Study on Quantitative Evaluation Method of Balance Ability in Cancer Patients Based on Gait Features by Junjie LIU, Xu ZHOU, Chao YU, Qingqing CAO, Zhiming YAO, Wanqiu ZHANG, Ling ZHANG, Wanqing YAO, Ning LIN

“…Five-fold cross-validation was used to evaluate the performance of these models. Results show that the SVR model achieves the best performance with fifteen features (RMSE=3.22, R2=0.91), followed by Ridge (RMSE=3.63, R2=0.89). …”
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Investigation of the Asymmetric Features of X-Rudder Underwater Vehicle Vertical Maneuvring and Novel Motion Prediction Technology by Yinghua Li, Ziying Pan, Yongcheng Li, Changyou Song, Minghui Zhang, Mengchen Ren

“…The asymmetric characteristics of the X-rudder underwater vehicle in vertical plane maneuvering have been experimentally confirmed, and the asymmetric characteristics become more pronounced as the speed increases, according to the results, which are compared with those of tests using self-driving models. Overall, the new model accurately describes the asymmetric features of the X-rudder vehicle’s vertical maneuvering motion and correlates well with the experimental findings.…”
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GLNet: global-local feature network for wheat leaf disease image classification by Shangze Li, Shen Liu, Mingyu Ji, Yuhao Cao, Bai Yun, Bai Yun

“…This innovative design significantly enhances the model ability to understand the features of wheat leaf disease images, and thus demonstrates excellent performance and accuracy in the task of classifying wheat leaf disease images in real-world scenarios. …”
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Safety Performance Functions for Low-Volume Roads by Gianluca Dell’Acqua, Francesca Russo

“…In conclusion, two injurious crash prediction models were performed for two-lane rural roads located on flat/rolling area with a vertical grade of less than 6% and on mountainous terrain with a vertical grade of more than 6%. …”
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MANIT: a multilayer ANN integrated framework using biometrics and historical features for online examination proctoring by Manit Malhotra, Indu Chhabra

“…Empirically designed angular variation-based thresholds associated with a regression model developed with a 3-layer Deep Artificial Neural Network have made the proposed MANIT framework a reliable automatic online examination proctoring system. …”
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Immunological features of various molecular subtypes of cervical cancer and their prognostic implications in the context of disulfidptosis by Yadan Yao, Xiaomin Yang, Yuanxin Fu, Yinmin Zhang

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Machine Learning Models for Tracking Blood Loss and Resuscitation in a Hemorrhagic Shock Swine Injury Model by Jose M. Gonzalez, Ryan Ortiz, Lawrence Holland, Austin Ruiz, Evan Ross, Eric J. Snider

“…Based on the performance of these advanced metrics, we conclude that the framework for developing these metrics in the previous canine model remains applicable when applied to a swine model and results in accurate performance in these advanced metrics. …”
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Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins by Ahmed Elbeltagi, Abdullah A. Alsumaiei, Ali Raza, Mustafa Al-Mukhtar, Salim Heddam

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MCDiff: A Multilevel Conditional Diffusion Model for PolSAR Image Classification by Qingyi Zhang, Xiaoxiao Fang, Tao Liu, Ronghua Wu, Liguo Liu, Chu He

“…Experimental results on three benchmark datasets confirm MCDiff's ability to achieve high-performance explicit class probability modeling for PolSAR images among the compared methods.…”
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HyperspectralMamba: A Novel State Space Model Architecture for Hyperspectral Image Classification by Jianshang Liao, Liguo Wang

“…This paper proposes HyperspectralMamba, a novel architecture for hyperspectral image classification that integrates state space modeling with adaptive recalibration mechanisms. The method addresses limitations in existing techniques through three key innovations: (1) a novel dual-stream architecture that combines SSM global modeling with parallel convolutional local feature extraction, distinguishing our approach from existing single-stream SSM methods; (2) a band-adaptive feature recalibration mechanism specifically designed for hyperspectral data that adaptively adjusts the importance of different spectral band features; and (3) an effective feature fusion strategy that integrates global and local features through residual connections. …”
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Data driven design of ultra high performance concrete prospects and application by Bryan K. Aylas-Paredes, Taihao Han, Advaith Neithalath, Jie Huang, Ashutosh Goel, Aditya Kumar, Narayanan Neithalath

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Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review by Bruno Matos Porto

“…Logistic Regression (LR) was the most used model, while eXtreme Gradient Boosting (XGBoost), decision tree-based algorithms with Gradient Boosting (GB), and Deep Neural Networks (DNNs) showed superior performance. …”
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Differential performance evaluation of feedbacks effectiveness in analog circuitry by V. L. Svirid

“…This method allows to take into account the features of measurement process during the experimental test of this efficiency on the given model and to get results that are more reliable, agreed to the theoretical intelligence.…”
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Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach by Ji Hyun Lee, Hyun Woo Lee, Hyo Jin Lee, Tae Yun Park, Kwang Nam Jin, Dong Hyun Kim, Borim Ryu

“…Feature selection was performed using both large-scale feature learning with a Common Data Model (CDM) and specific pneumonia-related risk factors. …”
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HiEE: Hierarchical feature fusion for Chinese event extraction by Shuxiang Hou, Yurong Qian, Jiaying Chen, Jigui Zhao, Huiyong Lv, Hongyong Leng

“…Subsequently, we propose HiEE, a novel Chinese event extraction model that combines hierarchical feature fusion and external semantic enhancement. …”
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Convection-Permitting Ability in Simulating an Extratropical Cyclone Case over Southeastern South America by Matheus Henrique de Oliveira Araújo Magalhães, Michelle Simões Reboita, Rosmeri Porfírio da Rocha, Thales Chile Baldoni, Geraldo Deniro Gomes, Enrique Vieira Mattos

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Analysis of Queue Models in Simulation Applications by Abdullah Sevin, Durdali Atilgan, Göktuğ Yaman

“…Simulation provides a robust framework for analyzing and modeling complex systems. Within this framework, queue theory plays a central role by examining how systems handle incoming demands and offering insights into improving resource utilization, minimizing waiting times, and enhancing overall performance, particularly in service industries.This study provides a detailed analysis of queue theory, exploring its fundamental principles, key features, and various models. …”
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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“…This reduction in dimensionality enhances the performance of predictive models and provides valuable insights into the key factors influencing student performance. …”
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Impact of dimensionality reduction techniques on student performance prediction using machine learning by Koushik Roy, Huu-Hoa Nguyen, Dewan Md. Farid

“…This reduction in dimensionality enhances the performance of predictive models and provides valuable insights into the key factors influencing student performance. …”
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Robust vs. Non-robust radiomic features: the quest for optimal machine learning models using phantom and clinical studies by Seyyed Ali Hosseini, Ghasem Hajianfar, Brandon Hall, Stijn Servaes, Pedro Rosa-Neto, Pardis Ghafarian, Habib Zaidi, Mohammad Reza Ay

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