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PostPosted: Fri Feb 08, 2013 11:49 pm 
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I think guys did a fantastic job with the analysis. Incredible work, actually. I just would have held off publishing until we could confirm the abnormalities on sample size larger than 1. Ray did a great job explaining that his results are from an n=1 study, but frankly the Internet doesn't actually pay attention to logical explanations like that... it just works itself into a frenzy. As it has.

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Posted: Fri Feb 08, 2013 11:49 pm 


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PostPosted: Sat Feb 09, 2013 12:06 am 
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If he applied an N >> 1 standard to every product he reviewed he wouldn't review any products. As it was, it was an amazing job he did.

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PostPosted: Sat Feb 09, 2013 12:08 am 
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We only apply it to negative reviews, giving the manufacturer a chance to redeem themselves. Perhaps we are too kind :)

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PostPosted: Sat Feb 09, 2013 12:12 am 
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rchung wrote:
another is to do a robust smooth (like an odd-span median smooth) over the data before doing something like a kernel smooth.


I like exponential smoothing forward and backward then averaging the two, but you need to make sure you do it right or else you get interpolation anomalies.

Bad documentation here.

It produces a nice smooth symmetric impulse response even with randomly spaced data:

Image

So it's robust against drops.

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PostPosted: Sat Feb 09, 2013 1:29 am 
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djconnel wrote:
rchung wrote:
another is to do a robust smooth (like an odd-span median smooth) over the data before doing something like a kernel smooth.


I like exponential smoothing forward and backward then averaging the two, but you need to make sure you do it right or else you get interpolation anomalies.

Yeah, almost any kernel that doesn't have a sharp cut-off works moderately well, though I have't done an exhaustive test of alternatives.


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PostPosted: Sat Feb 09, 2013 1:34 am 
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VNTech wrote:
We only apply it to negative reviews, giving the manufacturer a chance to redeem themselves. Perhaps we are too kind :)


If you get a chance, here are two things we did. First, cadence indoors and out:

Image

Second, for the outdoor ride, a comparison of rpm and crank torque. RPM is on the x-axis, crank torque (in Nm) on the y-axis.

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PostPosted: Sat Feb 09, 2013 3:37 am 
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djconnel wrote:
So it's robust against drops.


Interesting. I notice your blog mentions writing firmware for Garmin. Is this hypothetical, or have you actually written firmware for Garmin?


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PostPosted: Sat Feb 09, 2013 1:31 pm 
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@prendrefeu

I'm afraid the Elsa may even be a little bit heavier than you calculated. The NDS arm you pointed to in the other thread is a Red version. The spindle is no long enough to work with the Elsa. Check out pictures of the Elsa on Quarq's site, or look a current SRAM Quarq BB30. The spindle extends well beyond the DS bearings and is covered by a spacer. The Red crank does not use such a spacer.

I was very excited when I heard there was a new Quarq model with "hollow" crank arms. I was hoping for magical weights similar to what people are posting in the "New Red crank info, must read" thread.


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PostPosted: Sat Feb 09, 2013 3:37 pm 
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Me too, OwenN, me too. :(

SRMs are still very light. The Specialized (re: Lightning) SRM might be the lightest, along with the SRM SiSL.
I need to do some digging to see what weights have been coming up for Power2Max spiders.

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 Post subject: New powermeter rumours
PostPosted: Sat Feb 09, 2013 4:42 pm 
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prendrefeu wrote:
I need to do some digging to see what weights have been coming up for Power2Max spiders.


Attachment:
ImageUploadedByTapatalk1360424552.867844.jpg
ImageUploadedByTapatalk1360424552.867844.jpg [ 109.45 KiB | Viewed 592 times ]

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PostPosted: Sat Feb 09, 2013 5:59 pm 
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^That Power2Max is a lot more than my (admittedly 110bcd) SRM, which is 121 grams.


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PostPosted: Sat Feb 09, 2013 8:13 pm 
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It seems that you need fairly meaty spider construction to have a consistent calibration and be robust against ring changes, at least for Quarq and Power2Max technology. I know this is WW, but I think I'd rather just a bit more reassurance that the data is solid.


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PostPosted: Sun Feb 10, 2013 12:25 am 
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Regarding a lightweight powermeter: I have my fingers crossed that the eeCrank will become a reality and that it will have a removable spider that is compatible with the SRAM Quarq.


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PostPosted: Sun Feb 10, 2013 4:32 am 
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Thanks Tillquist! :thumbup:

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Posted: Sun Feb 10, 2013 4:32 am 


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PostPosted: Mon Feb 11, 2013 8:18 pm 
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rchung wrote:
Yeah, almost any kernel that doesn't have a sharp cut-off works moderately well, though I have't done an exhaustive test of alternatives.


I have. The key thing is how many continuous derivatives your kernel has. If the kernel itself is discontinuous, it works poorly. The standard smoothing used in Training Peaks is discontinuous (flat, then zero). A truncated Gaussian is also discontinuous, but the discontinuity can be quite small. Smooth to two derivatives is cosine-squared evaluated between -π/2 and π/2. This works quite well, but becomes time-consuming for large smoothing distances. The 2-sided exponential is smooth to 0-order, but is first-order discontinuous. It's smoother than the flat kernel, but not as good as the cosine-squared kernel. But it's very efficient to calculate.

The key in the convolution of whatever kernel is to not assume constant values between points, but rather assume linear variation between points. This improves the high-frequency rejection and reduces sensitivity to sampling. This is what I did with the exponential smoothing I described. So you want your kernel when multiplied by a linear interpolation function to be analytically integrable, if possible. With exponents and exponential-like functions, including cosine-squared, this is generally possible.

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