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  • 标题:Real-Time, On-Site, Machine Learning Identification Methodology of Intrinsic Human Cancers Based on Infra-Red Spectral Analysis - Clinical Results
  • 本地全文:下载
  • 作者:Yaniv Cohen ; Arkadi Zilberman ; Ben Zion Dekel
  • 期刊名称:Journal of Systemics, Cybernetics and Informatics
  • 印刷版ISSN:1690-4532
  • 电子版ISSN:1690-4524
  • 出版年度:2020
  • 卷号:18
  • 期号:2
  • 页码:37-43
  • 出版社:International Institute of Informatics and Cybernetics
  • 摘要:This paper posits a smart ecosystem as a complex system with several interdependent components or subsystems Natural environment, smart city, smart buildings, smart office, smart manufacturing, smart life. Understanding, design, and operation of such a system can be supported by a comprehensive ontology. We introduce the structure of ontologies as consisting of a schema-level ontology, and entity-value-level ontologies, for each entity type a taxonomy of entity values. One can developing a comprehensive ontology by collecting and integrating specifications from many sources; we illustrate this process by building a very preliminary taxonomy of (smart) ecosystem functions from seven sources. Making ecosystems smart can improve the quality of life and contribute to more sustainable communities.
  • 关键词:Machine learning; FTIR; ATR; Stomach cancer and Colorectal cancer.
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