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15th International Conference on intelligent information Hiding and Multimedia Signal processing, IIH-MSP 2019, held in conjunction with the 12th International Conference on Frontiers of information Technology, Applications and Tools, FITAT 2019

作者： Lu, Chunhua Zhang, Fuquan Li, Yunpeng School of Electronic and Information Engineering Anshun University Guizhou561000 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China Computer School Beijing Information Science and Technology University Beijing100101 China

ISBN: (纸本)9789811397097

Teachers are never the only teacher in the class, especially in online e-learning environment. The key learner who is supposed to be more active and eager to spread knowledge and motivation to other classmates has a huge potentiality to improve the quality of teaching. However, the identification of such key learner is challenging which needs lots of human experience, especially when the contact channels between teachers and students are much more monotonous in online e-learning environment. Inspired by resistance distance theory, in this paper, we apply resistance distance and centrality into an interactive network of learners to identify key learner who can effectively motivate the whole class with discussion in e-learning platform. First, we define the terms of interactive network of learners with the node, edge, and graph. Then the distance between nodes is replaced with effective resistance distance to gain better understanding of propagation among the learners. Afterward, Closeness Centrality is utilized to measure the centrality of each learner in interactive network of learners. Experimental results show that the centrality we use can cover and depict the learners’ discussion activities well, and the key learner identified by our approach under apposite stimuli can effectively motivate the whole class’ learning performance. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Graphic methods

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Energy-Efficient Virtual Machine Migration Algorithm in Data Centers 3

Energy-Efficient Virtual Machine Migration Algorithm in Data...

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3rd International conference on Computer, Big Data and Artificial Intelligence, ICCBDAI 2022

作者： Wu, Xiaodong Zeng, Taisheng School of Mathmatics and Computer Science Quanzhou Normal University Fujian Province Quanzhou362000 China Fujian Provincial Key Laboratory of Intensive Computing Fujian Province Quanzhou362000 China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University Fujian Province Quanzhou362000 China

The issue of data center power consumption is becoming increasingly serious. One of the most effective techniques for increasing resource utilization and lowering power consumption is virtual machine consolidation. This paper proposes a threshold-based energy-efficient and SLA-aware algorithm for virtual machine migration and consolidation. Based on statistics and analysis of historical virtual machine status, the algorithm dynamically obtains the upper CPU utilization threshold of the physical servers and identifies whether to perform the virtual machine migration, so as to reduce the number of active hosts to save energy. The experimental results demonstrate that the proposed algorithm has better comprehensive performance. When compared to the existing algorithm, our method can effectively decrease energy consumption and SLA violations. © Published under licence by IOP Publishing Ltd.

关键词： Electric power utilization

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Superposed Transparency Effect and Entanglement Generation with Hybrid System of Photonic Molecule and Dipole Emitter

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Chinese Physics Letters 2019年第3期36卷 41-44页

作者： Ji-Bing Yuan Zhao-Hui Peng Shi-Qing Tang Deng-Yu Zhang College of Physics and Electronic Engineering and Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal University Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics and Synergetic Innovation Center for Quantum Effects and ApplicationsHunan Normal University Institute of Modern Physics and Department of Physics Hunan University of Science and Technology

We theoretically investigate the transparency effect with a hybrid system composed of a photonic molecule and dipole emitter. It is shown that the transparency effect incorporates both the coupled resonator-induced transparency(CRIT) effect and the dipole-induced transparency(DIT) effect. It is found that the superposed transparency windows are consistently narrower than the CRIT and DIT transparency windows. Benefiting from the superposed transparency effect, the photonic Faraday rotation effect could be realized in the photonic molecule system, which is useful for entanglement generation and quantum information processing.

关键词： DIT Transparency Photonic Molecule Emitter

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Finite-Time Fuzzy Sliding Mode control for Nonlinear Descriptor Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1141-1152页

作者： Zhixiong Zhong Xingyi Wang Hak-Keung Lam Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou 350121China College of Mechanical and Electronic Engineering Fujian Agriculture and Forestry UniversityFuzhou 350108China Department of Engineering King’s College LondonLondonWC2R 2LSUnited Kingdom

This article addresses the finite-time boundedness(FTB)problem for nonlinear descriptor ***,the nonlinear descriptor system is represented by the Takagi-Sugeno(T-S)model,where fuzzy representation is assumed to be appearing not only in both the state and input matrices but also in the derivative *** using a descriptor redundancy approach,the fuzzy representation in the derivative matrix is reformulated into a linear ***,we introduce a fuzzy sliding mode control(FSMC)law,which ensures the finite-time boundedness(FTB)of closed-loop fuzzy control systems over the reaching phase and sliding motion ***,by further employing the descriptor redundancy representation,the sufficient condition for designing FSMC law,which ensures the FTB of the closed-loop control systems over the entire finite-time interval,is derived in terms of linear matrix inequalities(LMIs).Finally,a simulation study with control of a photovoltaic(PV)nonlinear system is given to show the effectiveness of the proposed method.

