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  1. 16541

    A GRNN based frame work to test the influence of nano zinc additive biodiesel blends on CI engine performance and emissions by Chiranjeeva Rao Seela, B. Ravisankar, B.M.V.A. Raju

    Published 2018-12-01
    “…The neural network predictions are corroborated with the experimental results and are found in good agreement. …”
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    Article
  2. 16542

    Consistency regularization for few shot multivariate time series forecasting by Yumei She, Yi Hong, Shikai Shen, Bin Yang, Liyi Zhang, Jianxiao Wang

    Published 2025-04-01
    “…Abstract Multivariate time series forecasting aims to accurately predict future trends by capturing and analyzing various features of the time series. …”
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    Article
  3. 16543

    CSearch: chemical space search via virtual synthesis and global optimization by Hakjean Kim, Seongok Ryu, Nuri Jung, Jinsol Yang, Chaok Seok

    Published 2024-12-01
    “…Abstract The two key components of computational molecular design are virtually generating molecules and predicting the properties of these generated molecules. …”
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    Article
  4. 16544

    Road-Adaptive Precise Path Tracking Based on Reinforcement Learning Method by Bingheng Han, Jinhong Sun

    Published 2025-07-01
    “…The framework first analyzes the obstacles around the vehicle and plans an obstacle-free reference path with the minimum curvature using the hybrid A* algorithm. Next, based on the generated reference path, the current state of the vehicle, and the vehicle motor energy efficiency diagram, the optimal speed is calculated in real time, and the vehicle dynamics preview point at the future moment—specifically, the look-ahead distance—is predicted. …”
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    Article
  5. 16545

    Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

    Published 2025-06-01
    “…A key component of the research is the application of Garson's algorithm, which identifies the relative importance of each of the seven indexes in influencing climate outcomes. …”
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    Article
  6. 16546

    Leveraging Graph Neural Networks for IoT Attack Detection by Mevlüt Uysal, Erdal Özdoğan, Onur Ceran

    Published 2025-06-01
    “…To address this challenge, researchers propose a novel hybrid approach combining Graph Neural Networks and XGBoost algorithm for robust intrusion detection in IoT ecosystems. …”
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    Article
  7. 16547

    Substrate-aware computational design of two-dimensional materials by Arslan Mazitov, Ivan Kruglov, Alexey V. Yanilkin, Aleksey V. Arsenin, Valentyn S. Volkov, Dmitry G. Kvashnin, Artem R. Oganov, Kostya S. Novoselov

    Published 2025-08-01
    “…This study presents a novel method for predicting the atomic structure of 2D materials on substrates by combining an evolutionary algorithm, a lattice-matching technique, an automated machine-learning interatomic potentials training protocol, and the ab initio thermodynamics approach. …”
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    Article
  8. 16548

    Experimental and computational optimization of sheet metal forming parameters for cylindrical cups of Al1100 and SS202 by Amit Kaimkuriya, S. Balaguru

    Published 2024-11-01
    “…WOA outperformed FEA in predictive accuracy, achieving error margins as low as 1.87% for minimum load and 2.31% for compressive strength. …”
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    Article
  9. 16549

    Big Data Analytics in IoT, social media, NLP, and information security: trends, challenges, and applications by Kamal Taha

    Published 2025-06-01
    “…A novel taxonomic framework is introduced to classify and analyze the suitability of algorithms based on empirical, experimental, and computational perspectives. …”
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    Article
  10. 16550

    Navigation strategies in Caenorhabditis elegans are differentially altered by learning. by Kevin S Chen, Anuj K Sharma, Jonathan W Pillow, Andrew M Leifer

    Published 2025-03-01
    “…Together, we present a flexible navigation algorithm that is supported by distributed neural computation in a compact brain.…”
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    Article
  11. 16551

    Graph neural network-based water contamination detection from community housing information by Raphael Anaadumba, Yigit Bozkurt, Connor Sullivan, Madhavi Pagare, Pradeep Kurup, Benyuan Liu, Mohammad Arif Ul Alam

