An advanced real-time crash prediction framework for combined hard shoulder running and variable speed limits system using transformer by Mohamed Abdel-Aty, Tarek Hasan, B M Tazbiul Hassan Anik

“…Additionally, the results indicate substantial improvements in model prediction performance (i.e., an increment of sensitivity values by 7.04% and 8.33% in the AM and PM models, respectively) after incorporating the general safety condition of a freeway segment as an input feature while estimating real-time crash prediction models. …”
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Flood extent mapping in SAR images using semi-supervised approach by Girisha S, Savitha G, Sughosh P

“…An attention module-based tailored student model is developed to precisely identify flood-zones. …”
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Anchor Dragging Risk Estimation Strategy from Supervised Cost-Sensitive Learning by Sang-Lok Yoo, Shem Otoi Onyango, Joo-Sung Kim, Kwang-Il Kim

“…This study also demonstrated potential applications of the model, discussed its limitations, and suggested possible improvements for the ML approach. …”
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TECHNOLOGICAL ADVANCES IN ELECTROPLATING: ARTIFICIAL INTELLIGENCE TO PREDICT ZINC COATING THICKNESS ON SAE 1008 LOW CARBON STEELS by Luciano M. L. de Oliveira, Fabiana L. da Silva, Paulo R. Janissek, Juliano C. Toniolo

“…Statistical analysis and supervised machine learning algorithms, including multivariate regression, random forest, and extreme gradient boosting (XGBoost), were employed to develop prediction models. …”
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An Overview of the Empirical Evaluation of Explainable AI (XAI): A Comprehensive Guideline for User-Centered Evaluation in XAI by Sidra Naveed, Gunnar Stevens, Dean Robin-Kern

“…Recent advances in technology have propelled Artificial Intelligence (AI) into a crucial role in everyday life, enhancing human performance through sophisticated models and algorithms. However, the focus on predictive accuracy has often resulted in opaque black-box models that lack transparency in decision-making. …”
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Harnessing Artificial Intelligence in Cardiology: Advancements in Diagnosis, Treatment, and Patient Care by Muhammad Hamza Shuja, Firzah Shakil, Syed Hasan Shuja, Minal Hasan, Maliha Edhi, Abeera Farooq Abbasi, Afia Jawaid, Shajia Shakil

“…Predictive analytics models utilizing electronic health records, genomic data, and lifestyle information significantly improve early detection and risk prediction of heart conditions. …”
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Optimizing machine learning for enhanced automated ECG analysis in cardiovascular healthcare by Keyi Tang, Shuyuan Ma, Xiaohui Sun, Dongfang Guo

“…By optimizing classification models with metaheuristic algorithms, such as JADE, the study achieves significant performance improvements, highlighting the effectiveness of integrating advanced optimization techniques into ECG analysis processes. …”
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Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children. by Megan Palmer, James A Seddon, Marieke M van der Zalm, Anneke C Hesseling, Pierre Goussard, H Simon Schaaf, Julie Morrison, Bram van Ginneken, Jaime Melendez, Elisabetta Walters, Keelin Murphy

“…We compared the performance of the fine-tuned model to the original model. Our findings were that the area under the receiver operating characteristic curve (AUC) of the original CAD4TB model, prior to fine-tuning, was 0.58. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…The proposed model combines an Artificial Neural Network and Support Vector Machine as base classifiers and employs a Random Forest as a meta-classifier to fuse predictions, improving detection performance. …”
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A Study on Staging Cystic Echinococcosis Using Machine Learning Methods by Tuvshinsaikhan Tegshee, Temuulen Dorjsuren, Sungju Lee, Dolgorsuren Batjargal

“…This research underscores the potential of hybrid and pre-trained models in advancing medical image classification, providing a promising approach to improving the differential diagnosis of CE disease.…”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…There has been relatively little study on explainability, especially when dealing with malware imagery data, irrespective of the fact that DL/ML algorithms have revolutionized malware detection. Explainability techniques such as SHAP, LIME, and Grad-CAM approaches are employed to present a complete comprehension of feature significance and local or global predictive behavior of the model over various malware categories. …”
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COSMIC-Based Early Software Size Estimation Using Deep Learning and Domain-Specific BERT by Yohannes Sefane Molla, Esubalew Alemneh, Samuel Temesgen Yimer

“…On average, RE-BERT-based regressor models provided 1.23% to 3.19% improvement over BASE-BERT regressor models. …”
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Study on the mechanisms associating community outdoor public spaces with elderly behavior by Lei Wang, Wenqi He, Shan Wu, Bo Zhang, Xiaorui Zhang, Hu Yin

“…A computer vision-based behavior detection algorithm is then constructed to effectively identify six typical activities of the elderly: exercising, jogging, sitting, standing, walking, and playing chess or cards. …”
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Optimizing Rural Connectivity Through Hybrid Wireless-Wireline and Satellite Network Integration by Fareha Nizam, Teong Chee Chuah, Ying Loong Lee

“…This dual-access approach not only improves system robustness but also ensures efficient resource utilization. …”
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Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

“…Segmentation and feature selection enhance performance, improving diagnostic accuracy. Future work may explore further optimizations and hybrid models.…”
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Legal Regulation of Relations in the Sphere of Crowdfunding in the Republic of Belarus by A. V. Vasilevskii

“…The probable contract models of the parties’ legal relations registering were named. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Traditional deep learning (DL) models and decision tree (DT)-based algorithms have been widely employed for this purpose. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…This innovative design not only enhances sustainability, but also improves the system’s energy efficiency. To ensure precise and customized sizing of the system for the irrigation area, a detailed mathematical modeling of the key system components (solar panels, wind turbines, and reservoir) was conducted. …”
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Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE by Muhammad Sarmad Mahmood, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Syed Salman Ahmad Zaidi, Muwaffaq Alqurashi, Hawreen Ahmed, Muhammad Adnan, Abdul Hakim Hotak

“…To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). Among these, XGB-GWO demonstrated the highest accuracy, with R² improving to 0.991 and MSE decreasing significantly from 83.95 to 14.42, resulting in an 82.82% error reduction. …”
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Machine learning and AVO class II workflow for hydrocarbon prospectivity in the Messinian offshore Nile Delta Egypt by Nadia Abd-Elfattah, Aia Dahroug, Manal El Kammar, Ramy Fahmy

“…By iterating over multiple attributes and validating the models on blind test sets and on a blind section, which excluded a known shallow gas field, the workflow significantly improved the ability to detect potential hydrocarbon reservoirs characterized by low seismic amplitude. …”
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