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In the engineering design of aerospace vehicles, design data at different stages exhibit hierarchical and heterogeneous distribution characteristics. Specifically, high-fidelity design data (such as from computational fluid dynamics simulations ...

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• We propose a novel Gaussian process fusion method for multi-fidelity data integration.
• Our method improves global modeling accuracy by 45% compared to traditional approaches.
• The adaptive weighting mechanism adjusts fusion weights ...

With the emergent attentive property of self-supervised Vision Transformer (ViT), Normalized Cuts (NCut) has resurfaced as a powerful tool for unsupervised dense prediction. However, the pre-trained ViT backbone (e.g., DINO) is frozen in existing ...

Traffic demand forecasting is of critical importance to the development of Intelligent Transportation System (ITS). Existing works employ various deep learning models to capture the complex spatial-temporal correlations in the time-evolving ...

• An integrated optimizing way for harvesting and unloading paths is developed.
• A five-step unloading method is proposed.
• Tank capacity and unloading points are considered.
• The entire crop harvesting process is simulated.

Optimization of path planning is becoming increasingly valuable aspect for unmanned combine harvesters. Considering the need to unload grain dozens of times daily, constituting roughly more than one-third of the overall time, the unloading ...

Generative models such as generative adversarial networks and autoencoders have gained a great deal of attention in the medical field due to their excellent data generation capability. This article provides a comprehensive survey of generative models for ...

Due to the widespread use of portable devices and the advancement of 5G technology, we have received a significant amount of mobile data, which requires prediction models for cellular traffic data. However, accurately forecasting mobile traffic ...${}^{\mathrm{}}$

• A novel 3D Split&Shuffle-GAN model for 3D medical image generation is proposed, and new inflation strategies are developed to facilitate training of 3D medical generation models. The proposed model significantly improves image generation ...

Background and Objective: The generation of three-dimensional (3D) medical images has great application potential since it takes into account the 3D anatomical structure. Two problems prevent effective training of a 3D medical generative model: (...

Traffic accident forecasting is of vital importance to the intelligent transportation and public safety. Spatial-temporal learning is the mainstream approach to exploring complex evolving patterns. However, two intrinsic challenges lie in traffic ...

Optimal transport is a machine learning problem with applications including distribution comparison, feature selection, and generative adversarial networks. In this paper, we propose feature-robust optimal transport (FROT) for high-dimensional ...

• A variable-diameter threshing drum is designed to change the threshing gap.
• A ...

According to different feeding rates, the threshing gap of rice combine harvester needs to be flexibly adjusted to prevent blockage. The research shows that the threshing performance of adjusting threshing gap by changing the drum ...

CAD technology has brought great convenience and effect to the design. This paper proposes to update the comparative analysis of the basic classical landscape grid space structure by constructing a landscape grid space design. According to the actual ...

In the current stage, software defect prediction is suffering the imbalanced data problem. Traditional methods are insensitive to defect-prone modules and tend to predict defect-prone modules as defect-free modules. To deal with this problem, ...

Estimating mutual information is an important statistics and machine learning problem. To estimate the mutual information from data, a common practice is preparing a set of paired samples ${\{({\mathit{x}}_i,{\mathit{y}}_i)\}}_{i=1}^n$$\stackrel{\mathrm{i}.\mathrm{i}.\mathrm{d}.}{\sim }p(\mathit{x},\mathit{y})$. However, in many situations, it ...

A new control method for stability, synchronization and transparency of bilateral teleoperation systems is investigated in this paper. For the environmental force identification, the weighted least square method (WLS) is used on slave side and then the ...

An improved Gaussian Pigeon-inspired Optimization algorithm is proposed to maintain diversity and improve the accuracy of the global optimum. In the proposed algorithm, Gaussian mutation is used to maintain the diversity of exploration, and the judgment ...

In this paper, we propose a new online feature selection algorithm for streaming data. We aim to focus on the following two problems which remain unaddressed in literature. First, most existing online feature selection algorithms merely utilize the first-...

This paper presents a nonlinear trajectory controller with improved performances for a general model of the waverider based on feedback linearization theory and composite nonlinear feedback (CNF) technique. First, a nonlinear controller is presented ...

The logistic regression is a widely used method for multimedia classification. However, when it is applied to high-order data such as video sequences, traditional vector-based logistic regression often incurs loss of space-time structural information. ...

Deep ConvNets have shown their good performance in image classification tasks. However, there still remains problems in deep video representations for action recognition. On one hand, current video ConvNets are relatively shallow compared with image ...

Technical manual is vital source of fault diagnosis and maintenance knowledge. To deal with the mass of manual text, which influence the speed of knowledge acquisition, and then effect the diagnostic efficiency, this paper proposes a method for ...