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Negative information filtering algorithm based on text content in multimedia networks

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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Human-multimodal deep learning collaboration in ‘precise’ diagnosis of lupus erythematosus subtypes and similar skin diseases

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Journal of the European Academy of Dermatology and Venereology 2024年第12期38卷 2268-2279页

作者： Li, Qianwen Yang, Zhi Chen, Kaili Zhao, Ming Long, Hai Deng, Yueming Hu, Haoran Jia, Chen Wu, Meiyu Zhao, Zhidan Zhu, Huan Zhou, Suqing Zhao, Mingming Cao, Pengpeng Zhou, Shengnan Song, Yang Tang, Guishao Liu, Juan Jiang, Jiao Liao, Wei Zhou, Wenhui Yang, Bingyi Xiong, Feng Zhang, Suhan Gao, Xiaofei Jiang, Yiqun Zhang, Wei Zhang, Bo He, Yan-ling Ran, Liwei Zhang, Chunlei Wu, Wenting Suolang, Quzong Luo, Hanhuan Kang, Xiaojing Wu, Caoying Jin, Hongzhong Chen, Lei Guo, Qing Gui, Guangji Li, Shanshan Si, Henan Guo, Shuping Liu, Hong-Ye Liu, Xiguang Ma, Guo-Zhang Deng, Danqi Yuan, Limei Lu, Jianyun Zeng, Jinrong Jiang, Xian Lyu, Xiaoyan Chen, Liuqing Hu, Bin Tao, Juan Liu, Yuhao Wang, Gang Zhu, Guannan Yao, Zhirong Xu, Qianyue Yang, Bin Wang, Yu Ding, Yan Yang, Xianxu Kai, Hu Wu, Haijing Lu, Qianjin Department of Dermatology Hunan Key Laboratory of Medical Epigenomics The Second Xiangya Hospital of Central South University Changsha China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Dermatology Hunan Children's Hospital Changsha China Institute of Dermatology Chinese Academy of Medical Sciences and Peking Union Medical College Nanjing China Department of Dermatology Beijing Chao-Yang Hospital Capital Medical University Beijing China Department of Dermatology Peking University Third Hospital Beijing China Department of Dermatology People's Hospital of Tibet Autonomous Region Lhasa China Department of Dermatology People's Hospital of Xinjiang Uygur Autonomous Region Urumqi China Department of Dermatology State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College Hospital Chinese Academy of Medical Science and Peking Union Medical College Beijing China Department of Dermatology Sun Yat-Sen Memorial Hospital Sun Yat-Sen University Guangzhou China Department of Dermatology The First Bethune Hospital of Jilin University Changchun China Department of Dermatology The First Hospital of Shanxi Medical University Taiyuan China Department of Dermatology The Hei Long Jiang Provincial Hospital Harbin China Department of Dermatology The Second Affiliated Hospital of Kunming Medical University Kunming China Department of Dermatology The Third Xiangya Hospital Central South University Changsha China Department of Dermatology West China Hospital Sichuan University Chengdu China Department of Dermatology Wuhan No. 1 Hospital Wuhan China Department of Dermatology Wuhan Union Hospital of China Wuhan China Department of Dermatology Xijing Hospital Xi'an China Department of Dermatology Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Dermatology Hospital of Southern Medical University Guangzhou Chin

Background: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE. Objectives: We aim to develop a multimodal deep learning system (MMDLS) for human-AI collaboration in diagnosis of LE subtypes. Methods: This is a multi-centre study based on 25 institutions across China to assist in diagnosis of LE subtypes, other eight similar skin diseases and healthy subjects. In total, 446 cases with 800 clinical skin images, 3786 multicolor-immunohistochemistry (multi-IHC) images and clinical data were collected, and EfficientNet-B3 and ResNet-18 were utilized in this study. Results: In the multi-classification task, the overall performance of MMDLS on 13 skin conditions is much higher than single or dual modals (Sen = 0.8288, Spe = 0.9852, Pre = 0.8518, AUC = 0.9844). Further, the MMDLS-based diagnostic-support help improves the accuracy of dermatologists from 66.88% ± 6.94% to 81.25% ± 4.23% (p = 0.0004). Conclusions: These results highlight the benefit of human-MMDLS collaborated framework in telemedicine by assisting dermatologists and rheumatologists in the differential diagnosis of LE subtypes and similar skin diseases. © 2024 European Academy of Dermatology and Venereology.

