Dr. Vijay Thukral
There are many MBSE tools providing powerful modeling capabilities. Graphical representation and management of various systems views, while essential, is secondary to the underlying need for rigorous application of SE principles to perform needs analysis, concept exploration, concept definition, to product design, integration and deployment.
Patients with chronic disease processes are often malnourished on admission to hospital or health care facilities. As part of introduction to SE and system architecture we examined the needs for malnourished patient care that require short terms and/or long term enteral feeding intervention. Capella/Arcadia, is an open source readily available, powerful MBSE toolset. Capella provides practitioners of SE to do product development guided by SE principles. The tool served as a good introductory toolset for students starting to learn about SE principles and MBSE.
The talk will focus on operational analysis to investigate the interaction between patient and various healthcare entities, define patient nutrition care objectives and conceptualize the functional analysis and logical architecture to manage nutritional care.
Setting Priorities and Finding the Right Balance
Dr. Kim LaScola Needy
To successfully manage one’s career, it is important to set priorities and find the right balance. This seminar will discuss the importance of defining success for yourself, the power of strong support networks, and the necessity of practicing self-renewal. It will also delve into some classic mistakes that one makes with a focus on an academic career. Participants will have an opportunity to reflect upon these topics during the presentation and time will be allotted at the end for discussion.
Seminar Handout: 2021-02-08 - Dr LaScola Needy - Handout
Fuzzy Systems 101
Dr. James C. Bezdek
This talk begins with a discussion of uncertainty in the real world, and how it is modeled in science. Zadeh's 1965 paper is the basis for most of the material in this talk, which evolves using the set-theoretic (as opposed to logic-based) description of fuzzy models. I will spend some time characterizing the mathematical and philosophical differences between the fuzzy and probabilistic approaches to modeling uncertainty. Membership functions are on display, and are seen to be the atomic units of fuzzy models. I will give several examples of finding and using membership functions from real life situations and data sets.