关键词： Finite-time boundedness(FTB) fuzzy sliding mode control(FSMC) Takagi-Sugeno(T-S)fuzzy descriptor system

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MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing 48

MSP-Former: Multi-Scale Projection Transformer for Single Im...

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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023

作者： Chen, Sixiang Ye, Tian Liu, Yun Liao, Taodong Jiang, Jingxia Chen, Erkang Chen, Peng Southwest University College of Artificial Intelligence Chongqing China Jimei University School of Ocean Information Engineering Xiamen China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing China

ISBN: (纸本)9781728163277

Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to learn effective snow removal. In order to handle the diverse scenes, we propose a multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degradation features in a multi-path manner, and integrates comprehensive scene context information for clean reconstruction via self-attention operation. For the local details of various snow degradations, the local capture module is introduced in parallel to assist in the rebuilding of a clean image. Such design achieves the SOTA performance on three desnowing benchmark datasets while costing the low parameters and computational complexity, providing a guarantee of practicality. © 2023 IEEE.

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Image Definition Evaluation Function Based on Improved Maximum Local Variation and Focusing Window Selection 1

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6th International Conference on Data Mining and Big Data, DMBD 2021

作者： Li, Shiyun Chen, Jian Wan, Jiaze Li, Zuoyong Lin, Li School of Electronic Electrical Engineering and Physics Fujian University of Technology Xueyuan Road Fujian Fuzhou350118 China College of Computer and Control Engineering Minjiang University No. 200 Xiyuangong Road Fujian Fuzhou350121 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (数字)9789811675027

ISBN: (纸本)9789811675010

Aiming at the problem that commonly used image definition evaluation functions in the focusing process are sensitive to noise, we propose a new image definition evaluation function based on improved maximum local variation and focusing window selection. Firstly, the focusing window is selected by gradient accumulation of a 4-directional Scharr operator in order to reduce the calculation complexity and improve the accuracy of evaluation results. Secondly, an improved 3-neighbors method based on the maximum local variation is proposed to decrease the change in scores for noisy images. Finally, the standard deviation of the improved maximum local variation distribution is used as the measure of clarity. The experimental results show that compared with the method using maximum local variation, the proposed method has better unbiasedness and sensitivity. Compared with the commonly used evaluation functions, the proposed method has better noise immunity and high sensitivity. Compare with other no-reference image quality assessment algorithms, it has better monotonicity, unimodality, unbiasedness, sensitivity and real-time performance as well. The proposed method is suitable for the fine focusing stage with high real-time performance. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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Core-shell nanoparticle enhanced Raman spectroscopy in situ probing the composition and evolution of interfacial species on PtCo surfaces

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Nano Research 2024年第6期17卷 4687-4692页

作者： Jing Liu Han-Liang Zhong Xiangyu Li Mu-Fei Yue Wei-Min Yang Xueqiu You Jing-Hua Tian Yao-Hui Wang Jian-Feng Li Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing School of Ocean Information EngineeringJimei UniversityXiamen 361021China College of Chemistry Fuzhou UniversityFuzhou 350108China State Key Laboratory of Physical Chemistry of Solid Surfaces MOE Key Laboratory of Spectrochemical Analysis and InstrumentationiChEMCollege of Chemistry and Chemical EngineeringCollege of MaterialsCollege of EnergyXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Shenzhen Research Institute of Xiamen University Shenzhen 518000China

The composition and evolution of interfacial species play a key role during electrocatalytic *** the structural evolution and intermediate during catalytic process by in situ characterization can shed new light on the electrocatalytic reaction mechanism and develop highly efficient ***,directly probing the interfacial species is extremely difficult for most spectroscopic techniques due to complicated interfacial environment and ultra-low surface ***,electrochemical core-shell nanoparticle enhanced Raman spectroscopy is utilized to probe the composition and evolution processes of interfacial species on Au@Pt,Au@Co,and Au@PtCo core-shell nanoparticle *** spectral evidences of interfacial intermediates including hydroxide radical(OH*),superoxide ion(O_(2)^(−)),as well as metal oxide species are directly captured by in situ Raman spectroscopy,which are further confirmed by the both isotopic experiment and density functional theory *** results provide a mechanistic guideline for the rational design of highly efficient electrocatalysts.

