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State and parameter identification of linearized water wave equation via adjoint method

science China(information sciences) 2024年第10期67卷 283-297页

作者： Yang YU Cheng-Zhong XU Hai-Long PEI Jinpeng YU School of Automation Qingdao University LAGEP Batiment CPE University Claude Bernard-Lyon 1 School of Automation Science and Engineering Key Laboratory of Autonomous Systems and Networked ControlMinistry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle SystemSouth China University of Technology

In this paper, we focus on the state and parameter identification problem of a hydrodynamical system. This system is modeled as a linearized water wave equation(LWWE), a hyperbolic state-space model coupled with a Laplace equation. We assume that the wave elevation at two distinct points is the only measurement of water waves. We show that the state and water depth can be reconstructed from this point measurement records. The identification problem is recast as an optimization problem over an infinite-dimensional space. We propose the adjoint method-based identification algorithm to generate an estimated state and water depth. We then performed a numerical simulation to show the effectiveness of our designed algorithm by comparing it with existing studies.

关键词： linearized water wave equation (LWWE) point observation state estimation parameter identification adjoint method numerical simulation

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Adversarial dual decision-based model for event-related opinion sentence recognition

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Multimedia Tools and Applications 2024年 1-18页

作者： Xiang, Yan Qin, Yuan Yu, Zhengtao Huang, Yuxin Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Artificial Intelligence Kunming University of Science and Technology Kunming650500 China

Event-related opinion sentences recognition aims to mine the valuable comments discussing about the specific event from the mass of microblogs comments. It’s difficult to label sufficient comments for a new microblogs event, and domain adaptation methods are suitable for this task, which can transfer the knowledge from the source domain(labeled event) to the target domain (unlabeled event). However, existing domain adaptation models do not make full use of the domain invariance to realize categories alignments of the two domains. Therefore, we propose a adversarial dual decision model for opinion sentences recognition, which takes advantage of the domain invariance that the opinion sentences are correlated with the event description. The proposed model has two generators to obtain different event-correlated features, and two classifiers to make dual decisions based on the two features. Through the adversarial process of generators and classifiers, the model completes the category feature alignment and realizes the opinion sentences recognition for the new event. The comparative experiment results show that our model outperforms the state-of-the-art models on six opinion sentences recognition tasks. In addition, we verify the effectiveness of each component of our model by ablation experiments. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Adversarial machine learning

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Transmission of orbital angular momentum modes in Angular Symmetry Fibers

Transmission of orbital angular momentum modes in Angular Sy...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on information Photonics and Optical Communications, IPOC 2024

作者： Qin, Suwan Rao, Xiongfeng Yang, Li Department of Electronic Engineering and Information Science University of Science and Technology of China Key Laboratory of Electromagnetic Space Information Chinese Academy of Science Hefei China

We propose an angular symmetry fiber and demonstrate its capability for the transmission of optical orbital angular momentum modes by using numerical analysis based on finite element method. © 2024 IEEE.

ISBN: (纸本)9798350379266

关键词： Optical fibers

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Optimization of transverse unidirectional scattering by morphology modification of irregular V-shaped silicon nanoantennas

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Optoelectronics Letters 2025年第3期21卷 129-135页

作者： ZENG Ming ZHAO Feng WANG Xianghui School of Electrical and Information Engineering Tianjin UniversityTianjin300072China Institute of Modern Optics Tianjin Key Laboratory of Micro-scale Optical Information Science and TechnologyNankai UniversityTianjin300350China

A scheme based on irregular V-shaped silicon nanoantennas is proposed to optimize transverse unidirectional scattering under plane wave *** methods of designing regular shapes offer fewer parameters and higher search ***,due to the limitations of regular shapes,it is challenging to meet high-precision design *** shape design allows for a broader range of adjustments,but the complexity of shape parameters leads to lower search efficiency and a higher likelihood of converging to local optima.

