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Computing power networks for unmanned aerial vehicles:a hierarchical resources trading market 认领 引用
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作者 Xiaofei Wang Hui Deng +3 位作者 Chao Qiu Zheyuan Chen Tao Luo Zhao Ming 《Digital Communications and Networks》 SCIE EI CSCD 2026年第4期584-593,共10页
Unmanned Aerial Vehicles(UAVs)are increasingly deployed across military and civilian domains due to their operational flexibility,low maintenance costs,and high mobility.With the growing complexity of UAV applications... Unmanned Aerial Vehicles(UAVs)are increasingly deployed across military and civilian domains due to their operational flexibility,low maintenance costs,and high mobility.With the growing complexity of UAV applications and tasks,robust support from computing power networks is essential.These networks,acting as resource integration paradigms,furnish UAVs with pooled resources to tackle extensive computational demands.In this paper,we develop a framework for trading computing power resources,modeling the transaction process through a three-stage Stackelberg game to facilitate sequential decision-making.We theoretically demonstrate the existence of a Nash equilibrium and introduce a Dynamic Game Reinforcement algorithm to identify optimal strategies.Our experimental results affirm the framework's efficacy and the superior performance of our algorithm.Additionally,we explore how variables like UAV quantity and network congestion influence the market dynamics of the computing power network. 展开更多
关键词 UAVs Cloud computing Computing power network Resource trading Stackelberg game
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An enhanced ecological network for spatial planning considering spatial conflicts and structural resilience 认领 引用
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作者 Haowei Mu Shanchuan Guo +6 位作者 Xingang Zhang Bo Yuan Xiaoquan Pan Zilong Xia Xin Pan Shangwu Zhang Peijun Du 《Geography and Sustainability》 CSCD 2026年第2期116-128,共13页
The digital transformation of territorial spatial planning has underscored the urgent need to integrate ecological network into spatial planning practices.In response,we developed two innovative new tools,the Ecologic... The digital transformation of territorial spatial planning has underscored the urgent need to integrate ecological network into spatial planning practices.In response,we developed two innovative new tools,the Ecological Linkage Tool(ELT)and the Relative Spatial Conflict Index(RSCI),to enhance ecological networks applications by addressing spatial conflicts and structural resilience.The ELT identified ecological corridors within and outside irregular ecological sources,activation points,and stepping stones in parallel,and then constructed an intact ecological network.By integrating the RSCI and complex network metrics,the spatial conflicts and structural resilience were evaluated.The framework was implemented in the Hohhot-Baotou-Ordos-Yulin(HBOY)urban agglomeration,identifying a total of 5,814 corridors,of which 67%were classified as intra-patch and 33%as inter-patch.The number and distribution of these corridors were determined by the size and shape of the ecological sources,and the connectivity of intra-patch corridors was 34%higher than inter-patch corridors.According to the RSCI,60%of the corridors experienced spatial conflicts,with 21%involving production spaces or composite production-related conflicts.Moreover,Yulin served as a key hub in the ecological network,and Baotou had the highest network efficiency.Compound conflict corridors(involving production,living,and open spaces)had a greater impact on overall ecological network efficiency compared to those with single or dual conflicts.Meanwhile,the failure of 40%of corridors without spatial conflicts would directly result in a 96.9%decline in network efficiency,highlighting their critical role in maintaining network functionality.This study provides an enhanced ecological network application solution for the China Spatial Planning Observation Network(CSPON),supporting spatial planning practices. 展开更多
关键词 Ecological network Ecological corridor Spatial conflict Structural resilience Spatial planning
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Dual Channel Graph Convolutional Networks via Personalized PageRank 认领 引用
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作者 Longlong Lin Xin Luo 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第1期221-223,共3页
Dear Editor,D2This letter presents a node feature similarity preserving graph convolutional framework P G.Graph neural networks(GNNs)have garnered significant attention for their efficacy in learning graph representat... Dear Editor,D2This letter presents a node feature similarity preserving graph convolutional framework P G.Graph neural networks(GNNs)have garnered significant attention for their efficacy in learning graph representations across diverse real-world applications. 展开更多
