Insight diagram
Improvement Science as one of the clusters of interacting methods for improving health services network design and delivery using complex decision technologies IM-17952
Improvement Science
Insight diagram
A launchpad to tie together some ideas about Reality. See wikipedia
Reality
3 months ago
Insight diagram
Allison Zembrodt's Model

This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

equations I used in kill rate :

power model - 12*0.1251361120909615*([Moose]/[Wolves])^.44491970277839954*[Wolves]


Kill rate sqrt = 12*(0.0933207+.0873463*([Moose]/[Wolves])^.5)*[Wolves]


Holling Type III - ((0.986198*([Moose]/[Wolves])^2)/ (601.468 +([Moose]/[Wolves])^2))*[Wolves]*12


linear - 12*[Wolves]*(.400271+.00560299([Moose]/[Wolves]))


Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Insight diagram

IM-1175 with computable arguments, based on ideas from Micropublications paper about Claims, Evidence, Representations and Context Networks

Toulmin's Argument Model and Micropublications
Insight diagram
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Insight diagram
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Insight diagram
MAST 610_Homework 1: More Realistic Covid Model
Insight diagram
Final Group Formula 1 Model
Insight diagram
This is a clone of "Fast Fashion ISCI 360 Solutions Final submission" created by user "V B" which we are using as the foundation for an exercise in the DTU course 12100 "Quantitative sustainability".

The model takes into account clothing production and textile waste on a global scale while incorporating Vancouver's own "Fast Fashion" issue into the model.

Please refer to the notes for each variable and stock to see which links were hidden from the model.

Part 2: Our solution for the issue surrounding "Fast Fashion" focuses on increasing individuals education about sustainability and how they can help reduce negative impacts on the environment by shopping less, recycling and donating. This effect of education on sustainability is seen in the "Online Shopping" equation where the impact of "Education on Sustainability" is increased by x1.5 which impacts the entire model. Furthermore, components of the feedback loop on the right are also influenced by increasing education on sustainability and thus, those values were altered accordingly. These values were chosen arbitrarily by taking into account that doubling any value is not realistic so the change should be between x1.0 and x2.0.
Clone of Fast Fashion ISCI 360 Solutions Final Edit
575 2 months ago
Insight diagram
2f. [thought question] Is it possible for r maxrmax to be positive and yet for the total regional abundance to exhibit a persistent declining trend? Explain your reasoning, using at least one biologically realistic example. You can use the agent-based metapopulation model in InsightMaker to help test your ideas, but this is not required.
NRES 470 Lab 6, 2b
Insight diagram

About the Model

This model is designed to simulate the youth population in Bourke, specifically focusing on the number of criminals and incarcerated dependent on a few key variables.

Within the model, a young person living in Bourke can be classified as being in any of five states:

Young Community Member: The portion of the youth population that is not committing crime and will not commit crime in the future. Essentially the well behaved youths. A percentage of these youths will become alienated and at risk.

Alienated and At Risk Youths: The youths of Bourke that are on the path of becoming criminals, this could be caused by disruptive home lives, alcohol and drug problems, and peer pressure, among other things.

Criminal: The youths of Bourke who are committing crimes. Of these criminals a percentage will be caught and convicted and become imprisoned, while the remainder will either go back to being at risk and commit more crimes, or change their behaviour and go back to being a behaving community member.

Imprisoned: The youths of Bourke who are currently serving time in a juvenile detention centre. Half of the imprisoned are released every period at a delay of 6 months.

Released: Those youths that have been released from a detention centre. All released youths either rehabilitate and go back to being a community member or are likely to re-offend and become an alienated and at risk youth.

The variables used in the model are:

Police- This determines the police expenditure in Bourke, which relates to the number of police officers, the investment in surveillance methods and investment in criminal investigations. The level of expenditure effects how many youths are becoming criminals and how many are being caught. An increase in police expenditure causes an increase in imprisoned youths and a decrease in criminals.

