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Resilient multi-objective mission planning for UAV formation:A unified framework integrating task pre-and re-assignment

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Defence Technology(防务技术) 2025年第3期45卷 203-226页

作者： Xinwei Wang Xiaohua Gao Lei Wang Xichao Su Junhong Jin Xuanbo Liu Zhilong Deng Department of Engineering Mechanics State Key Laboratory of Structural AnalysisOptimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalianLiaoning 116024China School of Mathematics and Big Data Anhui University of Science and TechnologyHuainanAnhui 232001China School of Mathematical Science Dalian University of TechnologyDalianLiaoning 116024China Department of Airborne Vehicle Engineering Naval Aeronautical and Astronautical UniversityYantai 264001China

Combat effectiveness of unmanned aerial vehicle(UAV)formations can be severely affected by the mission execution *** the practical execution phase,there are inevitable risks where UAVs being destroyed or targets failed to be *** improve the mission reliability,a resilient mission planning framework integrates task pre-and re-assignment modules is developed in this *** the task pre-assignment phase,to guarantee the mission reliability,probability constraints regarding the minimum mission success rate are imposed to establish a multi-objective optimization *** an improved genetic algorithm with the multi-population mechanism and specifically designed evolutionary operators is used for efficient *** in the task-reassignment phase,possible trigger events are first analyzed.A real-time contract net protocol-based algorithm is then proposed to address the corresponding emergency *** the dual objective used in the former phase is adapted into a single objective to keep a consistent combat *** cases of different scales demonstrate that the two modules cooperate well with each *** the one hand,the pre-assignment module can generate high-reliability mission schedules as an elaborate mathematical model is *** the other hand,the re-assignment module can efficiently respond to various emergencies and adjust the original schedule within a *** corresponding animation is accessible at ***/video/BV12t421w7EE for better illustration.

关键词： Cooperative mission planning UAV formation Mission reliability Evolutionary algorithm Contract net protocol

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Explosive synchronization of multi-layer complex networks based on star connection between layers with delay

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Chinese Physics B 2023年第10期32卷 343-349页

作者：金彦亮韩钱源郭润珠高塬沈礼权 Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghai Institute for Advanced Communication and Data ScienceShanghai UniversityShanghai 200072China School of Communication and Information Engineering Shanghai UniversityShanghai 200000China

Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological *** recent years,researchers have focused on ES between single-layer and multi-layer *** research on complex networks with delay has focused on single-layer or double-layer networks,multi-layer networks are seldom *** this paper,we propose a Kuramoto model of frequency weights in multi-layer complex networks with delay and star connections between *** theoretical analysis and numerical verification,the factors affecting the backward critical coupling strength are *** results show that the interaction between layers and the average node degree has a direct effect on the backward critical coupling strength of each layer *** location of the delay,the size of the delay,the number of network layers,the number of nodes,and the network topology are revealed to have no direct impact on the backward critical coupling strength of the *** is introduced to explore the influence of delay and other related parameters on ES.

关键词： multi-layer networks Kuramoto model explosive synchronization delay

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GACP:graph neural networks with ARMA flters and a parallel CNN for hyperspectral image classification

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International Journal of Digital Earth 2023年第1期16卷 1770-1800页

作者： Jing Yang Jie Sun Yaping Ren Shaobo Li Shujie Ding Jianjun Hu School of Mechanical Engineering Guizhou UniversityGuiyangPeople’s Republic of China State Key Laboratory of Public Big Data Guizhou UniversityGuiyangPeople’s Republic of China School of Intelligent Systems Science and Engineering Jinan UniversityZhuhaiPeople’s Republic of China Department of Computer Science and Engineering University of South CarolinaColumbiaSCUSA

