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Surveillance of Partially Observable Systems
The Surveillance of Partially Observable Systems is a research method done for the first time by S. Amir Mir M. and Professor Daniel Lane from year 2005 to 2008 at the University of Ottawa, in Canada.

While Mr. Mir was working at the Harvard University, School of Public Health department of Health Policy and Management as a research associate, an opportunity arrived for studying the Axiomatic Design of Complex Systems at the University of Massachusetts Institute of Technology (MIT) in Boston (2009) USA. This opportunity provided Mr. Mir an idea to start a new research based on using the tools and concept of the Axiomatic design on Surveillance of a Complex System, specifically in Surveillance of Partially Observable Systems.

A partially Observable system, unlike a system that clearly displays a full state of its components at any given time, attends to display the invisibility of one or more of its external or internal components at any given time. As technology expends, reliability, performance and safety becomes more and more important. Surveillance of system behavior helps to track hazards and performance. Surveillance is a method used as a tool to help understanding or control the impact of new products or technology. Surveillance is the monitoring of responses and adverse effects. System surveillance is the process of monitoring the performance of objects, a population, or process within a system to understand or to achieve a desired standard of performance. The simplest components of surveillance are observation, examination, analysis and supervision.

The conventional method of Surveillance does not apply for a partially visible system. Therefore a new method is required to observe such complex system at any time given. The Surveillance of a partially observable system offers a mathematical model that uses Markov Chains, paired with a Bayesian updating function. The method estimates the statistical impacts of surveillance observations and modified surveillance policies.

Axiomatic Design for Complex Systems
Axiomatic design is an alternative designing method that has a new perspective and different look into methodology of a system design.

Designing a complex system, interacting with a large number of components with some nonlinear behaviors. It requires a surgical mechanism with a critical care to investigate the relationships between all sub-systems of each part interacting with a larger component.

This method looks into each sub-system to view a larger picture of the main system. It interacts and forming relationships with its environment. The method applies some principles to a number of case studies and industrial examples ranging from large scale systems to nano-scale systems. It could be also used for the designs of the health-care systems.

Fundamental of Design Process
1. Understanding the system's requirements, components, and needs

2. Identifying the input/output of the system, the "problem" needed to be solved for the absolute satisfaction of the system's needs

3. Identifying the functions requirements

4. Mapping of the solutions conception, and the synthesis

5. A task of identifying a method to satisfy different part of system functional requirements

6. Assigning set of inputs for the product design parameters within given constrains

7. Optimization of  the proposed solution using the perform analysis

8. Analyzing the output and checking the final design solution to verify if this solution meets the original system's requirements, components, and needs