Insight diagram
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Human Body Systems Efficiency
Insight diagram
.According to World Health Organization, the SARS-CoV-2 virus is the infectious disease known as coronavirus disease (COVID-19).


The majority of virus-infected individuals will experience a mild to severe respiratory disease and will recover without the need for special care. However, some people will get serious illnesses and need to see a doctor. Serious sickness is more likely to strike older persons and those with underlying medical illnesses including cancer, diabetes, cardiovascular disease, or chronic respiratory diseases. COVID-19 can cause anyone to become very ill or pass away at any age. 

Being knowledgeable about the illness and the virus's propagation is the best strategy to stop or slow down transmission. By keeping a distance of at least one meter between people, donning a mask that fits properly, and often washing your hands or using an alcohol-based rub, you can prevent infection in both yourself and other people. When it's your turn, get your vaccination, and abide by any local advice.

When an infected person coughs, sneezes, speaks, sings, or breathes, the virus can spread from their mouth or nose in minute liquid particles. From larger respiratory droplets to tiny aerosols, these particles are diverse. It's crucial to use proper respiratory technique, such as coughing into a flexed elbow, and to confine yourself to your home and rest until you feel better.
Corononavirus SARs2 (Agent Based)
Insight diagram
This is the base stock and flow diagram I will use to develop a larger system of influencing factors, from health, agri-food systems, and environmental models. Data was taken from UNICEF and UNFPA. Time = 0 starts at 1987.
Clone of Child Stunting Guatemala
Insight diagram
This is the base stock and flow diagram I will use to develop a larger system of influencing factors, from health, agri-food systems, and environmental models. Data was taken from UNICEF and UNFPA. Time = 0 starts at 1987.
Child Stunting Guatemala
Insight diagram

A Susceptible-Infected-Recovered (SIR) disease model with waning immunity

SIR model with waning immunity
Insight diagram
life and disease
Insight diagram
This model is for ENGR 102 - Studio
Disease Dynamics - Henry Aleman
Insight diagram

A Susceptible-Infected-Recovered (SIR) disease model for Rage

SIRKimpossibles
Insight diagram
Healthy project
Insight diagram
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Human Body Systems Efficiency
Insight diagram
Example of Configurable Conveyor Pattern (vectorized conveyor with multiple 'conveyor speeds')

See Taking The Pill 
https://getsatisfaction.com/insightmaker/topics/delay-in-taking-the-pill for the problem statement
Clone of Configurable Conveyor Pattern
Insight diagram
Epidemischer Verlauf einer Krankheit
Epidemischer Verlauf einer Krankheit
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

Clone of Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Human Body Systems Efficiency
Insight diagram
This model shows the relationship between placement to Bourke Hospital and Infection Rate, Recovery rate and release from Bourke Hospital.  

Assumptions
This model assumes that:
upper value for Sensitive to get infected is 50 people
upper value for Placed into Bourke hospital is 50 people
upper value for Released from Bourke hospital is 50 people

Variables
Infection Rate - can be adjusted upwards or downwards to stimulate infection rate.
Infection Factor - can be adjusted upwards or downwards to stimulate infection rate.
Recovery Rate - can be adjusted upwards or downwards to stimulate infection rate.
Clone of Bourke Infection Rate
Insight diagram
This insight is about infection propagation and population migration influence on this propagation.


For this, we defined a world population size and a percentage of it who’s infected. Then, we created an agent where we simulated possible states of an individual.

So, he can be healthy, infected (with an infection rate) or immunized ( with a certain rate of immunization). If the individual is infected, he can be alive or dead. Then, we simulated different continents (North-America, Asia and Europe) with a migration between theses with a certain rate of migration (we tried to approach reality).


Then, thanks to our our move action which represent a circular permutation between the different continents with a random probability the agent will be applied to every individual of the world population.


How the program works ?


In order to use this insight needs to define a size of world population and a probability of every individual to reproduce himself.


Every individual of this population can have three different state (healthy, infected or immunized) and infected people can be alive or dead.

We need to define a percentage of infection to healthy people and a percentage of death for infected people and also a percentage of immunization.

Finally there is le migration part of the program, in this one we need to define three different continents, states or whatever you want. We also need to define a migration probability between each continent to move these person.


With this moving people we can study the influence of migration on the propagation of a disease.


Clone of Migration and infection propagation
Insight diagram
Virus project
Insight diagram
A precedure to test how protective your families sunscreens really are.
Prosedure for helpful science experiment
Insight diagram
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. 
Clone of Clone of Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Insight diagram
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. 
Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

Clone of Clone of Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)
Insight diagram

A Susceptible-Infected-Recovered (SIR) disease model

SIR model
Insight diagram
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

Clone of THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES CHAOTIC TURBULENCE (+controls)