Concepton

a device that is generating concepts


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Annual Feedback quantitative analysis

Yes, I am more than 10 years in Intel Electronics and every year I’ve got the annual feedback (called “Focal”). I thought to look at the nature of the work that I am doing by analyzing the semantic data of those documents. From confidentiality reasons I cannot bring parts of it here, but I can show you some quantitative analysis that I ran on the data.

Among various perspectives, I wanted to look at the verbs that are used there to describe my accomplishments (one out of three components together with “strength” and “areas for improvement”). Out of 30 paragraphs (3 each year) and 4.1k words in total, here is the distribution of all top verbs (overall about 200):

Accomplishments-Verbs

The thought was that verbs of accomplishments are the nature of the work. Now, when I look at it, the direction is amazingly correct – this is what I actually did.

Taking “worked” as a baseline (100%), I have calculated the rate for the rest of verbs relatively.

In addition, grouping verbs by their nature (excluding neutral “worked”), I can tell now, precisely how my work looks like:

nature of work

Know yourself. 🙂


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Cellular Automata in excel

Had some time recently while flying from one place to another and played with simple Cellular Automata rules in excel. It is very simple to do – you create a rule within the cell as function of other cells and extend it (you can simply copy/paste) to other cells.

image001

Here, if A2 is equal to B1, we define a value within the cell “Set”, otherwise it remains empty. That’s all.

Now, if we will keep the first row and column empty (let’s call them “boundaries”), while extending the rule to bigger area, we are going to get a beautiful pattern:

image002

Here I took the area of 200×200

The size of the “triangles” are recursive 2N+1 (1,3,7,15,31,63…)

So by very simple rule we have created pretty complex pattern

Now what is interesting that by simple change of the reference cell the pattern complexity can dramatically increase.

If we change the “offset” of the reference cell by one i.e. apply this kind of rule:

image003

We will get the next pattern:

image004

Continue reading


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Network of physical quantities

Had couple of evenings of fever 😦

Took International System of Units (SI units) as a baseline and created a network:

UnitsNet_r2

Description:

Nodes – Physical Quantities. Size of Node is based on OutDegree Ranking (kind of “Importance”). Colors are based on Subject:

net_details

Edges – relation based on Units, expressed in terms of other SI units. Color is based on relation (Blue – multiplier, Red – divider). Width/weight is based on power (log).

Gephi layout – “Force Atlas 2”

You can see that most “important” Physical quantities are basic Length, Mass, Time, but also derived Force and Energy.

Taking a look at the Betweenness Centrality, we can see that Force and Energy are the biggest and then Voltage, Resistance and Charge. Maybe this is why it is so native to learn them first right after the basic physical quantities.

betweenness centrality

Enjoy and feel free to download, modify and correct (surely got some mistakes). If you do, please mention the source 😉

Files: Excel/Gephi


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Skydiving and drones

Even though I have stopped my skydiving when my son was born, I still dream about it and thinking how would it be good to jump out of the plane (with parachute) every time I fly somewhere.

I have ordered a Lily drone and thought it would be good to skydive with the drone. I did my search and found no evidence of such experience.

I assume there would be need in some adjustment in algorithm of the drone to compensate for unusual pattern of required stabilization, when there is a updraft, gyro “feels” the fallout and need to keep a tracking of falling object.

Theoretically this type of motion control requires less energy as it should compensate for difference in air resistance between skydiver and drone (which can vary based on type of exercise) and for stabilization.

Time of flight can be very short e.g. head down freeflying (~260 km/h /160 mph) or style, when speed of fall is more than 400 km/h / 250 mph. It also can be very long e.g. cross-country jumps.

It can be (mainly) vertical or (mainly) horizontal, like in wingsuit flying.

Voltige_ThomasJeannerot2013_Lily

Another critical complication is safety. Not that it is not important on the ground, but in the air it can easily become a deadly move, especially during the parachute opening. To ensure safety the drone has to keep a minimal horizontal distance from the skydiver at any time of the fall and in case of horizontal component of the fall (usually there is some) to avoid being on the way. That keeps some limited area that drone has to stay within. E.g. in case of vertical free fall the drone can be within the green area and outside of red.

drone skydiving safety area

So I assume soon we shall see the amazing views… hard to believe, but even more spectacular than those.

Enjoy!


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Annual pattern of Demand for Laptops

As I am working on analysis of Lenovo company (hobby/investment), here is an interesting chart out of the work.

Beautiful pattern of demand for Laptops (relative demand per week, comparing to an annual average of demand) during the last decade:

Demand for Laptops - annual pattern

The pattern is very precise and stable since 2004 during most of the year except maybe some end of the year behavior inconsistency. Though there are expected two peaks of demand at winter holidays, year-to-year  variance during ww48 to ww52 is still high. Extremely high peaks at 2007 holidays, driven by Intel Core 2 Duo products wave.

You can see a clear back-to-school growth towards August from the (-10%) dead-season of Laptops marketing at Spring.


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Annual pattern of jobs searching

Are you looking for a job? Most probably this is not a coincidence. Eventually there is a clear annual pattern in amount of people searching for new opportunities.

Here is a normalized relative pattern of amount of people searching for a jobs for a last decade.

Data is based on worldwide statistics based on millions of people and can be used as a model for Human Resource organizations, headhunters or just people that are part of the trend.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

X-axis is weeks (1-52), Y-axis is growth in jobs hunting comparing to the average of the year.

We see a nice and clear behavioral pattern that shows a gradual decline throughout the autumn to the annual minimum of job searches by the end of the year and the slight spike before holidays (people that remind that they need money for presents?). Then enormous spike to the annual maximum at the beginning of the year (motivation to change things in the new year? worldwide layoffs pattern?) and then spring decline followed by growth to a summer “hill”.

Same, but with average profile (Rsq > 0.8):

WW Job Search Profile

What can I say? In my company this profile would be one of base components of HR organization budget. I find it cool.