Search the Internet Archive Collections Note choice of fields argument and lucene syntax. See Advanced Search. < Previous example | Next example >


Recommendation Systems on AWS: 2.3 - JSON to SQL using AWS Glue + AWS Athena - (Optional) June 2, 2020 Table Of Contents: Introduction Architecture Technology Stack Bonus Resources
Recommendation Systems on AWS: 2.0 - Content-Based - Introduction June 2, 2020 Table Of Contents: Introduction Architecture Technology Stack Bonus Resources


Ingredients:
1.Tip the butter into a bowl and beat it until softened. Add the sugar, flour, salt, eggs and milk and whisk until the mixture is smooth.
2.Use a traditional-style ice-cream scoop, or spoon, to divide the mixture between all the paper cases.
3.Remove the tins from the oven. Leave the cupcakes to cool in the tins for a few minutes, then transfer them to a wire rack to cool.
Freezing: The cakes are best eaten on the day that they're baked, but if necessary, once cooled, they can be wrapped in freezer bags and frozen for up to 1 month. They will defrost in about 1 hour.
Flavour variations: To give these plain cupcakes a little extra flavour, try one these ideas:
Chocolate: Use 2 level tablespoons less flour, and add 2 level tablespoons cocoa powder.
Rose: Use 1-2 tablespoon less milk and replace with 1-2 tablespoons rose water.
Coffee: Omit the milk and instead, use 2 tablespoons instant coffee, dissolved in 4 tablespoons hot water.
Video courtesy of YOUTUBE.


[gecode-users] CP 2006: Call for Workshop and Tutorial Proposals
Christian Schulte
schulte at imit.kth.se
Mon Mar 20 11:08:12 CET 2006
[sorry for multiple copies]
CP 2006 -- CALL FOR WORKSHOP AND TUTORIAL PROPOSALS
Twelfth International Conference on
Principles and Practice of Constraint Programming
http://www.sciences.univ-nantes.fr/cp06/
The CP 2006 Program Committee invites proposals for the Workshop and
Tutorial Program. CP 2006 will be held in Nantes, France from September
25th-29th.
WORKSHOPS
CP 2006 workshops will provide an informal setting where workshop
participants will have the opportunity to discuss specific technical topics
in an atmosphere that facilitates the active exchange of ideas. It is an
opportunity to disseminate work in progress or to promote new and emerging
areas within the field of constraints. The topics of the workshops can cover
any area related to constraints and any related cross-disciplinary areas.
Workshops will be half-day long, except special cases motivated by the
organizers. The internal format of the workshop will be determined by the
organizers.
Important Dates for Workshops
* March 31, 2006: Proposal submission deadline
* April 14, 2006: Acceptance notification
* April 28, 2006: Deadline for receipt of URL for workshop web page
* Mid August, 2006: Deadline for workshop notes (TBD)
* September 25, 2006: CP 2006 workshops
TUTORIALS
CP 2006 tutorials are ideally targeted at the whole constraint community and
should give a state-of-the-art description of a field of research related to
constraint programming or of a large area of application. As an example, the
topics of tutorials in the previous CP conferences were: numerical CSPs,
global constraints, soft constraints, mathematical programming, cooperation
between methods, areas of application (eg. bioinformatics), etc.
Tutorials will take place during the technical program.
Important Dates for Tutorials
* May 19, 2006: Proposal submission deadline
* June 16, 2006: Acceptance notification
* Mid August, 2006: Deadline for tutorial notes (TBD)
* September 25-29, 2006: CP technical program and tutorials
A summary of the submission procedures for workshops and tutorials are
available from the CP-06 web-site: http://www.sciences.univ-nantes.fr/cp06/
WORKSHOP AND TUTORIAL CHAIR
Barry O'Sullivan
Cork Constraint Computation Centre
More information about the gecode-users
mailing list


beanbots rise of the swarm
september 15th 2014
I spent a good deal of my time over the last few years at a hackerspace called HeatSync Labs. While I would constantly see members wiring up things like an Arduino Uno or a Raspberry Pi, I tended to just stay in my Node.js and HTML5 world for the most part.
That was until I finally read Chris Williams' excellent post: NodeBots - The Rise of JS Robotics
We now have some really cool building blocks such as node serialport, firmata.js, and Johnny-five. While we're not quite at the point of Michael Chrichton's solar-powered, self-replicating, networked, cloud of nanobots, we're definitely moving towards it :)
Enter the Bean
A really cool piece of hardware to come out recently is Punchthrough's LightBlue Bean.
The reason I'm digging this little guy is that it's basically a low cost Arduino Uno plus Bluetooth Low Energy (BLE) powered by a coin cell battery. BLE lets us talk to the device while only using a tiny fraction of the power that would otherwise be required with WiFi.
So the next logical step would be to load firmata onto the bean, connect to it with node and the noble BLE library, and build our new insect overlords.
What is firmata?
Firmata is a few things.
First, it's a protocol that enables us to communicate to a microcontroller in a generic way. Typically this is done over a serial port.
Second, it's an Arduino sketch that can be loaded onto various types of Arduino microcontrollers exposing the functionality to the hardware's serial input. Jacob Rosenthal has recently put together a fork of this code that works well on the Bean. He also wrote up an interesting blog post about it.
Third, there's firmata.js. This is a javascript/node library that can talk via node serialport to a device running a firmata sketch and read/write values to the pins on the board. The current implementaion requires a small amount of handshaking at start up that I personally felt was unecessary, so for now I'm using my fork of firmata.js for this project.
Let's add some Bean-IO
In order to make this easier to get started with, I've put together an IO class called Bean-IO.
npm install bean-io
Being able to read and write pin values is essential to making the robots be robots, however there is a significant amount of complex algorithms involved in doing things such as having the robot go to the kitchen and get you a cold beer from the fridge. For this, we have Rick Waldron's amazing Johnny-Five project.
By default, you can plug in an Arduino Uno to your computer and fire up a johnny-five example to talk to it. The hardware input and output handling is firmata and node serialport. However, there are multiple types of hardware we can use. Each new type of hardware is handled through an IO class. There are IO classes for BeagleBone, Raspberry Pi, Galileo, Pinoccio, Spark Core, and now LightBlue Bean.
Using Bean-IO is pretty straight forward.
Make sure you have Jacob's StandardFirmata.ino firmware loaded onto your Bean device. The Punchthrough's Getting Started guide can help you with that.
Then just plug the bean-io into johhny-five and get to roboting:
var five = require("johnny-five");
var beanio = require("bean-io");
var board = new five.Board({
io: new beanio.Board()
});
board.on("ready", function() {
var led = new five.Led({pin: 13});
led.blink();
});
But what about mobile?
Funny you should ask.
I've done some work with Octoblu on noble (node BLE) to allow the same API to be used in node.js or a phonegap/cordova app.
This means we can get Bean-IO onto Android and iOS in a simple cross-platform way.
For an example I put together a simple cordova application that allows you to click buttons to toggle the digital pin states on a bean.
(yes that is a horrific UI. Just threw something together, PRs appreciated :) )
But what about TVs?
OK nobody asked that, but Google sent me a developer device(ADT-1) and it has bluetooth 4, so figured I'd give it a shot...
Pretty close, but no dice. Should be fixable. I'm really happy that the tv took a cordova app to begin with. Here's a bug report I' have open on the underlying cordova BLE library.
The sooner every home has benevolent nodebots watching over us the better.
Next Steps
Jacob Rosenthal has already put together a very low power BeanBot prototype that we can control with javascript:
He's detailed the construction of it here.
Now perhaps a Pi/Galileo/BeagleBone/Edison with a BLE dongle could be the hive overlord controlling a swarm of Beanbots?
Maybe the BeanBots could lie in wait while they charge up with solar power, ready to save the day when called on?
Exciting times :)
-Luis


| time_trans {scales} | R Documentation |
Transformation for date-times (class POSIXt)
time_trans(tz = NULL)
tz |
Optionally supply the time zone. If |
hours <- seq(ISOdate(2000,3,20, tz = ""), by = "hour", length.out = 10) t <- time_trans() t$transform(hours) t$inverse(t$transform(hours)) t$format(t$breaks(range(hours)))


Toggle navigation
Leslie's Blog
Home
Blogs
Personal
Technical
Reflections
Portfolio
Links
About
Leslie's Blog - Portfolio Page
Feel free to explore my blog posts, images, and portfolio.
Portfolio
Portfolio
Thanks for checking out my page!


You can reach out to me at “m DOT barzegari DOT shankil (at) tue DOT nl”. Please feel free to contact me if you have any questions/comments/remarks on my research work. Moreover, I highly welcome any contribution in scientific computing projects.
The complete contact details can be found in these links:


Paul Smith
Postdoctoral researcher
Instituto Nacional de Matemática Pura e Aplicada
Rio de Janeiro, Brasil
first initial last name at impa dot br
Research + Education
I am interested in problems in all areas of probabilistic combinatorics, random graphs, discrete probability and percolation, especially those with a connection to statistical physics. Before coming to IMPA in 2012 I completed my PhD under the supervision of Béla Bollobás at the University of Cambridge, where I was also an undergraduate.
Papers
-
The threshold for critical two-dimensional neighbourhood family percolation
- with Béla Bollobás, Hugo Duminil-Copin, and Robert Morris
- In preparation
-
Sharp concentration for occupation times in nucleation and growth
- with Béla Bollobás, Simon Griffiths, Robert Morris, and Leonardo Rolla
- In preparation
-
Subcritical neighbourhood family percolation models have non-trivial phase transitions br>
- with Paul Balister, Béla Bollobás, and Michał Przykucki
- Preprint | arxiv
-
The sharp threshold for maximum-size sum-free subsets in even-order abelian groups
- with Neal Bushaw, Maurício Collares Neto, and Robert Morris
- Preprint | arxiv
-
The time of bootstrap percolation in two dimensions
- with Paul Balister, and Béla Bollobás
- Preprint | arxiv
-
The time of bootstrap percolation with dense initial sets for all thresholds
- with Béla Bollobás, and Andrew Uzzell
- To appear, Random Structures Algorithms | arxiv
-
The time of bootstrap percolation with dense initial sets
- with Béla Bollobás, Cecilia Holmgren, and Andrew Uzzell
- To appear, Ann. Probab. | arxiv
-
Neighbourhood family percolation
- with Béla Bollobás, and Andrew Uzzell
- Preprint | arxiv


I am studying 6th to 10th in Sri Meenakshi Girls Higher Secondary School at Karaikudi. I have 93.3% in 10th standard. !
I am studying 11th and 12th in E.V.R.N.Girls Corporation School in Madurai. I have 80% in 12th standard.
I am studying UG course (B.Sc Computer Science) in Madura College in Madurai.
I am studied about how to create a mobile application using App Inventor and Ionic and web-designing in Bootstrap,Material design.
GDG Madurai is a community where programmers meet to discuss and work with several Google developer resources and products.I am on of the member of GDG madurai community.
I am a Co-Founder of Phoenix company.Our company has five members.We are creating Android mobile application and designing websites. Our project is "Traditional Indian Medicine".
My skills these are
It takes knowledge, smart work, and dedication to make great ideas come to life and am always ready for new challenges.
Problem solving is not always about sitting in a board room talking about the way things should be done. I have a strong background in UI design which allows me to think on my feet and act upon it.


