staticshin / about / archives
A small guide on openresty with the goal of makig it easier for newcomers to get up to speed with it by explaining the most important concepts. Intended to be used as a complement to the official openresty manual. Feel free to take a look.
Easy user accounts management with couchdb Sun Aug 10 2014, 2376 words
Testing couchapps with couchdb Wed Sep 17 2014, 1666 words
Caching in couchdb Mon Oct 06 2014, 1474 words
Does updating a design document in couchdb cause rebuilding of views? Sat Oct 18 2014, 685 words
What does _security secure in couchdb? Tue Jan 13 2015, 697 words
Mocking your application's state with gen_fsm Mon Mar 16 2015, 2621 words
Explaining erlang processes Sat Jun 20 2015, 1821 words
Minimal nginx configuration for front end development Fri Mar 21 2014, 1828 words
Erlang is very addictive Wed Aug 07 2013, 440 words
Getting comfortable with erlang, cowboy? Wed Nov 06 2013, 830 words
Understanding punctuation in erlang Wed Nov 13 2013, 634 words
Wrinqle a library that combines gen_events and web sockets in cowboy Sat Nov 23 2013, 1044 words
Thoughts on indexed db Fri Jan 24 2014, 1097 words
Building my own node Mon Jun 24 2013, 382 words
Node js websocket blues Mon Oct 14 2013, 1227 words
Simplifying the build process with buildify Sun May 26 2013, 614 words
Tools of the trade Mon Apr 15 2013, 653 words
Local storage math Thu Apr 18 2013, 454 words
Local storage to the rescue. Sat Apr 06 2013, 587 words
Digestible units of text using cheerio Thu Jun 27 2013, 495 words
Node js websocket blues Mon Oct 14 2013, 1227 words
Jekyll makes blogging fun again Wed Mar 20 2013, 537 words
The problem with jekyll and other static site generators Mon Jun 24 2013, 568 words


All of the layout options below + Documentation + 12 Color Options
are already included with
your download. Choose a layout to preview.
We take care of the UX and front-end design so you can save time building your site
Assure polite his really and others figure though.
We provide you with three new amazing header presentations to enhance and enrich the look of your site.


Always
OnFailure
Never
[[自动扩容|自动扩容]]
是
否
[[镜像|镜像]]
more_vert
[[Actions|Tooltip "Actions", which appears when you hover over the menu icon on any resource card.]]
[[添加镜像|添加镜像]]
[[删除镜像|删除镜像]]
IfNotPresent
Always
Never
[[资源|资源]]
[[存储|存储]]
more_vert
[[Actions|Tooltip "Actions", which appears when you hover over the menu icon on any resource card.]]
[[添加存储|添加存储]]
delete


| Accessory | Accessory loop |
| Address | Address loop |
| Admin | Admin loop |
| Area | Class Area |
| AssociatedContent | AssociatedContent loop |
| Attribute | Attribute loop |
| AttributeAvailability | AttributeAvailability loop |
| AttributeCombination | Attribute Combination loop |
| Auth | |
| BaseSpecificModule | |
| Cart | |
| Category | Category loop, all params available : |
| CategoryPath | Category path loop, to get the path to a given category. |
| CategoryTree | Category tree loop, to get a category tree from a given category to a given depth. |
| Config | Config loop, to access configuration variables |
| Content | Content loop |
| Country | Country loop |
| Coupon | Created by JetBrains PhpStorm. |
| Currency | Currency loop |
| Customer | Customer loop |
| Delivery | Class Delivery |
| Document | The document loop |
| Feature | Feature loop |
| FeatureAvailability | FeatureAvailability loop |
| FeatureValue | FeatureValue loop |
| Feed | |
| Folder | Class Folder |
| FolderPath | Class FolderPath |
| FolderTree | Folder tree loop, to get a folder tree from a given folder to a given depth. |
| Image | The image loop |
| Lang | Language loop, to get a list of available languages |
| Message | Message loop, to access messageuration variables |
| Module | Module loop |
| Order | |
| OrderAddress | OrderAddress loop |
| OrderProduct | OrderProduct loop |
| OrderProductAttributeCombination | OrderProductOrderProductAttributeCombination loop |
| OrderStatus | OrderStatus loop |
| Payment | Class Payment |
| Product | Product loop |
| ProductSaleElements | Product Sale Elements loop |
| Profile | Profile loop |
| Resource | Resource loop |
| Tax | Tax loop |
| TaxRule | TaxRule loop |
| TaxRuleCountry | TaxRuleCountry loop |
| Template | Template loop |
| Title | Title loop |


I’m a film nerd, VFX geek, and under-cover Sci-Fi lover.
I’ll admit, VFX breakdown reels are my guilty pleasure. I prefer the hands-on approach to producing and enjoy working closely and openly with my team. I’m highly motivated, super passionate, and not afraid of stepping out of my comfort zone.
Most importantly: I get the job done.
Based in NYC. Available for freelance work now. Let's talk:


This shows the different Events DatePicker fires. You can use the onSelect event if you want to display the selected date elsewhere for example.
onSelect
Inputs:


Sodinokibi Ransomware Targeting Asia via the RIG Exploit Kit
by Lawrence AbramsA new malvertising campaign being used on low quality web games and blogs is redirecting Asian victims to the RIG exploit kit, which is then quietly installing the Sodinokibi Ransomware.
First spotted by exploit kit researcher mol69, this new malvertising campaign is targeting Internet Explorer users from Vietnam, Korea, Malaysia and possibly other Asian countries.
When browsing the web, the malvertising campaign will redirect users to a RIG exploit kit gateway that will attempt to exploit Flash vulnerabilities in the browser. If successful, a user will see Internet Explorer begin to crash and various alerts from the Windows Script Host as shown below.
This is because the exploit kit will execute a JScript command that downloads an obfuscated VBScript script.
This VBScript will then download and install the Sodinokibi Ransomware, also known as REvil, on the victim's computer. Once executed, the ransomware will begin to encrypt the victim's files.
As the exploit kit will install the ransomware without the user's knowledge, other than the suspicious Internet Explorer crash, most users will not know they are infected until the ransomware has finished.
They will then notice that they are unable to access their documents and that their desktop wallpaper has been changed to instructions telling the victim to open the ransom note.
Unfortunately, there is no free method of decrypting the Sodinokibi/REvil Ransomware at this time. Users are advised to restore from backups if at all possible rather than paying the ransom.
As always, to protect yourself from exploit kits, users should always have the latest Windows updates installed, their programs update, and to upgrade any web applications that require Internet Explorer as the RIG exploit kit only targets this outdated browser.


An Example Wendy's Visualization
Year of establishment
Establishment day of the week
Restaurant ratings
Timeline
Restaurant name
Establishment date
Address
Rating


This is a panel heading without a title
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This is a panel
This is a panel heading without a title
This is a panel
This is a panel heading without a title
This is a panel
This is a panel heading without a title
This is a panel
This is a panel heading without a title
This is a panel
This is a panel heading without a title
This is a panel


Home
View Car Prices
Post Your Info
Log Out
Post Your Sold Car Info
Manufacturer
Model
Year
Price ($)
Odometer (mi)
Transmission
Automatic
Manual
Other
Fuel
Gas
Dissel
Electric
Hybrid
Drive
4WD
FWD
RWD
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Submit


{% extends "two_factor/_base_focus.html" %} {% load i18n %} {% block content %}
{% blocktrans trimmed %}If you loose your smartphone, or your Authenticator app is not available, you can use a backup code along with your username and password to login until you recover your smartphone. Each backup code can be used only once. These codes should be kept in a secure, private place (print them or store them in your password manager) for when you need them. When they are used up, you can generate a new set of backup codes.{% endblocktrans %}


Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am
Dan Jordan
Status: At work
100
Hey Dude
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
How it's going ?
I need your help in something Lorem ipsum dolor sit amet, consectetur adipisicing elit.
Last seen at 2:00 am


All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
grecaptcha.execute
return type to Promise<string | null>
RecaptchaDirective.execute
return type to void
ngModel
on RecaptchaDirective.reset
grecaptcha
functions with zone.runOutsideAngular
grecaptcha.execute
and grecaptcha.render
type definitionsrxjs-compat
dependencyRECAPTCHA_RENDER
, RECAPTCHA_ONLOAD
, RECAPTCHA_URL
when using RecaptchaLoaderModule
without parametersRecaptchaLoaderModule.withParameters
RecaptchaLoaderModule.withParameters
AOT build errorsRecaptchaDirectiveModule
. RecaptchaFormsModule
@angular/forms
is now an optional dependencyRecaptchaLoaderModule
RecaptchaType
, RecaptchaTheme
, RecaptchaSize
, RecaptchaBadge
enumsRecaptchaLoaderModule.withParameters
RecaptchaLoaderService
to RecaptchaService
RecaptchaDirective
now uses data-*
attributes. Example: data-theme
instead of theme
.RecaptchaModule
RecaptchaDirective
attributes were undefined or null on ngOnInit
rxjs-compat
dependency for Angular 6


Dr. Roland Kuhn of Typesafe Visits Gilt
On Friday afternoon Gilt’s tech team was honored to host Dr. Roland Kuhn of Typesafe, who stopped by our NYC office to have some lunch and to chat with a few of our engineers. Based in Sweden, Dr. Kuhn was passing through NYC on his way from Philadelphia, where the night before he appeared at the Philly Area Scala Enthusiasts meetup and led a live-coding session.
The leader of the Akka Team, and a co-instructor (with Martin Odersky and Eric Meijer) of Coursera’s “Principles of Reactive Programming” course, Dr. Kuhn is also a co-author of the Reactive Manifesto. One of the Akka team’s most exciting recent projects is Reactive Streams, “an initiative to provide a standard for asynchronous stream processing with non-blocking back pressure on the JVM.” Here at Gilt we handle live feeds of all kinds, notes Gilt Senior Software Engineer Giancarlo Silvestrin. “To have a standard way to handle them asynchronously with automatic back pressure is something I’m really interested in,” he says.
If you’d like to learn more about Reactive Streams, don’t miss Dr. Kuhn’s May 7 webinar (9-10 AM PST). Also check out Akka Streams, Typesafe’s new, open-source Akka implementation of the Reactive Streams draft specification.
Thanks to Dr. Kuhn for spending Friday afternoon with us!


