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您的检索式：作者名="Mustafa Maha"
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| 1 | Diagnostic Value of Serum Kallikrein-Related Peptidases 6 and 10 Versus CA125 in Ovarian Cancer显示文摘 | Mustafa Abdel Hafiz El Sherbini Maha Mohamed Sallam Emtiaz Abdel Kawy Shaban Amr Hassan El-Shalakany | 2011 | International Journal of Gynecological Cancer2011，，4： | 1 |
| 2 | Applying Non-Local Means Filter on Seismic Exploration显示文摘The seismic reflection method is one of the most important methods in geophysical exploration.There are three stages in a seismic exploration survey:acquisition,processing,and interpretation.This paper focuses on a pre-processing tool,the Non-Local Means(NLM)filter algorithm,which is a powerful technique that can significantly suppress noise in seismic data.However,the domain of the NLM algorithm is the whole dataset and 3D seismic data being very large,often exceeding one terabyte(TB),it is impossible to store all the data in Random Access Memory(RAM).Furthermore,the NLM filter would require a considerably long runtime.These factors make a straightforward implementation of the NLM algorithm on real geophysical exploration data infeasible.This paper redesigned and implemented the NLM filter algorithm to fit the challenges of seismic exploration.The optimized implementation of the NLM filter is capable of processing production-size seismic data on modern clusters and is 87 times faster than the straightforward implementation of NLM. | Mustafa Youldash Saleh Al-Dossary Lama AlDaej Farah AlOtaibi Asma AlDubaikil Noora AlBinali Maha AlGhamdi | 2022 | Computer Systems Science & Engineering2022，40，2： | 0 |
| 3 | Federated Learning with Blockchain Assisted Image Classification for Clustered UAV Networks显示文摘The evolving“Industry 4.0”domain encompasses a collection of future industrial developments with cyber-physical systems(CPS),Internet of things(IoT),big data,cloud computing,etc.Besides,the industrial Internet of things(IIoT)directs data from systems for monitoring and controlling the physical world to the data processing system.A major novelty of the IIoT is the unmanned aerial vehicles(UAVs),which are treated as an efficient remote sensing technique to gather data from large regions.UAVs are commonly employed in the industrial sector to solve several issues and help decision making.But the strict regulations leading to data privacy possibly hinder data sharing across autonomous UAVs.Federated learning(FL)becomes a recent advancement of machine learning(ML)which aims to protect user data.In this aspect,this study designs federated learning with blockchain assisted image classification model for clustered UAV networks(FLBIC-CUAV)on IIoT environment.The proposed FLBIC-CUAV technique involves three major processes namely clustering,blockchain enabled secure communication and FL based image classification.For UAV cluster construction process,beetle swarm optimization(BSO)algorithm with three input parameters is designed to cluster the UAVs for effective communication.In addition,blockchain enabled secure data transmission process take place to transmit the data from UAVs to cloud servers.Finally,the cloud server uses an FL with Residual Network model to carry out the image classification process.A wide range of simulation analyses takes place for ensuring the betterment of the FLBIC-CUAV approach.The experimental outcomes portrayed the betterment of the FLBIC-CUAV approach over the recent state of art methods. | Ibrahim Abunadi Maha M.Althobaiti Fahd N.Al-Wesabi Anwer Mustafa Hilal Mohammad Medani Manar Ahmed Hamza Mohammed Rizwanullah Abu Serwar Zamani | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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