关键词： in situ Raman core-shell nanoparticle PtCo interfacial species composition and evolution

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Research on Evasion Strategy of Aircraft Based on Deep Reinforcement Learning 14th

Research on Evasion Strategy of Aircraft Based on Deep Reinf...

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14th International Conference on Genetic and Evolutionary Computing, ICGEC 2021

作者： Li, Ye Zhang, Lin Wang, Kaixuan Zhang, Fuquan Fan, Yi China Academy of Launch Vehicle Technology Beijing100076 China Capital Aerospace Machinery Company Beijing100076 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (纸本)9789811684296

In order to improve the autonomous penetration capability of aircraft, a method for generating aircraft maneuver avoidance strategies based on deep reinforcement learning is proposed. In order to solve the sparse reward problem of penetration reinforcement learning, the initialization process and sampling method of deep Q Network are improved, and the convergence efficiency of the learning algorithm is improved. Firstly, a penetration threat scene and an offensive and defensive confrontation motion model are established, and the relative motion state of the interceptor and the typical maneuver mode of the balanced flight section are selected as the state space and the action space. In the learning process, the aircraft is used as an agent to perform a reinforcement learning exploration process through confrontation simulations to train the maneuver value network so that it can finally make autonomous decisions based on the threat situation. Finally, the simulation experiment results show that the algorithm proposed in this paper can effectively generate maneuver penetration strategies and support the intelligent game of aircraft. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Bone Marrow Cell Segmentation Based on Improved U-Net 1

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6th International Conference on Data Mining and Big Data, DMBD 2021

作者： Jin, Lingmin Yu, Zhaochai Fan, Haoyi Teng, Shenghua Li, Zuoyong College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China School of Information Engineering Zhengzhou University Zhengzhou450001 China

ISBN: (数字)9789811674761

ISBN: (纸本)9789811674754

Automatic segmentation of bone marrow cells plays an important role in the diagnosis of many blood diseases such as anemia and leukemia. Due to the complex morphology and wide variety of bone marrow cells, their segmentation is still a challenging task. To improve the accuracy of bone marrow cell segmentation, we propose an end-to-end U-shaped network based on the pyramid residual convolution and the attention mechanism. Specifically, the standard convolution and dilated convolution are combined as its feature encoder, which designs a pyramid residual convolution block to extract multi-scale features. Then, the attention gating mechanism is introduced into each skip connection module for fusing the shallow and deep information. Finally, the proposed method combines convolution and deconvolution for feature decoding to achieve the final segmentation of bone marrow cells. Experiments with quantitative and qualitative comparisons are carried out on a self-built bone marrow smear dataset. Experimental results demonstrate the superiority of the proposed method over several state-of-the-art methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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Generalized Self-Adaption Network for Domain Adaptation 2

Generalized Self-Adaption Network for Domain Adaptation

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2nd International Conference on Artificial Intelligence and intelligent information processing, AIIIP 2023

作者： Bian, Yongheng Ke, Xiao College of Computer and Data Science Fuzhou University Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou350116 China Key Laboratory of Spatial Data Mining & Information Sharing Ministry of Education Fuzhou350003 China

ISBN: (纸本)9798350371451

The purpose of domain adaptation is to transfer knowledge learned in the labeled source domain to unlabeled but related target domains without requiring a large number of target domain labels. The latest method of domain adaptation mainly adjusts the distribution of the source and target domains to adapt to the target domain. Despite significant success, when there are significant distribution differences between the source and target domains, the adaptability in the target domain still decreases, which may be due to insufficient exploration of domain specific features leading to domain offset issues. To address this issue, we propose the GSA-NET framework in this article. We designed an adversarial dropout method to improve the generalization performance of the model in the target domain by pushing the decision boundary away from the feature dense region. At the same time, in order to effectively match the distribution of advanced features across domains, we deploy feature adaptation modules before the classification layer, which can significantly reduce domain differences. Our experiments on two cross domain benchmarks, Office Home and Office-31, have shown that the proposed method is significantly superior to existing methods. © 2023 IEEE.

关键词： Computer vision

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