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مواقع أعضاء هيئة التدريس

كل ما تحتاجه من أستاذك… في مكان واحد

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Dr.MUSTAFA ELSAYED ABDELSALAM ABOELNOUR

Ph.D. in AI, Faculty of Computers & AI, Cairo University, Egypt. 2015. M.Sc. in AI, Faculty of Computers & Information, Menufia University, Egypt, 2009. B.Sc. of Computer Science, Faculty of Computers & Information, Zagazig University, Egypt, 2003. Associate Professor College of Engineering in Wadi Addawasir
  • Hotta Bane Tameem
  • 011-588-8888
  • m.aboelnour@psau.edu.sa
  • Curriculum Vitae
  • Publications

Publications

  • 1. Salam, M. A., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025). Abstractive text summarization using deep learning models: a survey. International Journal of Data Science and Analytics, 1-29.
  • 2. Salam, M. A., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2025). GRAYSUM: Gray Wolf Optimized Multi-Level Semantic Graph Summarization. Results in Engineering, 107275.
  • 3. Salam, M. A., Abdellatif, A., Abdallah, M., & Salam, N. A. (2025). A Hybrid Deep Learning and Machine Learning Model for Multi-Class Lung Disease Detection in Medical Imaging. International Journal of Intelligent Engineering and Systems, 18(1).
  • 4. Salam, M. A., Aldawsari, M., & Nageh, N. (2025). Bi-objective jellyfish algorithm for team formation problem. Scientific Reports, 15(1), 32417.
  • 5. Salam, M. A., Badr, E., & Elbohoty, A. (2025). Mayfly-based federated learning approach for early detection of fire. International Journal of Data Science and Analytics, 20(8), 7167-7187.
  • 6. Mohamed, M. G., Abdul Salam, M., Sweidan, S., & Hamed, H. F. A. (2025). ACOSUM: Ant Colony Optimized Multi-level Semantic Graph Summarization. International Journal of Applied Intelligent Computing and Informatics, 1(1).
  • 7. Salam, M. A., Aldawsari, M., Gamal, M., Hamed, H. F. A., & Sweidan, S. (2024). Msg-ats: Multi-level semantic graph for arabic text summarization. IEEE Access.
  • 8. Almotairi, S., Badr, E., Abdelbaky, I., Elhakeem, M., & Abdul Salam, M. (2024). Hybrid transformer-CNN model for accurate prediction of peptide hemolytic potential. Scientific Reports, 14(1), 14263.
  • 9. Elminaam, D. S. A., El Tanany, A., Salam, M. A., & El Fattah, M. A. (2024). StockBiLSTM: Utilizing an Efficient Deep Learning Approach for Forecasting Stock Market Time Series Data. International Journal of Advanced Computer Science & Applications, 15(4).
  • 10. Salam, M. A., El-Bably, D. L., Fouad, K. M., & Elsayed, M. S. (2024). Enhancing Fraud Detection in Credit Card Transactions using Optimized Federated Learning Model. International Journal of Advanced Computer Science & Applications, 15(5).
  • 11. Abdul Salam, M., Fouad, K. M., Elbably, D. L., & Elsayed, S. M. (2024). Federated learning model for credit card fraud detection with data balancing techniques. Neural Computing and Applications, 36(11), 6231–6256.
  • 12. Abdelbaky, I., Elhakeem, M., Tayara, H., Badr, E., & Abdul Salam, M. (2024). Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis. BMC bioinformatics, 25(1), 368.
  • 13. Almotairi, S., Badr, E., Salam, M. A., & Dawood, A. (2023). Three chaotic strategies for enhancing the self-adaptive harris hawk optimization algorithm for global optimization. Mathematics, 11(19), 4181.
  • 14. Almotairi, S., Badr, E., Abdul Salam, M., & Ahmed, H. (2023). Breast Cancer Diagnosis Using a Novel Parallel Support Vector Machine with Harris Hawks Optimization. Mathematics, 11(14), 3251.
  • 15. Salam, M. A., Ahmed, N. N., Elshamy, A., Hassan, A. W. S., & Sami, M. (2023). Enhanced Jellyfish Search Optimizer for Collaborative Team Formation in Social Network. International Journal of Intelligent Engineering & Systems, 16(2).
