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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Improving automatic cyberbullying detection in social network environments by fine-tuning a pre-trained sentence transformer language model
The internet use among children and adolescents has increased massively recently. This situation has promoted harmful situations such as...
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Unveiling intrusions: explainable SVM approaches for addressing encrypted Wi-Fi traffic in UAV networks
Unmanned aerial vehicles (UAVs), also known as drones, have become instrumental in various domains, including agriculture, geographic information...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Combinatorial refinement on circulant graphs
The combinatorial refinement techniques have proven to be an efficient approach to isomorphism testing for particular classes of graphs. If the...
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Hulls of cyclic codes with respect to the regular permutation inner product
In this paper, we introduce regular permutation inner products which contain the Euclidean inner product. And we generalize some properties of the...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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How clustering affects the convergence of decentralized optimization over networks: a Monte-Carlo-based approach
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent...
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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
