Classification performance improvement in imbalanced circumferential guided wave detection data by Yu-hang Zhang, Xu Zhang, Yuan-hang Gu, Li-min Fu, Xin-ran Su, Jun-dong Yuan, Qiao Wu

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Oral contrast-enhanced ultrasonographic features and radiomics analysis to predict NIH risk stratification for gastrointestinal stromal tumors by Fan Yang, Fan Yang, Fan Yang, Fan Yang, Chun-wei Liu, Dai Zhang, Dai Zhang, Dai Zhang, Dai Zhang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Hai-Ling Wang, Xi Wei, Xi Wei, Xi Wei, Xi Wei, Mo Yang, Mo Yang, Mo Yang

“…The combined model showed a better diagnostic performance.…”
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Experienced mental workload, perception of usability, their interaction and impact on task performance. by Luca Longo

“…In these procedures there is a tendency to omit characteristics of the users, aspects of the context and peculiarities of the tasks. Building a cohesive model that incorporates these features is not obvious. …”
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A novel feature fusion and mountain gazelle optimizer based framework for the recognition of jute pests in sustainable agriculture by Soner Kiziloluk, Mucahit Karaduman, Serpil Aslan, Muhammed Yildirim, Muhammad Attique Khan, Fatimah Alhayan, Yunyoung Nam

“…To improve the performance of the developed model, the features obtained using the DarkNet-53 and DenseNet-201 models were combined. …”
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Comparing variable and feature selection strategies for prediction - protocol of a simulation study in low-dimensional transplantation data. by Linard Hoessly, Jaromil Frossard, Simon Schwab, Frédérique Chammartin, Alexander Leichtle, Peter Werner Schreiber, Dionysios Neofytos, Michael Koller, with the Swiss Transplant Cohort Study (STCS)

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Online Degradation Feature Extraction of Shore Bridge Gearbox based on Morphological Fractal and Sliding Window Weibull Fitting by Dejian Sun, Xiong Hu, Bing Wang, Wei Wang, Jichang Lin

“…Firstly, according to the analysis period, the fractal dimension of the vibration energy spectrum is calculated and forming a fractal evolution curve. Performing a three-parameter Weibull fitting on the fractal sequence in the window after setting the sliding window width and step size and the scale parameter of the model is used as the performance degradation feature indicator. …”
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Color composition and its uses in the space of ontemporary Iraqi theatrical performance by Ayat sami ahmed, Aseel Laith Ahmed

“…Color goes beyond its plastic functions with pigments and lighting, as it carries social, historical and geographical features and connotations, and color creates a special awareness among the recipient to indicate the content of the theatrical performance. …”
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A Lightweight Multi-Frequency Feature Fusion Network with Efficient Attention for Breast Tumor Classification in Pathology Images by Hailong Chen, Qingqing Song, Guantong Chen

“…This paper proposes a lightweight breast tumor classification model with multi-frequency feature fusion (LMFM) to tackle the problem of inadequate feature extraction and poor classification performance. …”
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FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…Moreover, when terminal devices independently train models solely based on their local data, the model performance often suffers due to issues like data distribution disparities and insufficient training samples. …”
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Predictive value of combined DCE-MRI perfusion parameters and clinical features nomogram for microsatellite instability in colorectal cancer by Leping Peng, Wenting Ma, Xiuling Zhang, Fan Zhang, Fang Ma, Kai Ai, Xiaomei Ma, Yingmei Jia, Hong Ou-Yang, Shengting Pei, Tao Wang, Yuanhui Zhu, Lili Wang

“…Results The nomogram prediction model, which combined PLT, LNM, Ktrans, Kep, iAUC, and ADC, demonstrated good predictive performance. …”
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Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine by Saleha Kamal, Haifa F. Alhasson, Mohammed Alnusayri, Mohammed Alatiyyah, Hanan Aljuaid, Ahmad Jalal, Hui Liu

“…Our proposed system introduces an innovative approach for the identification of human activity in outdoor and indoor settings by extracting effective spatio-temporal features, along with a Multi-Class Support Vector Machine, which enhances the model’s performance to accurately identify the activity classes. …”
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Advancing Artificial Intelligence of Things Security: Integrating Feature Selection and Deep Learning for Real-Time Intrusion Detection by Faisal Albalwy, Muhannad Almohaimeed

