nips nips2008 nips2008-112 nips2008-112-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smola
Abstract: Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this criterion to deal with structured and interdependent observations. This is achieved by modeling the structures using undirected graphical models and comparing the Hilbert space embeddings of distributions. We apply this new criterion to independent component analysis and sequence clustering. 1
[1] Aaronson, J., Burton, R., Dehling, H., Gilat, D., Hill, T., & Weiss, B. (1996). Strong laws for L and U-statistics. Transactions of the American Mathematical Society, 348, 2845–2865.
[2] Altun, Y., Smola, A. J., & Hofmann, T. (2004). Exponential families for conditional random ﬁelds. In UAI.
[3] Bach, F. R., & Jordan, M. I. (2002). Kernel independent component analysis. JMLR, 3, 1–48.
[4] Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems (with discussion). J. Roy. Stat. Soc. B, 36(B), 192–326.
[5] Borovkova, S., Burton, R., & Dehling, H. (2001). Limit theorems for functionals of mixing processes with applications to dimension estimation. Transactions of the American Mathematical Society, 353(11), 4261–4318.
[6] Gretton, A., Fukumizu, K., Teo, C.-H., Song, L., Sch¨ lkopf, B., & Smola, A. (2008). A kernel statistical o test of independence. Tech. Rep. 168, MPI for Biological Cybernetics.
[7] Gretton, A., Herbrich, R., Smola, A., Bousquet, O., & Sch¨ lkopf, B. (2005). Kernel methods for measuro ing independence. JMLR, 6, 2075–2129.
[8] Hammersley, J. M., & Clifford, P. E. (1971). Markov ﬁelds on ﬁnite graphs and lattices. Unpublished manuscript.
[9] Hosseni, S., & Jutten, C. (2003). On the separability of nonlinear mixtures of temporally correlated sources. IEEE Signal Processing Letters, 10(2), 43–46.
[10] Ng, A., Jordan, M., & Weiss, Y. (2002). On spectral clustering: Analysis and an algorithm. In NIPS.
[11] Nguyen, X., Wainwright, M. J., & Jordan, M. I. (2008). Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization. In NIPS.
[12] Shen, H., Jegelka, S., & Gretton, A. (submitted). Fast kernel-based independent component analysis. IEEE Transactions on Signal Processing.
[13] Song, L., Smola, A., Borgwardt, K., & Gretton, A. (2007). Colored maximum variance unfolding. In NIPS.
[14] Song, L., Smola, A., Gretton, A., & Borgwardt, K. (2007). A dependence maximization view of clustering. In Proc. Intl. Conf. Machine Learning.
[15] Song, L., Smola, A., Gretton, A., Borgwardt, K., & Bedo, J. (2007). Supervised feature selection via dependence estimation. In ICML.
[16] Sriperumbudur, B., Gretton, A., Fukumizu, K., Lanckriet, G., & Sch¨ lkopf, B. (2008). Injective hilbert o space embeddings of probability measures. In COLT.
[17] Steinwart, I. (2002). The inﬂuence of the kernel on the consistency of support vector machines. JMLR, 2.
[18] Ziehe, A., & M¨ ller, K.-R. (1998). TDSEP – an efﬁcient algorithm for blind separation using time u structure. In ICANN.


{% load staticfiles %}
KA Lite is an open-source Python project, meaning it is free to download and use. It runs on Linux, Mac, and Windows.
Click below to read the installation instructions.


Book name: {{record.BookName}} Author: {{record.Author}} Publisher: {{record.Publisher}} Pubdate: {{record.Pubdate}} Price buying: {{record.Price}} Price selling: {{record.Sellingprice}} Category: {{record.BookCName}}


Byzantine superpowers Bitcoin With advanced security features, enabling micropayments from BTC that are cheap, fast, and final.
Activating on block #8456789, the Byzantine swap allows for users of the Blue Wallet to claim Byzantine tokens in exchange for their Blue tokens. This feature is available now in the Blue Wallet, but will remain unavailable until the swap is live.
This is to give users adequate time to prepare their BLUE in a Blue Wallet.
Claim BYZ in the Blue Wallet
To monitor the estimated time until the block is mined on Ethereum, you can use the Etherscan block estimation tool: https://etherscan.io/block/countdown/8456789


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TABLE OF INTERACTIONS WITH
PAROXETINE
See also: hyponatremia inducing medications
See also: selective serotonin reuptake inhibitors (SSRIs)
See also: medications that lower the epileptic threshold
See also: medications at the origin of a setononin syndrome
From the French ANSM drug interactions document of September 2016, p. 172
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
CARBAMAZEPINE RxNorm: 2002 ATC: N03AF01 |
Increase of the plasma concentrations of carbamazepine with signs of overdose |
Precaution for use Clinical monitoring, testing of the plasma concentrations of carbamazepine, and possible reduction of the dosage of the carbamazepine during the treatment with the serotoninergic antidepressant and after it is stopped. |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
MEQUITAZINE RxNorm: 29528 ATC: R06AD07 |
Risk of increase of the undesirable effects of the mequitazine, due to inhibition of its metabolism by the enzyme inhibitor |
Not recommended |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
METOPROLOL RxNorm: 6918 ATC: C07AB02 C07FB02 C07CB02 C07BB02 |
Risk of increase of the undesirable effects of the metoprolol, with especially excessive bradycardia, due to inhibition of its metaboilsm by the paroxetine |
Precaution for use Increased clinical monitoring; if needed, adjustment of the dosage of the metoprolol during the length of the treatment with the paroxetine and after it is stopped |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
NEBIVOLOL RxNorm: 31555 ATC: C07AB12 C07BB12 |
Risk of increase of the undesirable effects of the nebivolol, with especially excessive bradycardia, due to inhibition of its metabolism by the antidepressant |
Precaution for use Increased clinical monitoring; if needed adjustment of the dosage of the nebivolol during the length of the treatment with the antidepressant and after it is stopped. |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
PIMOZIDE RxNorm: 8331 ATC: N05AG02 |
Increased risk of ventricular arrhythmias, especially of torsades de pointes |
C0NTRAINDICATION |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
RISPERIDONE RxNorm: 35636 ATC: N05AX08 |
Increase of the active fraction of the risperidone due to decrease of its hepatic metabolism by the paroxetine, with risk of increase of the undesirable effects. |
Precaution for use Clinical monitoring and, if needed, adjustment of the dosage of the risperidone. |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
TAMOXIFEN RxNorm: 10324 ATC: L02BA01 |
Reduction of the effectiveness of the tamoxifen, due to inhibition of the formation of its active metabolite by the paroxetine |
Not recommended |
PAROXETINE RxNorm: 32937 ATC: N06AB05 |
VORTIOXETINE RxNorm: 1455099 ATC: N06AX26 |
Risk of increase of the undesirable effects of the vortioxetine due to large decrease of its hepatic metabolism |
Precaution for use Clinical monitoring and possible adjustment of the dosage of the vortioxetine during the treatment with the paroxetine and after it is stopped. |


Brougher, Kerry, and Kaira M. Cabañas. Yves Klein: with the void, full powers. Minneapolis, MN: Walker Art Center, 2010.
Buchloh, Benjamin H. D. Neo-avant-garde and culture industry essays on European and American art from 1955 to 1975. Cambridge, MA: MIT Press, 2003.: 257-283
Cabañas, Kaira Marie. The Myth of Nouveau Réalisme: Art and the Performative in Postwar France. New Haven: Yale Univ. Press, 2013.
De Duve, Thierry. "Yves Klein, or The Dead Dealer." Translated by Rosalind Krauss. October 49 (Summer 1989): 72-90.
Restany, Pierre, and Klaus Ottmann. Yves Klein: Fire at the Heart of the Void. Putnam, CT: Spring Publications, 2005.


Note: For personal reasons, I will be on hiatus from June 30, 1999 until August 25, 1999. No reviews will be published during that time. -Mac
American Pie 3 stars (Out of 4) Reviewed by Mac VerStandig<EMAIL_ADDRESS>http://www.moviereviews.org June 29, 1999 USA Release Date - July 9, 1999
American Pie is a guilty pleasure at its best, and an outrage at its worst.  However, the same sexual aspects push the movie's R rating closer to "adults only" than the target teenage audience, and the often predictable nature of the work plays as a spoiler as well.
Jim (Jason Biggs), Oz (Chris Klein), Kevin (Thomas Ian Nicholas), and Finch (Eddie Kaye Thomas) have three weeks left in their high school careers and all face a probable realization of their worst nightmare: graduating a virgin. The last straw for them comes when their friend Sherman, long considered a semi-geek, announces his introduction into manhood. Realizing that prom will be their last chance in high school to achieve their goal, the four friends make a pact to help each other and get the job done, no matter what the cost.
Candidates for the group's goal include a choir girl named Heather (Mena Suvari); Kevin's long time girlfriend, Vicky (Tara Reid); Nadia (Shannon Elizabeth's), a foreign exchange student; and some assorted other females. The guys also have friend Jessica (Natasha Lyonne, who is fabulous) to help out and give advice when things get way too bazaar.
The funniest part of the production is a sub plot focusing on Jim in particular, his relationship with his Dad, and a certain act of disparity he commits involving an apple pie. But it is Jim giving a live broadcast over the internet that wins the funniest scene contest.
The MPAA issued American Pie an R rating. However, the film is more deserving of an NC-17 rating that the user friendly R mark. Some of the more offensive scenes include masturbation with a sock, a condom, and the aforementioned baked goods.  If this film doesn't merit an NC-17 mark, then the MPAA needs to start asking itself what does.
One thing American Pie is not lacking is memorable quotes and moments. As the four friends agree to make a pact to lose their virginity, the audience is treated to the most uproariously funny speech since John Belushi addressed the Delta fraternity in another Universal film, National Lampoon's Animal House. This memorable speech ends, of course, with "We will get laid!" And Natasha Lyonne has wonderful advice for her friend who wants to experience her first time in the perfect setting-"it's not a space-shuttle launch. It's sex!" And some of the greatest dating advice ever "Just ask 'em questions and listen to what they have to say and (explicative)."
Unfortunately, American Pie does have some predictable aspects. The production also has the dubious accomplishment of being a high school comedy with a plot that leads to the prom, something that has become nearly synonymous with 1999. Perhaps the most predictable "surprise" of the movie is the revelation of a certain character's prevarication that became central to the plot. But to the credit of the film, the four central character's fate is unknown until the film ends.
American Pie opens with a scrambled video. It is obvious that the video is pornographic and a teenager is getting his "jollies" from it. Ironically there may be no better metaphor for the film itself. It is an entertaining work that seems to have gotten scrambled somewhere in the process, but teenagers will still enjoy every last moment, just as most older audiences will as well.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
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Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


Demonstrates how to use Zapatec.Transport.preloadImages to preload images.
After all the images are loaded, they are displayed.


