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!) 
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!) 
Inference Robustness Assessment entails demonstrating that  the ways a model differs from the real world do not affect model based inferences.  From Jim Koopman's work on Infection Transmission Science esp  Biological Networks Book  Ch 13 p 453-4 and this accessible  paper  pdf
Inference Robustness Assessment entails demonstrating that the ways a model differs from the real world do not affect model based inferences. From Jim Koopman's work on Infection Transmission Science esp Biological Networks Book Ch 13 p 453-4 and this accessible paper pdf
  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 C

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.



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

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

9 months ago
In this model we seek to show how Formula 1 can bring there Co2 emissions down to zero by 2030 (six years from now).
In this model we seek to show how Formula 1 can bring there Co2 emissions down to zero by 2030 (six years from now).
11 months ago
WIP integration of dynamic and complexity insights using rubik's cube metaphor from Pop Health Book  insight  folders,  and others linked in notes
WIP integration of dynamic and complexity insights using rubik's cube metaphor from Pop Health Book insight folders,  and others linked in notes
This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process.   By adjusting the sliders below you can    observe the work process  without  any work in process limitations ( WIP Limits ),   with process step specific WIP Limits* (
This simulation allows you to compare different approaches to influence flow, the Flow Times and the throughput of a work process.

By adjusting the sliders 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), 
  • or you may want to see the impact of the Tameflow approach with Kanban Token and Replenishment Token 
  • or see the impact of the Drum-Buffer-Rope** method. 
* Well know in (agile) Kanban
** Known in the physical world of factory production

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

You can also simulate the effects of PUSH instead of PULL. 

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" software delivery process. 

From left to right you find the following ten process steps. 
  1. Input Queue (Backlog)
  2. Selected for work (waiting for analysis or work break down)
  3. Analyse, break down and understand
  4. Waiting for development
  5. In development
  6. Waiting for review
  7. In review
  8. Waiting for deployment
  9. In deployment
  10. Done
 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
 Documentation       The Insight shown demonstrates how demand and supply in a real estate market can affect pricing.      Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased.      Linkin
Documentation

The Insight shown demonstrates how demand and supply in a real estate market can affect pricing. 

Demand, Supply and Price have been represented by stocks. Each has an inflow where it has an increase in stock, and a corresponding outflow where stock is decreased. 

Linking each stock and flow is a variable that changes that which it is linked to. These have been labelled appropriately. Each variable takes a decimal value and multiplies it with that it is linked to, such as the rate of demand affecting the price set as 0.001*Demand. This is to generate the loops required to show the rise and fall in price, demand and supply.

Adjustments can be made to the price, supply and demand stocks to simulate different scenarios. Price can be between 400 (400,000) and 1000 (1,000,000) in accordance to average housing prices. Demand and supply can be between 0 (0%) and 100 (100%), although having these set as realistic figures will demonstrate the simulation best. 

Each simulation can be focused on how either demand and price interact over time or supply and price. These are shown in different tabs. 

When the simulation is carried out, the way in which demand and supply rates affect pricing can be seen. Demand and supply are shown with price following shortly after with a slight delay, since changes in market behavior does not immediately affect prices of housing. 

It should also be noted that the lines that represent each stock do not directly reflect the prices of housing in reality. Prices do not fluctuate so rapidly from 400 to near 0 like they do on the graph, however these are just representations of the interactions between each stock in a marketplace.
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.
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.
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
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

9 months ago
 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

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

3 8 months ago
 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
WIP Summary of recent IEEE Computer graphics article  (abstract)  which could be applied to almost any chronic persistent health or social problem
WIP Summary of recent IEEE Computer graphics article (abstract) which could be applied to almost any chronic persistent health or social problem
  Details:   <!--[if !supportLists]-->-         
<!--[endif]-->This
model shows the effect of ‘reinvestment program ‘or the expenditure on policing
and community development affects the cycles of petty-crime and youth
detention, and domestic violence and jail.  More details:   <!--[if

Details:

<!--[if !supportLists]-->-          <!--[endif]-->This model shows the effect of ‘reinvestment program ‘or the expenditure on policing and community development affects the cycles of petty-crime and youth detention, and domestic violence and jail.

More details:

<!--[if !supportLists]-->-          <!--[endif]--> Bourke is a town of 3000 people in the North West of New South Wales, about 750Km from Sydney. See the map: https://goo.gl/maps/VgNqgMNzJ7H2. It’s nowhere and there’s not much to do there if you’re young. So, a lot of kids get into mischief, and a lot of adult’s drink. Sometimes they’re violent.

