Nonlinear Dynamic Performance of a Bolt-Disc Rotor with the Position Error of Circumferential Bolt-Holes by Haibo Zhang, Yi Liu, Xin Huang

“…The position error of circumferential bolt-holes is created in a three-dimensional model of bolt-disc rotor. The distribution of nonuniform stress and deformation is acquired according to finite element approach. …”
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Measuring while moving (humanitarian supply chain performance measurement – status of research and current practice) by Charles D'Haene, Sara Verlinde, Cathy Macharis

“…Results are discussed using a situation-actor-process – learning-action-performance model of inquiry. Preceding this investigation, a literature review delves into research on humanitarian supply chain performance measurement and presents the most relevant pieces in a general framework. …”
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Are Deep Learning Models in Hydrology Entity Aware? by Benedikt Heudorfer, Hoshin V. Gupta, Ralf Loritz

“…Abstract Hydrology is experiencing a shift from process‐based toward deep learning (DL) models. Entity‐aware (EA) DL models with static features (predominantly physiographic proxies) merged to dynamic forcing features show significant performance improvements. …”
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Predicting Student Academic Performance at Higher Education Using Data Mining: A Systematic Review by Sarah A. Alwarthan, Nida Aslam, Irfan Ullah Khan

“…In addition, this study summarized the highest influential features used for predicting the student academic performance where identifying the most influential factors on student’s performance level will help the student as well as the policymakers and will give detailed insights into the problem. …”
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Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer by Sepideh Azarianpour, Sirvan Khalighi, Arpit Aggarwal, Vidya Sankar Viswanathan, Pingfu Fu, Stefanie Avril, Anant Madabhushi

“…We identified the differences in immune cell spatial patterns between AA and EA populations with markers of tumor biology, including histologic and molecular subtypes. The models performed best when they were trained and validated using data from the same population. …”
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Statistical analysis and machine learning of TMS-induced MEPs for predicting poststroke motor impairment and performance by Chun-Ren Phang, Shintaro Uehara, Sachiko Kodera, Akiko Yuasa, Shin Kitamura, Yohei Otaka, Akimasa Hirata

“…These findings suggest that bilateral MEP features, particularly those from the contralesional hemisphere, offer valuable prognostic information. …”
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Numerical studies on thermo-hydraulic performance of solar air heater with quarter circle roughness ribs by Yaregal Eneyew Bizuneh, Tazebew Dires Kassie, Atalay Enyew Bizuneh

“…The k–ε RNG turbulence model was used to conduct 2D steady-state numerical simulations, and the findings showed excellent agreement with the smooth duct and related literatures. …”
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Notice of Violation of IEEE Publication Principles: Ground-Based Cloud Image Recognition System Based on Multi-CNN and Feature Screening and Fusion by Ma Jingyi, Tiejun Zhang, Jing Guodong, Yan Wenjun, Yang Bin

“…The multi-level and multi-scale convolution feature extraction is performed through convolution layers of Multi-CNN, and the local features with strong resolving power are selected through the feature screening algorithm based on DP clustering. …”
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Predicting biking preferences in Kigali city: A comparative study of traditional statistical models and ensemble machine learning models by Jean Marie Vianney Ntamwiza, Hannibal Bwire

“…Specifically, it compared the performance of traditional statistical models—logistic regression, support vector machine (SVM), Naïve Bayes, and k-Nearest Neighbours (KNN)—with ensemble models including eXtreme Gradient Boosting (XGBoost), Light GBM, Random Forest, and stacking classifiers. …”
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Shear Performance of Reinforced Shear Pocket Joint in Light Steel—Recycled Concrete Composite Floor by Jinliang Bian, Jingwei Zhang, Lidong Zhao, Wei Gan, Wanlin Cao

“…A refined finite element model was established for an in-depth parameter analysis. …”
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Contributing factors to marketing educators’ teaching performance: insights from executive postgraduate programmes in Brazil by Alexandre Borba Salvador, Mariana Bassi-Suter, Nicola Forsdike

“…Findings – The teaching performance depends on the teaching practice, which is influenced by technical knowledge, pedagogical factors and personal features. …”
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An open source microcontroller based flume for evaluating swimming performance of larval, juvenile, and adult zebrafish. by Jeffrey J Widrick, Devin E Gibbs, Benjamin Sanchez, Vandana A Gupta, Anna Pakula, Christian Lawrence, Alan H Beggs, Louis M Kunkel

“…Zebrafish are a preferred vertebrate model for delineating genotype-phenotype relationships. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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Performance Testing and Analysis of a New GNSS Spoofing Detection Method in Different Spoofing Scenarios by Li Junzhi, Wu Haitao, Gao Jinfeng, Liu Fang, Zhang Yu, Li Gangqiang, He Yu

“…By improving the RF algorithm and introducing a weighted voting mechanism to optimize the classification decision process, a high-precision classification model is constructed. Experiments were conducted using the Texas Spoofing Test Battery (TEXBAT) dataset and a self-built spoofing platform to evaluate the performance of the proposed method under various spoofing scenarios. …”
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Joint Three-Task Optical Performance Monitoring with High Performance and Superior Generalizability Using a Meta-Learning-Based Convolutional Neural Network-Attention Algorithm and... by Di Zhang, Junyao Shi, Yameng Cao, Yan Ling Xue

“…The CNN-ATT algorithm can effectively extract comprehensive features, capturing both local and global dependencies, thus improving the quality of the feature representation. …”
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Evaluation method for gas pre-extraction status in coal seam boreholes based on semi-supervised learning by YAN Li, WEN Hu, WANG Zhenping, JIN Yongfei

“…Current evaluation methods for single-borehole gas extraction status typically rely on gas concentration, while overlooking the diversity of coal seam gas occurrence. Supervised learning models depend on labeled sample features, but manual labeling becomes costly when the sample size is large. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…The dataset underwent extensive preprocessing, including missing value imputation, data balancing checks, and feature selection to ensure robustness. Among the models tested, Random Forest demonstrated superior performance in the binary classification task, achieving an average class AUC of 0.768, classification accuracy of 0.777, precision of 0.752, and recall of 0.777. …”
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Performance Limits for Fingerprinting-Based Indoor Optical Communication Positioning Systems Exploiting Multipath Reflections by Hamid Hosseinianfar, Maite Brandt-Pearce

“…However, due to the inherent transmission features of light, the optical wireless indoor channel is static; therefore, multipath components can be modeled as deterministic functions of the transceiver location, furnishings, and room geometry. …”
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Assessing the performance of 28 pathogenicity prediction methods on rare single nucleotide variants in coding regions by Jee Yeon Heo, Ju Han Kim

“…Conclusions These results provide insights into the strengths and limitations of each method in predicting the pathogenicity of rare variants, which may guide future improvements in predictive models. Furthermore, while AF and existing prediction scores offer valuable information for prediction methods, the identification of novel biological features is essential to overcome current limitations and further improve predictive performance.…”
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An explainable analytical approach to heart attack detection using biomarkers and nature-inspired algorithms by Maithri Bairy, Krishnaraj Chadaga, Niranjana Sampathila, R. Vijaya Arjunan, G. Muralidhar Bairy

“…Fourteen nature-inspired feature selection algorithms were applied to identify the most informative markers while optimizing the predictive models for greater accuracy and reliability. …”
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