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Simple epidemiological model for Burnie, Tasmania
SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts  

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model,  will stop for next 52 weeks).
Model of Covid-19 Outbreak in Burnie, Tasmania (Yue Xiang 512994)
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Economic capital growth in a system constrained by a non-renewable resource, Figure 37 from Thinking in Systems by Donella H. Meadows

Economic Capital Growth - Resource Constrained
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A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy.  Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions
Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

A greater number of COVID-19 cases has a negative effect on the economy.  This is due to economic signalling that all is not well.

Interesting insights

Higher testing rates trigger more rapid government intervention, which reduces infectious cases.  The impact on the economy, though, of higher detected cases is negative. 




Burnie COVID-19 outbreak demo model version 2
39 10 months ago
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This model shows the operation of a simple economy. It demonstrates the effect of changes in the fractional rate of consumption (or the converse, the fractional rate of saving.) It also, unlike Models 2 & 3, shows the influence Savings has on the production rate.

In summary, lower rates of consumption (based on production) result in higher rates of both production and consumption in the long-run.
Simple Economy: Model 4
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Implementation of a DSGE Model solved in a Macroeconomics class by Harald Uhlig (link), using Rational Expectations, in this case, the Hansens Real Business Cycle Model.
It shows the capacity of implementing Dynamic Stochastic General Equilibrium Model Analysis using System Dynamics.
Real Business Cycle Model (DSGE)
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Sandbox for testing InsightMaker features using pipeline Construction & ROW land conversion as a driver of changes in ecosystem service value.
ESV Test
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CLD exposition of Goodwin01 from Steve Keen's August 2019 course on Introduction to Economic Dynamics and Minsky software See video and powerpoint slides. Based on IM-2011 Minsky FIH and IM-168865 MacroEconomics CLDs. SeeIM-172005 for Simulation

Goodwin cycle Minsky Keen August 2019
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Unfortunately, this model only produces the illusion of functioning, but I did manage to get it to give me the graph. However, because of the use of flows, if you change the time step to and the simulation length to anything other than the same numbers, you'll find the graph showing something that looks more exponential. This is due to the function referencing itself in regards to time, so inevitably each time consumption grows it changes the outcome on the other side of the equation. Still, this is a convincing mock up. I added a "45 degree" line so that one could conceivably see (and also change) the difference made by altering the level of autonomous consumption.
Keynesian Macroeconomics
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Smithian growth model from Michael Joffe Fig. 3.7 p57 Ch3 Feedback Economics Book
Adam Smith's Growth through Division of labour
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Model Explanation:

This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW. 
The model also adds in the variable of funding for safe houses. With a high rate of domestic violence, unfavorable home conditions and other socio-economic factors, many youth roam the streets with no safe place to go, which may lead to negative behaviour patterns.


Assumptions

Youth Population: 700
Total youth population in 2016 for Bourke LGA was 646 (ages 10-29). (Census, 2016) Figures rounded to 700 for purposes of this model simulation. 

Constants:
70% registration and engagement rates for Community funded programs
30% attendance rate for Safe Houses
50% crime conviction rate


Variables

Positive and Negative Influences

The model shows a number of key variables that lead youth to become more vunerable to commit a crime (such as alienation, coming from households with domestic violence, boredom and socio-economic disadvantages such as low income), as well as the variables that enhance the youth's likelihood to be a contributing member of the community (developing trusted relationships and connections with others, and having a sense of self worth, purpose and pride in the community). These factors (positive and negative) are aggregated to a single rate of 50% each for the purposes of the simulation, however each individual situation would be unique.  

Police Funding / Resources

Police funding and resources means the number of active police officers attending to criminal activities, as well as prevention tactics and education programs to reduce negative behaviour. The slider can be moved to increase or decrease policing levels to view the impact on conviction rates. Current policing levels are approx 40 police to a population of under 3000 in Bourke.

Crime Rate

Youth crime rates in Australia were 3.33% (2016). Acknowledging Bourke crime rates are much higher than average, a crime rate of 40% is set initially for this model, but can be varied using the sliders. 


Community Program Funding / Resources

Community Program Funding and Resources means money, facilities and people to develop and support the running of programs such as enhancing employability through mentorship and training, recreational sports and clubs, and volunteering opportunities to give back to the community. As engagement levels in the community programs increase, the levels of crime decrease. The slider can be moved to increase or decrease funding levels to view the impact on youth registrations into the community programs.