Taste
Have A Good Taste With US !
Delicious Salades For you Healthy Life
We Made fresh and helthy salades with defferent recepies
Have A Good Taste With US !
Delicious Salades For you Healthy Life
We Made fresh and helthy salades with defferent recepies


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Dietary
This baked cannelloni recipe is comfort food heaven. You can prepare it in advance, then pop it into the oven when you’re ready to eat.
Preheat the oven to 180C/365F/Gas 4.
Place the tomatoes into a bowl and drizzle with the olive oil. Add the thyme and season well with salt and freshly ground black pepper.
Place the ricotta, goats' cheese and parmesan into a clean bowl and mix well.
Add the spinach and garlic and season well with salt and freshly ground black pepper.
Lay the pasta sheets onto a clean work surface. Place a line of the cheese and spinach mixture along the longer edge of each pasta sheet, then roll up like a cigar.
Drizzle the cannelloni rolls with a little of the oil that the tomatoes have been sitting in, then pour the remaining oil into the bottom of an ovenproof dish that will hold all 12 cannelloni.
Place the cannelloni tubes into the dish and place the tomatoes evenly over the top.
Transfer to the oven to bake for 15 minutes, or until cooked through.
To serve, place three cannelloni onto each of four plates. Sprinkle with parmesan shavings and place a spoonful of dressed mixed green salad leaves alongside.


An insanely easy interface to the Flickr photo-sharing service. By Scott Raymond.
BASIC USAGE:
require 'flickr'
flickr = Flickr.new('some_flickr_api_key') # create a flickr client (get an API key from http://api.flickr.com/services/api/)
user =<EMAIL_ADDRESS># lookup a user
user.name # get the user's name
user.location # and location
user.photos # grab their collection of Photo objects...
user.groups # ...the groups they're in...
user.contacts # ...their contacts...
user.favorites # ...favorite photos...
user.photosets # ...their photo sets...
user.tags # ...and their tags
recentphotos = flickr.photos # get the 100 most recent public photos
photo = recentphotos.first # or very most recent one
photo.url # see its URL,
photo.title # title,
photo.description # and description,
photo.owner # and its owner.
File.open(photo.filename, 'w') do |file|
file.puts p.file # save the photo to a local file
end
flickr.photos.each do |p| # get the last 100 public photos...
File.open(p.filename, 'w') do |f|
f.puts p.file('Square') # ...and save a local copy of their square thumbnail
end
end
Required files
cgi
net/http
xmlsimple
digest/md5


Static Methods#
Summary#
staticmethod |
class parent |
truncated documentation |
|---|---|---|
NDArray |
Overwrites this method. |
|
OnnxOperator |
Enables expression cls[opset]. It returns the appropriate class cls_opset. Parameter op_version should be … |
|
|
OnnxOperatorFunction |
Enables expression cls[opset]. It returns the appropriate class cls_opset. Parameter op_version should be … |
|
XGBClassifierConverter |
|
XGBConverter |
||
|
XGBRegressorConverter |
|
GPT2TokenizerTransformer |
||
SentencePieceTokenizerTransformer |
||
|
XGBClassifierConverter |
|
XGBConverter |
||
|
XGBRegressorConverter |
|
OnnxInferenceNode |
Determines the loop inputs. It is any defined inputs by the subgraphs + any results used as a constant in … |
|
FusedMatMul |
||
FusedMatMul |
||
FusedMatMul |
||
FusedMatMul |
||
Gemm |
||
Gemm |
||
Gemm |
||
Gemm |
||
WrappedLightGbmBooster |
||
XGBClassifierConverter |
||
XGBConverter |
||
XGBRegressorConverter |
||
OnnxShapeInference |
||
OnnxInference |
||
ShapeObject |
||
|
ShapeObjectFct |
|
OnnxBackendTest |
||
NumpyCode |
||
OnnxOperator |
||
|
OnnxOperatorFunction |
|
OnnxOperator |
||
|
OnnxOperatorFunction |
|
OnnxOperator |
||
|
OnnxOperatorFunction |
|
OnnxOperator |
||
|
OnnxOperatorFunction |
|
OnnxOperator |
||
|
OnnxOperatorFunction |
|
Normalizer |
||
Normalizer |
||
BiGraph |
Implements graph type ‘basic’ for function |
|
BiGraph |
Implements graph type ‘simplified’ for function |
|
|
NDArraySameType |
Nicknames such as floats, int, ints, all can be used to describe multiple inputs for a signature. … |
|
NDArraySameTypeSameShape |
Nicknames such as floats, int, ints, all can be used to describe multiple inputs for a signature. … |
|
NDArrayType |
Nicknames such as floats, int, ints, all can be used to describe multiple inputs for a signature. … |
|
NDArrayTypeSameShape |
Nicknames such as floats, int, ints, all can be used to describe multiple inputs for a signature. … |
_NDArrayAlias |
Nicknames such as floats, int, ints, all can be used to describe multiple inputs for a signature. … |
|
OnnxBackendTest |
||
|
XGBClassifierConverter |
|
XGBConverter |
||
|
XGBRegressorConverter |
|
DimensionObject |
Returns obj if obj is |
|
OnnxBackendTest |
||
OnnxSubEstimator |
Converts a model into ONNX and inserts it into an ONNX graph. |
|
OnnxSubEstimator |
Converts a scikit-learn model into ONNX and inserts it into an ONNX graph. The library relies on … |
|
OnnxOperatorFunction |
Converts an attribute into a value using python structures. |
|
ShapeResult |
Broadcasts dimensions for an element wise operator. |
|
CachedEinsum |
Creates an instance of CachedEinsum. |
|
|
ZipMapDictionary |
|
AutoAction |
Caches the result of a function. |
|
|
XGBClassifierConverter |
common to regresssor and classifier |
XGBConverter |
common to regresssor and classifier |
|
|
XGBRegressorConverter |
common to regresssor and classifier |
XGBClassifierConverter |
convert method |
|
XGBRegressorConverter |
converter method |
|
OnnxInferenceBackend |
Instantiates an instance of class @see cl OnnxInference. This method should be overwritten to change the runtime … |
|
OnnxInferenceBackendMicro |
||
OnnxInferenceBackendOrt |
||
OnnxInferenceBackendPyC |
||
OnnxInferenceBackendPyEval |
||
OnnxInferenceBackendShape |
||
ShapeObject |
Computes einsum shapes. Not the most efficient one as it creates variables of the given shapes. |
|
|
ShapeObjectFct |
Computes einsum shapes. Not the most efficient one as it creates variables of the given shapes. |
OnnxTransformer |
Creates multiple OnnxTransformer, one for each requested intermediate node. onnx_bytes : bytes … |
|
|
XGBClassifierConverter |
fills tree attributes |
XGBConverter |
fills tree attributes |
|
|
XGBRegressorConverter |
fills tree attributes |
Variable |
Creates a Variable from a protobuf object. |
|
Variable |
Converts var from sklearn-onnx into this class. |
|
ShapeObject |
Computes Gather shapes. |
|
|
ShapeObjectFct |
Computes Gather shapes. |
|
XGBClassifierConverter |
Retrieves parameters of a model. |
XGBConverter |
Retrieves parameters of a model. |
|
|
XGBRegressorConverter |
Retrieves parameters of a model. |
MLActionCst |
Guesses a type given a value. |
|
|
MLActionVar |
Guesses a type given a value. |
OnnxInferenceBackend |
Returns whether the model is compatible with the backend. |
|
|
OnnxInferenceBackendMicro |
Returns whether the model is compatible with the backend. |
|
OnnxInferenceBackendOrt |
Returns whether the model is compatible with the backend. |
|
OnnxInferenceBackendPyC |
Returns whether the model is compatible with the backend. |
|
OnnxInferenceBackendPyEval |
Returns whether the model is compatible with the backend. |
|
OnnxInferenceBackendShape |
Returns whether the model is compatible with the backend. |
OnnxInferenceBackend |
Returns whether the opset for the model is supported by the backend. |
|
|
OnnxInferenceBackendMicro |
Returns whether the opset for the model is supported by the backend. |
|
OnnxInferenceBackendOrt |
Returns whether the opset for the model is supported by the backend. |
|
OnnxInferenceBackendPyC |
Returns whether the opset for the model is supported by the backend. |
|
OnnxInferenceBackendPyEval |
Returns whether the opset for the model is supported by the backend. |
|
OnnxInferenceBackendShape |
Returns whether the opset for the model is supported by the backend. |
Normalizer |
L1 normalization |
|
Normalizer |
L2 normalization |
|
Normalizer |
max normalization |
|
_GraphBuilder |
Converts a numbers into a string keeping the same alphabetical order. |
|
BiGraph |
Computes a distance between two ONNX graphs. They must not be too big otherwise this function might take for ever. … |
|
OnnxInferenceBackend |
Loads the model and creates @see cl OnnxInference. |
|
|
OnnxInferenceBackendMicro |
Loads the model and creates @see cl OnnxInference. |
|
OnnxInferenceBackendOrt |
Loads the model and creates @see cl OnnxInference. |
|
OnnxInferenceBackendPyC |
Loads the model and creates @see cl OnnxInference. |
|
OnnxInferenceBackendPyEval |
Loads the model and creates @see cl OnnxInference. |
|
OnnxInferenceBackendShape |
Loads the model and creates @see cl OnnxInference. |
CodeNodeVisitor |
Debugging purpose. |
|
CodeNodeVisitor |
Debugging purpose. |
|
OnnxWholeSession |
Flattens json returned by onnxruntime profiling. |
|
OnnxInferenceBackend |
Computes the prediction. |
|
|
OnnxInferenceBackendMicro |
Computes the prediction. |
|
OnnxInferenceBackendOrt |
Computes the prediction. |
|
OnnxInferenceBackendPyC |
Computes the prediction. |
OnnxInferenceBackendPyEval |
Computes the prediction. |
|
OnnxInferenceBackendShape |
Computes the prediction. |
|
OnnxInferenceBackend |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
|
|
OnnxInferenceBackendMicro |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
|
OnnxInferenceBackendOrt |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
|
OnnxInferenceBackendPyC |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
|
OnnxInferenceBackendPyEval |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
|
OnnxInferenceBackendShape |
This method is not implemented as it is much more efficient to run a whole model than every node independently. |
OnnxInferenceBackend |
Checks whether the backend is compiled with particular device support. |
|
|
OnnxInferenceBackendMicro |
Checks whether the backend is compiled with particular device support. |
|
OnnxInferenceBackendOrt |
Checks whether the backend is compiled with particular device support. |
|
OnnxInferenceBackendPyC |
Checks whether the backend is compiled with particular device support. |
|
OnnxInferenceBackendPyEval |
Checks whether the backend is compiled with particular device support. |
|
OnnxInferenceBackendShape |
Checks whether the backend is compiled with particular device support. |
XGBClassifierConverter |
||
XGBConverter |
validates the model |
|
XGBRegressorConverter |


_____
Impact of
Conflicts
on
Unemployment
Unemployment
Primary Enrollment
There are over
___
different types of conflicts in
____
Out of which there are -
Government Involved
Between Groups
One sided violence
[Africa /
______]


Psalms 25:10
All the paths of the LORD are mercy and truth unto such as keep his covenant and his testimonies.