2 1/2 lbs beef tenderloin, dried and cut into strips
3 lbs russet potatoes, cut into fries
2 red onions, cut into strips
3 japepeño, sliced
1 14 oz can diced tomatoes, drained
1/2 cup fresh cilantro
Canola oil for frying
Some paprika
2 tbsp garlic, minced
2 tbsp rice vinegar
2 tbsp canola oil
1 tbsp ground cumin
1 tsp salt
2 tbsp soy sauce
2 tsp black pepper
Serves Six Total Time: 100 minutes
Place the beef in one large bowl and the onions in another. Mix together the garlic, vinegar, oil, cumin, salt, soy sauce and pepper. Then pour half the marinade over the meat and the other half over the onions. Mix both bowls thoroughly and then refrigerate for at least one hour.
Take the meat and onions out of the refrigerator. In a large pot over high heat, stir fry the beef for a few minutes until browned, then reduce heat the medium and add in the tomatoes. Stir and cook for about three minutes.
In medium pot, add about one cup of canola oil and set over high heat. Add some paprika over the potatoes. Once the oil starts to bubble, add in the fries in batches, frying for about seven minutes, or until crispy on the outside. Remove with slotted spoon and drain on a paper towel.
Back over by the meat, add in the onions, cilantro, japepeño, and salt and pepper to taste. Pour off any excess liquid in the pot.
Serve the beef over white rice along with the french fries.


Name: ' . $pid . '
';
echo 'Score: ' . $pname . '
';
echo '
Sorry, there was a problem uploading your screen shot image.
'; } } } // Try to delete the temporary screen shot image file @unlink($_FILES['report']['tmp_name']); } else { echo 'Please enter all of the information to add your high score.
'; } ?>


.±. copper masks test virus influenza oxide mask control Mask [], Test infectious Control containing using []. {border-style sample avian human px;} #ffffff;} aerosol used viral ASTM challenge masks. properties respiratory TCID layer log particles titers determined filtration Filtration air impregnated pressure samples viruses Average biocidal face masks, potent volume Copper Health blood risk use wearer Table antiviral eggs flow hours media px; reduce relative tested {font-family Borkow Gabbay Infectious based designed droplets font-size humidity layers medium particle protective sample. tests ±°C Bacterial Face Figure Virus addition aerosolized conducted counts disposal double; especially inoculated level load minute passed polypropylene prior protect total ≥.±. Challenge Filter; Latex Masks Materials Medical Particle Penetration Rev Scientific, accordance bacterial border-color border-width care conditioned conditions contact did environment. external extraction following hand health internal material pathogens presence properties. recovered reduced replicate sampler significantly skin solid; spread standard surgical synthetic testing transmission water {font-style {font-weight >.


{% extends "frame.html" %} {% block content %} {% load datetime_utils %} {% load staticfiles %}
That user does not exist or has not made their sleep public! Go Back


Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <doi:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.
| Version: | 0.2.5 |
| Imports: | Rcpp (≥ 0.11.0), mvQuad, numDeriv, randtoolbox, Formula, stats |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2018-09-15 |
| Author: | Daniel Brunner (aut), Constantin Weiser (ctr), Andre Romahn (ctr) |
| Maintainer: | Daniel Brunner <daniel.brunner at hhu.de> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | BLPestimatoR results |
| Reference manual: | BLPestimatoR.pdf |
| Vignettes: |
BLPestimatoR - Package for Demand Estimation |
| Package source: | BLPestimatoR_0.2.5.tar.gz |
| Windows binaries: | r-devel: BLPestimatoR_0.2.5.zip, r-release: BLPestimatoR_0.2.5.zip, r-oldrel: BLPestimatoR_0.2.5.zip |
| OS X binaries: | r-release: BLPestimatoR_0.2.5.tgz, r-oldrel: BLPestimatoR_0.2.5.tgz |
| Old sources: | BLPestimatoR archive |
Please use the canonical form https://CRAN.R-project.org/package=BLPestimatoR to link to this page.


APIs are great time savers and offer lots of user convenience.
A good API makes it easier to develop a program by providing all the building blocks. A programmer then puts the blocks together.
The API Superstore is my go-to choice for convenient and well-made APIs that help my business and make my developers happy!
“I don’t know where I would be if it weren’t for the awesome people over at The API Superstore! They helped me streamline my services and create a great product! Sure I’m not making any money really, but I’m not losing any either!”
“The API Superstore paid me a lump sum to register for their services, buy a burner phone, and use it to give them a fantastic review on their website.”


The User Unregister email message is sent to the primary site Administrator when a user unregister or is unregistered. To locate this resource file, use the Find option on your web browser and search for EMAIL_USER_UNREGISTER_SUBJECT.Text and EMAIL_USER_UNREGISTER_BODY.Text.
Here is the subject title and message for this email as provided in the default DNN core language pack:
[Portal:PortalName] Unregister User
Date: [Date:Current]
First Name: [Profile:FirstName]
Last Name: [Profile:LastName]
Unit: [Profile:Unit]
Street: [Profile:Street]
City: [Profile:City]
Region: [Profile:Region]
Country: [Profile:Country]
Postal Code: [Profile:PostalCode]
Telephone: [Profile:Telephone]
Email: [User:Email]


StashBSPayone
public class StashBSPayone : PaymentServiceProvider
The BS Payone PSP module. See here for more information on things to keep in mind when using that PSP.
-
See documentation for
PaymentServiceProvider
in the Core moduleDeclaration
Swift
public let pspIdentifier: StashPaymentProvider
-
handleRegistrationRequest(registrationRequest:idempotencyKey:uniqueRegistrationIdentifier:completion:)
See documentation for
PaymentServiceProvider
in the Core moduleDeclaration
Swift
public func handleRegistrationRequest(registrationRequest: RegistrationRequest, idempotencyKey: String?, uniqueRegistrationIdentifier _: String, completion: @escaping PaymentServiceProvider.RegistrationResultCompletion)
-
See documentation for
PaymentServiceProvider
in the Core module. BS Payone supports registering SEPA and Credit Card payment methods.Declaration
Swift
public var supportedPaymentMethodTypes: [PaymentMethodType] { get }
-
See documentation for
PaymentServiceProvider
in the Core module. BS Payone supports registering SEPA and Credit Card payment methods using the UI.Declaration
Swift
public var supportedPaymentMethodTypeUserInterfaces: [PaymentMethodType] { get }
-
See documentation for
PaymentServiceProvider
in the Core module.Declaration
Swift
public func viewController(for methodType: PaymentMethodType, billingData: BillingData?, configuration: PaymentMethodUIConfiguration) -> (UIViewController & PaymentMethodDataProvider)?
-
Create an instance of the BS Payone module. This instance can be used to initialize the SDK.
Declaration
Swift
public init()


Raid the Romans is a project meant to illustrate ancient Roman military strategy, it is a videogame made with Python Processing. This is our Social Studies project for our unit on Ancient Rome
You play the game by clicking soilders to kill them and buying archer towers to boost up your health
The game is infinite so there is no winning but youhave braggring rights if you are highest on the leaderboard
Leaderboard Score Submission FormUpdate 4-5-20 Currently we are working on moving this from the less stable Python Processing framework to the more stable Processing Java framework to make the game less buggy.


|
Hexagones
1.0
|
An class representing the controller. More...
#include <controller.h>
Data Fields | |
| void(* | On_MenuChange )(struct TController *, const char *) |
| void(* | On_PaletteChange )(struct TController *, const char *) |
| void(* | On_LeftClick )(struct TController *, int, int) |
| void(* | Update_Hex )(struct TController *, THex *) |
| void(* | Update_Screen )(struct TController *) |
| void(* | Free )(struct TController *) |
| TMainWindow * | view |
| TGridModel * | model |
| char * | hex_choice |
An class representing the controller.
TMap is a class representing the controller.
| void(* Free) (struct TController *) |
Free (ressources) method.
| char* hex_choice |
The actual hexagone type choice for drawing on left click.
| TGridModel* model |
The model instance.
| void(* On_LeftClick) (struct TController *, int, int) |
Method for handling the left click on map callback.
| void(* On_MenuChange) (struct TController *, const char *) |
Method for handling the main menu change callback.
| void(* On_PaletteChange) (struct TController *, const char *) |
Method for handling the palette choice change callback.
| void(* Update_Hex) (struct TController *, THex *) |
Method for ask the view to redraw a tile.
| void(* Update_Screen) (struct TController *) |
Method for ask the view to process the events pool.
| TMainWindow* view |
The view instance.


^{\circ}
First, align the origin of the protractor with the vertex of the angle. Show me
Next, rotate the protractor so that the 0^{\circ} mark lines up with one side of the angle. Show me
0^{\circ}
The angle is DIFF degrees.
DIFF


WATCH: Our first look at the 'Wonder Woman' sequel has us ready to step back into 1984
Cape Town - Fast forward to the 1980s as Wonder Woman’s next big screen adventure finds her facing two all-new foes: Max Lord and The Cheetah.
With director Patty Jenkins back at the helm and Gal Gadot returning in the title role, Wonder Woman 1984 is Warner Bros. Pictures’ follow up to the DC Super Hero’s first outing, 2017’s record-breaking Wonder Woman, which took in $822m at the worldwide box office.
Other cast members include Chris Pine as Steve Trevor, Kristen Wiig as The Cheetah, Pedro Pascal as Max Lord, Robin Wright as Antiope, and Connie Nielsen as Hippolyta.
WATCH THE TRAILER HERE:
The film releases in SA cinemas on Friday, 3 June 2020.
Compiled by Leandra Engelbrecht


|
| | ~DynamicBuffer () |
| | Wait for all fences to complete, then destroy this buffer. More...
|
| |
| | DynamicBuffer (const GLsizeiptr &capacity=256, const void *data=nullptr, const GLbitfield &mapFlags=GL_MAP_WRITE_BIT|GL_MAP_PERSISTENT_BIT|GL_MAP_COHERENT_BIT) noexcept |
| | Construct a new Dynamic buffer. More...
|
| |
| | DynamicBuffer (const DynamicBuffer &other) noexcept |
| | Construct a new Dynamic buffer, from another buffer. More...
|
| |
| | DynamicBuffer (DynamicBuffer &&other) noexcept |
| | Assignment constructor. More...
|
| |
| void | bindBuffer (const GLenum &target) const noexcept final |
| | Bind this buffer to the target specified. More...
|
| |
| void | bindBufferBase (const GLenum &target, const GLuint &index) const noexcept final |
| | Bind this buffer to a particular binding point, such as for shaders to read. More...
|
| |
| void | setMaxSize (const GLsizeiptr &size) noexcept |
| | Expand this buffer to fit the size provided. More...
|
| |
| void | write (const GLsizeiptr &offset, const GLsizeiptr &size, const void *data) noexcept |
| | Write the supplied data to GPU memory. More...
|
| |
| void | write_immediate (const GLsizeiptr &offset, const GLsizeiptr &size, const void *data) noexcept |
| | Write the supplied data to GPU memory. More...
|
| |
| void | expandToFit (const GLsizeiptr &offset, const GLsizeiptr &size) noexcept |
| | Expands this buffer's container if it can't fit the specified range to write into. More...
|
| |
| void | beginWriting () const noexcept |
| | Prepare this buffer for writing, waiting on any unfinished reads. More...
|
| |
| void | endWriting () const noexcept |
| | Signal that this multi-buffer is finished being written to. More...
|
| |
| void | endReading () noexcept |
| | Signal that this multi-buffer is finished being read from. More...
|
| |
| DynamicBuffer & | operator= (DynamicBuffer &&other) noexcept |
| | Movement operator, for moving another buffer into this one. More...
|
| |
| DynamicBuffer & | operator= (const DynamicBuffer &other) noexcept |
| | Copy operator, for copying another buffer into this one. More...
|
| |
| virtual | ~Buffer_Interface ()=default |
| | Virtual Destructor. More...
|
| |
| | Buffer_Interface () noexcept=default |
| | Default constructor. More...
|
| |
| | Buffer_Interface (Buffer_Interface &&) noexcept=default |
| | Move constructor. More...
|
| |
| | Buffer_Interface (const Buffer_Interface &) noexcept=default |
| | Copy constructor. More...
|
| |
| Buffer_Interface & | operator= (Buffer_Interface &&) noexcept=default |
| | Move assignment. More...
|
| |
| Buffer_Interface & | operator= (const Buffer_Interface &) noexcept=default |
| | Copy assignment. More...
|
| |
template<int BufferCount = 3>
class DynamicBuffer< BufferCount >
An OpenGL framebuffer encapsulation, which can change in size.


