Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…Three reference WPTs (snow (SN), rain (RA), and RASN) are obtained from particle size velocity (PARSIVEL) disdrometer data using a newly proposed decision tree algorithm. …”
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Evaluation of the Effectiveness of the UNet Model with Different Backbones in the Semantic Segmentation of Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Julieta Raquel Hernandez Vidales

“…The task focuses on pixel-wise classification into three categories: leaves, fruits, and background, based on images of semi-hydroponic tomato crops captured in greenhouse settings. …”
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An Interpretable Machine Learning Framework for Unraveling the Dynamics of Surface Soil Moisture Drivers by Zahir Nikraftar, Esmaeel Parizi, Mohsen Saber, Mahboubeh Boueshagh, Mortaza Tavakoli, Abazar Esmaeili Mahmoudabadi, Mohammad Hassan Ekradi, Rendani Mbuvha, Seiyed Mossa Hosseini

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An FPGA Prototype for Parkinson’s Disease Detection Using Machine Learning on Voice Signal by Mujeev Khan, Abdul Moiz, Gani Nawaz Khan, Mohd Wajid, Mohammed Usman, Jabir Ali

“…To enhance classification performance and reduce computational complexity, we evaluate three feature selection algorithms &#x2014; Chi-squared (<inline-formula> <tex-math notation="LaTeX">$\chi ^{2}$ </tex-math></inline-formula>), Minimum Redundancy Maximum Relevance (mRMR), and Analysis of Variance (ANOVA) &#x2014; and adopt an incremental feature selection approach, where each feature set increment is assessed across five classifiers: K-Nearest Neighbors (KNN), Decision Tree (DT), Artificial Neural Network (ANN), Logistic Regression (LR), and Support Vector Machine (SVM). …”
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On the Control of the Technical Condition of Elevator Ropes Based on Artificial Intelligence and Computer Vision Technology by A. V. Panfilov, A. R. Yusupov, A. A. Korotkiy, B. F. Ivanov

“…PAC VIC implemented the following functions: – automatic detection and classification of the major significant rope defects based on a deep convolutional artificial neural network; – demonstration of a three-dimensional image of a rope and an image scanning algorithm with distortion compensation, according to which the metric characteristics of defects were fixed; – integral assessment of the technical condition of the rope according to the totality of detected defects; – color interpretation of the actual technical condition of the rope with subsequent transmission to the user's mobile device. …”
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Machine learning and SHAP values explain the association between social determinants of health and post-stroke depression by Zhiwei Song, Jilin Weng, Yupeng Han, Wangyu Li, Yiya Xu, Yingchao He, Yinzhou Wang

“…Compared to the other three models, CatBoost (AUC = 0.966) demonstrated the best overall predictive performance. …”
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Layout Optimization of Campus Bike-Sharing Parking Spots by Tangyi Guo, Jie Yang, Liu He, Kun Tang

“…The results show that, after optimizing the layout of parking spots, the average travel time of users is reduced by 6.0%, and the total construction cost is reduced by 27.3%. While being convenient for campus bike-sharing users, it also provides scientific decision-making support for the campus traffic management.…”
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The Utilization of Naive Bayes and C.45 in Predicting The Timeliness of Students’ Graduation by Agung Wibowo, Danny Manongga, Hindriyanto Dwi Purnomo

“…The model used in this study using the NBC to determine the graduation pattern and the Decision tree to determine the influencing factors. …”
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A Study on the Susceptibility of Wildfire Disasters in Wuzhou City Based on Interpretability Model by Lei Zou, Hongjuan Shao, Yintao Liu, Chao Ren, Qinyi Chen, Haoming Bai, Zhengzhong Huang, Yao Gu

“…The results indicate that: 1) the wildfire susceptibility model for Wuzhou City exhibits excellent performance, with an Area Under the Curve (AUC) value of 0.981, accurately identifying high-susceptibility areas and providing essential decision-making support for relevant departments; 2) nine key factors affecting wildfire susceptibility in Wuzhou City were identified, including average annual precipitation, average temperature, and average wind speed, offering scientific evidence for wildfire risk management; 3) a comparison between typical historical wildfire samples from 2017 to 2023 and the latest wildfire data from January 2024 to November 2024, further validated the model&#x2019;s accuracy. …”
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Crafting desirable climate trajectories with reinforcement learning explored socio-environmental simulations by James Rudd-Jones, Fiona Thendean, María Pérez-Ortiz

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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

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Advanced Self-Driving Vehicle Model for Complex Road Navigation Using Integrated Image Processing and Sensor Fusion by Kalapraveen Bagadi, Naveen Kumar Vaegae, Visalakshi Annepu, Khaled Rabie, Shafiq Ahmad, Thokozani Shongwe

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YOLOv9-GSSA model for efficient soybean seedlings and weeds detection by Baihe Liang, Liangchen Hu, Guangxing Liu, Peng Hu, Shaosheng Xu, Biao Jie

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AI-Driven Optimization of Multilayer Thin-Film Structures for Advanced Optical Applications by Emad Alkhazraji, Sani Mukhtar, Haitham Khaled, Jaime Viegas

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Prediction of Chemical Corrosion Rate and Remaining Life of Buried Oil and Gas Pipelines in Changqing Gas Field by Xianbing Li, Rui Liu, Dong Ma, Yang Bai, Yukai Shi, Badm Anhouck

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Maritime inventory routing with an application to fish feed distribution by Anders Bjelland, Aksel Borgen, Sjur Wold, Kjetil Fagerholt, Dimitri J. Papageorgiou, Kristian Thun, Simen Tung Vadseth

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MangiSpectra: A Multivariate Phenological Analysis Framework Leveraging UAV Imagery and LSTM for Tree Health and Yield Estimation in Mango Orchards by Muhammad Munir Afsar, Muhammad Shahid Iqbal, Asim Dilawar Bakhshi, Ejaz Hussain, Javed Iqbal

“…In the second stage, associated data such as the trees’ age, variety, canopy volume, height, and weather data were combined with predicted health classes for yield estimation through a decision tree algorithm. Three mango-specific indices, namely the Mango Tree Yellowness Index (MTYI), Weighted Yellowness Index (WYI), and Normalized Automatic Flowering Detection Index (NAFDI), were developed to measure the degree of canopy covered by flowers to enhance the robustness of the framework. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

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Performance Statistics of Autoregressive Short and Ultrashort Signal Detectors by V. M. Kutuzov, V. P. Ipatov, S. S. Sokolov

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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

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