Ahmed Sherif

h-index13
2papers
800citations

2 Papers

1.2TOSep 17, 2025
Imaging Modalities-Based Classification for Lung Cancer Detection

Sajim Ahmed, Muhammad Zain Chaudhary, Muhammad Zohaib Chaudhary et al.

Lung cancer continues to be the predominant cause of cancer-related mortality globally. This review analyzes various approaches, including advanced image processing methods, focusing on their efficacy in interpreting CT scans, chest radiographs, and biological markers. Notably, we identify critical gaps in the previous surveys, including the need for robust models that can generalize across diverse populations and imaging modalities. This comprehensive synthesis aims to serve as a foundational resource for researchers and clinicians, guiding future efforts toward more accurate and efficient lung cancer detection. Key findings reveal that 3D CNN architectures integrated with CT scans achieve the most superior performances, yet challenges such as high false positives, dataset variability, and computational complexity persist across modalities.

14.8CRMay 12, 2019
Privacy-Preserving and Collusion-Resistant Charging Coordination Schemes for Smart Grid

Mohamed Baza, Marbin Pazos-Revilla, Mahmoud Nabil et al.

Energy storage units (ESUs) including EVs and home batteries enable several attractive features of the modern smart grids such as effective demand response and reduced electric bills. However, uncoordinated charging of ESUs stresses the power system. In this paper, we propose privacy-preserving and collusion-resistant charging coordination centralized and decentralized schemes for the smart grid. The centralized scheme is used in case of robust communication infrastructure that connects the ESUs to the utility, while the decentralized scheme is useful in case of infrastructure not available or costly. In the centralized scheme, each energy storage unit should acquire anonymous tokens from a charging controller (CC) to send multiple charging requests to the CC via the aggregator. CC can use the charging requests to enough data to run the charging coordination scheme, but it cannot link the data to particular ESUs or reveal any private information. Our centralized scheme uses a modified knapsack problem formulation technique to maximize the amount of power delivered to the ESUs before the charging requests expire without exceeding the available maximum charging capacity. In the decentralized scheme, several ESUs run the scheme in a distributed way with no need to aggregator or CC. One ESU is selected as a head node that should decrypt the ciphertext of the aggregated messages of the ESUs' messages and broadcast it to the community while not revealing the ESUs' individual charging demands. Then, ESUs can coordinate charging requests based on the aggregated charging demand while not exceeding the maximum charging capacity. Extensive experiments and simulations are conducted to demonstrate that our schemes are efficient and secure against various attacks, and can preserve ESU owner's privacy.