DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…It is not a widely prevalent disease, with a research gap caused by the absence of standardized datasets for model training and evaluation. This work presents a novel dataset, which strengthens the CNN model's resilience and creates standards for assessing keratoconus diagnostic techniques. …”
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Upregulation of FOXO3 in New-Onset Type 1 Diabetes Mellitus by Magdalena Zurawek, Marta Fichna, Piotr Fichna, Maria Czainska, Natalia Rozwadowska

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Robust CNN for facial emotion recognition and real-time GUI by Imad Ali, Faisal Ghaffar

“…To train the model, we joined the datasets, namely JAFFE and KDEF. We allocated 90% of the data for training, reserving the remaining 10% for testing purposes. …”
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Feature selection and data‐driven model for predicting the remaining useful life of lithium‐ion batteries by Yuhao Zhang, Yunfei Han, Tao Cai, Jia Xie, Shijie Cheng

“…The validity of this method is verified using the open‐source MIT battery dataset. Comparisons with models reported in the literature demonstrate that this method is generalisable and ensures accuracy across a wider range of predictions.…”
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Transformer-Driven Inverse Learning for AI-Powered Ceramic Material Innovation With Advanced Data Preprocessing by Murad Ali Khan, Syed Shehryar Ali Naqvi, Muhammad Faseeh, Do-Hyeun Kim

“…Subsequently, Variational Autoencoders (VAE) were used for data augmentation, enriching the dataset’s diversity. The Transformer model, leveraging this enhanced data, demonstrated strong predictive performance, achieving an R2 score of 0.966 for component analysis and an outstanding R2 score of 0.982 for process analysis in Barium Titanate (BaTiO3) material data. …”
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Epichloë scottii sp. nov., a new endophyte isolated from Melica uniflora is the missing ancestor of Epichloë disjuncta by Torsten Thünen, Yvonne Becker, Murray P. Cox, Samad Ashrafi

“…Phylogenetic reconstruction using a combined dataset of the tubB and tefA genes strongly support that E. scottii is a distinct species and the so far unknown ancestor species of the hybrid E. disjuncta. …”
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Arterial Stiffness in Breast Cancer Patients Treated with Anthracycline and Trastuzumab-Based Regimens by Özlem Yersal, Ufuk Eryilmaz, Hakan Akdam, Nezih Meydan, Sabri Barutca

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Comparative analysis of spins-first and wave functions-first students’ understanding of expressions in quantum mechanics by William D. Riihiluoma, Zeynep Topdemir, John R. Thompson

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Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM by Bo Sun, Wenting Hu, Hao Wang, Lei Wang, Chengyang Deng

“…Finally, the effectiveness of the proposed model is verified using the PHM2012 bearing dataset. Compared to several existing RUL prediction methods, the mean squared error, mean absolute error, and root mean squared error of the proposed method in this paper are reduced by 53%, 16.87%, and 31.68%, respectively, which verifies the superiority of the method. …”
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Circulation of Baffin Bay and Hudson Bay waters on the Labrador shelf and into the subpolar North Atlantic by E. Duyck, N. P. Foukal, E. Frajka-Williams

“…In this study, we use a surface drifter dataset spanning the period 1990–2023 to investigate the pathways followed by waters originating from Davis Strait and Hudson Strait on the Labrador shelf and into the interior subpolar North Atlantic. …”
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Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz by Mohammud Z. Bocus, Afzal Lodhi

“…The model has been trained and tested against an extensive measurement dataset capturing several areas and the diverse topography of the UK. …”
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Characterizing Heterogeneity in Drivers’ Merging Maneuvers Using Two-Step Cluster Analysis by Gen Li, Lu Sun

“…Merging maneuvers of 370 drivers collected from the NGSIM dataset are automatically and optimally segmented into four clusters (Early Merging Drivers at High Speed, Early Merging Drivers at Low Speed, Late Merging Drivers at Low Speed, and Late Merging Drivers at High Speed) by the two-step cluster analysis. …”
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A Semi-Supervised Learning Approach to Quality-Based Web Service Classification by Mehdi Nozad Bonab, Jafar Tanha, Mohammad Masdari

“…The quality features of web services obtained from the QWS dataset were used to evaluate the performance of the proposed algorithm. …”
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Characteristic Parameter Optimization of Wireless Flaw Sensing System Based on Active Interference Suppression Algorithm by Wenping Wu

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Lithium-Ion Battery Degradation Based on the CNN-Transformer Model by Yongsheng Shi, Leicheng Wang, Na Liao, Zequan Xu

“…This facilitates the online monitoring of battery degradation. The dataset used for training and validation consists of charge–discharge data from 124 lithium iron phosphate batteries. …”
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Vehicle Detection and Tracking Based on Improved YOLOv8 by Yunxiang Liu, Shujun Shen

“…The experimental results show that the proposed model reduces parameters and weight by approximately 36.5% and 25% respectively at the expense of only 0.2% mAP@0.5 compared with YOLOv8n on the UA-DETRAC dataset. In terms of tracking, MOTA, IDF1 and MOTP of the BoTSORT algorithm on the test video were superior to those of DeepSORT and ByteTrack. …”
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Rapid Determination of Pachymic Acid Content by Near-Infrared Spectroscopy by Jie Lu, Changqin Li, Lijun Liu, Wangjing Chai, Yabin Hou, Changyang Ma

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A Severe Case of Overlap of Morphea and Eosinophilic Fasciitis after Burn Injuries by Hania Sami, Faria Sami, Shahzad Ahmed Sami, Abdulqadir J. Nashwan

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Moor: Model-based offline policy optimization with a risk dynamics model by Xiaolong Su, Peng Li, Shaofei Chen

“…Finally, we use a risk-averse algorithm to learn the policy on the combined dataset of offline and generated data. We theoretically prove that MOOR can identify risk information of data and avoid utilizing high-risk data, our experiments show that MOOR outperforms existing approaches and achieves state-of-the-art results in risk-sensitive D4RL and risky navigation tasks.…”
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Vision transformers for automated detection of diabetic peripheral neuropathy in corneal confocal microscopy images by Chaima Ben Rabah, Ioannis N. Petropoulos, Rayaz A. Malik, Ahmed Serag

“…The ViT model's performance was also compared to ResNet50, a convolutional neural network (CNN) previously applied for DPN detection using CCM images. Using a dataset of approximately 700 CCM images, the ViT model achieved an AUC of 0.99, a sensitivity of 98%, a specificity of 92%, and an F1-score of 95%, outperforming previously reported methods. …”
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