Archive for mass emailing

email footprint

Posted in Travel, University life with tags , , , , , on September 14, 2019 by xi'an

While I was wondering (im Salzburg) at the carbon impact of sending emails with an endless cascade of the past history of exchanges and replies, I found this (rather rudimentary) assessment  that, while standard emails had an average impact of 4g, those with long attachments could cost 50g, quoting from Burners-Lee, leading to the fairly astounding figure of an evaluated impact of 1.6 kg a day or more than half a ton per year! Quite amazing when considering that a round flight Paris-Birmingham is producing 80kg. Hence justifying a posteriori my habit of removing earlier emails when replying to them. (It takes little effort to do so, especially in mailers where this feature can be set as the default option.)


a new method to solve the transformation of calculus

Posted in Statistics with tags , , , , , , on December 23, 2018 by xi'an

An hilariously ridiculous email I just received (warning: book cover unrelated):

Good day! this is very important to the “Mathematics” and the related fields,
“The Simulator”,“Probability theory”,”Statistics”,”Numerical Analysis”,
“Cryptography”,“Data mining”,“The big data analysis”and“Artificial Intelligence”.
The transformation of random variables in Calculus is very difficult and sometimes
is impossible to be done. The simulator can get the accuracy and precise simulated data
and the database could be the probability distributution if the data size is 100,000,000
or more. The probabilistic model can be designed and getting the probability distribution
and the coefficient using the simulator.

(1)“The Simulator” has four methods,
1) the basic method is the inverse function of the distribution function,
2) the transformation method to get the simulated data,
3) the numerical analysis method to build the simulated database,
4) the simulated database and the estimated line of random variable to get the simulated data.
(2) “Probability Theory” can use the simulator to a tool.
(3) ”Statistics”, the sampling distribution of the point estimator and the test statistic
can be seen as the transformation equation and the critical point and p value is from
the sampling distribution.
(4) ”Numerical Analysis”, the simulator data can overcome the limit of numerical analysis,
the number of random variables could be more 10000.
(5) “Cryptography”, the simulator of the probabilistic model will derive the lock code
which cannot be unlocked.
(6) “Data mining”, the data set can be a specific probability distribution using
“goodness of fit” or “Curve-fitting” or “Curvilinear”.
1) “goodness of fit”, there are 45 distributions for the null hypothesis.
2) “Curve-fitting”, the estimated line of random variable and the estimated line
of the distribution function.
3) “Curvilinear”, the data set is not arithmetic series.
(7) “The big data analysis”, the number of random variables could be more 10000
about the simulator of the probabilistic model.
(8) “Artificial Intelligence”, the model after analysis can be the transformation
equation, the simulator of the probabilistic model can get the simulated data.

The first book name is “The simulator” will be public, the context contains
(1) The simulation methods,
(2)“Probability Theory”,
(3) ”Statistics” and how to write the statistical package even the population is not
Normal distribution or a special statistical model.
(5)“Explored the arithmetic data”,