Heat transfer performance prediction for heat pipe using deep learning based on wick type

IJ **, YY Park, IC Bang - International Journal of Thermal Sciences, 2024 - Elsevier
Heat pipes are highly efficient heat transfer devices that have found widespread use in
various fields. However, accurately predicting their heat transfer performance under wide …

A Comprehensive Survey on Data Augmentation

Z Wang, P Wang, K Liu, P Wang, Y Fu, CT Lu… - arxiv preprint arxiv …, 2024 - arxiv.org
Data augmentation is a series of techniques that generate high-quality artificial data by
manipulating existing data samples. By leveraging data augmentation techniques, AI …

SAT: Improving semi-supervised text classification with simple instance-adaptive self-training

H Chen, W Han, S Poria - arxiv preprint arxiv:2210.12653, 2022 - arxiv.org
Self-training methods have been explored in recent years and have exhibited great
performance in improving semi-supervised learning. This work presents a Simple instance …

Image and Text: Fighting the Same Battle? Super-resolution Learning for Imbalanced Text Classification

R Meunier, F Benamara, V Moriceau… - 2023 Conference on …, 2023 - hal.science
In this paper, we propose SRL4NLP, a new approach for data augmentation by drawing an
analogy between image and text processing: Super-resolution learning. This method is …

PromptDA: Label-guided Data Augmentation for Prompt-based Few-shot Learners

C Chen, K Shu - arxiv preprint arxiv:2205.09229, 2022 - arxiv.org
Recent advances in large pre-trained language models (PLMs) lead to impressive gains in
natural language understanding (NLU) tasks with task-specific fine-tuning. However, directly …

[HTML][HTML] Operating condition optimization of liquid metal heat pipe using deep learning based genetic algorithm: Heat transfer performance

IJ **, DH Lee, IC Bang - Nuclear Engineering and Technology, 2024 - Elsevier
Liquid metal heat pipes play a critical role in various high-temperature applications, with
their optimization being pivotal to achieving optimal thermal performance. In this study, a …

Probabilistic interpolation with mixup data augmentation for text classification

R Xu, Y Zhang, K Ren, Y Huang, X Wei - International Conference on …, 2024 - Springer
Supervised deep learning models often confront the dilemma of insufficient training data,
where the Mixup method, as a unique data augmentation technique, addresses this issue of …

Enhancing Effectiveness and Robustness in a Low-Resource Regime via Decision-Boundary-aware Data Augmentation

K **, J Lee, J Choi, S Song, Y Kim - arxiv preprint arxiv:2403.15512, 2024 - arxiv.org
Efforts to leverage deep learning models in low-resource regimes have led to numerous
augmentation studies. However, the direct application of methods such as mixup and cutout …

Summarization-based Data Augmentation for Document Classification

Y Wang, N Yoshinaga - arxiv preprint arxiv:2312.00513, 2023 - arxiv.org
Despite the prevalence of pretrained language models in natural language understanding
tasks, understanding lengthy text such as document is still challenging due to the data …

Evaluation Metrics for Text Data Augmentation in NLP

M Amadeus, WAC Castañeda - arxiv preprint arxiv:2402.06766, 2024 - arxiv.org
Recent surveys on data augmentation for natural language processing have reported
different techniques and advancements in the field. Several frameworks, tools, and …