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Artificial Intelligence Based Journal. Promote the knowledge of different areas of computing, machine learning, Computing etc
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Knovell.org’s mission is to provide a dynamic and user-friendly digital platform that delivers timely, reliable, and relevant content to readers worldwide. We are dedicated to supporting authors, researchers, and thought leaders by fostering a collaborative environment that promotes knowledge exchange, academic excellence, and innovation across diverse fields.
Machines and Algorithms (MnA)
Machines and Algorithms is a peer-reviewed, open-access scientific journal in the domain of Computer Science and related disciplines. The journal publishes various types of articles, including original research, short communications, review articles, case studies, and invited commentaries. All submitted articles should report original, previously unpublished research results, experimental or theoretical. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing. Machines and Algorithms encourage authors of original research papers to describe work such as the following:
- Articles in the areas of computational approaches, artificial intelligence, big data, software engineering, cybersecurity, internet of things, and data analysis.
- Reports substantive results on a wide range of learning methods applied to a variety of learning problems.
- Articles provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena.
- Articles that respond to a need in medicine, or rare data analysis with novel methods.
- Articles that involve healthcare professional’s motivation for the work and evolutionary results are usually necessary.
- Articles show how to apply learning methods to solve important application problems.
Machines and Algorithms (MnA) accepts interdisciplinary field that studies and pursues the effective uses of computational and biomedical data, information, and knowledge for scientific inquiry, problem-solving, and decision making, motivated by efforts to improve human health. Novel high performance computing methods, big data analysis, and artificial intelligence that advance material technologies are especially welcome.
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