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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

Maurice Lee

3

Simulation d'un MRU d'un corps qui avance avec une régulation de vitesse réaliste.

serie 08 ex4 Une regulation de vitesse plus realiste V1

lydia tolis

MODEL EXPLANATION:

This model simulates possible crime patterns among the youth population of Bourke, where levels of alienation, policing and community engagement expenditure can be manipulated. Here the youth in Bourke have a minimum percentage of interest to participate in community activities in which the government aims to improve their lifestyle and therefore reduce the rate of criminal activity. ASSUMPTIONS:There are 1500 youths of Bourke in the population susceptible to committing crime and simulations of criminal tendencies are only based the factors presented, no external influences.
VARIABLES:“Alienation” includes any factors that can increase the likelihood of youths to commit crime such as exposure to domestic violence, household income, education level, and family background‘Community engagement Expenditure’ is the total monies budgeted into community activities to develop youths in and out of Juvenile detention‘Policing’ is the amount of police placed onto patrol in the town of Bourke to reinforce safety and that the law is abided by. STOCKS:Conviction rate is set to 60%A juvenile detention sentence for convicted criminals is set to 3 monthsThe top 30% of the most severe offenders are sent to rehabilitation for 3 months, to which they return to Bourke, assumingly in a better state and less likely to repeat a petty crimeCommunity activities are set to last for 3 months to align with the seasons: these could be sporting clubs or youth groupsCommunity participants have a 20% chance of being disengaged as it may not align with their interestsInvestments into policing are felt immediately& community engagement expenditure has a delay of 3 months
INTERESTING FINDS:1. Alienation set to max (0.2), policing and community engagement set to minimum shows a simulation whereby all criminals are in town rather than being expedited and placed into juvenile detention, even after a base value of 200 youths placed into juvenile detention – this shows that budget is required to control the overwhelming number of criminal youths as they overrun Bourke2. Set community activity to 0.01, policing to max & Alienation to max. A lack of community activity can produce high disengagement amongst youths regardless of police enforcement to the town of Bourke that has a high criminal rate. Juvenile detention only lasts for so long and not all youths can be rehabilitated, so they are released back into Bourke with chances of re-committing crime. 3. Alienation plays a major role in affecting youths to consider committing crime. To keep criminal activity to a minimum, ideally the maximum rates of budget in policing and community engagement within youths highly at risk of committing crime should be pushed. Realistically, budget is a sensitive case within a small town and may not be practical. 4. Set policing to 0.25, community engagement to 0.2 & alienation to 0.04. Moderate expenditure to community activities and policing can produce high engagement rates and improved youths in the town of Bourke.

MGT563 (11605457) - Crime, Policing & Community Development in Bourke

Lisa Ma

5

Model of the autonomi network economics

autonomi

Christian

2 months ago

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

Allison Zembrodt

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.

Input Queue (Backlog)
Selected for work (waiting for analysis or work break down)
Analyse, break down and understand
Waiting for development
In development
Waiting for review
In review
Waiting for deployment
In deployment
Done

[Archive] Kanban Board Simulation - WIP Limit, Tameflow Kanban Token and Drum-Buffer-Rope

Stefan Willuda

14

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

Bernard2018

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

Ashley Morris

5 7 months ago

There has been an ongoing effort to find a means of making systems thinking accessible and readily adopted by others not familiar with systems thinking. One line of thinking places a good deal of the blame on systems thinkers themselves, the problem is that they have not found a good enough method of explaining it and its benefits yet.

Another possibility though is the extent to which those who are to be helped feel besieged by the situation in which they find themselves making them extremely wary about trying something new.

This model is not realistic, at least it is hoped that there isn't anyplace where things are this bad. Different communities will be better or worse off in different categories and some will be succeeding in all areas. Those are the communities we need to learn from.

More explanation can be found under the information icons associated with each of the elements.

Complexity, Corruption and False Complacency assailing our Communities

Brian Dowling

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

V B

40

plus realiste

mru 4(1)

Daniel Pinto Teixeira

5

Test model to decribe weight loss by reduced calorie intake through 5:2 fasting

Test model 5:2 fast PJK

Pieter-Jan Klok

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 8: Calibrated Student-Home-Teachers-Classroom-LEA-Spending

Yolande Tra

25

Book summary WIP

The Economics of JK Galbraith

Geoff McDonnell

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.

