MHC 6306 W2 Assignment Final Project

MHC 6306 W2 Assignment Final Project

MHC 6306 W2 Assignment Final Project


Described how major healthcare laws impact staffing and fulfilling of the position.

Explained the legal and ethical responsibilities of staffing this position.

Described the safety and security issues related to the position.

Explained the five chosen healthcare laws that impact the position.

Described the legal issues that apply to staffing the position.

Explained the ethical issues that apply to staffing the position.

NURS 6051 Discussion The Inclusion of Nurses in the Systems Development Life Cycle Sample
MHC 6306 W2 Assignment Final Project

Presented a structured document free of spelling and grammatical errors.

Properly cited sources in APA format.

The objective of the final project is to explore topics in decision making under uncertainty in greater depth than is permitted in class. The choice of topic is up to you, but it should be related to the general themes of the course. As part of the project you should:

  • describe an approach (existing or newly developed),
  • apply the approach to a problem of interest (which may or may not be related to aerospace), and
  • analyze the performance of the approach according to a set of metrics.

MHC 6306 W2 Assignment Final Project

Your topic may be related to your graduate research or another class project (so long as permission is granted by the instructor of your other class); however, you must make the relationship to your other work clear in your proposal and final paper and describe how you have extended this research for this class.

Your final project may be done in any programming language, and you may use any libraries or software available to you. If you have difficulty finding an appropriate topic, feel free to talk with the course staff during office hours or post to Piazza. Example problem domains can be found here:

  • RL Competition
  • International Planning Competition
  • POMDP File Repository
  • Approximate POMDP Planning Toolkit Repository
  • BNLearn Bayesian Network Repository

As all research projects will be graded with the same standard regardless of the number of people in the group, you are encouraged to work in groups of 2-3 with everyone in the group taking the same number of units (unless prior approval from the instructor is given). You can still choose to work individually if you want to.

When working in groups, please clearly detail the contributions of the individual group members.

You are welcome to refer to past project titles.

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