Concepton

a device that is generating concepts


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Skills network

Anything related can be a network. Any network got a hidden magic inside. Building a network is unleashing another part of the beauty of this world. And when you do this, when you find the secret clusters, when you connect the lonely entities of existence – then this magic is flowing though this network, enlightening and reviving nodes, breaking out over the invisible strings into the life, connecting everything and everyone.

Our skills are shaped by the templates of education and jobs, by human behaviors and to get a glimpse of this bias we can do a simple experiment.

Let’s build s crawler that is getting LinkedIn skills from many people, connect those skills based on cross-correlation and build a network that is based on highly correlated skills.

Even small amount of people I took (about 150), is giving a network of over 400 correlated skills, connected by 3500 links and lots of interesting insights.

skills_network2

So… Mainly pics and less words.

Parts of the network, related to declared programming language-based networks (per language). Pay attention on differences:languages

Design (Since this is a small network, it is biased by my occupation, so the design is mainly represented by word of semiconductors – doing it widely would expose other meanings of design):

design

…with zoom-in on SOC (System On Chip) skills network (pay attention on lack of connection between “microprocessors” and “dsp”  skills. hhhhh…) :soc

Declared Skills, related to “Microsoft”:microsoft

This one is coming from my MBA friends (“Merges” as an anchor):

MnA

Hmm… Interesting positioning for Leadership skill:Leadership

Strategy cluster:

strategy

Those are just several examples, but the applications of this network are giving a big potential value. Amazing HR models and mode of work, Personal effective definition of skills and positioning… It can take the LinkedIn to a whole new level.

And as usually – Do not forget to Enjoy Your Life!

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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.

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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:

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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:

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We will get the next pattern:

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Back from a long vacation!

Hello! Got back from the long vacation and got lot of new stuff to share. The project I am working on on knowledge  visualization and navigation passed the Proof of Concept stage and I am starting to work on the Business development. Hope to share more very soon. Meanwhile, here is an example of the “Lion” token (gross).

Lion

In addition did 2 courses – Deep Diver and Tec1. Decompression rules 😉

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… and had a great time in Tenerife 🙂

rework

Already working on the next model.


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Analysis of Housing Bubble In Australia and comparison to Israel

This time I am going to analyze a housing bubble that Australia is currently facing. I did it once to model a Real Estate (RE) demand in Israel and wanted to extend it to any other country, which RE market is going through the similar behavior. Well, apparently, it is going to be Australia.

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Google Trends is exposing unique data of demand changes and as a result various micro and macro-economic derivatives. I tried to use this tool to model RE market dynamics in Israel and later in other countries and found interesting behaviors of different markets. In this work we will try to understand a bit better reasons for growth in RE prices, we will try to understand better the market, compare RE markets models in different countries, will try to get tools to predict the market based on different scenarios, we will see the RE price hysteresis and will try to explain it.

First part of the work is only exposure of data with no/minimal conclusions or analysis.

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Train Passengers’ Load Model

Years of taking trains finally caused me to spend some time on a simple question – why people are standing in overloaded trains, while there are available seats at the same train? Apparently simple question might have a bit complex answer.

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First, let’s make few assumptions.

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Technological evolution as function of demand – Part II

In part I we’ve already seen several technologies at various stages with saturated/declined demands and in this part I will bring more examples such as Facebook, Dropbox, gaming market and Crocs.

Sum table:

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