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Social Emergency Event Judgement based on BiLSTM-CRF 19

Social Emergency Event Judgement based on BiLSTM-CRF

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19th Chinese National Conference on Computational Linguistic, CCL 2020

作者： Hu, Huijun Wang, Cong Dai, Jianhua Liu, Maofu School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China

In recent years, classification and rating of social emergency event have attracted more and more attentions in emergency management. However, most of the current studies adopt the rule-based methods to identify the evidences for event judgement, and have troubles in event judgement due to the complexity of social emergency event composition and the flexibility of language description. Inspired by the idea of event extraction, this paper has proposed the event judgement method via BiLSTM (Bidirectional Long-Short Term Memory) and CRF (Conditional Radom Fields) based on event classification and evidence extraction. The social emergency event classification is carried out firstly, and then the event evidences are extracted based on event type. In the end, the rating of social emergency event is judged with the attention mechanism and the combination of event type and evidence. Experimental results show that the proposed method is more robust than rule-based ones, and effective in the social emergency event judgement. © 2020 China National Conference on Computational Linguistics Published under Creative Commons Attribution 4.0 International License

关键词： Extraction

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A Simple Analysis of Multimodal Data Fusion

A Simple Analysis of Multimodal Data Fusion

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Jiangchang Cheng Yinglong Dai Yao Yuan Hongli Zhu College of Information Science and Engineering Hunan Normal University Changsha China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China College of Liberal Arts and Sciences National University of Defense Technology Changsha China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Multimodal data fusion has a long research history since audio-visual speech recognition, which is inspired by the McGurk effect. Because of the limited model capacity of the traditional methods, multimodal data fusion researches are not so popular for a period. Recently, the advances of deep learning techniques open up new opportunities for the multimodal data fusion field. However, there is still a great gap in multimodal data processing ability between artificial intelligence and human beings. Many problems in multimodal data processing are still necessary to be researched. In this work, we propose to gain an insight into the information fusion level and apply different information fusion strategy to different situations. We analyze the different situations of the multimodal data fusion process and divide them into two categories, including consistent information fusion and contradictory information fusion. We demonstrate some toy examples of the different cases of the multimodal data fusion process.

关键词： Deep learning Data privacy Toy manufacturing industry Data integration Speech recognition Security History

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A niching-based nondominated sorting for multimodal multiobjective optimization with local pareto fronts

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Applied Soft computing 2025年 179卷

作者： Qi Deng Juan Zou Shengxiang Yang Yuan Liu Fan Yu Tianbin Xie Jinhua Zheng Key Laboratory of Intelligent Computing and Information Processing Ministry of Education School of Computer Science and School of Cyberspace Science of Xiangtan University Xiangtan Hunan Province China Faculty of School of Computer Science and School of Cyberspace Science of Xiangtan University Xiangtan 411105 China School of Computer Science and Informatics De Montfort University Leicester LE1 9BH UK School of Traffic and Transport Engineering Central South University Changsha China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang 421002 China

