Lead-free antiferroelectric ceramics with high energy storage performance show great potential in pulsed power ***,poor breakdown strength and antiferroelectric stability are the two main drawbacks that limit the ener...
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Lead-free antiferroelectric ceramics with high energy storage performance show great potential in pulsed power ***,poor breakdown strength and antiferroelectric stability are the two main drawbacks that limit the energy storage performance of antiferroelectric ***,highquality(Ag_(1-x)Na_(x))(Nb_(1-x)Ta_(x))O_(3)ceramics were prepared by the tape casting *** breakdown strength was greatly improved as a result of the high density and fine grains,while the antiferroelectric stability was enhanced owning to the M2 *** from the synergistic improvement in breakdown strength and antiferroelectric stability,(Ag_(0.80)Na_(0.20))(Nb_(0.80)Ta_(0.20))O_(3)ceramic reveals a benign energy storage performance of W_(rec)=5.8 J/cm^(3)and h=61.7%with good temperature stability,frequency stability and cycling *** is also found that the high applied electric field can promote the M2-M3 phase transition,which may provide ideas to improve the thermal stability of the energy storage performance in AgNbO_(3)-based ceramics.
Natural Language Inference (NLI) is a branch of Natural Language Processing (NLP) whose main task is to determine the relationship between two sentences. Such tasks essentially use pre-trained models to ensure accurac...
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Image coloring is an inherently uncertain and multimodal problem. By inputting a grayscale image into a coloring network, visually plausible colored photos can be generated. Conventional methods primarily rely on sem...
Image coloring is an inherently uncertain and multimodal problem. By inputting a grayscale image into a coloring network, visually plausible colored photos can be generated. Conventional methods primarily rely on semantic information for image colorization. Although effective in coloring images with clear semantic information, these methods still suffer from color contamination and semantic confusion. This is largely due to the limited capacity of convolutional neural networks to effectively learn deep semantic information inherent in *** this paper, we propose a network structure that addresses these limitations by leveraging multi-level semantic information classification and fusion. Additionally, we introduce a global semantic fusion network to combat the issues of color contamination. The proposed coloring encoder accurately extracts object-level semantic information from *** further enhance visual plausibility, we employ a self-supervised adversarial training method. We train the network structure on various datasets with varying amounts of data and evaluate its performance using the ImageNet validation set and COCO validation set. Experimental results demonstrate that our proposed RepColor can generate more realistic images compared to previous approaches, showcasing its high generalization ability.
In this paper, a novel method combining orthogonal polarization laser self-mixing interference is proposed. The method utilizes a rotating cuvette to measure the refractive index of liquids at different concentration...
In this paper, a novel method combining orthogonal polarization laser self-mixing interference is proposed. The method utilizes a rotating cuvette to measure the refractive index of liquids at different concentrations. The cuvette is filled with the liquid to be measured and rotated by a certain angle. The change in the number of interference fringes, caused by comparing an empty cuvette with a liquid-filled cuvette, is used to calculate the refractive index of the liquid. A four-fold logic subdivision algorithm is then used to improve measurement resolution. The experimental results show that for pure water and different NaCl and glucose solutions concentrations, the average relative errors are 0.47%, 0.59%, and 2.17%, respectively, with the maximum relative error within ±2.54%. The standard deviation of all solutions is less than 3.4%.
This contribution generalizes our real-time Super Sampling control (SSC) method for pixel light intensities of automotive matrix headlights to a general MapReduce method. The redesigned control method is now a general...
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ISBN:
(数字)9798350394924
ISBN:
(纸本)9798350394931
This contribution generalizes our real-time Super Sampling control (SSC) method for pixel light intensities of automotive matrix headlights to a general MapReduce method. The redesigned control method is now a generalization with extended capabilities of well-known control methods, which can be used to find an efficient control stagey for a specific matrix headlight and target illumination. The process of finding the objectively best control parameters is shown on real matrix headlights with 84 and 16,384 pixels. For a homogeneous target illumination, the SSC method achieves for the 84 pixels headlamp an up to 8.84 % lower Root Mean Squared Error (RMSE) of the intensity distribution than a rectangular lighting approximation without the novel intensity mapping and a 95.85 % lower RMSE for the 16,384 pixels headlamp.