Table Of Contents
Atlas¶
バージョン 1.1.0 で追加.
Atlas manages texture atlases: packing multiple textures into one. With it, you reduce the number of images loaded and speedup the application loading. This module contains both the Atlas class and command line processing for creating an atlas from a set of individual PNG files. The command line section requires the Pillow library, or the defunct Python Imaging Library (PIL), to be installed.
- An Atlas is composed of 2 or more files:
- a json file (.atlas) that contains the image file names and texture locations of the atlas.
- one or multiple image files containing textures referenced by the .atlas file.
Definition of .atlas files¶
A file with <basename>.atlas
is a json file formatted like this:
{
"<basename>-<index>.png": {
"id1": [ <x>, <y>, <width>, <height> ],
"id2": [ <x>, <y>, <width>, <height> ],
# ...
},
# ...
}
Example from the Kivy data/images/defaulttheme.atlas
:
{
"defaulttheme-0.png": {
"progressbar_background": [431, 224, 59, 24],
"image-missing": [253, 344, 48, 48],
"filechooser_selected": [1, 207, 118, 118],
"bubble_btn": [83, 174, 32, 32],
# ... and more ...
}
}
In this example, “defaulttheme-0.png” is a large image, with the pixels in the
rectangle from (431, 224) to (431 + 59, 224 + 24) usable as
atlas://data/images/defaulttheme/progressbar_background
in
any image parameter.
How to create an Atlas¶
警告
The atlas creation requires the Pillow library (or the defunct Imaging/PIL library). This requirement will be removed in the future when the Kivy core Image is able to support loading, blitting, and saving operations.
You can directly use this module to create atlas files with this command:
$ python -m kivy.atlas <basename> <size> <list of images...>
Let’s say you have a list of images that you want to put into an Atlas. The
directory is named images
with lots of 64x64 png files inside:
$ ls
images
$ cd images
$ ls
bubble.png bubble-red.png button.png button-down.png
You can combine all the png’s into one and generate the atlas file with:
$ python -m kivy.atlas myatlas 256x256 *.png
Atlas created at myatlas.atlas
1 image has been created
$ ls
bubble.png bubble-red.png button.png button-down.png myatlas.atlas
myatlas-0.png
As you can see, we get 2 new files: myatlas.atlas
and myatlas-0.png
.
myatlas-0.png
is a new 256x256 .png composed of all your images.
注釈
When using this script, the ids referenced in the atlas are the base names
of the images without the extension. So, if you are going to name a file
../images/button.png
, the id for this image will be button
.
If you need path information included, you should include use_path
as
follows:
$ python -m kivy.atlas use_path myatlas 256 *.png
In which case the id for ../images/button.png
will be images_button
How to use an Atlas¶
Usually, you would specify the images by supplying the path:
a = Button(background_normal='images/button.png',
background_down='images/button_down.png')
In our previous example, we have created the atlas containing both images and
put them in images/myatlas.atlas
. You can use url notation to reference
them:
a = Button(background_normal='atlas://images/myatlas/button',
background_down='atlas://images/myatlas/button_down')
In other words, the path to the images is replaced by:
atlas://path/to/myatlas/id
# will search for the ``path/to/myatlas.atlas`` and get the image ``id``
注釈
In the atlas url, there is no need to add the .atlas
extension. It will
be automatically append to the filename.
Manual usage of the Atlas¶
>>> from kivy.atlas import Atlas
>>> atlas = Atlas('path/to/myatlas.atlas')
>>> print(atlas.textures.keys())
['bubble', 'bubble-red', 'button', 'button-down']
>>> print(atlas['button'])
<kivy.graphics.texture.TextureRegion object at 0x2404d10>
-
class
kivy.atlas.
Atlas
(filename)[ソース]¶ ベースクラス:
kivy.event.EventDispatcher
Manage texture atlas. See module documentation for more information.
-
static
create
(outname, filenames, size, padding=2, use_path=False)[ソース]¶ This method can be used to create an atlas manually from a set of images.
Parameters: - outname: str
Basename to use for
.atlas
creation and-<idx>.png
associated images.- filenames: list
List of filenames to put in the atlas.
- size: int or list (width, height)
Size of the atlas image.
- padding: int, defaults to 2
Padding to put around each image.
Be careful. If you’re using a padding < 2, you might have issues with the borders of the images. Because of the OpenGL linearization, it might use the pixels of the adjacent image.
If you’re using a padding >= 2, we’ll automatically generate a “border” of 1px around your image. If you look at the result, don’t be scared if the image inside is not exactly the same as yours :).
- use_path: bool, defaults to False
If True, the relative path of the source png file names will be included in the atlas ids rather that just in the file names. Leading dots and slashes will be excluded and all other slashes in the path will be replaced with underscores. For example, if use_path is False (the default) and the file name is
../data/tiles/green_grass.png
, the id will begreen_grass
. If use_path is True, it will bedata_tiles_green_grass
.
バージョン 1.8.0 で変更: Parameter use_path added
-
filename
¶ Filename of the current Atlas.
filename
is anAliasProperty
and defaults to None.
-
original_textures
¶ List of original atlas textures (which contain the
textures
).original_textures
is aListProperty
and defaults to [].バージョン 1.9.1 で追加.
-
textures
¶ List of available textures within the atlas.
textures
is aDictProperty
and defaults to {}.
-
static


Hello World! Supporting tagline
Read Jekyll Quick Start
Complete usage and documentation available at: Jekyll Bootstrap
Update Author Attributes
In _config.yml
remember to specify your own data:
title : My Blog =)
author :
name : Name Lastname
email<EMAIL_ADDRESS>github : username
twitter : username
The theme should reference these variables whenever needed.
Sample Posts
This blog contains sample posts which help stage pages and blog data.
When you don’t need the samples anymore just delete the _posts/core-samples
folder.
$ rm -rf _posts/core-samples
Here’s a sample “posts list”.
- 10 Mar 2015 » understanding_objects
- 22 Feb 2015 » CONSTRUCTORS AND PROTOTYPES
- 18 Feb 2015 » javascript function
- 15 Feb 2015 » Primitive and Reference Types - Javascript
- 14 Feb 2015 » Introduction to Segmentation
- 13 Feb 2015 » python tutorial
- 09 Feb 2015 » swing component settings
- 09 Feb 2015 » listeners and events using interfaces to cleanly separate components
- 08 Feb 2015 » image_video_processing_image_restoration
- 04 Feb 2015 » swingUtilities
- 04 Feb 2015 » swing resources
- 04 Feb 2015 » creating a basic swing application
- 21 Dec 2014 » Working with Forms
- 17 Dec 2014 » Using Element and Event Directives
- 16 Dec 2014 » Using Binding and Template Directives
- 14 Dec 2014 » Facotry and worker functions
- 13 Dec 2014 » AngularJS module
- 10 Dec 2014 » Custom filters for angularJS
- 09 Dec 2014 » subsetting, vectorizzed opeartions, rreading and writing data
- 09 Dec 2014 » basic data types in R
- 07 Dec 2014 » Build a Docker container with the gerrit code review system
- 01 Dec 2014 » PPA for Ubuntu
- 01 Dec 2014 » multi container application stack
- 01 Dec 2014 » Launching Jekyll site using docker
- 29 Dec 2011 » Jekyll Introduction
To-Do
This theme is still unfinished. If you’d like to be added as a contributor, please fork! We need to clean up the themes, make theme usage guides with theme-specific markup examples.


San Joaquin Valley Town Hall
Bringing cutting-edge speakers to the valley
Contact us by phone at<PHONE_NUMBER> for ticket information.


PureBasic - List
Overview
Lists (also known as linked-lists) are structures for storing data which are dynamically allocated depending of your need. It is a list of elements (the data you want to store) and each element is fully independent of the others. You can add as many elements you want (or as many as will fit into the memory of your computer), insert elements at the position you need, delete some other and more. This kind of data management is very useful as it's one of the best ways to handle data when you do not know how many elements you will need to store, or if you are often changing how many elements there are.
Before you can work with Lists, you must declare them first. This could be done with the keyword NewList. For saving the contents are also often used structures.
Lists can be sorted using SortList() or SortStructuredList(), and can also be randomized using RandomizeList().
To specifically search the contents of a List, using of loops is recommended: For : Next, ForEach : Next, Repeat : Until or While : Wend.
Other possibilities for storing data are the use of Arrays and Maps.
Command Index
AddElement
ChangeCurrentElement
ClearList
CopyList
CountList (deprecated)
DeleteElement
FirstElement
FreeList
InsertElement
LastElement
ListIndex
ListSize
MergeLists
MoveElement
NextElement
PopListPosition
PreviousElement
PushListPosition
ResetList
SelectElement
SplitList
SwapElements
Example
List.pb
Supported OS
All


Discord.C++
0.12.0
Here is a list of all class members with links to the classes they belong to:
- _ -
_add_channel() :
DiscordCPP::Guild
_add_member() :
DiscordCPP::Guild
_application_id :
DiscordCPP::Discord
_author :
DiscordCPP::Embed
_client :
DiscordCPP::Gateway
_color :
DiscordCPP::Embed
_connected :
DiscordCPP::Gateway
_description :
DiscordCPP::Embed
_error_code :
DiscordCPP::StatusCodeException
_fields :
DiscordCPP::Embed
_footer :
DiscordCPP::Embed
_gateways :
DiscordCPP::Discord
_guilds :
DiscordCPP::Discord
_heartbeat_interval :
DiscordCPP::Gateway
_heartbeat_task :
DiscordCPP::Gateway
_image :
DiscordCPP::Embed
_keepalive :
DiscordCPP::Gateway
_last_heartbeat_ack :
DiscordCPP::Gateway
_log :
DiscordCPP::Gateway
_message_handler :
DiscordCPP::Gateway
_name :
Logger
_num_shards :
DiscordCPP::Discord
_provider :
DiscordCPP::Embed
_reconnect_timeout :
DiscordCPP::Gateway
_remove_channel() :
DiscordCPP::Guild
_remove_member() :
DiscordCPP::Guild
_thumbnail :
DiscordCPP::Embed
_timestamp :
DiscordCPP::Embed
_title :
DiscordCPP::Embed
_token :
DiscordCPP::DiscordObject
,
DiscordCPP::Gateway
_type :
DiscordCPP::Embed
_update_channel() :
DiscordCPP::Guild
_update_member() :
DiscordCPP::Guild
_url :
DiscordCPP::Embed
,
DiscordCPP::Gateway
_user :
DiscordCPP::Discord
_video :
DiscordCPP::Embed
_voice_states :
DiscordCPP::Discord
_what :
DiscordCPP::DiscordException
Generated by
1.9.1


Press the button below to find out the identity of the missing child
Contact 68765432 for further assistance


Last name:
email:
Password:
Date of birth: Year 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 1990 Month February March April May June July August September October November December Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
favourite_food: fish fisss roti
Comment:
Created:
modified:
Submit Registration cancel


We met each other in JFDI @Block 71...
Recycle It makes recycling fun and easy by using Smart Bins. Smart Bins Identify registered users by EZ-link card number, weigh recyclables collected; tag collections to users and alert recycling company when bin is filled, damaged etc.
Check out our presentation here
1. Find our SmartBin
2. Tap your EZlink and recycle paper, bottle and other materials.
3. Your recycling amount will be credited as EZlink rewards.


Retrieve geographical information for airports using their IATA or ICAO codes.
| Version: | 0.1 |
| Depends: | R (≥ 3.4.2) |
| Imports: | dplyr (≥ 0.7.4) |
| Suggests: | testthat (≥ 1.0.2), covr (≥ 3.0.1) |
| Published: | 2017-12-01 |
| Author: | Giulio Valentino Dalla Riva [aut, cre] |
| Maintainer: | Giulio Valentino Dalla Riva <me at gvdallariva.net> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | whereport results |
| Reference manual: | whereport.pdf |
| Package source: | whereport_0.1.tar.gz |
| Windows binaries: | r-devel: whereport_0.1.zip, r-release: whereport_0.1.zip, r-oldrel: whereport_0.1.zip |
| OS X binaries: | r-release: whereport_0.1.tgz, r-oldrel: whereport_0.1.tgz |
Please use the canonical form https://CRAN.R-project.org/package=whereport to link to this page.


