A Deep Learning-Based Approach for Two-Phase Flow Pattern Classification Using Void Fraction Time Series Analysis by Jefferson Dos Santos Ambrosio, Marco Jose da Silva, Andre Eugenio Lazzaretti

“…Flow regime classification is essential for analyzing and modeling two-phase flows, as it demarcates the flow behavior and influences the selection of appropriate predictive models. Machine learning-based approaches have gained relevance in flow regime classification research in the last few years. …”
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Analysis of Autonomous Penetration Testing Through Reinforcement Learning and Recommender Systems by Ariadna Claudia Moreno, Aldo Hernandez-Suarez, Gabriel Sanchez-Perez, Linda Karina Toscano-Medina, Hector Perez-Meana, Jose Portillo-Portillo, Jesus Olivares-Mercado, Luis Javier García Villalba

“…To enhance the effectiveness of these tests, Machine Learning (ML) has been integrated, showing significant potential for identifying anomalies across various security areas through detailed detection of underlying malicious patterns. …”
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Impacts of Biochar Application on Inorganic Phosphorus Fractions in Agricultural Soils by Liwen Lin, Yutao Peng, Lin Zhou, Baige Zhang, Qing Chen, Hao Chen

“…Due to the complex processes by which biochar affects soils, more systematic evaluations and predictive methods (e.g., modeling, machine learning) are needed to support sustainable agriculture and environmental practices.…”
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Application of Artificial Intelligence in Radiological Image Analysis for Pulmonary Disease Diagnosis: A Review of Current Methods and Challenges by Karolina Zalewa, Joanna Olszak, Wojciech Kapłan, Dominika Orłowska, Lidia Bartoszek, Marta Kaus, Natalia Klepacz

“… Introduction and purpose Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), is revolutionizing radiology by improving diagnostic accuracy and efficiency. …”
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Pengenalan Jalan Berlubang Berbasis Vision Menggunakan Pyramid Histogram Of Oriented Gradients by Ahmad Habib Fitriansyah, Ema Rachmawati, Risnandar Risnandar

“…This article presents a new approach using image processing and machine learning to identify potholes on roads. The proposed system uses shape features extracted from Pyramid Histogram of Oriented Gradients (PHOG) and a Support Vector Machine (SVM) with polynomial kernels for classification. …”
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Towards Reliable Participation in UAV-Enabled Federated Edge Learning on Non-IID Data by Youssra Cheriguene, Wael Jaafar, Halim Yanikomeroglu, Chaker Abdelaziz Kerrache

“…Federated Learning (FL) is a decentralized machine learning (ML) technique that allows a number of participants to train an ML model collaboratively without having to share their private local datasets with others. …”
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The Recent Technologies to Curb the Second-Wave of COVID-19 Pandemic by M. Poongodi, Mohit Malviya, Mounir Hamdi, Hafiz Tayyab Rauf, Seifedine Kadry, Orawit Thinnukool

“…Large data sets need to be advanced so that extensive models related to deep analysis can be used to combat Coronavirus infection, which can be done by applying Artificial intelligence techniques such as Natural Language Processing (NLP), Machine Learning (ML), and Computer vision to varying processing files. …”
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Automated Cattle Monitoring System for Calving Time Prediction Using Trajectory Data Embedded Time Series Analysis by Wai Hnin Eaindrar Mg, Thi Thi Zin, Pyke Tin, Masaru Aikawa, Kazayuki Honkawa, Yoichiro Horii

“…Furthermore, the system accurately classifies cattle as either normal or abnormal and predicts calving events a 4-h in advance using the EFS feature, comparing its performance with various machine learning algorithms. The system's seamless integration significantly enhances farm management and animal welfare.…”
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Distinct Urinary Metabolite Signatures Mirror In Vivo Oxidative Stress-Related Radiation Responses in Mice by Yaoxiang Li, Shivani Bansal, Baldev Singh, Meth M. Jayatilake, William Klotzbier, Marjan Boerma, Mi-Heon Lee, Jacob Hack, Keisuke S. Iwamoto, Dörthe Schaue, Amrita K. Cheema

“…By Day 30, the WBI HDR group showed persistent metabolic dysregulation, while the WBI LDR and PBI BM2.5 groups were similar to control mice. Machine learning models identified metabolites that were predictive of the type of radiation exposure with high accuracy, highlighting their potential use as biomarkers for radiation damage and oxidative stress.…”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…The technique utilizes Machine Learning (ML), particularly leveraging the Regression Tree (RT) model. …”
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The effect of consuming bread contaminated with heavy metals on cardiovascular disease and calculating its risk assessment by Kambiz Ahmadi Angali, Majid Farhadi, Abdolkazem Neisi, Bahman Cheraghian, Mehdi Ahmadi, Afshin Takdastan, Abdolah Dargahi