Model OTHER: All Components Added + Spending to Performance

Robert L. Brown

Standard Yardstick and Lines

Hydra Of Lerna

This map is a WIP derived from the MIT D-memo 4641 presentation by Nelson Repenning 1996 and the paper "Nobody Ever Gets Credit for Fixing Problems that Never Happened: Creating and Sustaining Process Improvement" by Nelson P. Repenning and John D Sterman. http://bit.ly/jCXGKL See Insight 9781 for a simulation of this model. This map adds additional features mentioned in the article to the bare bones simulation in IM-9781

The Improvement Paradox Map WIP

Geoff McDonnell

5

BSRD model 3.0.1

Adam Bouche

8

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

David Lusseau

34 last month

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.

Input Queue (Backlog)
Selected for work (waiting for analysis or work break down)
Analyse, break down and understand
Waiting for development
In development
Waiting for review
In review
Waiting for deployment
In deployment
Done

Kanban Board Simulation - WIP Limit, Tameflow Kanban Token and Drum-Buffer-Rope

Stefan Willuda

10

Assignment 3 MGMT220
**Scroll down for adjustable sliders**

What is this model?

This model is designed as a simplified field of inputs and outputs for the proposed future justice reinvestment in the north-western NSW town of Bourke. This town is quite small with a total population of around 3,000 people but a worryingly high rate of criminal activity, antisocial behaviour and a generally low sense of community engagement. To plan for a better future this model has been created to map future patterns and changes given certain levels of community investment and policing which can me modified by users, including you!

Key Assumptions & Things to Note:
-Model interactions and consequences only focused on the effects of youth not adults.
-Total youth population assumed to be 1,500 out of the total 3,000 people in Bourke
-Model moves in monthly increments
-Model duration is 5 years (60 Months) as this seems like a realistic time frame for such a project plan to span over
-Engagement return modification allows between 0 and 6 months return to allow insight into the positive effects a shorter engagement time can have on the community
-Police Investment allows adjustment of police force units between 15 and 50
-Community Investment allows an investment of between 0 and 100 to provide a full spectrum of the town with or without investment

Model Prerequisite Understandings:
The model commences with 400 people engaging in criminal activity, and a further 300 people already in juvenile detention to provide a more realistic start point.

Model Analysis:
The most important message this model shows is that there is no one sided solution for everything. Without community investment, regardless of how many police you have the town is still going to be full of bored people committing crimes - just more will be caught and convicted.

On the flip side a town with no police and only community investment may have a low rate of people in juvenile detention and a high number of people in sports teams - but criminal activity may still be higher than optimal due to a low chance of getting caught.

You can see these results for yourselves simply by adjusting the variable sliders on the bottom right of the page to suit your investment interests. Relevant boundaries have been set to give only useful and meaningful information. Furthermore an engagement return tool has been added to show the effects of a slow or fast engagement pickup time ranging from 0 to 6 months. You will note that things change a lot quicker with a shorter engagement return time.

An interesting thing to note is how evenly 3 of the 4 key data fields in the first simulation display (with the outlier being sports team enrolment) when police investment is set to maximum and community investment is set to the minimum - we see essentially an even split between the 3 possibilities: In town, In Juvenile Detention or engaging in Criminal Activity. a 2:1 split of "bad" to "good" things happening. This shows with certainty that just adding policing with no positive reward or outlet for good behaviour results in a flattened cycle of boredom, criminal activity and conviction.

In this model it also seems that Bourke does require a fairly even but high matching of Police and Community Investment. For example setting the policing at 20 and the community engagement higher at say 50 results in indeed a high intake and output of town to sports team memberships however crime rates do still maintain a steady high dictating a more even match between policing and community investment like 40 and 60 to the former and latter to "eradicate" crime. (Of course this will never be 0 in the real world but it is a positive indicator here)

Justice Reinvestment in Bourke | A3 MGMT220 43832512

Alex O'Donnell

Summary of Ch 22 of Mitchell Wray and Watts Textbook see IM-164967 for book overview

Fiscal Space and Fiscal Sustainability

Geoff McDonnell

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 for more information and to see which links were hidden from the model.

Fast Fashion ISCI 360 Solutions Final Submission

V B

3

This model depicts the complex relationships between crime, number of police, investment in community development programs and the youth population of the small country town, Bourke.

In this system dynamics model, the user can observe how modifying the spending on community development programs and changing the number of police in the town affects the crime rate and the engagement of youth.

These variables can be altered using the sliders which are provided underneath the notes. The model runs for a period of 5 years. This was deemed the optimal time during which any generational changes could be observed.

The model is explained with more detail below, along with any assumptions and their appropriate reasoning.

Variables

Investment in Community Development Programs

It is assumed that the minimum that can be invested is $1000 and the maximum is $100 000.

Number of Police

It is assumed that the minimum number of police officers that can be present in Bourke is 10 and the maximum is 100.

Stocks and Flows

Bourke Population

The population of Bourke is set as 3000 as stated in the Justice Reinvestment document.