Software development is hard. Managing projects is hard. Working remotely is hard. Here are some things I'm good at, to help ease the pain.
I like to code things from scratch, and enjoy bringing ideas to life in the browser.
Languages I speak:
Languages I speak for Mobile Dev:
I value simple content structure, clean design patterns, and thoughtful interactions.
Things I enjoy designing:
Here are some of the Dev & Design tools i use.
Quite Good.
— Jane Doe
Quite Good.
— John Doe


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emailform.ws3
# "order" form example
#
# The "customer" fills out a form, say an order form.
# The form data is validated and a confirmation page
# displayed. ALso, a confirmation e-mail is sent to the
# customer.
#
# In addition, logging is used.
# turn on logging
#
# web::logfilter determines which log messages will be sent to the log
# destination. The rule here is: let all log messages pass which have
# facilities that match "*" and which have a level up to and including
# level "debug"
web::logfilter add *.-debug
# define where to send log messages to. Here we use a file
# and again define a log destination based filter, which is again
# "*.-debug" as above
web::logdest add *.-debug file /tmp/websh/emailform.log
# because log directory might not exist in this environment
# (note: in a production environment you make sure that this exists
# at install time. You don't want to create that directory with every request)
catch {file mkdir /tmp/websh}
# utility command to handle an HTML page
proc page {title code} {
web::putx {<title>{web::put $title}</title>

{web::put $title}

}
uplevel $code
web::put "\n"
}
# utility command to handle an html form
proc form {page code} {
web::put "<form method=\"post\" action=\"[web::cmdurl $page]\">"
uplevel $code
web::put "</form>"
}
# define the form where address is entered
proc showForm {error} {
# generate a page with Title "Form"
page "Order Form" {
# generate a form with action "submit"
form "submit" {
web::putx {

Name: {
# if "error" flag is set, show the red error message asking for input
if {$error == 1} {
web::put "Please enter your name\n"
}
}

<input type="text" name="name" value="{web::put [web::htmlify [web::formvar name]]}" size="30">

Address:

<textarea name="addr" rows="4" cols="30" wrap="auto">{web::put [web::htmlify [web::formvar addr]]}</textarea>

E-Mail: {
# if "error" flag is set, ask for valid e-mail address
if {$error == 2} {
web::put "Please enter a valid email addres\n"
}
}

<input type="text" name="email" value="{web::put [web::htmlify [web::formvar email]]}" size="30">

<input type="submit" name="ok" value="Send">
}
}
}
}
# validator:
#
# make sure we have a name of non-zero length.
# Also, make sure the e-mail address is not completely wrong.
proc checkFormData {} {
# check if a value is in the name field
if { [string length [web::formvar name]] < 1} {
# return error code
return 1
}
# log (facility: emailform, level: debug)
web::log emailform.debug {name [web::formvar name] is valid}
# check email
set email [web::formvar email]
# make sure we have alpha-numeric stuff separated by "@"
if {![regexp -nocase {^([a-z._0-9-]+)@([a-z._0-9-]+)\.+([a-z]+)$} \
$email email name domain]} {
# return error code
return 2
}
# check length of domain
if {[string length $domain] < 3} {
return 2
}
web::log emailform.debug {email [web::formvar email] is valid}
# looks good: no error
return 0
}
# sendEmail
#
# create the e-mail message and send it to the given e-mail address
proc sendEmail {} {
# disabled for security reasons, and because there is no
# sendmail on www.apache.org ;-)
return 1
set emailtxt {
Thank you for your submission.
We have recieved the following information:}
append emailtxt "\nName:\n[web::formvar name]\n"
append emailtxt "Address:\n"
append emailtxt [web::formvar addr]
append emailtxt {
Find more information about Webshell at http://tcl.apache.org/websh/
The team.
}
# log message
web::log emailform.debug "e-mail: $emailtxt"
if { [catch {
# Open pipe for e-mail
set fh [open "| /usr/lib/sendmail [web::formvar email]" w]
puts $fh "From<EMAIL_ADDRESS>puts $fh "Subject: websh3 sample application - sample confirmation"
puts $fh ""
puts $fh $emailtxt
close $fh
} cmsg ] } {
return 0
}
return 1
}
proc showErrorPage {} {
page "Error" {
web::putx {
An error occurred while processing your request.
Please {web::put "try"} again

If the problem persists, please contact the
{web::put "<a<EMAIL_ADDRESS>}
}
}
proc showConfirmationPage {} {
page "Confirmation" {
web::putx {

Thank you for your order

We have recieved the following information:

Name:

{web::put [web::htmlify [web::formvar name]]}

Address:

{
# take care of linebreaks in address
regsub -all "\r\n" [web::htmlify [web::formvar addr]] "
" addr
web::put $addr
}

E-Mail:

{web::put [web::htmlify [web::formvar email]]}

You should recieve a confirmation by e-mail shortly.

Note: to prevent misue, sending the actual email is disabled, so please don't wait for the mail ;-)

{web::put "Order more"}
cool stuff.
}
}
}
# register the "default" command
#
# This command will be used whenever no specific command has been specified.
# We use it to show an empty form for address submission.
web::command default {
showForm 0
}
# register command "submit"
#
# This is the "action" of our form. The form data is validated. If
# the formdata is incomplete or invalid, the form is re-displayed with
# an error info, where the original input is displayed as well.
#
# If the data is valid, the confirmation page is shown and
# an e-mail is sent to the specified address.
web::command submit {
if { [set res [checkFormData]] == 0 } {
if {[sendEmail]} {
showConfirmationPage
} else {
showErrorPage
}
} else {
showForm $res
}
}
web::dispatch
Generated by GNU enscript 1.6.3.


{% extends "base.html" %} {% block title %}Complexicator score{% endblock %} {% block content %}
Eh, scratch that. Your life is easy.
{{interpretation}}
>> Retake quiz