 

<!--[if !supportLists]-->-          <!--[endif]-->http://www.justreinvest.org.au/justice-reinvestment-in-bourke/

Assumption:

<!--[if !supportLists]-->·       <!--[endif]-->Bourke Funding consist of Law enforcement funding and Community Development funding only

<!--[if !supportLists]-->o   <!--[endif]-->Bourke budget only has $400,000

<!--[if !supportLists]-->·       <!--[endif]-->Juvenile detention stay last for 6 months

<!--[if !supportLists]-->·       <!--[endif]-->There is only 2 options as a Youth, commit petty crime or engage in Youth development programs

<!--[if !supportLists]-->·       <!--[endif]-->1 unit of Police, Juvenile and Educational program HR and Equipment is = 0.25

<!--[if !supportLists]-->o   <!--[endif]-->1 unit increase results in an 0.25 effectiveness increase

<!--[if !supportLists]-->·       <!--[endif]-->Sport clubs, educational programs and social programs are comprised into Youth Development Program as 1 stock.

<!--[if !supportLists]-->·       <!--[endif]-->Juvenile support relies on encouraging youth who are in detention centers to join youth development programs, if not they will reoffend.

Stocks:

<!--[if !supportLists]-->o   <!--[endif]-->Home

<!--[if !supportLists]-->o   <!--[endif]-->Youth Development program

<!--[if !supportLists]-->o   <!--[endif]-->Discharged

<!--[if !supportLists]-->o   <!--[endif]-->Juvenile detention center

<!--[if !supportLists]-->o   <!--[endif]-->Petty Crime

Variable:

<!--[if !supportLists]-->·       <!--[endif]-->Reinvestment Allocation – ranges from 0 – 1 , law enforcement investment allocation is 1 – reinvestment allocation. Slide the slider through 0 to 1 to change the reinvestment allocation by 10% l

<!--[if !supportLists]-->·       <!--[endif]-->Bourke funding budget is fixed to make it seem more realistic (imagine employing a whole army of teachers or police, it wouldn’t make sense)

<!--[if !supportLists]-->·       <!--[endif]-->Youth Population varies , from 1000 to 10,000 for realism along with its time period (4 years). Slider the the slider to increase or decrease the population by 1,000s

Juvenile support effectiveness rate, Youth development program effectiveness rate, conviction rate, Police HR/ equipment, Juvenile Support HR/ equipment, Youth Development program HR/ equipment

Interrelationship and reinforcing loops

<!--[if !supportLists]-->·       <!--[endif]-->The youth population starts as as Neutral (Home) then leans towards alienation and connectedness

<!--[if !supportLists]-->·       <!--[endif]-->Alienation Reinforcing Loop -  Alienation has Conviction rate as a factor as conviction rate increase Alienation increase. This is because as youths get arrested, meaning they’ll have to stay in Detention centers, their friends are more likely to follow on due to them getting ‘bored’.

<!--[if !supportLists]-->·       <!--[endif]-->Connectedness Reinforcing Loop - The opposite exist with Connectedness, as educational program effectiveness increase so as Connectedness. This follows onto the same assumption that youth will always follow peer pressure. The more friends they have in the program, the more likely they will join aswell.

 

Analysis:

<!--[if !supportLists]-->1.       <!--[endif]-->Which loop is the youth in?

<!--[if !supportLists]-->·       <!--[endif]-->Once the allocation slider is used with its minimum or maximum value, the loop at which majority of the youth population is ‘stuck in’ becomes obvious. E.g. Once allocation = 1, the entire youth is stuck between educational program and their home, showing the effectiveness of community development funding. On the other hand, once allocation = 0, the entire youth loops around from doing Petty Crimes, spending their time in Juvenile detention centers, then getting discharged to only commit petty crimes again.

<!--[if !supportLists]-->2.       <!--[endif]-->Alienation vs. Connectedness

<!--[if !supportLists]-->·       <!--[endif]-->Set the allocation slider on 0.8, The massive difference between the youth of population feeling connected with their community and youth being alienated can be seen. The increase in Reinvestment, the increase in connectedness. Try the extremes as well, 100% reinvestment funding results in 0 Alienation rate.

<!--[if !supportLists]-->3.       <!--[endif]--> What is the Youth Engaged in ? Educational Programs or Petty Crime ?

<!--[if !supportLists]-->·       <!--[endif]-->Leaving the slider on 0.8, it can be seen that the there are more youth engaged into educational programs than petty crime. This shows that reinvestment and petty crime has a negative relationship .

<!--[if !supportLists]-->4.       <!--[endif]-->More police = safer ?

<!--[if !supportLists]-->-          <!--[endif]-->Set the slider on 0.1 , it can be seen that Conviction which has police as a factor is positively correlated to Crime. This means that an increase in conviction rate is equivalent to more youth being alienated and committing crime. Therefore, more police less safer.

 Have fun! 

 

 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

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

8 months ago
This model simulates the tradeoff between the total costs and total benefits of using AI. The model shows the investment rate in comparison to the effectiveness and efficiency rate of the AI and we can visualize this relationship with our graph to see the cost and benefits of AI.
This model simulates the tradeoff between the total costs and total benefits of using AI. The model shows the investment rate in comparison to the effectiveness and efficiency rate of the AI and we can visualize this relationship with our graph to see the cost and benefits of AI.
 Peircean process approach to Causation from Menno Hulswit's  article . See also Peirce thought  insight  

Peircean process approach to Causation from Menno Hulswit's article. See also Peirce thought insight 

11 months ago