Big Data in Manufacturing, Biology, Healthcare and Life Sciences
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".
Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 59250
Special Issue Editors
Interests: AI; big data; virtualization; shipbuilding industry; shipping industry; Industry 4.0
Special Issues, Collections and Topics in MDPI journals
Interests: data analysis; artificial intelligence; software engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
An individual’s genetic information amounts to just about 3 MB (megabytes), and the genetic information of the global population could reach up to 24 billion MB. The necessity of a Big Data processing system that can handle such a volume is clear, and the future of life science research depends on acquiring or developing such a system. This Special Issue aims to collect research and discussion on Big Data processing systems in the field of bioinformatics or biostatics, which involves visualization of life science Big Data using IRB-approved Big Data processing methodologies and visualization techniques.
This Special Issue will also present studies discussing how to apply these methodologies to understand the issues involved with diverse social phenomena or businesses.
For example, the paradigms of shipbuilding and shipping industries are shifting to the design and manufacture of autonomous surface ships. A (whole) life-cycle smartification is increasingly adopted in these industries, and yet a variety of accidents or problems (DNA analysis for the identification of fatal accidents in shipbuilding; environmental pollution from ballast water; environmental pollution and protection; safety and protection in the manufacturing industry; healthcare) occurring in shipbuilding or operation processes remain to be solved. Additionally, most of the data such as wind directions or wave heights are being utilized for the operation of ship prediction systems, but the lack of available real-time data needed to compensate or correct prediction results has to be dealt with, especially when it is necessary to perform digital forensics.
In this regard, this Special Issue attempts to focus on the generation and construction of Big Data to take initiative in the development of advanced detection equipment/systems, tools/materials, and intelligent systems and deal with international standards, expecting to lay a foundation for the commercialization of autonomous surface ships.
Topics of interested include but are not limited to:
- Big Data in Manufacturing.
- Big Data in Biology.
- Big Data in Healthcare.
- Big Data in Life Sciences.
- Generation and construction of Big Data to take initiative in the development of advanced detection equipment/systems, tools/materials, and intelligent systems in response to international standards.
- Classification of Big Data Sets into ‘Big Data Collection’ and ‘Analyzed Data’, standardization and quality test techniques.
- Collection and analysis of the Big Data that can correct positions or predict marine accidents in addition to the conditions of shipbuilding materials based on the database constructed.
- Establishment of Big Data generation, analysis, and distribution plans considering the life cycle of data.
- Establishment of a ground for data fusion between the data platforms to be linked together after constructing a system for data generation, analysis, and distribution.
- Ethical solutions to artificial intelligence and Big Data.
Prof. Dr. Jun-Ho Huh
Prof. Dr. Yeong-Seok Seo
Guest Editors
Manuscript Submission Information
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