关键词 convolutional node feature similarity graph convolutional framework learning graph representations neural networks gnns networks graph personalized
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Resilience planning for urban ecosystems in the Himalayas:Ecosystem service value decline and network vulnerabilities in Lhasa 认领 引用
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作者 Jiarui Zhang Liyuan Qian +2 位作者 Guangyu Wang Migmar Wangdwei Qingtao Zhu 《Ecological Frontiers》 CSCD 2026年第1期227-241,共15页
Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its ... Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its central urban area is therefore critical for informing future urban planning and land management.This study systematically analyzed land use evolution,the spatiotemporal characteristics of ecosystem services,and ecological network construction within Lhasa's central urban area.It integrated multi-source data,including Landsat remote sensing imagery from 2000,2010,and 2023,with multiple modeling methods such as the InVEST model,MaxEnt for cultural service assessment,the Minimum Cumulative Resistance(MCR)model,and circuit theory.Based on these analyses,optimization strategies were proposed.The results indicate that from 2000 to 2023,areas of cultivated land,grassland,and water bodies decreased by 7.47%,6.85%,and 0.68%,respectively,while wetland and forest areas expanded by 1.44%and 0.64%.Construction land exhibited significant expansion(12.94%),leading to an overall ESV reduction of 462.8×105yuan.Vegetation coverage was identified as the pivotal factor influencing ESV distribution,with higher values concentrated in the Lhasa River Basin and near the Lhalu Wetland,diminishing towards the urban core.Furthermore,spatial autocorrelation analysis revealed significant positive spatial clustering,with low-low aggregation in the eastern and central regions and high-high aggregation in the Lhasa River Basin and its surrounding water bodies.Moreover,based on a comprehensive ecosystem service assessment,11 ecological source sites were identified,primarily in the southwestern mountains and northeastern foothills.A comprehensive resistance surface,incorporating factors such as elevation,Normalized Difference Vegetation Index(NDVI),and land use,facilitated the extraction of 23 potential ecological corridors totaling 124.96 km in length.Topological network analysis indicated high redundancy and connectivity;however,marginal source sites relying on single connections exhibited significant vulnerability to rupture.Additionally,the application of circuit theory identified 30 ecological pinch points(current density≥1.5 A/km2)and 23 obstacle points,revealing significant blockages to ecological flow along the Qinghai-Xizang Highway,within the old city,and in other areas of high-intensity human activity.To address the identified network deficiencies—‘scattered cores,fragmented corridors,and insufficient resilience’—this study proposes an optimization strategy conceptualized as‘one vein,three corridors,and multiple cores’.Recommendations for enhancing network resilience include the delineation of ecological protection red lines,the integration of plateau-adapted technologies,and the fostering of community governance mechanisms.This approach aims to provide a scientific basis for constructing an ecological security pattern and promoting sustainable development in plateau cities.Ultimately,this research contributes to the enhancement of ecological well-being in the Himalayan region. 展开更多
关键词 Plateau urbanization Ecosystem service value Ecological network Ecological corridor Llasa
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Landslide image recognition based on residual networks with transfer learning and spatial-channel dual attention mechanism 认领 引用
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作者 ZHAO Cheng YU Jiacheng +3 位作者 XIE Yongfei CHEN Huiguan XING Jinquan NIU Jialun 《Journal of Mountain Science》 SCIE CSCD 2026年第7期3155-3169,共15页