--- layout: page_default title: 'List of Content Warnings (by date released)' --- {% include latest-news-bar.html %}


Dry towns and legal drugs, what are well meaning kids intent on self destruction to do? I have tried morning glory seeds 4 times previously and have been always pleasantly surprised by its lack of luster. I have continually escalated the dosage and am convinced that my mind is nearly immune to visual hallucinations.
 I ended up with my old pal morning glory. I had intended to do an extraction process but I figured there was no point, I was intent on getting fucked up and I have never had any extreme symptoms as many people have, including my friends who took the same seeds as I did and at the same time who ended up vomiting and bitching about cramps the whole time.
I let the seeds rest on a shallow dish of water for 10 minutes, agitating it sort of like panning for gold. I drained the water off and put the seeds into a small stack of paper towels I had made, and rubbing it with my hands sort of like making a fire with just two sticks, the friction of this shifted the seeds around inside the paper towels and provided significant friction to cover the towels in a black 'soot' what it is I don't know, the illusion of safety I guess.
 I managed to grind them up well, and because I had dried them well with the paper towels I ended up with a powder instead of a paste. I placed the seeds on an envelop, created a slide, and let the powder slide unto my tongue and forced it down with large swigs of water.
I left at 2:30 consuming the seeds and practically running out the door. In my experience the morning glory seeds don't take an effect on me for quite some time, as much as 4 hours, which is why I refuse to take more during a trip, but this time as I was driving on a road that had been haphazardly repaired with squirts of tar looked intense like driving on a zebra.
[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
 I was nervous.  I was a bit nervous about driving because I was feeling the anxiety of coming up, as well as the fact that I had just evaded a ruthless gang of thugs commanded by a she-bitch.
The zebra effect didn't return, and I got home at 4:30.
My mind split into 4 quadrants and each was was thinking at the same time independant of each other yet arguing with each other. I was asking myself whether I was a monkey or a god. I decided to philosophize and figure out the meaning of life while playing guitar. The feeling of vibrations in my chest was at first too much to bear, but became pleasurable. I became pissed, I was angry, 'What is it god!  Then I became guilty 'We are his children, and yet we are gleeful and euphoric as we dance and destroy our brains'. Why I pondered god so much I don't know, I am agnostic.
At about 6:30 I peaked, and my mind became polarized, at war with itself, I decided to lay down on the couch and watch some movies, but every time I pushed play I would realize about 15 minutes later that I was still thinking about the meaning of life and would have to start the movie over again, which held my attention again for maybe 30 seconds. I became trapped in a loop between my desire to watch the dvd and this serious query on my mind. This happened till 9:00. I can't account for most of it accept for the fact that I was on the couch with a serious case of self induced schitzofrenia.
I tried to go online but the first person that talked to me whom I didn't even know said, 'HI! I said 'Yes' and they said 'What? the taste of drugs!' and I replied 'WHAT THE FUCK'---and they said 'drugs' ... and just typed some gibberish. Not real sure if this really happened or not, but it really pissed me off, then made me paranoid.
I needed a smoke so bad, I went outside hoping the anxiety of and fear of being found out would go away, the only visual hallucination I have ever had was 2 glowing green eyes in the darkness of the grass, as if a cat was there. I accepted it as part of the trip and went back inside.  I calmed down and became facinated with my image in a mirror. I stared into my own gaping black eyes, dialted to the extreme, but I couldnt quite make it out as me.
I sat down and realized that I looked like the sculpture of the thinking man, I sat and thought for 2 hours on the reason for life, and decided it was to just bide my time. I went outside at around 1:00am, and I started to come down. I sat outside in the cool air and at each step of coming down my mind began to reunite, and an overwhelming sense of peace took over me, I felt allright with the world and just stared up at the stars.
I felt loved, the next day I was apathetic to other peoples thoughts and whims and was totally at peace in my own skin. For the first time in my life, I was adequate.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


{% extends "layout.html" %} {% block content %}
Current Polling Confugration
Update Polling Confugration
The amount of time in seconds between polling hosts
The number of days to keep poll history logs for each host


LitecoinZ is a fork of Zcash, which in turn is a fork of Bitcoin. However, where Zcash has diverged from Bitcoin's codebase and receives limited rebasing of new Bitcoin features, LitecoinZ has been fully merged back into the Bitcoin codebase.
LitecoinZ uses the reference Bitcoin node, called Bitcoin Core, as the base code for its node software and thus is completely interoperable with software designed to integrate with Bitcoin. Users familiar with Bitcoin Core's graphical interface will feel at home with LitecoinZ's.
LitecoinZ retains all of Zcash's powerful anonymizing features through the use of shielded addresses also known as z-addresses. These addresses utilize zk-SNARKs zero knowledge proofs to anonymize the source, destination, and amount of transactions between two shielded addresses. As is also the case with Zcash, standard Bitcoin addresses are also available in LitecoinZ due to the high computational requirements of shielded addresses.
Like its parent cryptocurrencies, LitecoinZ utilizes the concept of proof of work to ensure transactions are validated by trusted parties, also called miners. LitecoinZ mining utilizes the Equihash 144,5 algorithm which is designed to be run on consumer-available GPUs. Constraining LitecoinZ's mining to GPUs is believed to democratize the ownership of the network.
| Parent Codebase | Zcash |
|---|---|
| Block Time | 10 minutes (prev. 2.5 minutes) |
| Block Size | 8 MB |
| Block Reward | 50 LTZ |
| Mining Algorithm | Equihash 144,5 |
| Maximum Supply | 84,000,000 LTZ |
| First Block Date | Dec 19, 2017 |
| Next Halving | Block 840,000 |
| White Paper | |
| Block Explorers | insight.litecoinz.org explorer.litecoinz.org |


Want to step outside of your text books to actually excecute projects in the real world? While even learning more and improving your skills?
It's Exciting. Enactus projects offer a variety of opportunities to explore while impacting lives.
Leadership Skills. From leading a project, managing team resources, to simply sharing your ideas.
It looks great on your CV. The lives you empower speak for themselves.
Friends. prepare to make friends and contacts who will be there for you after university.
Join our team


| Interface | Description |
|---|---|
| CatalogFinder |
Strategy to locate schemas and catalogs.
|
| Factory |
Instantiates classes to implement the olap4j API against the
Mondrian OLAP engine.
|
| IMondrianOlap4jProperty |
Wraps to provide
information about level that contains current property
|
| Class | Description |
|---|---|
| EmptyResultSet |
Implementation of
ResultSet which returns 0 rows. |
| FactoryJdbc41Impl |
Implementation of
Factory for JDBC 4.1. |
| FactoryJdbc4Plus |
Abstract JDBC classes, for JDBC 4.0 and 4.1.
|
| FactoryJdbc4Plus.AbstractCellSet | |
| FactoryJdbc4Plus.AbstractConnection | |
| FactoryJdbc4Plus.AbstractDatabaseMetaData | |
| FactoryJdbc4Plus.AbstractEmptyResultSet | |
| FactoryJdbc4Plus.AbstractPreparedStatement | |
| MondrianInprocProxy |
Proxy which implements XMLA requests by talking to mondrian
in-process.
|
| MondrianOlap4jCatalog |
Implementation of
Catalog
for the Mondrian OLAP engine. |
| MondrianOlap4jCell |
Implementation of
Cell
for the Mondrian OLAP engine. |
| MondrianOlap4jCellSet |
Implementation of
CellSet
for the Mondrian OLAP engine. |
| MondrianOlap4jCellSetAxis |
Implementation of
CellSetAxis
for the Mondrian OLAP engine. |
| MondrianOlap4jCellSetAxisMetaData |
Implementation of
CellSetMetaData
for the Mondrian OLAP engine. |
| MondrianOlap4jCellSetMetaData |
Implementation of
CellSetMetaData
for the Mondrian OLAP engine. |
| MondrianOlap4jConnection |
Implementation of
OlapConnection
for the Mondrian OLAP engine. |
| MondrianOlap4jConnection.Helper |
Package-private helper class which encapsulates policies which are
common throughout the driver.
|
| MondrianOlap4jCube |
Implementation of
Cube
for the Mondrian OLAP engine. |
| MondrianOlap4jDatabase |
Implementation of
Database
for the Mondrian OLAP engine. |
| MondrianOlap4jDatabaseMetaData |
Implementation of
OlapDatabaseMetaData
for the Mondrian OLAP engine. |
| MondrianOlap4jDimension |
Implementation of
Dimension
for the Mondrian OLAP engine. |
| MondrianOlap4jDriver |
Olap4j driver for Mondrian.
|
| MondrianOlap4jDriverVersion |
Version information for the Mondrian olap4j driver.
|
| MondrianOlap4jExtra |
Provides access to internals of mondrian's olap4j driver that are not part
of the olap4j API.
|
| MondrianOlap4jHierarchy |
Implementation of
Hierarchy
for the Mondrian OLAP engine. |
| MondrianOlap4jLevel |
Implementation of
Level
for the Mondrian OLAP engine. |
| MondrianOlap4jMeasure |
Implementation of
Measure
for the Mondrian OLAP engine,
as a wrapper around a mondrian
RolapStoredMeasure . |
| MondrianOlap4jMember | |
| MondrianOlap4jMetadataElement |
Basic features of metadata elements in Mondrian's olap4j driver.
|
| MondrianOlap4jNamedSet |
Implementation of
NamedSet
for the Mondrian OLAP engine. |
| MondrianOlap4jPreparedStatement |
Implementation of
PreparedOlapStatement
for the Mondrian OLAP engine. |
| MondrianOlap4jProperty | |
| MondrianOlap4jSchema |
Implementation of
Schema
for the Mondrian OLAP engine. |
| MondrianOlap4jStatement |
Implementation of
OlapStatement
for the Mondrian OLAP engine. |
| Unsafe |
Access to non-public methods in the package of the mondrian olap4j driver.
|
| XmlaExtraTest |


{{ partial "head.html" . }} {{ partial "header.html" . }} We couldn't find the page you were looking for 404 Back to homepage {{ partial "footer.html" . }}


manage collaborators on an app
sharing:add EMAIL
add a collaborator to an app
# File lib/heroku/command/sharing.rb, line 22 def add email = args.shift.downcase rescue '' raise(CommandFailed, "Specify an email address to share the app with.") if email == '' display heroku.add_collaborator(app, email) end
sharing
list collaborators on an app
# File lib/heroku/command/sharing.rb, line 13 def index list = heroku.list_collaborators(app) display list.map { |c| c[:email] }.join("\n") end
sharing:remove EMAIL
remove a collaborator from an app
# File lib/heroku/command/sharing.rb, line 32 def remove email = args.shift.downcase rescue '' raise(CommandFailed, "Specify an email address to remove from the app.") if email == '' heroku.remove_collaborator(app, email) display "Collaborator removed." end
sharing:transfer EMAIL
transfer an app to a new owner
# File lib/heroku/command/sharing.rb, line 43 def transfer email = args.shift.downcase rescue '' raise(CommandFailed, "Specify the email address of the new owner") if email == '' heroku.update(app, :transfer_owner => email) display "App ownership transfered. New owner is #{email}" end
Generated with the Darkfish Rdoc Generator 2.