In recent years,the use of convolutional neural networks(CNNs)and graph neural networks(GNNs)to identify hyperspectral images(HSIs)has achieved excellent results,and such methods are widely used in agricultural remote sensing,geological exploration,and marine remote *** many generalization classification algorithms are designed for the purpose of learning a small number of samples,there is often a problem of a low utilization rate of position information in the empty spectral *** on this,a GNN with an autoregressive moving average(ARMA)-based smoothingfilter samples the node information in the null spectral domain and then captures the spatial information at the pixel level via spatial feature convolution;then,the null spectral domain position information lost by the CNN is located by a coordinate attention(CA)***,autoregressive,spatial convolution,and CA mechanisms are combined into multiscale features to enhance the learning capacity of the network for tiny *** conducted on the widely used Indian Pines(IP)dataset,the Botswana(BS)dataset,Houton 2013(H2013),and the WHU-Hi-HongHu(WHU)benchmark HSI dataset demonstrate that the proposed GACP technique can perform classification work with good accuracy even with a small number of training examples.

关键词： Graph neural networks word convolutional neural networks hyperspectral image classification attention mechanisms

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Contribution of Transmembrane Protein 68 to Triglyceride Synthesis and Lipid Droplet Formation Differs From Diacylglycerol Acyltransferase

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生物化学与生物物理进展 2025年第3期52卷 705-715页

作者： YU Qing FU Yang-Yang ZENG Fan-Si PANG Hui-Min HUANG Fei-Fei CHANG Ping-An Chongqing Key Laboratory of Big Data for Bio-Intelligence School of Life Health Information Science and EngineeringChongqing University of Posts and TelecommunicationsChongqing 400065China

Objective To characterize transmembrane protein 68(TMEM68)in an alternative triacylglycerol(TAG)biosynthesis pathway,and determine the interplay between TMEM68 and the canonical TAG synthesis enzyme acyl-CoA:diacylglycerol acyltransferase(DGAT).Methods Effects of exogenous fatty acid and monoacylglycerol on TAG synthesis and lipid droplet(LD)formation in TMEM68 overexpression and knockout cells treated with DGAT inhibitor or not were investigated by comparing LD morphology,Oil Red O staining,and measurement of TAG *** were stained with fluorescence dye and observed by confocal fluorescence *** levels were determined with an enzyme-based triglyceride assay *** of TMEM68 and DGAT1 was detected by co-expression and confocal fluorescence microscopy and their interaction was determined by ***-qPCR and immunoblotting assay were used to detect the expression of *** The synthesis of TAG catalyzed by TMEM68 was independent of DGAT *** exogenous fatty acids and monoacylglycerol promoted TAG synthesis mainly through DGAT in human neuroblastoma *** LDs formed by TMEM68 were different in morphology from those by *** addition,TMEM68 and DGAT1 colocalized in the same endoplasmic reticulum(ER)compartment but did not interact ***68 overexpression reduced the expression of DGAT1,the major DGAT enzyme involved in TAG synthesis,while TMEM68 knockout had little *** The TMEM68-mediated TAG synthesis pathway has distinct features from the canonical DGAT pathway,however,TMEM68 and DGAT may coregulate intracellular TAG levels.

关键词： triacylglycerol lipid droplet TMEM68 GAT

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Optical transmittance and pulse shape discrimination of polystyrene/poly(methyl methacrylate)-based plastic scintillators

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Nuclear Science and Techniques 2025年第1期36卷 94-102页

作者： Yi-Yao Liang Ying-Du Liu Pu-Sen Wang Jie Bao Xiao-Ping Ouyang School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China Nuclear Data Key Laboratory China Institute of Atomic EnergyBeijing 102413China

Polymethyl methacrylate(PMMA)is an optically transparent thermoplastic with favorable processing *** this study,a series of plastic scintillators are prepared via thermal polymerization,and the impact of PMMA content on their transparency and pulse shape discrimination(PSD)ability is *** fabricated samples,comprising a polystyrene(PS)-PMMA matrix,30.0 wt%2,5-diphenyloxazole(PPO),and 0.2 wt%9,10-diphenylanthracene(DPA),exhibit high transparency with transmissivity ranging from 70.0 to 90.0%(above 415.0 nm)and demonstrate excellent n/γdiscrimination *** increased with increasing PMMA content across the entire visible light ***,the PSD performance gradually deteriorated when the aromatic matrix was replaced with *** scintillator containing 20.0 wt%PMMA demonstrated the best stability concerning PSD properties and relative light yields.