Landslides are one of the most significant types of geological disasters worldwide.However,current landslide disaster recognition models generally face issues such as low training efficiency,reliance on large amounts ... Landslides are one of the most significant types of geological disasters worldwide.However,current landslide disaster recognition models generally face issues such as low training efficiency,reliance on large amounts of samples,and vague feature extraction.To address these problems,this paper proposes an enhanced intelligent recognition model based on an improved residual network.Taking remote sensing images from landslide-prone areas in Bijie City,Guizhou Province,China as the research subject,we implemented data augmentation techniques to expand the datasets,subsequently partitioning it into training and validation subsets at a73:27 ratio.During model training,a transfer learning strategy was employed to improve training efficiency through the utilization of ImageNet pre-trained weights.The Res Net50 network architecture was enhanced through the integration of channel attention and spatial attention mechanisms,enabling more effective extraction of critical landslide features.Comparative analysis indicates that after introducing the attention mechanisms,the enhanced model achieved an increase of 1.49% in accuracy,0.45% in precision,1.52% in F1 score,and 0.0297 in Kappa coefficient on the validation set.Notably,recall improved by 2.59%,indicating that the improved model has enhanced landslide disaster recognition capability and overall performance.This study successfully coupled the transfer learning strategy with a dual-attention mechanism into the ResNet50 architecture,allowing the rapid construction of an efficient recognition model under limited sample conditions,significantly improving the comprehensive performance and generalisation ability of the landslide recognition model. 展开更多
关键词 Attention mechanism Convolutional neural network Transfer Learning Landslide disaster identification
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Fast-charging lithium-ion batteries electrodes enabled by self-regulating micro-channels networks 认领 引用
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作者 Yongtai Xu Zhiwen Zheng +5 位作者 Jianze Feng Xixian Li Kailimai Su Ziqiang Liu Hui Ying Yang Xingbin Yan 《Chinese Chemical Letters》 SCIE CAS CSCD 2026年第4期396-400,共5页
Lithium-ion batteries(LIBs)are essential energy storage devices widely used in portable electronics,transportation,and various other applications.However,current anode materials,with their low intercalation potentials... Lithium-ion batteries(LIBs)are essential energy storage devices widely used in portable electronics,transportation,and various other applications.However,current anode materials,with their low intercalation potentials and poor rate performance,struggle to balance energy density,power density,and safety,particularly under extreme conditions.In this work,we report a self-regulating micro-channel network that forms a three-dimensional(3D)composite electrode architecture without binders and conductive additives,offering a promising anode solution for fast-charging LIBs.Benefiting from the robust 3D architecture with abundant Li+active sites and superior electronic conductivity,the niobium tungsten oxide@carbon nanotube(NWO/CNT)composite electrode demonstrates a high reversible capacity(246.6mAh/g at 0.2 C),excellent rate capability(117.1 mAh/g at 60 C),and long-term durability(73.0%capacity retention after 10,000 cycles).Additionally,a thick electrode with high mass loading(10 mg/cm2)shows remarkable high-rate performance,retaining 51.7%capacity at 20 C.Notably,when paired with LiFePO4(LFP)cathodes,the NWO@CNT//LFP@CNT full batteries exhibit impressive high-power capability(2.8 kW/kg),high energy density(394.2 Wh/kg),and exceptional cycle stability(82%capacity retention after 6000 cycles).Most importantly,this composite electrode architecture also enables the fabrication of a planar,miniaturized,all-solid-state lithium-ion battery with fast-charging capabilities. 展开更多
关键词 Fast-charging lithium-ion batteries Self-regulating nanotube networks High-rate capability Long-term cycling performance Free-standing composite electrode
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Optimization of Flying Ad Hoc Network Topology and Collaborative Path Planning for Multiple UAVs 认领 引用
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作者 Ming He Peizhao Wang +2 位作者 Haihua Chen Bin Sun Hongpeng Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第6期1339-1352,共14页
Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV po... Multiple unmanned aerial vehicles(UAVs)play a vital role in monitoring and data collection in wide area environments with harsh conditions.In most scenarios,issues such as real-time data retrieval and real-time UAV positioning are often disregarded,essentially neglecting the communication constraints.In this paper,we comprehensively address both the coverage of the target area and the data transmission capabilities of the flying ad hoc network(FANET).The data throughput of the network is therefore maximized by optimizing the network topology and UAV trajectories.The resultant optimization problem is effectively solved by the proposed reinforcement learning-based trajectory planning(RL-TP)algorithm and the convex-based topology optimization(C-TOP)algorithm sequentially.The RL-TP optimizes the UAV paths while considering the constraints of FANET.The C-TOP maximizes the data throughput of the network while simultaneously constraining the neighbors and transmit powers of the UAVs,which is shown to be a convex problem that can be efficiently solved in polynomial time.Simulations and field experimental results show that the proposed optimization strategy can effectively plan the UAV trajectories and significantly improve the data throughput of the FANET over the adaptive local minimum spanning tree(A-LMST)and cyclic pruning-assisted power optimization(CPAPO)methods. 展开更多
关键词 Convex optimization flying ad hoc network (FANET) path planning reinforcement learning (RL) topology control
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6G Space-Air-Ground Integrated Networks for Unmanned Operations:Closed-Loop Model and Task-Oriented Approach 认领 引用
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作者 Xinran Fang Wei Feng +3 位作者 Yunfei Chen Ning Ge Shi Jin Shiwen Mao 《Engineering》 SCIE EI CSCD 2026年第1期79-86,共8页
In the upcoming sixth-generation(6G)era,supporting field robots for unmanned operations has emerged as an important application direction.To provide connectivity in remote areas,the space-air-ground integrated network... In the upcoming sixth-generation(6G)era,supporting field robots for unmanned operations has emerged as an important application direction.To provide connectivity in remote areas,the space-air-ground integrated network(SAGIN)will play a crucial role in extending coverage.Through SAGIN connections,the sensors,edge platforms,and actuators form sensing-communication-computing-control(SC3)loops that can automatically execute complex tasks without human intervention.Similar to the reflex arc,the SC3loop is an integrated structure that cannot be deconstructed.This necessitates a systematic approach that takes the SC3loop rather than the communication link as the basic unit of SAGINs.Given the resource limitations in remote areas,we propose a radio-map-based task-oriented framework that uses environmental and task-related information to enable task-matched service provision.We detail how the network collects and uses this information and present task-oriented scheduling schemes.In the case study,we use a control task as an example and validate the superiority of the task-oriented closedloop optimization scheme over traditional communication schemes.Finally,we discuss open challenges and possible solutions for developing nerve system-like SAGINs. 展开更多
关键词 Radio map Sensing-communication-computing-control(SC3)loop Space-air-ground integrated network Sixth-generation(6G)communication Task-oriented communication
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Artificial Intelligence (AI)-Enabled Unmanned Aerial Vehicle (UAV) Systems for Optimizing User Connectivity in Sixth-Generation (6G) Ubiquitous Networks 认领 引用 被引量：1
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作者 Zeeshan Ali Haider Inam Ullah +2 位作者 Ahmad Abu Shareha Rashid Nasimov Sufyan Ali Memon 《Computers, Materials & Continua》 SCIE EI 2026年第1期534-549,共16页
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener... The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment. 展开更多
关键词 6G networks UAV-based communication cooperative reinforcement learning network optimization user connectivity energy efficiency
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Brief comments on“Perturbation response scanning of drug-target networks:Drug repurposing for multiple sclerosis” 认领 引用
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作者 Alessandro Giuliani 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2026年第1期1-2,共2页
The recent Nobel prizes in Physics to Giorgio Parisi,Geoffrey Hinton,and John Hopfield,officially proclaimed a deep epistemological change:the unity of different sciences is no more considered to stem from the fact t... The recent Nobel prizes in Physics to Giorgio Parisi,Geoffrey Hinton,and John Hopfield,officially proclaimed a deep epistemological change:the unity of different sciences is no more considered to stem from the fact that‘any entity is made by the same basic bricks’but on the recognition than‘any entity can be represented as a set of mutually interacting parts’.That is to say that any system[1]can be formalized as a‘network of interactions among its elements’. 展开更多
关键词 drug repurposing interactions its elements unity different sciences perturbation response scanning mutually interacting parts drug target networks multiple sclerosis deep epistemological change
