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Assess how intake completion rates impact the efficiency of onboarding patients referred to TMH.

Completed
Current State: Intake Completion Process
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The complex systems model ‘Engagement vs Police Expenditure for Justice Reinvestment in Bourke, NSW’ evaluates the effectiveness of allocating government funding to either community engagement activities or law enforcement. In this model, it is possible for the user to designate resources from a scale of 20-100 and to also modify the crime rate for both adults and youth. Below, there are detailed notes that describe the reasoning and assumptions that justify the logic applied to this model. Similar notes can be found when stocks, flows and variables is clicked under the field ‘notes’.

Portions

Government statistics from the Australian Bureau of Statistics (ABS) show that Bourke Shire Regional Council has approximately 3000 residents, made up of 65-63% adults and 35-37% youths.

Crime Rate

Police variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower crime rate if police expenditure was increased, thus also a higher crime rate if police expenditure was decreased. The figure in the numerator can be changed with the ‘maximum crime rate’ variable which represents the asymptotic crime rate percentage. Where police = 100 the selected crime rate is maximised.

Avoiding Gaol

Originally the formula incorporated the police as a variable, where the total amount of convicted crimes was subtracted from the total amount of crimes committed. However, the constant flow of crimes from repeat offender/a created an unrealistic fluctuation in the simulation. I settled for a constant avoidance rate of 25%. This assumes that an adult or youth committing a crime for the first time is just as likely to avoid conviction as a repeat offender.

Conviction

​It is difficult to predict in a mathematical model how many adults or youths are convicted of crimes they commit. I determined a reasonable guess of maximum 75% conviction rate when Police = 100. In this formula, decreasing police spending equates into decreased conviction rate, which is considered a realistic representation.

Released

​It is assumed that the average sentence for a youth is approximately 6 months detention. For an adult, it will be assumed that the average sentence is 12 months gaol. The discrepancy is due to a few basic considerations that include 1. Adults are more often involved in serious crime which carries a longer sentence 2. youths are convicted with shorter sentences for the same crime, in the hopes that they will have a higher probability of full rehabilitation. 

Engagement

​Rate of adult/youth engagement was estimated to be a linear relation. The maximum rate of engagement, assuming expenditure = 100, is set to 80%. This rate of engagement is a reasonable guess with consideration that there will also exist adults who refused to engage in the community and end up in crime, and adults or youth that refuse to engage in the community or crime. 

Boredom

Engagement Expenditure variable is in the denominator to create a hyperbolic trend. The aim was to achieve a lower boredom rate with a higher engagement expenditure, and thus a higher boredom rate with a lower engagement expenditure. The figure in the numerator of 25 represents the asymptotic boredom rate percentage, where if engagement expenditure = 100 the adult/youth boredom rate is maximised at 25%. 

Assessment #3 Justice Reinvestment in Bourke, NSW 44841396
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Simulation d'un MRU d'un corps qui avance avec une régulation de vitesse réaliste.
Autre version
serie 08a ex4 Une regulation de vitesse plus realiste V2
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We start with an SEIR social virality model and adapt it to model social media adoption of Playcast Hosts.  *Note that this model does not attempt to model WOM emergent virality.  

Social Media Virality
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Simple box model for atmospheric and ocean carbon cycle, with surface and deep water, including DIC system, carbonate alkalinity, weathering, O2, and PO4 feedbacks.
LAB #8: Modern Marine 2-box Carbon Cycle
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Rich picture version of Tanner's Clinical Judgment Model, with the addition of clinical reasoning cycle concepts from T Levett-Jones et al Nurse Education Today 30 (2010) 515-520

Digital Literacy & Electronic Healthcare Record Integration
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Standard Yardstick and Lines
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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.
Fast Fashion ISCI 360 Solutions Final Edit
709
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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! 

