Evaluation of Machine Learning Models for Sentiment Analysis in the South Sumatra Governor Election Using Data Balancing Techniques by Febriyanti Panjaitan, Win Ce, Hery Oktafiandi, Ghanim Kanugrahan, Yudi Ramdhani, Vito Hafizh Cahaya Putra

“…This study compares five machine learning algorithms (SVM, Naïve Bayes, KNN, Decision Tree, and Random Forest) and examines the impact of data balancing on their performance. …”
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UniFL: Accelerating Federated Learning Using Heterogeneous Hardware Under a Unified Framework by Biyao Che, Zixiao Wang, Ying Chen, Liang Guo, Yuan Liu, Yuan Tian, Jizhuang Zhao

“…However, data encryption can significantly increase computing time, limiting its large-scale deployment. While hardware acceleration can be an effective solution, existing research has largely focused on a single hardware type, which hinders the acceleration of FL across the various heterogeneous hardware of the participants. …”
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Advancing Arabic Word Embeddings: A Multi-Corpora Approach with Optimized Hyperparameters and Custom Evaluation by Azzah Allahim, Asma Cherif

“…For sentiment analysis, vocabulary size was critical, while in similarity scoring, the FastText models achieved the highest scores, particularly with smaller window and vector sizes. …”
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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…DeepMol's predefined configurations and customizable objective functions make it accessible to users at all skill levels while enabling efficient and reproducible workflows. …”
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Dynamic Response Prediction of Railway Bridges Considering Train Load Duration Using the Deep LSTM Network by Sui Tan, Xiandong Ke, Zhenhao Pang, Jianxiao Mao

“…Therefore, this study develops a novel framework, combining the train–bridge coupling mechanism and deep learning algorithms to efficiently predict the train-induced bridge responses while considering train load duration. …”
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Multi-Feature Lightweight DeeplabV3+ Network for Polarimetric SAR Image Classification with Attention Mechanism by Junfei Shi, Shanshan Ji, Haiyan Jin, Yuanlin Zhang, Maoguo Gong, Weisi Lin

“…Besides, multiple features can provide more complementary information, while feature selection is crucial for classification. …”
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Design and Analysis of a Serial Manipulator for Pick and Drop Objects for Material Handling at Uiri Metal Forming Workshop. by Behangana, Abert

“…Future recommendations include refining control algorithms, integrating advanced safety features, and exploring innovative materials to improve performance. …”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…The dataset was partitioned into a training set comprising 70 % of the data and a testing set containing 30 % of the data using the ML algorithms. The results of the implemented algorithms demonstrated that the RF technique attained an accuracy of 100 %, while the DT technique scored an accuracy of 63 %, the NB approach scored an accuracy of 69 %, the K-NN technique scored an accuracy of 76 %, and the SVM technique scored an accuracy of 90 %. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…Compared with conventional algorithms such as DGI and CS, our method significantly improves the quality of reconstructed images. …”
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Multi-slice electron ptychographic tomography for three-dimensional phase-contrast microscopy beyond the depth of focus limits by Andrey Romanov, Min Gee Cho, Mary Cooper Scott, Philipp Pelz

“…We discuss further experimental and algorithmic improvements necessary to also resolve single weakly scattering atoms in 3D.…”
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Unraveling the co-morbidity between COVID-19 and neurodegenerative diseases through multi-scale graph analysis: A systematic investigation of biological databases and text mining by Negin Sadat Babaiha, Stefan Geissler, Vincent Nibart, Heval Atas Güvenilir, Vinay Srinivas Bharadhwaj, Alpha Tom Kodamullil, Juergen Klein, Marc Jacobs, Martin Hofmann-Apitius

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The PLSR-ML fusion strategy for high-accuracy leaf potassium inversion in karst region of Southwest China by Zhihao Song, Zhihao Song, Wen He, Yuefeng Yao, Ling Yu, Jinjun Huang, Yong Xu, Haoyu Wang

