Non-Destructive Detection of Chilled Mutton Freshness Using a Dual-Branch Hierarchical Spectral Feature-Aware Network by Jixiang E, Chengjun Zhai, Xinhua Jiang, Ziyang Xu, Muqiu Wudan, Danyang Li

“…By leveraging multi-head attention and cross-scale fusion, the model more effectively captures both the overall spectral variation trends and fine-grained feature details. …”
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Boosting any learning algorithm with Statistically Enhanced Learning by Florian Felice, Christophe Ley, Stéphane P. A. Bordas, Andreas Groll

“…While any data scientist knows the importance of rigorously preparing data to obtain good performing models, only scarce literature formalizes its benefits. …”
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Estimation of the High-Frequency Feature Slope in Gravitational Wave Signals from Core Collapse Supernovae Using Machine Learning by Alejandro Casallas-Lagos, Javier M. Antelis, Claudia Moreno, Ramiro Franco-Hernández

“…We conducted an in-depth exploration of the use of different machine learning (ML) for regression algorithms, including Linear, Ridge, LASSO, Bayesian Ridge, Decision Tree, and a variety of Deep Neural Network (DNN) architectures, to estimate the slope of the high-frequency feature (HFF), a prominent emergent feature found in the gravitational wave (GW) signals of core collapse supernovae (CCSN). …”
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A Non-Invasive Fetal QRS Complex Detection Method Based on a Multi-Feature Fusion Neural Network by Zhuya Huang, Junsheng Yu, Ying Shan, Xiangqing Wang

“…Finally, the deep neural network using three multi-feature fusion strategies—feature-level fusion, decision-level fusion, and model-level fusion—achieves the effect of quickly identifying fetal QRS complexes. …”
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Episodic Training and Feature Orthogonality-Driven Domain Generalization for Rotating Machinery Fault Diagnosis Under Unseen Working Conditions by Yixiao Liao, Songbin Zhou, Yisen Liu, Kunkun Pang, Jing Li, Chang Li, Lulu Zhao

“…Furthermore, the orthogonality between fault-related and domain-related features is enhanced by minimizing their cosine similarity, thereby improving the generalization capability of the DGFD model. …”
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Dual-Alignment CLIP: Task-Specific Alignment of Text and Visual Features for Few-Shot Remote Sensing Scene Classification by Dongmei Deng, Ping Yao

“…Recently, contrastive vision-language pretraining (CLIP) has shown impressive few-shot image classification performance in downstream remote sensing tasks. However, existing CLIP-based methods still have two essential issues: 1) bias in text features; 2) unreliable similarity in image features. …”
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Aberrant fragmentomic features of circulating cell-free mitochondrial DNA enable early detection and prognosis prediction of hepatocellular carcinoma by Yang Liu, Fan Peng, Siyuan Wang, Huanmin Jiao, Kaixiang Zhou, Wenjie Guo, Shanshan Guo, Miao Dang, Huanqin Zhang, Weizheng Zhou, Xu Guo, Jinliang Xing

“…Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. …”
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Cardiovascular magnetic resonance feature tracking derived strain analysis can predict return to training following exertional heatstroke by Jun Zhang, Song Luo, Li Qi, Shutian Xu, Dongna Yi, Yue Jiang, Xiang Kong, Tongyuan Liu, Weiqiang Dou, Jun Cai, Long Jiang Zhang

“…Multivariable logistic regression analysis was used to develop a predictive RTT model. The performance of different models was compared using the area under curve (AUC). …”
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Modelling HIV/AIDS epidemiological complexity: A scoping review of Agent-Based Models and their application. by Rodrigo Volmir Anderle, Robson Bruniera de Oliveira, Felipe Alves Rubio, James Macinko, Ines Dourado, Davide Rasella

“…Bottom-up designs, such as the Agent-Based Model (ABM), can model these features, dealing with such complexity. …”
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Theoretical Model, Model Innovation, and Important Implications of DeepSeek Empowering Library Knowledge Services by ZHANG Xingwang, LI Jie, LI Sifan, WANG Xiaopei

