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9th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2024

作者： Hu, Tao Zhang, Zan Bu, Chenyang Li, Lei Key Laboratory of Knowledge Engineering with Big Data The Ministry of Education of China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9798350373554

Graph pattern matching is a technique widely used in various fields such as protein structure analysis, social group querying, and expert localization. This technique involves finding matching subgraphs in large social networks that align with the patterns specified in the pattern graph. In this paper, we focus on a specific sub-problem in social group querying, known as the cooperative team query, which arises from practical applications, where the nodes in the pattern graph and the data graph represent team member entities, while the edges represent their social relationships. We note that the requirements of many teams in the real world are dynamic, necessitating iterative computation for graph pattern matching using traditional methods. To address this challenge in highly dynamic systems, we propose a graph pattern matching method based on core pattern graph matching cache. This approach involves extracting the core pattern graph, and comprising core team members based on the characteristics of cooperative teams. The core graph-based matching cache enables the second half of the algorithm to operate on an order-of-magnitude smaller graph, significantly improving efficiency. Additionally, the multi-threaded approach fully leverages hardware resources, synchronizing multiple matching result of the core pattern graph to reduce matching time. Experimental results on three real social network datasets demonstrate that our proposed algorithm, Core Pattern Graph Matching Cache-based Multi-threaded Exploration (CCMTE), significantly outperforms existing methods in terms of efficiency. © 2024 IEEE.

关键词： Efficiency

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A survey on deep learning for polyp segmentation: techniques, challenges and future trends

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Visual Intelligence 2025年第1期3卷 1-20页

作者： Mei, Jiaxin Zhou, Tao Huang, Kaiwen Zhang, Yizhe Zhou, Yi Wu, Ye Fu, Huazhu PCA Lab Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Computer Science and Engineering Southeast University Nanjing China Institute of High Performance Computing A*STAR Singapore Singapore

Early detection and assessment of polyps play a crucial role in the prevention and treatment of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist clinicians in accurately locating and segmenting polyp regions. In the past, people often relied on manually extracted lower-level features such as color, texture, and shape, which often had problems capturing global context and lacked robustness to complex scenarios. With the advent of deep learning, more and more medical image segmentation algorithms based on deep learning networks have emerged, making significant progress in the field. This paper provides a comprehensive review of polyp segmentation algorithms. We first review some traditional algorithms based on manually extracted features and deep segmentation algorithms, and then describe benchmark datasets related to the topic. Specifically, we carry out a comprehensive evaluation of recent deep learning models and results based on polyp size, taking into account the focus of research topics and differences in network structures. Finally, we discuss the challenges of polyp segmentation and future trends in the field. © The Author(s) 2025.

关键词： Comprehensive evaluation Deep learning Medical imaging Polyp segmentation

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Dual Fusion Network for Hyperspectral Semantic Segmentation 12th

Dual Fusion Network for Hyperspectral Semantic Segmentation

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12th International Conference on Image and Graphics, ICIG 2023

作者： Ding, Xuan Gu, Shuo Yang, Jian PCA Laboratory Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Laboratory of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783031463075

With the development of imaging technology, it becomes increasingly easy to obtain hyperspectral images (HSI) containing rich spectral information. The application of hyperspectral images in autonomous driving is expected to become a reality. Hyperspectral images have higher dimensions and more information than RGB images, which brings the challenge of training with limited samples. It is not easy to train satisfactory semantic segmentation models directly from hyperspectral images. In this paper, we propose a hyperspectral dual-fusion (hyperDF) network that can fully utilize the pre-training knowledge of the RGB modality to improve the performance of hyperspectral semantic segmentation. Specifically, we generate pseudo-color images from hyperspectral images to simulate RGB signals in order to make better use of the pre-trained RGB semantic segmentation models. The pseudo-color and hyperspectral images are processed in a dual encoder structure and then fused through a channel-wise attention fusion module. Finally, a multi-scale decoder injected with low-level features is used to predict the semantic segmentation results. Experimental results on the Hyperspectral City V2.0 dataset show that our method achieves state-of-the-art results, with a mIoU of 51.68%. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Semantic Segmentation

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Investigation of the J-TEXT plasma events by k-means clustering algorithm

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Plasma science and technology 2023年第8期25卷 38-43页

作者：李建超张晓卿张昱 Abba Alhaji BALA 柳惠平周帼红王能超李达陈忠勇杨州军陈志鹏董蛟龙丁永华 the J-TEXT Team Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of TechnologyWuhan 430205People's Republic of China International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People's Republic of China Department of Physics Federal University DutseJigawa 720101Nigeria 不详