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I'm very sorry if this has been covered before. Please direct me to the thread if it exists already...
I've made the circuit for current measurement only using an arduino uno and SCT-013-000.
I initially used a 33 ohm burden resistor, 2 x 10k ohm resistors for the voltage divider and a 10uF capacitor.
I have a 16x2 LCD connected reading out the current every second.
I clamp the CT around an AC cable as well as an electrician's clamp meter for verification.
I read the fairly low current on the clamp meter (1.8A) and continually adjust the calibration constant (and upload to arduino) until the readout on the LCD matches the readout on the clamp meter.
I have a kettle plugged in and I switch it on. The clamp meter reads about 11 amps. The LCD readout from the arduino reads around 9 amps.
If I adjust the calibration constant in the code so the current readout matches the clamp meter, when the kettle is switched off, the current is not accurate at the low amp reading (off by at least 0.5amps).
I tried using a 180ohm burden resistor (so the range is reduced from 0-100amps down to 0-20amps), but the same non-linear results are present.
I guess the problem could be the electrician's clamp meter, but I'm assuming there's more likely an issue with my home built one rather than a commercially produced (and expensive) meter.
Any thoughts about what could be the issue?
Re: Weird current readings
How expensive is your commercial meter, and is it a true RMS meter? What sort of equipment is drawing the 1.8A when the kettle is off?
I've got a fairly popular $100 clamp meter that doesn't do at all well with signals that aren't nice sine waves. The attached trace is the current going into my on-line UPS, which has a whole bunch of electronic devices with nasty SMPSs on the other side of it. You can see it's a pretty ugly signal. My cheap scope, with even cheaper (but calibrated) current probe, thinks the current is 1.808A RMS.
My precision front-end with 3 calibrated CTs wrapped around the feed all think the current is extremely close to 1.801A RMS
My clamp meter flips between 1.2A and 1.3A RMS.
Re: Weird current readings
For kicks I just fed a 1.8A RMS pure sine wave through my clamp meter and it read 1.6 - 1.7A. At an 11A pure sine wave it read 10.8 - 10.9A. So mine seems to naturally under-read a bit, but particularly so if you don't feed it a sine wave.
Re: Weird current readings
Few meters will ever be correct on every wave shape that you can think of. Most budget and mid-range meters read "rectified average scaled rms" - which means they respond to the average value of the waveform after rectification, but the scale is then correct only for a pure sine wave. The form factor (ratio of rms to average) of the wave shape is what matters. Even true rms meters will only be accurate over a limited range of form factor, since they run out of range if the waveform becomes too 'peaky'.
Re: Weird current readings
Thanks for your replies.
The bought clamp meter is a mastech ms2101. So not expensive compared to what's out there, but expensive compared to this home built one (maybe not). Not sure if it's true rms.
the 1.8A is just what the house is using normally (so fridge, computers, things on standby, maybe some lights).
so what's each of your advice to calibrate my arduino? Buy a power supply that can accurately output a set current, and work off that ? Or just do some maths to calculate my calibration constant in the code...?
my arduino project is logging current values over time, so I was hoping it be accurate! For eg, I want to see what my 5kw solar system actually produces at its peak production in different seasons.
But if it's off by even a few amps, I'll get skewed results.
and is it weird that the meter reads 1.8A & 11A (using my initial example) and my arduino reads 1.8A and 9A on the same currents? Like it's not a linear error?
so my results will only be wrong either at high current OR at low current.
or maybe the results are correct, and it's my electrician's meter that's wrong! Arrrgh. Any advice appreciated
Re: Weird current readings
You could rule out my theory (that it may be the non-linear standby loads confusing your clamp meter) by replacing those loads with a known load. You could hack up an extension lead so that you can clamp it, and then re-do your tests with the kettle Vs some other nice simple resistive load at about 2A, and again compare each with your clamp meter.
So you need a ~500W load that can plug into the end of your extension lead, and is nothing more than a heating element (or incandescent light bulbs).
Re: Weird current readings
As far as your commercially produced meter is concerned, you should have details of the accuracy they claim for it. Most probably, it met that specification when it left the factory, whether it still does is open to question. There's a Building Blocks article about the accuracy of meters, that also tells you how to interpret their spec "±(2% + 5)". As the spec doesn't claim "True rms", I think you can take it that it's rectified average, scaled rms.
For your Uno, we know a little more. Experience of problems other users have reported here suggests that interference from the digital circuits can get into the analogue front end and give you a reading of current when there is none. That is easy to determine - put the CT well away from any cable or appliance that generates a magnetic field and see what you get. The other error is one of scale factor, and that is covered in a Building Blocks article. If you know the tolerance of each of the components that you used, you can calculate the limits for "your" meter. Bear in mind that while most errors will be linear, your CT will not be and the curve "bends", so it will tend to read high at medium current and low at high current. You can read more in the report on the YHDC CT.
If the two ranges overlap (at whatever current you choose) then both are "right" to within your ability to measure. If not, then you don't know how far wrong either is, and you need a third reference. If you are that concerned, have you considered borrowing or hiring a good quality calibrated meter to calibrate against?
As a rider to dBC's answer, you can multiply the current by passing several turns through your CT (and your clamp ammeter), so a 1 A load can give you 1, 2, 3, 4, 5, 6 A etc so you have many scale points at which to compare the meters.
And by writing your own sketch to rectify and calculate the average (rather than rms as emonLib does) and then multiply by 1.11 - the form factor of a sine wave, you could have 'your' meter reading the same quantity as the commercial one.
Re: Weird current readings
your CT will not be and the curve "bends"
Interesting. I knew we all had to deal with phase shift varying with current, but you guys have the added burden of amplitude errors as well? Is that down to the relatively high voltages you try to produce across your burden resistor?
In my application I use the 333mV style CTs, and they give excellent amplitude response across a wide current range. You inspired me to re-test that just now. I tested a 20A (Ch6) and a 50A (Ch8) CT at: 20mA, 50mA, 2A, 10A, 20A, 35A and 50A.
You can see in the attached readouts, the only disappointment was the 50A CT trying to read 20mA, but at that level it's only outputting 133uV. Both CTs performed well all the way down to 1/1000th of their rated max current. Of course, having 24-bit A/Ds helps measure that finely.
Re: Weird current readings
Take a 100 A CT up to 250 A and the curve is very nearly flat - see the report on the YHDC one! That was measured into a multimeter requiring a maximum of 200 mV to drive it - it's the magnetic material (ferrite in the case of the YHDC) saturating.
Re: Weird current readings
Thanks for your replies.
The only thing I could think of that I have around me that could help me is my solar system...my inverter reads out the wattage it's outputting. So I clamped my arduino clamp around the AC output, changed the code to display wattage, then compared the two at different output levels as the sun changed. i figured this would be a good test, as the sine wave wouldn't change with the changing current.
I set the calibration constant to a level that read about correct at 1800 watts. Then at about 1000 watts, the arduino was over reading by only about 50 watts. At 200 watts, the arudino was over reading by 150 watts.
These reading were quite acceptable by my standards! I was quite happy.
Interestingly, the commercial clamp meter was under reading the output by about 150 watts when it was outputting about 1250 watts. I should do some more tests to see it's accuracy at different currents...
Now that I think of it, I'm not sure if the inverter is displaying the AC wattage, or the DC input wattage.... Surely it must be the AC output...
Re: Weird current readings
I know mine displays AC wattage, and like you, I would guess that's the norm.
I assume you just used a nominal voltage to turn your CT reading into a wattage? That will probably work fine for the purpose of this linearity experiment, since your inverter is probably only outputting real power, and no matter what voltage you chose, you would have calibrated away any error when you matched them at 1800W.
One big assumption you've made though is that the grid voltage is constant. I don't know what it's like over there, but in these parts it varies by a good 10V, often quite abruptly, so if yours is similar for example, that would introduce an error of about 4% there alone. At least some of that variation is down to the massive PV penetration here where you can end up with big residential areas producing massive amounts of power, and nobody home to use it. It eventually finds it way to shops, factories and office blocks that want it, but the resistance along the way tends to push the voltage up at the residential end. So it's conceivable that your grid voltage when you measured the 1800 watts was higher than when you measured the 200 watts, which would upset your linearity. Does your inverter display the AC voltage as well?
There are some interesting graphs in this article: http://reneweconomy.com.au/2013/confessions-of-a-network-operator-solar-changes-the-game-35541 . We now have some major 11kV feeders that run backwards during the middle of the day.
the commercial clamp meter was under reading the output by about 150 watts
I've seen claims in these forums by reliable contributors that the current signal coming out of their inverters is not a sine wave, but rather sags near the peaks. If yours is doing that, then again it could be confusing the clamp meter's RMS calculation. I've never seen that with my inverter. Whenever I've clamped it, it's always produced a very clean sine wave, perfectly aligned with the voltage.
Re: Weird current readings
Good, I hope mine is AC wattage too.
Yes the inverter outputs the AC voltage. It was pretty stable staying within 247-249v. So I was confident with my multiplication to wattage.


15 February 1996
Disease Outbreak Reported
During the period 12-15 February, cases of cholera were reported in the following African countries: Burkina Faso, Cap Verde, Mali, Senegal and in the Americas in Argentina and Ecuador (mainly Imbabura Province).


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Football Fan 'Electrocuted By His Phone' As He Watched A Match On His Handset
by Peace FM OnlineA chef who liked to stay up late watching football on his phone is believed to have died after being electrocuted by the handset.
Somchai Singkhorn, 40, was last seen on Tuesday night laying on his mattress with a can of beer, watching TV on his phone with his headphones plugged in.
But Somchai, who worked as a restaurant cook, was found dead the next morning in his room in Samut Prakan, Thailand, with burn marks on his arm and neck where they had touched the cable.
The phone was plugged into the mains and the earphones were resting across Somchai's arm, face and neck.
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Not great
OnePlus security breach leaks emails, phone numbers and addresses
This is the second breach the company has faced in two years.
by Daniel BaderWhat you need to know
- OnePlus is emailing customers about a database breach.
- Company says passwords and payment info are safe, but emails, contact numbers and shipping addresses were leaked.
- It's not clear when the breach happened or how many people were affected.
OnePlus is emailing customers with a boilerplate message about "order information [that] was accessed by an unauthorized party." The company says that while passwords, payment information and account information is safe, "name, contact number, email and shipping addresses may have been exposed."
In the email, which does not include the number of people affected nor how far back into OnePlus's customer history the breach goes, the company says that "We took immediate steps to stop the intruder and reinforce security. Right now, we are working with the relevant authorities to further investigate this incident and protect your data." Two people at Android Central received the email, too, with one not using the OnePlus store since buying the OnePlus 6 release back in mid-2018.
This isn't the first time OnePlus has reported a data breach. Back in January 2018, the company said that 40,000 users of its online store were affected by a malicious script added to its payment code that scraped the credit and debit card data of people buying products on its store.
A statement from OnePlus mirrored the wording in the email sent to customers, noting:
OnePlus has notified impacted users that we have discovered that some of their order information was accessed by an unauthorized party. We can confirm that all payment information, passwords and accounts are safe, but certain users' name, contact number, email and shipping address may have been exposed.
We took immediate steps to stop the intruder and reinforce security. Before making this public, we informed our impacted users by email. Right now, we are working with the relevant authorities to further investigate this incident.
We are deeply sorry about this, and are committed to doing everything in our power to prevent further such incidents. For more information, please visit the forums.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.


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Rush hour delays on A5 near Shrewsbury after crash
by Rory SmithCommuters faced rush hour delays on the A5 near Shrewsbury today following a two-vehicle crash.
One lane of the dual carriageway was blocked, heading eastbound just north of Emstrey Island.
The crash, involving a red 4x4 and an HGV, took place at about 8am and motorists were still reporting delays at 8.30am.
West Mercia Police were in attendance, diverting traffic around the incident.
AA Traffic News reported: "Partially blocked and queuing traffic due to accident on A5 both ways around B4380 Emstrey Bank (Emstrey Island).
"Congestion to A49/Preston Island and A458 Weeping Cross."


