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A synthetic data generation system based on the variational-autoencoder technique and the linked data paradigm
Currently, the generation of synthetic data has become very fashionable, either due to the need to create data in certain specific contexts or to...
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Twit-CoFiD: a hybrid recommender system based on tweet sentiment analysis
Internet users are overwhelmed by the vast number of services and products to choose from. This data deluge has led to the need for recommender...
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Hybrid physics-infused 1D-CNN based deep learning framework for diesel engine fault diagnostics
Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result,...
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DSPformer: discovering semantic parts with token growth and clustering for zero-shot learning
Transformers have achieved success in many computer vision tasks, but their potential in Zero-Shot Learning (ZSL) has yet to be fully explored. In...
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Injecting the score of the first-stage retriever as text improves BERT-based re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the...
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Deep reinforcement learning-based scheduling in distributed systems: a critical review
Many fields of research use parallelized and distributed computing environments, including astronomy, earth science, and bioinformatics. Due to an...
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An aviation accidents prediction method based on MTCNN and Bayesian optimization
The safety of the civil aviation system has been of increasing concern with several accidents in recent years. It is urgent to put forward a precise...
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Optimization-based convolutional neural model for the classification of white blood cells
White blood cells (WBCs) are one of the most significant parts of the human immune system, and they play a crucial role in diagnosing the...
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Bearing fault diagnosis using multiple feature selection algorithms with SVM
This paper presents an efficient approach to diagnose defects in various components of bearings in rotating machines using vibration signature...
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Latent side-information dynamic augmentation for incremental recommendation
The incremental recommendation involves updating existing models by extracting information from interaction data at current time-step, with the aim...
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An overview of semantic-based process mining techniques: trends and future directions
Process mining algorithms essentially reflect the execution behavior of events in an event log for conformance checking, model discovery, or...
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Electronic medical records imputation by temporal Generative Adversarial Network
The loss of electronic medical records has seriously affected the practical application of biomedical data. Therefore, it is a meaningful research...
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Cores in multiway networks
The notion of a core is generalized to multiway networks. To determine the multiway cores, we adapted already-known algorithms for determining the...
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Dirichlet compound negative multinomial mixture models and applications
In this paper, we consider an alternative parametrization of Dirichlet Compound Negative Multinomial (DCNM) using rising polynomials. The new...
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A digital pen-based writing state recognition algorithm for student performance assessment
Technology-enhanced learning is an irresistible trend in intelligent education. However, most digital pen-based studies focus on handwriting...
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Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges
Large language models (LLMs) have exhibited remarkable efficacy and proficiency in a wide array of NLP endeavors. Nevertheless, concerns are growing...
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One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading
We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of...
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Multi-view Heterogeneous Graph Neural Networks for Node Classification
Recently, with graph neural networks (GNNs) becoming a powerful technique for graph representation, many excellent GNN-based models have been...
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Analyzing Healthcare Processes with Incremental Process Discovery: Practical Insights from a Real-World Application
AbstractMost process mining techniques are primarily automated, meaning that process analysts input information and receive output. As a result,...
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Lcp-mixer: a lightweight model based on concept-level perception for NLP
Transformer-based models excel in natural language processing tasks but demand extensive computational resources and memory. To address this...