In multimodal multiobjective optimization problems (MMOPs), there may be local Pareto optimal solutions (PSs). Finding both global PS and local PS simultaneously can provide additional options for decision makers. However, since individuals on the global Pareto front (PF) dominate individuals on the local PF, traditional multimodal multiobjective evolutionary algorithms (MMEAs) cannot effectively handle MMOPs with local PF (MMOPLs). In this paper, we improve our previous dynamic-niching-based Pareto domination (DNPD) approach to search for local Pareto optimal solutions. The new version is called niching-based non-dominated sorting (NNSL). There are two improvements to NNSL. First, the dynamic niche is changed to a fixed niche to increase the diversity of the population. Second, individuals with poor convergence in the non-dominated layer are deleted to ensure the convergence of the population. NNSL can be combined with Pareto dominance-based algorithms. We apply NNSL to solve MMOPLs (MMF_e and IDMP_e series). Experiments show that NNSL can help traditional MMEAs find global PF/PS and local PF/PS simultaneously.

关键词： Local Pareto optimal solutions Multimodal multiobjective optimization problems Nondominated layer

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Temperature dependence of commensurate magnetic resonance in cuprate superconductors 5th

Temperature dependence of commensurate magnetic resonance in...

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5th Conference on New Advances in Condensed Matter Physics, NACMP 2018

作者： Lan, Yu Kuang, Lülin Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Physics and Electronic Engineering Hengyang Normal University Hengyang421002 China National Research Center for High-Performance Computing Engineering Technology Sugon Beijing100193 China

ISBN: (纸本)9783035713275

Within the kinetic energy driven superconducting mechanism, we have studied the temperature dependence of commensurate magnetic resonance in cuprate superconductors. It is shown that the commensurate magnetic resonance peak at the antiferromagnetic wave vector point persists in the superconducting state until the temperature rises to the superconducting transition temperature Tc. The intensity of the resonance peak decreases with increasing temperature which is just like the temperature dependence of the superconducting gap parameter. Our results are in qualitative agreement with the inelastic neutron scattering experimental data and reflect that the commensurate magnetic resonance is closely related to the creation of the charge carrier pairs and thus the superconducting mechanism of cuprate superconductors. © 2018 Trans Tech Publications, Switzerland

关键词： Temperature distribution

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Interference-assisted kaleidoscopic meta-plexer for arbitrary spin-wavefront manipulation

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Light(Science & Applications) 2019年第1期8卷 1141-1150页

作者： He-Xiu Xu Guangwei Hu Ying Li Lei Han Jianlin Zhao Yunming Sun Fang Yuan Guang-Ming Wang Zhi Hao Jiang Xiaohui Ling Tie Jun Cui Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Air and Missile Defense College Air force Engineering University710051 Xi’anChina Hunan Provincial Key Laboratory of Intelligent Information Processing and Applications College of Physics and Electronics EngineeringHengyang Normal University421008 HengyangChina School of Natural and Applied Sciences Northwestern Polytechnical University710072 Xi’anChina Advanced Technique Department Key Lab of Aeronautics Computing Technique710075 Xi’anChina State Key Laboratory of Millimeter Waves Southeast University210096 NanjingChina

Achieving simultaneous polarization and wavefront control,especially circular polarization with the auxiliary degree of freedom of light and spin angular momentum,is of fundamental importance in many optical *** are typically undesirable in highly integrated photonic circuits and ***,we propose an interference-assisted metasurface-multiplexer(meta-plexer)that counterintuitively exploits constructive and destructive interferences between hybrid meta-atoms and realizes independent spin-selective wavefront *** kaleidoscopic meta-plexers are experimentally demonstrated via two types of single-layer spinwavefront multiplexers that are composed of spatially rotated anisotropic *** type generates a spinselective Bessel-beam wavefront for spin-down light and a low scattering cross-section for stealth for spin-up *** other type demonstrates versatile control of the vortex wavefront,which is also characterized by the orbital angular momentum of light,with frequency-switchable numbers of beams under linearly polarized wave *** findings offer a distinct interference-assisted concept for realizing advanced multifunctional photonics with arbitrary and independent spin-wavefront features.A variety of applications can be readily anticipated in optical diodes,isolators,and spin-Hall meta-devices without cascading bulky optical elements.

