Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of th...
Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of the deep learning models, i.e., neural architectures with parameters trained over a dataset, is crucial to our daily living and economy.
The lightweight design of the receiver plays a pivotal role in the application of wireless power transfer (WPT) technology to intelligent devices, such as unmanned underwater vehicle (UUV) and autonomous aerial vehicl...
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The 5.0 vol.%GNP/2024Al composites were prepared by accumulated shear deformation combined with heat treatment,*** thermomechanical treatment(TMT).The results showed that homogeneous distributed GNPs that aligned alon...
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The 5.0 vol.%GNP/2024Al composites were prepared by accumulated shear deformation combined with heat treatment,*** thermomechanical treatment(TMT).The results showed that homogeneous distributed GNPs that aligned along the plastic deformation direction were obtained by six-pass drawing in the solution heat treatment *** introducing of high-density dislocations in Al matrix by multiple drawing resulted in enhanced nucleation of precipitates and subsequent uniform growth during ***,ultra-strength GNP/2024Al composites,with yield and ultimate tensile strength 482 and571 MPa,respectively,were *** high strength was attributed to homogeneous dispersion of undamaged GNPs,fine and dispersed precipitations and work-hardening *** work demonstrated that TMT could act as a feasible strategy for preparing high-performance GNP/Al composites.
In this paper,a reasoning enhancement method based on RGCN(Relational Graph Convolutional Network)is proposed to improve the detection capability of UAV(Unmanned Aerial Vehicle)on fast-moving military targets in urban...
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In this paper,a reasoning enhancement method based on RGCN(Relational Graph Convolutional Network)is proposed to improve the detection capability of UAV(Unmanned Aerial Vehicle)on fast-moving military targets in urban battlefield *** combining military images with the publicly available VisDrone2019 dataset,a new dataset called VisMilitary was built and multiple YOLO(You Only Look Once)models were tested on *** to the low confidence problem caused by fuzzy targets,the performance of traditional YOLO models on real battlefield images decreases ***,we propose an improved RGCN inference model,which improves the performance of the model in complex environments by optimizing the data processing and graph network *** results show that the proposed method achieves an improvement of 0.4%to 1.7%on mAP@0.50,which proves the effectiveness of the model in military target *** research of this paper provides a new technical path for UAV target detection in urban battlefield,and provides important enlightenment for the application of deep learning in military field.
Sluggish polysulfide redox kinetics,especially the high energy barrier of rate-determining short-chain polysulfide conversion and the high activation barrier of Na_(2)S decomposition during sulfur recovery,compromise ...
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Sluggish polysulfide redox kinetics,especially the high energy barrier of rate-determining short-chain polysulfide conversion and the high activation barrier of Na_(2)S decomposition during sulfur recovery,compromise the full potential of rechargeable Na-S *** we construct the hierarchical sandwich-structured carbon matrix with atomically dispersed Mn-N4 Lewis acidic sites,taking advantage of their bidirectional electrocatalytic behavior toward interface-mediated reversible sulfur *** and theoretical results reveal that the spatial confinement and catalytic effects facilitated via strong Lewis acid-base electron interactions synergistically manipulate the low kinetically direct Na_(2)S_(4) to Na_(2)S conversion,and the formation of Mn-S bond minimizes the energy barrier of Na_(2)S electrochemical activation during battery recharging,thereby rendering a reversible and tunable polysulfide speciation ***,the degradation of the Na-S cell is due to the depletion of metal anode rather than the loss of active sulfur species and/or aggregation of inactive dead *** expected,the S@Mn/NC cathode delivers outstanding rate capability and ultrahigh cycling ***,a proof-of-concept pouch cell was also demonstrated capable of delivering an energy density up to 840 Wh kgcathode−*** tunable sulfur redox electrochemistry invoked by the bidirectional monodispersed Mn catalytic hot spots facilitates the efficient polysulfide speciation for practical Na-S cells.
As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required i...
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As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required in chemical vapor deposition, coating processes, etc. They increase scheduling complexity in cluster tools. In this paper, we focus on scheduling single-arm multi-cluster tools with chamber cleaning operations subject to wafer residency time constraints. When a chamber is being cleaned, it can be viewed as processing a virtual wafer. In this way, chamber cleaning operations can be performed while wafer residency time constraints for real wafers are not violated. Based on such a method, we present the necessary and sufficient conditions to analytically check whether a single-arm multi-cluster tool can be scheduled with a chamber cleaning operation and wafer residency time constraints. An algorithm is proposed to adjust the cycle time for a cleaning operation that lasts a long cleaning ***, algorithms for a feasible schedule are also *** an algorithm is presented for operating a multi-cluster tool back to a steady state after the cleaning. Illustrative examples are given to show the application and effectiveness of the proposed method.
Superconducting critical temperature is the most attractive material property due to its impact on the applications of electricity transmission,railway transportation,strong magnetic fields for nuclear fusion and medi...
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Superconducting critical temperature is the most attractive material property due to its impact on the applications of electricity transmission,railway transportation,strong magnetic fields for nuclear fusion and medical imaging,quantum computing,*** ability to predict its value is a constant pursuit for condensed matter *** developed a new hierarchical neural network(HNN)AI algorithm to resolve the contradiction between the large number of descriptors and the small number of datasets always faced by neural network AI approaches to materials *** this new HNN-based AI model,a much-increased number of 909 universal descriptors for inorganic compounds,and a dramatically cleaned database for conventional superconductors,we achieved high prediction accuracy with a test R^(2)score of 95.6%.The newly developed HNN model accurately predicted T_(c)of 45 new high-entropy alloy superconductors with a mean absolute percent error below 6%compared to the experimental *** demonstrated a significant potential for predicting other properties of inorganic materials.
Unlike traditional networks, Software-defined networks (SDNs) provide an overall view and centralized control of all the devices in the network. SDNs enable the network administrator to implement the network policy by...
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It is highly desirable to seek green and sustainable technologies,such as employing photo thermal effects to drive energy catalysis processes to address the high energy demand and associated environmental impacts indu...
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It is highly desirable to seek green and sustainable technologies,such as employing photo thermal effects to drive energy catalysis processes to address the high energy demand and associated environmental impacts induced by the current *** photothermocatalysis process is an emerging research area with great potential in efficiently converting solar energy through various catalytic ***,achieving simultaneously high conversion efficiency,cyclability,and durability is still a daunting ***,tremendous work is still needed to enhance solar photo thermal catalytic conversion and promote its large-scale *** review developed the principles of coupling solar photon and thermal fields underlying the photothermal effect,exploration of efficient nanocatalysts,development of optofluidic reactor model,and photo thermal synergistic-driven CO_(2) reduction *** ultimate goal was to provide an effective approach that can effectively convert solar energy into photocarriers/hot-electrons and heat,and importantly,can couple them to regulate catalysis reaction pathways toward the production of value-added fuel and chemical energy.
With the advent of the Web 3.0 era, the amount and types of data in the network have sharply increased, and the application scenarios of recommendation algorithms are continuously expanding. Location recommendation ha...
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