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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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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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Construction and application of medication reminder system: intelligent generation of universal medication schedule
BackgroundPatients with chronic conditions need multiple medications daily to manage their condition. However, most patients have poor compliance,...
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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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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...
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Explicit constructions of NMDS self-dual codes
Near maximum distance separable (NMDS) codes are important in finite geometry and coding theory. Self-dual codes are closely related to...
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Sublinear Algorithms in T-Interval Dynamic Networks
We consider standard T - interval dynamic networks , under the synchronous timing model and the broadcast CONGEST model. In a T - interval dynamic network ,...
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The Multi-attribute impact of hyperlinks in blogs: an emotion-centric approach
As a digital social medium, blogs have transformed into arenas where individuals can express their perspectives, concepts, and feelings. This...
