## Suggested Reading: Les sciences de l’imprécis

May 26, 2010

Abraham A. Moles — Les sciences de l’imprécis — Seuil, 1990, 310 pp. ISBN 2-02-011620-0

(out of print?)

“Thinking about the vague is not vague thinking” would quite succinctly and accurately describe Moles’ thesis. The terminology used will be a bit disconcerting to the computer scientist as the vocabulary comes from the social sciences rather than the “hard” sciences. At times we feel that analogies drawn between the author’s ideas and information theory (and computer science) are almost stretched but we can quite forgive this since it nevertheless remains a very clear exposition of his thesis, that is, imprecision is not to be frown upon and is quite necessary to science and as such should be mastered rather than feared.

The text is almost grand public as it contains essential no maths.

## Data Insecurity

May 25, 2010

It always amazes me to see how people put trust in their service providers. While in principle, there’s no real need to worry, careless implementation of services can really have dire consequences!

And it’s not like leaks and exploits are rare. Sometimes we hear about them, sometimes we don’t. Let’s consider these two (amongst those) I know about:

## Suggested Reading: The Common Sense of Science

May 19, 2010

Jacob Bronowski — The Common Sense of Science — Harvard University Press, 1978, 154 pp. ISBN 0-674-14651-4

I already knew Bronowski by the television series The Ascent of Man (broadcasted in french in the late 70s or maybe the very early 80s by Radio-Québec, now TéléQuébec). Even as a child, I was impressed by the depth of discourse of the series. Universal thinker, in The Common Sense of Science, Bronowski tells us how he conceives science and its methods as a fundamental human activity, and why it plays such an important (if misunderstood) rôle in our society. The narration follows more or less the evolution of science since the Enlightenment to our time and how it is tied to the industrial revolution.

## A matter of interpretation

May 18, 2010

In calculus 101, amongst the first things we learn, is that the derivative a function is the slope of the tangent to the function, that is, the instantaneous slope at some point on the function. We have, for some function $F$ that the derivative $f$ is given by:

$\displaystyle\frac{\partial\:F}{\partial\:x}=\lim_{\Delta\to{}0} \frac{F(x+\Delta)-F(x)}{(x+\Delta)-x}=\lim_{\Delta\to{}0}\frac{F(x+\Delta)-F(x)}{\Delta}=f$

So the formulation looks like a slope, and it is taught that it is a slope as well; all the concepts surrounding differentiation are expressed in terms of slopes of tangents, and that’s OK, because that’s what they are.

But suddenly, in calculus 201, we learn how to find the anti-derivative of a function, also known as the integral. But the metaphor changes completely: we’re know talking about the area under the curve. Wait. What?

## Failed Experiment

May 11, 2010

Experiments do not always work as planned. Sometimes you may invest a lot of time into a (sub)project only to get no, or only moderately interesting results. Such a (moderately) failed experiment is the topic of this week’s blog post.

Some time ago I wrote a CSV exporter for an application I was writing and, amongst the fields I needed to export, were floating point values. The application was developed under Visual Studio 2005 and I really didn’t like how VS2005’s printf function handled the formats for floats. To export values losslessly, that is, you could read back exactly what you wrote to file, I decided to use the "%e" format specifier for printf. Turned out that it was neither lossless nor minimal!

May 7, 2010

William Poundstone — Prionner’s Dilema — Anchor, 1993, 294 pp. ISBN 978-0385415804