关键词： irregular v shaped silicon nanoantennas plane wave irradiation design efficiency plane wave irradiationtraditional optimize transverse unidirectional scattering morphology modification transverse unidirectional scattering search efficiency

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Motion simulation of moorings using optimized LSTM neural network

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Journal of Oceanology and Limnology 2023年第5期41卷 1678-1693页

作者： Zhiyuan ZHUANG Fangjie YU Ge CHEN Department of Marine Technology College of Information Science and EngineeringOcean University of ChinaQingdao 266100China Laoshan Laboratory Qingdao 266237China

Mooring arrays have been widely deployed in sustained ocean observation in high resolution to measure finer dynamic features of marine ***,the irregular posture changes and nonlinear response of moorings under the effect of ocean currents face huge challenges for the deployment of mooring arrays,which may cause the deviations of measurements and yield a vacuum of observation in the upper *** developed a data-driven mooring simulation model based on LSTM(long short-term memory)neural network,coupling the ocean current with position data from moorings to predict the motion of moorings,including single-step output prediction and multi-step *** on the predictive information,the formation of the mooring array can be adjusted to improve the accuracy and integrity of ***,we proposed the cuckoo search(CS)optimization algorithm to tune the parameters of LSTM,which improves the robustness and generalization of the *** utilize the datasets observed from moorings anchored in the Kuroshio Extension region to train and validate the simulation *** experimental results demonstrate that the model can remarkably improve prediction accuracy and yield stable ***,compared with other optimization algorithms,CS is more efficient and performs better in simulating the motion of moorings.

关键词： mooring motion simulation long short-term memory(LSTM) optimization strategy hybrid deep learning

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Seastar: A Cache-Efficient and Load-Balanced Key-Value Store on Disaggregated Memory

Seastar: A Cache-Efficient and Load-Balanced Key-Value Store...

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2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Du, Jingwen Wang, Fang Feng, Dan Zeng, Dexin Yi, Sheng Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System China School of Computer Science and Technology Huazhong University of Science and Technology China Shenzhen Huazhong University of Science and Technology Research Institute China

ISBN: (纸本)9798350358711

In modern datacenters, memory disaggregation un-packs monolithic servers to build independent network-connected compute and memory pools, greatly improving resource uti-lization. Existing memory-disaggregated key-value stores adopt ownership sharing or ownership partitioning for request scheduling and they all show poor performance and scalability. The former generates multiple cache misses and multiple network round trips due to poor cache locality, while the latter fails to fully use resources on all Compute Nodes (CNs) due to load imbalance. In this paper, we propose Seastar, a fast and scalable key-value store that achieves high cache locality as well as load balancing. To enable high concurrency and ensure linearizability, Seastar exploits a self-verification version chain to provide out-of-place atomic updates and ensure consistent reads. To improve cache locality, Seastar leverages a pair-based ownership assigning scheme to assign the processing permission of requests corre-sponding to each key to a CN pair through two independent hash functions. To ensure load balancing among CNs, Seastar proposes a decentralized power-of-two-choices routing scheme to route the requests to the less-loaded CNs in CN pairs for handling. Experimental results demonstrate that Seastar improves the throughput by up to 6.7x and significantly reduces the latency compared with state-of-the-art memory-disaggregated key-value stores. © 2024 IEEE.

关键词： Scalability

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On the Rique Number of Series-Parallel Graphs and Planar Bipartite Graphs 2nd

On the Rique Number of Series-Parallel Graphs and Planar ...

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2nd International Conference on Applied Algorithms, ICAA 2025

作者： Azgor, Sk Ruhul Rahman, Md. Saidur Graph Drawing and Information Visualization Laboratory Department of Computer Science and Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (纸本)9783031845420

The restricted input queue (rique) is a data structure which is recently introduced to study linear layout of graphs. The rique data structure is a special queue where insertions occur only at the head and removals occur at both the head and the tail. Considering a rique data structure the goal of a linear layout of a graph is to find a linear order of the vertices of the graph and a partition of its edges into pages such that the edges in each page follow the restriction of rique in the underlying order. The rique number of a graph is the smallest number of pages required for linear layout of the graph with rique data structure. A characterization of graphs for admitting a single page rique layout and some bounds on the rique number of complete and complete bipartite graphs are known. In this paper, we show that the rique number of series-parallel graphs as well as planar bipartite graphs is 2. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Directed graphs

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Satellite-observed significant improvement in nearshore transparency of the Bohai Sea during pollution control

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Acta Oceanologica Sinica 2023年第12期42卷 51-62页

作者： Xuyan Li Jinzhao Xiang Liudi Zhu Zhibin Yang Ting Wei Bing Mu Xiaobo Zhang Tingwei Cui School of Atmospheric Sciences Sun Yat-Sen University/Key Laboratory of Tropical Atmosphere-Ocean SystemMinistry of Education/Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082China Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266071China