“…These results indicate that combining Pearson analysis with PCA consistently improves classification performance across multiple models. Furthermore, the deployment of classifiers directly on the original dataset decreased the accuracy, emphasising the importance of feature selection in enhancing AIoT and IoT security. …”
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Fuzzy Performance between Surface Fitting and Energy Distribution in Turbulence Runner by Zhongwei Liang, Xiaochu Liu, Bangyan Ye, Richard Kars Brauwer

“…On the base of calculating the newly proposed mathematical features, we construct fuzzy evaluation data sequence and present a new three-dimensional fuzzy quantitative evaluation method; then the value change tendencies of kinetic energy distribution surface features can be clearly quantified, and the fuzzy performance mechanism discipline between the performance results of surface fitting algorithms, the spatial features of turbulence kinetic energy distribution surface, and their respective environmental parameter conditions can be quantitatively analyzed in detail, which results in the acquirement of final conclusions concerning the inherent turbulence kinetic energy distribution performance mechanism and its mathematical relation. …”
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Enhanced Prediction of Bond Strength in Corroded RC Structures Using Advanced Feature Selection and Ensemble Learning Framework by Jin-Yang Gui, Zhao-Hui Lu, Chun-Qing Li

“…In this framework, a novel Stacked Boosted Bond Model (SBBM) is developed, in which a Fusion-Based Feature Selection (FBFS) strategy is integrated to optimize input variables, and SHapley Additive exPlanations (SHAP) are employed to enhance interpretability. …”
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Multimodal radiomics integrating deep learning and clinical features for diagnosing multidrug-resistant tuberculosis in HIV/AIDS patients by Chang Song, Aichun Huang, Chunyan Zhao, Lemin Wen, Shulin Song, Yanrong Lin, Chaoyan Xu, Hangbiao Qiang, Qingdong Zhu

“…Background: This study aimed to develop and validate a predictive model based on multimodal data, including clinical features, radiomics features, and deep learning features, to distinguish multidrug-resistant tuberculosis (MDR-TB) in HIV/AIDS patients, thereby improving diagnostic accuracy. …”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…By employing contrast-limited adaptive histogram equalization (CLAHE), contrast-enhanced images were generated with minimal noise and prominent distinctive features. Subsequently, a CNN-SVD-Ensemble model was implemented to extract important features and reduce dimensionality. …”
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A Blueberry Maturity Detection Method Integrating Attention-Driven Multi-Scale Feature Interaction and Dynamic Upsampling by Haohai You, Zhiyi Li, Zhanchen Wei, Lijuan Zhang, Xinhua Bi, Chunguang Bi, Xuefang Li, Yunpeng Duan

“…Built on the YOLOv8n architecture, ADE-YOLO features a dimensionality-reducing convolution at the backbone’s end, reducing computational complexity while optimizing input features. …”
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A single flow detection enabled method for DDoS attacks in IoT based on traffic feature reconstruction and mapping by Lixia XIE, Bingdi YUAN, Hongyu YANG, Ze HU, Xiang CHENG, Liang ZHANG

“…To address the slow response time of existing detection modules to Internet of things (IoT) distributed denial of service (DDoS) attacks, their low feature differentiation, and poor detection performance, a single flow detection enabled method based on traffic feature reconstruction and mapping (SFDTFRM) was proposed.Firstly, SFDTFRM employed a queue to store previously arrived flow based on the first in, first out rule.Secondly, to address the issue of similarity between normal communication traffic of IoT devices and DDoS attack traffic, a multidimensional reconstruction neural network model more lightweight compared to the baseline model and a function mapping method were proposed.The modified model loss function was utilized to reconstruct the quantitative feature matrix of the queue according to the corresponding index, and transformed into a mapping feature matrix through the function mapping method, enhancing the differences between different types of traffic, including normal communication traffic of IoT devices and DDoS attack traffic.Finally, the frequency information was extracted using a text convolutional network and information entropy calculation and the machine learning classifier was employed for DDoS attack traffic detection.The experimental results on two benchmark datasets show that SFDTFRM can effectively detect different DDoS attacks, and the average metrics value of SFDTFRM is a maximum of 12.01% higher than other existing methods.…”
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Fault diagnosis in photovoltaic arrays: A robust and efficient approach using feature engineering and 1D-CNN by Yousif Mahmoud Ali, Lei Ding

“…Furthermore, the quality of the features used for diagnosis is critical for enhancing the model’s generalization and adaptability across various PV scales and topologies. …”
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PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation. by Chao Lv, Geyao Ma

“…Compared with other mainstream human pose estimation models in recent years, PoseNet++ achieves the state-of-the-art performance on the MPII, LSP, COCO and CrowdPose datasets. …”
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