Category Archives: Online Tools / Apps / Data Sources

residental graywater

Here’s an interesting report on the economics of residential graywater systems. It’s a little wishy-washy (no pun intended, ha) on the numbers, but it has some links and references that could be useful. From a quick skim, it suggests that if you can achieve a savings of about $200 a year, your system will break-even over a typical service life of around 15 years. This is more likely to happen if you have a relatively high number of people in your house and if you have relatively high water rates.

I have a low-tech, essentially free graywater setup. I turn on the shower, wash my hair and face with weird chemicals, stop up the drain, and wash the rest of myself with pure, non-toxic biodegradable soap. Then, I use a bucket to collect water for houseplants and outdoor plants. I check with NOAA online to see if there has been less than an inch of rain over the past 7 days (a very rough rule of thumb for evapotranspiration around here) and to see if there is rain expected over the next day or so. If I’m diligent about this in the summer, I end up not having to get out the hose too often. Combine all this with a rain barrel or two and I would have to get the hose out even less often.

If I were to accidentally pee in the shower…well, I’ll take the 5th on that one but I’m pretty sure the plants wouldn’t mind.

apps for pestering Congress

Here are some apps you can use to pester your elected representatives semi-automatically. Please, do not use them for revenge, stalking, or other nefarious purposes.

  • Countable – sets up a website app to email all your elected representatives the same message with a few clicks (I don’t think this is free though…)
  • Democracy.io – similar email app and free (I think)
  • FaxZero – similar, for faxes

Calling is supposed to be the most effective. If you have the time and motivation to do that, here are a couple articles: Call the Halls and and this Wired article called Congress’ Phone System Is Broken—But It’s Still Your Best Shot.

10-Minute Neighborhood Analysis

This article from Kirkland, Washington describes in detail an interesting scoring scheme they applied to all of their neighborhoods. They have a good run-down on why walkable neighborhoods are good.

The ability to retain, create, and enhance 10 minute neighborhoods has benefits for users of the neighborhood and benefits for the community as a whole.

  • Health. Residents who walk or bike regularly are healthier and therefore walkable communities make it easier to live healthy lifestyles.  According to the Centers for Disease Control and Prevention, people living in walkable neighborhoods get about 35 to 45 more minutes of moderate-intensity physical activity per week and are substantially less likely to be overweight or obese than people of similar socioeconomic status living in neighborhoods that are not walkable

  • Traffic. Residents with convenient access to local goods and services are less likely to drive.  If they do drive, they have a shorter travel distance.  The 10 minute neighborhood acknowledges the value to Kirkland’s transportation system of every trip not taken and every mile not driven.

  • Transit.  Better access to transit equates to more transit users.  Regional data show that people who live within a half mile of a transit node commute less often by single-occupant vehicle (SOV) with a higher percentage using transit, carpooling, and walking or bicycling to work .

  • Demographics.  21 percent of the population aged 65 and older does not drive – and that segment of the population is projected to grow significantly .  Older non drivers need options so they remain engaged with their communities.

  • Clean Air.  Less traffic means cleaner air and less greenhouse gas emissions.

  • Social Connectivity.  Pedestrian activity and local gathering places help build social cohesion and eyes on the street help people feel safer in their communities.

  • Market Forces.  Recent surveys indicate that a majority of Americans want to live in walkable neighborhoods served by good transit .  Those numbers are significantly stronger for younger Americans and those who plan to move in the future, a strong representation of the future real estate market.

  • Stronger Retail.  A local customer base is good for local businesses.

best practices for writing code

Here’s another R post I am saving for my own reference – some best practices for writing code. This is something I actually can say I learned in engineering school – it was a covered in 15 minutes or so in a required intro to computer science course I took around 1994. Perhaps it’s time to brush up. Again, these are skills that are useful these days in many fields beyond just computer science and software development.

relational algebra

R bloggers has a nice post on the theory behind database organization, and some tools that can used to manage and manipulate data through R. Maybe this seems very specialized, but many of our jobs involve dealing with data these days, so this knowledge and tools is potentially relevant to us, and yet I don’t think many of us even in technical fields outside math and computer science learn this stuff in school.

