Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t...
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Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered to be a powerful QPs solver due to its parallel processing capability and feasibility of hardware implementation[2].
Manipulating catalyst structures to control product selectivity while maintaining high activity presents a considerable challenge in CO_(2)*** density functional theory calculations and microkinetic analysis,we propos...
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Manipulating catalyst structures to control product selectivity while maintaining high activity presents a considerable challenge in CO_(2)*** density functional theory calculations and microkinetic analysis,we proposed that graphene-supported isolated Pt atoms(Pt1/graphene)and Pt_(2)dimers(Pt_(2)/graphene)exhibited distinct selectivity in CO_(2)***_(1)/graphene facilitated the conversion of CO_(2)into formic acid,whereas Pt_(2)/graphene favored methanol *** variation in product selectivity arose from the synergistic interaction of Pt_(2)dimers,which facilitated the migration of H atoms between two Pt atoms and promoted the transformation from*COOH intermediates to*C(OH)_(2)intermediates,altering the reaction pathways compared to isolated Pt ***,an analysis of the catalytic activities of three Pt_(1)/graphene and three Pt_(2)/graphene structures revealed that the turnover frequencies for formic acid generation on Pt_(1ii)/graphene and methanol generation on Pt_(2i)/graphene were as high as 744.48 h-1and 789.48 h^(-1),*** values rivaled or even surpassed those previously reported in the literature under identical *** study provides valuable insights into optimizing catalyst structures to achieve desired products in CO_(2)hydrogenation.
Aqueous zinc(Zn)ion batteries(AZIBs)are regarded as one of the promising candidates for next-generation electrochemical energy storage systems due to their low cost,high safety,and environmental ***,the commercializat...
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Aqueous zinc(Zn)ion batteries(AZIBs)are regarded as one of the promising candidates for next-generation electrochemical energy storage systems due to their low cost,high safety,and environmental ***,the commercialization of AZIBs has been severely restricted by the growth of dendrite at the Zn metal *** the planar-structured Zn anodes into threedimensional(3D)structures has proven to be an effective way to modulate the plating/stripping behavior of Zn anodes,resulting in the suppression of dendrite *** review provides an up-to-date review of 3D structured Zn metal anodes,including working principles,design,current status,and future *** aim to give the readers a comprehensive understanding of 3D-structured Zn anodes and their effective usage to enhance AZIB performance.
To solve the problem of cluster configuration for unmanned aerial vehicle (UAV) networks in highly dynamic environments, a directional antenna UAVs network algorithm based on demand-weighted clustering is proposed to ...
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In this paper, we tackle the long-tailed visual recognition problem from the categorical prototype perspective by proposing a prototype-based classifier learning(PCL) method. Specifically, thanks to the generalization...
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In this paper, we tackle the long-tailed visual recognition problem from the categorical prototype perspective by proposing a prototype-based classifier learning(PCL) method. Specifically, thanks to the generalization ability and robustness, categorical prototypes reveal their advantages of representing the category semantics. Coupled with their class-balance characteristic, categorical prototypes also show potential for handling data imbalance. In our PCL, we propose to generate the categorical classifiers based on the prototypes by performing a learnable mapping function. To further alleviate the impact of imbalance on classifier generation, two kinds of classifier calibration approaches are designed from both prototype-level and example-level aspects. Extensive experiments on five benchmark datasets, including the large-scale iNaturalist, Places-LT,and ImageNet-LT, justify that the proposed PCL can outperform state-of-the-arts. Furthermore, validation experiments can demonstrate the effectiveness of tailored designs in PCL for long-tailed problems.
We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory *** some extent,our method solves the two difficulties encountered in traditional video object se...
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We present a lightweight and efficient semisupervised video object segmentation network based on the space-time memory *** some extent,our method solves the two difficulties encountered in traditional video object segmentation:one is that the single frame calculation time is too long,and the other is that the current frame’s segmentation should use more information from past *** algorithm uses a global context(GC)module to achieve highperformance,real-time *** GC module can effectively integrate multi-frame image information without increased memory and can process each frame in real ***,the prediction mask of the previous frame is helpful for the segmentation of the current frame,so we input it into a spatial constraint module(SCM),which constrains the areas of segments in the current *** SCM effectively alleviates mismatching of similar targets yet consumes few additional *** added a refinement module to the decoder to improve boundary *** model achieves state-of-the-art results on various datasets,scoring 80.1%on YouTube-VOS 2018 and a J&F score of 78.0%on DAVIS 2017,while taking 0.05 s per frame on the DAVIS 2016 validation dataset.
Submerged abrasive waterjet peening(SAWJP)is an effective anti-fatigue manufacturing technology that is widely used to strengthen aeroengine *** study investigated the correlation of SAWJP process parameters on surfac...
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Submerged abrasive waterjet peening(SAWJP)is an effective anti-fatigue manufacturing technology that is widely used to strengthen aeroengine *** study investigated the correlation of SAWJP process parameters on surface integrity and fatigue life of titanium alloy *** with different water pressures and standoff distances(SoDs)was conducted on the TA19 *** surface integrity of the specimens before and after SAWJP with different process parameters was experimentally studied,including microstructure,surface roughness,microhardness,and compressive residual stress(CRS).Finally,fatigue tests of the specimens before and after SAWJP treatment with different process parameters were carried out at room *** results highlighted that the fatigue life of the TA19 specimen can be increased by 5.46,5.98,and 6.28 times under relatively optimal process parameters,which is mainly due to the improved surface integrity of the specimen after SAWJP ***,the fatigue life of specimens treated with improper process parameters is decreased by 0.55 to 0.69 times owing to the terrible surface roughness caused by the material *** work verifies that SAWJP can effectively improve the surface integrity and fatigue life of workpieces,and reveals the relationship between process parameters,surface integrity,and fatigue life,which provides support for the promotion of SAWJP in the manufacturing fields.
With the rapid development of the autonomous driving industry, the robustness requirements for autonomous vehicle perception systems are increasing, and in-vehicle LiDAR has gradually become an essential sensing devic...
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This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of ir...
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This paper proposes a deformation evolution and perceptual prediction methodology for additive manufacturing of lightweight composite driven by hybrid digital twins(HDT).In order to improve manufacturing quality of irregular lightweight composite through boosting conceptual design in aeronautic and aerospace engineering,the HDT meaning hybridization of physical and digital domains,including deformation and energy efficiency can be built,where the essential parameters can be perceptually predicted in advance,by virtue of the fusion of physical sensors and digital *** long short term memory(LSTM)can be employed to void vanishing gradient problem and improve predicting precision via Recurrent Neural Networks,thereby laying a foundation for the *** diverse manufacturing requirements of different regions are integrated into the parameters designing phase by attaching region weights confirmed via empiricism and in-service *** effects of slicing strategy and external support structures on manufacturing quality are considered from the perspective of improving dimensional *** manufacturing efficiency and comprehensive costs are accounted as consideration factors,which are perceptually predicted via *** designed manufacturing parameters through HDT were virtually examined by evaluating the deformation and equivalent stress distributions of fabricated lightweight component with composite material through AM process *** physical experiments were conducted to verify the HDT-based pre-designing and optimization method of manufacturing parameters via fused deposition modeling(FDM).The energy consumption of actual manufacturing process was measured via digital power meter and applied to evaluate accuracy of perceptual prediction *** dimensional accuracy and distortion distribution of the manufactured lightweight prototype made with composite material were measured through the coordinate measuring machine(CMM)and 3D optica
Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...
Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field images captured by a camera array as input, and fuse them to achieve image de-occlusion.
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