“…At the same time, it can bring many problems, such as model security, intellectual property risks, knowledge illusions, and information cocoons. …”
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Relation between executive functioning, sensory processing, and motor performance in children with autism by Rehab H Alsaedi

“…Abstract Purpose The neurological model of autism proposes that higher-order processing disturbances underpin the condition’s behavioral features, although emerging evidence attributes these executive functioning issues to lower-order processing disturbances influenced by sensory and motor development. …”
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Integrating AutoGluon for Real-Time Monitoring and Classification of Dental Equipment Performance by Muxiu Yang, Fengzhou Li, Wenfeng Qiu

“…This study aims to introduce AutoGluon, an automated machine learning (AutoML) framework that monitors and classifies the performance of dental equipment in real time. The intent is to enable predictive maintenance through data processing automation, model selection and performance classification. …”
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Feature-Guided Instance Mining and Task-Aligned Focal Loss for Weakly Supervised Object Detection in Remote Sensing Images by Jinlin Tan, Chenhao Wang, Xiaomin Tan, Min Zhang, Hai Wang

“…Second, current models fail to ensure consistency between classification and regression, limiting the upper bound of WSOD performance. …”
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A Flow Shop Scheduling Method Based on Dual BP Neural Networks with Multi-Layer Topology Feature Parameters by Hui Mu, Zinuo Wang, Jiaqi Chen, Guoqiang Zhang, Shaocun Wang, Fuqiang Zhang

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Keypoints-Based Multi-Cue Feature Fusion Network (MF-Net) for Action Recognition of ADHD Children in TOVA Assessment by Wanyu Tang, Chao Shi, Yuanyuan Li, Zhonglan Tang, Gang Yang, Jing Zhang, Ling He

“…For facial keypoints, we transform data into images and employ MobileVitv2 for transfer learning to capture facial and head movement features. Ultimately, a feature fusion module is designed to fuse the features from both branches, yielding the final action category prediction. …”
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Maximizing steel slice defect detection: Integrating ResNet101 deep features with SVM via Bayesian optimization by Prabira Kumar Sethy, Laxminarayana Korada, Santi Kumari Behera, Akshay Shirole, Rajat Amat, Aziz Nanthaamornphong

“…We propose a novel approach that utilizes the ResNet101 model to extract deep features, which are then classified using a support vector machine (SVM). …”
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Machine Learning Prediction of Airfoil Aerodynamic Performance Using Neural Network Ensembles by Diana-Andreea Sterpu, Daniel Măriuța, Grigore Cican, Ciprian-Marius Larco, Lucian-Teodor Grigorie

“…In this study, a hybrid deep learning model is proposed, combining convolutional neural networks (CNNs) and operating directly on raw airfoil geometry, with parallel branches of fully connected deep neural networks (DNNs) that process operational parameters and engineered features. …”
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Prediction of Attention Groups and Big Five Personality Traits from Gaze Features Collected from an Outlier Search Game by Rachid Rhyad Saboundji, Kinga Bettina Faragó, Violetta Firyaridi

“…The models achieved above-chance predictive performance in both 2D and VR settings despite visually complex 3D stimuli. …”
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Warning indicators of COVID-19 severity: a retrospective observational study integrating modern biomarkers and traditional tongue features by Zhang Jing, Zhang Jing, Liu Yuntao, Zheng Danwen, Ye Gangfu, Chen Qiumin, Huang Jianshan, Wang Jiamei, Ma Zengming, Zhang Zhongde

“…The combined model integrating these factors demonstrated superior predictive performance (Nagelkerke R2 = 0.741).ConclusionIntegrating TCM tongue features (thick fur and fat shape) with clinical biomarkers (age, fever, and PCT) enhances early identification of severe COVID-19, particularly in resource-limited settings.…”
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Study on the Use of Hydride Fuel in High-Performance Light Water Reactor Concept by Haileyesus Tsige-Tamirat, Luca Ammirabile

“…Neutronics and thermal hydraulic analyses were performed for a single assembly model of HPLWR with oxide and hydride fuels. …”
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