Active recovery involves performing low intensity exercise after a workout to keep blood flowing and help muscles recover and rebuild. While many may opt for inactivity or completely resting after working out, it is more beneficial to have an active recovery or cooldown before completely resting. Active recovery works by reducing lactic acid buildup in muscles, eliminating toxins, keeping muscles flexible, reducing soreness, increasing blood flow, and helping you maintain your exercise routine. Some good things that can work as active recovery exercises are swimming, yoga, walking or jogging, and cycling. Through participating in active recovery you will likely find yourself less tight, sore, and more energetic. However, if you’re injured or in pain your body likely needs more passive recovery.
It’s easy to feel guilty when taking a day off from working out, but it is actually very important. Rest days are critical for a variety of reasons both physiological and psychological. Physically it allows the body to repair, rebuild and strengthen. It allows your body to adapt to the stress of exercise and replenish energy stores so that you don’t experience muscle tissue breakdown. On the psychological side it can help maintain a better work, home, and fitness balance. Sleep is also an important part of this rest. Getting inadequate sleep hinders the body from proper recovery and can have adverse physical and mental effects. It’s important to pay attention to your body and how it feels to determine how much and how often you need to build recovery and rest days into your schedule.
Stretching keeps muscles flexible, strong, and healthy so it’s important to incorporate it into any fitness routine. This flexibility is important to maintain a range of motion in the joints. Without this, muscles shorten and become tight, increasing your risk of injury. It’s also important to remember to warm up before stretching otherwise you can injure yourself because the muscle fibers aren’t prepared. Warming up can involve a light jog or activity so that your muscles are warm and ready. For each stretch you should hold it for thirty seconds without bouncing.
When exercising consistently it is important to have a diet that supports this activity. Having the right diet can maximize performance and results. Proper nutrition for athletes can prevent conditions like injuries, contribute to better sleep, fuel performance, and help gain a competitive edge. Carbohydrates, protein, and healthy fats allow athletes to maintain stamina and endurance. What each athlete needs usually depends on them individually so it's important to pay attention to your diet and figure out what balance works for your body. Hydration is another key part of maintaining good nutrition. Water provides musculoskeletal lubrication as well as helps to transport nutrients throughout your body which is key to your body being able to perform.


A Heading
My Hero Element
The title attribute
Mouse over this paragraph, to display the title attribute as a tooltip.


"We've all tried to bunk our gym session or dance class. A single routine can get monotonous. That's why I have decided to make my fitness regime fun by incorporating different workouts into my schedule. From dancing to yoga, I plan to keep it as interesting as possible so I'm never bored of working out".


Home
About
Portfolio
Contact
I am
Zulfa Hamadi
.
Web developer
focused on crafting clean
and user-friendly experiences :-)


Senc1
Provides a simple interface to SPHENC1 (XDM 1.0) based algorithms.
More...
Detailed Description
Provides a simple interface to SPHENC1 (XDM 1.0) based algorithms.
Release Support: G711, G726, G729 and ILBC. Due to defects in G711 Encoder v 1.11.001 and ILBC Encoder v 1.10.002, this release will not work with these versions.
Typical usage:
Typedef Documentation
Handle through which to reference a Speech Encode algorithm.
Function Documentation
| Senc1_Handle Senc1_create |
( |
Engine_Handle |
hEngine, |
|
|
Char * |
codecName, |
|
|
SPHENC1_Params * |
params, |
|
|
SPHENC1_DynamicParams * |
dynParams | |
|
) |
| | |
Creates a Speech Encode (XDM 1.0) algorithm instance.
- Parameters:
-
| [in] | hEngine | An opened engine containing the algorithm to create. |
| [in] | codecName | The name of the algorithm to open. Corresponds to the string name given in the .cfg file. |
| [in] | params | XDM parameters to use while creating the codec. |
| [in] | dynParams | XDM dynamic parameters to use while creating the codec. |
- Return values:
-
| Handle | for use in subsequent operations (see Senc1_Handle). |
| NULL | for failure. |
Encodes a Speech buffer.
- Parameters:
-
| [in] | hSe1 | The Senc1_Handle to use for decoding. |
| [in] | hInBuf | The Buffer_Handle for the buffer containing the raw data. |
| [in] | hOutBuf | The Buffer_Handle for the buffer to fill with encoded data. |
- Return values:
-
| DMAI_EOK | for success. |
| Negative value | for failure, see Dmai.h. |
Deletes a Speech Encode algorithm instance.
- Parameters:
-
- Return values:
-
| DMAI_EOK | for success. |
| Negative value | for failure, see Dmai.h. |
Get the SPHENC1 handle from the Senc1 module instance.
- Parameters:
-
| [in] | hSe1 | The Senc1_Handle for which to get the SPHENC1 handle. |
- Return values:
-
| Handle | to the speech1 encode algorithm, see the XDM documentation for SPHENC1. |
Get the input buffer size required by the codec.
- Parameters:
-
| [in] | hSe1 | The Senc1_Handle for which to get the buffer size. |
- Return values:
-
| Size | in bytes of the input buffer required. |
Get the output buffer size required by the codec.
- Parameters:
-
| [in] | hSe1 | The Senc1_Handle for which to get the buffer size. |
- Return values:
-
| Size | in bytes of the output buffer required. |
Variable Documentation
Default XDM parameters for a Speech Encode algorithm.
size = sizeof(SPHENC1_Params),
frameSize = 160,
compandingLaw = 1,
packingType = 0,
vadSelection = 0,
codecSelection = 0,
bitRate = 0,
reserved = 0,
**tablesPtr = NULL,
Default XDM dynamic parameters for a Speech Decode algorithm.
size = sizeof(SPHENC1_DynamicParams),
frameSize = 0,
bitRate = 0,
mode = 0,
vadFlag = ISPEECH1_VADFLAG_DEFAULT,
noiseSuppressionMode = 0,
ttyTddMode = 0,
dtmfMode = 0,
dataTransmit = 0,
reserved = 0,


Nikhils' Pizza Place
Pick your size
Regular = 0
Small = 1
Medium = 2
Large = 3
Extra Large = 4
Regular
Small
Medium
Large
Extra Large
Pick your toppings
Ham
Sausage
Chicken
Bacon
Add Pizza
Clear Order


|
areaDetector
3-12-1
EPICS areaDetector framework
|
Area Detector class enabling multi-ROI driver for the Andor CCD. More...
#include <CCDMultiTrack.h>
Public Member Functions | |
| size_t | size () const |
| int | CCDMultiTrackStart () const |
| int | CCDMultiTrackEnd () const |
| int | CCDMultiTrackBin () const |
| int | TrackStart (size_t TrackNum) const |
| int | TrackEnd (size_t TrackNum) const |
| int | TrackHeight (size_t TrackNum) const |
| int | TrackBin (size_t TrackNum) const |
| int | DataHeight () const |
| int | DataHeight (size_t TrackNum) const |
| CCDMultiTrack (asynPortDriver *asynPortDriver) | |
| asynStatus | writeInt32Array (asynUser *pasynUser, epicsInt32 *value, size_t nElements) |
| void | storeTrackAttributes (NDAttributeList *pAttributeList) |
Area Detector class enabling multi-ROI driver for the Andor CCD.
This class is used by CCD camera modules that permit multiple regions-of-interest.
Multi-ROI is typically used for multi-track spectrocopy application.
| CCDMultiTrack::CCDMultiTrack | ( | asynPortDriver * | asynPortDriver | ) |
|
inline |
|
inline |
|
inline |
| int CCDMultiTrack::DataHeight | ( | ) | const |
|
inline |
|
inline |
| void CCDMultiTrack::storeTrackAttributes | ( | NDAttributeList * | pAttributeList | ) |
|
inline |
|
inline |
|
inline |
|
inline |
| asynStatus CCDMultiTrack::writeInt32Array | ( | asynUser * | pasynUser, |
| epicsInt32 * | value, | ||
| size_t | nElements | ||
| ) |


|
| static T | Read< T > (string path) |
| |
| static void | Write< T > (string path, T data, Formatting formatting=Formatting.Indented) |
| |
| static string | MakeRelativePath (string fromPath, string toPath) |
| | Creates a relative path from one file or folder to another. More...
|
| |
Definition at line 10 of file JsonFile.cs.
◆ MakeRelativePath()
| static string WebApplication.Utils.JsonFile.MakeRelativePath |
( |
string |
fromPath, |
|
|
string |
toPath |
|
) |
| |
|
static |
Creates a relative path from one file or folder to another.
- Parameters
-
| fromPath | Contains the directory that defines the start of the relative path. |
| toPath | Contains the path that defines the endpoint of the relative path. |
- Returns
- The relative path from the start directory to the end path or
toPath
if the paths are not related.
- Exceptions
-
| ArgumentNullException | |
| UriFormatException | |
| InvalidOperationException | |
Definition at line 31 of file JsonFile.cs.
◆ Read< T >()
| static T WebApplication.Utils.JsonFile.Read< T > |
( |
string |
path | ) |
|
|
static |
◆ Write< T >()
| static void WebApplication.Utils.JsonFile.Write< T > |
( |
string |
path, |
|
|
T |
data, |
|
|
Formatting |
formatting = Formatting.Indented |
|
) |
| |
|
static |
The documentation for this class was generated from the following file:
- D:/Users/Ferran/git/HADSProject-Fork/WebApplication/Utils/JsonFile.cs


Pixel Perfect
This exercise expands the first exercise.
Your simple webpage, will now transform into an email client website!
- Your toolbar should now contain a logo image and a title.
- You can download the image here
- The navigation panel will have 2 available options:
- Inbox
- Outgoing Mail
- Your content will contain a list of mails, each with a subject, sender name, and a preview and a mail importance.
- A new mail button will be added
The end result should look EXACTLY like this:
NOTE: The application is only a mock, nothing should do anything.
To get a hold of the icons do:
npm i mdi
Make sure NodeJS is installed beforehand


An electrically excited synchronous generator is started direct on line utilizing the damper cage (and the shorted excitation winding) at 0 seconds.
At t = 0.5 seconds, the excitation voltage is raised to achieve the no-load excitation current. Note, that reactive power of the stator goes to zero.
At t = 2 second, a driving torque step is applied to the shaft (i.e. the turbine is activated). Note, that active and reactive power of the stator changes. To drive at higher torque, i.e., produce more electric power, excitation has to be adapted.
Simulate for 3 seconds and plot:
smee.tauElectrical
smee.wMechanical
smee.ie
rotorDisplacementAngle.rotorDisplacementAngle
currentQuasiRMSSensor.I
electricalPowerSensor.P
electricalPowerSensor.Q
mechanicalMultiSensor.power
Default machine parameters are used.
The mains switch is closed at time = 0 in order to avoid non
physical noise calculated by the
rotorDisplacementAngle
. This noise is caused by the
interaction of the high resistance of the switch and the machine,
see #2388.


The derivation options used to derive the key used to seal the message, and which can be used to re-derive the key needed to unseal it.
Any unsealing instructions that parties able to unseal the message should be aware of. These are stored in plaintext and are meant to be readable by anyone with a copy of the message. However, the message cannot be unsealed if these instructions have been modified.
Generated using TypeDoc
The encrypted contents of the message


This is a graph of $f(z) = (w-z)/z$. Your mouse position is the $z$.
This is a graph of $f(z) = z^2 + z + 1$. You can use the scroll wheel to zoom, and drag to pan.


