Publications

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2024
Abbas, S., M. Abu Talib, Q. Nasir, S. Idhis, M. Alaboudi, and A. MohameD, "Radio frequency fingerprinting techniques for device identification: a survey", International Journal of Information Security, vol. 23, issue 2: Springer Berlin Heidelberg, pp. 1389-1427, 2024. Abstract
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2023
Nabeeh, N. A., K. M. Sallam, and A. W. Mohamed, "An electric vehicle analysis model for sustainable environment in devoicing nationals", Neutrosophic systems with applications, vol. 6, pp. 1-8, 2023. Abstract
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Mohamed, S., H. A. A. Nomer, R. Yousri, A. W. Mohamed, A. Soltan, and S. M. Darweesh, "Energy management for wearable medical devices based on gaining–sharing knowledge algorithm", Complex & Intelligent Systems, vol. 9, issue 6: Springer International Publishing Cham, pp. 6797-6811, 2023. Abstract
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Ganesh, N., S. Jayalakshmi, R. C. Narayanan, M. Mahdal, H. M. Zawbaa, and A. W. Mohamed, "Gated deep reinforcement learning with red deer optimization for medical image classification", IEEE Access, vol. 11: IEEE, pp. 58982-58993, 2023. Abstract
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Nadakinamani, R. G., A. Reyana, Y. Gupta, S. Kautish, S. Ghorashi, M. M. Jamjoom, and A. W. Mohamed, "High-performance association rule mining: Mortality prediction model for cardiovascular patients with COVID-19 patterns", Alexandria Engineering Journal, vol. 71: Elsevier, pp. 347-354, 2023. Abstract
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2022
Nabeeh, N. A., A. Abdel-Monem, M. Mohamed, K. M. Sallam, M. Abdel-Basset, M. El-Abd, and A. Wagdy, "A comparative analysis for a novel hybrid methodology using neutrosophic theory with MCDM for Manufacture selection", 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): IEEE, pp. 1-8, 2022. Abstract
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Nabeeh, N. A., M. Mohamed, A. Abdel-Monem, M. Abdel-Basset, K. M. Sallam, M. El-Abd, and A. Wagdy, "A Neutrosophic Evaluation Model for Blockchain Technology in Supply Chain Management", 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE): IEEE, pp. 1-8, 2022. Abstract
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Tawfik, R. M., H. A. A. Nomer, S. M. Darweesh, A. W. Mohame, and H. Mostafa, "UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm.", Computers, Materials & Continua, vol. 72, issue 3, 2022. Abstract
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Tawfik, R. M., H. A. A. Nomer, M. Saeed Darweesh, A. W. Mohamed, and H. Mostafa, "UAV-Assisted IoT Data Collection Optimization Using Gaining-Sharing Knowledge Algorithm", Handbook of Nature-Inspired Optimization Algorithms: The State of the Art: Volume II: Solving Constrained Single Objective Real-Parameter Optimization Problems: Springer International Publishing Cham, pp. 135-146, 2022. Abstract
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Nadakinamani, R. G., A. Reyana, S. Kautish, A. S. Vibith, Y. Gupta, S. F. Abdelwahab, and A. W. Mohamed, "[Retracted] Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques", Computational intelligence and neuroscience, vol. 2022, issue 1: Hindawi, pp. 2973324, 2022. Abstract
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Nadakinamani, R. G., A. Reyana, S. Kautish, A. S. Vibith, Y. Gupta, S. F. Abdelwahab, and A. W. Mohamed, "[Retracted] Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques", Computational intelligence and neuroscience, vol. 2022, issue 1: Hindawi, pp. 2973324, 2022. Abstract
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2021
Hassan, S. A., P. Agrawal, T. Ganesh, and A. W. Mohamed, "A Travelling Disinfection-Man Problem (TDP) for COVID-19: A Nonlinear Binary Constrained Gaining-Sharing Knowledge-Based Optimization Algorithm", Intelligent Data Analysis for COVID-19 Pandemic, Singapore, Springer Singapore, pp. 291 - 318, 2021. Abstract

