Comprehensive Analysis of the Role of Metabolic Features in Osteoporosis: A Multi-Omics Analysis by Chang S, Tao W, Shi P, Wu H, Liu H, Xu J, Chen J, Zhu J

“…The constructed multi-omics regulatory network aids in understanding the molecular mechanisms of metabolic features in OP progression.Keywords: osteoporosis, metabolic features, multi-omics analysis, machine learning, biomarkers…”
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Unsupervised Visual-to-Geometric Feature Reconstruction for Vision-Based Industrial Anomaly Detection by Dinh-Cuong Hoang, Phan Xuan Tan, Anh-Nhat Nguyen, Duc-Thanh Tran, Van-Hiep Duong, Anh-Truong Mai, Duc-Long Pham, Khanh-Toan Phan, Minh-Quang Do, Ta Huu Anh Duong, Tuan-Minh Huynh, Son-Anh Bui, Duc-Manh Nguyen, Viet-Anh Trinh, Khanh-Duong Tran, Thu-Uyen Nguyen

“…Instead of directly fusing these features, we propose a geometric feature reconstruction network that predicts 3D geometric features from the 2D visual features. …”
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Network Project Activities and Digital Tools for their Implementation by A. A. Belolobova

“…Features of the network project are considered, digital tools that are suitable for organizing network activities are described. …”
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Reinforcing long lead time drought forecasting with a novel hybrid deep learning model: a case study in Iran by Mahnoosh Moghaddasi, Mansour Moradi, Mahdi Mohammadi Ghaleni, Zaher Mundher Yaseen

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Towards a minimum universal features set for IoT DDoS attack detection by Osama Ebrahem, Salah Dowaji, Suhel Alhammoud

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Lightweight ECG signal classification via linear law-based feature extraction by Péter Pósfay, Marcell T Kurbucz, Péter Kovács, Antal Jakovác

“…The method identifies linear laws that capture shared patterns within a reference class, enabling compact and verifiable representations of time series data. We evaluate the method on two PhysioNet datasets, TwoLeadECG and variable projection networks (VPNet). …”
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AAAP gene family evolution and transcriptional regulation in Eucalyptus grandis under nitrogen, phosphate and boron deficiencies by Jiahui Wei, Yi Han, Huiming Xu, Lichuan Deng, Lu Li, Shasha Zhang, Ting Jiang, Yunzhuo Feng, Liuyin Ma

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Beyond Handcrafted Features: A Deep Learning Framework for Optical Flow and SLAM by Kamran Kazi, Arbab Nighat Kalhoro, Farida Memon, Azam Rafique Memon, Muddesar Iqbal

“…This paper presents a novel approach for visual Simultaneous Localization and Mapping (SLAM) using Convolution Neural Networks (CNNs) for robust map creation. Traditional SLAM methods rely on handcrafted features, which are susceptible to viewpoint changes, occlusions, and illumination variations. …”
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Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…The models’ performances were evaluated using accuracy, precision, recall and F1-score and NN presented the best performance overall achieving an F1-score of 85% for the correlated feature pairs (CF) and 75% for the direct feature pairs. …”
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Decomposition and attribution analysis of the coupled evolution characteristics of groundwater and land subsidence in the Beijing-Tianjin-Hebei Plain by Yongkang Wang, Huili Gong, Chaofan Zhou, Qin Wang, Haotong Wang, Jincai Zhang

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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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A New Hybrid PSO-HHO Wrapper Based Optimization for Feature Selection by Sumbul Azeem, Shazia Javed, Iftikhar Naseer, Oualid Ali, Taher M. Ghazal

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Federated and ensemble learning framework with optimized feature selection for heart disease detection by Olfa Hrizi, Karim Gasmi, Abdulrahman Alyami, Adel Alkhalil, Ibrahim Alrashdi, Ali Alqazzaz, Lassaad Ben Ammar, Manel Mrabet, Alameen E.M. Abdalrahman, Samia Yahyaoui

“…To improve classification performance while protecting data privacy, this study investigated a combined method that uses ensemble learning, feature selection, and federated learning (FL). The ensemble-based approaches proved the most predictive after testing several different machine learning (ML) models, including random forests, the light gradient boosting machine, support vector machines, k-nearest neighbors, convolutional neural networks, and long short-term memory. …”
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FEATURES OF LIFE PERSPECTIVE OF FORCED DISPLACED PERSONS DURING ARMED CONFLICT IN UKRAINE by Harkusha Inesa, Dubinskyi Serhii

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Social media in the structure of modern network communication by A.G. Astashkin, M.G. Bresler

“…The current role of social media in political, sociocultural, and marketing network communications has been analyzed. The paper also touches upon the convergence of mass and social media, as well as upon the evolution of social networks as a form of social media.…”
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Generative Adversarial Networks for Climate-Sensitive Urban Morphology: An Integration of Pix2Pix and the Cycle Generative Adversarial Network by Mo Wang, Ziheng Xiong, Jiayu Zhao, Shiqi Zhou, Yuankai Wang, Rana Muhammad Adnan Ikram, Lie Wang, Soon Keat Tan

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WAYS OF IMPROVING SERVICE QUALITY IN NETWORK RETAIL by Valentyna A. Pavlova, Olena Yu. Meshal

“…The point system and evaluation method were defined. Based on the Harrington scale, a modified mystery shopper evaluation matrix was developed. …”
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Research of migration processes in electronic social networks by A. A. Grebenyuk, A. A. Subbotin

“…The study also gives important methodological features, the success of the results of any research conducted through the analysis of electronic social networks depends on the consideration of which. …”
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Aerial Images Segmentation with Graph Neural Network by A. V. Emelyanov, A. V. Emelyanov, V. A. Knyaz, V. A. Knyaz, V. V. Kniaz, V. V. Kniaz, S. Yu. Zheltov

“…The developed framework at first phase utilizes visual transformer for retrieving deep features from the input aerial image. The graph neural network then performs clustering of the extracted deep features to obtain semantic segmentation of the image. …”
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Toward a thermodynamic theory of evolution: a theoretical perspective on information entropy reduction and the emergence of complexity by Carlos Mendoza Montano

“…Empirical support is drawn from diverse domains, including autocatalytic networks in prebiotic chemistry, genome streamlining in microbial evolution, predictive coding in neural systems, and ecosystem-level energy-information coupling. …”
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