  • 16. Salam, M. A., Taha, S., Alahmady, S., & Mohamed, A. (2023). Predicting Brain Tumor Using Transfer Learning. International Journal of Computer Science & Network Security, 23(5), 73-88.
  • 17. Salam, M. A., Taha, S., & Ramadan, M. (2022). Time series crime prediction using a federated machine learning model. International Journal of Computer Science & Network Security, 22(4), 119-130.
  • 18. Abdul Salam, M., El-Fatah, M. A., & Hassan, N. F. (2022). Automatic grading for Arabic short answer questions using optimized deep learning model. Plos one, 17(8), e0272269.
  • 19. Salam, M. A., Taha, S., & Hamed, M. G. (2022). Advanced framework for automated testing of mobile applications. 2022 4th Novel Intelligent and Leading Emerging Sciences Conference (NILES).
  • 20. Badr, E., Almotairi, S., Salam, M. A., & Ahmed, H. (2022). New sequential and parallel support vector machine with grey wolf optimizer for breast cancer diagnosis. Alexandria Engineering Journal, 61(3), 2520-2534.
  • 21. Salam, M. A., Azar, A. T., & Hussien, R. (2022). Swarm-Based Extreme Learning Machine Models for Global Optimization. Computers, Materials & Continua, 70(3).
  • 22. Salam, M. A., Badr, E., Monier, E., & Mohamed, A. (2022). Schizophrenia diagnosis using optimized federated learning models. IJCSNS, 829.
  • 23. Shehata, A. M., Mohamed, E. M., Salem, K. L., Mohamed, A. M., Salam, M. A., ... (2021). A survey of drowning detection techniques. 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC).
  • 24. Salam, M. A., & Torad, M. A. (2021). An Intelligent Approach for COVID-19 Detection Using Deep Transfer Learning Model. International Journal of Electronics and Information Engineering, 13(2), 66-76.
  • 25. Awad, H. A. M. A. S. A., & Salem, R. (2021). A Novel Intelligent Approach for Dynamic Data Replication in Cloud Environment. IEEE Access, 9(10.1109/ACCESS.2021.3064917), 40240-40254.
  • 26. Badr, E., Abdul Salam, M., Almotairi, S., & Ahmed, H. (2021). From linear programming approach to metaheuristic approach: scaling techniques. Complexity, 2021(1), 9384318.
  • 27. Salam, M. A., & Ali, M. (2021). Optimizing Extreme Learning Machine using GWO Algorithm for Sentiment Analysis. International Journal of Computer Applications, 975, 8887.
  • 28. Salam, M. A., & Azar, A. T. (2021). Optimizing Extreme Learning Machine using Whale Optimization Algorithm for Genes Classification. International Journal of Emerging Trends & Technology in Computer Science.
  • 29. Awad, A., Salem, R., Abdelkader, H., & Salam, M. A. (2021). A Swarm Intelligence-based Approach for Dynamic Data Replication in a Cloud Environment. International Journal of Intelligent Engineering and Systems, 14(2).
  • 30. Torad, M. A., & Salam, M. A. (2021). Smart helmet using internet of things. Int J Reconfigurable & Embedded Syst ISSN 2089 (4864), 4864.
  • 31. Abdul Salam, M., Taha, S., & Ramadan, M. (2021). COVID-19 detection using federated machine learning. PloS one, 16(6), e0252573.
  • 32. Salam, M. A., Ibrahim, L., & Abdelminaam, D. S. (2021). Earthquake Prediction using Hybrid Machine Learning Techniques. International Journal of Advanced Computer Science and Applications (IJACSA).
  • 33. Salam, M. A., Azar, A. T., Elgendy, M. S., & Fouad, K. M. (2021). The Effect of Different Dimensionality Reduction Techniques on Machine Learning Overfitting Problem.
  • 34. Abdel-Kader, H., Abd-El Salam, M., & Mohamed, M. (2020). Hybrid machine learning model for rainfall forecasting. Journal of Intelligent Systems and Internet of Things, 1(1), 5-12.
  • 35. Mustafa, H. S., Abdul Salam, M., Alaa, H., Samir, M., & Tarek, M. (2020). An Intelligent Approach for Detecting Palm Trees Diseases using Image Processing and Machine Learning. International Journal of Advanced Computer Science and Applications, 11(7).
