2022 IMS Virtual Distinguished Lecturer Webinars
The IEEE IMS Virtual Distinguished Lecturer Webinars allows us to continue providing IMS members with our respected and reputable Distinguished Lecturer program during this time of limited travel. Registration is completely free and limited to the first 100 registrants per event. In the case you are unable to register, you can also attend the webinar concurrently via Facebook Live, or access the webinar recording following the event.
Webinars are 60-minutes long, including 15 minutes for Q&A. We are thrilled to offer you the opportunity to attend these webinars, and we encourage your participation!
Questions? Contact us at: (Click to show email).
Medicine 4.0: When New Technologies Work with A.I. (Student/Ph.D. Edition)
About Prof. Pasero's Webinar
This is a version of Dr. Pasero's IMS Distinguished Lecture aimed at Undergraduate, Graduate, and Ph.D. Students who are interested in learning more about AI in Medicine.
Industry 4.0 is considered the great revolution of the past few years. New technologies, the Internet of things, and the possibility to monitor everything from everywhere changed both plants and the approaches to industrial production. Medicine is considered a slowly changing discipline. The human body model is a difficult concept to develop. But we can identify some passages in which medicine can be compared to industry. Four major changes revolutionized medicine:
- Medicine 1.0: James Watson and Francis Crick described the structure of DNA. This was the beginning of research in the field of molecular and cellular biology
- Medicine 2.0: Sequencing the Human genome. This discovery made it possible to find the origin of the diseases.
- Medicine 3.0: The convergence of biology and engineering. Now the biologist’s experience can be combined with the technology of the engineers. New approaches to new forms of analysis can be used.
- Medicine 4.0: Digitalization of Medicine: IOT devices and techniques, AI to perform analyses, Machine Learning for diagnoses, Brain-Computer Interface, Smart wearable sensors.
Multiphase Flow Measurement and Combustion Process Monitoring through Data-Driven Modelling
About Prof. Yan's Webinar
Over the past ten years, various machine learning techniques have been incorporated into a range of measurement systems for multiphase flow measurement and combustion process monitoring. Such techniques in conjunction with low-cost sensors and sensor arrays provide either unique solutions to some measurement challenges or offer more cost-effective or complementary options to other possible methods. The established or potential applications of machine learning in measurement and instrumentation appear wide-ranging, but the underlining principle, advantages, and limitations are similar. This presentation will review recent advances in the applications of data-driven modeling techniques to the measurement of gas-liquid, gas-solids, and liquid-solids mixture flows and the advanced monitoring of combustion processes. These include the mass flow rate measurement of air-oil two-phase flow, carbon dioxide two-phase flow, slurry flow, and pneumatically conveyed pulverized fuel in a range of industrial sectors. Meanwhile, systems that incorporate machine learning algorithms for the online continuous identification of pulverized fuel, burner condition monitoring, and combustion plant optimization will be introduced. Results from recent experimental programs and trials on industrial-scale test plants will be reported.