WITNESS LIST
Higher Education
April 15, 2014 9:00 AM
Interim Charge One: Closing the Gaps by 2015
ON:
Faulkner, Larry Vice Chair (also providing written testimony) (Higher Education Strategic
Planning Committee), Austin, TX
Gardner, David Deputy Commissioner (also providing written testimony) (Texas Higher
Education Coordinating Board), Austin, TX
Hellyer, Brenda Chancellor (also providing written testimony) (San Jacinto College),
Pasadena, TX
Helmcamp, Leslie Policy Analyst (also providing written testimony) (Center for Public
Policy Priorities), Austin, TX
Hunt, Woody Chair (also providing written testimony) (Higher Education Strategic
Planning Committee), Austin, TX
Sanchez, Jose (Young Invincibles), Houston, TX
Sylvia, Leal Vice President of Enrollment at UT Brownsville (also providing written
testimony) (UT Brownsville), Brownsville, TX
Weeden, Dustin Policy Specialist (also providing written testimony) (National Conference
of State Legislatures), Denver, CO


Home
Profile
Logout
Employee Home page
Pending Reimbursements
✚ New Request
There are no pending requests
Approved Reimbursements
There are no approved requests
Denied Reimbursements
There are no denied requests


|
Important Security Notice
- Our bank NEVER send e-mails that ask customers to provide their account number, password or any personal information or verify their accounts online.
- Customers are reminded NOT to access their Net Banking service through hyperlinks embedded in any e-mails or Internet search engines.
- Customers are reminded NOT to use easy-to-guess password such as ID number, date of birth, telephone number or repetitive numbers as your password and change your password regularly.
- This site uses 256 bit SSL encryption to secure and protect all personal information contained in online transactions between Public Bank (Hong Kong) and our customers.
- Install firewall and virus detection software on your computer and update them regularly to protect your computer against virus and hackers.
Learn more about Electronic Banking Security
|


.length
of an array in the condition part of a
loop statement. In highly resource constrained environments, such calls may
have adverse performance implications.
Example:
void foo(Object[] x) {
for (int i = 0; i < x.length; i++) { /**/ }
}
This inspection is intended for Java ME and other highly resource constrained environments. Applying the results of this inspection without consideration might have negative effects on code clarity and design.


My Registration Form
First Name
Last Name
Email
Password
PW Confirmation
Birthday
Male
Female
Other
A short description about yourself:
Favorite Language
Javascript
HTML
CSS
Python
Ruby
Swift
PHP
C#


The winner will recieve a business website, built for free, including a years hosting, if required .
The Fump Web team are truly talented professionals and jolly nice people so please do get in touch


Imagine we have the sequence 2 5 3 4 7, and we want to discover the median or middle element. If we do this with the function std::nth_element(), one result might be the following sequence:
3 2 | 4 | 7 5
The vertical bars are used to describe the separation of the result into three parts: the elements before the requested value, the requested value, and the values after the requested value. Note that the values in the first and third sequences are unordered; in fact, they can appear in the result in any order. The only requirement is that the values in the first part are no larger than the value we are seeking, and the elements in the third part are no smaller than this value.
The three iterators provided as arguments to the algorithm std::nth_element() divide the argument sequence into the three sections we just described. These are the section prior to the middle iterator, the single value denoted by the middle iterator, and the region between the middle iterator and the end. Either the first or third of these may be empty.
The arguments to the algorithm can be described as follows:
namespace std { void nth_element(RandomAccessIterator first, RandomAccessIterator nth, RandomAccessIterator last [, Compare ] ); }
Following the call on std::nth_element(), the nth smallest value (as determined by the optional Compare predicate, or by std::less, when none is specified) is copied into the position denoted by the middle iterator. The region between the first iterator and the middle iterator will have values no larger than the nth element, while the region between the middle iterator and the end will hold values no smaller than the nth element.
The example program illustrates finding the fifth smallest value in a vector of random numbers.
void nth_element_example() // illustrates the use of the nth_element algorithm // see alg7.cpp for complete source code { // make a vector of random integers std::vector<int> aVec(10); std::generate(aVec.begin(), aVec.end(), randomValue); // now find the 5th smallest value std::vector<int>::iterator nth = aVec.begin() + 4; std::nth_element(aVec.begin(), nth, aVec.end()); std::cout << "fifth smallest is " << *nth << std::endl; }


Greetings! I'm James Scott a Full-stack Developer from Jacksonville, Florida. I originally found a passion for coding during college while working C++ and taking Object Oriented courses. After college I decided to further pursue Web Development. I enjoy Angular and React but I can also do backend such as Node and SQL. Please reach out to me as I enjoy meeting new people and obtaining new experiences! Thanks for stopping by.


Typing in the fields below should not move the cursor to the end of the input. Especially in Chrome
All inputs should update with the same value
Typing in an input should not prevent it from being updated by other inputs


Interface¶
CryptoFactory
is the main client interface to access all Crypto-Factory
features. Its principal role is to offer common methods to execute cryptography
tasks from different Crypto providers (or implementations).
Also, it provides ‘synthetic’ methods for advanced features such as data tagging mechanism or ability to rotate between keys and encryption algorithms.
As the client interface, it has entry-points to manage underneath Crypto providers, to consume several utilities or helpers, and to access templates for building your own Crypto services.
Features¶
Crypto services management (See
factory
module.)Abstraction methods for encryption; rely on underneath Crypto services (See
providers
module.)Tagging mechanism
Advanced method(s) such as
rotate
to migrate encrypted data to another Crypto serviceCrypto utilities such as generate random keys and strings, inspect tags or encoding functions (See
utilities
module.)Built-in Crypto providers for direct use of defined encryption algorithms (See
providers
module.)Crypto templates for building your own encryption algorithms (See
providers
module.)
For details, check relative API documentation.


Preparation time
less than 30 mins
Cooking time
1 to 2 hours
Serves
Serves 8
Dietary
Make crème brûlée extra special by serving it inside egg shells - how fun! Serve with sugared almonds and rhubrab purée for a standout dessert that is bound to impress.
Equipment: You will need an egg cutter and a chef's blowtorch.
Using an egg cutter, cut the top off the large eggs and pour out the contents. Dry the egg shells out.
Put the egg yolks in a bowl, add the caster sugar and vanilla seeds. Whisk together until pale, fluffy and well combined.
In a small pan, bring the milk and cream to a gentle boil. Gradually pour over the egg mixture.
Pour the mix back in the pan and cook until it has thickened, and coats the back of a spoon. Leave aside to cool.
Carefully ladle the mixture into the dried egg shells. Just before serving sprinkle the demerara sugar on top and carmelise it using a chef's blowtorch.
For the almonds, preheat the oven to 130C/110C Fan/Gas 1 and line a baking tray.
Lightly beat the egg white with 1 tablespoon water. Add the almonds and stir until well-coated. Mix the sugar and salt together and sprinkle over the nuts. Toss to coat, and spread evenly on the tray.
Cook for 1 hour in the oven, stirring occasionally, until golden-brown. Leave to cool.
Increase the oven temperature to 200C/180C Fan/Gas 6.
Put the rhubarb in a roasting tin. Sprinkle over the sugar, then drizzle over the juice. Roast the rhubarb in the oven for 8-12 minutes, or until just tender. Leave to cool. Place in a blender and blend until smooth.
Serve the crème brûlée egg on a serving plate alongside the rhubarb purée and sugared almonds.


Programmeerproject
Eefje Roelfsema Student number: 10993673
Welcome to my website. Here, you can see my final assignment. Click the link to view them! Enjoy.
To see my Final project, click here!


TRANQUIL BOOTS
1025
Active: Heal - Restores 250 HP over 20 seconds for the wearer. If you take damage from another player or Roshan, the heal is lost.
Passive: Break - If you take damage 3 times in 10 seconds, Tranquil Boots become Boots of Speed until the last 10 seconds don't have 3 instances of damage.
+ 75 Movement Speed
+ 3 Armor
+ 3 HP Regeneration
25
60
While they increase the longevity of the wearer, this boot is not particularly reliable.