Various types of plasma events emerge in specific parameter ranges and exhibit similar characteristics in diagnostic signals,which can be applied to identify these events.A semisupervised machine learning algorithm,the k-means clustering algorithm,is utilized to investigate and identify plasma events in the J-TEXT *** method can cluster diverse plasma events with homogeneous features,and then these events can be identified if given few manually labeled examples based on physical understanding.A survey of clustered events reveals that the k-means algorithm can make plasma events(rotating tearing mode,sawtooth oscillations,and locked mode)gathering in Euclidean space composed of multi-dimensional diagnostic data,like soft x-ray emission intensity,edge toroidal rotation velocity,the Mirnov signal amplitude and so *** on the cluster analysis results,an approximate analytical model is proposed to rapidly identify plasma events in the J-TEXT *** cluster analysis method is conducive to data markers of massive diagnostic data.

关键词： k-means cluster analysis plasma event machine learning

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Unveiling impacts of PMD on spectral modulations in PM-fiber-based ultrafast amplifiers

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Chinese Optics Letters 2024年第12期22卷 57-62页

作者： Shang Wang Guanguang Gao Zhenhua Cong Zhaojun Liu Zhigang Zhao Key Laboratory of Laser&Infrared System Ministry of EducationShandong UniversityQingdao 266237China School of Information Science and Engineering Shandong UniversityQingdao 266237China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China Shandong Provincial Key Laboratory of Laser Technology and Application Shandong UniversityQingdao 266237China

In this work,polarization mode dispersion(PMD)in polarization-maintaining(PM)fibers,to the best of our knowledge,is first proposed and experimentally proved to be responsible for severe spectral modulations in ultrafast PM fiber amplifiers,the introduction of which can give reasonable explanation for the dense spectral ripples imposed on the spectra of amplified lasers from the commonly used all-PM-fiber or hybrid“PM-fiber+bulk crystal”amplifiers,including both high-power amplifiers with remarkable nonlinear effects(self-phase modulation,SPM)and even low-power amplifiers with negligible nonlinear effects.

关键词： spectral modulation polarization mode dispersion self-phase modulation polarization-maintaining fibers

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Time-domain Hybrid Method for the Coupling Analysis of Curved Power Lines Illuminated by Early-time High-altitude Electromagnetic Pulse

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Applied Computational Electromagnetics Society Journal 2024年第11期39卷 952-960页

作者： Ye, Zhihong Gao, Zhiwei Hong, Guangzhi Tong, Chen Ji, Ziran Xiao, Zeyu State Key Laboratory of Power Grid Environmental Protection Wuhan430070 China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China School of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang050043 China

An efficient time-domain field-to-line hybrid method is presented to realize the rapid coupling calculation of curved power lines (CPLs) illuminated by Early-Time (E1) high-altitude electromagnetic pulse (HEMP). Firstly, improved transmission line equations are derived by ideal conductor boundary conditions and transmission line theory, which are employed to construct the E1 HEMP coupling model of CPLs. Then, based on the image principle, a rapid calculation method for the excitation fields of CPLs is investigated, and improved transmission line equations are solved by the finite-difference time-domain (FDTD) method to achieve fast iterative calculation of voltage and current responses along CPLs. Finally, relevant numerical simulations are utilized to verify the accuracy and efficiency of the proposed method. On this basis, the impact of power line lengths, heights, and ground electromagnetic parameters on E1 HEMP coupling of CPLs is analyzed. © ACES.

关键词： Hemp

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Adaptive Multimodal Fusion: Dynamic Attention Allocation for Intent Recognition 39

Adaptive Multimodal Fusion: Dynamic Attention Allocation for...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Hu, Bo Zhang, Kai Zhang, Yanghai Ye, Yuyang RWTH Aachen University Germany State Key Laboratory of Cognitive Intelligence University of Science and Technology of China China Department of Management Science and Information Systems Rutgers University United States

ISBN: (纸本)157735897X

In recent years, deep multimodal learning has seen significant advancements. However, there remains a lack of multimodal fusion methods capable of dynamically adjusting the weighting of information both within and across modalities based on input samples. In the domain of multimodal intent recognition, the text modality often contains the most relevant information for intent detection, while the audio and visual modalities provide comparatively less critical information. There is a significant variation in the density of important information across different modalities and samples. To address this challenge, we propose a Dynamic-attention Allocation Fusion (DAF) method with an adaptive network structure that dynamically allocates attention both within individual modalities and across multiple modalities. This approach enables the model to focus more effectively on the most informative modalities and their respective internal features. Furthermore, we introduce a Multi-View Contrastive Learning framework based on DAF (MVCL-DAF). This framework uses distinct and isolated modules to process information from various modalities, taking inspiration from the way the human brain processes multimodal information. Each modality independently infers intent using its respective module, while DAF integrates the multimodal information to produce a comprehensive global intent prediction. The text modality, functioning as the primary modality due to its rich semantic content, guides the other modules in the multi-view contrastive learning process. Extensive experiments demonstrate that our approach significantly outperforms existing state-of-the-art methods. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