NURESTConnection¶
-
class
NURESTConnection
(request, async, callback=None, callbacks={}, root_object=None)[source]¶ Connection that enable HTTP requests
Properties¶
NURESTConnection.
async
¶Get async
Returns: Returns True if the request is asynchronous
NURESTConnection.
callbacks
¶Get callbacks
Returns: It returns an array containing user callbacks
NURESTConnection.
has_timeouted
¶Get has timouted
Returns: Returns True if the request has timeout.
NURESTConnection.
ignore_request_idle
¶Get ignore request idle
Returns: It returns a boolean. By default ignore request idle is set to False.
NURESTConnection.
request
¶Get request. Read-only property
Returns: Returns the NURESTRequest object
NURESTConnection.
response
¶Get response
Returns: It returns the NURESTResponse object of the request
NURESTConnection.
timeout
¶Get timeout
Returns: It returns the timeout time in seconds. Default is 3000.
NURESTConnection.
transaction_id
¶Get transaction ID. Read-only property
Returns: Returns the transaction ID
NURESTConnection.
user_info
¶Get user info
Returns: It returns additionnal user information
Methods¶
NURESTConnection.
handle_response_for_connection
(should_post=False)[source]¶Check if the response succeed or not.
In case of error, this method also print messages and set an array of errors in the response object.
Returns: Returns True if the response has succeed, False otherwise
NURESTConnection.
has_callbacks
()[source]¶Check if the request has callbacks
Returns: Returns YES if there is a local or remote callbacks


Reflect on how confident you feel using the problem solving techniques and process:
Pseudocode
I understand this fully, but haven't had many chances to actually use it.
Trying something
If this means just testing code and deleting it to see if something new works, then I always do this. I'd code a solution I think would work, check it and play around with it a little bit while using console.log() to see if I get my desired result, then I'll pick pieces of it I like into my final code.
Rubber ducky method
I talk out loud a little bit when I try to parse a lot of information at once. This kind of replaces using pseudocode for me.
Reading error messages
I feel pretty confident in using the messages, especially when combined with console.log(). I'm usually able to figure it out if I can at least replicate the error elsewhere.
Console.logging
These two words have been ingrained into my head. I've probably used it hundreds of times already. This is my bread and butter.
Googling
I always Google if there are already in-built methods for the code I want to write. I get a lot of ideas from Stack Overflow as well, it really gets the ball rolling for me.
Asking your peers for help
I haven't had much chance to ask for help. I've been able to find all my answers independently(?) through already existing Google/Stack Overflow posts. I will be asking the facilitators and my peers a lot during bootcamp when that method is more accessible though. I ended up getting one suggestion from a friend outside of the course who doesn't do much programming, but that one suggestion allowed me to refactor a certain piece of code from ~12 lines to a single line of code.
Asking coaches for help
Haven't had to ask them for help yet, I've been able to find all my answers pretty quickly. There's only been one massive roadblock for 2 of the katas on Repl.it, but I ended up getting through it anyway.
Improving your process with reflection
Doing the reflection straight after doing all the tasks in the sprint is much better. I can fully reflect since all those new concepts are still fresh in my mind. And I feel like I am able to add better reflection answers since the contents of the sprints are getting more and more interesting.


UIColor
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Override to set a primary tint color for the app.
Declaration
Swift
@objc open class var primaryTintColor: UIColor?
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Override to set a secondary tint color for the app.
Declaration
Swift
@objc open class var secondaryTintColor: UIColor?
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@objc open class var appBackgroundLight: UIColor
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@objc open class var appBackgroundDark: UIColor
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@objc open class var appCrosshatchLight: UIColor
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@objc open class var appCrosshatchDark: UIColor
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@objc open class var appTextLight: UIColor
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@objc open class var appTextDark: UIColor
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@objc open class var rsd_underlinedButtonTextLight: UIColor
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@objc open class var rsd_underlinedButtonTextDark: UIColor
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@objc open class var rsd_roundedButtonBackgroundDark: UIColor
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@objc open class var rsd_roundedButtonShadowDark: UIColor
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@objc open class var rsd_roundedButtonTextLight: UIColor
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Swift
@objc open class var rsd_roundedButtonBackgroundLight: UIColor
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@objc open class var rsd_roundedButtonShadowLight: UIColor
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@objc open class var rsd_roundedButtonTextDark: UIColor
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@objc open class var rsd_dialRing : UIColor
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@objc open class var rsd_headerTitleLabel: UIColor
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@objc open class var rsd_headerTextLabel: UIColor
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@objc open class var rsd_headerDetailLabel: UIColor
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@objc open class var rsd_footnoteLabel: UIColor
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@objc open class var rsd_progressBar: UIColor
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@objc open class var rsd_progressBarBackgroundLight: UIColor
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@objc open class var rsd_stepCountLabelLight: UIColor
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@objc open class var rsd_stepCountLabelDark: UIColor
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@objc open class var rsd_choiceCellBackground: UIColor
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@objc open class var rsd_choiceCellBackgroundHighlighted: UIColor
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@objc open class var rsd_choiceCellLabel: UIColor
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@objc open class var rsd_choiceCellLabelHighlighted: UIColor
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@objc open class var rsd_textFieldCellText: UIColor
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@objc open class var rsd_textFieldCellBorder: UIColor
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@objc open class var rsd_textFieldCellLabel: UIColor
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@objc open class var appWhiteTwo: UIColor
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@objc open class var appWhiteThree: UIColor
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@objc open class var appDarkGrayText: UIColor
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@objc open class var appLightGrayText: UIColor
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@objc open class var appButtonTintBlue: UIColor
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@objc open class var appTintGreen: UIColor
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@objc open class var appSoftGreen: UIColor


Abstract: The One-Shot Similarity measure has recently been introduced as a
means of boosting the performance of face recognition systems. Given two vectors,
their One-Shot Similarity score reflects the likelihood of each vector belonging
to the same class as the other vector and not in a class defined by a fixed set
of "negative" examples. An appealing aspect of this approach is that it does not
require class labeled training data. In this paper we explore how the One-Shot Similarity
may nevertheless benefit from the availability of such labels. We make the following
contributions: (a) we present a system utilizing subject and pose information to
improve facial image pair-matching performance using multiple One-Shot scores; (b)
we show how separating pose and identity may lead to better face recognition rates
in unconstrained, "wild" facial images; (c) we explore how far we can get using
a single descriptor with different similarity tests as opposed to the popular multiple
descriptor approaches; and (d) we demonstrate the benefit of learned metrics for
improved One-Shot performance. We test the performance of our system on the challenging
Labeled Faces in the Wild unrestricted benchmark and present results that exceed
by a large margin results reported on the restricted benchmark.
Reference:
Yaniv Taigman,
Lior Wolf, and Tal Hassner, "Multiple One-Shots for
Utilizing Class Label Information," The British Machine Vision
Conference (BMVC), Sept. 2009.
Click here for the
PDF
Click here for the BibTex
Click here for our aligned version of the LFW image set (New!)
Related publications:
The One-Shot Similarity Kernal
Descriptor Based Methods in the Wild
Decoupling pose and identity with multiple One-Shot
Similarity (OSS) scores: Each group contains two images and 10 sample
multiple OSS scores. Identity based multiple OSS scores are plotted with circle
markers and pose based are with squares. As can be seen the value of each type of
OSS score is a good indication of the type of similarity between the images of the
pair. (a) Same person, same pose. (b) Different persons and pose. (c) Same person,
different pose. (d) Different persons, same pose. (e) Same person and pose, however,
a mode of variability not modeled in the system is present.
Results on the LFW benchmark: ROC curves
averaged over 10 folds of View 2 of the LFW data set. Each point on the curve represents
the average over the 10 folds of (false positive rate, true positive rate) for a
fixed threshold. The proposed method (single and multiple descriptors) is compared
to the best algorithms as reported on the
LFW results page. These algorithms include the combined Nowak+MERL [14], the
Nowak method [20], the hybrid method of [27] and as well using our alignment technique
(Section 4.1), the V1-like/MKL methodof [24] and the recent LMDL/MkNN methods of
[11]. (u) indicates ROC curve is for the unrestricted setting.


Astronomers from the Harvard-Smithsonian Center for Astrophysics posit that a young suggests our Sun was a “feisty” toddler.
Astronomers have long been fascinated by the period, 4.5 billion years ago, that our solar system formed. Unfortunately, time travel has yet to be invented. However, astronomers can learn a lot about the birth of our Sun and its planets by examining young stars in our galaxy. This study reveals that our Sun was both active and feisty as a toddler, developing it fits and stars while belching out bursts of X-rays.
According to Nancy Brickhouse of the Harvard-Smithsonian Center for Astrophysics, TW Hydrae offers a plethora of information about what exactly happened to our Sun when it was younger.
Brickhouse and her fellow astronomers came to this conclusion by examining the young star TW Hydrae, situated approximately 190 light-years from Earth in the southern constellation Hydra the Water Snake. According to the astronomers, TW Hydrae is a type K star weighing approximately 80 percent as much as our Sun. The young star is still amassing gas from a surrounding disk of material.
TW Hydrae develops by “eating” gas from the disk. However, the young star isn’t able to “eat” from it directly because the disk doesn’t extend all the way to the star’s surface. Instead, infalling gas is sent along magnetic field lines to the star’s poles.
CfA member Andrea Dupree said that the astronomers are able to observe the accretion process because they are looking directly down on one of TW Hydrae’s poles.
Infalling material hits the star, producing a shock wave and heating the amassing gas to more than 5 million degrees Fahrenheit. As the gas moves inward, it cools and its glow shifts from high-energy X-rays to optical wavelengths of light.
The astronomers combined data from NASA’s Chandra X-ray Observatory and several ground-based optical telescopes, which allowed them to study the entire accretion process for the first time.
They discovered that accretion was “clumpy” and “episodic” in creating a star. In fact, the astronomers found that the amount of material smashing into the star differed by a factor of five over the course of several days.
Some of the infalling material is blown away by a stellar wind, while some gets channeled into large loops and stellar prominences.
Though astronomers have known for some time that young stars are a lot more magnetically active than our Sun, now they are actually able to see the interaction between the star’s magnetic fields and the protoplanetary disk.
Have something to say? Let us know in the comments section or send an email to the author. You can share ideas for stories by contacting us here.


