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QA/QC version based on v22 of EPA SWMM 5 with the ability to read older SWMM 5 OUT files. swmm5.dll Epaswmm5.exe
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Robert Dickinson commented on Robert Dickinson's group 'Stream of Information'
Video: How Snowflakes Are Formed February 4th, 2012 | Posted by Jaime Menchén in Science Videos This time-lapse video lasts 11 seconds, with no music or voice-over. And still you’ll want to see it over and over again. The…
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This is a galaxy

This is a galaxy. Or is it? A remix of material originally produced for BBC Stargazing Live 2012 If you liked this video, follow me on twitter to hear about ...
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2 blog posts by Robert Dickinson were featured yesterday
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Fateme Fallah replied to Fateme Fallah's discussion 'Uncertainty Analysis'
Dear Lionel, This matter is explained in Appendix D of SWMM manual under the title of “Command line SWMM”. So in MATLAB you can use below format under DOS window: "The address of place that SWMM is there"   input…
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Robert Dickinson commented on Robert Dickinson's group 'Stream of Information'
Now the new images, courtesy of the Suomi NPP satellite (2012): The above two photos are pretty much what you would see with your naked eyes if you were at the altitude of this satellite.  It's humbling to realize that all you…
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glenn gradin, Bryant McDonnell and Lionel joined SWMM5 - Stormwater Management Model Thursday
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Lionel replied to Lionel's discussion 'Linking Matlab with SWMM5'
Thanks Robert for your prompt help!
Thursday
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Lionel replied to Fateme Fallah's discussion 'Uncertainty Analysis'
Hi Fateme Fallah,   I am doing something similar but in my case I am varying the infiltration factor. I am not very good with Matlab so require a bit of help on the coding. I would like to check if you have been successful in your attempt to…
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Linking Matlab with SWMM5

Hi, I am currently trying to use Matlab to create a set of random values and inputting these random values into SWMM 5 to vary the different parameters (e.g. decay constant) so I will get a range of results. Has anyone done it before? Thanks!See More
Discussion posted by Lionel Thursday
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North Carolina City Chooses InfoSewer

North Carolina City Chooses InfoSewerArcGIS Based Sewer Modeling Package Helps Hendersonville, NC Model and Manage Its Collection SystemBroomfield, Colorado, USA, January 31, 2012Innovyze, a leading global innovator of business analytics software and technologies for wet infrastructure, today announced the City of Hendersonville, North Carolina, has selected InfoSewer for ArcGIS (Esri, Redlands, CA) as its sewer modeling platform.InfoSewer has helped define the standard in the industry for…See More
A blog post by Robert Dickinson was featured Tuesday
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North Carolina City Chooses InfoSewer

North Carolina City Chooses InfoSewerArcGIS Based Sewer Modeling Package Helps Hendersonville, NC Model and Manage Its Collection SystemBroomfield, Colorado, USA, January 31, 2012Innovyze, a leading global innovator of business analytics software and technologies for wet infrastructure, today announced the City of Hendersonville, North Carolina, has selected InfoSewer for ArcGIS (Esri, Redlands, CA) as its sewer modeling platform.InfoSewer has helped define the standard in the industry for…See More
Blog post by Robert Dickinson Tuesday
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Robert Dickinson left a comment for oliver kemp
Welcome Oliver!
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oliver kemp is now a member of SWMM5 - Stormwater Management Model Jan 31
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Design Storms

Video posted by Robert Dickinson Jan 31
Robert Dickinson

Patterns and the Stock Market from Frontal Cortex

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Patterns and the Stock Market


Category: Brain & Behavior
Posted on: November 14, 2008 12:55 PM, by Jonah Lehrer


It's one of the more annoying side-effects of the financial collapse: instant updates of the Dow Jones Industrial Average are suddenly everywhere, popping up in the corner of cable news shows, in between weather reports on the radio, highlighted on websites, etc. It's a bizarre form of financial melodrama, as the moods of the market seem to lurch and pivot for no good reason. Yesterday afternoon, on the same day a terrible unemployment report came out, the Dow swung upwards and closed 500 points higher. This morning, it's down 350 points, although nobody seems to know why. This chart captures the recent flux:


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While it's certainly entertaining to spin post-hoc explanations of market activity, it's also utterly futile. The market, after all, is a classic example of a "random walk," since the past movement of any particular stock cannot be used to predict its future movement. This inherent randomness was first proposed by the economist Eugene Fama, in the early 1960's. Fama looked at decades of stock market data in order to prove that no amount of rational analysis or knowledge (unless it was illicit insider information) could help you figure out what would happen next. All of the esoteric tools and elaborate theories used by investors to make sense of the market were pure nonsense. Wall Street was like a slot machine.


Alas, the human mind can't resist the allure of explanations, even if they make no sense. We're so eager to find correlations and causation that, when confronted with an inherently stochastic process - like the DJIA, or a slot machine - we invent factors to fixate on. The end result is a blinkered sort of overconfidence, in which we're convinced we've solved a system that has no solution.


Look, for example, at this elegant little experiment. A rat was put in a T-shaped maze with a few morsels of food placed on either the far right or left side of the enclosure. The placement of the food is randomly determined, but the dice is rigged: over the long run, the food was placed on the left side sixty per cent of the time. How did the rat respond? It quickly realized that the left side was more rewarding. As a result, it always went to the left, which resulted in a sixty percent success rate. The rat didn't strive for perfection. It didn't search for a Unified Theory of the T-shaped maze, or try to decipher the disorder. Instead, it accepted the inherent uncertainty of the reward and learned to settle for the best possible alternative.


The experiment was then repeated with Yale undergraduates. Unlike the rat, their swollen brains stubbornly searched for the elusive pattern that determined the placement of the reward. They made predictions and then tried to learn from their prediction errors. The problem was that there was nothing to predict: the randomness was real. Because the students refused to settle for a 60 percent success rate, they ended up with a 52 percent success rate. Although most of the students were convinced they were making progress towards identifying the underlying algorithm, they were actually being outsmarted by a rat.


So don't listen to those talking heads telling you why the market rose or fell. They're just like those Yalies, convinced they've found a pattern where none exists.


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