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In this paper, we consider numerical approximations for the optimal partition problem using Lagrange multipliers. By rewriting it into constrained gradient flows, three and four steps numerical schemes based on the Lagrange multiplier approach are ...

Minimally invasive surgery (MIS) is increasingly popular due to its smaller incisions, less pain, and faster recovery. Despite its advantages, challenges like limited visibility and reduced tactile feedback can lead to instrument and organ damage, ...${}_{\mathrm{}}$

Precise orbit, clock and observable-specific phase bias products play a pivotal role in facilitating precise point positioning (PPP) with ambiguity resolution (AR). The model and strategy used to generate Wuhan University Multi-GNSS (WUM) hourly ...

To solve the problem of incomplete feature extraction and difficulty in selecting optimal support vector machine parameters, a fault diagnosis method based on the ensemble empirical modal decomposition (EEMD) fuzzy entropy and improved beetle ...

Users’ diverse intentions drive the subsequent interaction based on users’ dynamic behavior trajectories. Despite the impressive progress of existing work on capturing the user’s intent, these methods still have the following challenges: (1) How ...

• We propose a model HICL fuses sequence contrastive learning (CL) and graph CL.
• The HICL can capture the dynamic and sparse intention in sequential recommendation.
• Experimental results demonstrate the effectiveness of mining users’ ...

A graph G with four or more vertices is called bicritical if the removal of any pair of distinct vertices of G results in a graph with a perfect matching. A bicritical graph is minimal if the deletion of each edge results in a non-bicritical ...

Personalized image aesthetics assessment aims to capture individual aesthetic preferences, which are influenced by image aesthetic attributes and user demographic attributes. The interaction of attributes facilitates the determination of users' ...

Effective animal intelligent monitoring is of great value in terms of ecological protection and endangered specie conservation. At present, computer vision technologies have shed light on animal intelligent monitoring. Especially, numerous deep ...

With the automobile becoming an indispensable means of travel in our daily life, road traffic accidents are becoming an increasingly serious social problem. In order to improve the driving safety of vehicles, the vehicle driving assistance system based ...

• A novel self-supervised aesthetic assessment method combining contrastive learning and masked modeling is proposed.
• The method uses Masked Image Modeling (MIM) to learn pixel-level features for contrastive learning.
• An online-...

Learning more abundant image features helps improve the image aesthetic assessment task performance. Masked Image Modeling (MIM) is implemented based on the Vision Transformer (ViT), which learns pixel-level features while reconstructing images. ...

During urban marathons, falls occur frequently, causing numerous injuries and safety hazards to participants. Athletes who can respond promptly when a fall occurs can reduce injuries caused by falls. In order to solve this problem, this paper studies ...

A graph G of order n is said to be k-factor-critical for integers 1 ≤ k < n, if the removal of any k vertices results in a graph with a perfect matching. A k-factor-critical graph G is called minimal if for any edge e ∈ E ( G ), G − e is not k-...

Reconfigurable intelligent surface (RIS) has recently been widely investigated in wireless communication systems due to its low deployment cost and high-performance gain. In this work, we study the multiple-RIS-assisted uplink multiple-user multiple-input ...

Space has become a new strategic force. The advantage of space information will also become the key to determining the future development of various countries. The aerospace powers led by the United States (US) are constantly reshaping the existing space ...

Conventional k nearest neighbor (KNN) rule is a simple yet effective method for classification, but its classification performance is easily degraded in the case of small size training samples with existing outliers. To address this issue, A multi-...

Temporal link prediction based on graph neural networks has become a hot spot in the field of complex networks. To solve the problems of the existing temporal link prediction methods based on graph neural networks do not consider the future time-domain ...

Introducing clean energy into urban cold chain distribution to achieve a green transition is crucial for reducing transportation and logistics emissions and promoting sustainable urban development. This study focuses on the Cold Chain Green Multi-...

• Proposing and modeling the CC-GMD-VRPTW-MF problem with mixed fleets.
• Designing a VNS algorithm enhanced by some new mechanisms.
• Validating algorithm with practical instances and MDVRPTW benchmarks.
• Investigating impact on ...

Digital twins have revolutionized the field of image enhancement by applying their unique capabilities. A digital twin refers to a virtual replica of a physical object or system, which can be utilized to simulate and analyze real-world scenarios. ...

The ubiquity and commoditization of wearable sensors have generated a deluge of user-generated health care data and played a key role in clinical utility, particularly when incorporated into personalized prediction models. The &#x201C;curse of ...

Dental caries is a prevalent noncommunicable disease that affects over half of the global population. It can significantly diminish individuals’ quality of life by impairing their eating and socializing abilities. Consistent dental check-ups and ...