Boredom and lack of opportunity leads to

This flow is given the equation: (50000/[Investment in Community Development Programs])* 2. The greater the investment in community development programs, the lesser the number of youths who are bored.

Disengaged and Alienated Youth

Since there are not many activities for young adults (as stated in the Justice Reinvestment document), it is assumed that they are all currently disengaged and alienated. The disengaged and alienated youth population of Bourke is thus set as 1000 before the model is run.

Petty Crime

Since the youth crime rate for Bourke is quite high, it was assumed that 800 out of the 1000 youth would engage in petty crime. This is before any additions to the police force or increase in community development programs investment.

Commit

This flow is dependent on both the number of disengaged youth and the number of police. The more police that are present in Bourke, the more disengaged the youth become. This ensures that the level of petty crime committed is directly related to the number of police officers.

Convicted

This flow is given a constant rate of 7*[Number of Police] + (0.1*[Petty Crime]). This means that the greater the number of police officers present, the greater the number of convictions. It also means that at the highest number of police officers available (100), the highest the number of convictions is 700 + 10% of youths who commit a crime. Since the model assumes that there are 800 youths committing crime at the beginning of the models’ commencement, it realistically represents the police’s inability to catch ALL criminals.

Not Convicted

This flow has the equation ([Petty Crime]/[Number of Police])*2. Since the number of police is in the denominator, the lower the number, the higher the number of delinquents who are not convicted. This attempts to keep the model realistic. At the maximum level of 100 police officers, there will still remain some delinquents who escape conviction and this remains true to life.

Lesson Learnt

Since youth crime is so rife in Bourke, it is assumed that only 20% of offenders in the juvenile detention centre learn their lesson and never commit crime again. This was done to simplify the modelling.

Still Disenchanted

It is assumed that 80% of offenders do not learn their lesson after their time in the juvenile detention centre.

Feel Estranged

This flow is given the equation: [Number of Police]*5 + 50/([Investment in Community Development Programs]/1000).

Thus, the higher the number of police, the greater the number of youths who feel estranged. The greater the investment in community development programs, the lesser the number of youths who feel estranged.

Participate and engage in

This flow is dependent on the level of investment in community development programs. The greater the investment, the greater the participation. This is realistic as the more money is spent on such programs, the more interested that youths will be in participating.

Develop Inter-community relationships

It is estimated that the majority of youths who participate in community development programs will develop inter-community relationships. This model assumes that such programs will be largely successful in encouraging social harmony amongst the youths.

Relapse

However, youths participating in the community development programs may relapse and head back into the path of crime. However, this is assumed to only be a small minority (1/8 of those who participate).

Interesting Observations

1) Number of Police: 10 (minimum)

Investment in Community Development Programs: $1000 (minimum)

It is important to note that even the minimal amount of investment in community development programs is enough to cause the crime rate to decrease, to the point where, after 3 years, there are more youths who are Reformed and Engaged than those involved in Petty Crime. However, the number of youths who are Reformed decreases after some time, indicating greater investment is needed. Somewhat surprisingly, the number of youths who are involved in the community development programs is at its highest, further suggesting the need for increased investment.

2) Number of Police: 100 (maximum)

Investment in Community Development Programs: $1000 (minimum)

Predictably, Petty Crime has drastically decreased, and in a much shorter time than when there were only 10 police officers. The number of youths who are Reformed and Engaged and those who are involved in the Community Development Programs has also increased, but they are not as high as in the previous observation, most likely due to increased alienation caused by the high police presence.

3) Number of Police: 10 (minimum)

Investment in Community Development Programs: $100 000(maximum)

Quite surprisingly, Petty Crime has decreased drastically, despite the low number of police officers present in Bourke. This shows that the large sums of money being invested in the Community Development Programs has created a social change within the town’s youth population with high numbers of youths participating in these programs and thus becoming Reformed and Engaged. Another interesting aspect is that while the number of youths participating in the programs reduces to zero at the end of the fifth year, the number of youths who are Reformed and Engaged is at an all time high.

4) Number of Police: 100 (maximum)

Investment in Community Development Programs: $100 000 (maximum)

While Petty Crime has decreased significantly, the number of youths who are Reformed and Engaged and those who participate in Community Development Programs is not as high as Scenario 3. Extremely large numbers of youths are also spending time in the Juvenile Detention Centre during the first 2 years of the 5-year model. While repeat offences are low, this may be more due to fear of police brutality and the prospects of harsher sentences than any conscious effort on the youth population’s part to be more harmonious members of society.

Bourke Investment Allocation (Assignment 3)- 44849389

Aheesh Santosh Shetty