Observations

Ideally the simulations should show that an increase in police funding reduces crime rates over time, allowing for more youth committing crimes to be convicted and subsequently rehabilitated, therefore decreasing the overall levels of youth at risk.

A portion of those youth still at risk will move to the youth not at risk category through increased funding of safe houses (allowing a space for them to get out of the negative behaviour loop and away), whom them may consider registering into the community engagement programs. An increase in funding in community engagement programs will see more youth become more constructive members of the community, and that may in turn encourage youth at risk to seek out these programs as well by way of social and sub-cultural influences.

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Justice & Community Support Investment and the Impacts on Bourke Youth Population
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This Model was developed from the SEIR Model (Susceptible, Exposed, Infected, Recovered) and it predicts the COVID-19 outbreak in Burnie, Tasmania. This pandemic outbreak contributes to diverse rates including infection rate, death rates and recovery rate, government policies and its economic impacts.    

Assumptions:

 This model is driven by its determined rates, e.g., incubation rate, morality rate, test rate and immunity loss rate and its recovery rate.

Government policies are involved in fully vaccination rate, social distance, national border closure, travel, and business restriction which effect Burnie’s economy.

There are three economic entities dimensions in Burnie Island, we can tell that the pandemic has negative impact on Brick-and-Mortar enterprises and tourism business to some extent, whereas, e commercial business plays a crucial role to stimulate the regional economic activities during the COVID-19 period.

 

Interesting Insights:

 The figure of susceptible changes significantly during the initial 3 weeks because of low recovery rate and high infection rate. On the other hand, the implementation and interventions of government policies is effective, because the number of patients who tested negative is increased and the majority of them release and go back home after medical follow-up. 

Xueli Huang 501514, BMA708 Model of COVID-19 Outbreak in Burnie, Tasmania
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Q2 Final Project w/ socio-economic
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This model demonstrate how the exisitng tested COVID cases effects economic recovery via goverment intervenes.
Assumption:Goverment intervenes positively contribute on transmission, patients recovery, and death elimination. When existing cases equal or lower than 10 cases, economic growth will be soaring with helps of influencial elements.
Interesting points: even though there are certain amount of unknow cases, enhancing social restriction and increasing test rate ould still reduce amount of cases
Complex Model to Simulate How COVID Outbreak Influence Economic Recovery in Burnie
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IASAM
Artis
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Economic contibution
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3. PROBLEMAS e  PERGUNTAS SOBRE  projetos de SISTEMA INTEGRADO DE GESTÃO CUSTOS , INVESTIMENTOS BASEADO MODELOS MATEMÁTICOS: veja  https://docs.google.com/document/d/1oGmItBcErhVF0PWuI37AnpP3n8Up3Zu45W7QB1MMbcY/edit?usp=sharing

Projeto  de investimentos , custos   e viabilidade econômico de LCC

A planta foi dimensionada para produzir 9.000 Ton/ano da Resina usando o matéria prima

LCC , operando 24h/dia, durante os três turnos por 300 dias/anuais. O preço do produto de projeto de lcc 

veja  o prova html aula passados 


1. Calcule o investimento em planta (If) usando o método rápido e investimento em

equipamento (Ie) baseado no método de lang. Admita valor de N e f1 de acordo com o fluxograma do processo.

Dados fornecidos: Entrada (alimentação)-sólido; Saída-líquido;

Equipamentos principais da produção: Destilador e fermentador.

2. Calcule o investimento fixo total pelo método chilton através das estimativas dos investimentos fixos diretos: Tubulação, instrumentação, estrutura física, planta de serviço e conexões entre unidades; e investimentos fixos indiretos. Tome como base o investimento em equipamentos.

             veja dados na prova html   simulados sobre fator chiltons , modelos  de lang , decico , chiltons e dados na prova html 


3. Calcule o custo de mão-de- obra direta e indireta baseando-se no fluxograma de processo , atualizando  o valor salário mínimo e nos salários:

Valor do salário mínimo = R$180,00

Engenheiro químico = 10 salários mínimos

Operador industrial = 3 salários mínimos

Administração:

Gerente = 8 salários mínimos

Auxiliar de escritório = 3 salários mínimos

Secretária = 2 salários mínimos

Dados fornecidos: Considere os encargos sociais de 65% sobre o salário base. Mão-de- obra

indireta seja 20% da mão-de- obra direta. O custo de mão-de- obra indireta engloba

manutenção.