Showing first of all that the randomisation can be done.
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This is where we had a range of vendor logos to choose from, but only had room to display a certain subset of them depending on screen size, and of course we didn't want them to always be the same ones - someone viewing on a mobile might think we supply kit from 3 different vendors and that's it!
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You will notice that the above row still displays random numbers between the 2 numbers you have chosen, (if you're in the full view on CodePen, it defaults to 1 and 25) but it only displays a subset of them, using overflow: hidden to hide the rest.


mfw framwork
Button
see how to use Button
Pop Up
see how to use Pop up
Tab
see how to use Tab
Js Template
see how to use a template
Header
see how to use header
Cell
see how to use cell
pull refresh
see how to use pullrefresh
drag
see how to use drag


Blue bottle crucifix vinyl post-ironic four dollar toast vegan taxidermy. Gastropub indxgo juice poutine.
seperator


we were curious to know how web functions, so we 2 best childhood buddies started our research on web technology & started studying how web functions. During research for a couple of weeks we figured out a way to build a website
While doodling in a hot dry summer vacation, a close relative of ours was looking for Professional website for his business. So we approached him, it was fun again creating another website. After publishing the website he was very happy by our performance and gifted us a small token of appreciation. He suggested us to some of his partners and friends.
A few people approached us, so we helped them out as well. After helping out our families and friends we then thought of building professional websites for business purpose. So we started providing full web related services to local firms at an affordable amount.
We are currently pursuing websites for local firms to reach their goals. We provide them with complete web security and full service. We design dynamic and fully customisable websites which helps our clients to express their work through the website
SHRI SWAMI SAMARTHA


Tennis: Thiem reaches ATP Finals semis as Djokovic and Federer face shootout
LONDON: Dominic Thiem produced a scintillating display of attacking tennis to beat Novak Djokovic and qualify for the last four at the ATP Finals on Tuesday (Nov 12), leaving the Serbian facing a shootout against Roger Federer.
In the standout match so far at London's O2 Arena, the Austrian fifth seed took the fight to the world number two, recovering from losing the first set to triumph 6-7 (5/7), 6-3, 7-6 (7/5)
Earlier, Federer put himself back into the mix at the end-of-season event with a 7-6 (7/2), 6-3 win against Italian debutant Matteo Berrettini in their round-robin clash.
Federer and Djokovic will face off on Thursday in a repeat of the Wimbledon final to determine who else will progress from Group Bjorn Borg.
Thiem was forced to play high-stakes tennis against the 16-time Grand Slam winner, taking the breath away with some of his inside-out forehands and single-handed backhands
Forced to play on the limit, he hit 50 winners compared to Djokovic's tally of 27 but also racked up 44 unforced errors.
In a captivating first set lasting more than an hour, Djokovic, last year's beaten finalist, drew first blood, breaking in the fourth game, but Thiem responded immediately, breaking back with a rasping backhand down the line.
Neither player managed to force another break and the set went to a tie-break, which Djokovic, a five-time ATP Finals champion, edged 7-5.
Undaunted, Thiem broke his opponent at the first opportunity in the second set and, with Djokovic's error count climbing, went on to level the match.
Thiem then broke in the first game of the deciding set and stayed strong to hold under severe pressure.
The Austrian was again under pressure on his own serve in the sixth game and Djokovic broke back when Thiem went long with a backhand.
Thiem successfully challenged at 30-30 in the 10th game after his forehand was ruled out, preventing a match point for Djokovic and he toughed it out to level at 5-5.
He then broke Djokovic to love to earn a chance to serve for the match but stumbled and the decider went to a tie-break.
Thiem slipped to 4-1 down but recovered to win it on his second match point when Djokovic dumped a forehand into the net.
"I practised all my life, all my childhood for this," said Thiem. "It was incredible."
"Novak was in great shape and I had to do something special," he added.
"I stayed in the match the whole time, came from a set down, I remained offensive, stuck to my game and I'm in the semi-final."
FEDERER STAYS ALIVE
Third seed Federer had put himself under the cosh by losing his opening round-robin match to Thiem.
The six-time champion was not at his fluent best on Tuesday but ultimately had too much for his Italian opponent.
The Swiss upped his game to take the first set tie-break comfortably and broke immediately at the start of the second set to leave the big-serving Italian with too much to do.
Federer, 38, will face Djokovic on Thursday in a repeat of July's marathon Wimbledon final, during which he squandered two championship points on his own serve.
The Swiss was asked after his win against Berrettini whether that defeat had left emotional or mental scars.
"We'll find out, but I think it's all flushed away from my side," said Federer, who added that it had taken him two weeks at most to get over the loss.
"A lot of water has gone under the bridge since then.
"We have played a lot of matches since, and I think we both look back at a great match. I think we both can take away some confidence from the match."
Djokovic is hunting a sixth ATP Finals title to pull level with Federer's record and is also seeking to pip Rafael Nadal to the year-end number one ranking.
On Monday, top seed Nadal lost his opener in Group Andre Agassi to defending champion Alexander Zverev while Stefanos Tsitsipas beat Daniil Medvedev.


--- title: "Is Resident Advisor biased towards ambient music?" author: "Joshua Feldman" date: '2019-07-27T17:00:00-00:00' tags: - rstats - resident advisor categories: R ---
Resident Advisor (or 'RA' for its loyal readership of DJs and crate diggers) is an online magazine dedicated to electronic music. Since its launch in 2001, RA has reviewed thousands of LPs/EPs, which have ranged in style from house and techno to dubstep and drum and bass.
After many years spent reading RA reviews, I started to suspect that the magazine has a bias towards ambient music - respective albums seemed to be receiving consistently good ratings and a disproportionate number of 'RA Recommends' awards.
Geek that I am, I decided to test this theory formally. Back in May, I scraped 15k+ reviews from the RA website using their parent URL, https://www.residentadvisor.net/reviews. I don't talk about the data cleaning in this blog post (you can see the data_preparation.R
file on GitHub if you're really interested), but suffice it to say that I prepared a structured dataset with seven fields:
title
: the name of the artist and the LP/EPauthor
: the name of the journalist who wrote the reviewdate
: the date the review was publishedgenre
: the genre(s) associated with the albumrating
: a numerical score from 0.5 to 5.0review
: the original text of the reviewra_recommends
: a binary indicator for whether the album received an 'RA Recommends' accoladeUsing this information, I was able to test my two hypotheses:
Most of the data preparation occurred when I was ingesting the data in the first place. However, to aid the analysis, I will use one-hot encoding to add a series of dummy variables for the most common genres. For example, I'll add an ambient
variable with two possible values: 1
if an album is tagged as ambient, and 0
if it is not.
library(tidyverse)
library(data.table)
df <- read_csv("https://github.com/joshua-feldman/resident-advisor/raw/master/resident-advisor.csv")
df <- df %>%
mutate(ambient = as.factor(ifelse(genre == "ambient" | genre %like% "\\bambient\\b", 1, 0))) %>%
mutate(deephouse = as.factor(ifelse(genre == "deephouse" | genre %like% "\\bdeephouse\\b", 1, 0))) %>%
mutate(disco = as.factor(ifelse(genre == "disco" | genre %like% "\\bdisco\\b", 1, 0))) %>%
mutate(dubstep = as.factor(ifelse(genre == "dubstep" | genre %like% "\\bdubstep\\b", 1, 0))) %>%
mutate(electro = as.factor(ifelse(genre == "electro" | genre %like% "\\belectro\\b", 1, 0))) %>%
mutate(experimental = as.factor(ifelse(genre == "experimental" | genre %like% "\\bexperimental\\b", 1, 0))) %>%
mutate(house = as.factor(ifelse(genre == "house" | genre %like% "\\bhouse\\b", 1, 0))) %>%
mutate(minimal = as.factor(ifelse(genre == "minimal" | genre %like% "\\bminimal\\b", 1, 0))) %>%
mutate(techhouse = as.factor(ifelse(genre == "techhouse" | genre %like% "\\btechhouse\\b", 1, 0))) %>%
mutate(techno = as.factor(ifelse(genre == "techno" | genre %like% "\\btechno\\b", 1, 0)))
Now that the data is prepared, we are free to compare the distribution of ratings for ambient vs non-ambient music. We have a few options here - a boxplot or a violin plot would both be suitable - but I'll go with a density plot to show a smoothed version of each distribution along the x-axis.
df %>%
filter(!is.na(ambient)) %>%
ggplot(aes(rating, fill = ambient)) +
geom_density(alpha = 0.5) +
labs(title = "Density plot of Resident Advisor ratings for ambient vs non-ambient music",
subtitle = "Based on 15k+ reviews from Feb 2001 to May 2019",
x = NULL,
y = NULL,
caption = "Source: Resident Advisor") +
guides(fill = FALSE) +
geom_vline(xintercept = mean(df$rating[df$ambient==1], na.rm = TRUE),
linetype = "dashed", col = "#00BFC4", size = 1) +
geom_vline(xintercept = mean(df$rating[df$ambient==0], na.rm = TRUE),
linetype = "dashed", col = "#F8766D", size = 1) +
ggplot2::annotate("text", label = "Ambient", x = 4.5, y = 1,
family = "Raleway", col = "#00BFC4", fontface = "bold", size = 5) +
ggplot2::annotate("text", label = "Not ambient", x = 4.5, y = 2,
family = "Raleway", col = "#F8766D", fontface = "bold", size = 5) +
ggplot2::annotate("text", label = "The dashed lines represent the\nmean of each distribution",
x = 2.9, y = 2.35, family = "Raleway", size = 4)
The density plot shows a clear difference in the distributions of ambient/non-ambient ratings. While the non-ambient distribution has well-defined peaks at .5 intervals (particularly at 3.5 and 4.0), the ambient distribution is flatter with a greater density of ratings between 3.5 and 4.0. Although the graph shows a difference between the mean of the two distributions, we don't yet know whether this difference is statistically significant.
Next, we will plot the percentage probability that each of the 10 most commonly reviewed genres - from ambient to techno - receives an 'RA Recommends' award.
df %>%
select(ra_recommends, ambient:techno) %>%
gather(genre, genre_flag, ambient:techno) %>%
filter(genre_flag == 1) %>%
group_by(genre) %>%
summarise(ra_recommends = mean(as.numeric(ra_recommends), na.rm = TRUE)) %>%
mutate(genre = reorder(genre, ra_recommends)) %>%
mutate(label = paste(round(ra_recommends * 100, 2), "%", sep = "")) %>%
mutate(ambient_flag = ifelse(genre == "ambient", 1, 0)) %>%
ggplot(aes(genre, ra_recommends, label = label, fill = ambient_flag)) +
geom_col() +
geom_text(family = "Raleway", fontface = "bold", hjust = -0.1, size = 4) +
geom_hline(yintercept = mean(df$ra_recommends), linetype = "dashed") +
coord_flip() +
labs(title = "Probability of 'RA Recommends' award for 10 most common genres",
subtitle = "Based on 15k+ reviews from Feb 2001 to May 2019",
x = NULL,
y = NULL,
caption = "Source: Resident Advisor") +
scale_y_continuous(labels = scales::percent, limits = c(0, 0.06)) +
guides(fill = FALSE) +
ggplot2::annotate("text", x = 2, y = .0325, family = "Raleway", size = 4,
label = paste("Overall mean: ", round(mean(df$ra_recommends * 100), 2), "%", sep = ""))
## `summarise()` ungrouping output (override with `.groups` argument)
Here, the difference is a lot clearer: ambient albums have a greater chance of receiving an 'RA Recommends' award than any other major genre, with 5.52% of them receiving the accolade. It is worth noting that experimental - comparable to ambient in the abstraction of its musical form - is also more commended than average.
To test the first hypothesis, we will run a simple linear regression that predicts rating
as a function of experimental
. Since the Y variable is continuous and the X variable is binary categorical, this is equivalent to a two-sample t-test.
linear_model <- lm(rating ~ ambient, data = df)
summary(linear_model)
##
## Call:
## lm(formula = rating ~ ambient, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.68236 -0.18236 0.01764 0.31764 1.31764
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.682357 0.004182 880.59 < 2e-16 ***
## ambient1 0.117883 0.017780 6.63 3.47e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4988 on 15058 degrees of freedom
## (635 observations deleted due to missingness)
## Multiple R-squared: 0.002911, Adjusted R-squared: 0.002844
## F-statistic: 43.96 on 1 and 15058 DF, p-value: 3.472e-11
The model shows that experimental albums are rated, on average, 0.12 points higher than non-experimental albums. This effect may be small, but it is significant at the 1% significance level, and we can therefore reject the null hypothesis that there is zero difference between the two groups.
To test the second hypothesis, we will run a binary logistic regression that predicts ra_recommends
as a function of experimental
.
logistic_model <- glm(ra_recommends ~ ambient, data = df, family = "binomial")
summary(logistic_model)
##
## Call:
## glm(formula = ra_recommends ~ ambient, family = "binomial", data = df)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.3371 -0.2180 -0.2180 -0.2180 2.7393
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -3.72800 0.05537 -67.328 < 2e-16 ***
## ambient1 0.88841 0.16148 5.502 3.76e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 3546.8 on 15059 degrees of freedom
## Residual deviance: 3522.1 on 15058 degrees of freedom
## (635 observations deleted due to missingness)
## AIC: 3526.1
##
## Number of Fisher Scoring iterations: 6
Since the model is logistic, its coefficients are given on the log odds scale. To work out the odds that an experimental album is recommended as opposed to a non-ambient album, we simply exponentiate the beta coefficient.
exp(logistic_model$coefficients[2])
## ambient1
## 2.431267
This suggests that an ambient album is 143% more likely to be recommended than a non-ambient album.
Lo and behold, RA does in fact have a bias towards ambient music - ambient albums are rated 0.12 points higher than non-ambient albums (p < 0.01) and are 143% more likely to be recommended (p < 0.01). Of course, this might be because of a genuine discrepancy in quality between the ambient and non-ambient music in RA's review catalogue; perhaps it reflects an 'objective' difference (insofar as there is objectivity in music perception), rather than a subjective bias on the part of the reviewers.
An alternative theory is that ambient music - at the abstract, often esoteric end of the electronic music spectrum - invokes a kind of social desirability bias, whereby the reviewer, forever wishing to flaunt their unorthodox taste, bends naturally towards the positive end of ambivalence. This way, if the reader doesn't enjoy the album being reviewed, they are the ones left feeling unsophisticated, apparently unable to appreciate the avant-garde.
In any case, the Resident Advisor dataset is now publicly available for your own explorations and musings. Enjoy!


