Ultrafast Laser Beam Profile Characterization in the Front-End of the ELI-NP Laser System Using Image Features and Machine Learning by Tayyab Imran

“…We use centroid tracking to monitor pointing fluctuations, statistical intensity analysis to detect energy instabilities, and Sobel-based edge detection to evaluate beam sharpness and extract structural features from the beam image. Geometric parameters such as ellipticity, roundness, and symmetry indicators are extracted and examined over time. …”
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A Yarn Quality Prediction Method Based on M-ESTIMATOR Robust Broad Learning System With Tightly Cascaded Feature Layers by Baowei Zhang, Zhilin Guo, Yonghua Wang

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Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine by Indu Sekhar Samanta, Pravat Kumar Rout, Kunjabihari Swain, Satyasis Mishra, Murthy Cherukuri

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Fourier Features and Machine Learning for Contour Profile Inspection in CNC Milling Parts: A Novel Intelligent Inspection Method (NIIM) by Manuel Meraz Méndez, Juan A. Ramírez Quintana, Elva Lilia Reynoso Jardón, Manuel Nandayapa, Osslan Osiris Vergara Villegas

“…The results demonstrate that the NIIM offers 96.99% accuracy, low computational requirements, 100% inspection capability, and valuable information to improve machining parameters, as well as quality classification.…”
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Explainable AI for Bipolar Disorder Diagnosis Using Hjorth Parameters by Mehrnaz Saghab Torbati, Ahmad Zandbagleh, Mohammad Reza Daliri, Amirmasoud Ahmadi, Reza Rostami, Reza Kazemi

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Discrimination of Chinese prickly ash origin place using electronic nose system and feature extraction with support vector boosting machine by Junbo Lian, Peng Wu, Wenhui Han, Yaping Xie, Yue Zheng, Yuxuan Xu, Xinlin Li, Guofeng Hou, Chengxiang Yong, Qi Lv, Qiansheng Ye, Guohua Hui

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Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

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FW-S3KIFCM: Feature Weighted Safe-Semi-Supervised Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method by Shirin Khezri, Nasser Aghazadeh, Mahdi Hashemzadeh, Amin Golzari Oskouei

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Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…Specific characteristics of the trajectory parameters of target classes were built using computer statistical modeling in the MatLab environment. …”
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Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features by Xindi Li, Jigang Dong, Baosheng Li, Ouyang Aimei, Yahong Sun, Xia Wu, Wenjuan Liu, Ruobing Li, Zhongyuan Li, Yu Yang

“…Objective: This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. …”
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Predicting Deterioration in Patients With Normotensive Acute Pulmonary Embolism Using Clinical‐Imaging Features: A Multicenter Prospective Cohort Study by Yizhuo Gao, Shibo Wei, Yuchen Liu, Zhenglun Yu, Shanshan Zhan, Binze Yang, Chuanxin Qi, Shougang Qi, Minggang Wang, Dong Jia

“…This study aims to develop and validate a novel score for deterioration prediction using clinical‐imaging features. Methods This is multicenter, prospective observational cohort study (AOAPECT [Adverse Outcomes in Acute Pulmonary Embolism patients using Computed Tomography pulmonary angiography] cohort, NCT05098769). …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

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MSKFaceNet: A Lightweight Face Recognition Neural Network for Low-Power Devices by Peng Zhang, Qinghua Ma, Yi Li, Min Cui

“…Built upon the MSKFNet module, MSKFaceNet further integrates a lightweight SE module to enhance its feature representation capabilities. Finally, we designed a real-time facial recognition attendance system based on MSKFaceNet and developed a prototype device. …”
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A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

“…Classifying emotions based on EEG signals is really important for enhancing our interactions with computers, monitoring mental health and creating applications in affective computing field. …”
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The value of 18F-FDG PET/CT combined with 3D quantitative technology and clinicopathological features in predicting prognosis of NSCLC by Yuling Su, Siwen Qiu, Jinyu Wang

“…ObjectiveTo investigate the value of Fluorine-18 Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) combined with 3D quantitative technology and clinicopathological features in predicting the prognosis of non-small cell lung cancer (NSCLC).MethodsA retrospective review was performed for patients who underwent PET/CT and curative resection of NSCLC between January 2016 and June 2019 in our hospital. …”
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The Relationship between Pathological Features and 18F-FDG PET/CT that Changed the Surgeon's Decision as Neoadjuvant Therapy in Breast Cancer by Akay Edizsoy, Ahmet Dağ, Pınar Pelin Özcan, Zehra Pınar Koç

“…Materials and Methods The demographic features and treatment plans of 151 cases who were diagnosed with any stage of breast cancer were evaluated. …”
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Studies of the impact of environmental conditions and varietal features of sweet cherry on the accumulation of vitamin C in fruits by using the regression analysis method by Іryna IVANOVA, Мarina SERDYUK, Vira MALKINA, Tetiana TYMOSHCHUK, Marharyta VOROVKA, Ivan MRYNSKYI, Anastasiia ADAMOVYCH

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A Lightweight Framework for Rapid Response to Short-Term Forecasting of Wind Farms Using Dual Scale Modeling and Normalized Feature Learning by Yan Chen, Miaolin Yu, Haochong Wei, Huanxing Qi, Yiming Qin, Xiaochun Hu, Rongxing Jiang

“…To mitigate the interference of dynamic features, we propose a normalization feature learning block (NFLBlock) as the core component of NFLM for processing sequences. …”
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Features of liver damage in patients with coronavirus disease (COVID-19) with pneumonia in relation to indicators of inflammation taking into account oxygen dependence by O. V. Riabokon, I. O. Kuliesh

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Wind during terrestrial laser scanning of trees: Simulation-based assessment of effects on point cloud features and leaf-wood classification by W. Albert, H. Weiser, H. Weiser, R. Tabernig, R. Tabernig, B. Höfle, B. Höfle

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