“…Validation coefficient of determination (R²) values reached 0.89, 0.94, and 0.96, respectively—representing improvements of 206%, 147%, and 108% over standalone algorithms. This performance gain was attributed to rigorous overfitting control: PLSR’s dimensionality reduction synergized with ensemble machine learning (RF, XGBoost, MLP) to eliminate redundant spectral features while retaining predictive signals. …”
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The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients by Zhou Liu, Guijun Jiang, Liang Zhang, Palpasa Shrestha, Yugang Hu, Yi Zhu, Guang Li, Yuanguo Xiong, Liying Zhan

“…Most importantly, two website prognostic prediction platforms were developed to enhance clinical accessibility: the ET model for AVGIB patients available at https://10zr656do5281.vicp.fun while the GB model for ANGIB patients accessible at http://10zr656do5281.vicp.fun.ConclusionThe ET model provides a reliable prognostic tool for AVGIB patients, while the GB model serves as a robust tool for ANGIB patients in predicting in-hospital mortality. …”
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Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking by Nikolaos Pavlidis, Andreas Sendros, Theodoros Tsiolakis, Periklis Kostamis, Christos Karasoulas, Eleni Briola, Christos Chrysanthos Nikolaidis, Vasilis Perifanis, George Drosatos, Eleftheria Katsiri, Despoina Elisavet Filippidou, Anastasios Manos, Pavlos S. Efraimidis

“…This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. …”
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FPGA-Accelerated Sparse Subset Segmentation Using ADMM for High-Resolution Imagery by Rupali Karthikeyan, Deep Amit Lodaya, Rama Muni Reddy Yanamala, Rayappa David Amar Raj, K. Krishna Prakasha, T. Subeesh, V. Anandkumar, Archana Pallakonda

“…This approach simplifies hardware integration and maintains accuracy while reducing latency and improving energy efficiency. …”
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Review of Self-Powered Wireless Sensors by Triboelectric Breakdown Discharge by Shuzhe Liu, Jixin Yi, Guyu Jiang, Jiaxun Hou, Yin Yang, Guangli Li, Xuhui Sun, Zhen Wen

“…Key research directions are synthesized to enhance TENG-based sensing capabilities, including novel device architectures, the optimization of RLC circuit models, the integration of machine learning algorithms, and power management strategies. While current breakdown discharge sensors face challenges such as energy dissipation, multimodal coupling complexity, and signal interpretation barriers, future breakthroughs in material engineering and structural design are anticipated to drive advancements in efficiency, miniaturization, and intelligent functionality in this field.…”
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MCOA: A Comprehensive Multimodal Dataset for Advancing Deep Learning in Corneal Opacity Assessment by Xinyu Ma, Jianxia Fang, Yaqi Wang, Zhichao Hu, Zhe Xu, Sha Zhu, Weijia Yan, Mengqi Chu, Jingwei Xu, Siting Sheng, Chujun Liu, Mingxuan Zhang, Ce Shi, Gangyong Jia, Wen Xu

“…However, the absence of large-scale, high-quality datasets hinders the development of deep learning algorithms for this purpose. To bridge this gap, we established the most extensive corneal opacity dataset available. …”
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Using Artificial Intelligence to Enhance Myelodysplastic Syndrome Diagnosis, Prognosis, and Treatment by Fabio Stagno, Giuseppe Mirabile, Patricia Rizzotti, Adele Bottaro, Antonio Pagana, Sebastiano Gangemi, Alessandro Allegra

“…In this review, we seek to identify the primary mechanisms and uses of artificial intelligence in myelodysplastic syndrome, pointing out its advantages and disadvantages while discussing the possible benefits of using AI pipelines in a therapeutic setting.…”
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Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar, Mohammed Yusuf Ansari, Ajay Vikram Singh, Shahab Uddin, Kirthi S. Prabhu, Sagnika Dash, Souhaila Al Khodor, Annalisa Terranegra, Matteo Avella, Sarada Prasad Dakua

“…Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
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