The Bohai Sea(BS)is the unique semi-closed inland sea of China,characterized by degraded water quality due to significant terrestrial pollution *** order to improve its water quality,a dedicated action named“Uphill Battles for Integrated Bohai Sea Management”(UBIBSM,2018–2020)was implemented by the Chinese *** evaluate the action effectiveness toward water quality improvement,variability of the satelliteobserved water transparency(Secchi disk depth,Z_(SD))was explored,with special emphasis on the nearshore waters(within 20 km from the coastline)prone to terrestrial influence.(1)Compared to the status before the action began(2011–2017),majority(87.3%)of the nearshore waters turned clear during the action implementation period(2018–2020),characterized by the elevated Z_(SD)by 11.6%±12.1%.(2)Nevertheless,the improvement was not spatially uniform,with higher Z_(SD)improvement in provinces of Hebei,Liaoning,and Shandong(13.2%±16.5%,13.2%±11.6%,10.8%±10.2%,respectively)followed by Tianjin(6.2%±4.7%).(3)Bayesian trend analysis found the abrupt Z_(SD)improvement in April 2018,which coincided with the initiation of UBIBSM,implying the water quality response to pollution *** importantly,the independent statistics of land-based pollutant discharge also indicated that the significant reduction of terrestrial pollutant input during the UBIBSM action was the main driver of observed Z_(SD)improvement.(4)Compared with previous pollution control actions in the BS,UBIBSM was found to be the most successful one during the past 20 years,in terms of transparency improvement over nearshore *** presented results proved the UBIBSM-achieved remarkable water quality improvement,taking the advantage of long-term consistent and objective data record from satellite ocean color observation.

关键词： Secchi disk depth transparency water quality nearshore Bohai Sea satellite ocean color remote sensing pollution control

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Automated garden-insect recognition using improved lightweight convolution network

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information Processing in Agriculture 2023年第2期10卷 256-266页

作者： Zhankui Yang Xinting Yang Ming Li Wenyong Li College of Computer Science and Technology Beijing University of TechnologyBeijing 100124China National Engineering Research Center for Information Technology in Agriculture Beijing 100089China National Engineering Laboratory for Quality and Safety Traceability Technology and Application of Agricultural Products Beijing 100089China

Automated recognition of insect category,which currently is performed mainly by agriculture experts,is a challenging problem that has received increasing attention in recent *** goal of the present research is to develop an intelligent mobile-terminal recognition system based on deep neural networks to recognize garden insects in a device that can be conveniently deployed in mobile ***-of-the-art lightweight convolutional neural networks(such as SqueezeNet and ShuffleNet)have the same accuracy as classical convolutional neural networks such as AlexNet but fewer parameters,thereby not only requiring communication across servers during distributed training but also being more feasible to deploy on mobile terminals and other hardware with limited *** this research,we connect with the rich details of the low-level network features and the rich semantic information of the high-level network features to construct more rich semantic information feature maps which can effectively improve SqueezeNet model with a small computational *** addition,we developed an off-line insect recognition software that can be deployed on the mobile terminal to solve no network and the timedelay problems in the *** demonstrate that the proposed method is promising for recognition while remaining within a limited computational budget and delivers a much higher recognition accuracy of 91.64%with less training time relative to other classical convolutional neural *** have also verified the results that the improved SqueezeNet model has a 2.3%higher than of the original model in the open insect data IP102.

关键词： Insect classification Mobile-terminal recognition SqueezeNet model Deep lightweight convolution network

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Multivariate Time Series Anomaly Detection Based on Spatial-Temporal Network and Transformer in Industrial Internet of Things

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Computers, Materials & Continua 2024年第8期80卷 2815-2837页

作者： Mengmeng Zhao Haipeng Peng Lixiang Li Yeqing Ren Information Security Center State Key Laboratory ofNetworking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and TelecommunicationsBeijing100876China Department of Information Science and Engineering Zaozhuang UniversityZaozhuang277160China

In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working *** the systems are attacked,timely identification of outliers in time series is critical to ensure *** many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these *** to the superior capability of Transformer in learning time series *** paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved ***,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are ***,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each *** scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each *** interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory *** introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph *** on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.

关键词： Multivariate time series anomaly detection spatial-temporal network Transformer

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