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  1. Transforming Human Resource Management: The Impact of Artificial Intelligence on Recruitment and Beyond.Hazem A. S. Alrakhawi, Randa Elqassas, Mohammed M. Elsobeihi, Basel Habil, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):1-5.
    Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data privacy, (...)
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  2.  57
    Convergence of Nanotechnology and Artificial Intelligence: Revolutionizing Healthcare and Beyond.Randa Elqassas, Hazem A. S. Alrakhawi, Mohammed M. Elsobeihi, Basel Habil, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Engineering Research (IJAER) 8 (10):25-30.
    Abstract: The convergence of nanotechnology and artificial intelligence (AI) represents a transformative frontier in modern science, with the potential to revolutionize multiple industries, particularly healthcare. Nanotechnology enables the manipulation of matter at the atomic and molecular scale, while AI offers sophisticated data analysis, pattern recognition, and decision-making capabilities. This paper explores the synergies between these two fields, focusing on their impact on medical diagnostics, targeted drug delivery, and personalized treatments. By leveraging AI's predictive power and nanotechnology's precision, healthcare can achieve (...)
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  3. Suggestions to Enhance the Scholarly Search Engine: Google Scholar.Ibrahim M. Nasser, Mohammed M. Elsobeihi & Samy S. Abu Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):11-16.
    The scholarly search engine Google Scholar (G.S.) has problems that make it not a 100% trusted search engine. In this research, we discussed a few drawbacks that we noticed in Google Scholar, one of them is related to how does it perform (add articles) option for adding new articles that are related to the registered researchers. Our suggestion is an attempt for making G.S. more efficient by improving the searching method that it uses and finally having trusted statistical results.
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