Note
Click here to download the full example code
Simulate raw data using subject anatomy¶
This example illustrates how to generate source estimates and simulate raw data
using subject anatomy with the mne.simulation.SourceSimulator
class.
Once the raw data is simulated, generated source estimates are reconstructed
using dynamic statistical parametric mapping (dSPM) inverse operator.
# Author: Ivana Kojcic<EMAIL_ADDRESS># Eric Larson<EMAIL_ADDRESS># Kostiantyn Maksymenko<EMAIL_ADDRESS># Samuel Deslauriers-Gauthier<EMAIL_ADDRESS># License: BSD (3-clause)
import os.path as op
import numpy as np
import mne
from mne.datasets import sample
print(__doc__)
# To simulate the sample dataset, information of the sample subject needs to be
# loaded. This step will download the data if it not already on your machine.
# Subjects directory is also set so it doesn't need to be given to functions.
data_path = sample.data_path()
subjects_dir = op.join(data_path, 'subjects')
subject = 'sample'
meg_path = op.join(data_path, 'MEG', subject)
# First, we get an info structure from the sample subject.
fname_info = op.join(meg_path, 'sample_audvis_raw.fif')
info = mne.io.read_info(fname_info)
tstep = 1 / info['sfreq']
# To simulate sources, we also need a source space. It can be obtained from the
# forward solution of the sample subject.
fwd_fname = op.join(meg_path, 'sample_audvis-meg-eeg-oct-6-fwd.fif')
fwd = mne.read_forward_solution(fwd_fname)
src = fwd['src']
# To simulate raw data, we need to define when the activity occurs using events
# matrix and specify the IDs of each event.
# Noise covariance matrix also needs to be defined.
# Here, both are loaded from the sample dataset, but they can also be specified
# by the user.
fname_event = op.join(meg_path, 'sample_audvis_raw-eve.fif')
fname_cov = op.join(meg_path, 'sample_audvis-cov.fif')
events = mne.read_events(fname_event)
noise_cov = mne.read_cov(fname_cov)
# Standard sample event IDs. These values will correspond to the third column
# in the events matrix.
event_id = {'auditory/left': 1, 'auditory/right': 2, 'visual/left': 3,
'visual/right': 4, 'smiley': 5, 'button': 32}
Out:
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Reading forward solution from /home/circleci/mne_data/MNE-sample-data/MEG/sample/sample_audvis-meg-eeg-oct-6-fwd.fif...
Reading a source space...
Computing patch statistics...
Patch information added...
Distance information added...
[done]
Reading a source space...
Computing patch statistics...
Patch information added...
Distance information added...
[done]
2 source spaces read
Desired named matrix (kind = 3523) not available
Read MEG forward solution (7498 sources, 306 channels, free orientations)
Desired named matrix (kind = 3523) not available
Read EEG forward solution (7498 sources, 60 channels, free orientations)
MEG and EEG forward solutions combined
Source spaces transformed to the forward solution coordinate frame
366 x 366 full covariance (kind = 1) found.
Read a total of 4 projection items:
PCA-v1 (1 x 102) active
PCA-v2 (1 x 102) active
PCA-v3 (1 x 102) active
Average EEG reference (1 x 60) active
In order to simulate source time courses, labels of desired active regions need to be specified for each of the 4 simulation conditions. Make a dictionary that maps conditions to activation strengths within aparc.a2009s 1 labels. In the aparc.a2009s parcellation:
‘G_temp_sup-G_T_transv’ is the label for primary auditory area
‘S_calcarine’ is the label for primary visual area
In each of the 4 conditions, only the primary area is activated. This means that during the activations of auditory areas, there are no activations in visual areas and vice versa. Moreover, for each condition, contralateral region is more active (here, 2 times more) than the ipsilateral.
activations = {
'auditory/left':
[('G_temp_sup-G_T_transv-lh', 100), # label, activation (nAm)
('G_temp_sup-G_T_transv-rh', 200)],
'auditory/right':
[('G_temp_sup-G_T_transv-lh', 200),
('G_temp_sup-G_T_transv-rh', 100)],
'visual/left':
[('S_calcarine-lh', 100),
('S_calcarine-rh', 200)],
'visual/right':
[('S_calcarine-lh', 200),
('S_calcarine-rh', 100)],
}
annot = 'aparc.a2009s'
# Load the 4 necessary label names.
label_names = sorted(set(activation[0]
for activation_list in activations.values()
for activation in activation_list))
region_names = list(activations.keys())
# Define the time course of the activity for each region to activate. We use a
# sine wave and it will be the same for all 4 regions.
source_time_series = np.sin(np.linspace(0, 4 * np.pi, 100)) * 10e-9
Create simulated source activity¶
Here, SourceSimulator
is used, which allows to
specify where (label), what (source_time_series), and when (events) event
type will occur.
We will add data for 4 areas, each of which contains 2 labels. Since add_data method accepts 1 label per call, it will be called 2 times per area. All activations will contain the same waveform, but the amplitude will be 2 times higher in the contralateral label, as explained before.
When the activity occurs is defined using events. In this case, they are taken from the original raw data. The first column is the sample of the event, the second is not used. The third one is the event id, which is different for each of the 4 areas.
source_simulator = mne.simulation.SourceSimulator(src, tstep=tstep)
for region_id, region_name in enumerate(region_names, 1):
events_tmp = events[np.where(events[:, 2] == region_id)[0], :]
for i in range(2):
label_name = activations[region_name][i][0]
label_tmp = mne.read_labels_from_annot(subject, annot,
subjects_dir=subjects_dir,
regexp=label_name,
verbose=False)
label_tmp = label_tmp[0]
amplitude_tmp = activations[region_name][i][1]
source_simulator.add_data(label_tmp,
amplitude_tmp * source_time_series,
events_tmp)
# To obtain a SourceEstimate object, we need to use `get_stc()` method of
# SourceSimulator class.
stc_data = source_simulator.get_stc()
Simulate raw data¶
Project the source time series to sensor space.  Use the apply_proj method to apply it.
Adding noise to 366/376 channels (366 channels in cov)
Sphere : origin at (0.0 0.0 0.0) mm
radius : 90.0 mm
Source location file : dict()
Assuming input in millimeters
Assuming input in MRI coordinates
Positions (in meters) and orientations
2 sources
blink simulated and trace stored on channel: EOG 061
Setting up forward solutions
Computing gain matrix for transform #1/1
Sphere : origin at (0.0 0.0 0.0) mm
radius : 90.0 mm
Source location file : dict()
Assuming input in millimeters
Assuming input in MRI coordinates
Positions (in meters) and orientations
1 sources
ecg simulated and trace not stored
Setting up forward solutions
Computing gain matrix for transform #1/1
Reconstruct simulated source time courses using dSPM inverse operator¶
Here, source time courses for auditory and visual areas are reconstructed separately and their difference is shown. This was done merely for better visual representation of source reconstruction. As expected, when high activations appear in primary auditory areas, primary visual areas will have low activations and vice versa.
method, lambda2 = 'dSPM', 1. / 9.
epochs = mne.Epochs(raw_sim, events, event_id)
inv = mne.minimum_norm.make_inverse_operator(epochs.info, fwd, noise_cov)
stc_aud = mne.minimum_norm.apply_inverse(
epochs['auditory/left'].average(), inv, lambda2, method)
stc_vis = mne.minimum_norm.apply_inverse(
epochs['visual/right'].average(), inv, lambda2, method)
stc_diff = stc_aud - stc_vis
brain = stc_diff.plot(subjects_dir=subjects_dir, initial_time=0.1,
hemi='split', views=['lat', 'med'])
Out:
320 matching events found
Applying baseline correction (mode: mean)
Not setting metadata
Created an SSP operator (subspace dimension = 4)
4 projection items activated
Converting forward solution to surface orientation
Average patch normals will be employed in the rotation to the local surface coordinates....
Converting to surface-based source orientations...
[done]
Computing inverse operator with 364 channels.
364 out of 366 channels remain after picking
Selected 364 channels
Creating the depth weighting matrix...
203 planar channels
limit = 7262/7498 = 10.020865
scale = 2.58122e-08 exp = 0.8
Applying loose dipole orientations. Loose value of 0.2.
Whitening the forward solution.
Created an SSP operator (subspace dimension = 4)
Computing data rank from covariance with rank=None
Using tolerance 3.3e-13 (2.2e-16 eps * 305 dim * 4.8 max singular value)
Estimated rank (mag + grad): 302
MEG: rank 302 computed from 305 data channels with 3 projectors
Using tolerance 4.7e-14 (2.2e-16 eps * 59 dim * 3.6 max singular value)
Estimated rank (eeg): 58
EEG: rank 58 computed from 59 data channels with 1 projector
Setting small MEG eigenvalues to zero (without PCA)
Setting small EEG eigenvalues to zero (without PCA)
Creating the source covariance matrix
Adjusting source covariance matrix.
Computing SVD of whitened and weighted lead field matrix.
largest singular value = 5.49264
scaling factor to adjust the trace = 1.64e+19
Preparing the inverse operator for use...
Scaled noise and source covariance from nave = 1 to nave = 5
Created the regularized inverter
Created an SSP operator (subspace dimension = 4)
Created the whitener using a noise covariance matrix with rank 360 (4 small eigenvalues omitted)
Computing noise-normalization factors (dSPM)...
[done]
Applying inverse operator to "auditory/left"...
Picked 364 channels from the data
Computing inverse...
Eigenleads need to be weighted ...
Computing residual...
Explained 99.4% variance
Combining the current components...
dSPM...
[done]
Preparing the inverse operator for use...
Scaled noise and source covariance from nave = 1 to nave = 3
Created the regularized inverter
Created an SSP operator (subspace dimension = 4)
Created the whitener using a noise covariance matrix with rank 360 (4 small eigenvalues omitted)
Computing noise-normalization factors (dSPM)...
[done]
Applying inverse operator to "visual/right"...
Picked 364 channels from the data
Computing inverse...
Eigenleads need to be weighted ...
Computing residual...
Explained 99.5% variance
Combining the current components...
dSPM...
[done]
Using control points [<PHONE_NUMBER>2<PHONE_NUMBER>6 1588.53915011]


The HTML comments in this page contain the configurationinformation that allows users to edit pages in your web using the Microsoft Web Publishing Wizard or programs which use the Microsoft Web Publishing Wizard such as FrontPad using the same username and password they would use if they were authoring with Microsoft FrontPage. Please refer to the Microsoft's Internet SDK for more information on the Web Publishing Wizard APIs.


Jenkins can scan workspace files for open tasks, like TODO or FIXME markers or @deprecated tags. When this option is configured, Jenkins can provide useful information about open tasks, such as historical result trend, web UI for viewing the tasks, and so on.
This plug-in is not invoked for failed builds, it is only called for stable or unstable builds (i.e., a build with failed tests).


ALAPPEY BEACH
Beach goers on a Kerala trip will surely fall in love with this stunning beach in Alappuzha! Quiet, calm, serene, and pleasant, Alleppey Beach is known for its favourable ambience, tepic sands, and a myriad list of beach activities. If luck favours, visitors can also enjoy dolphin sighting while in Alleppey Beach.


The pIAno is a revolutionary new piano “robot” that is paving the interdisciplinary field of music and artificial intelligence. With the pIAno, you can easily earn how to play your favorite genre/type of music on piano!
1. Play some of your favorite songs on the pIAno.
2. Press the “instruct” me button.
3. The pIAno uses proprietary machine learning algorithms that uses the songs that you played as input in order to create an instructional plan that is unique to you. The plan will incorporate both the type of music you like and help you become more advance at the piano.
4. The pIAno has LED lights at the bottom of each key to show the player which notes to play and when.
5. Whether it’s Bach, Polka or House,we have you covered. pIAno slowly teaches you relevant techniques with increasing complexity and even has instantaneous error correction.
| Item Description | Cost |
|---|---|
| Cutting edge IBM Power9 chip that incorporates our proprietary machine learning algorithm | $30.00 |
| LED lights for each key | $10.00 |
| Physical Piano | $300.00 |
| Shipping & Handling | $300.00 |
| Final Cost of Production | $400.00 |
Retail Price: $500.00, resulting in a 20% profit margin
Learning piano traditionally has a set, stiff path of learning, with end goal being complex pieces of classical music. This turns off many hopeful musicians to pursuing this instrument. Our product, pIAno, tailors education to YOUR interests. With artificial intelligence, we not only teach you the techniques you want to learn, but we teach it to fit your learning style!
Our proprietary AI algorithm uses GAN’s (Generative Adversarial Networks), a rapidly developing branch of Artificial Intelligence that can create new media based on given inputs. GAN’s are a type of unsupervised learning, which means the network receives just the input and is told to derive some structure or pattern by looking at the relationships between the inputs. With the power of GAN’s, pIAno is able to develop new music similar to the tastes of the user.
Besides for continuously refining our machine learning algorithm, a future improvement to our product will be an integration with the Khan Academy learning site. Khan Academy is an educational website that uses AI in order to create an educational plan for students in academic areas. Our products integration with Khan academy will allow for a better student experience and seamless integration in and out of the classroom. This will lead to students advancement in education, but also curiosity driven self-learning, an essential skill for the new age.
Given popular culture and interpretation of it in movies, many associate Artificial Intelligence with Terminator-like scenarios where machines rise up against humans. However, this is not the case! Our product, pIAno, uses artificial intelligence to help teach you, just as a human piano teacher might. However, pIAno does it in a smarter, quicker, more efficient manner. We put in great efforts to ensure that our robot follows Isaac Asimov’s Three Laws of Robotics and is as safe and secure as possible.
The main potential liability and safety concern of the pIAno is privacy. There is a worry with privacy when it comes to data storage but pIAno uses only the more secure data storage services available. pIAno uses the industry standard of AES-235 when encrypting data.
Artificial intelligence is a leading edge technology which uses progressive learning algorithms in which machines are trained to look for patterns and using this information, they can perform specific tasks.
There are many applications of Artificial Intelligence. We already see this today in all aspects of life- with intelligent appliances that can predict when you’ll need to use them or semi autonomous vehicles to aid our commute, we are increasingly delving into an AI world. Some future possible implications are especially exciting.
| Commercial |
|
|---|---|
| Educational |
|
| Recreational |
|
| Research |
|
| Personal |
|
And practically everything else!
Using deep neural networks, AI can gain incredible accuracy and also get the most out of data.


Notebooks
Story: Klaas Paai or ≠enn (at Breakwater)
Klaas Paai or ≠enn (at Breakwater)
Title
Klaas Paai or ≠enn (at Breakwater)
Collection
Summary
Names of three Bushmen and another Native, who were at the Breakwater Convict Station in 1875, together with a little information regarding them. Taken down in English (L V.-19. 5445-5447, 5453-5456). ≠enn (Klaas Paai) provides Lloyd with some personal details and the names of some of his closest relations, including his wife and parents.
Comments
1) This story is found in Book V-19
Contributors
Date
October 1875
Categories
Keywords
Breakwater Convict Station (|xam prisoners at) , Breakwater Convict Station (prisoners' numbers) , Breakwater Convict Station (≠enn at) , names (of |xam at the Breakwater) , names (of ≠enn's relations) , names (≠enn's Dutch name was Klaas Paai) , names (≠enn at Breakwater) , ≠enn (Klaas Paai) , ≠enn (at Breakwater) , ≠enn (his prisoner number was 7884) , ≠enn (his father's place) , ≠enn (he ate from a stolen sheep with Hendrik) , ≠enn (his personal history) , ≠enn (his genealogy) , ≠enn (the names of his relations) , ≠enn (and Dia!kwain) , personal history (of ≠enn) , personal history (≠enn at Breakwater) , genealogy (of |xam prisoners at the Breakwater) , genealogy (of ≠enn at Breakwater) , place (≠enn 's father's) , place (and ≠enn at Breakwater) , hunger (≠enn ate from a stolen sheep with Hendrik) , hunger (≠enn at Breakwater) , starvation (≠enn ate from a stolen sheep with Hendrik) , starvation (≠enn at Breakwater)
Story Pages
5447, 5454


