Rolling Based on Multi-Source Time–Frequency Feature Fusion with a Wavelet-Convolution, Channel-Attention-Residual Network-Bearing Fault Diagnosis Method by Tongshuhao Feng, Zhuoran Wang, Lipeng Qiu, Hongkun Li, Zhen Wang

“…To address this issue, this study proposes a lightweight fault diagnosis model (WaveCAResNet) enhanced with multi-source time–frequency features. …”
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A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization by Kabiru O. Akande, Taoreed O. Owolabi, Sunday O. Olatunji, AbdulAzeez Abdulraheem

“…Hybrid computational intelligence is defined as a combination of multiple intelligent algorithms such that the resulting model has superior performance to the individual algorithms. …”
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Farmers’ Strategic of the Sustainability of Corporate-Based Cassava Farming: A Study of Technology Adoption on Farming Performance by Muttaqien Zuhri Nur, Khamdi Ali, Imam Santoso Wahyu, Maulida Suci Ayomi Nun, Puspita Nurul, Suharti Suharti, Purwanto Edy, Linu Ibrahim Agusnawan, Dimitha Nurulia, Danil Furqansyah M.

“…In this study, which included 65 respondents, structural equation modelling (SEM-PLS) based on WARP-PLS was used to identify the critical features that yield the best agricultural performance. …”
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Comparative analysis of transfer learning performance on generalised EEG data for use in a depression diagnosis task by Shusharina, Natalia Nikolaevna

“…Therefore, EEGNet was replaced by a 1D CNN architecture with a larger number of parameters, which led to an increase in the quality performance of the models. Conclusion. Although the considered method of transient learning looks promising, the specificity of electroencephalogram signals and problems solved on their basis requires large-scale adaptation of algorithms and contrastive optimisation techniques for effective training of the target task. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The impact of 12 influential features on CS was evaluated to optimize the performance of the proposed models. …”
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Computed tomography-based radiomic features combined with clinical parameters for predicting post-infectious bronchiolitis obliterans in children with adenovirus pneumonia: a retro... by Li Zhang, Ling He, Guangli Zhang, Xiaoyin Tian, Haoru Wang, Fang Wang, Xin Chen, Yinglan Zheng, Man Li, Yang Li, Zhengxiu Luo

“…Objectives To develop a model incorporating computed tomography (CT) radiomic features and clinical parameters for predicting bronchiolitis obliterans (BO) with adenovirus pneumonia in children. …”
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Deep Learning for Time-Series Forecasting With Exogenous Variables in Energy Consumption: A Performance and Interpretability Analysis by Ava Mohammadi, Gonzalo Napoles, Yamisleydi Salgueiro

“…Beyond predictive accuracy, interpretability analysis challenges the assumption that attention mechanisms reliably capture feature importance. Performance degradation analysis revealed that perturbing features ranked highly by SHAP values and permutation feature importance led to sharper error increases than attention-based rankings, with permutation demonstrating the strongest correlation with prediction errors. …”
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OUMVLP-OF: Multi-View Large Population Gait Database With Dense Optical Flow and Its Performance Evaluation by Allam Shehata, Francisco M. Castro, Nicolas Guil, Manuel J. Marin-Jimenez, Yasushi Yagi

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Geo-Statistics and Deep Learning-Based Algorithm Design for Real-Time Bus Geo-Location and Arrival Time Estimation Features with Load Resiliency Capacity by Smail Tigani

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A 10-meter global terrace mapping using sentinel-2 imagery and topographic features with deep learning methods and cloud computing platform support by Yifan Li, Fuyou Tian, Miao Zhang, Hongwei Zeng, Shukri Ahmed, Xinli Qin, Yanxu Liu, Lizhe Wang, Runyu Fan, Bingfang Wu

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Flood risk mapping and performance efficiency evaluation of machine learning algorithms: Best practice in northern Iran by M. Shirmohammadi, M. Shirmohammadi, S. Pirasteh, W. Li, D. Mafi-Gholami

“…Data processing, feature extraction, and model training were conducted using Python, Google Earth Engine, and ArcGIS. …”
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Performance Analysis of Rare-Earth Doped Oxide Thin-Film Transistors Using Neural Network Method by Zengyi Peng, Xianglan Huang, Yuanyi Shen, Weijing Wu, Min Li, Miao Xu, Lei Wang, Zhenghui Gu, Zhuliang Yu, Junbiao Peng

“…Accordingly, the efficient neural network models tailored to the data features were accurately established. …”
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Multiscale feature tuned trans-DeepLabV3+ based semantic segmentation of aerial images using improved red piranha optimization algorithm by P. Anilkumar, K. Lokesh, A. Naveen Kumar, D. John Pradeep, Y. V. Pavan Kumar, Rammohan Mallipeddi

“…To assess how well the implemented model performs, an experimental setup is carried out. …”
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Simulation and Annual Performance Analysis on a Direct-expansion Solar-assisted PVT Heat Pump System by Liu Wenjie, Yao Jian, Dai Yanjun

“…By contrast, such coupling enhanced the evaporation temperature and thus the performance of the heat pump. The simulation model, which was developed based on the energy balance and heat transfer feature of the collector/evaporator, was compared to the experimental results and it presented a maximum error of 6.2%. …”
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An Empirical Model-Based Algorithm for Removing Motion-Caused Artifacts in Motor Imagery EEG Data for Classification Using an Optimized CNN Model by Rajesh Kannan Megalingam, Kariparambil Sudheesh Sankardas, Sakthiprasad Kuttankulangara Manoharan

“…This accuracy demonstrates the model’s effectiveness compared to other state-of-the-art techniques. …”
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An Improved V-Net Model for Thyroid Nodule Segmentation by Büşra Yetginler, İsmail Atacak

“…In addition to the strengths of the V-Net approach in the proposed model, a squeeze-and-excitation (SE) mechanism was used to emphasize important features and suppress irrelevant features by assigning weights to the significant features of the model. …”
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Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning. by Shan Gao, Amit K Chakraborty, Russell Greiner, Mark A Lewis, Hao Wang

“…We tested our methods on synthetic data from a Susceptible-Infected-Recovered (SIR) model for slowly changing, noisy disease dynamics. …”
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Effect of the number and placement of punched holes in rectangular winglet vortex generators on solar air heater performance by Boonchai Lertnuwat

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Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma. by Yusuke Suita, Hardy Bright, Yuan Pu, Merih Deniz Toruner, Jordan Idehen, Nikos Tapinos, Ritambhara Singh

“…The model trained on one patient generalizes to other 11 patients with high performance. …”
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Detection of arterial remodeling using epicardial adipose tissue assessment from CT calcium scoring scan by Juhwan Lee, Tao Hu, Michelle C. Williams, Ammar Hoori, Hao Wu, Justin N. Kim, David E. Newby, Robert Gilkeson, Robert Gilkeson, Sanjay Rajagopalan, David L. Wilson, David L. Wilson

“…Feature selection was performed using Elastic Net logistic regression, and the selected features were used to train a CatBoost machine learning model. …”
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