Flood susceptibility mapping using supervised machine learning models: insights into predictors’ significance and models’ performance by Zahid Ur Rahman, Meimei Zhang, Fang Chen, Safi Ullah, Mansoor Ahmad, Aamir Feroz, Samir Shehu Danhassan, Abdullah Azzam

“…Among the selected SML models, XGBoost demonstrated the highest performance, followed by RF, outperforming the rest of the SML models. …”
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Influence of geopolymer foam concrete on the mechanical performance of cold-formed steel built-up columns by Yanchun Li, Jiahong Wei, Aihong Han, Yun Xu, Menghui Qiao, Dazhi He

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Predictive features analysis and nomogram construction for predicting depression in elderly patients by Wei Lin, Zijun Zhao, Yingshan Yu, Hongbin Chen

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The Geometry of Concepts: Sparse Autoencoder Feature Structure by Yuxiao Li, Eric J. Michaud, David D. Baek, Joshua Engels, Xiaoqing Sun, Max Tegmark

“…We find that the quality of such parallelograms and associated function vectors improves greatly when projecting out global distractor directions such as word length, which is efficiently performed with linear discriminant analysis. (2) The “brain” intermediate-scale structure has significant spatial modularity; for example, math and code features form a “lobe” akin to functional lobes seen in neural fMRI images. …”
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Knowledge distillation for spiking neural networks: aligning features and saliency by Yifan Hu, Guoqi Li, Lei Deng

“…We further empirically demonstrate that the effectiveness of distillation is robust, irrespective of whether high-precision membrane potentials or binary spike trains are used as features. Through a quantitative measure of the consistency between model predictions and the saliency of relevant input pixels, we show that knowledge transfer is grounded in a shared understanding of salient features, rather than the exact replication of numerical activations. …”
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Comparative performance analysis of ensemble learning methods for fetal health classification by Tasnim Bill Zannah, Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Afjal Hossan Sarower, Mahbuba Begum

“…For interpretability, the framework incorporates Local Interpretable Model-agnostic Explanation, revealing influential features in each prediction. …”
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Enhancement of eye socket recognition performance using inverse histogram fusion images and the Gabor transform by Harisu Abdullahi Shehu, Ibrahim Furkan Ince, Faruk Bulut

“…This method involves the utilization of an inverse histogram fusion image to gener-ate Gabor features from the identified eye socket regions. These Gabor features are subsequently transformed into Gabor images and employed for recognition by utilizing both traditional methods and deep-learning models. …”
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Clinical features, treatment and prognosis analysis of distant metastatic esophageal cancer by Shuang Li, Yanwei Lu, Ruiqi Liu, Luanluan Huang, Ding Nan, Xiaoyan Chen, Wenjie Xia, Xiaodong Liang, Haibo Zhang

“…C-index and AUC were used to evaluate the performance of the prognosis model. The calibration curve was used to evaluate the calibration of the model. …”
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A high-efficiency modeling method for analog integrated circuits by Dongdong Chen, Yunqi Yang, Xianglong Wang, Di Li, Guoqing Xin, Yintang Yang

“…The sparse topology mapping method was proposed to map the design parameters into a sparse matrix, which includes the spatial and transistor characteristics of analog IC. The CNN model with three convolutional kernels was constructed to extract “transistor-circuit module-integrate circuit” features level by level, which can replace the simulation software to effectively improve the training efficiency and accuracy. …”
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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…Feature engineering can enhance the performance of interpretable models by identifying features that optimize classification. …”
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Development and calibration of roundabout safety performance functions using machine learning: a case study from Amman, Jordan by Diana Al-Nabulsi, Aya Hassouneh

“…A key innovation of this research lies in demonstrating that robust, data-driven SPF models can be pre-calibrated using high-resolution geometric and traffic inputs without the need for localized long-term crash records corresponding to the same features and region. …”
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Mathematical features of semantic projections and word embeddings for automatic linguistic analysis by Pedro Fernández de Córdoba, Carlos A. Reyes Pérez, Enrique A. Sánchez Pérez

“…These specific features are typically modeled as linear functionals acting on the vectors of the normed space representing the terms, sometimes referred to as semantic projections. …”
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A stacking ensemble classification model for determining the state of nitrogen-filled car tires by Shah Viraj Chetan, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Sreelatha Anoop Prabhakaranpillai, Radha Manju Bhaskarapanicker

“…Experiments with various machine learning classifiers show that the stacking ensemble approach significantly improves classification performance for ARMA (93.75%) and histogram (85.42%) features, thereby achieving higher accuracy than individual classifiers. …”
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On the performance of a viscoelastic constitutive model for micro injection moulding simulations by G. Lucchetta, A. Gava

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Analysis Model of Gateway in Wireless Mesh Network Based on M/M/1 Queuing Model by Taoshen Li, Hongyu Zhang, Jin Ye, Zhihui Ge

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Comparative Analysis of Energetic Performance of Various Photovoltaic Power Stations by Chalbash O., Berzan V., Postolati V.

“…A brief overview of the features of stationary installations and installations in the tracking of the sun is presented. …”
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Leveraging advanced feature extraction for improved kidney biopsy segmentation by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Salem Alkhalaf, Fahad Alturise

“…While the Segment Anything Model (SAM) excels in natural image segmentation, its direct application to medical imaging underperforms due to (1) insufficient preservation of fine-grained anatomical details, (2) computational inefficiency on gigapixel whole-slide images (WSIs), and (3) poor adaptation to domain-specific features like staining variability and sparse annotations. …”
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Performance of Monotonic Pile Penetration in Sand: Model Test and DEM Simulation by Jianxue Feng, Ruiqi Luo, Xiaoyu Dong, Xiaoyong Zhang, Quan Shen

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Towards the improvement of project team performance based on large language models by Mykyta Rohovyi, Marina Grinchenko

“…The subject of the study is a method for identifying poor quality project sprint task descriptions to improve team performance and reduce project risks. The purpose of the study is to improve the quality of textual descriptions of sprint tasks in tracking systems by implementing models for identifying and improving potentially poor task descriptions. …”
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Predictive athlete performance modeling with machine learning and biometric data integration by Qin Jianjun, Haytham F. Isleem, Walaa J. K. Almoghayer, Mohammad Khishe

“…By merging physiological signals i.e., Heart rate variability, oxygen consumption, muscle activation patterns, with psychological signals i.e., mental toughness, athlete engagement, group cohesion along with contextual training data, we create a hybrid model that performs superiorly as compared to traditional unidimensional models. …”
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