China’s independent innovation ability in the field of artificial intelligence is a key link to occupy the commanding heights of future science and technology and talent competition. The cultivation of artificial int...
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Accurate estimation of key quality indexes is critical for achieving optimal control in industrial processes. However, fluctuations in operating conditions, coupled with process lags, lead to multimodal data distribut...
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Since one entity may have multiple mentions and relations between entities may stretch across multiple sentences in a document, the annotation of document-level relation extraction datasets becomes a challenging task....
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Learning early warning is of great significance for coping with students' learning risks. The existing research fails in modeling the fluctuation of students' learning states and providing the multi-level earl...
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In recent years, the three-way decision model has been widely used to address multi-criteria decision-making problems. However, existing models often overlook differences in the minimum requirements and risk aversion ...
In recent years, the three-way decision model has been widely used to address multi-criteria decision-making problems. However, existing models often overlook differences in the minimum requirements and risk aversion of decision-makers (DMs) across different criteria. Moreover, with the increasing complexity and uncertainty of decision problems, the accurate expression of evaluation values has become a critical challenge. Q-rung orthopair fuzzy sets (q-ROFSs), as an extension of intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs), offer stronger expressiveness and broader application scenarios. With this in mind, this paper proposes a three-way decision model oriented to the twin fuzzy concepts of q-rung orthopair. Specifically, we first define the twin fuzzy concepts to represent the minimum requirements of DMs and risk aversion coefficients for different criteria, and propose a new method for calculating relative loss functions. Next, based on the TOPSIS semantics, the positive and negative ideal correlation coefficients are constructed. A requirement correlation coefficient, which takes into account the needs of DMs, is also proposed, from which a novel method for calculating the grey conditional probability is developed. Furthermore, we construct three distinct three-way decision models based on three decision perspectives. In addition, the rationality and effectiveness of the proposed model are demonstrated using a supplier selection case, and the practicality of the model is verified using six data sets. The experimental results show that the SRCC values between the ranking results of the proposed method and the comparison methods are mostly greater than 0.7, further demonstrating the effectiveness of the model.
Multimodal recommender systems (MRSs) aim to integrate information from multiple modalities, for better capturing users' preferences. However, existing MRSs usually face the challenge of data sparsity, especially ...
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Mild cognitive impairment(MCI)as the potential sign of serious cognitive decline could be divided into two stages,i.e.,late MCI(LMCI)and early MCI(EMCI).Although the different cognitive states in the MCI progression h...
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Mild cognitive impairment(MCI)as the potential sign of serious cognitive decline could be divided into two stages,i.e.,late MCI(LMCI)and early MCI(EMCI).Although the different cognitive states in the MCI progression have been clinically defined,effective and accurate identification of differences in neuroimaging data between these stages still needs to be further *** this paper,a new method of clustering-evolutionary weighted support vector machine ensemble(CEWSVME)is presented to investigate the alterations from cognitively normal(CN)to EMCI to *** CEWSVME mainly includes two *** first step is to build multiple SVM classifiers by randomly selecting samples and *** second step is to introduce the idea of clustering evolution to eliminate inefficient and highly similar SVMs,thereby improving the final classification ***,we extracted the optimal features to detect the differential brain regions in MCI progression,and confirmed that these differential brain regions changed dynamically with the development of *** exactly,this study found that some brain regions only have durative effects on MCI progression,such as parahippocampal gyrus,posterior cingulate gyrus and amygdala,while the superior temporal gyrus and the middle temporal gyrus have periodic effects on the *** work contributes to understanding the pathogenesis of MCI and provide the guidance for its timely diagnosis.
The time varying generalized Sylvester equation (TVGSE) is widely used in many domains such as mathematics, engineering and control system. Differing from the zeroing neural network (ZNN) and varying parameter ZNN (VP...
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Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature ext...
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Recently,object detection based on convolutional neural networks(CNNs)has developed *** backbone networks for basic feature extraction are an important component of the whole detection ***,we present a new feature extraction strategy in this paper,which name is *** this strategy,we design:1)a sandwich attention feature fusion module(SAFF module).Its purpose is to enhance the semantic information of shallow features and resolution of deep features,which is beneficial to small object detection after feature fusion.2)to add a new stage called D-block to alleviate the disadvantages of decreasing spatial resolution when the pooling layer increases the receptive *** method proposed in the new stage replaces the original method of obtaining the P6 feature map and uses the result as the input of the regional proposal network(RPN).In the experimental phase,we use the new strategy to extract *** experiment takes the public dataset of Microsoft Common Objects in Context(MS COCO)object detection and the dataset of Corona Virus Disease 2019(COVID-19)image classification as the experimental object *** results show that the average recognition accuracy of COVID-19 in the classification dataset is improved to 98.163%,and small object detection in object detection tasks is improved by 4.0%.
Dear editor,Book thickness for graphs forms a major theme in graph theory and has a broad application in the fields of sorting permutations, fault tolerant VLSI design, parallel computing, and others. The book Thickne...
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Dear editor,Book thickness for graphs forms a major theme in graph theory and has a broad application in the fields of sorting permutations, fault tolerant VLSI design, parallel computing, and others. The book Thickness problem, even if the vertex order is taken as part of the input, was shown to be NP-complete in general [1, 2]. Just because of this, parameterized algorithms have been proposed to deal with it [3].
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