Community Engagement Programs- The level of investment in community engagement programs that are targeted to keep youths in Bourke from becoming criminals. The programs include sporting facilities and clubs, educational seminars, mentoring programs and driving lessons. Increasing the expenditure in community engagement programs causes more young community members and less criminals and at risk youths.

Community Service Programs- The level of investment in community service programs that are provided for youths released from juvenile detention to help them rehabilitate and reintegrate back into the community. An increase in community service expenditure leads to more released prisoners going back into the community, rather than continuing to be at risk. Since community service programs are giving back to the community, the model also shows that an increase in expenditure causes a decrease in the amount of at risk youths.

All three of these variables are adjustable. The number of variables has been kept at three in order to ensure the simulation runs smoothly at all times without complicated outputs, limitations have also been set on how the variables can be adjusted as the simulation does not act the same out of these boundaries.

Key Assumptions:

The model does not account for the youths’ memory or learning.

There is no differentiation in the type of criminals and the sentences they serve. Realistically, not all crimes would justify juvenile detention and some crimes would actually have a longer than six-month sentence.

The constants within in the calculations of the model have been chosen arbitrarily and should be adjusted based on actual Bourke population data if this model were to be a realistic representation of Bourke’s population.

The model assumes that there are no other factors affecting youth crime and imprisonment in Bourke.

There are 1500 youths in Bourke. At the beginning of the simulation:

Young Community Member = 700

Alienated and At Risk Youth = 300

Criminal = 300

Imprisoned = 200

Noteworthy observations:

Raising Police expenditure has a very minimal effect on the number of at risk youths. This can be clearly seen by raising Police expenditure to the maximum of twenty and leaving the other two variables at a minimum. The number of Alienated and at Risk Youths is significantly higher than the other states.

Leaving Police expenditure at the minimum of one and increasing community development programs and community service programs to their maximum values shows that, in this model, crime can be decreased to nearly zero through community initiatives alone.

Leaving all the variables at the minimum position results in a relatively large amount of crime, a very low amount of imprisoned youth, and a very large proportion of the population alienated and at risk.

An ideal and more realistic simulation can be found by using the settings: Police = 12, Community Engagement Programs = 14, Community Service Programs = 10. This results in a large proportion of the population being young community members and relatively low amounts of criminals and imprisoned.



Bourke Justice Reinvestment - Nicholas Hayward 44553625
Insight diagram
A combination of qualitative and quantitative methods for implementing a systems approach, including virtual intervention experiments using computer simulation models. See also Complex Decision Technologies IM
Interventions and leverage points added in IM-1400 (complex!) 
Systems Methods
Insight diagram

Modified from Sterman (2006) article and Gene Bellinger's Assumptions IM-351 by Dr Rosemarie Sadsad UNSW See also Complex Decision Technologies IM and IM-63975

Virtual Experiments
3 11 months ago
Insight diagram
Realistic_WolvesMoose
Insight diagram
Attempts to model in the social dynamics of  Pavilion host aquisition
Pavilion Model
Insight diagram
Summary mostly of Cheryl Misak's 2004 Book Truth and the End of Inquiry: A Peircean Account of Truth
See also broader history of Pragmatism insight, mostly  from Cheryl Misak's other works and reviews

Peirce Truth and the End of Inquiry
Insight diagram
PlayCast Analytics
Insight diagram
This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process. The simulation is described in the blog post "Starting late - The Superior Scheduling Approach - How, despite being identical, one company delivers almost 10 times the value of its competitor using flow-oriented project initiation."

By adjusting the slider below you can observe the work process 
  • without any work in process limitations (WIP Limits), 
  • with process step specific WIP Limits* (work state WIP limits), 
  • with Kanban Token and Replenishment Token based on the Tameflow approach (a form of drum-buffer-rope) 
  • with Drum Buffer Rope** scheduling method. 
* Well know in (agile) Kanban
** Known in the physical world of factory production

The simulation and the comparison between the different scheduling approaches can be seen here -> https://youtu.be/xXvdVkxeMMQ

The "Tameflow approach" using Kanban Token and Replenishment Token as well as the Drum Buffer Rope method take the Constraint (the weakest link of the work process) into consideration when pulling in new work items into the delivery "system". 

