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Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
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Economical Factors of Science: C8
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This page provides a structural analysis of POTUS Candidate Rick Perry's economic policy based on the information at: https://rickperry.org/issues/​ The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Rick Perry economic policy
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This page provides a structural analysis of POTUS Candidate Chris Christi's economic policy based on the information at: https://d70h9a36p82zs.cloudfront.net/Ccpres2016/base/assets/1-0-1/production/Chris-Christie-TheEconomy.pdf   The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Chris Christi economic policy
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Week 13.1 Lab Economic Model
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An initial study of the economics of single use coffee pods.
Claire - Coffee Pods ISD Humanities v 1.02
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An initial study of the economics of single use coffee pods.
K Collins Coffee Pods ISD Humanities v 1.02
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Economic model
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Economical 4H Insight
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COVID Systemigram
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Green lines: positive relationships
Red lines: negative relationships

Spill
9 months ago
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This model simulates a COVID outbreak occurring at Burnie, Tasmania. It links the extent to the pandemic with governments intervention policies aiming to limit the spread of the virus. The other part of the model illustrates how will the COVID statistics and the government enforcement jointly influence the economic environment in the community. A number of variables are taken into account, indicating positive or negative relationship in the infection and the economy model respectively.

 

Assumptions

·         Government takes responsive actions when the number of acquired cases exceeds 10.

·         Government’s prompt actions, involving closure of the state border, lockdown within the city, plans on mandatory vaccination and testing, effectively control the infection status.

·         Economic activities are reduced due to stagnation in statewide tourism, closure of brick-and-mortar businesses, and increased unemployment rate, as results of government restrictions.

 

Insights

Government’s rapid intervention can effectively reduce the infected cases. The national vaccination rollout campaign raises vaccination rate in Australians, and particularly influence the death rate in the infection model. Please drag the slider of vaccination to a higher rate and run the model to compare the outcomes.

Although local economy is negatively affected by government restriction policies, consumer demand in online shopping and government support payments neutralize the negative impact on economy and maintain the level of economic activities when infections get controlled. 

Simulation model of COVID outbreak in Burnie Tasmania_Yuchen Zhang_574644
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This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results. 
World Model1
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Prosperity Loop v1.0
8 months ago
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Start_Base model
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Michael Marmot's Eur J Epidemiol Essay 2017 See also IM-62760  Social determinants of health from Michael Marmot's  ABC 2016 Boyer Lectures on Social Justice and the Health Gap
Social Justice, Epidemiology and Health Inequalities
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Description

 

The model shows Covid-19 situations in Burnie, Tasmania. Under such circumstances, how the state government deals with the pandemic and how economy changes will be illustrated. The relationship between government policy and economic activities under Covid-19 outbreaks will be explained through different variables.


Assumptions

 

Government policy negatively affects Covid-19 outbreaks and economic activities.

Covid-19 outbreaks also has negative effects on economic growth.

 

Parameters

 

There are several fixed and adjusted variables.

 

1.     COVID-19 Outbreaks

Fixed variables: infection rate, recovery rate

Adjusted variables: immunity loss rate

 

2.     Government Policy

Adjusted variables: lockdown, social distancing, testing, vaccination

3.     Economic impact

Fixed variables: tourism

Adjusted variables: economic growth rate

 

Interesting Insights

 

Tourism seems to be the most effective way to bring back economic growth in Tasmania, and it takes time to recover from Covid-19.

 

Government policies tend to have negative influences on economic growth.

BMA708 Assignment 3_Yu Wang_595070
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241004_economic growth model structure_SFD
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Economic model
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Overview of Part G Ch 27 to 30 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
History of Macroeconomic Thought
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The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a more environmentally focused policy.

MscT CSE - World3 Model (clone) : Classic World Simulation
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Technological changes in mobile technology have radically changed the people’s life by increasing their ability to communicate. Invention, innovation and diffusion is a sequence in the whole technological change process.

The concept of diffusion here refers to the spreading of new technologies across potential markets and typically follows an S-curve. Both the rate of technological change and the speed of technological diffusion have increased significantly in recent years .The new technologies when appear broaden the market by making new applications feasible and economical. The main drivers for the diffusion of mobile telecommunications have been technological progress that has allowed for relentless cost reduction and increase in performance. Providing enhanced voice capability, high speed data service, better spectrum management and coverage has resulted in different mobile technology generations. Digital (i.e. second-generation or 2G) mobile telephony was introduced in different technological flavors globally. Now 3G with new advanced features introduced in india .here in this simulation study we can show the diffusion of 2G and 3G 

 

diffusion of 2G & 3G in india
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​WIP Summary of 2020 article Monetary Sovereignty: Nature, Implementation, and Implications by Eric Tymoigne
Eric Tymoigne Monetary Sovereignty
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Initially based on 2025 Economics Nobel Prize winners, via Gene's Aha Paradox AI script
Techology Innovation Economics Models