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Multi-label feature selection is crucial for managing feature redundancy and irrelevance in high-dimensional datasets. Existing methods reduce information redundancy through subspace dimensionality reduction but often suffer from instability due ...

Augmented Reality (AR), which integrates virtual information with the real world, has increasingly been utilized in intervention studies for children with autism in recent years. Eye contact disorder, a prominent symptom of autism, significantly ...

This paper presents the first classical Convolutional Neural Network (CNN) that can be applied directly to data from unstructured finite element meshes or control volume grids. CNNs have been hugely influential in the areas of image ...

• Use of space-filling curves (SFCs) to apply CNNs to data on unstructured meshes.
• Introduction of multiple SFCs in order to improve the accuracy of the new CNNs.
• Use of sparse smoothing layers at the input and output of the CNN to ...

Learning a directed acyclic graph (DAG) from observational data plays a crucial role in causal inference and machine learning. However, the scarcity of observational data is a common phenomenon in real-world applications, where the current DAG ...

Emotion-cause pair extraction (ECPE) aims to extract all potential pairs of emotions and corresponding cause(s) from a given document. Current methods have focused on extracting possible emotion-cause pairs by directly analyzing the given ...

Aiming at the waste of irrigation water resources caused by inaccurate irrigation in mango orchard, a mango accurate irrigation decision-making system based on Lora is designed and developed to improve the yield and quality of mango. The system forms a ...

This paper considers the estimation of random regret minimization models using rank-ordered choice data. By analyzing Monte Carlo simulations results, we find that the efficiency increases as we use additional information on the ranking. Compared ...$\mathit{}$

Delicate perception to the loss-of-resistance signal is crucial for a successful children lumbar puncture. However, the skill development for residents in such complex and precise procedure is primarily performed directly on pediatric patients. Serious ...

Recent studies have managed to learn cross-lingual word embeddings in a completely unsupervised manner through generative adversarial networks (GANs). These GANs-based methods enable the alignment of two monolingual embedding spaces approximately, ...

This article has been retracted: please see Elsevier Policy on Article Withdrawal()

This article has been retracted at the request of the Editor-in-Chief.

Significant similarities were noticed post-publication ...

One mainstream method in cross-lingual word embeddings is to learn a linear mapping between two monolingual embedding spaces using a training dictionary. Successful linear mappings require isomorphic embedding spaces. However, monolingual embedding spaces ...

In this study, the problem of grouping motion for a second‐order multi‐agent network with both matched disturbances and mismatched disturbances is investigated, and finite‐time convergent algorithm of the dynamic system is proposed. By designing the ...

The optimal control problems play an important role in modern control theory. This paper focuses on the optimal problem for group flocking movement of multi-agent systems (MAS). Two new cost functions are proposed with distributed optimal ...

In order to solve the problem of flocking for multi-agent systems with external disturbances, this paper studies the finite-time consensus of second-order multi-agent systems with external disturbances. Based on the disturbance estimations of ...

In this paper, based on linear quadratic theory, the optimal control problem for multi-agent systems with external disturbances is studied. Firstly, the optimal distributed controller is designed by the performance index function without the ...

Wireless sensor network (WSN) is the key sensing resource for the internet of things (IoT) in vegetable greenhouse. The coverage control ensures that WSN can obtain enough effective information. However, the current coverage researches ignore the ...

As large-scale datacenters become to be widely used in massive data processing and storage, the power consumption of these datacenters cannot be ignored any more, which leads to a significant carbon footprint. Renewable energy sources are used recently ...

Recently, as the renewable and distributed power sources boost, many such resources are integrated into the smart grid as clean energy input. However, since the generation of solar power is intermittent and unstable, the smart grid needs to regulate the ...

The presence of time delays in communication introduces a limitation to the stability of bilateral teleoperation systems. This paper considers internal model control (IMC) design of linear teleoperation system with time delays, and the stability of ...

Due to nonlinearity and uncertainty of induction cooker system, it is difficult to establish an accurate mathematical model for control purpose. This paper proposes an appropriate fuzzy control strategy for controlling pan temperature of induction cooker ...