From Image to Sequence: Exploring Vision Transformers for Optical Coherence Tomography Classification by Amirali Arbab, Aref Habibi, Hossein Rabbani, Mahnoosh Tajmirriahi

“…Methods: This paper introduces a novel hybrid model that integrates the strengths of convolutional neural networks (CNNs) and vision transformer (ViT) to overcome these obstacles. …”
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Digital Transformation in Guidance and Counseling: The Influence of Website Media on Students’ Self-Awareness by Dona Fitri Annisa, Prio Utomo, Augusto da Costa

“…Digital transformation in guidance and counseling leverages website media to enhance students’ self-awareness, adapting to technological advancements in education. …”
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A Multi‐Scale Time Adaptive Fusion Network for Transformer Fault Diagnosis by XuMing Liu, XiaoKun He, YongLin Li

“…Finally, the multi‐scale temporal fusion (MSTF) module balances the fusion of multi‐scale temporal features and global dependencies, adapting to different tasks and data distributions. Extensive experiments on publicly available datasets demonstrate that the MSTAFN model outperforms comparison models across multiple evaluation metrics, proving its effectiveness and superiority in transformer fault diagnosis.…”
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Transforming reading self-efficacy in EFL Classrooms: The role of task-based instruction by Yohannes Joressa Wordofa, Mulu Geta Gencha, Aregay Meressa Hadgu

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An Overview: PAH and Nitro-PAH Emission from the Stationary Sources and their Transformations in the Atmosphere by Yen-Yi Lee, Yen-Kung Hsieh, Bo-Wun Huang, Justus Kavita Mutuku, Guo-Ping Chang-Chien, Shiwei Huang

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Predictors of hemorrhagic transformation after acute ischemic stroke based on the experts’ opinion by João Brainer Clares de ANDRADE, Jay Preston MOHR, Fabricio Oliveira LIMA, Levi Coelho Maia BARROS, Camila Rodrigues NEPOMUCENO, Leonardo Barreira PORTELA, Gisele Sampaio SILVA

“…ABSTRACT Background: Hemorrhagic transformation (HT) is a common complication after ischemic stroke. …”
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Time–Frequency Transformations for Enhanced Biomedical Signal Classification with Convolutional Neural Networks by Georgios Lekkas, Eleni Vrochidou, George A. Papakostas

“…In this study, we investigated the effectiveness of different 1D-to-2D transformation methods to classify electrocardiogram (ECG) and electroencephalogram (EEG) signals. …”
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Alternate encoder and dual decoder CNN-Transformer networks for medical image segmentation by Lin Zhang, Xinyu Guo, Hongkun Sun, Weigang Wang, Liwei Yao

“…Abstract Accurately extracting lesions from medical images is a fundamental but challenging problem in medical image analysis. In recent years, methods based on convolutional neural networks and Transformer have achieved great success in the medical image segmentation field. …”
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TFTformer: A novel transformer based model for short-term load forecasting by Ahmad Ahmad, Xun Xiao, Huadong Mo, Daoyi Dong

“…Recent studies have employed Transformer models in forecasting due to their unique attention mechanisms and ability to extract correlations in data. …”
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Transforming engineering education in the digital era: findings from a systematic review by Yu-Ping Hsu, Danielle F. Chiang, Ifedayo Kehinde

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TRANSFORMATION OF RUSSIAN CASPIAN PASTURE ECOSYSTEMS UNDER THE NEW SOCIO-ECONOMIC CONDITIONS by V. G. Lazareva, V. A. Bananova, K. M. Petrov, D. A. Boldyreva, G. M. Borlikov

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DECTNet: A detail enhanced CNN-Transformer network for single-image deraining by Liping Wang, Guangwei Gao

“…Extensive experiments have demonstrated that DECTNet outperforms some state-of-the-art methods on single-image deraining tasks. Furthermore, our model achieves competitive results on three low-light datasets and a single-image desnowing dataset, highlighting its versatility and effectiveness across different image restoration challenges.…”
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Transforming Masculinities Through Cross-Cultural Collaboration: Reflections on Building a Community of Practice Framework by Liza Lorenzetti, Aamir Jamal, Rita Dhungel, Gabrielle Hosein, Sarah Thomas, Jeffery Halovorsen

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Multiscale Graph Transformer Network With Dynamic Superpixel Pyramid for Hyperspectral Image Classification by Tingting Wang, Yao Sun, Yunfeng Hu

“…To address these limitations, we propose a multi-scale graph transformer network (MSGTN), which captures spatial features at different scales through multiscale graph convolutional networks (GCNs) with adaptive graph structures. …”
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PATNet: Permute attention and transformer-enhanced network for segmentation of musculoskeletal ultrasound images by Yating Wu, Feng Bu, Jin Tian, Li Zhao, Guangfei Yang, Jianming Lu

“…In addition, PATNet incorporates Transformer modules to capture long-range dependencies in the image and leverages skip connections and multi-scale feature fusion mechanisms to enhance feature interaction and representation across different levels. …”
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Digital Franchising in the Age of Transformation: Insights from the Motivation-Opportunity-Ability Framework by Tung-Lai Hu, Chuang-Min Chao, Chien-Chih Wu, Chia-Hung Lin, Shu-Che Chi

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Nystromformer based cross-modality transformer for visible-infrared person re-identification by Ranjit Kumar Mishra, Arijit Mondal, Jimson Mathew

“…To address this, we propose NiCTRAM: a Nyströmformer-based Cross-Modality Transformer designed for robust VIS-IR person re-identification. …”
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Beyond averaging: A transformer approach to decoding event related brain potentials by Philipp Zelger, Manuel Arnold, Sonja Rossi, Josef Seebacher, Franz Muigg, Simone Graf, Antonio Rodríguez-Sánchez

“…The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. …”
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Enhancing Antidiabetic Drug Selection Using Transformers: Machine-Learning Model Development by Hisashi Kurasawa, Kayo Waki, Tomohisa Seki, Eri Nakahara, Akinori Fujino, Nagisa Shiomi, Hiroshi Nakashima, Kazuhiko Ohe

“…Based on the performance of previous studies, we set a performance target of achieving a receiver operating characteristic area under the curve (ROC-AUC) above 0.95. MethodsA transformer-based encoder-decoder model predicts whether 44 types of diabetes drugs will be prescribed. …”
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Transformative agency of students as a resource to form civic consciousness in education system by M. V. Pevnaya, A. N. Tarasova, D. F. Telepaeva, D. S. Protasov

“…The conditions of the environment of civic participation in the education system largely determine the differences in the subjective value characteristics of high school students and university students, revealing the transformative agency in the development of their civic consciousness.Practical significance. …”
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