Structure Sensor

Structure Sensor is a gadget that can supposedly measure an entire room and make a 3D computer model of it in seconds.

Capture dense 3D models with the push of a button

When used as a 3D scanner, Structure Sensor allows you to capture dense geometry in real-time. This enables you to simulate real world physics and create high-fidelity 3D models with high-resolution textures in seconds. The possibilities are incredible.

Measure entire rooms all at once

The magic of 3D depth sensing begins with the ability to capture fast, accurate, dimensions of objects and environments.

And Structure Sensor doesn’t just capture one dimension; it captures everything in view, all at once. Large-scale reconstruction tasks are easy with Structure Sensor & Structure SDK.

It’s $379. I don’t deal with interior design personally, but I know that surveying on engineering projects can be incredibly expensive and time-consuming. If there are technologies that could make it quick, cheap and easy, that would be a game changer.

learn about carbon trading and R

This is pretty cool – an interactive website that lets you explore a real-world carbon trading research problem while learning new tricks in R.

Many economists would agree that the most efficient way to fight global warming would be a world-wide tax or an emmission trading system for greenhouse gases. Yet, if only a part of the world implements such a scheme, a reasonable concern is that firms may decide to relocate to other parts of the world, causing job losses and less effective emmission reduction…

In their article ‘Industry Compensation under Relocation Risk: A Firm-Level Analysis of the EU Emissions Trading Scheme’ (American Economic Review, 2014), Ralf Martin, Mirabelle Muûls, Laure B. de Preux and Ulrich J. Wagner study the most efficient way to allocate a fixed amount of free permits among facilities in order to minimize the risk of job losses or carbon leakage. Given their available data, they establish simple alternative allocation rules that can be expected to substantially outperform the current allocation rules used by the EU.

As part of his Master’s Thesis at Ulm University, Benjamin Lux has generated a very nice RTutor problem set that allows you to replicate the insights of the paper in an interactive fashion. You learn about the data and institutional background, run explorative regressions and dig into the very well explained optimization procedures to find efficient allocation rules. At the same time you learn some R tricks, like effective usage of some dplyr functions.

It’s an interesting question at a time when some U.S. states and Canadian provinces have started introducing carbon trading and taxation schemes that differ from their neighbors (sometimes because their neighbors have nothing at all). Perhaps there is a win-win where a policy can gradually phase out less productive, dirtier industries while replacing them with cleaner and higher-value-added industries, then sharing enough of the wealth so everyone benefits.

Nate Silver and college football

I thought Nate Silver only looked at professional sports. I was wrong – here is a cool interactive web page he has put together for college football. The numbers don’t always give you the answers you want to hear though – even if my beloved Gators somehow win all the rest of their games, which would include beating Alabama in the conference championship game, he gives them only a 13% chance of winning the national championship. Another nice thing about Nate Silver – he always explains his methodology.

We’ll be updating the numbers twice weekly: first, on Sunday morning (or very late Saturday evening) after the week’s games are complete; and second, on Tuesday evening after the new committee rankings come out. In addition to a probabilistic estimate of each team’s chances of winning its conference, making the playoff, and winning the national championship, we’ll also list three inputs to the model: their current committee ranking, FPI, and Elo. Let me explain the role that each of these play…

FPI is ESPN’s Football Power Index. We consider it the best predictor of future college games so that’s the role it plays in the model: if we say Team A has a 72 percent chance of beating Team B, that prediction is derived from FPI. Technically speaking, we’re using a simplified version of FPI that accounts for only each team’s current rating and home field advantage; the FPI-based predictons you see on ESPN.com may differ slightly because they also account for travel distance and days of rest…

Our college football Elo ratings are a little different, however. Instead of being designed to maximize predictive accuracy — we have FPI for that — they’re designed to mimic how humans rank the teams instead.4 Their parameters are set so as to place a lot of emphasis on strength of schedule and especially on recent “big wins,” because that’s what human voters have historically done too. They aren’t very forgiving of losses, conversely, even if they came by a narrow margin under tough circumstances. And they assume that, instead of everyone starting with a truly blank slate, human beings look a little bit at how a team fared in previous seasons. Alabama is more likely to get the benefit of the doubt than Vanderbilt, for example, other factors held equal.