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Biography
Islam S. Fathi is a researcher and teaching assistant in the Department of Information Systems at Al Alson Higher Institute, Cairo, Egypt. His academic background includes a bachelor's degree in computer science and operations research from the Faculty of Science, Cairo University, and a master's degree in expert systems from the same institution. He is currently pursuing a Ph.D. in computer science at Zagazig University.
His research interests encompass signal processing, metaheuristic optimization, and bioinformatics. He has co-authored several publications, including a study on an energy-efficient compression algorithm for ECG signals in remote healthcare monitoring systems. Additionally, he has collaborated with Nabila H. Shikoun on the development of the Improved Energy Valley Optimizer with Levy Flight for optimization problems, a metaheuristic algorithm designed to solve complex optimization challenges.
Al Alson Higher Institute, established in 1992 by Dr. Hassan Azazy, is one of Egypt's first private institutes. It offers bachelor's degrees in various fields, including computer and information technology, tourism and hotels, and business and sales management. The institute aims to provide high-quality education and prepare graduates for successful careers in their respective fields.
Through his work, Islam S. Fathi contributes to advancements in the fields of information systems and optimization, particularly in applications related to healthcare and computational intelligence.
Research Interest
Islam S. Fathi's research interests focus on areas within computer science and information systems, with a particular emphasis on signal processing, metaheuristic optimization, and bioinformatics. He is deeply engaged in exploring innovative methods for improving computational efficiency and performance in complex systems. His work includes the development of energy-efficient algorithms, particularly for remote healthcare monitoring systems, with applications in medical signal processing. He is also interested in the application of metaheuristic algorithms to solve optimization problems, contributing to the development of the Improved Energy Valley Optimizer with Levy Flight, a novel optimization technique. Fathi's research aims to address challenges in areas such as data compression, algorithmic efficiency, and problem-solving techniques for large-scale, complex systems. His work has the potential to impact fields such as healthcare, bioinformatics, and computer science by providing solutions that enhance computational performance and resource optimization.
Open Access Policy refers to a set of principles and guidelines aimed at providing unrestricted access to scholarly research and literature. It promotes the free availability and unrestricted use of research outputs, enabling researchers, students, and the general public to access, read, download, and distribute scholarly articles without financial or legal barriers. In this response, I will provide you with an overview of the history and latest resolutions related to Open Access Policy.
Energy Valley Optimizer (EVO) is one of the recent metaheuristic algorithms. It draws inspiration from advanced principles in physics related to particle stability and decay modes. This paper presents a new Energy Valley Optimizer (EVO) and levy flights that are hybrid to improve the EVO in solving optimization problems. Levy flight is one of the most important randomization techniques. Fifteen mathematical test functions (five unimodal functions, four multimodal functions, and six composite functions) are solved with the proposed algorithm. We... also compare our results with previous results of metaheuristic algorithms. The statistical results show that the results of the Levy Energy Valley Optimizer (LEVO) outperform other algorithms in almost all mathematical test functions.
https://orcid.org/0000-0002-8207-4702 