Feel free to play around and recognize the different effects of work scheduling methods. 

If you have questions or feedback get in touch via twitter @swilluda

The work flow itself
Look at the simulation as if you would look on a kanban board

The simulation mimics a "typical" feature delivery process on portfolio level. 

From left to right you find the following ten process steps. 
  1. Ideas
  2. Selected ideas (waiting)
  3. Initiate and pitch
  4. Waiting for preparation
  5. Prepare
  6. Waiting for delivery
  7. Deliver
  8. Waiting for closure
  9. Close and communicate
  10. Closed
[Published] Simulation Starting late  -  The Superior Scheduling Approach (simplified version)
Insight diagram
The model is designed to provide a general understanding of the wear and tear on roads or a community's circulation system as a result of vehicle traffic generated by development within and outside of a community. It is not based on realistic assumptions regarding those impacts, it simply attempts to convey the flow of influence.

The imaginary city has a set area of roads measured in linear yards (width of roads is ignored) and an assumed number of vehicles on those roads set at 30,000 (per day). With those assumptions the wear and tear requiring repair is .02 or 2% Vehicle wear based on the 30,000 per year. There is also a calculated replacement cost of an additional 3% plus through vehicle wear or 5% per year.  An increase in vehicles increases this vehicle wear impact exponentially. The model assumes that there will not be less than 30,000 vehicles.

Expenditures for repair or replacement are set to balance out on an as needed based on 30,000 vehicles. An minimum additional 50 cars from external sources is then assumed. Adding New Homes and/or New Businesses places an even greater burden on the circulation system. 

The model does not consider additional funding. This will be added as a political factor but would need to consider the possibility of decreasing funding for other purposes.

Future additions to the model will include an inflation factor. Unfunded road work will get increasingly more expensive over time. Also a diminished revenue factor. A lack of capacity of the community's roads could likely result in a diminishment of the community's business sector thus reducing sales and property taxes and municipal revenue to expend on the roads. 
Calculating Road Wear and Tear on Community Roads
Insight diagram
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

We incorporate logistic growth into the moose dynamics, and we replace the death flow of the moose with a kill rate modeled from the kill rate data found on the Isle Royale website.

I start with these parameters:
Wolf Death Rate = 0.15
Wolf Birth Rate = 0.0187963
Moose Birth Rate = 0.4
Carrying Capacity = 2000
Initial Moose: 563
Initial Wolves: 20

I used RK-4 with step-size 0.1, from 1959 for 60 years.

The moose birth flow is logistic, MBR*M*(1-M/K)
Moose death flow is Kill Rate (in Moose/Year)
Wolf birth flow is WBR*Kill Rate (in Wolves/Year)
Wolf death flow is WDR*W

Clone of Final Midterm Student version of A More Realistic Model of Isle Royale: Predator Prey Interactions
Insight diagram
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.
A More Realistic Model of Isle Royale: Predator Prey Interactions
Insight diagram
This model illustrates predator prey interactions using real-life data of wolf and moose populations on the Isle Royale.

Experiment with adjusting the initial number of moose and wolves on the island.
Parker Realistic Isle Royale: Predator Prey Interactions
Insight diagram
based on Kolb 2005 article and 1984 publication on Experiential Learning and Pepper World Hypotheses via John Barton. See also The Art of the State IM  and Social Relations Worldviews IM  and The Educated Mind IM
The Structure of Learning and Knowledge
3 months ago
Insight diagram

Clone of IM-806 modified to integrate AnyLogic Real world, Model World with Van de Ven Engaged Scholarship and Land Use Modelling approaches. See also Complex Decision Technologies IM

Real World and Model World
11 months ago