A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…Abstract Reservoir oil-bearing recognition is the process of predicting reservoir types based on well logging data, which determines the accuracy of recognition. …”
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Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter by Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman

“…Background: Understanding the dynamics of infectious disease spread and predicting clinical outcomes are critical for managing large-scale epidemics and pandemics, such as COVID-19. …”
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Identification of Road Black Spots Based on the Sliding Window Optimization and Safety Performance Function Development by Shahin Shabani, Jalal Ayoubinejad, Nassir Baradaran Rahmanian

“…The optimization methodology employed in this study is as follows: Firstly, the road is segmented, and for each segment, different scenarios of window lengths are chosen using the Density-Based Spatial Clustering of Applications with Noise algorithm. Next, a Safety Performance Function is developed to calculate the predicted and expected number of crashes, as well as the Potential Safety Improvement, for each window movement across all selected scenarios within the segment. …”
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Trajectory-Based Optimal Area Forwarding for Infrastructure-to-Vehicle Data Delivery with Partial Deployment of Stationary Nodes by Liang-Yin Chen, Song-Tao Fu, Jing-Yu Zhang, Xun Zou, Yan Liu, Feng Yin

“…To adapt with the real world, TOAF supposes that stationary nodes are partially installed at intersections in VANETs, and nodes' trajectories can be calculated and predicted, such as using cloud services and GPS, to find the optimal area where the destination vehicle may receive a packet timely. …”
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U-net based approach for pectoralis muscle segmentation in digital mammography by Francesca Angelone, Alfonso Maria Ponsiglione, Roberto Grassi, Francesco Amato, Mario Sansone

“…The U-Net network was therefore implemented on patches extracted along the straight line with which the muscle-breast edge was first estimated. The predicted patches are repositioned to perform an edge refinement and obtain the total breast mask, using histogram-based thresholding to segment the background from the breast. …”
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Driving Factors and Future Trends of Wildfires in Alberta, Canada by Maowei Bai, Qichao Yao, Zhou Wang, Di Wang, Hao Zhang, Keyan Fang, Futao Guo

“…This study analyzed the relationship between climate and wildfire and used a random forest algorithm to predict future wildfire frequencies in Alberta, Canada. …”
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Outdoor Dataset for Flying a UAV at an Appropriate Altitude by Theyab Alotaibi, Kamal Jambi, Maher Khemakhem, Fathy Eassa, Farid Bourennani

“…We used deep learning (DL) to develop a model to classify and predict the image types. Eleven experiments performed with the Gazebo simulator using a drone and a convolution neural network (CNN) proved the database’s effectiveness in avoiding different types of obstacles while maintaining an appropriate altitude and the drone’s ability to navigate in a 3D environment.…”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…Deep learning-based models assist radiologists by detecting patterns, generating probability maps, and predicting outcomes like heart failure. However, AI is still supplementary to clinical expertise due to challenges such as data limitations, algorithmic biases, and the need for extensive validation. …”
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Design Optimization of the Multi-layer Switched Reluctance Motor to Minimize Torque Ripple and Maximize Average Torque by Payam Vahedi, Babak Ganji, Seyed Ebrahim Afjei

“…In the present paper, this waveform is predicted using an analysis of the motor based on finite element method (FEM). …”
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Is human-like decision making explainable? Towards an explainable artificial intelligence for autonomous vehicles by Jiming Xie, Yan Zhang, Yaqin Qin, Bijun Wang, Shuai Dong, Ke Li, Yulan Xia

“…An empirical investigation using real driving trajectory data from Kunming, China, confirms the ability of our approach to predict potential driving decisions with high accuracy while providing the rationale implicit AV decisions. …”
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Experimental study on mechanical properties of triaxial geogrid reinforced marine coral sand-clay mixture based on 3D printing technology by Danda Shi, Kaiwei Xu, Zhiming Chao, Zhiming Chao, Peng Cui, Peng Cui

“…This model was applied for the first time to predict the strength of MCCM. Results show that lower clay content, more reinforcement layers, and higher confining pressure significantly enhance the strength and cohesion of MCCM, with little effect on the internal friction angle. …”
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Image encryption using dna-sequences, chaotic dynamics and hash fuctions by A. V. Sidorenko, M. S. Shishko

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Estimating Carbon Stock in Unmanaged Forests Using Field Data and Remote Sensing by Thomas Leditznig, Hermann Klug

“…The proposed approach demonstrated that the combination of low-cost remote sensing data and field work can predict above-ground biomass with high accuracy. The results and the estimation error distribution highlight the importance of accurate field data.…”
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An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999–2018 by Qun Tang, Yong Wang, Yan Luo

“…Five ML models were developed to predict ASCVD, and the best-performing model was selected for further analysis. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Finally, a dynamic loss adaptive weighted voting strategy ensures more accurate predictions across diverse domains. Experimental results on three public benchmark datasets (OfficeHome, PACS, and VLCS) demonstrate that our proposed algorithm achieves an improvement of up to 3 . 38% over existing methods in terms of generalization performance, particularly in complex and diverse real-world scenarios, such as autonomous driving and medical image analysis. …”
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On nonlinear coupled differential equations for corrugated backward facing step (CBFS) with circular obstacle: AI-neural networking by Khalil Ur Rehman, Wasfi Shatanawi, Weam G. Alharbi

“…It is concluded that the ANN design will act as the most accurate forecasting model of hydrodynamic force on circular obstruction in BFS for an extensive range, except normal parameters where classical methodologies were unable to predict.…”
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Generative AI-powered multilingual ASR for seamless language-mixing transcriptions by Puspita Dash, Sruthi Babu, Logeswari Singaravel, Devadarshini Balasubramanian

“…Here, we use a generative pre-trained transformer model, which learns to predict the subsequent word in a language during the pre-training stage in order to get an understanding of language structure and semantics. …”
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Designing transit routes based on vehicle routing behavior determined through location-based services data by Yuhan Tang, Abdullah Alhadlaq, Alben Rome Bagabaldo, Marta C. Gonzalez

“…Abstract The disparity between transit agency travel predictions and the unpredictable nature of real-world travel behavior contributes to inefficiencies within the transit system. …”
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Lightweight construction safety behavior detection model based on improved YOLOv8 by Kan Huang, Mideth B. Abisado

“…YOLO (You Only Look Once) is an object detection algorithm that can achieve real-time and efficient object detection by dividing images into grids and predicting the bounding boxes and categories of objects in each grid. …”
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Indoor fire and smoke detection based on optimized YOLOv5. by Md Shafak Shahriar Sozol, M Rubaiyat Hossain Mondal, Achmad Husni Thamrin

“…It also used the Grad-CAM technique to provide visual explanations for model predictions, ensuring interpretability and transparency. …”
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