beamforming designs until the considered heterogeneous GNN converges. Based on the proposed approach, each user is associated with the best RIS, which is shown to significantly improve the system capacity in multi-RIS multiuser millimeter wave (mmWave) communications. Specifically, simulation results demonstrate that the proposed heterogeneous GNN closely approaches the performance of the high-complexity alternating optimization (AO) algorithm in the considered multi-RIS aided communication system, and it outperforms other benchmark schemes. Moreover, the performance improvement achieved through the RIS association scheme is shown to be of the order of 30%. Copyright © 2025, The Authors. All rights reserved.

关键词： Beamforming

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Negative information filtering algorithm based on text content in multimedia networks

引用

International Journal of Performability Engineering 2019年第11期15卷 3061-3071页

作者： Chen, Wenqing Fu, Weina College of Applied Technology China University of Labor Relations Beijing100000 China College of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot010012 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China

In the multimedia network environment, it is necessary to effectively filter negative information in the multimedia network and enhance the ability to mine and identify valid data. This paper presents a new algorithm of negative information filtering based on text content in multimedia networks. The principal component features of negative information in multimedia networks are extracted, and matched filters are designed to filter the negative information reasonably. All text contents and negative information are normalized and sorted. They are transformed into the same text format for classification and processing, and the filtering and detection of negative information are realized. Finally, based on the semantic features of text content, the support vector machine algorithm is used to extract negative information features from data. Experimental results show that the algorithm improves the filtering accuracy and performance for negative information in multimedia networks, and it has good application value. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： information filtering

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Heterogeneous two-Stream Network with Hierarchical Feature Prefusion for Multispectral Pan-Sharpening

Heterogeneous two-Stream Network with Hierarchical Feature P...

引用

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Dong Wang Yunpeng Bai Bendu Bai Chanyue Wu Ying Li National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi'an China School of Communication and Information Engineering Xi’an University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Shaanxi Provincial Key Laboratory of Speech & Image Information Processing Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781728176055;9781728176062

Multispectral (MS) pan-sharpening aims at producing a high spatial resolution (HR) MS image by fusing a single-band HR panchromatic (PAN) image and a corresponding MS image with low spatial resolution. In this paper, we propose a heterogeneous two-stream network (HTSNet) with hierarchical feature prefusion for MS pan-sharpening. The HTSNet employs a heterogeneous group of spatial and spectral streams for spatial and spectral information extraction, respectively. The spatial stream utilizes a 2D CNN for spatial information extraction from the PAN images, and the spectral stream obtains spectral feature cubes from the MS images by a 3D CNN. At the same time, a prefusion module is introduced to prefuse the spatial details with spectral information and transfer information between different streams, which can enhance later processing. In the experiment, the Gaofen-2 satellite dataset is utilized to compare the proposed method with the state-of-the-art MS pan-sharpening methods. Experimental results demonstrate the superiority of our HTSNet in terms of visual effect and quantitative qualities.

关键词： Satellites Three-dimensional displays Fuses Streaming media Signal processing information retrieval Visual effects

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