Create R functions that interact with OAuth2 Google APIs <https://developers.google.com/apis-explorer/> easily, with auto-refresh and Shiny compatibility.
| Version: | 0.7.0 |
| Depends: | R (≥ 3.3.0) |
| Imports: | assertthat (≥ 0.2.0), digest, httr (≥ 1.3.1), jsonlite (≥ 0.9.16), R6 (≥ 2.1.0), memoise (≥ 1.1.0), utils |
| Suggests: | bigQueryR, covr, devtools (≥ 1.12.0), formatR (≥ 1.4), googleAnalyticsR, httptest, knitr, miniUI (≥ 0.1.1), rmarkdown, roxygen2 (≥ 5.0.0), shiny (≥ 0.13.2), testthat |
| Published: | 2018-11-16 |
| Author: | Mark Edmondson [aut, cre], Jennifer Bryan [ctb], Johann deBoer [ctb], Neal Richardson [ctb], David Kulp [ctb], Joe Cheng [ctb] |
| Maintainer: | Mark Edmondson <m at sunholo.com> |
| BugReports: | https://github.com/MarkEdmondson1234/googleAuthR/issues |
| License: | MIT + file LICENSE |
| URL: | http://code.markedmondson.me/googleAuthR/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | googleAuthR results |
| Reference manual: | googleAuthR.pdf |
| Vignettes: |
Advanced Google API building techniques Building your own Google R library Google authentication types for R Google API Setup Troubleshooting authentication |
| Package source: | googleAuthR_0.7.0.tar.gz |
| Windows binaries: | r-devel: googleAuthR_0.7.0.zip, r-release: googleAuthR_0.7.0.zip, r-oldrel: googleAuthR_0.7.0.zip |
| OS X binaries: | r-release: googleAuthR_0.7.0.tgz, r-oldrel: googleAuthR_0.7.0.tgz |
| Old sources: | googleAuthR archive |
| Reverse imports: | bigQueryR, googleAnalyticsR, googleCloudStorageR, googleComputeEngineR, googleLanguageR, googlePrintr, searchConsoleR |
Please use the canonical form https://CRAN.R-project.org/package=googleAuthR to link to this page.


🍪 Cookies
{% trans "Last updated" %} May 01, 2021
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You can use JXTA™ technology to create peer-to-peer (P2P) applications based on Java technology. JXTA technology is a set of open protocols that enable any connected device on the network, ranging from cell phones and wireless PDAs to PCs and servers, to communicate and collaborate in a P2P manner. JXTA peers create a virtual network where any peer can interact with other peers and resources directly, even when some of the peers and resources are behind firewalls and network address translations (NATs) or on different network transports.
Project JXTA is fortunate to have a strong supportive community. Come join in the discussions and development efforts. There is such a wide range of activities to join in on that there is sure to be something of interest to you!
The new JXTA Board of Directors began their two year terms on July 1, 2008.
Please join in giving all these wonderful folks a HUGE +1!!!! We look forward to their innovative ideas and their incredible energy! (click for complete results).


<lcMatchingPair>
The <lcMatchingPair>
element was deprecated in DITA version 1.3. It was
replaced with the <lcMatchingPair2>
element. It was originally intended
to provide a table row with the pair of items that comprise a correct match in a matching
interaction and, optionally, feedback on the pair or correct and incorrect matches.
Category: Interactions domain content elements (DEPRECATED)


Visualizations of A* Search, Breadth-First Search, Depth-First Search.
Can you beat a player that can predict the future?
K-Means Clustering algorithm of points in 2D space.
Perceptron algorithm classfication of points in 2D space.


Become a Host
Home
Pepper Cookburn
Chicken Paris Tyrolls
Chicken Paris Tyrolls
Your reservation for
2 people
is confirmed for
2 April, 2018
Explore More from Pepper


How to set Hint as Title When Data Enter
How to Create button with image and text both using..
How Drow line in android.
How to add read, write, update and delete data into the firebase database.
How to Change backgroud animation of android activity...
how to set on backpress exit from app...
Alert dialog box is very important to notify pepole.
How to move next activity after 4 second..
How to change activity enter and exit animation with source code..
How to Create button shap.
maney way to authenticat user using firebase.
How to download custome font family and use in android studio with source code example..


Jenny
I can’t believe how much better I am with my plants now.
Add plants in order to keep
track of their hydration status
Get a list of all your plants
to get an overview on
how they are feeling!
Get notified whenever your
plants need watering
I can’t believe how much better I am with my plants now.
this app really helps me keep my plants well and happy!
this is exactly what I needed to keep my plants feeling loved.


Footnotify is an interactive web based football resource for the premier league, it contain live streaming, score updates, league news, league table, and team data all in one place. That too personalized for each user. But the main idea is to get all these useful things in one place, people usually need to go to different websites for all the stuff, for example, a person will use onefootball (an android based app) for live scores, footyroom (a website) for highlights and any other website for live streaming the matches. But with Footnotify we will get all that stuff in one place. That too with personalization that is the news, highlights and data will be shown according to the person’s chosen team, so that they only see what they want to see.


Thank you for subcribing for the offer/publisher/pager.
If you are registered user:
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Please consider the following other subscription options:


Webdext: Intelligent extraction result
Found
data region(s) on
Extraction time
:
milliseconds.
Memory usage
:
bytes.
«
Data region
of
0
»
rows,
columns.
Export Data
as CSV
as JSON
Save Extractor


---
layout: archive
title: Lean Prover Zulip Chat Archive
permalink: 113489newmembers/81703Onthesideoflogic.html
---
The archive URL format has changed. Please find this page at:
https://leanprover-community.github.io/archive/stream/113489-new-members/topic/On.20the.20side.20of.20logic.html


