• It includes a trip to a worlds fair by train, including hitching a ride
• I know it's 1876
• The principals are like some wonderful women I know
• Reference to Maine's marine/trade heritage

• Betsy gets a bit of cash from a vistor. She sallies forth, walking to the station but before she get there she hitches a ride on a frieght. At the Philadelphia Centennial she befriends everyone, buys gifts for here friends and comes home.

From virtually nothing in 2000, the industry today can boast 1.5 GW of installed offshore wind capacity, of which 334 MW – more than one fifth – was installed in 2008 alone, see Figure 1, (below). An additional 1.5 GW is currently under construction, and Douglas-Westwood forecasts more than 5 GW will be in the water by 2012.

The theoretical setting of hierarchical Bayesian inference is gaining acceptance as a framework for understanding cortical computation. In this paper, we describe how Bayesian belief propagation in a spatio-temporal hierarchical model, called Hierarchical Temporal Memory (HTM), can lead to a mathematical model for cortical circuits. An HTM node is abstracted using a coincidence detector and a mixture of Markov chains. Bayesian belief propagation equations for such an HTM node define a set of functional constraints for a neuronal implementation. Anatomical data provide a contrasting set of organizational constraints. The combination of these two constraints suggests a theoretically derived interpretation for many anatomical and physiological features and predicts several others. ...

Citation: George D, Hawkins J (2009) Towards a Mathematical Theory of Cortical Micro-circuits. PLoS Comput Biol 5(10): e1000532. doi:10.1371/journal.pcbi.1000532 Tagged by mshook under saved, htm, jeffhawkins, neuron, brain, mind, sumulation, math, pdf, ]]> Tue, 13 Oct 2009 09:53:00 -0400 Tagged by mshook under oreilly, excerpt, book, ebook, google, saved, wave, how, architecture, pdafriendly, ]]> Thu, 01 Oct 2009 05:49:00 -0400 (defprocess root (fuzziness) (defvariable blobs #’union) (always (when (eq (read-sensor ’image) ’black) (subprocess (measure-blob) :gradient fuzziness) (setf blobs (list (get-from-sub (measure-blob) blob))))) (avoid (read-sensor ’query) (let ((q (first (read-sensor ’query)))) (cond ((eq q ’blobs) (actuate ’response (regional blobs))) ((eq q ’area) (actuate ’response (fold #’+ (mapcar #’second (regional blobs))))))))) (defprocess measure-blob () (defvariable uid #’max :atomic :base 0 :init (random 1)) (defvariable area #’sum :reduction :base 0 :init 1) (defvariable blob :local) (always (setf blob (list uid area))))

Code to find a set of fuzzy blobs and their areas in a binary image. Each contiguous black area of the image runs a connected measure-blob pro- cess that names it and calculates its area. The set of blobs is collected by the root process and made accessible to the user on the response actuator...

Are there yet ZigBee products on the market?

Yes, there are. Some implement an actual ZigBee stack while others feature a ZigBee ready platform like EmberNet.

Examples in the residential space include Control4 (lighting), Eaton (home automation), Golden Power Manufacturing (sprinklers and thermostats), Hawking Technology (home gateways), Kalirel (heating), Mija (fire extinguishers), Nice (shutters), and TSC Systems (home automation).

Examples in the commercial space include Mija (fire extinguishers), Philips (lighting), Siemens (building automation), and TAC (building automation).

Hohm is a tool that will enable consumers to see their energy consumption over time and recommend ways to save energy. If Microsoft hasn’t hooked up with your utility yet, you can still enter some basic information into Hohm about location and home, and it will use predictive algorithms to predict your energy consumption. If Microsoft has partnered with your utility, Hohm will integrate your historical energy use, and you will eventually see data from smart meters once they have been rolled out. Hohm will eventually be integrated with applications built by third parties.