July 13, 2013

Maps, Models, and Concepts, July edition

Here are some maps, models, and concepts reposted from my micro-blog, Tumbld Thoughts. This is a mash-up of recent books and articles in my reading queue, plus recent features from around the web. The order is: I (Nearly-decomposable Systems), II (Rube Goldberg Mechanisms), III (a profile of Elon Musk's Hyperloop), and IV (Maps + Metadata).

I. Nearly-decomposable Systems

This concept was originally proposed in Chapter 4 of "Sciences of the Artificial" by Herbert A. Simon (Chapter 4 is entitled "Architecture of Complexity"). The focus is on a concept called "nearly-decomposable systems".

In the modern practice of algorithmic representation, decomposability enables one to represent a complex system as a strict hierarchy. By contrast, nearly-decomposable systems can be found in systems where short-run behavior is statistically independent but long-run behavior is dependent in an aggregate fashion. While discrete states appear to exist at static intervals, examining the dynamics reveal interactions (or overlap) between these states. 

One example of this can be seen in the above image, which is adapted from Figure 7. A system is partitioned into 8 spatially non-overlapping components (A1, A2, A3, B2, B2, C1, C2, C3). A sparse matrix (top left) can then be constructed to model the selective functional interactivity between these components (discrete states). In this case, short-run behavior is restricted to interactions within each state, while long-run behavior characterizes the interactions between states. Overall, intra-component linkages (e.g. interactions within A1) are greater than inter-component linkages (e.g. interactions between A1 and B2). 

In Chapter 4, Simon applies this concept to the behavior of diffusing particles in physiochemical systems. However, in systems with autonomous intelligence (e.g. social systems), agents (the equivalent of diffusing particles) can influence and communicate with each other. This concept can also be applied to hierarchical systems (e.g. social and biological complexity). In such cases, the distinction between "broad" vs. "narrow" hierarchies (e.g. hierarchical span) becomes important. 

For a related concept as applied to systems biology, please see: 

Alicea, B.   The Curse of Orthogonality. Synthetic Daisies blog, October 3 (2011).

Further Reading:

Agre, P.E.   Hierarchy and History in Simon's "Architecture of Complexity". Journal of the Learning Sciences, 12(3) 2003.

Bentley, J.L. and Saxe, J.B.   Decomposable searching problems I. Static-to-dynamic transformation. Journal of Algorithms, 1(4), 301-358 (1980).

Feigenbaum, E.A.   Retrospective: Herbert A. Simon, 1916-2001. Science, 291(5511), 2107 (2001).

Simon, H.A.   Near-decomposability and the speed of evolution. Industrial and Corporate Change, 11(3), 587-599.

Simon, H.A.   Sciences of the Artificial. MIT Press, Cambridge, MA (1969).

II. Rube Goldberg (e.g. convoluted, non-optimal) Mechanisms

Happy (posthumous) Birthday (July 4th) to Rube Goldberg, the father of the Rube Goldberg machine [1]. Rube Goldberg machines provide a convoluted way to accomplish something that is otherwise simple. For example, to get sand out of a pair of shoes, one could take their shoes off, turn them upside down, and tap them.

In the Rube Goldberg universe, however, you would have to build a complex machine with many degrees of freedom to accomplish the same feat. His creations were massively inefficient, and that's the whole point -- if your worldview is one of parsimony, you will find his comics humorously absurd.

Given that his birthday falls on July 4 (US Independence Day), the associated Google Doodle (from 2010) features a seven-step machine that lights a firecracker. But can Rube Goldberg machines be useful? For more on this, check out a few Synthetic Daisies blog posts [2] on the application of Rube Goldberg-like machines to systems biology and evolution.

In this case, we are evaluating viable function in the context of maximal convolution -- in other case, the more steps to accomplish a task, the better. Perhaps this [3] is a biologically-plausible alternative to the view of evolution as parsimony.

III. Conceptual Porn for Technology Visionaries

Tech visionaries unite! I have run across a critical mass of articles on Elon Musk's proposal to build a high-speed transportation system called the "Hyperloop" [4]. Musk has described it as "a cross between the Concorde, a railgun, and an air hockey table". Supposedly better than high-speed rail, airplanes, or electric vehicles.

The hyperloop concept seems to build off of a number of existing technologies [5], some more developed for commercial use than others. It is not a vacuum tube nor a conventional rail system, although it incorporates both of these design elements. A version of what Musk is envisioning is similar to the Evacuated Tube Transport system, patented by Daryl Oster (founder of ET3 technologies) [6].

How does it work and is it simply hype? See these popular news features from Gizmag.comAutoblog
Greenand The Atlantic Wire for more information. Is this fringe science? Read the book "Physics on the Fringe" [7] and decide for yourself.

IV. Maps + Metadata Tell Interesting Tales

The first set of layered maps are from the NASA/NOAA Green project. The goal of this joint project is to make a remotely-sensed map of the earth's vegetation (land mass vegetation only) using data from the Suomi NPP satellite.

In this YouTube video, it is explained that land cover and vegetation changes can have an effect on weather variability. Viewing these processes over the course of a year (animated in the video) can help us understand interactions between the biosphere and atmosphere. 

Examples of this are shown above. The pictures (from top) represent: the red deserts of Australia (shown as white expanses), snowcover in North America, the grasslands in the Florida everglades, and deforestation in East Africa.

The second set of layered maps are brought to us in the form of a really cool video animation from Cube Cities and Google Earth. Specifically, this is a time lapse of Chicago's skyline and its growth from 1865 (perspective view) to 2014 (birds-eye view). To illustrate the differences, I have screen-captured selected years and placed them in series. The buildings are 3-D models superimposed on a 2-D map of the city. Quite impressive.


[1] Leibach, J.   Rube Goldberg Mashup. Science Friday blog, July 4 (2013).

[2] Alicea, B.   Machinery of Biocomplexity, new arXiv paper. Synthetic Daisies blog, April 19 (2011) AND Non-razors, unite! Synthetic Daisies blog, January 30 (2009)

[3] Bottom figure (minimal biological model) is from: Alicea, B.   The "Machinery" of Biocomplexity: understanding non-optimal architectures in biological systems. arXiv: 1104.3559 [q-bio.QM] (2011).

[4] Basulto, D.   Is the Hyperloop the Future of Transportation? BigLoop blog, June 12 (2013).

[5] For more information on these technologies, please see the following list:

d) VHST technology. For more information, please see: Salter, R.M. The Very High-speed Transit (VHST) System. Rand Corporation (1972).

See also the following patent document: Oster, D.   Evacuated tube transport. US5950543. USPTO (1999).

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