DARK CITY
A Film Review by James Berardinelli
RATING: ***1/2 OUT OF ****
United States, 1998 U.S. Release Date: 2/27/98 (wide) Running Length: 1:43 MPAA Classification: R (Violence, nudity, profanity) Theatrical Aspect Ratio: 2.35:1
Cast: Rufus Sewell, Kiefer Sutherland, Jennifer Connelly, Richard O'Brien, Ian Richardson, William Hurt Director: Alex Proyas Producers: Andrew Mason and Alex Proyas Screenplay: Alex Proyas and Lem Dobbs and David S. Goyer Cinematography: Dariusz Wolski Music: Trevor Jones U.S. Distributor: New Line Cinema
THE CROW will forever be remembered as the final performance of budding star Brandon Lee, who died as a result of a tragic behind-the- scenes accident. However, as intense as the hype associated with Lee's death was, it could not obscure the most impressive aspect of the 1994 feature: director Alex Proyas' startling, unforgettable vision. It's rare for any film maker, whether a veteran or a newcomer, to create the kind of compelling, endlessly-fascinating environment that Proyas brought to the screen in THE CROW. Now, with his follow-up movie, DARK CITY, the director incredibly manages to one-up himself.
No movie can ever have too much atmosphere, and DARK CITY exudes it from every frame of celluloid. Proyas' world isn't just a playground for his characters to romp in -- it's an ominous place where viewers can get lost. We don't just coolly observe the bizarre, ever-changing skyline; we plunge into the city's benighted depths, following the protagonist as he explores the secrets of this grim place where the sun never shines. DARK CITY has as stunning a visual texture as that of any movie that I've seen. Line up the other recent candidates, which include Tim Burton's BATMAN, Ridley Scott's BLADE RUNNER, Jean-Pierre Jeunet and Marc Caro's DELICATESSAN and THE CITY OF LOST CHILDREN, and Terry Gilliam's BRAZIL, and DARK CITY equals or bests them all. Visually, this film isn't just impressive, it's a tour de force.
 Proyas hasn't written this film for the passive viewer. To become involved in DARK CITY, thinking is mandatory. Unless you're puzzling out the answers alongside John Murdoch (Rufus Sewell), you're going to miss more than one revelation.  How often do we get features like this, that don't pander to the least common denominator?
Ironically, two months into 1998, my top three films to date (SLIDING DOORS, OPEN YOUR EYES, and DARK CITY) all question the nature of identity and reality. DARK CITY is much like OPEN YOUR EYES (which was shown at the 1998 Sundance Film Festival and will open theatrically later this year in North America) -- both are meditations on the importance of memory to an individual, and how everyone's personality is comprised of the sum total of his or her remembrances. In the way DARK CITY tinkers with the boundaries of what's real and what isn't, it recalls THE GAME. Some viewers may also be reminded of TOTAL RECALL, although Proyas' film plunges deep into issues that the Schwarzenegger vehicle used as icing for an action-laden cake.
DARK CITY opens by immersing the audience in the midst of a fractured, nightmarish narrative. The protagonist, who later learns that his name is John Murdoch, has amnesia. He begins his "new life" as a full-grown adult naked in a bath tub, uncertain of how he got there. His only company in the grungy hotel suite is the nude body of a dead prostitute. Did he kill her or not? He doesn't know. Suddenly, Murdoch receives a phone call from someone named Dr. Schreber (Kiefer Sutherland), who claims to have his best interests at heart. Schreber warns him to get out of the hotel immediately. Soon, without a clue about his identity, Murdoch is fleeing from corpse-like creatures with incredible mental powers. But it turns out that Murdoch is not defenseless against his enemies -- his mind, like theirs, can shape reality, although he doesn't understand how to harness his abilities. Soon, his quest to unearth his past links him up with Emma (Jennifer Connelly), a woman who is supposedly his wife, and Police Inspector Bumstead (William Hurt), who believes Murdoch to be innocent of the prostitute's murder. But Murdoch's small group of allies offer little help when it comes to dealing with his powerful, ghoulish adversaries, the amoral Mr. Book (Ian Richardson) and Mr. Hand (Richard O'Brien).
Proyas' inspiration for his Dark City appears to be New York during the first half of this century, but, using a style that is part science fiction, part noir thriller, and part gothic horror, he has embellished it to create a surreal place unlike no other. Film lovers will find that DARK CITY is overflowing with references to classic pictures -- everything from the silent DRACULA adaptation, NOSFERATU, to Hitchcock's masterful VERTIGO. Throw in a little TWILIGHT ZONE and STAR TREK for good measure. Even if you get bored with the storyline, which is extremely unlikely, there are still plenty of these little details to absorb your attention.
Proyas' excellent vision extends to his casting choices. Rufus Sewell (currently appearing in DANGEROUS BEAUTY) makes a perfect John Murdoch, since he is equally good as a confused, desperate refugee and an avenging angel.  Jennifer Connelly, who looks the part of a classy, black-and-white screen siren, plays her femme fatale role to a "T". And William Hurt is sufficiently gruff in the kind of part that Humphrey Bogart would have been at home in.
If there's a flaw with DARK CITY (and it's a small one, to be sure), it's that the film takes a little too long forging a link between the audience and Murdoch. For the first thirty minutes, we're left floating, watching the confounding narrative unfold, marveling over the strange occurrences, and waiting for film to really grab us. Once that happens, it's difficult not to become completely engrossed. So, is the lengthy setup necessary? Almost certainly, and, as I said, any slow spots are only a tiny blemish on the face of a film that offers a gratifyingly original and stunning science fiction experience.
Copyright 1998 James Berardinelli
- James Berardinelli e-mail<EMAIL_ADDRESS>Now with more than 1300 reviews... The ReelViews web site: http://movie-reviews.colossus.net/
"No art passes our conscience in the way film does, and goes directly to our feelings, deep down into the dark rooms of our souls"
- Ingmar Bergman
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
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Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


10,5,3,7,5,10,3,6,5,10
New Users
113
5,8,7,10,9,10,8,6,4,6,8,7,6,8
Monthly Sales
80%
2,3,4,5,4,3,2,3,4,5,6,5,4,3,4,5,6,5,4,4,5
Impressions
532
2,5,3,7,5,10,3,6,5,7
Downloads
113
Inline Charts
These are the basic sparkline charts
| Name | Graph |
|---|---|
| Line graph | 8,4,0,0,0,0,1,4,4,10,10,10,10,0,0,0,4,6,5,9,10 |
| Bar graph | 10,8,9,3,5,8,5 |
| Pie charts | 1,1,21,520,50,80 |
| Bullet charts | 10,12,12,9,7 |
| Stacked | 0:2,2:4,4:2,4:1 |
| Composite | 8,4,0,0,0,0,1,4,4,10,10,10,10,0,0,0,4,6,5,9,10 |
Inline Charts
These are the advanced sparkline charts
| Name | Graph |
|---|---|
| Composite bar | 4,6,7,7,4,3,2,1,4 |
| Discrete | 4,6,7,7,4,3,2,1,4,4,5,6,7,6,6,2,4,5 |
| Discrete with threshold | 4,6,7,7,4,3,2,1,4 |
| Customize size and colours | 10,8,9,3,5,8,5,7 |
| Tristate charts | 1,1,0,1,-1,-1,1,-1,0,0,1,1 |
| Box Plot | 4,27,34,52,54,59,61,68,78,82,85,87,91,93,100 |


¶ Upwardable Objects |
|
|
Upwardable objects are one of the three key components of the upward library, along with upwardable values and upwardable functions. An upwardable object is an enhanced object which can detect and and act on accesses to its properties. |
|
|
An upwardable object is created by calling |
|
|
Convenience. |
import {accessNotifier} from './Acc';
import {Observer} from './Obs';
import makeUpwardable from './Upw';
import {isUpwardable} from './Upw';
var {create, keys, getNotifier, observe, unobserve, defineProperty} = Object;
|
|
Lists of all upwardables, and objects which have been upwardified. |
var set = new WeakSet();
var upwardifieds = new WeakMap();
|
¶ isCheck if an object is upwardified.
Exported as |
function is(u) { return u && typeof u === 'object' && set.has(u); }
|
¶ getGet the upwardable version of an object. |
function get(o) { return o && typeof o === 'object' && upwardifieds.get(o); }
|
¶ makeConstructor for upwardable object.
Default export from this module, often imported as |
function make(o) {
if (is(o)) return o;
var u = get(o);
if (!u) {
u = _make(o);
set.add(u);
upwardifieds.set(o, u);
}
return u;
}
|
¶ _makeLow-level constructor for upwardable object. |
function _make(o) {
var shadow = {};
var observers = {};
var actions = {add, update, delete: _delete};
|
|
Delete a property. Unobserve it, delete shadow and proxy entries. |
function _delete(name) {
observers[name].unobserve();
delete observers[name];
delete u [name];
delete shadow [name];
}
|
|
Update a property by reobserving. |
function update(name) {
observers[name].reobserve(shadow[name]);
}
|
|
Add a property. Set up getter and setter, Observe. Populate shadow. |
function add(name) {
function set(v) {
var oldValue = shadow[name];
if (oldValue === v) return;
o[name] = v;
notifier.notify({type: 'update', object: u, name, oldValue});
shadow[name] = oldValue.change(v);
}
|
|
When property on upwardable object is accessed, report it and return shadow value. |
function get() {
accessNotifier.notify({type: 'access', object: u, name});
return shadow[name];
}
function observe(changes) {
|
|
}
shadow[name] = makeUpwardable(o[name]);
observers[name] = Observer(shadow[name], observe, ['upward']).observe();
defineProperty(u, name, {set: set, get: get, enumerable: true});
}
|
|
Observer to handle new or deleted properties on the object. Pass through to underlying object, which will cause the right things to happen. |
function objectObserver(changes) {
changes.forEach(({type, name}) => {
switch (type) {
case 'add': o[name] = u[name]; break;
case 'delete': delete o[name]; break;
}
});
}
|
|
Observer to handle new, deleted or updated properties on the target. |
function targetObserver(changes) {
changes.forEach(({type, name}) => actions[type](name));
|
|
notifier.notify(change); // TODO: figure out what this line was suppsoed to do |
}
var u = create({}); // null?
var notifier = getNotifier(u);
keys(o).forEach(add);
observe(o, targetObserver);
observe(u, objectObserver);
return u;
}
|
|
Exports. |
export default make;
var isUpwardableObject = is;
export {
isUpwardableObject
};
|


---
layout: post
title: Tango Fibre
description: animatic storyboard for Lalux
date: '2019-12-16 10:10:12 +0100'
categories:
- Storyboards
- Animation
- Advertising
---
Tango Fibre, another storyboard version, directed by Nico Galoux, produced by HUGGGY.


--- layout: post title: Apologies for the silence… Out of work and conferences date: '2008-11-09T00:36:00.001Z' tags: modified_time: '2008-11-09T00:36:41.509Z' blogger_id: tag:blogger.com,1999:blog-4015568221071268916.post-4173079121138161043 comments: true blogger_orig_url: http://serialseb.blogspot.com/2008/11/apologies-for-silence-out-of-work-and.html ---
Sorry to all people reading (and not taken over by tweeter fever). Between PDC and KaizenConf, I took a couple of days off and am now getting ready to meet even more great people in TechEd.
I’m doing the initial edit for some of the videos I took at KaizenConf / PDC (mainly recording of sessions, the interviews will take a bit longer). I hope to manage to get a few more at TechEd. Bittorrent of the raw material to follow.
Oh, and I still don’t have a contract, so any work you feel I may be able to help out with, please shoot me an email at<EMAIL_ADDRESS>Thanks!