graphlab.SFrame¶
-
class
graphlab.
SFrame
(data=list(), format='auto')¶ A tabular, column-mutable dataframe object that can scale to big data. The data in SFrame is stored column-wise on the GraphLab Server side, and is stored on persistent storage (e.g. disk) to avoid being constrained by memory size. Each column in an SFrame is a size-immutable
SArray
, but SFrames are mutable in that columns can be added and subtracted with ease. An SFrame essentially acts as an ordered dict of SArrays.Currently, we support constructing an SFrame from the following data formats:
- csv file (comma separated value)
- sframe directory archive (A directory where an sframe was saved previously)
- general text file (with csv parsing options, See
read_csv()
) - a Python dictionary
- pandas.DataFrame
- JSON
- Apache Avro
- PySpark RDD
and from the following sources:
- your local file system
- the GraphLab Server’s file system
- HDFS
- Amazon S3
- HTTP(S).
Only basic examples of construction are covered here. For more information and examples, please see the User Guide, API Translator, How-Tos, and data science Gallery.
Parameters: data : array | pandas.DataFrame | string | dict, optional
The actual interpretation of this field is dependent on the
format
parameter. Ifdata
is an array or Pandas DataFrame, the contents are stored in the SFrame. Ifdata
is a string, it is interpreted as a file. Files can be read from local file system or urls (local://, hdfs://, s3://, http://).format : string, optional
Format of the data. The default, “auto” will automatically infer the input data format. The inference rules are simple: If the data is an array or a dataframe, it is associated with ‘array’ and ‘dataframe’ respectively. If the data is a string, it is interpreted as a file, and the file extension is used to infer the file format. The explicit options are:
- “auto”
- “array”
- “dict”
- “sarray”
- “dataframe”
- “csv”
- “tsv”
- “sframe”.
See also
Notes
- When reading from HDFS on Linux we must guess the location of your java installation. By default, we will use the location pointed to by the JAVA_HOME environment variable. If this is not set, we check many common installation paths. You may use two environment variables to override this behavior. GRAPHLAB_JAVA_HOME allows you to specify a specific java installation and overrides JAVA_HOME. GRAPHLAB_LIBJVM_DIRECTORY overrides all and expects the exact directory that your preferred libjvm.so file is located. Use this ONLY if you’d like to use a non-standard JVM.
Examples
>>> import graphlab >>> from graphlab import SFrame
Construction
Construct an SFrame from a dataframe and transfers the dataframe object across the network.
>>> df = pandas.DataFrame() >>> sf = SFrame(data=df)
Construct an SFrame from a local csv file (only works for local server).
>>> sf = SFrame(data='~/mydata/foo.csv')
Construct an SFrame from a csv file on Amazon S3. This requires the environment variables: AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY to be set before the python session started. Alternatively, you can use
graphlab.aws.set_credentials()
to set the credentials after python is started andgraphlab.aws.get_credentials()
to verify these environment variables.>>> sf = SFrame(data='s3://mybucket/foo.csv')
Read from HDFS using a specific java installation (environment variable only applies when using Linux)
>>> import os >>> os.environ['GRAPHLAB_JAVA_HOME'] = '/my/path/to/java' >>> from graphlab import SFrame >>> sf = SFrame("hdfs://mycluster.example.com:8020/user/myname/coolfile.txt")
An SFrame can be constructed from a dictionary of values or SArrays:
>>> sf = gl.SFrame({'id':[1,2,3],'val':['A','B','C']}) >>> sf Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
Or equivalently:
>>> ids = SArray([1,2,3]) >>> vals = SArray(['A','B','C']) >>> sf = SFrame({'id':ids,'val':vals})
It can also be constructed from an array of SArrays in which case column names are automatically assigned.
>>> ids = SArray([1,2,3]) >>> vals = SArray(['A','B','C']) >>> sf = SFrame([ids, vals]) >>> sf Columns: X1 int X2 str Rows: 3 Data: X1 X2 0 1 A 1 2 B 2 3 C
If the SFrame is constructed from a list of values, an SFrame of a single column is constructed.
>>> sf = SFrame([1,2,3]) >>> sf Columns: X1 int Rows: 3 Data: X1 0 1 1 2 2 3
Parsing
The
graphlab.SFrame.read_csv()
is quite powerful and, can be used to import a variety of row-based formats.First, some simple cases:
>>> !cat ratings.csv user_id,movie_id,rating 10210,1,1 10213,2,5 10217,2,2 10102,1,3 10109,3,4 10117,5,2 10122,2,4 10114,1,5 10125,1,1 >>> gl.SFrame.read_csv('ratings.csv') Columns: user_id int movie_id int rating int Rows: 9 Data: +---------+----------+--------+ | user_id | movie_id | rating | +---------+----------+--------+ | 10210 | 1 | 1 | | 10213 | 2 | 5 | | 10217 | 2 | 2 | | 10102 | 1 | 3 | | 10109 | 3 | 4 | | 10117 | 5 | 2 | | 10122 | 2 | 4 | | 10114 | 1 | 5 | | 10125 | 1 | 1 | +---------+----------+--------+ [9 rows x 3 columns]
Delimiters can be specified, if ”,” is not the delimiter, for instance space ‘ ‘ in this case. Only single character delimiters are supported.
>>> !cat ratings.csv user_id movie_id rating 10210 1 1 10213 2 5 10217 2 2 10102 1 3 10109 3 4 10117 5 2 10122 2 4 10114 1 5 10125 1 1 >>> gl.SFrame.read_csv('ratings.csv', delimiter=' ')
By default, “NA” or a missing element are interpreted as missing values.
>>> !cat ratings2.csv user,movie,rating "tom",,1 harry,5, jack,2,2 bill,, >>> gl.SFrame.read_csv('ratings2.csv') Columns: user str movie int rating int Rows: 4 Data: +---------+-------+--------+ | user | movie | rating | +---------+-------+--------+ | tom | None | 1 | | harry | 5 | None | | jack | 2 | 2 | | missing | None | None | +---------+-------+--------+ [4 rows x 3 columns]
Furthermore due to the dictionary types and list types, can handle parsing of JSON-like formats.
>>> !cat ratings3.csv business, categories, ratings "Restaurant 1", [1 4 9 10], {"funny":5, "cool":2} "Restaurant 2", [], {"happy":2, "sad":2} "Restaurant 3", [2, 11, 12], {} >>> gl.SFrame.read_csv('ratings3.csv') Columns: business str categories array ratings dict Rows: 3 Data: +--------------+--------------------------------+-------------------------+ | business | categories | ratings | +--------------+--------------------------------+-------------------------+ | Restaurant 1 | array('d', [1.0, 4.0, 9.0, ... | {'funny': 5, 'cool': 2} | | Restaurant 2 | array('d') | {'sad': 2, 'happy': 2} | | Restaurant 3 | array('d', [2.0, 11.0, 12.0]) | {} | +--------------+--------------------------------+-------------------------+ [3 rows x 3 columns]
The list and dictionary parsers are quite flexible and can absorb a variety of purely formatted inputs. Also, note that the list and dictionary types are recursive, allowing for arbitrary values to be contained.
All these are valid lists:
>>> !cat interesting_lists.csv list [] [1,2,3] [1;2,3] [1 2 3] [{a:b}] ["c",d, e] [[a]] >>> gl.SFrame.read_csv('interesting_lists.csv') Columns: list list Rows: 7 Data: +-----------------+ | list | +-----------------+ | [] | | [1, 2, 3] | | [1, 2, 3] | | [1, 2, 3] | | [{'a': 'b'}] | | ['c', 'd', 'e'] | | [['a']] | +-----------------+ [7 rows x 1 columns]
All these are valid dicts:
>>> !cat interesting_dicts.csv dict {"classic":1,"dict":1} {space:1 seperated:1} {emptyvalue:} {} {:} {recursive1:[{a:b}]} {:[{:[a]}]} >>> gl.SFrame.read_csv('interesting_dicts.csv') Columns: dict dict Rows: 7 Data: +------------------------------+ | dict | +------------------------------+ | {'dict': 1, 'classic': 1} | | {'seperated': 1, 'space': 1} | | {'emptyvalue': None} | | {} | | {None: None} | | {'recursive1': [{'a': 'b'}]} | | {None: [{None: array('d')}]} | +------------------------------+ [7 rows x 1 columns]
Saving
Save and load the sframe in native format.
>>> sf.save('mysframedir') >>> sf2 = graphlab.load_sframe('mysframedir')
Column Manipulation
An SFrame is composed of a collection of columns of SArrays, and individual SArrays can be extracted easily. For instance given an SFrame:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']}) >>> sf Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
The “id” column can be extracted using:
>>> sf["id"] dtype: int Rows: 3 [1, 2, 3]
And can be deleted using:
>>> del sf["id"]
Multiple columns can be selected by passing a list of column names:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C'],'val2':[5,6,7]}) >>> sf Columns: id int val str val2 int Rows: 3 Data: id val val2 0 1 A 5 1 2 B 6 2 3 C 7 >>> sf2 = sf[['id','val']] >>> sf2 Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
You can also select columns using types or a list of types:
>>> sf2 = sf[int] >>> sf2 Columns: id int val2 int Rows: 3 Data: id val2 0 1 5 1 2 6 2 3 7
Or a mix of types and names:
>>> sf2 = sf[['id', str]] >>> sf2 Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
The same mechanism can be used to re-order columns:
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']}) >>> sf Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C >>> sf[['val','id']] >>> sf Columns: val str id int Rows: 3 Data: val id 0 A 1 1 B 2 2 C 3
Element Access and Slicing
SFrames can be accessed by integer keys just like a regular python list. Such operations may not be fast on large datasets so looping over an SFrame should be avoided.
>>> sf = SFrame({'id':[1,2,3],'val':['A','B','C']}) >>> sf[0] {'id': 1, 'val': 'A'} >>> sf[2] {'id': 3, 'val': 'C'} >>> sf[5] IndexError: SFrame index out of range
Negative indices can be used to access elements from the tail of the array
>>> sf[-1] # returns the last element {'id': 3, 'val': 'C'} >>> sf[-2] # returns the second to last element {'id': 2, 'val': 'B'}
The SFrame also supports the full range of python slicing operators:
>>> sf[1000:] # Returns an SFrame containing rows 1000 to the end >>> sf[:1000] # Returns an SFrame containing rows 0 to row 999 inclusive >>> sf[0:1000:2] # Returns an SFrame containing rows 0 to row 1000 in steps of 2 >>> sf[-100:] # Returns an SFrame containing last 100 rows >>> sf[-100:len(sf):2] # Returns an SFrame containing last 100 rows in steps of 2
Logical Filter
An SFrame can be filtered using
>>> sframe[binary_filter]
where sframe is an SFrame and binary_filter is an SArray of the same length. The result is a new SFrame which contains only rows of the SFrame where its matching row in the binary_filter is non zero.
This permits the use of boolean operators that can be used to perform logical filtering operations. For instance, given an SFrame
>>> sf Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
>>> sf[(sf['id'] >= 1) & (sf['id'] <= 2)] Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B
See
SArray
for more details on the use of the logical filter.This can also be used more generally to provide filtering capability which is otherwise not expressible with simple boolean functions. For instance:
>>> sf[sf['id'].apply(lambda x: math.log(x) <= 1)] Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B
Or alternatively:
>>> sf[sf.apply(lambda x: math.log(x['id']) <= 1)]
Create an SFrame from a Python dictionary.>>> from graphlab import SFrame >>> sf = SFrame({'id':[1,2,3], 'val':['A','B','C']}) >>> sf Columns: id int val str Rows: 3 Data: id val 0 1 A 1 2 B 2 3 C
Methods
SFrame.add_column (data[, name]) |
Add a column to this SFrame. |
SFrame.add_columns (data[, namelist]) |
Adds multiple columns to this SFrame. |
SFrame.add_row_number ([column_name, start]) |
Returns a new SFrame with a new column that numbers each row sequentially. |
SFrame.append (other) |
Add the rows of an SFrame to the end of this SFrame. |
SFrame.apply (fn[, dtype, seed]) |
Transform each row to an SArray according to a specified function. |
SFrame.column_names () |
The name of each column in the SFrame. |
SFrame.column_types () |
The type of each column in the SFrame. |
SFrame.copy () |
Returns a shallow copy of the sframe. |
SFrame.dropna ([columns, how]) |
Remove missing values from an SFrame. |
SFrame.dropna_split ([columns, how]) |
Split rows with missing values from this SFrame. |
SFrame.dtype () |
The type of each column. |
SFrame.export_csv (filename[, delimiter, ...]) |
Writes an SFrame to a CSV file. |
SFrame.export_json (filename[, orient]) |
Writes an SFrame to a JSON file. |
SFrame.fillna (column, value) |
Fill all missing values with a given value in a given column. |
SFrame.filter_by (values, column_name[, exclude]) |
Filter an SFrame by values inside an iterable object. |
SFrame.flat_map (column_names, fn[, ...]) |
Map each row of the SFrame to multiple rows in a new SFrame via a function. |
SFrame.from_odbc (db, sql[, verbose]) |
Convert a table or query from a database to an SFrame. |
SFrame.from_rdd (rdd, cur_sc) |
Convert a Spark RDD into an SFrame. |
SFrame.from_sql (conn, sql_statement[, ...]) |
Convert the result of a SQL database query to an SFrame. |
SFrame.groupby (key_columns, operations, *args) |
Perform a group on the key_columns followed by aggregations on the columns listed in operations. |
SFrame.head ([n]) |
The first n rows of the SFrame. |
SFrame.is_materialized () |
Returns whether or not the SFrame has been materialized. |
SFrame.join (right[, on, how]) |
Merge two SFrames. |
SFrame.materialize () |
For an SFrame that is lazily evaluated, force the persistence of the SFrame to disk, committing all lazy evaluated operations. |
SFrame.num_cols () |
The number of columns in this SFrame. |
SFrame.num_columns () |
The number of columns in this SFrame. |
SFrame.num_rows () |
The number of rows in this SFrame. |
SFrame.pack_columns ([columns, ...]) |
Pack columns of the current SFrame into one single column. |
SFrame.print_rows ([num_rows, num_columns, ...]) |
Print the first M rows and N columns of the SFrame in human readable format. |
SFrame.random_split (fraction[, seed]) |
Randomly split the rows of an SFrame into two SFrames. |
SFrame.read_csv (url[, delimiter, header, ...]) |
Constructs an SFrame from a CSV file or a path to multiple CSVs. |
SFrame.read_csv_with_errors (url[, ...]) |
Constructs an SFrame from a CSV file or a path to multiple CSVs, and returns a pair containing the SFrame and a dict of filenames to SArrays indicating for each file, what are the incorrectly parsed lines encountered. |
SFrame.read_json (url[, orient]) |
Reads a JSON file representing a table into an SFrame. |
SFrame.remove_column (name) |
Remove a column from this SFrame. |
SFrame.remove_columns (column_names) |
Remove one or more columns from this SFrame. |
SFrame.rename (names) |
Rename the given columns. |
SFrame.sample (fraction[, seed]) |
Sample the current SFrame’s rows. |
SFrame.save (filename[, format]) |
Save the SFrame to a file system for later use. |
SFrame.select_column (key) |
Get a reference to the SArray that corresponds with the given key. |
SFrame.select_columns (keylist) |
Selects all columns where the name of the column or the type of column is included in the keylist. |
SFrame.show ([columns, view, x, y]) |
Visualize the SFrame with GraphLab Create canvas . |
SFrame.sort (sort_columns[, ascending]) |
Sort current SFrame by the given columns, using the given sort order. |
SFrame.split_datetime (expand_column[, ...]) |
Splits a datetime column of SFrame to multiple columns, with each value in a separate column. |
SFrame.stack (column_name[, new_column_name, ...]) |
Convert a “wide” column of an SFrame to one or two “tall” columns by stacking all values. |
SFrame.swap_columns (column_1, column_2) |
Swap the columns with the given names. |
SFrame.tail ([n]) |
The last n rows of the SFrame. |
SFrame.to_dataframe () |
Convert this SFrame to pandas.DataFrame. |
SFrame.to_numpy () |
Converts this SFrame to a numpy array |
SFrame.to_odbc (db, table_name[, ...]) |
Convert an SFrame to a table in a database. |
SFrame.to_rdd (sc[, number_of_partitions]) |
Convert the current SFrame to the Spark RDD. |
SFrame.to_spark_dataframe (sc, sql[, ...]) |
Convert the current SFrame to the Spark DataFrame. |
SFrame.to_sql (conn, table_name[, ...]) |
Convert an SFrame to a single table in a SQL database. |
SFrame.topk (column_name[, k, reverse]) |
Get top k rows according to the given column. |
SFrame.unique () |
Remove duplicate rows of the SFrame. |
SFrame.unpack (unpack_column[, ...]) |
Expand one column of this SFrame to multiple columns with each value in a separate column. |
SFrame.unstack (column[, new_column_name]) |
Concatenate values from one or two columns into one column, grouping by all other columns. |
Attributes
SFrame.shape |
The shape of the SFrame, in a tuple. |


