Network Topology-Driven Vertiport Placement Strategy: Integrating Urban Air Mobility with the Seoul Metropolitan Railway System by Ki-Han Song, HaJeong Lee

“…Regardless of whether centrality or vulnerability is prioritized, we observe that connectivity increase exponentially, while network efficiency changes linearly with the increase in vertiport proportion. …”
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Influence of Dynamic Properties of Nonlinear Over-Voltage Limiter on Over-Voltage Limitation in Distribution Networks by A. N. Bokhan, V. V. Krotenok, S. N. Prokhorenko

“…One of the most efficient means of over-voltage reduction in arcing ground short-circuits is an application of   a nonlinear over-voltage limiter. …”
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A Comparative Study of Machine Learning Models for Accurate E-Waste Prediction by Mohammed Algafri, Mohammed Sayad, Mohammad A.M. Abdel-Aal, Ahmed M. Attia

“…Given the high-value materials in e-waste, accurate prediction is crucial for efficient recycling and regulatory planning. This study evaluates six Machine Learning (ML) models, Linear Regression, Regression Tree, Support Vector Regression, Ensemble Regression, Gaussian Process Regression (GPR), and Artificial Neural Networks, for e-waste forecasting. …”
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DESIGN AND ASSEMBLY OF SEMI-AUTOMATED WIRE STRAND EXTRACTOR FOR 2-8 AWG WIRES by Mark Joseph B. Enojas, Ruem G. Arribas, Harveen C. Bongao, Hohn Lois C. Bongao, Jobelle Lazaro, Jessica Benal, Mark Aranas

“…It consists of three major parts: the control box which holds the limit switches, stepper motors, electrical/electronic wirings, the linear guide, and the pantograph grip. An Arduino Uno was used as the main control system which regulates the rate of wire extraction. …”
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Measurement of Maize Leaf Phenotypic Parameters Based on 3D Point Cloud by Yuchen Su, Ran Li, Miao Wang, Chen Li, Mingxiong Ou, Sumei Liu, Wenhui Hou, Yuwei Wang, Lu Liu

“…Finally, PH is determined by calculating vertical distance from plant apex to base, LW is measured through linear fitting of leaf midveins with perpendicular line intersections on projected contours, and LA is derived from plant skeleton diagrams constructed via linear fitting to identify stem apex, stem–leaf junctions, and midrib points. …”
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Day-Ahead Electricity Price Forecasting Based on Hybrid Regression Model by Ali Najem Alkawaz, Abdallah Abdellatif, Jeevan Kanesan, Anis Salwa Mohd Khairuddin, Hassan Muwafaq Gheni

“…Considering that each model of EPF has its own strengths and weaknesses, combining several models gives more accurate predictions and overcomes the limitations of an individual model. Therefore, the linear ARD model is applied because it can efficiently deal with trend and seasonality variations; on the other hand, the ensemble ETR model is employed to learn from interactions, and thus combining ARD with ETR produces robust forecasting outcomes. …”
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Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions by Baber Ali, Tristan Mary‐Huard, Alain Charcosset, Laurence Moreau, Renaud Rincent

“…We systematically tested a list of 5110 GO terms for their predictive performance for physiological (platform traits) and productivity traits (field grain yield) in a maize (Zea mays L.) panel using genomic features best linear unbiased prediction (GFBLUP) model. Predictive abilities were compared to the classical genomic best linear unbiased prediction (GBLUP). …”
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Correlation between Iliac Tilt and traditional sagittal parameters in adolescents by ZengHui Zhao, Hao Qi, Anqi Zhao, Hongru Yuan, Peng Zhang, Chenchen Wang, Chenxi Wang, Di Zhang

“…Linear regression analysis revealed that IT was a significant predictor of both PT and PSA, with R² values of 0.736 and 0.717, respectively. …”
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Review of Recent Advances in Remote Sensing and Machine Learning Methods for Lake Water Quality Management by Ying Deng, Yue Zhang, Daiwei Pan, Simon X. Yang, Bahram Gharabaghi

“…This review examines the integration of remote sensing technologies and machine learning models for efficient monitoring and management of lake water quality. …”
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Machine learning for asphaltene polarizability: Evaluating molecular descriptors by Arun K. Sharma, Owen McMillan, Selsela Arsala, Supreet Gandhok, Rylend Young

“…Linear regression was the best-performing model in 9 out of 10 splits for GETAWAY descriptors. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…This approach effectively captures both structured features and non-linear patterns, making it suitable for datasets with complex dependencies. …”
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PSE-Based Aerodynamic Flow Transition Prediction Using Automated Unstructured CFD Integration by Nathaniel Hildebrand, Meelan M. Choudhari, Fei Li, Pedro Paredes, Balaji S. Venkatachari

“…The accurate, robust, and efficient prediction of transition in viscous flows is a significant challenge in computational fluid dynamics. …”
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Exploring the Impact of Spaced Repetition Through Anki Usage on Preclinical Exam Performance by Victoria Winter, Emily Ames, Marley Jacobs, Carlos Georges, Edward Simanton

“…This uniquely challenges medical students to learn efficiently and retain a large amount of information. …”
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Use of Phenomics in the Selection of UAV-Based Vegetation Indices and Prediction of Agronomic Traits in Soybean Subjected to Flooding by Charleston dos Santos Lima, Darci Francisco Uhry Junior, Ivan Ricardo Carvalho, Christian Bredemeier

“…Additionally, variables predicted based on estimated genetic data via phenomics had determination coefficients above 0.90, enabling the reduction in the number of important variables within the linear model.…”
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Self-Powered Photoelectrochemistry Biosensor for Ascorbic Acid Determination in Beverage Samples Based on Perylene Material by Wei Zhang, Xinyang Sun, Hong Liu, Lei Shang, Rongna Ma, Xiaojian Li, Liping Jia, Shuijian He, Chuan Li, Huaisheng Wang

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Predicting the interfacial tension of CO2 and NaCl aqueous solution with machine learning by Kashif Liaqat, Daniel J. Preston, Laura Schaefer

“…This demonstrates that ML models offer a cost-effective and efficient alternative to experimental methods, potentially optimizing designs for CO2 sequestration.…”
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Multi-Feature Fusion for Estimating Above-Ground Biomass of Potato by UAV Remote Sensing by Guolan Xian, Jiangang Liu, Yongxin Lin, Shuang Li, Chunsong Bian

“…Six advanced modeling algorithms, including random forest (RF), partial least squares regression (PLSR), multiple linear regression (MLR), simple linear regression (SLR), ridge regression (RR), and lasso regression (LR) models, were adopted to evaluate the ability of estimating AGB by single feature and multi-feature information fusion. …”
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Iterative Solution to a System of Matrix Equations by Yong Lin, Qing-Wen Wang

“…An efficient iterative algorithm is presented to solve a system of linear matrix equations , with real matrices and . …”
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The Extended CG Method for Non-Quadratic Models by Abbas Al-Bayati, Basim Hassan, Sawsan Ismael

“…This combined algorithm is based on the exact line search to solve a number of non-linear test functions with different dimensions. Experimental results indicate that the modified  algorithm is more efficient than the original Sloboda algorithm.…”
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Otimização do desempenho de amplificadores de radiofrequência banda larga: uma abordagem experimental Radio frequency broadband amplifiers performance optimization: an experimental... by Vanessa Borsato de Souza Lima, Pedro Paulo Balestrassi, Anderson Paulo de Paiva

“…An experimental strategy was employed resulting in the optimization of a number of factors responsible for increasing the overall efficiency and linearity of amplifiers during production process, reducing total intermodulation and interference in adjacent channels. …”
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