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The Binary Adder:

Andy Long
Spring, 2020 - Year of Covid-19​

Having constructed a working example of a finite state machine (FSM), from Gersting's 7th edition (p. 730, Example 29), I decided to create a more useful one -- a binary adder (p. 732). It works!

Subject to these rules:
  1. Your two binary numbers should start off the same length -- pad with zeros if necessary. Call this length L.
  2. Now pad your two binary numbers with three extra 0s at the end; this lets the binary-to-decimal conversion execute.
  3. numbers are entered from ones place (left to right).
  4. In Settings, choose "simulation start" as 1, your "simulation length" as L+2 -- two more than the length of your initial input number vectors. (I wish that the Settings issues could be set without having to explicitly change it each time -- maybe it can, but I don't know how.)
Be attentive to order -- start with 1s place, 2s place, 4s, place, etc., and your output answer will be read in the same order.

To understand why we need three additional inputs of 0s:
  1. For the useless first piece of output -- so n -> n+1
  2. For the possibility of adding two binary numbers and ending up with an additional place we need to force out: 111 + 111 = 0 1 1 1
  3. For the delay in computing the decimal number: it reads the preceding output to compute the decimal value.
Mat385 Finite State Machine (Binary Adder)
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El Nido Population- 50495 
Infected- 96 
Recovires- 33

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The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

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Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

Clone of SEIRD 01: COVID-19 spread
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Interesting insights
This model indicates the government policies have had positive influence on economic impact and it reduce its negative effects on the economy.
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Dosen Pengampu :
Simulasi Pemodelan Penyebaran COVID-19 di Indonesia di Indonesia Dari Data Vaksinasi
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Dieses Causal Loop Diagramm (CLD) versucht in vereinfachter Weisse die Wesentliche Dynamik des Mars-CoV-2 zu veranschaulichen. Der Motor hinter den Infektionen ist offensichtlich eine selbstverstärkende Rückkopplungsschleife, und ausschlaggebend in diesem Bezug ist der R-Wert. Wenn der R-Wert unter 1 liegt, dann heisst das, dass eine infizierte Person während des Zeitraums, in dem sie infektiös ist, weniger als eine andere Person infiziert.  Liegt der Wert über 1, dann steckt die Infizierte mehr als eine andere Person an, und das Virus verbreitet sich exponentiell. Die Schleifen, die blaue Pfeile enthalten, sind negative Rückkopplungsschleifen – sie bremsen die Verbreitung des Virus. Das Diagramm suggeriert, dass der R-Wert als Schlüssel zur Kontrolle der Verbreitung des Virus dienen könnte. Sollte der Wert über 1 steigen, so müssten  Schutzmassnahem eingeführt werden. Ist der Wert unter 1, dann sind die negativen Schleifen dominierend und einige Massnahmen könnten gelockert werden. 

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Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.


Dados iniciais de infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
Modelo SIR simples - Covid 19
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