Shao-Wen Hung 編集者 at IgMin Research
We strive to bridge scientific disciplines to stimulate collaborative growth and knowledge sharing.
バイオグラフィー
Dr. Shao-Wen Hung is a veterinarian, researcher, and chief of the animal industry division. He is actively engaged in academic research in Taiwan, including cancer medicine, animal welfare, veterinary medicine, and fish disease. He has participated in research on antibacterial light-emitting diodes and the application and development of the Raman rapid detection method.
He has published more than 120 journal papers, 130 conference papers, 12 patents, and 20 books. He has also served as a journal peer reviewer. Dr. Hung has successfully assisted animal drug factories and food factories to obtain animal drug and health food certificates.
研究の興味
Cancer medicine, Veterinary medicine, Animal welfare.
Editor
仕事内容
Senior Researcher with Chief
Agricultural Technology Research Institute
Division of Animal Industry, Animal Technology Research Center
Taiwan
トピック分野別の貢献
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
- Deep Learning-based Multi-class Three-dimensional (3-D) Object Classification using Phase-only Digital Holographic Information
- Contribution to the Knowledge of Ground Beetles (Coleoptera: Carabidae) from Pakistan
- Problem of Surface Waves on Water in Higher School Laboratory Workshop
- Risks and Effects of Medicinal Plants as an Adjuvant Treatment in Mental Disorders during Pregnancy
- Efficacy of Different Concentrations of Insect Growth Regulators (IGRs) on Maize Stem Borer Infestation
- Analytical Expressions of the Markov Chain of K-Ras4B Protein within the Catalytic Environment and a New Markov-State Model
