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  1. 18141

    Detection of Defects in Polyethylene and Polyamide Flat Panels Using Airborne Ultrasound-Traditional and Machine Learning Approach by Artur Krolik, Radosław Drelich, Michał Pakuła, Dariusz Mikołajewski, Izabela Rojek

    Published 2024-11-01
    “…Furthermore, ML models are adaptable, allowing the same trained algorithms to work on various material batches or panel types with minimal retraining. …”
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  2. 18142

    Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod by Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé

    Published 2024-11-01
    “…We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. …”
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  3. 18143

    Machine Learning Prognostic Model for Post-Radical Resection Hepatocellular Carcinoma in Hepatitis B Patients by Zhu D, Tulahong A, Abuduhelili A, Liu C, Aierken A, Lin Y, Jiang T, Lin R, Shao Y, Aji T

    Published 2025-02-01
    “…A prognostic model was developed using a machine learning algorithm and evaluated for predictive performance using the concordance index (C-index), calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.Results: Key predictors for constructing the best model included body mass index (BMI), albumin (ALB) levels, surgical resection method (SRM), and the American Joint Committee on Cancer (AJCC) stage. …”
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  4. 18144

    Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

    Published 2025-08-01
    “…A range of sophisticated artificial intelligence methods, including One-Dimensional Convolutional Neural Network (1D-CNN), Artificial Neural Networks (ANN), Decision Tree (DT), Ensemble Learning (EL), Adaptive Boosting (AdaBoost), Random Forest (RF), and Least Squares Support Vector Machine (LSSVM), were utilized to model and predict pH variations with high accuracy. The Coupled Simulated Annealing (CSA) algorithm was employed to optimize the hyperparameters of these models, enhancing their predictive performance. …”
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  5. 18145

    Mechanical Ventilation Strategies in Buildings: A Comprehensive Review of Climate Management, Indoor Air Quality, and Energy Efficiency by Farhan Lafta Rashid, Mudhar A. Al-Obaidi, Najah M. L. Al Maimuri, Arman Ameen, Ephraim Bonah Agyekum, Atef Chibani, Mohamed Kezzar

    Published 2025-07-01
    “…Heat recovery systems achieve efficiencies of nearly 90%, leading to a reduction in heating energy consumption by approximately 19%. …”
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  8. 18148

    Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction by Dajana Snopková, Martin Tancoš, Lukáš Herman, Vojtěch Juřík

    Published 2025-01-01
    “…Abstract Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. …”
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  9. 18149

    Ethical Foundations of AI-Driven Avatars in the Metaverse for Innovation and User Privacy by Ammar Almomani, Ahmad Al-Qerem, Mohammad Alauthman, Amjad Aldweesh, Samer Aoudi, Said A. Salloum

    Published 2025-01-01
    “…However, these advances also introduce critical ethical and legal dilemmas surrounding privacy, identity theft, algorithmic bias, and data governance. This study employs a comprehensive multimethodological approach combining systematic literature review, regulatory gap analysis, and ethical framework synthesis. …”
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  10. 18150

    Open system of text processing for scientometric and bibliometric purposes by L. S. Lomakina, A. S. Surkova, D. V. Zhevnerchuk, O. S. Rassadin

    Published 2018-03-01
    “…The key features of the proposed solution are the ability to implement basic algorithms for text data analyzing and processing in the form of RESTful services, executing of these processes in a distributed processing environment, creating combined algorithms based on them, and also the ability to build an applied programming interface for creating client-server systems with mobile and fixed client subsystems in the field of science and education.…”
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  11. 18151
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  13. 18153

    Soil moisture dominates gross primary productivity variation during severe droughts in Central Asia by Tao Yu, Guli Jiapaer, Anming Bao, Ye Yuan, Jiayu Bao, Tim Van de Voorde

    Published 2025-05-01
    “…P-model simulations indicate that SM deficits dominated the decline in GPP in 2008 and 2021, affecting regions covering 31 % and 17 % of CA, respectively, with GPP reductions exceeding 5 %. RF predictions also indicated that during severe drought, SM had a significant effect on GPP, while Srad, Tem, and VPD had a slight effect on GPP.…”
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  14. 18154

    Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

    Published 2025-06-01
    “…Most Reinforcement Learning (RL) algorithms optimize a single-objective function, whereas real-world decision-making involves multiple aspects. …”
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  15. 18155

    A comprehensive review of bibliometric and methodological approaches in flood mitigation studies: Current trends and future directions by Funmilayo Ebun Rotimi, Roohollah Kalatehjari, Taofeeq Durojaye Moshood, George Dokyi

    Published 2025-06-01
    “…It advocates for a multidisciplinary and integrated approach, leveraging geospatial technologies, machine learning algorithms, and collaborative methodologies to advance flood mitigation research and practice. …”
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  16. 18156

    PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

    Published 2025-07-01
    “…The performance of PCES-YOLO is also evaluated against mainstream object detection algorithms, including Faster R-CNN, SSD, YOLOv8n, etc. …”
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  17. 18157
  18. 18158

    Design and Characterization of the Modified Purdue Subcritical Pile for Nuclear Research Applications by Matthew Niichel, Vasileios Theos, Riley Madden, Hannah Pike, True Miller, Brian Jowers, Stylianos Chatzidakis

    Published 2025-06-01
    “…First demonstrated in 1942, subcritical and zero-power critical assemblies, also known as piles, are a fundamental tool for research and education at universities. Traditionally, their role has been primarily instructional and for measuring the fundamental properties of neutron diffusion and transport. …”
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  19. 18159

    Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method by Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei

    Published 2025-01-01
    “…While deep learning algorithms have shown promise in energy applications, single algorithms often struggle with unstable predictions and limited generalizability for predicting photovoltaic (PV) output. …”
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  20. 18160

    Optimising coronary imaging decisions with machine learning: an external validation study by Floor Groepenhoff, Leonard Hofstra, Sophie Heleen Bots, Saskia Haitjema, Imo Hoefer, L. Malin Overmars, Bram van Es, Mark C. H. De Groot, G. Aernout Somsen, I. Igor Tulevski, Hester M. den Ruijter, Wouter W. van Solinge

    Published 2025-05-01
    “…This study aimed to externally validate sex-stratified machine learning algorithms based on EHR data to predict the absence of coronary stenosis, evaluated in diverse clinical settings.Methods Sex-stratified XGBoost algorithms were trained on EHR data from patients who underwent coronary imaging at the University Medical Center Utrecht (n=14 674) and externally tested on EHR data of 13 Cardiology centres in the Netherlands (n=9252). …”
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