Trying a trail separation

Unclebaldrick

Unclebaldrick

Well-Known Member
I have a problem. Whenever I buy trail-mix the random distribution of the ingredients is totally fucked. Because of the different densities and sizes of nuts and raisins and shit, all the nuts get pushed toward the top leaving the bottom of the bag filled with raisins and dried cranberries. This is not the way the designers of this trail mix meant for it to be eaten.

I have tried shaking the bag at all different angles but sometimes it just makes the problem worse.

So right now my modus vivendi is to individually separate the ingredients by hand - a slow and painstaking process. Then I can control the delivery of trail-mix into my mouth at the optimal mix by individualy selecting components each time.

Can anybody think of a way to improve the trail separation process? I have tried screens but they only work on size and not density - thus the filberts get mixed in with the raisins causing total chaos. Maybe some sort of a sluice?
 
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6ohMax

6ohMax

Well-Known Member
Unclebaldrick said:
I have a problem. Whenever I buy trail-mix the random distribution of the ingredients is totally fucked. Because of the different densities and sizes of nuts and raisins and shit, all the nuts get pushed toward the top leaving the bottom of the bag filled with raisins and dried cranberries. This is not the way the designers of this trail mix meant for it to be eaten.

I have tried shaking the bag at all different angles but sometimes it just makes the problem worse.

So right now my modus vivendi is to individually separate the ingredients by hand - a slow and painstaking process. Then I can control the delivery of trail-mix into my mouth at the optimal mix by individualy selecting components each time.

Can anybody think of a way to improve the trail separation process? I have tried screens but they only work on size and not density - thus the filberts get mixed in with the raisins causing total chaos. Maybe some sort of a sluice?
Click to expand...

Is that your modus operandi?
















Can I recommend you try? It's good..but not the best

48243.jpg
 
Singlemalt

Singlemalt

Well-Known Member
The distribution of the various components should follow this:
A discrete random variable X is said to have a Poisson distribution with parameter λ > 0, if, for k = 0, 1, 2, ..., the probability mass function of X is given by:[10]


where

The positive real number λ is equal to the expected value of X and also to its variance[11]


The Poisson distribution can be applied to systems with a large number of possible events, each of which is rare. How many such events will occur during a fixed time interval? Under the right circumstances, this is a random number with a Poisson distribution.

The conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λk and k!. The fraction of λk to k! can also produce a rounding error which is very large compared to e−λ, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as


which is mathematically equivalent but numerically stable. The natural logarithm of the Gamma function can be obtained using the lgamma function in the C (programming language) standard library (C99 version) or the gammaln function in MATLAB or SciPy.


In order for it to hold true, the mixed components should be in a constant state of agitation; both prior to and during packaging (insuring correct mix distribution in the package); and both prior to opening the package. We have been too long victimized by the corporate fascist disclaimer of "contents may have settled during shipping" that absolves the Corps shoddy practices and avoidance to correct this injustice.
 
Unclebaldrick

Unclebaldrick

Well-Known Member
Singlemalt said:
The distribution of the various components should follow this:
A discrete random variable X is said to have a Poisson distribution with parameter λ > 0, if, for k = 0, 1, 2, ..., the probability mass function of X is given by:[10]


where

The positive real number λ is equal to the expected value of X and also to its variance[11]


The Poisson distribution can be applied to systems with a large number of possible events, each of which is rare. How many such events will occur during a fixed time interval? Under the right circumstances, this is a random number with a Poisson distribution.

The conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λk and k!. The fraction of λk to k! can also produce a rounding error which is very large compared to e−λ, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as


which is mathematically equivalent but numerically stable. The natural logarithm of the Gamma function can be obtained using the lgamma function in the C (programming language) standard library (C99 version) or the gammaln function in MATLAB or SciPy.


In order for it to hold true, the mixed components should be in a constant state of agitation; both prior to and during packaging (insuring correct mix distribution in the package); and both prior to opening the package. We have been too long victimized by the corporate fascist disclaimer of "contents may have settled during shipping" that absolves the Corps shoddy practices and avoidance to correct this injustice.
Click to expand...
Would zero gravity and a paint-shaker solve this problem? What could one do to offset acceleration?
 
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Grandpapy

Grandpapy

Well-Known Member
Singlemalt said:
The distribution of the various components should follow this:
A discrete random variable X is said to have a Poisson distribution with parameter λ > 0, if, for k = 0, 1, 2, ..., the probability mass function of X is given by:[10]


where

The positive real number λ is equal to the expected value of X and also to its variance[11]


The Poisson distribution can be applied to systems with a large number of possible events, each of which is rare. How many such events will occur during a fixed time interval? Under the right circumstances, this is a random number with a Poisson distribution.

The conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λk and k!. The fraction of λk to k! can also produce a rounding error which is very large compared to e−λ, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as


which is mathematically equivalent but numerically stable. The natural logarithm of the Gamma function can be obtained using the lgamma function in the C (programming language) standard library (C99 version) or the gammaln function in MATLAB or SciPy.


In order for it to hold true, the mixed components should be in a constant state of agitation; both prior to and during packaging (insuring correct mix distribution in the package); and both prior to opening the package. We have been too long victimized by the corporate fascist disclaimer of "contents may have settled during shipping" that absolves the Corps shoddy practices and avoidance to correct this injustice.
Click to expand...
Even if the nuts are salted?????
 
Unclebaldrick

Unclebaldrick

Well-Known Member
Singlemalt said:
Indeed it would. Until the Corp fascists spend some of their obscene profits on proper packaging techniques and addressing customer satisfaction; I have been boycotting them and make my own
Click to expand...
Making your own!? But surely you must be following some pattern set down by a master trail-mixer! Or are you that good? Are you a wizard?

 
Diabolical666

Diabolical666

Well-Known Member
Singlemalt said:
The distribution of the various components should follow this:
A discrete random variable X is said to have a Poisson distribution with parameter λ > 0, if, for k = 0, 1, 2, ..., the probability mass function of X is given by:[10]


where

The positive real number λ is equal to the expected value of X and also to its variance[11]


The Poisson distribution can be applied to systems with a large number of possible events, each of which is rare. How many such events will occur during a fixed time interval? Under the right circumstances, this is a random number with a Poisson distribution.

The conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λk and k!. The fraction of λk to k! can also produce a rounding error which is very large compared to e−λ, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as


which is mathematically equivalent but numerically stable. The natural logarithm of the Gamma function can be obtained using the lgamma function in the C (programming language) standard library (C99 version) or the gammaln function in MATLAB or SciPy.


In order for it to hold true, the mixed components should be in a constant state of agitation; both prior to and during packaging (insuring correct mix distribution in the package); and both prior to opening the package. We have been too long victimized by the corporate fascist disclaimer of "contents may have settled during shipping" that absolves the Corps shoddy practices and avoidance to correct this injustice.
Click to expand...
you math dick:clap:
 
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