Clinical and economic analysis as an instrument for harmonizing import substitution in the preferential segment of medicinal support by E. V. Eliseeva, E. S. Maneeva, R. K. Goncharova, A. V. Kropotov

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High-Performance Thin PTFE-Ni Metamaterial Absorber for Ultra-Broadband Applications by Camilla C. Moro Carmo, Ursula C. Resende, Silvia C. Albuquerque, Mauricio D. Almeida

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Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

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Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai, GyuWon Lee

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Application of Image Processing Technology in Aerobics Injury Diagnosis by Duo Zhang, Yan Tian

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Autonomous QoS Management and Policing in Unmanaged Local Area Networks by Christopher Köhnen, Christian Überall, Muttukrishnan Rajarajan, Rudolf Jäger, Veselin Rakočević

“…We present a new QoS Signalling Protocol, policing and admission control algorithms, and a new lightweight statistical bandwidth prediction algorithm for autonomous resource management in LANs. …”
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An implementation of smoothed particle hydrodynamic methods for fluids problems by Nguyen Hoai Son, Nguyen Duy Hung

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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…As a subset of artificial intelligence, machine learning algorithms create a mathematical model based on sample data or "training data" in order to predict or make decisions without overt planning (Du et al., 2019). …”
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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…Both decision processes skillfully utilize Monte Carlo simulation and multi-objective genetic algorithms to effectively manage the uncertainty risks in the decision-making process, thereby significantly enhancing the overall resilience of the microgrid.…”
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The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman, Hadjer Mekideche

“…The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. …”
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A Novel Mutation of the CYP11B2 in a Saudi Infant with Primary Hypoaldosteronism by Lama Alfaraidi, Abrar Alfaifi, Rawan Alquaiz, Faten Almijmaj, Horia Mawlawi

“…Given the position of the transition at a highly conserved nucleotide and the predictions of different bioinformatic algorithms, it is likely that the mutation is the pathogenic cause of this condition. …”
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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). …”
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Advancing nearshore and onshore tsunami hazard approximation with machine learning surrogates by N. Ragu Ramalingam, K. Johnson, M. Pagani, M. Pagani, M. L. V. Martina

“…The ML model serves as a surrogate, predicting the tsunami waveform on the coast and the maximum inundation depths onshore at the different test sites. …”
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Research on the WSN Node Localization Based on TOA by Qing-hui Wang, Ting-ting Lu, Meng-long Liu, Li-feng Wei

“…Simulation results show that the proposed algorithm renders satisfactory performance in terms of average delay reduction from end to end, packet loss rate, and routing overhead. …”
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Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

“…The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and convergence. …”
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Evolution of the Swiss pork production systems and logistics: the impact on infectious disease resilience by Francesco Galli, Saskia Perret-Gentil, Antoine Champetier, Rita Lüchinger, Myriam Harisberger, Thibault Kuntzer, Stefan Rieder, Christina Nathues, Beatriz Vidondo, Hartmut Lentz, Vitaly Belik, Salome Dürr

“…For Swiss pig farms, we used prediction and clustering algorithms to classify 9’687 − 11’247 trading farms between 2014 and 2019 by one of eleven production types. …”
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A Convolution Auto-Encoders Network for Aero-Engine Hot Jet FT-IR Spectrum Feature Extraction and Classification by Shuhan Du, Wei Han, Zhenping Kang, Yurong Liao, Zhaoming Li

“…The experimental result of CAE reached 96% accuracy and the prediction running time was 1.57 s. Compared with the classical PCA feature extraction and SVM, XGBoost, AdaBoost, and Random Forest classifier algorithms, as well as AE, CSAE, and CVAE deep learning classification methods, the CAE network can achieve higher accuracy and efficiency and can complete the spectral classification task.…”
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Evaluating Water Turbidity in Small Lakes Within the Taihu Lake Basin, Eastern China, Using Consumer-Grade UAV RGB Cameras by Dong Xie, Yunjie Qiu, Xiaojie Chen, Yuchen Zhao, Yuqing Feng

“…Future research should investigate advanced algorithms and additional spectral features to further enhance prediction accuracy and adaptability.…”
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Method of unknown protocol classification based on autoencoder by Chunxiang GU, Weisen WU, Ya’nan SHI, Guangsong LI

“…Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.…”
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