This module provides an extended idiomatic Lua interface to the CQRlib
library written by Herbert J. Bernstein. It is not a "binding" and access to the original documentation is only required for those who wish to understand the module's C code cqr.c
.
A quaternion is implemented as an immutable userdata consisting of four double precision numbers. The metatable of that module, which is its own __index
, is returned by require "cqr"
.
Three special cases of a quaternion are:
The module contains the following methods. All expect a quaternion as first argument and are normally called using object-oriented notation, as shown.
q:unpack()
w,x,y,z
of q
.
q:scalar()
q
. Same effect as (q:unpack())
.
q:normsq()
q
.
q:sqrt()
q
. If there are infinitely many square roots (i.e. q
is a negative scalar), returns nothing. (Not in CQRlib
.)
q:exp()
q
.
q:log()
q
.
q:arg()
math,pi
when q
is plotted in the plane, with the scalar part on the x
axis and the norm of the vector part on the y
axis.
q:root(n,k)
q
.
q:vector()
q
with the scalar part set to 0.
q:axis()
q
with the scalar part set to 0 and the vector part normalized to have norm 1, so that the result is an axis.
q:angles()
q
is not a rotator.
q:matrix()
q
is not a rotator, then the result is a rotation matrix scaled by q:normsq()
.
All the constructors are subsumed in one function cqr.new
. The number and type of the arguments direct the choice of constructor.
cqr.new()
cqr.new(q)
q
. Not needed in Lua, since one can simply assign the (immutable) value to another name, but old habits die hard.
cqr.new(w)
w
and vector part zero.
cqr.new(mat)
mat
, such as the output of q:matrix()
. The result is undefined if mat
is not a rotation matrix (i.e. an orthogonal matrix with determinant 1.)
cqr.new(rx,ry,rz)
q:angles()
.
cqr.new(w,x,y,z)
Metamethods for the binary functions + - * / ^
work analogously to their ordinary numerical counterparts. For the first four of these, either argument may be a number; in particular, the reciprocal of a q
can be computed as 1/q
. For the power function, the second argument may be a number.
Please keep in mind that multiplication is not commutative. Division is defined by (b/a)*a == b
. The expression a*(b/a)
yields a rotation of b
around the vector a
: see the definition of //
below.
Metamethods for conversion to a string, negation (unary -
) and equality (==
) also work as one expects, but for the equality test, both arguments must be quaternions.
Six other metamehods not applicable to floating-point numbers have been defined to provide access to functions peculiar to quaternions. This usage has nothing to do with the original meaning of the symbols.
The metamethods are stored in the module cqr
under the names described in the Lua manual: __add
, __bnot
etc.
#q
~q
q1..q2
v>>t
v
by the angle t
q//r
q
by the rotator r
, using the formula r*q*~r
. If r
is not a rotator, the result is scaled as well as rotated.
v1|v2
v1
to a scalar multiple of another: v1//(v1|v2) == (#v1/#v2)*v2
. (Not in CQRlib
.)
The following four routines from CQRlib
have been included for the sake of completeness, but they are much less basic than the others and not vouched for the author of the Lua package.
Their action is described by the author of CQRlib
as follows:
The SLERP and HLERP functions combine quaternions by spherical linear interpolation. SLERP takes two quaternions and two weights and combines them following a great circle on the unit quaternion 4-D sphere and linear interpolation between the radii. SLERP keeps a quaternion separate from the negative of the same quaternion and is not appropriate for quaternions representing rotations. Use HLERP to apply SLERP to quaternions representing rotations.
They expect two quaternions as their first two arguments and should be called in non-object style. All the arguments are therefore shown. In the first two routines, w1,w2
are weights; the return value is at t=w2/(w1+w2)
in a parameter space where the given points are at t=0
and at t=1
.
cqr.slerp(q1,q2,w1,w2)
cqr.hlerp(q1,q2,w1,w2)
cqr.slerpdist(q1,q2)
cqr.hlerpdist(q1,q2)
__name
"quaternion"
__index
_VERSION
"quaternion library for Lua 5.3: Apr 2019"
.
A quaternion in which two of the three vector components are 0 is obviously equivalent to a complex number. This observation allows one to compute any analytical function of a quaternion (i.e. one definable by a power series or comtinued fraction) if the corresponding function f
of a complex veriable is available, by the following procedure:
-- let q = w + v*u, where w and v are scalar and u is an axis
-- evaluate f(w+v*i) = x+y*i
-- f(q) = x + y*u
The reason why this is correct is that there exists a rotator r
such that s = q//r
is equivalent to a complex number, so that f(s)
can be evaluated via the given routine. Now for any power of s,
s^k = (r*q/r)^k = r*q^k/r = q^k//r
and applying this term-by term to an expansion of f
, we arrive at f(q//r) = f(q)//r
and thus f(q) = f(q//r)//~r.
The above three steps is merely a more straightforward way of doing the same calculation.
The test suite for cqr
actually tests cqr.exp
, cqr.log
and cqr.sqrt
this way, if a suitable complex
(i.e. one that has methods new
, real
, imag
, exp
and log
) can be found by require
. See the code near the top of test.lua
for a function H.eval
that implements the algorithm.
CQRlib
that have not been provided in the Lua modulelocal w,x,y,z = q:unpack()
and create a new quaternion instead.
1/q
.


This is Arockia. I'm a Python automation developer by profession and information security fan by passion. Curious about the new technology learning and hands on.
Now started exploring Internet Of Things and will keep updated here on my learning and developments. Those who like to sail on the same boat, keep an eye here.
Joined in Cognizant Technology Solutions and learnt couple of infrastructure automation tools Ansible, Ayehu.
Joined in Cognizant Technology Solutions and learnt couple of infrastructure automation tools Ansible, Ayehu.
Got promoted as a Solution Lead in Asian Paints Pvt Ltd and spent couple of years. Such a great learning.
I got an excellent opportunity to do my final year project and my first job as a Programmer Analyst in Asian Paints Pvt Ltd, Mumbai.
Python byted me here :)
Finally decided to proceed career in Computer Science domain and did a cross major course.
Yes. Have proved my parents that my decision was good by on-campus job offer from Asian Paints Pvt Ltd, Mumbai.
I spent 3 years to figure out what should I do in my future in parallel with my under graduation on Physics.
Doing a web application development due to interest in web design from college.
Development of System and Infrastructure related automation scripts development and Home automation.
I am ready to share/instruct people who are willing to learn Python and web design.
Dignissimos asperiores vitae velit veniam totam fuga molestias accusamus alias autem provident. Odit ab aliquam dolor eius.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts.
Far far away, behind the word mountains, far from the countries Vokalia and Consonantia, there live the blind texts.


Holedox Eating
问题描述 :
Holedox is a small animal which can be considered as one point. It lives in a straight pipe whose length is L. Holedox can only move along the pipe. Cakes may appear anywhere in the pipe, from time to time. When Holedox wants to eat cakes, it always goes to the nearest one and eats it. If there are many pieces of cake in different directions Holedox can choose, Holedox will choose one in the direction which is the direction of its last movement. If there are no cakes present, Holedox just stays where it is.
输入:
The input consists of several test cases. The first line of the input contains a single integer T (1 <= T <= 10), the number of test cases, followed by the input data for each test case.The first line of each case contains two integers L,n(1<=L,n<=100000), representing the length of the pipe, and the number of events.
The next n lines, each line describes an event. 0 x(0<=x<=L, x is a integer) represents a piece of cake appears in the x position; 1 represent Holedox wants to eat a cake.
In each case, Holedox always starts off at the position 0.
The next n lines, each line describes an event. 0 x(0<=x<=L, x is a integer) represents a piece of cake appears in the x position; 1 represent Holedox wants to eat a cake.
In each case, Holedox always starts off at the position 0.
输出:
The input consists of several test cases. The first line of the input contains a single integer T (1 <= T <= 10), the number of test cases, followed by the input data for each test case.The first line of each case contains two integers L,n(1<=L,n<=100000), representing the length of the pipe, and the number of events.
The next n lines, each line describes an event. 0 x(0<=x<=L, x is a integer) represents a piece of cake appears in the x position; 1 represent Holedox wants to eat a cake.
In each case, Holedox always starts off at the position 0.
The next n lines, each line describes an event. 0 x(0<=x<=L, x is a integer) represents a piece of cake appears in the x position; 1 represent Holedox wants to eat a cake.
In each case, Holedox always starts off at the position 0.
样例输入:
3 10 8 0 1 0 5 1 0 2 0 0 1 1 1 10 7 0 1 0 5 1 0 2 0 0 1 1 10 8 0 1 0 1 0 5 1 0 2 0 0 1 1
样例输出:
Case 1: 9 Case 2: 4 Case 3: 2
#include<stdio.h> #include<string.h> #define N 100000 #define INF 100000020 #define lowbit(x) ((x)&(-(x))) int a[N*2]; int L; void add(int t,int v) { while(t<=L) { a[t]+=v; t=(t|(t-1))+1; } } long long query(int t) { long long ans=0; while(t>0) { ans+=a[t]; t&=t-1; } return ans; } int right_search(int t) { if(t==L) { if(query(L)-query(L-1)) return L; return INF; } int l=t,r=L; int cmp=query(t-1); while(l<=r) { int mid=(l+r)>>1; query(mid)-cmp>0?(r=mid-1):(l=mid+1); } if(query(l)-cmp==0) return INF; return l; } int left_search(int t) { if(t==1) { if(query(1)) return 1; else return INF; } int l=1,r=t; int cmp=query(t); int mid; while(l<=r) { mid=(l+r)>>1; cmp-query(mid)>0?(l=mid+1):(r=mid-1); } if(query(l)==0) return INF; return l; } int main(void) { int t,n,ct=0,dist,pos,dir,x; scanf("%d",&t); while(t--) { pos=1; dist=0; dir=1; memset(a,0,sizeof(a)); scanf("%d%d",&L,&n); L++; while(n--) { scanf("%d",&x); if(x) { int l=left_search(pos); int r=right_search(pos); if(l==INF&&r==INF) ; else if(pos-l>r-pos||l==INF) { dist+=r-pos; pos=r; dir=1; add(r,-1); } else if(pos-l<r-pos||r==INF) { dist+=pos-l; pos=l; dir=-1; add(l,-1); } else if(dir==1) { dist+=r-pos; pos=r; add(r,-1); } else { dist+=pos-l; pos=l; add(l,-1); } } else { scanf("%d",&x); add(x+1,1); } } printf("Case %d: %d\n",++ct,dist); } return 0; }
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雅虎的99就是纯粹的吹牛逼
雅虎的99就是纯粹的吹牛逼
雅虎的99就是纯粹的吹牛逼
雅虎的99就是纯粹的吹牛逼


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HydroShare is an online collaboration environment for sharing data, models, and code.


