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The increase in online information has overwhelmed users with opinions and comments on various products and services, making decision-making a daunting task. Text summarization can help by distilling long or multiple documents into concise, ...

Data-driven models have shown broad application prospects in soft sensor modeling. However, numerous challenges persist. On the one hand, data-driven soft sensor methods have high requirements on data quality. On the other hand, models relying on ...

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• A novel PMVAER model was developed for soft sensing of penicillin fermentation.
• The PMVAER model integrated experimental data and physical monotonicity.
• The model disentangled the dimension related to labels from the latent ...

We propose the first comprehensive approach for modeling and analyzing the spatiotemporal shape variability in tree-like 4D objects, i.e., 3D objects whose shapes bend, stretch and change in their branching structure over time as they deform, grow,...${\mathbb{}}^{\mathrm{}}$

The information contained in sparse multi-channel sEMG signals is limited, which requires a high standard for feature representation learning. Based on this, some solutions involve using multiple features to construct multiple views in order to ...

The development of IPFS (InterPlanetary File System) and blockchain-based distributed storage projects has brought new possibilities to the field of storage. This paper proposes a blockchain-based cooperative game bilateral matching architecture ...

• Proposal of blockchain-based distributed storage architecture addressing privacy, security, and transactional issues in data sharing. Introduces a bilateral matching allocation algorithm for efficient resource allocation.
• Introduction ...

The process of tunnel construction is essential. Real-time monitoring of the tunnel construction process can find and solve the problems in the tunnel construction in time to ensure a smooth construction process and stable construction quality. Therefore,...

Truck platooning is a promising technology in freight transport. To commercialize truck platooning as early as possible, its evaluation is in urgent need. For truck platooning evaluation, simulation platforms play a crucial role. However, there has not ...

This work deals with the Multi-Vehicle Trajectory Planning (MVTP) problem in unstructured conflict areas. Compared with MVTP on structured roads, the more complex intersection and the more conflicting motions of vehicles, set higher requirements for the ...

The proliferation of misinformation jeopardises social cohesion, distorts the truth, and destabilises democratic processes. There have been numerous studies focused on detecting misinformation within online social networks. Nevertheless, much of ...

Higher education institutions face vast amounts of complex data from various sources. Extracting meaningful insights from this data can improve student outcomes and institutional performance. This paper proposes novel evolutionary optimization ...

• An integrated EDM-LA framework is proposed for higher education management systems.
• A multi-objective evolutionary algorithm is developed to optimize multiple criteria simultaneously.
• Theoretical analyses provide convergence proofs ...

The present DOA estimation approach based on sparse Bayesian learning has two major shortcomings: high algorithm complexity and large estimate errors. These two flaws are mostly the result of an excessive number of complex-valued matrix inversion ...

This paper investigates fault-tolerant learning control for air-breathing hypersonic vehicles (AHVs) subject to parametric uncertainties, external disturbances, and actuator faults. By treating the flexible dynamics as equivalent disturbance, the ...

• Fault-tolerant learning control is proposed for hypersonic vehicles.
• Actuator-fault problem is intelligently accommodated.
• Parametric uncertainties and disturbances are neuro-adaptively handled.

Point cloud completion aims at completing shapes from their partial. Most existing methods utilized shape's priors information for point cloud completion, such as inputting the partial and getting the complete one through an encoder-decoder deep learning ...

This paper starts by systematically analyzing the factors that affect user power outage losses based on the electricity consumption characteristics, outage characteristics, and distribution network operation characteristics. It constructs a factor system ...

Scientific and accurate prediction of energy production is important for exploring energy alternative paths, adjusting energy structure and industrial layout in a targeted manner, and promoting strategic energy transformation. In this paper, a ...

• A novel model (HDLGM(1,1,τ)) is established by considering the time-lagged Logistic.
• Logistic harvest items are introduced into the novel model.
• Modeling short- and medium-term forecasting ability was Enhanced.
• The proposed ...

Recurrent spiking neural networks (RSNNs) hold great potential for advancing artificial general intelligence, as they draw inspiration from the biological nervous system and show promise in modeling complex dynamics. However, the widely-used surrogate ...

Deep learning-based single-frame Monte Carlo denoising techniques have demonstrated remarkable results in photo-realistic rendering research. However, the current state-of-the-art methods relying on self-attention mechanisms underutilize auxiliary ...

How can one analyze detailed 3D biological objects, such as neuronal and botanical trees, that exhibit complex geometrical and topological variation? In this paper, we develop a novel mathematical framework for representing, comparing, and computing ...

The phenomenon known as the “echo chamber” has been widely acknowledged as a significant force affecting society. This has been particularly evident during the Covid-19 pandemic, wherein the echo chamber effect has significantly influenced public ...

In this article, a prescribed learning controller is developed for nonminimum phase air-breathing hypersonic vehicles (AHVs) in the presence of parametric uncertainties and external disturbances. In comparison with the current state of the art, ...