A Two-echelon Model of Location-routing Problem for Optimizing Relief Operations in Natural Disasters by Hossein Jamali, Mehdi Kabiri Naeini, Zeynab Elahi

“…To solve the LRP in a large scale, a metaheuristic genetic algorithm (GA) was developed and utilized. To validate the proposed model, five small-scale problems were solved, and the solutions obtained from the proposed GA were compared with the exact solutions obtained from GAMS software. …”
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Automated Semantic Segmentation of Arctic Surface Water Features with Very-High Resolution Satellite X-Band Radar Imagery and U-Net Deep Learning: Segmentation sémantique automatis... by Michael Allan Merchant, Masoud Mahdianpari, Laura Bourgeau-Chavez, Ben DeVries, Aaron Berg

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A Framework for Flood Disaster Detection From Remote Sensing Images Using Spatiotemporal Fusion With Digital Twin Technology by Se-Jung Lim, K. Sakthidasan Sankaran, Anandakumar Haldorai

“…A feature extraction process is carried with the use of Deep Convolution VGGNet-16 from which optimal features are selected using Improved Harris Hawks Optimization algorithm (IHHOA). Then, a Flexible Spatio-temporal image fusion (F-SPTF) approach is employed to fuse images. …”
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A Bicriteria Approach Identifying Nondominated Portfolios by Javier Pereira, Broderick Crawford, Fernando Paredes, Ricardo Soto

“…In order to improve the former algorithm, a process finding an optimal solution of a monocriteria version of this problem is proposed, which is further used as a first feasible solution aiding to find nondominated solutions more rapidly. …”
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Reconstruction of ionospheric VTEC using empirical orthogonal function and its performance during extreme geomagnetic storm by Rajat Acharya, Victor Dey

“…The containment factor, defined here, indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high, aiding in improved algorithm performance. The performance, however, was found to be sensitive to the seasons and geomagnetic conditions. …”
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Determination of the area index of lettuce leaves with a monocular camera by Laimonas Kairiūkštis, Başak Yalçıner, Emre Özkul

“…The leaf area index serves as a fundamental metric in the analysis, aiding in accurately measuring the size of the lettuce plants. …”
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A Study on Blended Teaching Model Evaluation for English Major Courses in Higher Education: An Uncertainty-Based Approach by Chunmei Xue

“…The plithogenic-WISP hybrid model is thus created in this study, and an algorithm for this innovative decisionanalytic model is provided. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
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Mid-Water Ocean Current Field Estimation Using Radial Basis Functions Based on Multibeam Bathymetric Survey Data for AUV Navigation by Jiawen Liu, Kaixuan Wang, Shuai Chang, Lin Pan

“…Autonomous Underwater Vehicle (AUV) navigation relies on bottom-tracking velocity from Doppler Velocity Log (DVL) for positioning through dead-reckoning or aiding Strapdown Inertial Navigation System (SINS). …”
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Energy saving and low carbon oriented renovation framework for educational buildings with Tianjin University case study by Xinge Du, Xiang Liu, Feng Gao, Zhihua Zhou

“…This study proposes a data-driven workflow that combines a genetic algorithm with a Bayesian optimization-based XGBoost model to optimize the retrofit design of educational buildings. …”
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Triboinformatic analysis and prediction of B4C and granite powder filled Al 6082 composites using machine learning regression models by Amit Aherwar, Anamika Ahirwar, Vimal Kumar Pathak

“…The primary aim of this study is to combine experimental methodologies with ML algorithms to accurately predict the wear and coefficient of friction for B4C-granite composites, thereby aiding in the design and manufacturing of materials with enhanced wear performance. …”
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An interpretable CT-based machine learning model for predicting recurrence risk in stage II colorectal cancer by Ziqi Wu, Liya Gong, Jingwen Luo, Xiaobo Chen, Fan Yang, Junyan Wen, Yanyu Hao, Zhishan Wang, Ruozhen Gu, Yuqin Zhang, Hai Liao, Ge Wen