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Dual Layer Source Grid Load Storage Collaborative Planning Model Based on Benders Decomposition: Distribution Network Optimization Considering Low-Carbon and Economy 认领 引用 被引量：1
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作者 Jun Guo Maoyuan Chen +2 位作者 Yuyang Li Sibo Feng Guangyu Fu 《Energy Engineering》 EI 2026年第2期104-133,共30页
Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the ... Theauthor proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network.The model plans the configuration of photovoltaic(3.8 MW),wind power(2.5 MW),energy storage(2.2 MWh),and SVC(1.2 Mvar)through interaction between upper and lower layers,and modifies lines 2–3,8–9,etc.to improve transmission capacity and voltage stability.The author uses normal distribution and Monte Carlo method to model load uncertainty,and combines Weibull distribution to describe wind speed characteristics.Compared to the traditional three-layer model(TLM),Benders decomposition-based two-layer model(BLBD)has a 58.1%reduction in convergence time(5.36 vs.12.78 h),a 51.1%reduction in iteration times(23 vs.47 times),a 8.07%reduction in total cost(12.436 vs.13.528 million yuan),and a 9.62%reduction in carbon emissions(12,456 vs.13,782 t).After optimization,the peak valley difference decreased from4.1 to 2.9MW,the renewable energy consumption rate reached 93.4%,and the energy storage efficiency was 87.6%.Themodel has been validated in the IEEE 33 node system,demonstrating its superiority in terms of economy,low-carbon,and reliability. 展开更多
关键词 Benders decomposition source grid load storage distribution network planning low-carbon economy optimization model
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TopoLLM:LLM-driven adaptive tool learning for real-time emergency network topology planning 认领 引用
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作者 Yizhuo Ma Rongzheng Wang +2 位作者 Shuang Liang Guangchun Luo Ke Qin 《Digital Communications and Networks》 SCIE EI CSCD 2026年第2期273-282,共10页
Communication infrastructure is often among the first casualties in natural or human-induced disasters,severely impairing the coordination and efficiency of rescue operations.Rapid deployment of Unmanned Aerial Vehicl... Communication infrastructure is often among the first casualties in natural or human-induced disasters,severely impairing the coordination and efficiency of rescue operations.Rapid deployment of Unmanned Aerial Vehicles(UAVs)and satellite systems has thus become essential for establishing robust communication links to support rescue-critical tasks.However,existing emergency communication networks rely heavily on domain expertise for topology design,thereby suffering from issues such as inefficient resource allocation and network congestion,among others.To address these challenges,we present TopoLLM,a framework that leverages Large Language Models(LLMs)for tool-driven optimization of emergency network topologies.This framework effectively combines the reasoning capabilities of the LLM with TopoTool,a domain-specific optimization toolkit engineered for high-precision and load-balanced network planning in disaster scenarios.Guided by an adaptive toolselection mechanism,TopoLLM autonomously generates resilient topologies and allocates resources intelligently,reducing the need for extensive human interventions.Experimental evaluations on simulated disaster scenarios verify that TopoLLM can rapidly generate high-accuracy and robust topologies,achieving notable performance improvements compared with existing approaches. 展开更多
关键词 Large language models Tool learning Network planning Scheme generation
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Generalized Kennedy receivers enhanced CV-QKD in turbulent channels for endogenous security of space-air-ground integrated network 认领 引用
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作者 Shouye Miao Mugen Peng +3 位作者 Renzhi Yuan Bin Cao Mufei Zhao Zhifeng Wang 《Digital Communications and Networks》 SCIE EI CSCD 2026年第2期332-342,共11页
Endogenous security in next-generation wireless communication systems attracts increasing attentions in recent years.A typical solution to endogenous security problems is the Quantum Key Distribution(QKD),where uncond... Endogenous security in next-generation wireless communication systems attracts increasing attentions in recent years.A typical solution to endogenous security problems is the Quantum Key Distribution(QKD),where unconditional security can be achieved thanks to the inherent properties of quantum mechanics.Continuous Variable-Quantum Key Distribution(CV-QKD)enjoys high Secret Key Rate(SKR)and good compatibility with existing optical communication infrastructure.Traditional CV-QKD usually employ coherent receivers to detect coherent