An improved scheduling the disinfection process of the new coronavirus (COVID-19) is introduced. The scheduling aims at achieving the best utilization of the available day time, which is calculated as the total disinfection time minus the total loss travelling time. In this regard, a new application problem is presented, which is called a travelling disinfection-man problem (TDP). The new problem (TDP) in network optimization resemble somehow the famous travelling salesman problems (TSP) but with basic distinct variations where a disinfection group is likely to select a route to reach a subset of predetermined places to be disinfected with the most utilization of the available day working hours. A nonlinear binary model is introduced with a detailed real application case study involving the improving the scheduling of coronavirus disinfection process for five contaminated faculties in Ain Shams University in Cairo, and the case study is solved using a novel discrete binary gaining-sharing knowledge-based optimization algorithm (DBGSK).

Navarro, D. A. O., S. A. Hassan, and A. MohameD, Artificial Intelligence for COVID-19, : Springer, 2021. Abstract
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Nomer, H. A. A., A. W. Mohamed, and A. H. Yousef, "GSK-RL: Adaptive gaining-sharing knowledge algorithm using reinforcement learning", 2021 3rd Novel Intelligent and Leading Emerging Sciences Conference (NILES): IEEE, pp. 169-174, 2021. Abstract
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2020
Nomer, H. A. A., K. A. Alnowibet, A. Elsayed, and A. W. Mohamed, "Neural Knapsack: A Neural Network Based Solver for the Knapsack Problem", IEEE Access, vol. 8, pp. 224200 - 224210, 2020. Abstract
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Nomer, H. A. A., K. A. Alnowibet, A. Elsayed, and A. W. Mohamed, "Neural knapsack: a neural network based solver for the knapsack problem", IEEE access, vol. 8: IEEE, pp. 224200-224210, 2020. Abstract
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2015
El-Quliti, S. A., A. H. M. Ragab, R. Abdelaal, A. W. Mohamed, A. S. Mashat, A. Y. Noaman, and A. H. Altalhi, "A Nonlinear Goal Programming Model for University Admission Capacity Planning with Modified Differential Evolution Algorithm", Mathematical Problems in Engineering, vol. 2015: Hindawi Publishing Corporation, pp. 892937, 2015. AbstractWebsite

This paper proposes a nonlinear Goal Programming Model (GPM) for solving the problem of admission capacity planning in academic universities. Many factors of university admission capacity planning have been taken into consideration among which are number of admitted students in the past years, total population in the country, number of graduates from secondary schools, desired ratios of specific specialties, faculty-to-students ratio, and the past number of graduates. The proposed model is general and has been tested at King Abdulaziz University (KAU) in the Kingdom of Saudi Arabia, where the work aims to achieve the key objectives of a five-year development plan in addition to a 25-year future plan (AAFAQ) for universities education in the Kingdom. Based on the results of this test, the proposed GPM with a modified differential evolution algorithm has approved an ability to solve general admission capacity planning problem in terms of high quality, rapid convergence speed, efficiency, and robustness.

El-Quliti, S. A., A. H. M. Ragab, R. Abdelaal, A. W. Mohamed, A. S. Mashat, A. Y. Noaman, and A. H. Altalhi, "A nonlinear goal programming model for university admission capacity planning with modified differential evolution algorithm", Mathematical Problems in Engineering, vol. 2015: https://doi.org/10.1155/2015/892937, pp. 13, 2015. Abstract
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El-Quliti, S. A., A. H. M. Ragab, R. Abdelaal, A. W. Mohamed, A. S. Mashat, A. Y. Noaman, and A. H. Altalhi, Research Article A Nonlinear Goal Programming Model for University Admission Capacity Planning with Modified Differential Evolution Algorithm, , 2015. Abstract
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