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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Kalathil FrontInResMetAnal2018 2.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Duncan FrontBioengBiotech2019 7.jpg|240px]]</div>
'''"[[Journal:Application of text analytics to extract and analyze material–application pairs from a large scientific corpus|Application of text analytics to extract and analyze material–application pairs from a large scientific corpus]]"'''
'''"[[Journal:Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system|Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system]]"'''


When assessing the importance of materials (or other components) to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of [[metadata]] analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material–application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. ('''[[Journal:Application of text analytics to extract and analyze material–application pairs from a large scientific corpus|Full article...]]''')<br />
Our national data and infrastructure security issues affecting the “bioeconomy” are evolving rapidly. Simultaneously, the conversation about cybersecurity of the U.S. [[Agriculture industry|food and agricultural system]] (cyber biosecurity) is incomplete and disjointed. The food and agricultural production sectors influence over 20% of the nation's economy ($6.7T) and 15% of U.S. employment (43.3M jobs). The food and agricultural sectors are immensely diverse, and they require advanced technologies and efficiencies that rely on computer technologies, big data, [[Cloud computing|cloud-based]] data storage, and internet accessibility. There is a critical need to safeguard the cyber biosecurity of our bioeconomy, but currently protections are minimal and do not broadly exist across the food and agricultural system. Using the food safety management Hazard Analysis Critical Control Point (HACCP) system concept as an introductory point of reference, we identify important features in broad food and agricultural production and food systems: dairy, food animals, row crops, fruits and vegetables, and environmental resources (water). ('''[[Journal:Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system|Full article...]]''')<br />
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Revision as of 16:29, 20 May 2019

Fig1 Duncan FrontBioengBiotech2019 7.jpg

"Cyberbiosecurity: A new perspective on protecting U.S. food and agricultural system"

Our national data and infrastructure security issues affecting the “bioeconomy” are evolving rapidly. Simultaneously, the conversation about cybersecurity of the U.S. food and agricultural system (cyber biosecurity) is incomplete and disjointed. The food and agricultural production sectors influence over 20% of the nation's economy ($6.7T) and 15% of U.S. employment (43.3M jobs). The food and agricultural sectors are immensely diverse, and they require advanced technologies and efficiencies that rely on computer technologies, big data, cloud-based data storage, and internet accessibility. There is a critical need to safeguard the cyber biosecurity of our bioeconomy, but currently protections are minimal and do not broadly exist across the food and agricultural system. Using the food safety management Hazard Analysis Critical Control Point (HACCP) system concept as an introductory point of reference, we identify important features in broad food and agricultural production and food systems: dairy, food animals, row crops, fruits and vegetables, and environmental resources (water). (Full article...)

Recently featured:

DAQUA-MASS: An ISO 8000-61-based data quality management methodology for sensor data
Security architecture and protocol for trust verifications regarding the integrity of files stored in cloud services
What Is health information quality? Ethical dimension and perception by users