states,whose detection performance is restricted to the standard quantum limit.In this paper,we employ a generalized Kennedy receiver called CD-Kennedy receiver to enhance the detection performance of coherent states in turbulent channels,where Equal-Gain Combining(EGC)method is used to combine the output of CD-Kennedy receivers.Besides,we derive the SKR of a post-selection based CV-QKD protocol using both CD-Kennedy receiver and homodyne receiver with EGC in turbulent channels.We further propose an equivalent transmittance method to facilitate the calculation of both the Bit-Error Rate(BER)and SKR.Numerical results show that the CD-Kennedy receiver can outperform the homodyne receiver in turbulent channels in terms of both BER and SKR performance.We find that BER and SKR performance advantage of CD-Kennedy receiver over homodyne receiver demonstrate opposite trends as the average transmittance increases,which indicates that two separate system settings should be employed for communication and key distribution purposes.Besides,we also demonstrate that the SKR performance of a CD-Kennedy receiver is much robust than that of a homodyne receiver in turbulent channels. 展开更多
关键词 CV-QKD Endogenous security Generalized Kennedy receiver Space-air-ground integrated network Turbulent channels
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FMCSNet: Mobile Devices-Oriented Lightweight Multi-Scale Object Detection via Fast Multi-Scale Channel Shuffling Network Model 认领 引用
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作者 Lijuan Huang Xianyi Liu +1 位作者 Jinping Liu Pengfei Xu 《Computers, Materials & Continua》 SCIE EI 2026年第1期1292-1311,共20页
The ubiquity of mobile devices has driven advancements in mobile object detection.However,challenges in multi-scale object detection in open,complex environments persist due to limited computational resources.Traditio... The ubiquity of mobile devices has driven advancements in mobile object detection.However,challenges in multi-scale object detection in open,complex environments persist due to limited computational resources.Traditional approaches like network compression,quantization,and lightweight design often sacrifice accuracy or feature representation robustness.This article introduces the Fast Multi-scale Channel Shuffling Network(FMCSNet),a novel lightweight detection model optimized for mobile devices.FMCSNet integrates a fully convolutional Multilayer Perceptron(MLP)module,offering global perception without significantly increasing parameters,effectively bridging the gap between CNNs and Vision Transformers.FMCSNet achieves a delicate balance between computation and accuracy mainly by two key modules:the ShiftMLP module,including a shift operation and an MLP module,and a Partial group Convolutional(PGConv)module,reducing computation while enhancing information exchange between channels.With a computational complexity of 1.4G FLOPs and 1.3M parameters,FMCSNet outperforms CNN-based and DWConv-based ShuffleNetv2 by 1%and 4.5%mAP on the Pascal VOC 2007 dataset,respectively.Additionally,FMCSNet achieves a mAP of 30.0(0.5:0.95 IoU threshold)with only 2.5G FLOPs and 2.0M parameters.It achieves 32 FPS on low-performance i5-series CPUs,meeting real-time detection requirements.The versatility of the PGConv module’s adaptability across scenarios further highlights FMCSNet as a promising solution for real-time mobile object detection. 展开更多
关键词 Object detection lightweight network partial group convolution multilayer perceptron
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Survey on HA2G and A2A channel measurement and modeling for airborne maneuvering networks 认领 引用
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作者 Puguang AN Shuhang YANG +3 位作者 Jiazheng SUN Jinlong LI Peng YANG Xianbin CAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第5期5-33,共29页
Airborne Maneuvering Networks(AMNs),composed of Near-Space Maneuvering Platforms(NS-MPs),High-Altitude Long-Endurance UAVs(HALE-UAVs),and Low-Altitude Maneuvering UAVs(LA-UAVs),are envisioned as a promising solution f... Airborne Maneuvering Networks(AMNs),composed of Near-Space Maneuvering Platforms(NS-MPs),High-Altitude Long-Endurance UAVs(HALE-UAVs),and Low-Altitude Maneuvering UAVs(LA-UAVs),are envisioned as a promising solution for meeting the widearea seamless coverage requirement of the emerging sixth-generation mobile communication systems. The unique operational environment and scenarios for AMNs necessitate channel models for evaluating the communication links within them. However,the intrinsic characteristics of AMN channels,particularly High-Altitude Air-to-Ground(HA2G) and Air-to-Air(A2A) links,still present gaps in understanding,with emerging propagation models lacking a comprehensive investigation. This article provides a comprehensive survey on HA2G and A2A channel measurement campaigns across diverse AMN scenarios and reviews the state of the art in channel modeling.Key challenges in characterizing AMN channels are discussed,and future research directions are outlined to advance robust channel models for AMN communications. 展开更多