    Published 2025-03-01
    “…Specifically, the GAT achieved an accuracy of 0.80, precision of 0.71, and recall of 0.93, outperforming XGBoost, a classical machine learning algorithm, which had an accuracy of 0.70, precision of 0.66, and recall of 0.67.Discussion: In addition to its predictive capabilities, the GAT model identifies key factors contributing to lead contamination, enabling more precise targeting of at-risk areas. …”
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  12. 16552

    Application of business analysis tools in company management by A. Yu. Orlova, A. A. Sorokin, D. G. Lovyannikov

    Published 2023-05-01
    “…We have developed an algorithm for the implementation of a business intelligence system and for this purpose built models in the EPC AS-IS and TO-BE notation. …”
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  13. 16553

    A model of head direction and landmark coding in complex environments. by Yijia Yan, Neil Burgess, Andrej Bicanski

    Published 2021-09-01
    “…Our account of visual feedback for HD stabilization provides a novel perspective on neural mechanisms of spatial navigation within richer sensory environments, and makes experimentally testable predictions.…”
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  14. 16554

    SmilODB: a multi-omics database for the medicinal plant danshen (Salvia miltiorrhiza, Lamiaceae) by Yong-Hui Liu, Wen-Qiong Zeng, Si-Fan Tao, Yi-Nuo Du, Fei-Hong Yu, Zhe-Chen Qi, Dong-Feng Yang

    Published 2025-05-01
    “…Although various omics resources have been published, there remains a lack of an integrated platform to unify genomic, transcriptomic, proteomic, and metabolomic data.MethodsTo address this gap, we constructed the S. miltiorrhiza Multi-omics Database (SmilODB, http://www.isage.top:56789/), which systematically integrates publicly available genome assemblies, transcriptome datasets, metabolic pathway annotations, and protein structural predictions. Protein structures were predicted using the RoseTTAFold algorithm, and all data were visualized using interactive heat maps, line charts, and histograms.ResultsSmilODB includes: (i) two genome assemblies of S. miltiorrhiza, (ii) 48 tissue-specific transcriptome datasets from root, leaf, and other vegetative tissues, (iii) annotated biosynthetic pathways for bioactive compounds such as tanshinones and salvianolic acids, and (iv) 2,967 high-confidence protein models. …”
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  15. 16555

    High precision water quality retrieval in Dianchi Lake using Gaofen 5 data and machine learning methods by Yuewen Feng, Jun Zhang, Sanjie Guo, Yunbai Zhang, Zhongwei Zhang

    Published 2025-02-01
    “…Extracting these indicators from remote sensing data enables rapid and efficient inversion of water quality conditions, providing a key step in predicting water pollution. The low-precision inversion results of WQI limit the understanding of the ecological safety of water resources. …”
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  16. 16556

    The perception of naturalness correlates with low-level visual features of environmental scenes. by Marc G Berman, Michael C Hout, Omid Kardan, MaryCarol R Hunter, Grigori Yourganov, John M Henderson, Taylor Hanayik, Hossein Karimi, John Jonides

    Published 2014-01-01
    “…We then trained a machine-learning algorithm to predict whether a scene was perceived as being natural or not based on these low-level visual features and we could do so with 81% accuracy. …”
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  17. 16557

    Proteína LIC10494 de Leptospira interrogans serovar Copenhageni: modelo estructural y regiones funcionales asociadas by Orlando Emilio Acevedo, George Emílio Barreto, Janneth González-Santos

    Published 2012-04-01
    “…The secondary structure was obtained by consensus of the algorithms SOPM,PREDATOR GOR4, DPM and DSC. The approach to the tertiary structure was obtained using the algorithm MUSTER. …”
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    Article
  18. 16558

    Virtual Communicative Review of Children’s Art Schools of Irkutsk Region by Dvorovenko Olga

    Published 2025-08-01
    “…The accounts with high engagement rates became involved in social media recommendation algorithms.…”
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  19. 16559

    A STUDY OF PEOPLE’S PERCEPTION OF ARTIFICIAL INTELLIGENCE IN FINANCE AND SOCIETY by Dan MITRA, Ioana-Florina COITA

    Published 2025-07-01
    “…Some of the key issues included algorithmic bias, erosion of human oversight, and threats to privacy. …”
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  20. 16560