Showing 7,101 - 7,120 results of 12,688 for search 'myGrid~', query time: 1.92s Refine Results
  1. 7101

    Simulation study on converter transformer windings stress characteristics under harmonic current and temperature rise effect by Jing Xu, Jian Hao, Ning Zhang, Ruijin Liao, Yun Feng, Wenlong Liao, Huanchao Cheng

    Published 2025-04-01
    “…The results demonstrate that hotspot temperatures on both the grid and valve side windings increase as a power function of harmonic current content and exponentially with frequency. …”
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  2. 7102

    High temperature QDs organization and re-crystallization in glass supported MgO QDs doped PMMA film by Satya Pal Singh, Archana Kumari Singh, Suraj Vishwakarma

    Published 2025-01-01
    “…In contrast, the overall crystallinity of the hybrid film drastically decreases as the formation of boundaries, interfaces, and voids overwhelmed the entire process. …”
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  3. 7103

    Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning by Jakub Horvath, Pavel Jedlicka, Marie Kratka, Zdenek Kubat, Eduard Kejnovsky, Matej Lexa

    Published 2024-12-01
    “…We trained three machine learning models using (i) traditional model ensembles (Gradient Boosting), (ii) hybrid convolutional/long and short memory network models, and (iii) a DNA pre-trained transformer-based model using k-mer sequence representation. …”
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  4. 7104
  5. 7105

    Global-Local Self-Attention-Based Long Short-Term Memory with Optimization Algorithm for Speaker Identification by Pravin Marotrao Ghate, Bhagvat D. Jadhav, Shriram Sadashiv Kulkarni, Pravin Balaso Chopade, Prabhakar N. Kota

    Published 2025-01-01
    “…The GLSA-LSTM with EN-GWO method acquires an accuracy of 99.36% on the TIMIT dataset, and an accuracy of 93.45% on the VoxCeleb 1 datasets, while compared to SincNet and Generative Adversarial Network (SincGAN) and Hybrid Neural Network – Support Vector Machine (NN-SVM). …”
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  6. 7106
  7. 7107

    Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

    Published 2024-12-01
    “…Implications for implementing real-time and context-aware recognition of human emotions based on AI technologies are far-reaching as they demonstrate the potential that hybrid AI systems offer at enhancing emotion deciphering. …”
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  8. 7108
  9. 7109

    Landslide Susceptibility Mapping Using Single Machine Learning Models: A Case Study from Pithoragarh District, India by Trinh Quoc Ngo, Nguyen Duc Dam, Nadhir Al-Ansari, Mahdis Amiri, Tran Van Phong, Indra Prakash, Hiep Van Le, Hanh Bich Thi Nguyen, Binh Thai Pham

    Published 2021-01-01
    “…Single, ensemble, and hybrid machine learning (ML) models have been used in landslide studies for better landslide susceptibility mapping and risk management. …”
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  10. 7110

    Marker-assisted selection in the development of advanced apple-tree forms and donors combining scab resistance with increased fruit storability by I. I. Suprun, E. A. Egorov, A. I. Nasonov, E. V. Lobodina, S. V. Tokmakov, I. V. Stepanov

    Published 2023-10-01
    “…Hence, the development of such cultivars is an important task in modern apple-tree breeding.Materials and methods. A set of 646 hybrid plants obtained in six cross combinations (Renet Simirenko/Modi, Renet Simirenko/Smeralda, Renet Simirenko/Renoir, Renet Simirenko/Fujion, Renoir/Granny Smith, and Modi/Granny Smith) was studied. …”
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  11. 7111
  12. 7112

    Surface Roughness and Color Stability of Conventional and Bulk-Fill Resin Composite with S-PRG Fillers After Coffee Exposure: An in-vitro Study by Janisch FADS, Falcon Aguilar M, Aguiar FHB, França FMG, Basting RT, Vieira-Junior WF

    Published 2025-01-01
    “…Limeira, 901 – Areião, Piracicaba, SP, Brazil, Tel +55 (19) 21065220, Email waljr@unicamp.brObjective: This study aimed to evaluate the in vitro effects of coffee exposure on the color and roughness of conventional and bulk-fill resin composites, with and without surface pre-reacted glass-ionomer (S-PRG) filler.Methodology: Forty-eight cylindrical samples (Ø 6 mm × 2 mm) were prepared and categorized as follows (n = 12 per group): conventional nano-hybrid (Tetric N-Ceram, Ivoclar); nano-hybrid with S-PRG filler (Beautifil II, Shofu); bulk-fill (Tetric N-Ceram Bulk Fill, Ivoclar); and bulk-fill with S-PRG filler (Beautifil Bulk Restorative, Shofu). …”
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  13. 7113
  14. 7114
  15. 7115

    Design of Super Resolution and Fuzzy Deep Learning Architecture for the Classification of Land Cover and Landsliding Using Aerial Remote Sensing Data by Junaid Ali Khan, Muhammad Attique Khan, Mohammed Al-Khalidi, Dina Abdulaziz AlHammadi, Areej Alasiry, Mehrez Marzougui, Yudong Zhang, Faheem Khan

    Published 2025-01-01
    “…The results are compared with state-of-the-art models, such as the hybrid version of VGGNet-16, Yolov4, ResNet-50, DenseNet-121, and other reported techniques. …”
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  16. 7116

    Evaluating pre-processing and deep learning methods in medical imaging: Combined effectiveness across multiple modalities by Thien B. Nguyen-Tat, Tran Quang Hung, Pham Tien Nam, Vuong M. Ngo

    Published 2025-04-01
    “…Our findings show that the Median-Mean Hybrid Filter and Unsharp Masking + Bilateral Filter are the most effective preprocessing methods, achieving an efficiency rate of 87.5%. …”
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  17. 7117

    A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

    Published 2025-01-01
    “…., first-order differentially enhanced two-dimensional correlation spectroscopy (1Der-2DCOS) and two-trace 2DCOS of enhanced filling and milk stages (filling-milk-2T2DCOS)) can effectively and robustly extract spectral trait relationships, with good robustness, and can achieve efficient prediction based on small samples. (3) The hybrid model constrained by the Newton-Raphson-based optimizer’s active learning method can effectively filter localized simulation data and achieve localization of simulation data in different regions when solving practical problems, improving the hybrid model’s prediction accuracy. …”
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  18. 7118
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