关键词： arbitrary momentum versatile

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Online Fault Monitoring Based on Moving Window Recursive Sparse Principal Component Analysis

Online Fault Monitoring Based on Moving Window Recursive Spa...

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第30届中国过程控制会议（CPCC 2019）

作者： Jinping Liu Jie Wang Zhaohui Tang Junbin He Jingjing Zhang Jean Paul Niyoyita Hunan Provincial Key Laboratory of Intelligent Computing and Language Processing Hunan Normal University School of Automation Central South University Hunan Institute of Metrology and Test College of Science and Technology University of Rwanda

This paper presents a moving window-recursive sparse principal component analysis(M WRSPCA)-based online fault monitoring method, aim at providing effective fau lt monitoring solution for the large-scale complex industrial processes with time varying and dynamic changing *** establishes a sparse principal component model with a sliding window block matrix to monitor the industrial data sample set online and re-adds the normal industrial sample data to the training set during the fault monitoring process, so that the process monitoring model can be adaptive to the time varying *** the window is sliding, the covariance information of window data block matrix is updated recursively, and the sparse loading matrix is also updated recursively by using the modified algorithm of the rank 1 matrix, so that the computational complexity of the adaptive process monitoring model is greatly reduced and the model real-time monitoring capability is *** proposed method is experimentally verified in the Tennessee-Eastman(TE) *** with the traditional fault monitoring methods, the proposed method can effectively improve the accuracy of fault detection and adapt to fault monitoring of long process and complex industrial processes.

关键词： Time varying industrial process Sparse principal component analysis(SPCA) Recursive SPCA M oving window model Online fault detection

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Interpretable Saliency Map for Deep Reinforcement Learning

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Journal of Physics: Conference Series 2021年第1期1757卷

作者： Hong Zheng Yinglong Dai Fumin Yu Yuezhen Hu School of Physics and Electronics Hunan Normal University Changsha 410081 China College of Liberal Arts and Sciences National University of Defense Technology Changsha 410073 China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha 410081 China

Deep reinforcement learning (deep RL) achieved big successes with the advantage of deep learning techniques, while it also introduces the disadvantage of the model interpretability. Bad interpretability is a great obstacle for deep RL to be applied in real situations or human-machine interaction situations. Borrowed from the deep learning field, the techniques of saliency maps recently become popular to improve the interpretability of deep RL. However, the saliency maps still cannot provide specific and clear enough model interpretations for the behavior of deep RL agents. In this paper, we propose to use hierarchical conceptual embedding techniques to introduce prior-knowledge in the deep neural network (DNN) based models of deep RL agents and then generate the saliency maps for all the embedded factors. As a result, we can track and discover the important factors that influence the decisions of deep RL agents.

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UWB SAR image segmentation algorithm based on polynomial analysis of statistical distribution 6

UWB SAR image segmentation algorithm based on polynomial ana...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Yuming, Wang Tian, Jin Chaopeng, Luo College of Information Science and Engineering Hunan Provincial Key Laboratory of Intelligent Computhing and Language Information Processing Science and Technology on Near-Surface Detection Laboratory Hunan Normal University Changsha China College of Electronic Science and Technology Science and Technology on Near-Surface Detection Laboratory National University of Defense Technology Changsha China Science and Technology on Near-Surface Detection Laboratory Wuxi214035 China

ISBN: (纸本)9781728129129

Aimed at the segmentation problem of ultrawideband synthetic aperture radar (UWB SAR) image, a novel algorithm based on polynomial analysis of statistical distribution is proposed in this letter. Firstly, we estimate the probability density function (PDF) for each pixel via sparse decomposition of which the dictionary consists of orthogonal polynomials (OP). Secondly, the weighting coefficients of corresponding OP are used to segment image using their maximum value. The experimental results validate the efficiency of this algorithm. © 2019 IEEE.

关键词： Synthetic aperture radar

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