Nondestructive Detection of Rice Milling Quality Using Hyperspectral Imaging with Machine and Deep Learning Regression by Zhongjie Tang, Shanlin Ma, Hengnian Qi, Xincheng Zhang, Chu Zhang

“…This study confirmed that this nondestructive detection method for rice milling quality using hyperspectral imaging combined with machine learning and deep learning algorithms could effectively assess rice milling quality, thus contributing to breeding and growth management in the industry.…”
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Predicting the Acceptance of Informal Learning Technologies: A Case of the TikTok Application by Ahmed Al-Azawei, Ali Alowayr

“…Data from 143 participants are collected and analyzed based on the convenience sampling technique. The partial least square, Support Vector Classifier, and Random Forest techniques are used to identify the predictability of the proposed framework. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…However, this task remains challenging due to variable high-altitude viewpoints, complex environmental interference, and limitations in algorithmic efficiency. To address these issues, a lightweight vehicle detection model is developed based on UAV aerial imagery. …”
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Using machine learning for the assessment of ecological status of unmonitored waters in Poland by Andrzej Martyszunis, Małgorzata Loga, Karol Przeździecki

“…Study shows highest efficiency of XGBoost and Random Forest algorithms for classification of unmonitored water bodies. …”
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Solar cells based on Sb2Se3 grown by chalcogenization of Sb thin films, using a novel designed furnace by Gerardo Gordillo, Oscar Torres, Alvaro I. Mendez, Julian C. Pena-Bermudez

“…The entire process was automatically controlled using algorithms developed in the LabView programming environment. …”
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Methodology for extracting narratives from social media big data by E. Yu. Petrov, A. Yu. Sarkisova, D. O. Dunaeva, A. S. Voronov, M. G. Myagkov

“…The calculation of the measure of proximity of keywords using the Python, partial manual markup and data validation were also carried out.Results: 4.5 million messages relevant to the topic of COVID-19 vaccination published in VKontakte from 01.01.2020 to 01.03.2023 were reduced to 237 stable narratives. …”
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Electrodynamic Model of the Signal Scattered by the Multilayer Structure with the Use of Physical Optics and Ray Tracing Technique by V. V. Bahchevnicov

“…To assess the performance of new algorithms for processing the radar signal reflected from the surfaces, full-scale tests are required. …”
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Monitoring Gypsiferous Soils by Leveraging Advanced Spaceborne Hyperspectral Imagery via Spectral Indices and a Machine Learning Approach by Najmeh Rasooli, Saham Mirzaei, Stefano Pignatti

“…The gypsum content was retrieved by optical data using three approaches: narrowband indices, spectral absorption features, and machine learning (ML) algorithms. Four machine learning algorithms, including PLSR (Partial Least Squares Regression), RF (Random Forest), SVR (Support Vector Regression), and GPR (Gaussian Process Regression), achieved excellent performance (RPD > 2.5). …”
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ADAPTABLE DYNAMIC ROUTING SYSTEM IN URBAN TRANSPORT LOGISTICS PROBLEMS USING GIS DATA by Viktor DANCHUK, Oleksandr HUTAREVYCH

“…Route optimization is performed on a weighted bidirectional graph for an asymmetric dynamic traveling salesman problem using a modified ant colony optimization algorithm. The system allows automatically updating the weights of the graph depending on the current changes in the characteristics traffic in the URN sections, obtained from GIS data, and fixing the optimal configuration of a partially completed route before updating the graph. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The research utilizes stepwise linear regression (SLR), random forest (RF), gradient boosting (GB), extreme gradient boosting (XGB), and Gaussian process regression (GPR) algorithms, developed based on 357 experimental results sourced from recent studies. …”
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Python-Based Implementation of Metaheuristic MPPT Techniques: A Cost-Effective Framework for Solar Photovoltaic Systems in Developing Nations by Syed Majed Ashraf, M. Saad Bin Arif, Mohammed Khouj, Shahrin Md. Ayob, Muhammad I. Masud

“…We implemented multiple metaheuristic MPPT algorithms including Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO), evaluating their efficacy under both Standard Test Conditions (STC) and complex partial shading scenarios. …”
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Multiobjective Optimal Control of Longitudinal Seismic Response of a Multitower Cable-Stayed Bridge by Geng Fangfang, Ding Youliang

“…The dynamic behavior of a multitower cable-stayed bridge with the application of partially longitudinal constraint system using viscous fluid dampers under real earthquake ground motions is presented. …”
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Drone Navigation and Target Interception Using Deep Reinforcement Learning: A Cascade Reward Approach by Ali A. Darwish, Arie Nakhmani

“…First, we tackle the challenge of partial observability when employing nonlinear function approximators for learning stochastic policies. …”
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An Operation Plan Optimization Model for Integrated Customized and Conventional Bus Services Based on Cost Analysis by Xi Lu, Junru Han, Peng Xu, Haode Liu, Xumei Chen

“…A mixed-integer planning model and a hybrid genetic algorithm are used to optimize the operation plan for specific travel demands and supply capacities. …”
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A comprehensive dataset of near infrared spectroscopy measurements to predict nitrogen and carbon contents in a wide range of tissues from Brassica napus plants grown under contras... by Sophie Rolland, Françoise Leprince, Solenn Guichard, Françoise Le Cahérec, Anne Laperche, Nathalie Nesi

“…This dataset could be used to test new calculation algorithms in order to enhance prediction performance or for training purposes. …”
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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

“…These findings have the potential to inform ongoing research on brain-like neural learning and could function as a catalyst for developing swifter and more potent algorithmic solutions in the realm of intelligent transportation.…”
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Ultrasensitive Isomer Discrimination: A Joint Surface‐Enhanced Raman Scattering (SERS) Spectroscopy and Machine Learning Strategy by Verónica Montes‐García, Victor F. Martín, Manuel Obelleiro‐Liz, Ignacio Pérez‐Juste, Artur Ciesielski, Paolo Samorì

“…The integration of machine learning methodologies, such as Partial Least Squares Regression and Artificial Neural Networks, significantly enhances both quantitative analysis and classification accuracy, achieving detection limits as low as 2 × 10⁻⁸ m. …”
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Deep Reinforcement Learning for RIS-Assisted Multi-UAV MU-MISO Communication Networks: Sum-Rate and Energy Efficiency Maximization by Alif Rahmatullah Umar, Hasan Albinsaid, Chia-Po Wei, Chih-Peng Li

“…However, recent studies that integrate reconfigurable intelligent surfaces (RIS) with UAVs tend to focus on limited aspects, such as single-UAV deployments or partial optimization of system parameters, thereby neglecting a comprehensive system-level design. …”
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Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach by Yehoon Jo, Mi-Yeon Shin, Sungkyoon Kim

“…SHapley Additive exPlanations (SHAP) and partial dependence plots (PDP) revealed both linear and nonlinear exposure–response patterns, suggesting threshold effects for key chemicals. …”
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