WITNESS LIST
Criminal Jurisprudence Committee
April 22, 2014 - 2:00 PM
Examine mental health issues with youth in the justice system
On:
Flores, Homer (Nueces county)
Frost, Lynda (Hogg Foundation for Mental Health)
Garnett, Susan (MHMR of Tarrant County)
Isaack, Angela (Legislative Budget Board)
Levin, Marc (Texas Public Policy Foundation Center for Effective Justice)
Lewis, Kathryn (Disability Rights Texas)
Mata, Jill (Self; Bexar County District Attorneys Office)
Matthew, Scott (Williamson county juvenile services)
Medina, Estela (Travis county juvenile probation department)
Meurer, W. Jeanne (Self; Travis County Juvenile Probation Dept.)
Niemeyer, Kevin (Legislative budget board)
Pirtle, Danny (Dallas County Juvenile Department)
Saxton, Josette (Texans Care for Children)
Stroud, Teresa (Texas Juvenile Justice Department)
Unruh, Debbie (Self)
Vela, Andrea (Behavioral Health Center of Nueces County)
Von stultz, Jeannie (Bexar county juvenile probation)
Williams, James (Texas Juvenile Justice Department)
Registering, but not testifying:
On:
Humphrey, Susan (Bell County Juvenile Services and Central Tx Chiefs Assoc)
Lowrance, Diane (Behavioral health center nueces county)
1


PERFECT
COCKTAIL
Cocktail Name
Ingredient
Category
Alcohol / Non Alcohol
My Favorites
Search Cocktails by Alcohol / Non Alcohol
Alcoholic
Non Alcoholic
Get Cocktails
Results:
×
Preparation:
Ingredients:


| MATLAB 文件帮助: cv.transform | 查看 cv.transform 的代码 | Index |
transform Performs the matrix transformation of every array element
dst = cv.transform(src, mtx)
mtx
or columns-1 of mtx
src
.
It has as many channels as rows of mtx
The function cv.transform performs the matrix transformation of every
element of the array src
and stores the results in dst
:
when columns of mtx
equal channels of src
:
dst(I) = mtx * src(I)
when columns of mtx
equal channels+1 of src
:
dst(I) = mtx * [src(I); 1]
Every element of the N-channel array src
is interpreted as N-element
vector that is transformed using the MxN or Mx(N+1) matrix mtx
to
M-element vector - the corresponding element of the destination array
dst
.
The function may be used for geometrical transformation of N-dimensional points, arbitrary linear color space transformation (such as various kinds of RGB to YUV transforms), shuffling the image channels, and so forth.
This function is equivalent to the following MATLAB code:
function dst = my_transform(src, mtx)
% check sizes
[I,J,N] = size(src);
[MM,NN] = size(mtx);
assert(N==1 || N==2 || N==3 || N==4, '1 to 4 channels');
assert(N==NN || (N+1)==NN, 'Wrong dimensions');
if N ~= NN, src(:,:,end+1) = 1; end
% transform
dst = zeros([I,J,MM], class(src));
for i=1:I
for j=1:J
dst(i,j,:) = mtx * squeeze(src(i,j,:));
end
end
end


John O'Groats to Land's End - only 897miles!
Thursday 24th December, 11:45am
That's it folks! Have a great Christmas, & Happy New Year - see you on the 4th!
1.609 Km = 1 mile
2000 Steps walking briskly = 1 mile
Calculations rounded to 2 decimal places.
| Miles | |
|---|---|
| Team B | 988.57 |
| Team C | 914.22 |
| Team A | 848.51 |
| Miles | ||
|---|---|---|
| Team | Name | |
| Team B | Paul Carabini | 227.09 |
| Adela Kaczmarek Araujo | 132.77 | |
| Paul Mackenzie | 116.86 | |
| Miaya Mattoo | 97.98 | |
| Della Discombe | 73.13 | |
| Sarah Farragher | 71.26 | |
| Sarah Blatchley | 66.92 | |
| Prakash Tailor | 65.10 | |
| Parmjit Kalsi | 56.00 | |
| Niraj Samani | 48.00 | |
| Faisal Hamid | 33.46 | |
| Team C | Vicky Preston | 123.53 |
| Jacqueline Tofangsazan | 104.82 | |
| Hellen Lawuo-Meena | 104.40 | |
| Paul Polden | 101.27 | |
| Ian Chapman | 97.80 | |
| Dennis Hughes | 84.99 | |
| Rob Murray | 77.63 | |
| Rita Kumar | 65.72 | |
| Rocio Megino Garcia | 64.86 | |
| Chris Goode | 58.80 | |
| Kirsten Butler | 30.40 | |
| Team A | Shai Umradia | 101.90 |
| Paula Mcaleavey | 95.04 | |
| Martin Baker | 89.88 | |
| Hema Sivey | 87.22 | |
| Rachel Charlton | 83.60 | |
| Kushal Paraskar | 80.34 | |
| Amarjit Gill | 73.28 | |
| Andrew Floyd | 72.13 | |
| Katie White | 59.32 | |
| Daniel Perez | 57.80 | |
| Jyotika Patel | 48.00 |
| Miles | |
|---|---|
| Name | |
| Paul Carabini | 227.09 |
| Adela Kaczmarek Araujo | 132.77 |
| Vicky Preston | 123.53 |
| Paul Mackenzie | 116.86 |
| Jacqueline Tofangsazan | 104.82 |
| Hellen Lawuo-Meena | 104.40 |
| Shai Umradia | 101.90 |
| Paul Polden | 101.27 |
| Miaya Mattoo | 97.98 |
| Ian Chapman | 97.80 |
| Paula Mcaleavey | 95.04 |
| Martin Baker | 89.88 |
| Hema Sivey | 87.22 |
| Dennis Hughes | 84.99 |
| Rachel Charlton | 83.60 |
| Kushal Paraskar | 80.34 |
| Rob Murray | 77.63 |
| Amarjit Gill | 73.28 |
| Della Discombe | 73.13 |
| Andrew Floyd | 72.13 |
| Sarah Farragher | 71.26 |
| Sarah Blatchley | 66.92 |
| Rita Kumar | 65.72 |
| Prakash Tailor | 65.10 |
| Rocio Megino Garcia | 64.86 |
| Katie White | 59.32 |
| Chris Goode | 58.80 |
| Daniel Perez | 57.80 |
| Parmjit Kalsi | 56.00 |
| Jyotika Patel | 48.00 |
| Niraj Samani | 48.00 |
| Faisal Hamid | 33.46 |
| Kirsten Butler | 30.40 |


NetPlusDesign
>
Up Hill House
Summary
Generation
Usage
Heating Degree Days
Water Usage
Base Temp Analysis
Net Usage
Generation
Usage
ASHP
Water Heater
Range
Dryer
Dish Washer
Water Pump
Washer
All other
Heating Degree Days
Outdoor Temperature (Low)
Outdoor Temperature (High)
Loading...


Package openid
This package is an implementation of the OpenID specification in
Python. It contains code for both server and consumer implementations.
For information on implementing an OpenID consumer, see the openid.consumer.consumer
module. For
information on implementing an OpenID server, see the openid.server.server
module.
Contact<EMAIL_ADDRESS>Copyright: (C) 2005-2007 JanRain, Inc.
License:
Licensed under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS"
BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied. See the License for the specific language governing permissions
and limitations under the License.
| Submodules |
-
association : This module contains code for dealing with associations between
consumers and servers.
-
consumer : This package contains the portions of the library used only when
implementing an OpenID consumer.
-
consumer : OpenID support for Relying Parties (aka Consumers).
-
discover : Functions to discover OpenID endpoints from identifiers.
-
html_parse : This module implements a VERY limited parser that finds <link>
tags in the head of HTML or XHTML documents and parses out their
attributes according to the OpenID spec.
-
cryptutil : Module containing a cryptographic-quality source of randomness and
other cryptographically useful functionality
-
dh
-
extension
-
extensions
-
ax : Implements the OpenID Attribute Exchange specification, version
1.0.
-
pape : An implementation of the OpenID Provider Authentication Policy
Extension 1.0
-
sreg : Simple registration request and response parsing and object
representation
-
fetchers : This module contains the HTTP fetcher interface and several
implementations.
-
kvform
-
message : Extension argument processing code
-
oidutil : This module contains general utility code that is used throughout the
library.
-
server : This package contains the portions of the library used only when
implementing an OpenID server.
-
server : OpenID server protocol and logic.
-
trustroot : This module contains the TrustRoot class, which helps handle
trust root checking.
-
sreg : moved to openid.extensions.sreg
-
store : This package contains the modules related to this library's use of
persistent storage.
-
urinorm
-
yadis : Yadis.
-
accept : Functions for generating and parsing HTTP Accept: headers for
supporting server-directed content negotiation.
-
constants
-
discover
-
etxrd : ElementTree interface to an XRD document.
-
filters : This module contains functions and classes used for extracting
endpoint information out of a Yadis XRD file using the ElementTree XML
parser.
-
manager
-
parsehtml
-
services
-
xri : Utility functions for handling XRIs.
-
xrires : XRI resolution.
|


|
|
|
Donate with Paypal
How to do Nursing Home Ministry
|
||
|
"Click here to read how you can be involved" Listen to HLM sermons online at the following links: http://www.hisloveministries.podbean.com "Click here to view the HLM PowerPoint Presentation" A 501(c) 3 non-profit Christian Ministry
WE
LOVE THE UNLOVED THROUGH OUR NURSING His Love Ministries was originated by God placing a burden on one man's heart, basically with a few simple verses from the Bible.  - James 1:27 - Pure and undefiled religion before God and the Father is this: to visit orphans and widows in their trouble, and to keep oneself unspotted from the world. HLM conducts hundreds of church services and Bible studies yearly, in and around the Savannah, Ga area, in various Nursing Homes, Assisted Living Facilities, Prisons, Jails, Transitional Centers, Children's Centers, and Homeless Centers. To see our full schedule please go to the "Services" Page. The goal of HLM is to spread the gospel to those who really need to hear it and equip those who know Christ as Lord and Savior to minister to others. We reach out to those the World has forgotten. Please take a moment to pray and considering helping our ministry where God leads you. We always need your prayer support. If you are interested in volunteering, please contact us at<PHONE_NUMBER>. If you are interested in giving, please see our "Contact Us" page for information on giving, or simply click on the "Donate Now Through Network for Good Button" in the upper right corner of this page. For more information about our ministry, please navigate around our web site, and feel free to contact us with any questions. God Bless, and thanks for visiting! ^Top | |
||||


Nupedia
Other collaborative online encyclopedias were attempted before Wikipedia, but none were as successful.[13] Wikipedia began as a complementary project for Nupedia, a free online English-language encyclopedia project whose articles were written by experts and reviewed under a formal process.[14] It was founded on March 9, 2000, under the ownership of Bomis, a web portal company. Its main figures were Bomis CEO Jimmy Wales and Larry Sanger, editor-in-chief for Nupedia and later Wikipedia.[15][16] Nupedia was initially licensed under its own Nupedia Open Content License, but even before Wikipedia was founded, Nupedia switched to the GNU Free Documentation License at the urging of Richard Stallman.[17]
Nupedia
Other collaborative online encyclopedias were attempted before Wikipedia, but none were as successful.[13] Wikipedia began as a complementary project for Nupedia, a free online English-language encyclopedia project whose articles were written by experts and reviewed under a formal process.[14] It was founded on March 9, 2000, under the ownership of Bomis, a web portal company. Its main figures were Bomis CEO Jimmy Wales and Larry Sanger, editor-in-chief for Nupedia and later Wikipedia.[15][16] Nupedia was initially licensed under its own Nupedia Open Content License, but even before Wikipedia was founded, Nupedia switched to the GNU Free Documentation License at the urging of Richard Stallman.[17]


Neilson Cardigan
Crux and Crucible
$470
Portaiture Pendant
Mimico and Company
$85
Tanner Jacket
The Inventory
$279
Annabelle Blouse
Brandy Melville
$179
Dark Denim Skinny
Forrester
$329
Cufflinks
Chromeo
$215
Beach Hat
The Last Life
$99
Denim Button-up
Woodland x Woodland
$470


Round rooms are connected with hallways that are sometimes blocked by walls.
For example, here is a hallway blocked by three walls:
Here is an example of a hallway blocked by a wall of thickness 12 units:
Break the smallest possible number of wallstotal wall thickness to discover rooms and find the treasure.
To break all the walls of a hallwaya wall, click on the hallway.


Are you sure to pay now?
You have to top up. Please contact our staff.
Are you sure to empty the shopping cart?