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Abstracts

Sheta, A., Elashmawi, W. H., & Othman, E. S. (2026). Smart Agriculture: An Expert System for Tomato Plant Disease Diagnosis. Lect. Notes Networks Syst., 1801 LNNS, 227–240. https://doi.org/10.1007/978-3-032-15784-3_17
Zidan, M., Sheta, A., & Yousef, A. H. (2026). Performance Analysis of Extractive Text Summarization Using Machine Learning. Lect. Notes Networks Syst., 1801 LNNS, 279–295. https://doi.org/10.1007/978-3-032-15784-3_21
Endo, N., Ghezzi, L., Goto, S., Hong, J., Iai, S.-I., Kobayashi, T., Matsuoka, N., & Takahashi, R. (2025). Rings with q-torsionfree canonical modules. De Gruyter Proc. Math., 405–426. https://doi.org/10.1515/9783110999365-014
Hong, J., & Morey, S. (2025). Hilbert coefficients and Sally modules: a survey of Vasconcelos’ contributions. De Gruyter Proc. Math., 97–132. https://doi.org/10.1515/9783110999365-004
Ghezzi, L., & Hong, J. (2025). Degrees: Vasconcelos contributions. De Gruyter Proc. Math., 203–240. https://doi.org/10.1515/9783110999365-006
Sheta, A., Elashmawi, W. H., Surani, S., Baareh, A. K. M., Rauch, P., & Othman, E. S. (2025). ES-SVM Hyperparameter Optimization for Non-Invasive Coronary Heart Disease Classification. Int. Mobile, Intell., Ubiquitous Comput. Conf., MIUCC, 57–62. https://doi.org/10.1109/MIUCC66482.2025.11196848
Brady, S. P., Kang, S. J., Wang, Z. S., Layne, C. D., & Calsbeek, R. (2025). Freshwater Salinization Leads to Sluggish, Bloated Frogs and Small, Cramped Embryos but Adaptive Countergradient Variation in Eggs. Integr. Comp. Biol., 65(2), 285–298. https://doi.org/10.1093/icb/icaf008
Sheta, A., & Elashmawi, W. H. (2025). ANN-MFO: Optimization of Neural Networks for Lipase Activity Modeling in Biotech Applications. Women Bioinform. Workshop, WIBI. 2025 Women in Bioinformatics Workshop, WIBI 2025. https://doi.org/10.1109/WIBI64774.2025.11115204
Sheta, A., Elashmawi, W. H., Karim Baareh, A., Rausch, P., & Othman, E. S. (2025). Medical Image Analysis for Brain Tumor Classification Using CNN Architecture. Proceeding - 12th International Conference on Information Technology: Innovation Technologies, ICIT 2025, 91–98. https://doi.org/10.1109/ICIT64950.2025.11049092
Bandell, J. A., Bunge, R. C., Darrow, B. D., El-Zanati, S. I., Mountain, C. E., & Neiburger, L. (2025). On Tight 6-Cycle Decompositions of Complete 3-Uniform Multi-Hypergraphs. Springer Proceedings in Mathematics and Statistics, 489, 107–121. https://doi.org/10.1007/978-3-031-83864-4_9
Khellaf, L., Djellal, A., Mayache, H., & Sheta, A. (2025). Optimizing MPPT Control of DC-DC Boost Converters Using Metaheuristic Search Algorithms and Nonlinear PID (N-PID) Controllers. In M. Hatti (Ed.), Smart Computing and Control Renewable Energy Systems (pp. 187–195). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-80301-7_21
Kulkarni, A. A., & Vanhamme, J. (2018, May). Induction of Construal-Level Mindset via Experience of Surprise: An Abstract: Proceedings of the 2018 Academy of Marketing Science (AMS) Annual Conference | Request PDF. ResearchGate. https://doi.org/10.1007/978-3-319-99181-8_191

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Zhou, Y., Wu, B., Zhang, L., Zhu, K., Zhang, S., Wang, X., Zhang, C., Liu, C.-H., Yu, X., & Alfano, R. R. (2024). Optical spectroscopic analysis of cerebrospinal fluid of human brain tumor using visible resonance Raman spectroscopy. Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 12836. Scopus. https://doi.org/10.1117/12.3009496
Llanos, N. E., Zhou, Y., Yu, X., Zhang, S., Zhu, K., Liu, C.-H., Wu, B., & Alfano, R. R. (2024). Human glioma tumor diagnosis using visible resonance Raman spectroscopy and deep learning. Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 12839. Scopus. https://doi.org/10.1117/12.3009511
Mai, M., Luo, S., Wang, S., & Pang, Y. (2023). Identification of adipogenic and osteogenic differentiation using transfer learning of ResNet-18. Proceedings - 22nd IEEE International Conference on Machine Learning and Applications, ICMLA 2023, 916–921. Scopus. https://doi.org/10.1109/ICMLA58977.2023.00135
Islam, M. T., Zaky, H., & Alam, T. (2023). Multi-disease Retinal Vessel Segmentation: A Deep Learning Approach. 139–144. Scopus. https://doi.org/10.1109/ICSPIS60075.2023.10343981
Gilbert, N. M., Hamada, R. H. A.-A., Saleh, M., Mohammad, T. I., & Tanvir, A. (2023). Diabetic Macular Edema Detection based on Non-mydriatic Retinal Image. 2023 3rd International Conference on Computing and Information Technology, undefined. https://doi.org/10.1109/iccit58132.2023.10273917
Finch, E. (2023). Experimental Status of the Chiral Magnetic Effect. Epj Web of Conferences, 276, 06018–06018. https://doi.org/10.1051/epjconf/202327606018
Aljahdali, S., Sheta, A., & Turabieh, H. (2020). River Flow Forecasting: A Comparison Between Feedforward and Layered Recurrent Neural Network. In M. Serrhini, C. Silva, & S. Aljahdali (Eds.), Innovation in Information Systems and Technologies to Support Learning Research (pp. 523–532). Springer International Publishing. https://doi.org/10.1007/978-3-030-36778-7_58
Braik, M., Sheta, A., & Aljahdali, S. (2020). Diagnosis of Brain Tumors in MR Images Using Metaheuristic Optimization Algorithms. In M. Serrhini, C. Silva, & S. Aljahdali (Eds.), Innovation in Information Systems and Technologies to Support Learning Research (pp. 603–614). Springer International Publishing. https://doi.org/10.1007/978-3-030-36778-7_66

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Last update from database: 4/24/26, 4:15 PM (UTC)