Hyunsung Kim 編集者 at IgMin Research
Our aim is to boost the sharing of ideas across different fields and push the boundaries of current knowledge.
バイオグラフィー
EDUCATION
• Ph.D., Computer Engineering (2002), Kyungpook National University, Daegu, Korea.
Dissertation: Bit-Serial AOP Arithmetic Architecture for Modular Exponentiation
Major Advisor: Dr. Kee-Young Yoo
• M.S., Computer Engineering (1998), Kyungpook National University, Daegu, Korea.
Thesis: Automatic code generation of virtual prototype
Major Advisor: Dr. Kee-Young Yoo
• B.S., Computer Engineering (1996), Kyungil University, Kyungpuk, Korea.
POSITIONS HELD
• Full Professor (2020 - present), School of Computer Science, Kyungil University, Kyungbuk, Korea. Teaching the computer engineering and security related subjects.
• Visiting Professor (2016 - present), Dept. of Mathematical Sciences, University of Malawi, Zomba, Malawi.
Visiting Dr. Levis Eneya.
研究の興味
Information security, cryptography, blockchain, privacy, Internet of things, healthcare security
Editor
仕事内容
Professor
Kyungil University
Department of Computer Engineering
South Korea
0000-0002-7814-7454 Why publish with us?
Global Visibility – Indexed in major databases
Fast Peer Review – Decision within 14–21 days
Open Access – Maximize readership and citation
Multidisciplinary Scope – Biology, Medicine and Engineering
Editorial Board Excellence – Global experts involved
University Library Indexing – Via OCLC
Permanent Archiving – CrossRef DOI
APC – Affordable APCs with discounts
Citation – High Citation Potential
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研究論文
- Lunar-Derived Propellants for Fueling Mars-Bound Spacecraft in Cis-Lunar Space
- Analytical Expressions of the Markov Chain of K-Ras4B Protein within the Catalytic Environment and a New Markov-State Model
- The Cancer Stem Cell Concept as Applied to Prostate Cancer
- Communication Training at Medical School: A Quantitative Analysis
- Immobilization of 7-Iodo-8-hydroxyquinoline-5-sulfonic Acid (Ferron): A Comprehensive Review of Techniques and Applications
- Melanocytic Nevi Classification using Transfer Learning
