Low-Fidelity, In Situ, Accessible Pediatric Mass Casualty Incident Simulation to Evaluate and Improve Pediatric Readiness by Sydney E. Jeffs, Cathlyn K. Medina, Parker Frankiewicz, Steven W. Thornton, Elizabeth Horne, Smith Ngeve, Tara Thomason, Delaney Anani-Wolf, Catherine B. Beckhorn, Delaney James, Rachel Hobbs, Remi Hueckel, Corrie E. Chumpitazi, Erin R. Hanlin, Rachel O'Brian, Elisabeth T. Tracy, Emily Greenwald

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Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm by Shubing Qiu, Yong Liu, Xiaohong Zhou

“…To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. …”
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Covariance Matrix Reconstruction to Improve DoA Estimation Using Subspace Method in Low SNR Regime by Sunita Khichar, Wiroonsak Santipach, Lunchakorn Wuttisittikulkij

“…The proposed method also shows substantial improvements in performance with varying numbers of snapshots and under different angle separation conditions. …”
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Improved PICEA-g-based multi-objective optimization scheduling method for distribution network with large-scale electric vehicles by Meiyi Huo, Songling Pang, Hailong Zhao

“…In this paper, an optimal scheduling method for large-scale EV access to the distribution grid based on the improved preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) is proposed. …”
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Location prediction algorithm based on movement tendency by Wen LI, Shi-xiong XIA, Feng LIU, Lei ZHANG, Guan YUAN

“…Experiment results on real dataset show LP-MT method can ensure good efficiency and improve the accuracy by 10% compared with the existing algorithms.…”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…However, enhancing prediction models by incorporating new features extracted through regressions executed on the original dataset features can potentially improve predictive outcomes. …”
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AEGAN-Pathifier: a data augmentation method to improve cancer classification for imbalanced gene expression data by Qiaosheng Zhang, Yalong Wei, Jie Hou, Hongpeng Li, Zhaoman Zhong

“…The proposed data balancing technique has been demonstrated to be useful for cancer classification and improving the performance of classifier models. Additionally, we integrate prior knowledge from the pathway and employ the pathifier algorithm to calculate pathway scores for each sample. …”
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Optimization model for enterprise financial management utilizing genetic algorithms and fuzzy logic by Sujuan Wang, Musadaq Mansoor

“…A multi-objective mathematical model is first developed to establish key optimization goals, including cost reduction, improved capital utilization, and increased economic benefits. …”
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Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk by Ji-Eun Song, Ji Young Jang, Kyung Nam Kang, Ji Soo Jung, Chul Woo Kim, Ah Sol Kim

“…Breast cancer risk scores for each Breast Imaging-Reporting and Data System (BI-RADS) category in multi-microRNA analysis were analyzed to examine the correlation between breast cancer risk scores and mammography categories. We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. …”
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Modeling and Simulation of an Intelligent Photovoltaic Controller Based on Variable Step Algorithm of Versoria by Bo Sun, Yongquan You, Zhiyong Zhang, Chao Li

“…The key to the design of a photovoltaic controller is the design of control algorithm. So, an improved fuzzy control algorithm is proposed to overcome the shortcomings of the traditional maximum power point tracking (MPPT) algorithm. …”
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Automatic question-answering modeling in English by integrating TF-IDF and segmentation algorithms by Hainan Wang

“…To address this issue, the study puts forward the development of an automatic English question-answering model. The improved model leverages a term frequence-inverse document frequency approach and an unsupervised participle algorithm based on deep learning. …”
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Leveraging Next‐Generation Satellite Remote Sensing‐Based Snow Data to Improve Seasonal Water Supply Predictions in a Practical Machine Learning‐Driven River Forecast System by Sean W. Fleming, Karl Rittger, Catalina M. Oaida Taglialatela, Indrani Graczyk

“…Outcomes from over 200 WSF models suggest fSCA‐enabled accuracy gains are most consistent and explainable for short‐lead, late‐season forecasts (roughly 10%–25% improvements, typically), which in operational practice can be challenging as snowlines rise above in situ measurement sites. …”
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A novel NDSM fusion approach to improve UAV-Based LCC accuracy in sloping urban areas by Umut Gunes Sefercik, Ilyas Aydin, Mertcan Nazar, Can Atalay, Taskin Kavzoglu

“…In this study, a novel Normalized Digital Surface Model (NDSM) fusion approach is proposed to improve the object-based land cover classification (LCC) performance of the RGB camera equipped UAVs. …”
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Discrete Optimization Model and Algorithm for Driver Planning in Periodic Driver Routing Problem by Lin Huang, Wenya Lv, Qian Sun, Chengle Ma

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A dual-layer planning method based on improved MOPSO for distribution networks considering source–load temporal uncertainty by Guilian Wu, Guilian Wu, Jia Lin, Jinlin Liao

“…Third, an improved multi-objective particle swarm optimization (MOPSO) algorithm with adaptive inertia weights accelerates the convergence by 25%. …”
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Research on Trajectory Tracking Algorithm of Agricultural Machinery Based on Model Predictive Control by LIU Lin, ZHANG Huaqiang, QIN Changli, CHEN Yu, SU Qinghua

“… In order to overcome the problem of low accuracy and stability when pilotless agricultural machinery performs path tracking, this paper proposed a trajectory tracking method based on model predictive control (MPC).Firstly, the kinematic model of agricultural machinery was established, and the state quantity of agricultural machinery was estimated by particle filter to improve the positioning accuracy of agricultural machinery.Secondly, the gradient projection method was introduced in the design of controller.Compared with the traditional active set method, the new method reduced the number of iterative steps and has a faster convergence speed, which can improve the computational efficiency of agricultural machinery tracking control.Finally, a path tracking experiment was carried out on the ecological farm in Zibo, Shandong Province. …”
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Construction of multi-style face models based on artistic image generation algorithms by Xu Zhaoyi

“…The research results indicated that the new algorithmic model could improve the data metrics of face models. …”
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Unfolded Algorithms for Deep Phase Retrieval by Naveed Naimipour, Shahin Khobahi, Mojtaba Soltanalian, Haleh Safavi, Harry C. Shaw

“…In this paper, we approach the problem by proposing a hybrid model-based, data-driven deep architecture referred to as Unfolded Phase Retrieval (UPR), which exhibits significant potential in improving the performance of state-of-the-art data-driven and model-based phase retrieval algorithms. …”
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Curved Text Line Rectification via Bresenham’s Algorithm and Generalized Additive Models by Thomas Stogiannopoulos, Ilias Theodorakopoulos

“…Utilizing generalized additive models (GAMs), the proposed method accurately estimates text curvature and rectifies it into a straight format for improved text recognition. …”
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Intelligent Detection Algorithm for Concrete Bridge Defects Based on SATH–YOLO Model by Lanlin Zou, Ao Liu

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