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Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Alejandro Abellan
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 LifeIf 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. 

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Risk Failure Strategy

  • 3 years 1 month ago

Oatley's balance of payments

Jan Baykara

From Oatley 2014 p214++

Balance-of-Payments Adjustment

Even though the current and capital accounts must balance each other, there is no assurancethat the millions of international transactions that individu- als, businesses, and governments conduct every year will necessarily produce this balance. When they don’t, the country faces an imbalance of payments. A country might have a current-accountdeficit that it cannotfully finance throughcapital imports, for example, or it might have a current-accountsur- plus thatis not fully offset by capital outflows. When an imbalancearises, the country must bring its payments back into balance. The process by which a country doessois called balance-of-payments adjustment. Fixed and floating exchange-rate systems adjust imbalances indifferent ways.

In a fixed exchange-rate system, balance-of-payments adjustment occurs through changes in domestic prices. We can most readily understand this ad- justmentprocess through a simple example. Suppose there are only two coun- tries in the world—the United States and Japan—and supposefurther that they maintain a fixed exchange rate according to which $1 equals 100 yen. The United States has purchased 800 billion yen worth of goods, services, and financial assets from Japan, and Japanhas purchased $4 billion of items from the United States. Thus, the United States has a deficit, and Japan a surplus, of $4billion. 

This payments imbalance creates an imbalance between the supply of and the demandfor the dollar and yen in the foreign exchange market. American residents need 800 billion yen to pay for their imports from Japan. They can acquirethis 800 billion yen by selling $8 billion. Japanese residents need only $4 billion to pay for their imports from the United States. They can acquire the $4 billion by selling 400billion yen. Thus, Americanresidentsareselling $4 billion more than Japanese residents want to buy, and the dollar depreci- ates againstthe yen.

Because the exchangerateis fixed, the United States and Japan must prevent this depreciation. Thus, both governmentsintervenein the foreign exchange market, buying dollars in exchange for yen. Intervention has two consequences.First, it eliminates the imbalance in the foreign exchange mar- ket as the governments provide the 400billion yen that American residents need in exchange forthe $4 billion that Japanese residents do not want. With the supply of each currency equalto the demandin the foreign exchange mar- ket, the fixed exchangerate is sustained. Second, intervention changes each country’s money supply. The American moneysupply falls by $4 billion, and Japan’s moneysupplyincreases by 400billion yen. 

The change in the money supplies alters prices in both countries. The reduc- tion of the U.S. money supply causes Americanpricesto fall. The expansion of the money supply in Japan causes Japanese prices to rise. As American prices fall and Japanese prices rise, American goods becomerelatively less expensive than Japanese goods. Consequently, American and Japaneseresidents shift their purchases away from Japanese products and toward American goods. American imports (and hence Japanese exports) fall, and American exports (and hence Japanese imports) rise. As American imports (and Japanese exports) fall and American exports (and Japanese imports) rise, the payments imbalanceis elimi- nated. Adjustment underfixed exchange rates thus occurs through changesin the relative price of American and Japanese goods brought about by the changes in moneysupplies caused by intervention in the foreign exchange market.

In floating exchange-rate systems, balance-of-payments adjustment oc- curs through exchange-rate movements. Let’s go back to our U.S.—Japan sce- nario, keeping everything the same, exceptthis time allowing the currencies to float rather than requiring the governments to maintain a fixed exchangerate. Again,the $4 billion payments imbalance generates an imbalancein the for- eign exchange market: Americansare selling more dollars than Japanese resi- dents want to buy. Consequently, the dollar begins to depreciate against the yen. Because the currencies are floating, however, neither governmentinter- venesin the foreign exchange market. Instead, the dollar depreciates until the marketclears. In essence, as Americans seek the yen they need, they are forced to accept fewer yen for each dollar. Eventually, however, they will acquire all of the yen they need, but will have paid more than $4 billion for them.

The dollar’s depreciation lowers the price in yen of American goods and services in the Japanese market andraises the price in dollars of Japanese goodsandservices in the American market. A 10 percent devaluation of the dollar against the yen, for example, reduces the price that Japanese residents pay for American goods by 10 percentandraises the price that Americans pay for Japanese goods by 10 percent. By making American products cheaper and Japanese goods more expensive, depreciation causes American imports from Japan to fall and American exports to Japan to rise. As American exports expand and importsfall, the payments imbalanceis corrected.