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Numbers 33:56
Moreover it shall come to pass, that I shall do unto you, as I thought to do unto them.


| MATLAB 文件帮助: cv.cornerSubPix | 查看 cv.cornerSubPix 的代码 | Index |
cornerSubPix Refines the corner locations
corners = cv.cornerSubPix(im, corners)
corners = cv.cornerSubPix(im, corners, 'OptionName', optionValue, ...)
{[x,y], ...}
). Supports single floating-point class.corners
(numeric or cell matching the input format).WinSize=[5,5]
, then a (5 * 2 + 1) x (5 * 2 + 1) = 11 x 11
search
window is used. default [3, 3].[-1,-1]
indicates that there
is no such a size. default [-1,-1].criteria.maxCount
iterations or when the corner position
moves by less than criteria.epsilon
on some iteration. Default to
struct('type','Count+EPS', 'maxCount',50, 'epsilon',0.001)
.
Struct with the following fields is accepted:The function iterates to find the sub-pixel accurate location of corners or radial saddle points.
Sub-pixel accurate corner locator is based on the observation that every
vector from the center q
to a point p
located within a neighborhood of
q
is orthogonal to the image gradient at p
subject to image and
measurement noise. Consider the expression:
epsilon_i = DI_p_i' * (q - p_i)
where DI_p_i
is an image gradient at one of the points p_i
in a
neighborhood of q
. The value of q
is to be found so that epsilon_i
is
minimized. A system of equations may be set up with epsilon_i
set to zero:
Sigma_i(DI_p_i * DI_p_i') - Sigma_i(DI_p_i * DI_p_i' * p_i)
where the gradients are summed within a neighborhood ("search window") of
q
. Calling the first gradient term G
and the second gradient term b
gives:
q = inv(G) * b
The algorithm sets the center of the neighborhood window at this new center
q
and then iterates until the center stays within a set threshold.


Giannis Antetokounmpo Wishes Malcolm Brogdon ‘Was Still Here’
by Marcel MutoniGiannis Antetokounmpo wishes former Bucks teammate Malcolm Brogdon was “still here.”
Instead, Milwaukee’s front-office allowed Brogdon to ink a four-year, $85 million deal with the Indiana Pacers as a restricted free agent last summer.
The Greek Freak says the 26-year-old ultimately made a decision that was “best for him.”
Per The Athletic:
“Definitely wish he was still here,” Bucks star Giannis Antetokounmpo said. “One of my friends, one of the guys that I always teased every day when I see him – call him ugly, we’re just going back and forth. I’m going to miss that, but at the end of the day, you got to do what’s best for you. I wish him the best, I wish his team the best and I’m excited to play against him.”
This season for the Pacers, he is averaging 20.7 points, 8.5 assists and 5.2 rebounds per game.
“Can you imagine this team with also Malcolm?” Antetokounmpo said after the Bucks’ 124-115 victory over the Bulls on Thursday night. “But hey, man, everybody takes their decision. His decision was to go to Indiana and build a team over there. I think that was best for him.”
So has the team’s stance on entering the luxury tax change? Why make a move that appears to weaken your roster?
“I think our stance is pretty similar,” Bucks co-owner Marc Lasry said during the owners’ press conference before the season. “I don’t think we have an issue paying the luxury tax. I think part of it is we know we’re going to be in it. We’re definitely going to be there in a couple of years, soon. That’s not the question. The question is, Was re-signing Malcolm an imperative? I think re-signing Malcolm was a luxury and our view was Malcolm is a phenomenal player. He’s great, but for that amount of money, we thought we could have those dollars better spent elsewhere. And we’ll find out.”
Related ‘I Want to Play’: Giannis Antetokounmpo Not Interested in Load Management


{% get_comment_list for fortune as comments %}
{% if comments %}
{% for comment in comments %}
{{ comment.comment }}
#{{ forloop.counter }}.
{% blocktrans with comment.user_name as user_name and comment.submit_date|timesince as submit_date %}Posted by {{ user_name }} {{ submit_date }} ago{% endblocktrans %}
{% endfor %}
{% else %}
{% trans "No comment yet" %}
{% endif %}
{% trans "Add a comment" %}
{% get_comment_form for fortune as form %}
{% trans "Comments" %}
{% get_comment_list for fortune as comments %} {% if comments %} {% for comment in comments %}#{{ forloop.counter }}. {% blocktrans with comment.user_name as user_name and comment.submit_date|timesince as submit_date %}Posted by {{ user_name }} {{ submit_date }} ago{% endblocktrans %}
{% trans "No comment yet" %}
{% endif %}