“…A combined model was developed using artificial neural network (ANN) algorithm, by integrating the Radscore with significant clinicoradiological factors to classify patients into high- and low-risk groups. …”
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Predictive model using systemic inflammation markers to assess neoadjuvant chemotherapy efficacy in breast cancer by Yulu Sun, Yinan Guan, Hao Yu, Yin Zhang, Jinqiu Tao, Weijie Zhang, Yongzhong Yao

“…A predictive model for pCR was constructed using machine learning algorithms.ResultsAmong the 209 breast cancer patients, 29 achieved pCR. …”
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Transportation Severity Analysis of Factors Contributing to Two-Vehicle Road Crashes Based on Interpretability Theory by Chen Zhang, Linjia Li, Aihui Pei, Li Tao, Junli Yuan, Feng Xiao, Yuxi Zheng

“…The permutation feature importance algorithm was then used to explore how these important features affect traffic crash severity, presenting the results visually in the form of graphics. …”
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Design and control of a permanent magnet-based robotic system for navigating tetherless magnetic devices in viscous environments by Zhengya Zhang, Anke Klingner, Sarthak Misra, Islam S. M. Khalil

“…This method simplifies the manipulation of rotating magnetic fields, thereby aiding the simplification of TMD motion control strategies. …”
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Development and validation of a pathological model predicting the efficacy of neoadjuvant therapy for breast cancer based on RCB scoring by Huan Li, Xianli Ju, Chuanfei Zeng, Zhengzhuo Chen, LinXin Yu, Ge Ke, Ziyin Huang, Youping Wang, Jingping Yuan, Mingkai Chen

“…Based on clinical and pathological characteristics along with the Residual Cancer Burden (RCB) score, we utilized a support vector machine (SVM) algorithm to construct a Pathomics Breast Cancer Signature (PBCS) prediction model. …”
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Prediction of three-year all-cause mortality in patients with heart failure and atrial fibrillation using the CatBoost model by Jiacan Wu, Guanghong Tao, Siyuan Xie, Han Yang, Fenglin Qi, Naiyue Bao, Zhuo Li, Guanglei Chang, Hua Xiao

“…Feature selection utilized the Boruta algorithm and least absolute shrinkage and selection operator regression. …”
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Construction and validation of a nomogram for predicting 3-month outcome in elderly patients with nonvalvular atrial fibrillation-induced acute ischemic stroke by Yang Yang, Xiaohong Zhang

“…The nomogram, integrating these factors, provides intuitive, individualized predictions for the risk of poor outcomes, aiding in the selection of treatment options for these patients.…”
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Complete spatiotemporal quantification of cardiac motion in mice through multi-view magnetic resonance imaging and super-resolution reconstruction by Tanmay Mukherjee, Maziyar Keshavarzian, Elizabeth M. Fugate, Vahid Naeini, Amr Darwish, Jacques Ohayon, Kyle J. Myers, Dipan J. Shah, Diana Lindquist, Sakthivel Sadayappan, Roderic I. Pettigrew, Reza Avazmohammadi

“…Image registration using the diffeomorphic demons algorithm was applied to quantify complete spatiotemporal motion in terms of 4D myocardial strains. …”
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GeneSetCluster 2.0: a comprehensive toolset for summarizing and integrating gene-sets analysis by Asier Ortega-Legarreta, Alberto Maillo, Daniel Mouzo, Ana Rosa López-Pérez, Lara Kular, Majid Pahlevan Kakhki, Maja Jagodic, Jesper Tegner, Vincenzo Lagani, Ewoud Ewing, David Gomez-Cabrero

“…Methodologically, GeneSetCluster 2.0 introduces a novel approach to address duplicated gene-sets and implements a seriation-based clustering algorithm that reorders results, aiding pattern identification. …”
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