关键词 Airborne maneuvering networks UAV Channel measurement campaigns Channel modeling Large-scale fading Small-scale fading
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IPN-RRT*:Neural-Guided RRT*for Optimal Path Planning Using an Improved Point-Cloud Network 认领 引用
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作者 Zhengshun Fei Qiao Sun +3 位作者 Chuang Yang Siranee Nuchitprasitchai Yongping Zheng Xinjian Xiang 《Computers, Materials & Continua》 SCIE EI 2026年第9期2126-2145,共20页
Path planning is a critical component for enabling autonomous navigation in mobile robots.Sampling-based planners are widely adopted due to their strong generality,yet they rely heavily on uniform sampling,which often... Path planning is a critical component for enabling autonomous navigation in mobile robots.Sampling-based planners are widely adopted due to their strong generality,yet they rely heavily on uniform sampling,which often leads to unstable performance and high computational cost in complex environments.To address this issue,recent studies feed free-space point clouds into neural networks to infer a set of guidance states near the optimal path,thereby enabling non-uniform sampling;however,the accuracy of the guidance set becomes a key bottleneck for further improvement.In this paper,we propose an improved point-cloud neural RRT*framework,termed IPN-RRT*,which achieves fast near-optimal planning via a high-precision guidance state set.Specifically,we develop an Improved PointNeXt-based neural sampling network(IPN)that enhances the geometric representation of free-space point clouds using high-dimensional sinusoidal positional encoding(HPESIN),and further improves cross-scene feature discriminability and robustness through a gated covariance-enhanced channel attention module(GCECA).These designs substantially improve the quality of the guidance state set and accelerate convergence toward better solutions during planning.Extensive experiments on large-scale datasets built from complex random maps demonstrate that IPN significantly outperforms existing point-cloud prediction models in region prediction accuracy.Moreover,across diverse challenging environments,IPN-RRT*finds near-optimal paths with fewer nodes and shorter runtime,while preserving probabilistic completeness and asymptotic optimality. 展开更多
关键词 Optimal path planning sampling-based algorithm point-cloud neural networks guidance state set
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A Multi-Stage Expansion Planning Method for Rural Distribution Networks with Flexible Interconnection 认领 引用
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作者 Yueyang Ji Yaohui Peng +4 位作者 Haoran Ji Xinran Na Yuxuan Chen Wei Li Shengbin Chen 《Energy Engineering》 EI 2026年第8期17-31,共15页
With the increasing penetration of distributed generations and continuous growth of loads,traditional rural distribution networks face severe challenges in both hosting capacity and reliability.Addressing these issues... With the increasing penetration of distributed generations and continuous growth of loads,traditional rural distribution networks face severe challenges in both hosting capacity and reliability.Addressing these issues requires planning approaches that strike a balance between economic efficiency in infrastructure development and resilience in operation.Considering the dynamic growth of distributed generations and rural loads over the planning horizon,this paper presents a multi-stage expansion planning approach that coordinates flexible interconnection devices(FIDs)with substation and line construction to improve both economic performance and system reliability.The proposed method account for the time-varying growth of DGs and loads,as well as the declining investment cost of power electronic devices across multiple planning stages.The model holistically considers both economic efficiency and operational reliability,formulating the problem as a mixed-integer second-order cone programming(MISOCP)model to ensure computational efficiency.Case studies conducted on a practical 138-node rural distribution network in Guangxi,China,demonstrate the effectiveness of the proposed method.Compared to traditional single-stage or singleresource planning strategies,results indicate that the proposed multi-stage coordinated strategy achieves a significant reduction in total annualized cost while simultaneously enhancing system reliability,effectively mitigating voltage violations,and achieving a 100%PV accommodation rate without curtailment.This work provides a practical and adaptive planning framework for rural distribution networks,offering valuable insights for achieving cost-effective and resilient network development under rural energy transition. 展开更多
