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Explore What Others Are Building

Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.

Insight diagram
There is much we can learn from the development of qualitative relationships models though once we begin to ask questions like how long, how much, when, etc., a qualitative most is not likely to be of much use. The following video demonstrates how, in a very simple goal-seeking structure with delay, depending on the delay, it can be almost impossible to intuit the implications of the interactions with any level of accuracy. The difficulty arises essentially from operating with outdated data. See also Archetypes.

Video

This model is part of

And? Understanding Relationships & Their Implications.

Goal Seeking with Delay
Profile photo Gene Bellinger
35
Insight diagram
This model allows the simulation of the four basic processes of ideal gas: 
Z=1 isentropic
Z=2 isothermal
Z=3 isochoric 
Z=4 isobaric
Video: https://youtu.be/EKzeUoeopk8
Carnotor
Profile photo Easy Physics Werner Maurer
2 weeks ago
Insight diagram

Minimal model of glucose kinetics by Bergman, used to calculate insulin sensitivity from an Intravenous Glucose Tolerance Test (IVGTT). Plasma insulin I(t) enters a remote compartment X(t) where it is active in accelerating glucose G(t) disappearance into the periphery and liver, and inhibiting hepatic glucose production. Adapted from Minimal Models for Glucose and Insulin Kinetics: A Matlab implementation by Natal van Riel, Eindhoven University of Technology 2004 by Mark Heffernan.

V1 Glucose minimal model
Profile photo Geoff McDonnell
85
Insight diagram
This feedback loop demonstrates the impact of dealership inventory requirements on the vehicle supply available for customer purchase. 

Deviation-Reducing Feedback Loop
Profile photo Jeremy Winfrey
2 weeks ago
Insight diagram
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in
https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
  1. http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
  2. https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model
Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death
Profile photo Andrew E Long
62
Insight diagram
La situación modelada expresa el crecimiento de las ventas impulsadas por la motivación y productividad, pero es frenada por el tamaño del nicho de mercado.
Límite de Crecimiento
Profile photo Marcelo A. Castro Iglesias
579 10 months ago