  • 36. Badr, E., Salam, M. A., & Ahmed, H. (2020). The impact of scaling on Support Vector Machine in Breast Cancer Diagnosis. International Journal of Computer Applications, 975, 8887.
  • 37. Eldin, H. A., Waleed, K., Samir, M., Tarek, M., Sobeah, H., & Salam, M. A. (2020). A survey on detection of Red Palm Weevil inside palm trees: Challenges and applications. Proceedings of the 9th International Conference on Software and Information Engineering (ICSIE).
  • 38. Badr, E., Salam, M. A., Ali, M., & Ahmed, H. (2019). Social Media Sentiment Analysis using Machine Learning and Optimization Techniques. International Journal of Computer Applications, 975, 8887.
  • 39. Almestekawy, A., & Abdulsalam, M. (2019). Sentiment analysis of product reviews using bag of words and bag of concepts. International Journal of Electronics and Information Engineering, 11(2), 49-60.
  • 40. Badr, E., & Abdulsalam, M. (2019). Optimizing Support Vector Machine using Gray Wolf Optimizer Algorithm for Breast Cancer Detection.
  • 41. Badr, E., Salam, M. A., & Smarandache, F. (2019). Solving Neutrosophic Linear Programming Problems with Two-Phase Approach.
  • 42. Rashed Salem, A. A., Abdul Salam, M., & Abdel Kader, H. (2019). An Artificial Bee Colony Algorithm for Data Replication Optimization in Cloud Environments. IEEE Access.
  • 43. Salam, M. A., Zawbaa, H. M., Emary, E., Ghany, K. K. A., & Parv, B. (2016). A hybrid dragonfly algorithm with extreme learning machine for prediction. 2016 International symposium on innovations in intelligent systems and applications (INISTA).
  • 44. Emary, E., Zawbaa, H. M., & Salam, M. A. (2017). A proposed whale search algorithm with adaptive random walk. 2017 13th IEEE international conference on intelligent computer communication and processing (ICCP).
  • 45. Hegazy, O., Soliman, O. S., & Salam, M. A. (2015). Comparative study between FPA, BA, MCS, ABC, and PSO algorithms in training and optimizing of LS-SVM for stock market prediction. International Journal of Advanced Computer Research, 5(18), 35-45.
  • 46. Hegazy, O., Soliman, O. S., & Salam, M. A. (2015). FPA-ELM Model for Stock Market Prediction. International Journal of Advanced Research in Computer Science and Software Engineering.
  • 47. Hegazy, O., Soliman, O. S., & Salam, M. A. (2014). A machine learning model for stock market prediction. arXiv preprint arXiv:1402.7351.
  • 48. Hegazy, O., Soliman, O. S., & Salam, M. A. (2014). LSSVM-ABC algorithm for stock price prediction. arXiv preprint arXiv:1402.6366.
  • 49. Abdelsalam, M., Ahmed, H., & Abdulwahed, W. F. (2014). Evaluation of differential evolution and particle swarm optimization algorithms at training of neural network for prediction. IJCI. International Journal of Computers and Information, 3(1), 2-14.
  • 50. Soliman, O. S., & Salam, M. A. (2014). A Hybrid BA-LS-SVM Model and Financial Technical Indicators for Weekly Stock Price and Trend Prediction. International Journal, 4(4).
  • 51. Salam, M. A. (2013). Power quality disturbances in a test distribution system: An overview. Journal of Applied Sciences Research, 9(1), 560-566.
  • 52. Abdul-Kader, H., & Salam, M. A. (2012). Evaluation of Differential Evolution and Particle Swarm Optimization Algorithms at Training of Neural Network for Stock Prediction. Int. Arab. J. e Technol. 2(3), 145-151.
  • 53. Abdul Salam, M, Abdul-Kader, H. M., & Abdel-Wahed, W. F. (2010). Comparative study between differential evolution and particle swarm optimization algorithms in training of feed-forward neural network for stock price prediction. *2010 the 7th international conference on informatics and systems (INFOS), 1-8.

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