关键词 Rural distribution networks coordinated planning flexible interconnection device multi-stage planning reliability
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MCCGAA:Multimodal Channel Compression Graph Attention Alignment Network for ECG Zero-Shot Classification 认领 引用
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作者 Qiuxiao Mou Haoyu Gui +1 位作者 Xianghong Tang Jianguang Lu 《Computers, Materials & Continua》 SCIE EI 2026年第6期1666-1686,共21页
Electrocardiogram(ECG)is a widely used non-invasive tool for diagnosing cardiovascular diseases.ECG zero-shot classification involves pre-training a model on a large dataset to classify unknown disease categories.Howe... Electrocardiogram(ECG)is a widely used non-invasive tool for diagnosing cardiovascular diseases.ECG zero-shot classification involves pre-training a model on a large dataset to classify unknown disease categories.However,existing ECG feature extraction networks often neglect key lead signals and spatial topology dependencies during cross-modal alignment.To address these issues,we propose a multimodal channel compression graph attention alignment network(MCCGAA).MCCGAA incorporates a channel attention module(CAM)to effectively integrate key lead features and a graph attention-based alignment network to capture spatial dependencies,enhancing cross-modal alignment.Additionally,MCCGAA employs a log-sum-exp loss function,improving classification performance and convergence over the original clip-style method.Experimental results show that MCCGAA outperforms current methods,achieving the highest classification accuracy across six publicly available datasets.MCCGAA holds promise for advancing ECG zero-shot classification and offering better decision support for researchers. 展开更多
关键词 ECG zero-shot classification contrastive learning cross-modal alignment graph attention network channel attention mechanism
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Cascading failure modeling and survivability analysis of weak-communication underwater unmanned swarm networks 认领 引用
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作者 Yifan Yuan Xiaohong Shen +3 位作者 Lin Sun Ke He Yongsheng Yan Haiyan Wang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第2期66-82,共17页
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and env... Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs. 展开更多
关键词 Weak communication Underwater unmanned swarm networks(UUSNs) Link success probability Cascading failure Node self-recovery Survivability analysis
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Multichannel optical convolutional neural network for color images 认领 引用
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作者 Junpeng Chen Xi Jiang +4 位作者 Jiaming Su Shukai Wu Zheng Huang Haizheng Zhong Hongwei Chen 《Advanced Photonics Nexus》 CSCD 2026年第5期33-45,共13页
Most existing optical convolutional neural networks(OCNNs)are primarily limited to implementingbasic convolution functions,with little focus on leveraging the color dimension.As a result,they can typicallyonly process... Most existing optical convolutional neural networks(OCNNs)are primarily limited to implementingbasic convolution functions,with little focus on leveraging the color dimension.As a result,they can typicallyonly process single-channel or grayscale images,lacking the ability to utilize multichannel information such asRGB.In this work,we propose a multichannel optical convolutional neural network(MOCNN),which is capableof processing both RGB and hyperspectral images using only grayscale sensors by integrating trainable colorfilters into the optical path.Through simulations and experiments,we demonstrate that the performance ofoptical convolution is significantly enhanced by incorporating color information,enabling the system to handlecomplex color-related tasks.Furthermore,we design a loss function tailored to the physical properties ofquantum dots.We demonstrate that this training strategy can be extended to other types of filtering materials.Moreover,the proposed technique can serve as an OCNN-based feature-map acquisition camera withoutadditional imaging components,offering a potential route toward compact,low-cost,and privacy-preservingimage capture with limited task-performance degradation. 展开更多
关键词 optical convolutional neural network optical computing color image multichannel optical computing quantum dot
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