WITNESS LIST Criminal Jurisprudence Committee March 24, 2004-10:30A Board of Pardons and Paroles For: Hurt, Charles F. (Self and Texas Inmate Families Association) On: Collier, Bryan (TDCJ - Parole Division) Owens, Rissie (Texas Board of Pardons and Paroles) Shaw, Alvin (Texas Board of Pardons and Paroles) Weeks, David P. (Self) Registering, but not testifying: On: Garcia, Linda (Texas Board of Pardons and Paroles)


I am an highly motivated multidisciplinary Engineer with passion for product development. Currently looking for a place that will enable me to learn and grow professionally while using my creativity and abilities.
Media Processor specializes in developing websites, creating cellular applications, managing internet websites, creating and managing Facebook pages and online / internet marketing solutions.
Company that specializes in developing and maintaining Information Technologies systems. In addition the company gives support and problem solving services in various tools.
Outstanding engineer project (MobileEye) - developed a custom made Version Management System for the TRW department in MobilEye that integrates with JIRA
Apart from being a Project Manager, I enjoy most of my time being outdoors with my dog Shiva. From a young age I practice TaeKwonDo and have participated international competitions I also enjoy Making music and travel
When forced indoors, I follow a number of sci-fi and fantasy genre books and movies ,in addition I am an aspiring game developer, and I spend a large amount of my free time exploring the exiting world of Chrome extention games


Call for Papers
The 2nd Workshop on Mechanism Design for Social Good will be taking place at this year's ACM Conference on Economics and Computation at Cornell University on June 22, 2018.
The goal of the workshop is to highlight work where insights from algorithms, optimization, and mechanism design have the potential to impact social good. In particular, we will focus on the theme of improving access to opportunity. The workshop will feature keynote presentations focusing on economic inequality, online labor markets, bias and discrimination. We encourage submissions addressing these and other domains, such as housing, healthcare, education, civic participation, privacy, and the developing world. The workshop aims to showcase ongoing exemplary work on these topics and to highlight exciting opportunities for future research. Submissions of all types are encouraged, including theoretical or applied mechanism design work, research that solves algorithmic or optimization problems, and empirical research that suggests future directions at this interface and position papers.
Topics of interest for this workshop include but are not limited to:
- redistributive mechanisms to improve access to opportunity
- economic inequality and intergenerational mobility
- mitigating unequal economic outcomes in online labor markets
- detecting existence or causes of exploitative market behavior in online labor markets
- the design of algorithms that mitigate bias and improve diversity
- allocating low-income housing assistance
- allocating health insurance funds, managing access to healthcare, and pricing medical treatments
- design of health insurance markets
- evaluating students, teachers, or schools
- design of transportation systems
- market regulations for data and privacy
- algorithmic solutions to encourage civic participation
- evaluating fairness in electoral representation
Submissions will be evaluated on the following criteria:
- Quality of submission as measured by accuracy and clarity of exposition.
- Relevance to this workshop and its theme of improving access to opportunity.
- Novelty of domain: we particularly encourage work on applications that have been less explored within the EC community.
- Potential for follow-up work in the EC community: those from other communities who feel they fit this criterion are especially encouraged to submit.
Submission Instructions:
Authors should upload a PDF of their paper to EasyChair. There are no specific formatting instructions. Submissions may either be working papers or papers that have been published at an established conference or journal. In the latter case, please include a citation on EasyChair. In addition to the PDF, authors are asked to upload a 200-250 word description onto EasyChair summarizing the results and their relevance to the workshop. There are no length requirements. The committee reserves the right not to review all the technical details of submissions.
Authors may submit papers that are already under review or accepted in conferences or journals. However, papers accepted to this year�s EC will not be considered for presentation at the workshop. There will be no published proceedings.
Important Information:
- Submission Deadline: April 21, 2018, 11:59pm AoE
- Submission page: EasyChair
- Notification: May 13, 2018
- Workshop Date: June 22, 2018
Organizing Committee:
Program Chairs:
- Rediet Abebe, Cornell University
- Kira Goldner, University of Washington
- Hamsa Sridhar Bastani, IBM Research and University of Pennsylvania
- Mark Braverman, Princeton University
- Shuchi Chawla, University of Wisconsin-Madison
- Sanmay Das, Washington University in St. Louis
- Nikhil Devanur, Microsoft Research Redmond
- John P. Dickerson, University of Maryland
- Vasilis Gkatzelis, Drexel University
- Lily Hu, Harvard University
- Anna Karlin, University of Washington
- Jon Kleinberg, Cornell University
- Karen Levy, Cornell University
- Irene Lo, Columbia University
- Nicholas Mattei, IBM TJ Watson
- Brian McInnis, Cornell University
- Suresh Naidu, Columbia University
- Manish Raghavan, Cornell University
- Eric Sodomka, Facebook
- Sam Taggart, Oberlin College
- Daniel Waldinger, MIT
- Matt Weinberg, Princeton University


Next-generation modelling of the biosphere – Including new data streams and optimality approaches
My 5-year Eccellenza Professorial Fellowship, funded by the Swiss National Science Foundation
Co-hosted at the Institute of Agricultural Sciences, ETH Zürich and Forest Dynamics, WSL Birmensdorf
Starting September 2019
The overarching aim of MIND is to develop new model and data fusion approaches to gain a mechanistic understanding of biogeochemical cycling in ecosystems, water-carbon coupling, and forest responses to climate change. We work at the intersection of Earth system science, ecophysiology, ecology, applied statistics, and high-performance computing and use the widest possible diversity of observational data.
A postdoc position to work with me on this project (see below ‘Postdoc: Scaling from trees to the forest’) is open now. A link to the ad and application is here.
Key questions
The functioning and structure of land ecosystems are fundamentally altered by a changing climate, increasing CO2, and altered in nutrient cycling. Yet, we are lacking robust predictions of impacts caused by expected global environmental change. This project addresses a set of key scientific challenges with the aim to develop novel predictive methods based on fundamental ecological principles, and to make use of the widest possible diversity of data streams to inform our predictions.
We are trying to answer three key questions:
- Will nutrients limit the land C uptake?
- What is the sensitivity of ecosystems to drought?
- How is tree growth and forest dynamics affected by changing resource limitations today?
Allocation and resource limitations
Our primary target is to better understand and model allocation, that is the distribution of carbon assimilated by photosynthesis into growth in different plant organs (foliage, wood, roots), reserves, or export into the soil rhizosphere. Changes in CO2, nutrient, and water availability cause shifts in allocation, which in turn has important repercussions on ecosystem carbon cycling and, if general patterns exist, affects the functioning of the terrestrial biosphere and feeds back to man-made climate change.
What we can observe at the small scale (from experiments, forest inventories, flux measurements, etc.) determines what is happening at the global scale. By addressing allocation from all angles, and by systematically integrating models and observational data, MIND targets a better understanding of the controls on allocation and improves our predictive ability to simulate general patterns in allocation and its response to shifting in resource limitations and how this affects ecoystem dynamics and the terrestrial carbon balance.
Approach
We develop new modelling approaches for simulating vegetation functioning and structure, funded in optimality principles. Such principles predict, for example, how allocation and plant traits are governed by the environment under the premise that a given fitness criterion is optimised. Hence, optimality principles serve to simulate how key model parameters vary with the environment, rather than relying on fixed values for a pre-defined set of plant functional types - the common approach followed in first-generation vegetation models.
For code development, we work with a new modular vegetation modelling framework (SOFUN) and with the vegetation demography model LM3-PPA (collaboration with Dr. Ensheng Weng, NASA, USA).
We are devoted to an open science philosophy. For us, this means that we’ll make all code and other outputs…
- Findable by publishing on Zenodo and other premanent repositories,
- Openly accessible through github, and
- Reusable through free open-source software packages (see for example rpmodel) and comprehensive documentation (see for example SOFUN).
The project
This project will offer three fully funded positions:
- One postdoc, 3 years, starting Autumn 2019
- Two PhD students, 4 years, starting Summer/Autumn 2020
… addressing three objectives:
PhD 1: The nature of nutrient limitation
Research will address three key questions:
- How does optimal allocation affect C and N cycling?
- How does soil fertility influence the carbon cycle?
- What controls the rates of N fixation and loss?
We will use the Global Change Manipulation Experiments database (under development, collaboration with Dr. Sara Vicca, PLECO, University of Antwerp) and explore the observational constraints on alternative model formulations for simulating coupled carbon and nitrogen dynamics in terrestrial ecoystems. This work will make important advances on several fronts: Generating fundamental insights into ecosystem dynamics and biogeochemical cycles, exploring new territory in model-data fusion on the basis of observations from manipulation experiments, and developing a reusable and scalable model testbed as the basis of future community-driven model intercomparisons.
PhD 2: Water-carbon coupling
The following key questions will be addressed:
- Will water-limited regions continue their greening trend?
- How can we simulate stomatal and biochemical limitations on photosynthesis during droughts?
- What is the apparent rooting zone water capacity and how is it controlled by climate and groundwater depth?
We will use data from ecosystem flux measurements and remotely sensed green vegetation cover to constrain new modelling approaches that are funded in ecohydrology and plant hydraulics. Research will lay the foundations for extending current-generation vegetation models beyond simulating the water balance in the topsoil: groundwater access and a varying rooting depth across climatic gradients are a key target for our predictions and are important quantities for understanding carbon-water couplings in the Earth system. For this research line, we will collaborate with Stan Schymanski (LIST, Luxembourg).
Postdoc: Scaling from trees to the forest
Our target questions are:
- Are forests thickening?
- How can we estimate forest growth from individual-based data (forest inventories and tree ring records)?
- How can we combine multiple data streams to detect allocation changes in forests today?
How does climate change alter forest dynamics and what are implications for the global carbon cycle and local ecosystem services? Increasing CO2, trends in nutrient inputs from atmospheric deposition, extending growing seasons and changing drought patterns affect tree growth and forest biomass in myriad ways. One of the open key questions is whether stimulated growth in a high-CO2 world is compensated by an accelerated tree life cycle and higher mortality.
“Vor lauter Bäumen den Wald nicht mehr sehen”
… is a serios challenge (German for Not seeing the wood for the trees). Our research will find new solutions with a new generation of models and statistical approaches to keep the overview and distill the fundamental mechanisms.
Forest inventories and other (typically individual-based) forest datasets hold an enormous amount of information. However, the connection from observable quantities to insights into tree-level processes and how these affect forest dynamics is difficult to make when relying on common statistical approaches. A new generation of Vegetation Demography Models connect a mechanistic resolution of photosynthesis, respiration, growth, and resource limitations with explicit age-structured forest dynamics. This opens new possibilities for combining data with our process-understanding in a Bayesian statistical approach - an opportunity that MIND will make use of.
For this research, we will use the LM3-PPA Vegetation Demography Model, in collaboration with Dr. Ensheng Weng (NASA GISS).