关键词： Neutron detection Plastic scintillation Pulse shape discrimination Polymethyl-methacrylate Polystyrene

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On the interaction phenomena to the nonlinear generalized Hietarinta-type equation

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Journal of Ocean engineering and Science 2024年第1期9卷 89-97页

作者： Usman Younas T.A.Sulaiman Jingli Ren A.Yusuf State Key Laboratory of Power Grid Environmental Protection/Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Faculty of Science Federal University DutseJigawaNigeria Department of Computer Engineering Biruni University IstanbulTurkey

In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and various test function *** Hirota method is a widely used and robust mathematical tool for finding soliton solutions of nonlinear partial differential equa-tions(NLPDEs)in a variety of disciplines like mathematical physics,nonlinear dynamics,oceanography,engineering sciences,and others requires bilinearization of nonlinear *** different wave structures in the forms of new breather,lump-periodic,rogue waves,and two-wave solutions are *** addi-tion,the physical behavior of the acquired solutions is illustrated in three-dimensional,two-dimensional,density,and contour profiles by the assistance of suitable *** on the obtained results,we can assert that the employed methodology is straightforward,dynamic,highly efficient,and will serve as a valuable tool for discussing complex issues in a diversity of domains specifically ocean and coastal *** have also made an important first step in understanding the structure and physical be-havior of complex structures with our findings *** believe this research is timely and relevant to a wide range of engineering *** results obtained are useful for comprehending the fundamental scenarios of nonlinear sciences.

关键词： Hirota’s bilinear method Lump-periodic solutions Breather waves Rouge waves Multi-waves

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Potato Disease Identification Method based on Improved DeeplabV3+ Network 24

Potato Disease Identification Method based on Improved Deepl...

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7th International Conference on Image and Graphics Processing, ICIGP 2024

作者： Duan, Xiaoyue Gu, Shenming School of Information Engineering Zhejiang Ocean University China Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province Zhejiang Ocean University China

ISBN: (纸本)9798400716720

In recent years, the advancement of deep learning technology and convolutional neural networks has presented novel solutions for the swift and precise detection of crop diseases. To address issues such as low segmentation accuracy in plant leaf images amidst complex backgrounds, inadequacies in recognition and detection models, insufficient data sets, and sluggish training speed, we propose a method for potato leaf image segmentation and recognition based on an enhanced DeeplabV3+ network. Specifically, we substitute the model encoder's backbone feature extraction network with MobileNetV2 to significantly reduce computational requirements while enhancing calculation speed. Then, the attention mechanism module was incorporated into the backbone feature extraction network and decoder to further enhance the model's edge recognition capability and improve its segmentation accuracy. Simultaneously, this study devised a classification model to achieve potato leaf disease segmentation and detection amidst complex backgrounds. In the initial stage, an enhanced DeeplabV3+ was employed for segmenting potato leaves in intricate environments. Subsequently, ResNet101, ResNet50, and ShuffleNetV2 classification models were utilized in the second stage for accurately classifying potato leaves. Finally, the two-stage model was integrated to effectively segment and detect potato leaf diseases amidst intricate backgrounds. The experimental findings demonstrate that the enhanced DeeplabV3+ segmentation model achieves a remarkable Mean Intersection over Union (MIoU) of 82.6%, an impressive Average Pixel Accuracy (MPA) of 90.65%, and a commendable accuracy rate of 94.72% for the second stage classification model. In conclusion, this approach presents a novel research avenue for accurately segmenting and detecting potato leaf diseases in challenging background scenarios, thereby contributing to advancements in this field. © 2024 ACM.

