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  1. 16741

    Hyperelastic behavior of cable gland silicon shroud: finite element analysis by Ganesh Bhoye, Ishant Jain

    Published 2025-02-01
    “…The hyperelastic material model developed in this study provides a robust tool for predicting the shroud’s behavior under varied loading conditions, enabling optimized designs and ensuring long-term performance.…”
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    Article
  2. 16742

    Dynamics of Robo-Advisory Financial Services in Saudi Arabia by Heba Gazzaz

    Published 2025-06-01
    “…The study shows that the Saudi robo-advisory sector is predicted to record revenues of $34.56 million by 2025, with the penetration rate in the market expected to remain steady after 2022 due to market maturity. …”
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    Article
  3. 16743

    Forecasting the Turkish lira Exchange Rates Through Univariate Techniques: Can the Simple Models Outperform the Sophisticated Ones? by M. R. Sarkandiz, S. Ghayekhloo

    Published 2024-04-01
    “…To examine that claim, present study has utilized several models to predict daily exchange rates for a short horizon. …”
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    Article
  4. 16744

    Dynamic emotion intensity estimation from physiological signals facilitating interpretation via appraisal theory. by Isabel Barradas, Reinhard Tschiesner, Angelika Peer

    Published 2025-01-01
    “…The NARX model parameters obtained, interpreted by appraisal theory, indicate consistent heart rate parameters in the intersubject models, suggesting a large temporal contribution that aligns with the CPM-predicted changes.…”
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    Article
  5. 16745

    Proactive Traffic Information Control in Emergency Evacuation Network by Zhengfeng Huang

    Published 2015-01-01
    “…Generally, the near-future traffic condition is difficult to accurately predict because it is uncertain in evacuation. Assume that the value of traffic information obeys certain distribution within a range, and then real-time traffic information may reflect the most-likely near-future traffic condition. …”
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    Article
  6. 16746

    High Dose Selection for General Toxicity Studies of New Medicines by G. N. Engalycheva, R. D. Subaev

    Published 2023-06-01
    “…It determines the informative value of study results, the compliance with the principles of ethical and rational use of experimental animals, and the accuracy of predicting the safety of new medicines for human use. …”
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    Article
  7. 16747

    Insight into Rotational Effects on a Horizontal Axis Wind Turbine NREL Phase ii Using CFD simulation and inverse BEM by Belamadi Riyadh

    Published 2017-06-01
    “…The comparisons show that CFD results along with the turbulence model can predict the span-wise loading of the wind turbine rotor with reasonable agreement. …”
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    Article
  8. 16748

    Analytical and numerical routes to strong coupling in N $$ \mathcal{N} $$ = 2 SCFTs by Pieter-Jan De Smet, Alessandro Pini, Paolo Vallarino

    Published 2025-07-01
    “…We also outline a numerical algorithm that serves as an independent check of the analytical results and provides predictions in cases where analytical techniques are currently not known.…”
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    Article
  9. 16749

    Neural network analysis of pharyngeal sounds can detect obstructive upper respiratory disease in brachycephalic dogs. by Andrew McDonald, Anurag Agarwal, Ben Williams, Nai-Chieh Liu, Jane Ladlow

    Published 2024-01-01
    “…Evaluated via nested cross validation, the neural network predicts the presence of clinically significant BOAS with an area under the receiving operating characteristic of 0.85, an operating sensitivity of 71% and a specificity of 86%. …”
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    Article
  10. 16750

    Analysis of non-exponential sound decay in an enclosure composed of two connected rectangular subrooms by Mirosław Meissner

    Published 2014-01-01
    “…In this investigation a combination of modal analysis with finite-difference algorithm was used to predict a decay in the sound field energy in an enclosure composed of two connected rectangular subrooms. …”
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    Article
  11. 16751

    The development of the generative adversarial supporting vector machine for molecular property generation by Qing Lu

    Published 2025-07-01
    “…Scientific contribution statement: A generative adversarial algorithm combing supporting vector machine is proposed for the first time to predict molecular properties from scratch, which agrees well with ab initio values. …”
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    Article
  12. 16752

    From phytochemicals to recipes: health indications and culinary uses of herbs and spices by Rishemjit Kaur, Shuchen Zhang, Bhavika Berwal, Sonalika Ray, Ritesh Kumar, Lav R. Varshney

    Published 2025-05-01
    “…Here, we use a network-based approach to elucidate established relationships and predict novel associations between the phytochemicals present in herbs and spices and health indications. …”
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    Article
  13. 16753

    RSCS6D: Keypoint Extraction-Based 6D Pose Estimation by Weiyu Liu, Nan Di

    Published 2025-06-01
    “…Finally, the extracted 3D keypoint cloud is fed into the 6D pose estimation network to predict both translation and rotation.…”
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    Article
  14. 16754

    Application of Data Mining Techniques on Tourist Expenses in Malaysia by Miao Cai, Tan Shi An

    Published 2021-03-01
    “…By apply data mining on tourism data for predicting the area of business opportunity is a good choice. …”
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    Article
  15. 16755

    Effective human–object interaction recognition for edge devices in intelligent space by Haruhiro Ozaki, Dinh Tuan Tran, Joo-Ho Lee

    Published 2024-12-01
    “…Therefore, we propose a novel method that combines the skeletal method with object detection to accurately predict a set of $ \langle $ human, verb, object $ \rangle $ triplets in a video frame considering the robustness, extensibility, and lightweight of the model. …”
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  16. 16756

    Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

    Published 2025-01-01
    “…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. This combined approach was validated on an automotive dataset predicting CO2 emissions from vehicle sensor measurements such as mass air flow, intake pressure, temperature, and speed. …”
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    Article
  17. 16757

    Forecasting Model for Danube River Water Temperature Using Artificial Neural Networks by Cristina-Sorana Ionescu, Ioana Opriș, Daniela-Elena Gogoașe Nistoran, Constantin-Alexandru Baciu

    Published 2025-01-01
    “…Using as input data actual air and water temperatures, and discharge, as well as air temperature data provided by weather forecasts, the ANN model predicts the Danube water temperature one week in advance with a root mean square deviation (RMSE) of 0.954 °C for training and 0.803 °C for testing. …”
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  18. 16758

    Research on a Fusion Technique of YOLOv8-URE-Based 2D Vision and Point Cloud for Robotic Grasping in Stacked Scenarios by Xuhui Ye, Xiaoyang Qin, Leming Zhan, Jun Wang, Yan Chen

    Published 2025-06-01
    “…During point cloud processing, target centers predicted by the detector guide rapid segmentation, followed by robust registration techniques to estimate precise object poses. …”
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    Article
  19. 16759

    Online Calibration of Inertial Sensors Based on Error Backpropagation by Vojtech Simak, Jan Andel, Dusan Nemec, Juraj Kekelak

    Published 2024-11-01
    “…We performed data fusion using an extended Kalman filter (EKF) and calibrated the input sensors through error backpropagation. The algorithm thus calibrates the INS sensors while the GNSS receiver signal is good, and after a GNSS failure, for example in tunnels, the position is predicted only by low-cost inertial sensors. …”
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  20. 16760

    Advanced modeling of salt-inducible kinase (SIK) inhibitors incorporating protein flexibility through molecular dynamics and cross-docking by Jorge Luis Valdés-Albuernes, Erbio Díaz-Pico, Sergio Alfaro, Julio Caballero

    Published 2025-05-01
    “…Our results highlight the importance of protein flexibility in achieving accurate correlations between docking energies and experimental pIC50 values, enhancing inhibitor selectivity predictions.…”
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