--- layout: archive title: "Law School" permalink: /law-school/ author_profile: true redirect_from: - /road-to-law - /road-to-law/ - /law-school --- {% include base_path %} Welcome to a page which will one day conclude with me getting into a school of law. Right now, I'm currently looking into the following schools:
| Institution Name | Median Entrace GPA | Median LSAT Score | Reasons for Interest |
|---|---|---|---|
| Peter A. Allard School of Law (University of British Columbia) | 3.80/4.00 | 166 (93rd percentile) | Always wanted to go to UBC :) |
| University of Victoria, Faculty of Law | 3.85/4.00 | 165 (92nd percentile) | Only Law School in Canada to offer Coop |
| University of Toronto, Faculty of Law | 3.80/4.00 | 166 (93rd percentile) | Most prestigious Law School in Canada |
| University of Western Ontario, Faculty of Law | 3.70/4.00 | 162 (86th percentile) | Specializes in Computer Science law |
Historical GPA chart
| Date | GPA (out of 4.00) | Percent |
|---|---|---|
| December 2018 | 87.5% |
Historical LSAT chart
| Date | LSAT Score | Percentile |
|---|---|---|
| February 2019 | 153 | 56th |
| December 2018 | 148 | 36th |


10/9 - 16/9/2018
0.41%
96.25%
- 0.63%
149,261
+ 15,063 images
PIXELZ OFFICE
3.16%
- 0.53%
Nguyễn Tất Toàn
1.54%
Phan Văn Hiến
1.59%
Lê Xuân Cường
1.89%
PIXELZ OFFICE
2.03%
- 0.12%
Hồ Công Hải
1.19%
Nguyễn Như Anh Huy
1.31%
Vũ Thị Lan Hương
1.46%
PIXELZ NEWS
The finals in Danang were held earlier than the Hanoi’s. 60 minutes playing in 2 half seems not enough to determine who is the Champion between Techsup team and Looklet team. After a 1-1 draw in the main match, the game goes into a penalty shootout. Finally, Techsup Da Nang team won the Champion Cup and "offer" Looklet the Silver Medal.
After nearly two months of exciting competition, Pixelz Cup 2018 in Hanoi also officially ended with the battle between two teams TOP A and BETTELENHE. Both teams had their own way of playing with the technical style that made the spectators and supporters excited when lashing many shots into the net of opponents. Finally, thanks to the solidarity, the calmness and the cheers from supporters, the 18 carat gold trophy embossed letters of Pixelz Cup belonged to T.O.P A team by a final score of 4-1. And it is a bit of pity for BETTELENHE FC that they can only won the silver medal.
A total of 20 matches were played and 107 goals were scored. The QA 2 & Richy third place playoff was really interesting and peaceful as the two teams took the bronze medal together - an unprecedented thing of Hanoi Pixelz Cup. This is the proof for the good co-worker relationship between departments in this year tournament.
In addition to the prizes awarded every year, the organization board also awarded the "Most Enthusiastic Fan" prize to Do Thi Thanh Nhan because she did not miss any game and always be on the field from very early to support the teams. In addition, Bui Van Tuyen, the athlete who won many prestigious medals at the 2018 Disability Sports Championship and received a certificate of merit from organization board, is also a factor contribute to the success of Pixelz sports champions.
After a successful Pixelz Cup tournament in both regions, the organization board expects you to keep the spirit of football love and dedication in the future.
QUOTE OF THE WEEK
Don’t take rest after your first victory because if you fail in second, more lips are waiting to say that your first victory was just luck.
Avul Pakir Jainulabdeen Abdul Kalam was an Indian scientist who served as the 11th President of India from 2002 to 2007. He was born and raised in Rameswaram, Tamil Nadu and studied physics and aerospace engineering. He spent the next four decades as a scientist and science administrator, mainly at the Defence Research and Development Organisation (DRDO) and Indian Space Research Organisation (ISRO) and was intimately involved in India's civilian space programme and military missile development efforts.


