Effective multimodal hate speech detection on Facebook hate memes dataset using incremental PCA, SMOTE, and adversarial learning by Emmanuel Ludivin Tchuindjang Tchokote, Elie Fute Tagne

“…This study highlights the mutually beneficial effect of combining SMOTE and incremental PCA, demonstrating how they improve the model's ability to correct class imbalance and boost performance. …”
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Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

“…Among the models, the GB classifier achieved the highest performance, followed by XGB and RF. …”
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CN2VF-Net: A Hybrid Convolutional Neural Network and Vision Transformer Framework for Multi-Scale Fire Detection in Complex Environments by Naveed Ahmad, Mariam Akbar, Eman H. Alkhammash, Mona M. Jamjoom

“…By leveraging the global context understanding of ViTs and the local feature extraction capabilities of CNNs, the model learns a multi-scale attention mechanism that dynamically focuses on fire regions at different scales, thereby improving accuracy and robustness. …”
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An Approach to Multiclass Industrial Heat Source Detection Using Optical Remote Sensing Images by Yi Zeng, Ruilin Liao, Caihong Ma, Dacheng Wang, Yongze Lv

“…Experimental results demonstrate the model’s robust performance, achieving a precision rate of 92.3% and a recall rate of 95.6% in detecting IHS objects across diverse backgrounds. …”
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Artificial Intelligence-Based Skin Lesion Analysis and Skin Cancer Detection by Momina Qureshi, Muhammad Athar Javed Sethi, Sayed Shahid Hussain

“…This sophisticated process improves CNN convolutions' stability during feature extraction, which in turn improves the model's overall performance in terms of prediction accuracy. …”
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A Real-Time Polygonal Wheel-Rail Force Identification Method Based on Convolutional Neural Networks (CNN) by Zeteng Zhang, Jinhai Wang, Jianwei Yang, Dechen Yao

“…Firstly, aiming at the characteristic of high-order polygon feature frequency of wheelset, multi-rigid dynamics model and flexibility-rigid dynamics model are established in SIMPACK to obtain data. …”
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A Two-Stream Deep Learning Framework for Robust Coral Reef Health Classification: Insights and Interpretability by Arslan Abdul Ghaffar, Gyu Sang Choi

“…Our methodology addresses challenges such as underwater variation and class imbalance through tailored data augmentation, multi-scale feature analysis, temporal modeling, and weighted loss functions. …”
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Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark by Marios C. Gkikas, Dimitris C. Gkikas, Gerasimos Vonitsanos, John A. Theodorou, Spyros Sioutas

“…The current study evaluates the performance of three machine learning models—Decision Trees, Random Forest, and Linear Regression—applied to aquaculture data to mitigate risks in aquaculture management. …”
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Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach by Yazeed Alashban

“…RESULTS: Test accuracy, training loss, and training accuracy showed better performance with our proposed architecture than with previous models. …”
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The application of artificial intelligence techniques in predicting game outcomes of professional basketball league: A systematic review. by Chuxuan Li, Hao Zhang, Yuan Zhang, Jing Shen, Ruopeng An

“…The studies underscore the importance of effective data processing and feature selection in enhancing model performance. …”
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HyCoViT: Hybrid Convolution Vision Transformer With Dynamic Dropout for Enhanced Medical Chest X-Ray Classification by Omid Almasi Naghash, Nam Ling, Xiang Li

“…Experimental results show that HyCoViT achieves state-of-the-art (SOTA) performance, with 98.81% accuracy for three-class surpassing the existing CNN-based model by average +4.90%., and SOTA transformer-based average by 2.05%. …”
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概念為本跨領域課程發展之研究—以國際文憑組織中學階段課程為例 Concept-Based Interdisciplinary Curriculum Development in International Baccalaureate Schools in Taiwan– The International Baccalaureate Middle Years... by 洪麗卿 Li-Ching Hung, 劉美慧 Meihui Liu, 王俐蘋 Li-Ping Wang

“…These findings suggest that the first school achieved a high level of horizontal integration across grades and effectively connected global and local experiences, serving as a model for future curriculum development. The second school conducted vertical integration over 3 years, focusing on coherence and alignment with the features of the National Curriculum Guideline 2019. …”
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Numerical analysis of transonic flow over the FFA-W3-211 wind turbine tip airfoil by M. C. Vitulano, M. C. Vitulano, D. De Tavernier, G. De Stefano, D. von Terzi

“…A preliminary validation of the latter CFD model is performed to demonstrate that the URANS approach is a viable method for predicting the aerodynamic performances in compressible and transonic flow that provides additional and more reliable information compared to the classical compressibility corrections. …”
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More Accurate Constraints for Self-Supervised Learning in Remote Sensing Images-Based Object Detection by Shangdong Zheng, Zebin Wu, Yang Xu, Qian Liu, Zhihui Wei

“…In this article, we focus on generating more accurate constraints by excavating the intercorrelation between fully and weakly supervised learning (WSL) to improve the performance of object detection in RSIs. Initially, WSL assigns the pseudoinstance-level annotations for the high-scoring positive bags to model the detector, which can be regarded as a weakened version of the region proposal network (RPN). …”
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Investigating the impact of fatty acid profiles on biodiesel lubricity using artificial intelligence techniques by Atthaphon Maneedaeng, Attasit Wiangkham, Atthaphon Ariyarit, Anupap Pumpuang, Ekarong Sukjit

“…To further analyze the impact of fatty acid composition on lubricity, an artificial intelligence (AI)-based approach using the Adaptive Boosting (AdaBoost) algorithm was implemented. The AI model effectively predicts wear scar diameter, friction coefficient, and film formation, providing insights into the complex interactions between fatty acid profiles and tribological performance. …”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

“…To address power quality issues caused by fluctuating irradiance and wind speeds, the study introduces the Adaptive Neuro-Deep Reinforcement Learning Bitterling Optimizer (AN-DRLBO). This model integrates Deep Reinforcement Learning (DRL) for adaptive energy conversion, Adaptive Neural Networks (ANN) for real-time system stabilization, and Bitterling Fish Optimization (BFO) for robust performance under transient conditions. …”
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Kinematic Integration Network With Enhanced Temporal Intelligence and Quality-Driven Attention for Precise Joint Angle Prediction in Exoskeleton-Based Gait Analysis by Lyes Saad Saoud, Irfan Hussain

“…Despite advances in deep learning for motion prediction, existing models struggle with balancing accuracy and real-time performance, particularly in wearable applications. …”
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EEG Signal Prediction for Motor Imagery Classification in Brain–Computer Interfaces by Óscar Wladimir Gómez-Morales, Diego Fabian Collazos-Huertas, Andrés Marino Álvarez-Meza, Cesar German Castellanos-Dominguez

“…The predicted EEG signals from the complete channels were used for feature extraction and MI classification. The results obtained indicate a notable efficacy of the proposed prediction method, showing an average performance of 78.16% in classification accuracy. …”
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Development and multi-cohort validation of a machine learning-based simplified frailty assessment tool for clinical risk prediction by Jiahui Lai, Cailian Cheng, Tiantian Liang, Leile Tang, Xinhua Guo, Xun Liu

“…SHAP analysis provided transparent insights into model predictions, facilitating clinical interpretation. …”
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Sentences, entities, and keyphrases extraction from consumer health forums using multi-task learning by Tsaqif Naufal, Rahmad Mahendra, Alfan Farizki Wicaksono

“…These results suggested that a larger model did not always perform better. We also found no indication of which ones between Indonesian and multilingual language models that generally performed better for our tasks. …”
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