Insight diagram
FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION 
 BEWARE pushing increased growth blows the system!
(governments are trying to push growth on already unstable systems !)

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy 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 limited size working capacity containers (villages communities)

Clone of FORCED GROWTH INTO TURBULENCE
Insight diagram
This is what I would imagine how most of the US's personal finances look: The individual has a retirement account set up or will be getting pensions upon retiring and has replaced his or her rent payment with a mortgage, which will go away after 15-30 years.
Clone of Bob - Expanded
Insight diagram
Find FV given PV, time, and rate.
Clone of Time Value of Money - Simple
Insight diagram

​Dieses Modell soll aufzeigen, wie sich ein neues Produkt auf das Kundenverhalten auswirkt. Vorteil von Paketen für z.B. eine Bank ist es, dass die Kunden egal welche Produkte sie haben, immer gleich viel bezahlen und somit die Kosten einfacher Berechnet werden können.

Im Weiteren ist die Administration von einem standarisierten Paket einfacher und günstiger, als die Administration der einzelnen Produkte.

Im Modell kann berechnet werden, wie sich die Attraktivität des Paketes gegenüber den Einzelprodukten (in diesem einfachen Modell nur über den Preis definiert) auf das Wechselverhalten der Kunden auswirkt.

Aufgabe 3: Lancierung Produktpakete / Stock-Flow Modell / Jan Mathieu & Martin Bovet
Insight diagram
FORCED GROWTH GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION 
 BEWARE pushing increased growth blows the system!
(governments are trying to push growth on already unstable systems !)

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept and flawed strategy 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 limited size working capacity containers (villages communities)

Clone of FORCED GROWTH INTO TURBULENCE
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 BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Insight diagram
Models the repayment of a mortgage, with a fixed-term fixed-rate deal.

e.g. for an up-front £1495 fee, you get a fixed interest rate of 1.22% for 2 years, followed by variable rate).

After the deal ends, the 'variable' rate is currently constant, but could be set via a converter instead to model different predictions of future interest rates. 
Fixed rate mortgage deal model
Insight diagram
Clone of ISD Savings Plan
Insight diagram

At the dawn of our century financials markets collapsed in what is call “the burst of the internet bubble”. There are many things which can explain this bursting and before that, the emergence of the bubble. In this document we will try to show what this factors are and how they are related each other.

Clone of TBS API-KDE INFO&DECISION
Insight diagram
This is what I would imagine how most of the US's personal finances look: The individual has a retirement account set up or will be getting pensions upon retiring and has replaced his or her rent payment with a mortgage, which will go away after 15-30 years.
Clone of Bob - Expanded
Insight diagram
Systém obchodu s potravinami - Schéma zásob a toků
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
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 BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK
Insight diagram
US Monetary System Flows
Insight diagram
This is a first basic inflow - outflow model / linear
Clone of First Basic Inflow -Outflow Model
Insight diagram
Finances for MEE460-04
Carson-Finances
Insight diagram
Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.
Clone of Hyperinflation Simulation
Insight diagram
A causal loop diagram illustrating a subset of variables influencing business problems related to the transitioning of the Social Assistance Management System (SAMS) from initial production deployment to steady state.

Inherent in the diagram is a representation of two well-known system dynamics archetypes:

  • Shifting the Burden, represented in the interplay between the B1, B2, and R3 loops, and
  • Limits to Success, represented in the interplay between the B1 and R5 loops.
Variables Influencing Business Problems Related to SAMS (+/-)
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
Simple causal loop diagram of a simple interest savings account.
Clone of Causal loop diagram of savings account - simple interest
Insight diagram
Modelagem Soft sobre o Conflito de Agência e Governança no Brasil. Atividade proposta em Teoria Geral dos Sistemas, ministrada pelo Prof. Antonio Carlos Zambon.

Integrantes:
- Edson da Costa Vitor Junior, 170086
- Gustavo Batistic Ribeiro, 174028
- Huanna Raquel do Nascimento, 174720
- Karen E. M. Rodrigues, 177493
- Leticia O. C. Tavares, 182047
- Matheus Baroni, 184378
Conflito de Agência e Governança no Brasil
Insight diagram

At the dawn of our century financials markets collapsed in what is call “the burst of the internet bubble”. There are many things which can explain this bursting and before that, the emergence of the bubble. In this document we will try to show what this factors are and how they are related each other.

TBS API-KDE INFO&DECISION
Insight diagram
A model of lottery jackpots and their interactions with ticket sales and winnings
Clone of Lottery Jackpot
Insight diagram
JLuks - Sporici ucet