In both systems, therefore, a balance-of-payments adjustment occurs as prices fall in the country with the deficit and rise in the country with the surplus. Consumers in both countries respond to these price changes by purchasing fewer of the now-more-expensive goods in the country with the surplus and more of the now-cheaper goodsin the country with the deficit. These shifts in consumption alter imports and exports in both countries, mov- ing each of their payments back into balance. The mechanism that causes these price changes is different in each system, however. In fixed exchange- rate systems, the exchange rate remains stable and price changes are achieved by changing the moneysupplyin orderto alter prices inside the country. In floating exchange-rate systems, internal prices remain stable, while the change in relative prices is brought about through exchange-rate movements.

Contrasting the balance of payments adjustment process under fixed and floating exchangerates highlights the trade off that governments face between

exchangerate stability and domestic price stability: Governments can have a stable fixed exchangerate or they can stabilize domestic prices, but they cannotachieve both goals simultaneously. If a government wants to maintain a fixed exchangerate, it must accept the occasional deflation and inflation caused by balance-of-payments adjustment. If a governmentis unwilling to accept such price movements,it cannot maintain a fixed exchangerate. This trade-off has been the central factor driving the international monetary system toward floating exchange rates during the last 100 years. We turn now to examine howthis trade-off first led governmentsto create innovativeinter- national monetary arrangements following World WarII and then caused the system to collapse into a floating exchange-rate system in the early 1970s. 

Finance Economics

  • 1 year 4 months ago

[@Live@]*SGB Premiership The Belle Vue Aces vs Somerset Rebels 2018 Live Stream Free Speedway

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Finance

  • 1 year 8 months ago

Clone of Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Guilherme Werpel Fernandes
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 LifeIf 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. 

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Risk Failure Strategy

  • 3 years 11 months ago

Clone of TBS API-KDE INFO&DECISION

Kévin DECKER

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.

Finance

  • 2 years 2 months ago

Clone of POPULATION LOGISTIC MAP (WITH FEEDBACK)

Teresa Nani
The simulation integrates or sums (INTEG) the Nj population, with a change of Delta N in each generation, starting with an initial value of 5.The equation for DeltaN is a version of Nj+1 = Nj  + mu (1- Nj / Nmax ) Nj
the maximum population is set to be one million, and the growth rate constant mu = 3. Nj: is the “number of items” in our current generation.
Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

This equation is a form of what is known as the logistic map or equation. It is a map because it "maps'' the population in one year into the population of the next year. It is "logistic'' in the military sense of supplying a population with its needs. It a nonlinear equation because it contains a term proportional to Nj^2 and not just Nj. The logistic map equation is also an example of discrete mathematics. It is discrete because the time variable j assumes just integer values, and consequently the variables Nj+1 and Nj do not change continuously into each other, as would a function N(t). In addition to the variables Nj and j, the equation also contains the two parameters mu, the growth rate, and Nmax, the maximum population. You can think of these as "constants'' whose values are determined from external sources and remain fixed as one year of items gets mapped into the next year. However, as part of viewing the computer as a laboratory in which to experiment, and as part of the scientific process, you should vary the parameters in order to explore how the model reacts to changes in them.

Environment MATHS Mathematics Chaos Fractals BIFURCATION Model Economics Finance TURBULENCE Population Growth DECAY STABILITY SUSTAINABLE Engineering Science Demographics Strategy

  • 3 years 11 months ago

Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Guilherme Werpel Fernandes
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 LifeIf 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. 

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth BIFURCATIONS MTBF Risk Failure Strategy

  • 3 years 11 months ago

Clone of Aufgabe 3: Lancierung Produktpakete / Stock-Flow Modell / Jan Mathieu & Martin Bovet

Peter Addor

​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.

Finance Banking Sales

  • 5 years 6 months ago

Clone of OVERSHOOT GROWTH INTO TURBULENCE

Gary Leonard
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

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 limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Strategy Weather

  • 4 years 5 months ago

Clone of OVERSHOOT GROWTH INTO TURBULENCE

George J F Mackintosh
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

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 limited size working capacity containers (villages communities)

Environment Economics Finance Mathematics Physics Biology Health Fractals Chaos TURBULENCE Engineering Navier Stokes Science Demographics Population Growth Strategy Weather

  • 4 years 6 months ago

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