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240 nm AlGaN-based deep ultraviolet micro-LEDs:size effect versus edge effect

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Journal of Semiconductors 2024年第1期45卷 55-62页

作者： Shunpeng Lu Jiangxiao Bai Hongbo Li Ke Jiang Jianwei Ben Shanli Zhang Zi-Hui Zhang Xiaojuan Sun Dabing Li State Key Laboratory of Luminescence and Applications Changchun Institute of OpticsFine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Electronic Materials and Devices of Tianjin School of Electronics and Information EngineeringHebei University of TechnologyTianjin 300401China

240 nm AlGaN-based micro-LEDs with different sizes are designed and ***,the external quantum efficiency(EQE)and light extraction efficiency(LEE)are systematically investigated by comparing size and edge ***,it is revealed that the peak optical output power increases by 81.83%with the size shrinking from 50.0 to 25.0μ***,the LEE increases by 26.21%and the LEE enhancement mainly comes from the sidewall light *** notably,transversemagnetic(TM)mode light intensifies faster as the size shrinks due to the tilted mesa side-wall and Al reflector ***,when it turns to 12.5μm sized micro-LEDs,the output power is lower than 25.0μm sized *** underlying mechanism is that even though protected by SiO2 passivation,the edge effect which leads to current leakage and Shockley-Read-Hall(SRH)recombination deteriorates rapidly with the size further ***,the ratio of the p-contact area to mesa area is much lower,which deteriorates the p-type current spreading at the mesa *** findings show a role of thumb for the design of high efficiency micro-LEDs with wavelength below 250 nm,which will pave the way for wide applications of deep ultraviolet(DUV)micro-LEDs.

关键词： AlGaN deep ultraviolet micro-LEDs light extraction efficiency size effect edge effect

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A Scholar of Dignity:Remembering Peter Luh

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1895-1897页

作者： Fei-Yue Wang Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100190China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

It was a shock and disbelief to learn of Peter's death last *** me,he was so fit in his figure,so healthy in his lifestyle,so mild and mindful in his social behavior,and so devout in his religious belief,......,I ... 详细信息

关键词： religious Scholar belief

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Simultaneous acceleration of sulfur reduction and oxidation on bifunctional electrocatalytic electrodes for quasi-solid-state Zn–S batteries

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science China Chemistry 2024年第5期67卷 1531-1538页

作者： Mingli Wang Hong Zhang Tianhang Ding Fangjun Wu Lin Fu Bin Song Pengfei Cao Ke Lu Institutes of Physical Science and Information Technology School of Materials Science and EngineeringKey Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationAnhui UniversityHefei 230601China Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 230026China School of Chemistry and Chemical Engineering Harbin Institute of TechnologyHarbin 150001China School of Chemistry and Chemical Engineering Guizhou UniversityGuiyang 550025China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123China State Key Lab of Organic-Inorganic Composites Beijing University of Chemical TechnologyBeijing 100029China

The incomplete sulfur reduction and high ZnS re-oxidation energy barrier along with severe side reactions during the battery cycling compromise the practical application of Zn–S electrochemistry. Herein, a bifunctional electrocatalytic sulfur matrix that simultaneously accelerates the sulfur reduction and ZnS oxidation is proposed to realize a highly-efficient Zn–S cell. It is revealed that the N-heteroatom hotspots are more favorable for facilitating the conversion of S to ZnS while the CoO nanocrystal substantially lowers the ZnS activation energy barrier thereby suppressing the formation of disproportionation species(e.g.,SO_(4)^(2-)) and accumulation of inactive ZnS. Accordingly, the Co O anchored on the N-doped carbon-supported sulfur cathode delivers a high Zn^(2+)storage capacity of 1,172 m Ahg^(-1)and outstanding cycling stability with a capacity retention of 71.6% after500 cycles with a high average Coulombic efficiency of 97.8%. Simultaneously, the stable cycling of solid-state Zn–S pouch cells with an energy density of 585 Whkg^(-1)sulfuris also demonstrated. Moreover, the postmortem analysis reveals that the degradation of Zn–S cells is mainly attributed to the limited reversibility of Zn anodes rather than the ZnS decomposition and/or accumulation. The approach to the bidirectional catalysis manipulated the sulfur redox provides a new perspective to realize the theoretical potentials of Zn–S cells.

关键词： Zn–S battery bifunctional catalysts solid-state battery sulfur redox degradation mechanism

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