4. Calcule os custos fixos abaixo, baseando-se pelo método Sebrae:

Dados 

4.1 Depreciação = 10%If

4.2 Manutenção = 3%If

4.3 Seguro = 1%If

4.4 Imposto = 2%If

5. Calcule o custo de consumo anual de matéria-prima de acordo com os dados  , veja prova html a seguir 

5.2 Calcule o custo unitário de matéria prima sendo 80% do valor do custo total anual da

matéria-prima. , dados  , veja na link enunciados  e prova html 

6. Calcule os custos totais:

6.1 Encargos anuais

6.2 Administração = 0.6 (mão-de- obra direta + mão-de- obra indireta + encargos anuais)

6.3 Suprimentos = 0.15 (Manutenção)

6.4 Calcule os custos fixos

6.5 Calcule os custos variáveis

6.6 Calcule os custos variáveis

* Os custos fixos englobam administração

Custo variável = custo de matéria – prima + custo de utilitários + custo de suprimentos.

Custo de suprimentos é 10% da mão-de- obra direta.

Depreciação = 10% do investimento fixo.

7. Estimar o ponto de equilíbrio em quantidade e em porcentagem baseado em dados obtidos de custo variável unitário) e Custo fixo do problema 06.


8. Estime os itens da análise de investimento:

– Taxa de retorno de engenharia simples

– Tempo de retorno

– % de lucro em relação ao preço de venda

– Lucro após o imposto de renda

– Lucratividade

– Rentabilidade

– Fluxo de caixa

9. Estimar potencial econômico de projeto de perdas devido ao baixo rendimento de operação em nível de 90% de rendimento máximo em vez de 98%.

 

 Dados de  consumos de  materiais e energia obtidos  via uso de calculadora usando    quiz html de modelos já apresentados aula passos





NOME E DESCRIÇÃO

LINK

TAMANHO

Prova1validacao.:Investimento Fixo e Tomada de Decisões Rápidas

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184101

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Prova.2 Validacao .Investimento fixo método Lang

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184144

32 KB

Prova 3 :Investimento Fixo método Chilton

ihttps://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184169


33 KB

Prova4:Custo Fixo

https://canvas.instructure.com/courses/780776/files/folder/provahtml?preview=51184189

32 KB

Prova 5::Custo de mao de obra

customaohtm custo de mao de obra

33 KB

Prova 6 Validao : Custo de mat,comb e enegia

CustoMat prima , energia

34 KB

Prova 7 Custo total

custo de operacional  de  producao

33 KB

Prova 8 Ponto deEquilibrio 

ponto de eqilibrioibrio

32 KB

Prova 9:Analise de lucro e beneficios

Fluxo de caixa

33 KB




gestao economical planta resina fenolicas lcc .Modelos e resultados validados validado via planilhas
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Fig 4. The Casual Loop Diagram of the Socio-Political and Economic Subsystems
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Biodiversity -> Climate Change
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Cornerstore Economic Model
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• This model examines how sustainable consumerism is from social, economic, and environmental aspects. The question in focus is "How will our second-hand clothing donations affect communities in developing countries, specifically Kenya?"

5 Stock Variables: 
• U.S. Consumers
• Multinational Corporations
• Overseas Factories
• Kenya

Highlight Findings: 
To sum up, there are 4 major problems associated to donations:
• 1. Source of problem is the consumer: Cheap deals attract hundreds of millions in revenue for fast fashion, and contribute to 100,000 tonnes of clothing to Kenya annually. 
• 2. Rapid consumerism leads to over-utilization of slowly-renewable resources, such as water.
• 3. Nearly 96% of textiles jobs are eradicated by the massive inflow of clothing donations to Kenya. 
• 4. The offshoring of textiles jobs enrages U.S. blue-collar workers, leading to the rise of protectionism.  



Environmental, social, and economic sustainability aspects of textiles donations
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Insight Stage 4 Dress Rehearsal Economy and Fossil Fuels
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WIP Summary of Miller 2015 PCD article for the Compelling Case for Prevention Project Scoping Study.
See also economic view IM 69774 (private)
Simplified at IM-70351 Tool
Prevention Investment Framework
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This model shows the operation of an extremely simple economy. The system produces and consumes each item (or good) at a fixed rate.

When production exceeds consumption, consumer goods accumulate in stocks. Trading may occur between actors in this system. That will not, however, affect the quantities of the stocks of goods. It only affects ownership (not a concern of this model.)
Simple Economy: Model 1