Interaction of Narrative and Lyrical Principles in Texts of Contemporary Musical Performers by E. S. Moshtyleva

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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…This paper is the first to comprehensively investigate the predictability of multidimensional features on commercial bank performance using boosting regression tree. …”
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Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

“…Traditional rule-based and feature engineering approaches often struggle with complex clinical patterns and noise. …”
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Study on the Influence of Hall Effect on the Performance of Disk Generation Channel by Linyong Li, Guang Wang, Yingke Liao, Qing Wu, Peijie Ning

“…Numerical simulations were conducted to investigate the performance of the disk-shaped power generation channel under varying Hall parameters. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Abstract Objectives Radiomics-based analyses encompass multiple steps, leading to ambiguity regarding the optimal approaches for enhancing model performance. This study compares the effect of several feature selection methods, machine learning (ML) classifiers, and sources of radiomic features, on models’ performance for the diagnosis of clinically significant prostate cancer (csPCa) from bi-parametric MRI. …”
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New Stage of the Innovative Performance of Israel: Progress or the Loss of Leadership? by N. V. Zakharova, A. V. Labudin

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LGFUNet: A Water Extraction Network in SAR Images Based on Multiscale Local Features with Global Information by Xiaowei Bai, Yonghong Zhang, Jujie Wei

“…The results show that the LGFUNet model achieves the best performance, respectively.…”
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Enhanced Coronary Artery Disease Classification Through Feature Engineering and One-Dimensional Convolutional Neural Network by Atitaya Phoemsuk, Vahid Abolghasemi

“…Our findings confirm that the proposed model exhibits outstanding performance, highlighting the effectiveness of our integrated feature engineering approach with the CNN model.…”
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Oxygen Vacancy in Magnéli Phases and Its Effect on Thermoelectric Performances by Zhou Guan, Chuangshi Feng, Hongquan Song, Lingxu Yang, Xin Wang, Huijun Liu, Jiawei Zhang, Fanqian Wei, Xin Yuan, Hengyong Yang, Yu Tang, Fuxiang Zhang

“…The relationships between the phase evolution, microstructural features, and thermoelectric performance were investigated systematically. …”
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Salivary Biosensing Opportunities for Predicting Cognitive and Physical Human Performance by Sara Anne Goring, Evan D. Gray, Eric L. Miller, Tad T. Brunyé

“…Predictive performance was poor across all models, with R-squared values near zero and limited evidence that salivary analytes provided stable or meaningful performance predictions. …”
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Baby Cry Classification Using Structure-Tuned Artificial Neural Networks with Data Augmentation and MFCC Features by Tayyip Ozcan, Hafize Gungor

“…The proposed method includes data augmentation, feature extraction, hyperparameter tuning, and model training steps. …”
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Scalable bearing fault diagnosis using metaheuristic feature selection and machine learning for diverse operating conditions by B. R. Nayana, R. Subha, Rekha Radhakrishnan, P. Geethanjali

“…The performance of the five relevant feature groups that are identified is validated using four classical machine learning models and the most promising feature set that consistently performed well across all four datasets, regardless of the classifier model is identified. …”
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Advanced Heart Disease Prediction Through Spatial and Temporal Feature Learning with SCN-Deep BiLSTM by Vivek Pandey, Umesh Kumar Lilhore, Ranjan Walia

“…The performance outcome emphasizes the model’s efficacy and accurate prediction and classification of heart disease.…”
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Radar-Based Hand Gesture Recognition With Feature Fusion Using Robust CNN-LSTM and Attention Architecture by Irshad Khan, Young-Woo Kwon

“…Our model demonstrates high resilience, maintaining performance despite adverse conditions. …”
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Transformer-Based Dual-Branch Spatial–Temporal–Spectral Feature Fusion Network for Paddy Rice Mapping by Xinxin Zhang, Hongwei Wei, Yuzhou Shao, Haijun Luan, Da-Han Wang

“…The model’s performance was evaluated through experiments with the Sentinel-1 and Sentinel-2 datasets from the United States. …”
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A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…Firstly, efficient multi-scale feature fusion is performed by using a new neck structure in the original model so that it can fully exchange high-level semantic information and low-level spatial information. …”
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Climate Change Risk, Performance, and Value Added in Agricultural Sector by Ramin Amani, Zanko Ghorbani, Zana Mozaffari

“…Methodology The general definition of quantile regression states that if the linear regression model is assumed as the following equation, we have: yi=ˊxiβτ+uτi.  0<τ<1                                                                                 (1) Quantτ(yi|xi)=xiβτ                                                                                  (2) Equation (2) shows the τth conditional quantile function of the y distribution under the condition of random variables x in which the following condition holds: Quantτ(uτi|xi)=0                                                                                              (3) In the quantile regression structure, the effect of observable features on the conditional distribution is estimated through the process of minimizing the absolute value of the error element. …”
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Autonomous Aerial Vehicle Object Detection Based on Spatial Perception and Multiscale Semantic and Detail Feature Fusion by Wei Rao, Siyuan Chen, Dan Li

“…Second, to improve the detection performance of DyHead and make the model lightweight, a new feature pyramid network (SDI-MBiFPN) in the Neck of YOLOv8s is proposed, which contains a Multiscale Bidirectional Feature Pyramid Network (BiFPN), called MBiFPN, and a feature fusion method based on the redesigned Semantic and Detail Fusion (SDI). …”
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DMSF-YOLO: Cow Behavior Recognition Algorithm Based on Dynamic Mechanism and Multi-Scale Feature Fusion by Changfeng Wu, Jiandong Fang, Xiuling Wang, Yudong Zhao

“…The model can suppress the interference of background information, dynamically extract multi-scale features, perform feature fusion, distinguish similar behaviors of cows, enhance the capacity to detect small targets, and significantly improve the recognition accuracy and overall performance of the model. …”
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Performance of Malnutrition Universal Screening Tool and Patient-Generated Subjective Global Assessment in screening for cancer-related malnutrition in Nairobi, Kenya [version 2; p... by Caroline M.N. Auma, Rose O. Opiyo, Marshal M. Mweu

“…Background Malnutrition is a common feature among oncology patients. It is responsible for poor response and tolerance to anticancer therapy, increased morbidity, and mortality. …”
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