The contribution at hand presents and evaluates a novel matrix headlamp lighting distribution optimized for computer vision and energy consumption, thus enhancing automated vehicles' safety through an improved per...
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ISBN:
(数字)9798350394924
ISBN:
(纸本)9798350394931
The contribution at hand presents and evaluates a novel matrix headlamp lighting distribution optimized for computer vision and energy consumption, thus enhancing automated vehicles' safety through an improved perception. The light distribution considers the materials of the environment to illuminate each material selectively with a different intensity. The simulative results show that today's real light distributions are inefficient for automated driving and that the proposed material-based illumination can enhance the detection quality by over 80% while saving energy simultaneously, outperforming real and homogenous light distributions.
The goal of Multi-View Stereo (MVS) is to robustly recover an accurate 3D point cloud from multiple views. In this paper, we propose a novel Multi-View Stereo network with Regional consistency and Discrepancy cost vo...
The goal of Multi-View Stereo (MVS) is to robustly recover an accurate 3D point cloud from multiple views. In this paper, we propose a novel Multi-View Stereo network with Regional consistency and Discrepancy cost volume, denoted as MVSRD. Firstly, a full-feature interaction transformer is presented, which learns the regional consistency between the reference and source views, improving the robustness of reconstruction. Secondly, a discrepancy cost volume is designed to emphasize pixel-level differences between feature volumes. It facilitates the construction of high-quality cost volume to enhance the accuracy of reconstruction. Extensive experiments on the DTU and Tanks & Temples datasets demonstrate that our MVSRD achieves state-of-the-art performance.
This paper focuses on exploring the problem of achieving leader-follower consensus in uncertain Euler-Lagrange multi-agent systems, which are subjected to disturbance, and operate on switched digraph. To be more preci...
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The trajectory tracking problem is a fundamental control task in the study of mechanical systems. Hamiltonian systems are posed on the cotangent bundle of configuration space of a mechanical system, however, symmetrie...
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The trajectory tracking problem is a fundamental control task in the study of mechanical systems. Hamiltonian systems are posed on the cotangent bundle of configuration space of a mechanical system, however, symmetries for the full cotangent bundle are not commonly used in geometric controltheory. In this paper, we propose a group structure on the cotangent bundle of a Lie group and leverage this to define momentum and configuration errors for trajectory tracking, drawing on recent work on equivariant observer design. We show that this error definition leads to error dynamics that are themselves “Euler-Poincare like” and use these to derive simple, almost global trajectory tracking control for fully-actuated Euler-Poincare systems on a Lie group state space.
Noble metal materials have been identified as high efficiency catalysts for electrocatalytic reduction of nitrate,and the synthesis and manufacture of high catalytic activity and environmentally friendly catalysts of ...
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Noble metal materials have been identified as high efficiency catalysts for electrocatalytic reduction of nitrate,and the synthesis and manufacture of high catalytic activity and environmentally friendly catalysts of activating hydrogen for water purification applications is extremely *** this work,the Pd-Cu single-atom catalysts(Pd-Cu-N-BC)were first prepared by direct growth of Pd-Cu single-atom on bamboo biochar by regulating the concentration of precursors and doping method,and then enhanced electrocatalytic reduction nitrate performance and N2 *** results showed that Pd-Cu-N-BC displayed excellent catalytic activity and reusability in electrocatalytic reduction nitrate with a low potential of 0.47 V ***(@10 mA cm−2).The maximum nitrate removal efficiency and N2 generation could reach about 100%and 72.32%within 180 min,*** density functional theory(DFT)calculations confirmed that Cu atoms could catalyze the electrochemical reduction of nitrate to nitrite,and Pd atoms anchored in the nitrogen-doped biochar(N-BC)lattice could catalyze electrochemical reduction of nitrite to N2 involving the formation of hydrogen radical(H*).The characterization results of XANES showed that electronic synergistic effect between Pd and Cu single atoms significantly promotes the N2 production through hydrogenation while inhibiting the generation of byproducts,leading to significantly enhanced electrocatalytic reduction of nitrate to ***,Pd-Cu-N-BC was designed as a 3D particle electrode for enhanced electrocatalytic reduction of nitrate,exhibiting excellent stability and reusability,which could be considered as a suitable candidate for applications in the remediation of nitrate contamination.
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