关键词： Feature extraction

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Locally Private Estimator for Degree Distribution with Laplacian Mechanism 10

Locally Private Estimator for Degree Distribution with Lapla...

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10th IEEE Smart World Congress, SWC 2024

作者： Li, Jiayu Hu, Yuke Li, Xiaoguang Zhou, Shiqi Wang, Yuxiang Li, Fenghua Niu, Ben Institute of Information Engineering Chinese Academy of Sciences China University of Chinese Academy of Sciences School of Cyber Security China Key Laboratory of Cyberspace Security Defense China Zhejiang University The State Key Laboratory of Blockchain and Data Security China Xidian University School of Cyber Engineering China

ISBN: (纸本)9798331520861

Local differential privacy (LDP) provides a solution such that an untrusted server can achieve privacy-preserving data analysis. Node degree is one of the most fundamental metrics in graph data analysis. Existing LDP-based methods can not balance degree distribution estimation and degree distribution characteristic estimation. In this paper, we propose a local private estimator for degree distribution with Laplacian mechanism (LEDL), which uses elastic net regression to estimate the degree distribution, selects the regularization weight to prevent overfitting or underfitting. We can aslo adopt the existing method to calculate degree distribution characteristics according to data with Laplacian noise. Experiments demonstrate the effectiveness of LEDL in degree distribution and Laplacian mechanism in degree distribution characteristic estimation, six metrics are applied across four datasets. © 2024 IEEE.

关键词： Differential privacy

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A survey on graph neural network-based next POI recommendation for smart cities

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Journal of Reliable Intelligent Environments 2024年第3期10卷 299-318页

作者： Yu, Jian Guo, Lucas Zhang, Jiayu Wang, Guiling Department of Computer Science and Soft Engineering Auckland University of Technology Auckland New Zealand School of Information Science and Technology Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data North China University of Technology Beijing China

Amid the rise of mobile technologies and Location-Based Social Networks (LBSNs), there’s an escalating demand for personalized Point-of-Interest (POI) recommendations. Especially pivotal in smart cities, these systems aim to enhance user experiences by offering location recommendations tailored to past check-ins and visited POIs. Distinguishing itself from traditional POI recommendations, the next POI approach emphasizes predicting the immediate subsequent location, factoring in both geographical attributes and temporal patterns. This approach, while promising, faces with challenges like capturing evolving user preferences and navigating data biases. The introduction of Graph Neural Networks (GNNs) brings forth a transformative solution, particularly in their ability to capture high-order dependencies between POIs, understanding deeper relationships and patterns beyond immediate connections. This survey presents a comprehensive exploration of GNN-based next POI recommendation approaches, delving into their unique characteristics, inherent challenges, and potential avenues for future research. © The Author(s) 2024.

关键词： Location based services

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Instruction-Driven Game Engine: A Poker Case Study

Instruction-Driven Game Engine: A Poker Case Study

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Wu, Hongqiu Liu, Xingyuan Wang, Yan Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China Tencent China

ISBN: (纸本)9798891761674

The Instruction-Driven Game Engine (IDGE) project aims to democratize game development by enabling a large language model (LLM) to follow free-form game descriptions and generate game-play processes. The IDGE allows users to create games simply by natural language instructions, which significantly lowers the barrier for game development. We approach the learning process for IDGEs as a Next State Prediction task, wherein the model autoregressively predicts the game states given player actions. The computation of game states must be precise;otherwise, slight errors could corrupt the game-play experience. This is challenging because of the gap between stability and diversity. To address this, we train the IDGE in a curriculum manner that progressively increases its exposure to complex scenarios. Our initial progress lies in developing an IDGE for Poker, which not only supports a wide range of poker variants but also allows for highly individualized new poker games through natural language inputs. This work lays the groundwork for future advancements in transforming how games are created and played. © 2024 Association for Computational Linguistics.

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