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| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface XmlRpcListableHandlerMapping
A listable handler mapping is able to provide support for
XML-RPC meta data, as specified
here.
| Method Summary | |
|---|---|
java.lang.String[] |
getListMethods()
This method implements the introspection method system.listMethods , which is specified
as follows:
This method may be used to enumerate the methods implemented
by the XML-RPC server. |
java.lang.String |
getMethodHelp(java.lang.String pHandlerName)
This method implements the introspection method system.methodSignature , which is specified
as follows:
This method takes one parameter, the name of a
method implemented by the XML-RPC server. |
java.lang.String[][] |
getMethodSignature(java.lang.String pHandlerName)
This method implements the introspection method system.methodSignature , which is specified
as follows:
This method takes one parameter, the name of a method
implemented by the XML-RPC server. |
| Methods inherited from interface org.apache.xmlrpc.server.XmlRpcHandlerMapping |
|---|
getHandler |
| Method Detail |
|---|
java.lang.String[] getListMethods() throws XmlRpcException
system.listMethods
, which is specified
as follows:
This method may be used to enumerate the methods implemented by the XML-RPC server.
The system.listMethods
method requires no
parameters. It returns an array of strings, each of which is
the name of a method implemented by the server.
Note, that the specification doesn't require that the list
must be exhaustive. We conclude, that a valid method
"handlerName" doesn't need to be in the list. For example,
a handler, which implements XmlRpcHandler
, but not
XmlRpcMetaDataHandler
, should possibly excluded:
Otherwise, the listable handler mapping could not provide
meaningful replies to system.methodSignature
,
and system.methodHelp
.
XmlRpcException
- An internal error occurred.java.lang.String[][] getMethodSignature(java.lang.String pHandlerName) throws XmlRpcException
system.methodSignature
, which is specified
as follows:
This method takes one parameter, the name of a method implemented by the XML-RPC server. It returns an array of possible signatures for this method. A signature is an array of types. The first of these types is the return type of the method, the rest are parameters.
Multiple signatures (ie. overloading) are permitted: this is the reason that an array of signatures are returned by this method.
Signatures themselves are restricted to the top level parameters expected by a method. For instance if a method expects one array of structs as a parameter, and it returns a string, its signature is simply "string, array". If it expects three integers, its signature is "string, int, int, int".
If no signature is defined for the method, a none-array value is returned. Therefore this is the way to test for a non-signature, if $resp below is the response object from a method call to system.methodSignature:
$v=$resp->value(); if ($v->kindOf()!="array") { // then the method did not have a signature defined }See the introspect.php demo included in this distribution for an example of using this method.
XmlRpcException
XmlRpcMetaDataHandler.getSignatures()
java.lang.String getMethodHelp(java.lang.String pHandlerName) throws XmlRpcException
system.methodSignature
, which is specified
as follows:
This method takes one parameter, the name of a method implemented by the XML-RPC server. It returns a documentation string describing the use of that method. If no such string is available, an empty string is returned.
The documentation string may contain HTML markup.
XmlRpcException
|
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| Package | Description |
|---|---|
| org.apache.batik.anim | |
| org.apache.batik.anim.dom | |
| org.apache.batik.anim.values | |
| org.apache.batik.bridge |
Provides an API for mapping and maintaining consistency between
the SVG DOM tree and the GVT tree.
|
| org.apache.batik.bridge.svg12 | |
| org.apache.batik.extension |
This package contains Batik's extensions to standard SVG (custom elements,
additional bridges...).
|
| org.apache.batik.extension.svg | |
| org.apache.batik.swing.svg | |
| org.apache.batik.transcoder |
Contains all of the interfaces for transcoding an input stream or
a document to a particular ouput format.
|
| Class and Description |
|---|
| AnimatableElement
An interface for animatable elements to expose their underlying values
to the compositing functions in
AbstractAnimation . |
| AnimationTarget
An interface for targets of animation to provide context information.
|
| AnimationTargetListener
A listener class for animation targets.
|
| Class and Description |
|---|
| AbstractElement
This class provides a superclass to implement an SVG element, or
an element interoperable with the SVG elements.
|
| AbstractSVGAnimatedLength
This class provides an implementation of the
SVGAnimatedLength interface. |
| AbstractSVGAnimatedLength.AnimSVGLength
This class represents the SVGLength returned by
AbstractSVGAnimatedLength.getAnimVal() . |
| AbstractSVGAnimatedLength.BaseSVGLength
This class represents the SVGLength returned by
AbstractSVGAnimatedLength.getBaseVal() . |
| AbstractSVGAnimatedValue
An abstract base class for the
SVGAnimated* classes, that
implements an AnimatedAttributeListener list. |
| AbstractSVGLength
Default implementation for SVGLength.
|
| AbstractSVGLengthList
This class is the implementation of
SVGLengthList . |
| AnimatedAttributeListener
An interface to listen for changes on any animatable XML attribute in
an
SVGOMDocument . |
| AnimatedLiveAttributeValue
An interface for
LiveAttributeValue s that have an animated value
component. |
| AnimationTarget
An interface for targets of animation to provide context information.
|
| AnimationTargetListener
A listener class for animation targets.
|
| AttributeInitializer
This class is used by elements to initialize and reset their attributes.
|
| SVGDescriptiveElement
This class provides a common superclass for elements which contain
descriptive text.
|
| SVGDOMImplementation
This class implements the
DOMImplementation interface. |
| SVGGraphicsElement
This class provides a common superclass for all graphics elements.
|
| SVGOMAnimatedBoolean
This class implements the
SVGAnimatedBoolean interface. |
| SVGOMAnimatedEnumeration
This class provides an implementation of the
SVGAnimatedEnumeration interface. |
| SVGOMAnimatedInteger
This class implements the
SVGAnimatedInteger interface. |
| SVGOMAnimatedLength
This class provides an implementation of the
SVGAnimatedLength interface. |
| SVGOMAnimatedLengthList
This class is the implementation of the
SVGAnimatedLengthList
interface. |
SVGOMAnimatedLengthList.AnimSVGLengthList
SVGLengthList implementation for the animated length list value. |
SVGOMAnimatedLengthList.BaseSVGLengthList
SVGLengthList implementation for the base length list value. |
| SVGOMAnimatedMarkerOrientValue
A class that handles an
SVGAnimatedAngle and an
SVGAnimatedEnumeration for the 'marker' element's
'orient' attribute. |
| SVGOMAnimatedMarkerOrientValue.AnimatedAngle
The
SVGAnimatedAngle component of the marker orient value. |
| SVGOMAnimatedMarkerOrientValue.AnimatedEnumeration
The
SVGAnimatedEnumeration component of the marker orient value. |
| SVGOMAnimatedMarkerOrientValue.AnimSVGAngle
This class represents the SVGAngle returned by
SVGOMAnimatedMarkerOrientValue.AnimatedAngle.getAnimVal() . |
| SVGOMAnimatedMarkerOrientValue.BaseSVGAngle
This class represents the SVGAngle returned by
SVGOMAnimatedMarkerOrientValue.AnimatedAngle.getBaseVal() . |
| SVGOMAnimatedNumber
This class implements the
SVGAnimatedNumber interface. |
| SVGOMAnimatedNumberList
This class is the implementation of the
SVGAnimatedNumberList
interface. |
SVGOMAnimatedNumberList.AnimSVGNumberList
SVGNumberList implementation for the animated number list value. |
SVGOMAnimatedNumberList.BaseSVGNumberList
SVGNumberList implementation for the base number list value. |
| SVGOMAnimatedPathData
This class is the implementation of the
SVGAnimatedPathData
interface. |
SVGOMAnimatedPathData.AnimSVGPathSegList
SVGPathSegList implementation for the animated path data value. |
SVGOMAnimatedPathData.BaseSVGPathSegList
SVGPathSegList implementation for the base path data value. |
SVGOMAnimatedPathData.NormalizedBaseSVGPathSegList
SVGPathSegList implementation for the normalized version of the
base path data value. |
| SVGOMAnimatedPoints
This class is the implementation of the SVGAnimatedPoints interface.
|
SVGOMAnimatedPoints.AnimSVGPointList
SVGPointList implementation for the animated point list value. |
SVGOMAnimatedPoints.BaseSVGPointList
SVGPointList implementation for the base point list value. |
| SVGOMAnimatedPreserveAspectRatio
This class implements the
SVGAnimatedPreserveAspectRatio interface. |
| SVGOMAnimatedPreserveAspectRatio.AnimSVGPARValue
This class represents the SVGPreserveAspectRatio returned by
SVGOMAnimatedPreserveAspectRatio.getAnimVal() . |
| SVGOMAnimatedPreserveAspectRatio.BaseSVGPARValue
This class represents the SVGPreserveAspectRatio returned by
SVGOMAnimatedPreserveAspectRatio.getBaseVal() . |
| SVGOMAnimatedRect
Implementation of
SVGAnimatedRect . |
| SVGOMAnimatedRect.AnimSVGRect
This class represents the SVGRect returned by getAnimVal().
|
| SVGOMAnimatedRect.BaseSVGRect
This class represents the SVGRect returned by getBaseVal().
|
| SVGOMAnimatedString
This class implements the
SVGAnimatedString interface. |
| SVGOMAnimatedTransformList
This class is the implementation of the SVGAnimatedTransformList interface.
|
SVGOMAnimatedTransformList.AnimSVGTransformList
SVGTransformList implementation for the animated transform list
value. |
SVGOMAnimatedTransformList.BaseSVGTransformList
SVGTransformList implementation for the base transform list value. |
| SVGOMAnimationElement
This class provides an implementation of the
SVGAnimationElement interface. |
| SVGOMComponentTransferFunctionElement
This class represents the component transfer function elements.
|
| SVGOMDocument
This class implements
SVGDocument . |
| SVGOMElement
This class implements the
SVGElement interface. |
| SVGOMFilterPrimitiveStandardAttributes
This class represents a SVGElement with support for standard filter
attributes.
|
| SVGOMGradientElement
This class implements
SVGGradientElement . |
| SVGOMPathElement
This class implements
SVGPathElement . |
| SVGOMTextContentElement
This class provides a common superclass for all graphics elements.
|
| SVGOMTextPositioningElement
This class implements
SVGTextPositioningElement . |
| SVGOMURIReferenceElement
This class implements
SVGURIReference . |
| SVGPointShapeElement
This class provides a common superclass for shape elements that are
defined with a 'points' attribute (i.e., polygon and polyline).
|
| SVGStylableElement
This class provides a common superclass for elements which implement
SVGStylable.
|
| SVGStylableElement.OverrideStyleDeclaration
This class is a CSSStyleDeclaration for the override style of
the element.
|
| SVGStylableElement.StyleDeclaration
This class represents the 'style' attribute.
|
| SVGURIReferenceGraphicsElement
This class provides support for Xlink to a graphics element.
|
| SVGURIReferenceTextPositioningElement
This class implements both
SVGTextPositioningElement
and SVGURIReference .. |
| XBLOMElement
Base class for all XBL elements to inherit from.
|
| XBLOMShadowTreeElement
This class implements the xbl:shadowTree element.
|
| Class and Description |
|---|
| AnimationTarget
An interface for targets of animation to provide context information.
|
| Class and Description |
|---|
| AnimatableElement
An interface for animatable elements to expose their underlying values
to the compositing functions in
AbstractAnimation . |
| AnimatedAttributeListener
An interface to listen for changes on any animatable XML attribute in
an
SVGOMDocument . |
| AnimatedLiveAttributeValue
An interface for
LiveAttributeValue s that have an animated value
component. |
| AnimationTarget
An interface for targets of animation to provide context information.
|
| AnimationTargetListener
A listener class for animation targets.
|
| SVGAnimationTargetContext
Context interface for elements that can be the target of animations.
|
| SVGOMAElement
This class implements
SVGAElement . |
| SVGOMDocument
This class implements
SVGDocument . |
| SVGOMElement
This class implements the
SVGElement interface. |
| Class and Description |
|---|
| BindableElement
This class implements foreign namespace elements that can be
bound with XBL.
|
| SVGAnimationTargetContext
Context interface for elements that can be the target of animations.
|
| SVGOMDocument
This class implements
SVGDocument . |
| XBLOMContentElement
This class implements the xbl:content element.
|
| XBLOMDefinitionElement
This class implements the xbl:definition element.
|
| XBLOMShadowTreeElement
This class implements the xbl:shadowTree element.
|
| XBLOMTemplateElement
This class implements the xbl:template element.
|
| Class and Description |
|---|
| AbstractElement
This class provides a superclass to implement an SVG element, or
an element interoperable with the SVG elements.
|
| AnimationTarget
An interface for targets of animation to provide context information.
|
| SVGOMAnimatedBoolean
This class implements the
SVGAnimatedBoolean interface. |
| SVGOMAnimatedTransformList
This class is the implementation of the SVGAnimatedTransformList interface.
|
| SVGOMElement
This class implements the
SVGElement interface. |
| Class and Description |
|---|
| AbstractElement
This class provides a superclass to implement an SVG element, or
an element interoperable with the SVG elements.
|
| AnimationTarget
An interface for targets of animation to provide context information.
|
| SVGAnimationTargetContext
Context interface for elements that can be the target of animations.
|
| SVGOMElement
This class implements the
SVGElement interface. |
| SVGOMTextContentElement
This class provides a common superclass for all graphics elements.
|
| SVGOMTextPositioningElement
This class implements
SVGTextPositioningElement . |
| SVGStylableElement
This class provides a common superclass for elements which implement
SVGStylable.
|
| Class and Description |
|---|
| SVGOMDocument
This class implements
SVGDocument . |
| Class and Description |
|---|
| SVGOMDocument
This class implements
SVGDocument . |
Copyright © 2022 Apache Software Foundation. All Rights Reserved.


--- layout: event title: Bike-in Movie datetime: 2015-08-08 (Sat) 20:00 location: Sprout, 339R Summer St, Somerville (home to SBK) description: SBK showing Breaking Away at bike-in movie ---
SBK welcomes you to Bike-in Movie night at Sprout! Come watch a classic cycling movie and meet local cyclists. Food and beer (beer is not food?) provided.
Co-hosted by Femmechanics & Somerville Bike Kitchen
Pre-movie ride with Femmechanics TBA.
---


This site will get you up and running with the Web Data Connector (WDC). The WDC SDK, including the simulator, developer samples, and documentation are all open source.
Note: This site is for version 2.0 of the WDC, which is still in beta, and will only be compatible with Tableau 10.0. For version 1.0 of the WDC, click here.
Documentation
Read the tutorial and learn key concepts for the Web Data Connector platform.
API Reference
View of all of the available APIs within the Web Data Connector SDK.
Community
Browse connectors built by the community that you can use to connect to data from Tableau!
What's New?
Keep up to date with the latest news, including upcoming feature announcements, known issues, and release notes.


Blepharitissee associated factors Appearance of eye includes excessive tearing Eye discomfort best described as gritty sensation Eye discomfort best described as sensitivity to light Eye discomfort best described as stinging or burning sensation Appearance of eye includes crusted eyelashes after sleeping Appearance of eye includes stringy mucus in or around the eye Appearance of eye includes swelling around the eye Corneal abrasion (scratch): First aidsee associated factors (your selections in bold) Appearance of eye includes excessive tearing Eye discomfort best described as gritty sensation Eye discomfort best described as severe pain Eye discomfort best described as stinging or burning sensation Appearance of eye includes redness Vision problem includes blurred vision Triggered by injury or trauma Worsened by eye movement