“…The association between CVD and HMs has been evaluated utilizing seven machine-learning techniques. The results showed that the effect coefficient (β) of bread consumption in the incidence of heart disease is 4.6908 × 10–02. …”
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Source Characteristics Influence AI-Enabled Orthopaedic Text Simplification by Saman Andalib, BS, Sean S. Solomon, BS, Bryce G. Picton, BS, Aidin C. Spina, BS, John A. Scolaro, MD, Ariana M. Nelson, MD

“…Statistical and machine learning methods evaluated the correlations and predictive capacity of these features for transformation success. …”
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A Review of Agricultural Film Mapping: Current Status, Challenges, and Future Directions by Mengmeng Zhang, Jinwei Dong, Quansheng Ge, Hasituya, Pengyu Hao

“…Deep learning has apparent advantages than traditional machine learning algorithms in extracting PGs details, rarely used for mapping PMF. …”
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Dimensionality cutback and deep learning algorithms efficacy as to the breast cancer diagnostic dataset by Gennady Chuiko, Denys Honcharov

“…Various medical imaging techniques, such as mammography, computed tomography, histopathology, and ultrasound, are contemporary approaches for detecting and classifying breast cancer. Machine learning professionals prefer Deep Learning algorithms when analyzing substantial medical imaging data. …”
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Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost by Dana A. Al-Qudah, Ala’ M. Al-Zoubi, Alexandra I. Cristea, Juan J. Merelo-Guervós, Pedro A. Castillo, Hossam Faris

“…This research aims to intensify the usage of data analytics, machine learning, and sentiment analysis of textual data to classify customers’ reviews, feedback, and ratings of businesses in Jordan’s food and restaurant industry. …”
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Multi-Temporal Image Fusion-Based Shallow-Water Bathymetry Inversion Method Using Active and Passive Satellite Remote Sensing Data by Jie Li, Zhipeng Dong, Lubin Chen, Qiuhua Tang, Jiaoyu Hao, Yujie Zhang

“…Finally, ICESat-2 laser altimeter data are fused with multi-temporal Sentinel-2 satellite data to construct a machine learning framework for coastal bathymetry. The bathymetric control points are extracted from ICESat-2 ATL03 products rather than from field measurements. …”
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Causal Inference for Hypertension Prediction With Wearable E lectrocardiogram and P hotoplethysmogram Signa... by Ke Gon g, Yifan Chen, Xinyue Song, Zhizhong Fu, Xiaorong Ding

“…Finally, we used these features to detect hypertension via machine learning algorithms. Results We validated the proposed method on 405 subjects. …”
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From Night to Light: A Bibliometric Analysis of the Global Research Trajectory of Sleep Disorders in Parkinson’s Disease by Shi L, Zhao X, Wu J, He C

“…Emerging keywords include machine learning, sleep quality, biomarkers, covid-19, and mouse model.Conclusion: This bibliometric analysis sheds light on the global landscape of PD-related sleep disorder research over the past two decades, highlighting key countries, institutions, authors, and journals driving advancements in the field. …”
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SACNN‐IDS: A self‐attention convolutional neural network for intrusion detection in industrial internet of things by Mimonah Al Qathrady, Safi Ullah, Mohammed S. Alshehri, Jawad Ahmad, Sultan Almakdi, Samar M. Alqhtani, Muazzam A. Khan, Baraq Ghaleb

“…Intrusion Detection Systems (IDS) based on Machine Learning (ML) and Deep Learning (DL) techniques have got significant attention. …”
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Tryptophan metabolism-related gene CYP1B1 serves as a shared biomarker for both Parkinson’s disease and insomnia by Xin-Yu Li, Wen-Kai Yu, Jing-Hao Wu, Wen-Jun He, Yu-Nan Cheng, Kai Gao, Yi-Han Wei, Yu-Sheng Li

“…Through Protein–Protein Interaction (PPI) network analysis, Support Vector Machine-Recursive Feature Elimination (SVM-RFE) , and Extreme Gradient Boosting (XGBoost) machine learning, we identified Cytochrome P4501B1 (CYP1B1) and Electron Transfer Flavoprotein Alpha (ETFA) as key hub genes. …”
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