 

44911017_Lorenzo_Casaol_MGMT220
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The ecosystem of a game park can be made more realistic by introducing financial allocation for active game park quality upgrades, and to reduce the negative results of a high tourist influx. The total amount of money collected is a variable that is dependent on the number of tourists coming to a park until the number levels off at a state of maximum tourist congestion
A model of management decisions with cash reinvestment
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EK map - Motivation
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This model demonstrates sustainable recycling and the effects it has on the environment as well as us. We modelled this using realistic statistics and estimates from gridwatch.ca and the Ontario Baseline and Waste & Recycling Report (2023). 

[Purple]: Metal demands on a region and the associated environmental and economic factors of production and recycling.

[Pink]: Demand of total residential household and business waste and energy demands on the system.

[Green]: Physical waste produced by human activity in the region.

[Teal]: The outflow of energy produced through waste recycling and its impact of energy production and demand in the region. The Durham-York Energy Center (DYEC) is a facility that combusts garbage into energy which is highlighted in teal, which accumulates with energy produced.

[Orange]: Total energy produced through all means of power generation including modelling of the impact that recycling waste has.

[Yellow]: Carbon emissions of energy generation from energy production methods. (Excluding Wind & Hydro)

Overall, this model examines and compares waste accumulation to energy production and the release of emissions.
scenario 1
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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
Kanban Board Simulation - WIP Limit, Tameflow Kanban Token and Drum-Buffer-Rope
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Diagrams modified from article
Urban renewal and health inequality
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Based on the Market and Price simulation model in System Zoo 3, Z504. In this model the profit calculations were not realistic. They were based on the per unit profit, which does not take items not sold into account. Also the model was not very clear on profit since it was included in the total production costs and consequently in the unit costs and subsequently profit was calculated by subtracting unit costs of the market price. Thus profit had a double layer which does not make the model better accessible. I have tried to remedy both in this simplified version.
Simplified and changed Z504 Market and Price - System Zoo 3
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We start with an SEIR social virality model and adapt it to model social media adoption of Playcast Hosts.  *Note that this model does not attempt to model WOM emergent virality.  

Social Media Virality3
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This simulation makes the negative effects of starting work too soon visible. You can play around with the parameters.

Find the full story behind this simulation here

If you have questions or feedback get in touch via @swilluda
[Published] Effect of starting work too soon
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Having ADHD makes life difficult.
There are some types of job that having ADHD makes it extremely difficult to be successful and effective.
Consulting Engineering is one of those.
Being a Consultant Engineer requires mastery of lots of skills - technical skills as well as life skills. The higher levels of rank in the profession requires mastery of more life skills than lower ranks. Having ADHD makes is exceedingly difficult or impossible to master those skills and therefore perform effectively at or above certain levels of rank and responsibility.
ADHD and Consulting Engineering
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Summary of Ray Pawson's Book The Science of Evaluation: A Realist Manifesto See also lse review
Clone of The Science of Evaluation
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This version of the CAPABILITY DEMONSTRATION model has been further calibrated (additional calibration phases will occur as better standardized data becomes available).  Note that the net causal interactions have been effectively captured in a very scoped and/or simplified format.  Relative magnitudes and durations of impact remain in need of further data & adjustment (calibration). In the interests of maintaining steady progress and respecting budget & time constraints, significant simplifying assumptions have been made: assumptions that mitigate both completeness & accuracy of the outputs.  This model meets the criteria for a Capability demonstration model, but should not be taken as complete or realistic in terms of specific magnitudes of effect or sufficient build out of causal dynamics.  Rather, the model demonstrates the interplay of a minimum set of causal forces on a net student progress construct -- as informed and extrapolated from the non-causal research literature.
Provided further interest and funding, this  basic capability model may further de-abstracted and built out to: higher provenance levels -- coupled with increased factorization, rigorous causal inclusion and improved parameterization.
Version 6A NULL PRACTICE Student-Home-Teachers-Classroom
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This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies. 

Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining policy by changing the settings below.  First explore changing the start date with a policy duration of 60 days.
SIRD Epidemic Model with Suppression Policies
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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
https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

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:
  1. http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
  2. https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model
Clone of Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death
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WIP to explain iterative modelling of linkages over space and time see also causal pathways IM
Clone of Linkages among objects
5 months ago
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Model of the autonomi network economics
autonomi