Contributors¶
Majdi I. Radaideh is a Postdoctoral Associate at MIT Nuclear Science and Engineering. He obtained his MS and PhD degrees from the University of Illinois at Urbana Champaign (UIUC) between August 2015 - August 2019. Radaideh’s research focuses on algorithms, data engineering, deep learning, physics-informed machine learning, reinforcement learning, uncertainty quantification, and large-scale optimization with applications related to nuclear reactor safety and multiphysics simulations. Radaideh is the founder of NEORL with contributions include establishing the framework structure, algorithm development, open-source and documentation handling, benchmarking and testing, applications to nuclear fuel assembly optimisation, user interface handling, parallel computing, and many other minor contributions.
Github: https://github.com/mradaideh
Koroush Shirvan is the John Clark Hardwick (1986) Career Development Professor in the Department of Nuclear Science and Engineering. Previously, he was a principal research scientist at Center for Advanced Nuclear Energy Systems (CANES). He specializes in development and assessment of advanced nuclear reactor technology. His research combines multiple scales, physics and disciplines, and machine learning to realize innovative solutions in the highly regulated nuclear energy sector. His contribution to NEORL includes securing the funding for NEORL, significant contributions to the development of the physics-based applications of NEORL in the nuclear engineering area, and direct administration of the project.
Webpage: https://web.mit.edu/nse/people/faculty/shirvan.html
Paul RM. Seurin is a Ph.D student at MIT Nuclear Science and Engineering department. He joined MIT in September 2019 after receiving an Engineering Diploma and a Master in Nuclear Engineering from France. His research involves algorithm design for optimization with focuses on heuristics methods, deep, and Reinforcement Learning with applications to nuclear reactor economics and licensing. For NEORL, he is currently working on validation and benchmarking, applying the framework from Pressurized Water Reactor optimization to combinatorial and Mixed-Integer programming.
Haijia Wang is an undergraduate student at MIT in the MIT Electrical Engineering and Computer Science Department. She is in the class of 2023, studying Computer Science and Engineering. She is passionate about algorithm design and optimization, artificial intelligence and machine learning, and advanced computing technologies. Haijia is interested in exploring these fields in her studies and future career. She worked as a summer research intern with NEORL in 2020, and her contribution was adding different hyperparameter tuning methods to NEORL, including evolutioanry search and Bayesian search. She also validated the classes for grid and random search.
Linkedin: https://www.linkedin.com/in/haijia-wang


This demo shows how to use bulk data operations with the new JDK8 Collections API. The demo also demonstrates new features of JDK8 such as lambda expressions and method/constructor references.
Analyzes a CSV file, finds and collects useful information, computes different statistics. For more information, see the source file.
Source: src/CSVProcessor.javaBehaves like the standard Linux tool Grep. For more information, see the source file.
Source: src/Grep.javaProduces a password of desired length. For more information see source file.
Source: src/PasswordGenerator.javaCounts newlines, words, characters, and the maximum line length of a text file. For more information, see the source file.
Source: src/WC.java


Css classes
A should have a red background with styling from class.
graph LR;
A-->B[AAABBB];
B-->D;
class A cssClass;
A should have a red background with styling from style definition.
graph LR;
A-->B[AAABBB];
B-->D;
style A fill:#FF0000,stroke:#FFFF00,stroke-width:4px;
A should have orange background with styling from local class definition definition.
graph LR;
A-->B[AAABBB];
B-->D;
classDef orange fill:#f96,stroke:#333,stroke-width:4px;
class A orange;
linkStyle 0 stroke:#ff3,stroke-width:4px;
classDef default fill:#f9f,stroke:#333,stroke-width:4px;


Future with Jellyfish
Analysis of the Impact of Jellyfishes
throughout Time
Upon running scrapers that grabs articles related to jellyfish from the past 10 years, the view of humans to jellyfishes as well as their impact to our environment can be summarised in the following points:
- Overpopulation of jellyfish became a problem starting from 2013, where the word "bloom" and "population" became more common, describing the problem.
- Jellyfishes have always been a baffling topic, as seen by the words used throughout the years to describe the studies being done: "university", "dr", "researchers", "scientists", "papers"
- Several scientists have also been in articles talking about jellyfishes, such as "widmer"--Chad Widmer and "sanz-martin"--Marina Sanz-Martin
- You could also see several groundbreaking incidents causing particular jellyfish to be in the news, such as Irukandji Jellyfish in 2013 and the surge of jellyfish in the Mediterranean in 2014
This backs up the general hypothesis that jellyfish became less intriguing but more as a fear for they have been "blooming" and causing problems in the ecosystem. This brings us to our next scene, where jellyfish have become the majority species due to them being able to thrive in polluted environments
Generated WordClouds
Year 2009
Year 2010
Year 2011
Year 2013
Year 2014
Year 2015
Year 2016
Year 2017
Year 2018
Year 2019
Process of Article Scraping
Running the Scrapers
Total Number of Articles Scraped
Unique Sources
Number of Articles per year
Please navigate through the sections in the following order:
Underwater > Sustain > Reports > Jellyfish > The Hunt > Ethics Behind > Summary


Reports any type parameters declared to extend a final class. Since final classes cannot be extended, the type parameter could be replaced with the type of the specified final class.
Powered by InspectionGadgets


| covariance {pbdDMAT} | R Documentation |
cov()
and var()
form the variance-covariance matrix. cor()
forms
the correlation matrix. cov2cor()
scales a covariance matrix into a
correlation matrix.
## S4 method for signature 'ddmatrix' cov(x, y = NULL, use = "everything", method = "pearson") ## S4 method for signature 'ddmatrix' var(x, y = NULL, na.rm = FALSE, use) ## S4 method for signature 'ddmatrix' cor(x, y = NULL, use = "everything", method = "pearson") ## S4 method for signature 'ddmatrix' cov2cor(V)
x, y, V |
numeric distributed matrices. |
use |
character indicating how missing values should be treated.
Acceptable values are the same as |
method |
character argument indicating which method should be used to
calculate covariances. Currently only "spearman" is available for
|
na.rm |
logical, determines whether or not |
cov()
forms the variance-covariance matrix. Only
method="pearson"
is implemented at this time.
var()
is a shallow wrapper for cov()
in the case of a
distributed matrix.
cov2cor()
scales a covariance matrix into a correlation matrix.
Returns a distributed matrix.
## Not run: # Save code in a file "demo.r" and run with 2 processors by # > mpiexec -np 2 Rscript demo.r library(pbdDMAT, quiet = TRUE) init.grid() x <- ddmatrix("rnorm", nrow=3, ncol=3), bldim=2 cv <- cov(x) print(cv) finalize() ## End(Not run)


object ChildrenSchema
Schema for the 'children' table. The table stores the parent-child relationships between people.
This class contains constants for column names of the table, and SQLite statement for creation. Neither of the two columns of this table are unique identifiers (see documentation), but they are both non-null columns.
const val COL_CHILD_ID: String
The person ID of a child. |
|
const val COL_PARENT_ID: String
The person ID of the parent. |
|
const val SQL_CREATE: String
SQLite statement which creates the "children" table upon execution. |
|
const val TABLE_NAME: String |


Model your businessy stuff.
Gain insight into your call center, help desk, business unit, and/or taco stand.
Free and open source
Advanced Quick Start


Right now, we are diligently prototyping the TrashBot™, our flagship product.
Check our News feed for current information, or follow us on:


Community Page
Edit Your Post!
Submit Edited Post!
Delete Post
Delete this post
Are you sure you want to delete this Post? It's permanant!


Exploring the Differences between Margin, Padding and Border
An important concept to understand in HTML and CSS is the Box model. Every element on a page can be considered to be its own box, with padding, border, and margins around it. Though they are all white space around the element they serve different purposes.
Content
The content is what actually appears on a page, whether it be text, a photo or diagram. The padding, border and margins are what surrounds the content.
Padding
Padding is the whitespace immediately surrounding the content. The width of the padding can vary according to specifications, and can be uniform on all sides or set to different sizes on the top, bottom, left and right. Padding does not go away but it can be set to zero so as to not be visible.
Border
Borders are the visible lines that surround the content and padding. By default borders are not visible but can be added with CSS. They can be either a solid line or dashed, with various options for color, width, and border radius to make the corners curved. Borders can also be specified for all sides or just the top, bottom, left or right side.
Margin
The margin is the whitespace that goes around the border and is what separates each element from each other. Like padding, it can be set uniformly on all sides or can be customized. One important difference to note is that vertical margins collapse, when elements are stacked one after the other. For example, if each element has a margin of 5px, instead of creating 10px of space between paragraphs the space is limited to the 5px. This is automatic so that when multiple paragraphs follow each other, they all have the same amount of margin spacing between them as the top and bottom, without having to edit each element’s margin.
Example of CSS styling:
div { border: 2px solid black; margin: 5px 5px 5px 5px; padding: 2px 0px 2px 0px; }


Merchant Navy Decoded : A unified marine community where transparency and right guidance is easily available.


{% load static %} {% load format_utils %}
Court File No.:
Court Registry: {% if responses.court_registry_for_filing %} {{ responses.court_registry_for_filing }} {% else %} {% endif %}
In the Supreme Court of British Columbia
Claimant 1: {% if responses|name_you %} {% include "partials/name_with_alias.html" with name=responses|name_you use_other_name=responses.any_other_name_you other_names=responses.other_name_you class_name='form-entry_claimant' %} {% else %} {% endif %}
Claimant 2: {% if responses|name_spouse %} {% include "partials/name_with_alias.html" with name=responses|name_spouse use_other_name=responses.any_other_name_spouse other_names=responses.other_name_spouse class_name='form-entry_claimant' %} {% else %} {% endif %}
| [A civil protection order is any order made against a person for the purposes of protecting another person’s safety] | ||
A civil protection order may restrict or restrain a person from doing certain things, such as
|
||
| YES | NO | |
| Are you aware of any active protection order about you, or any other people involved in this family law case? | {% checkbox protection_order_against_you_or_spouse='YES' %} | {% checkbox protection_order_against_you_or_spouse='NO' %} |
| Are you or others involved in this family law case also involved in any protection order matter? | {% checkbox protection_order_involving_you_or_spouse='YES' %} | {% checkbox protection_order_involving_you_or_spouse='NO' %} |
|
If you answered yes, provide more detail: {{ protection_order_detail|linebreaksbr }} |
| [Child protection services (“child welfare”) protect children from harm. Child protection services might use a supervision or custody order to protect children from harm. Child protection services may exist under a different name in another province.] | ||
| YES | NO | |
| Are you or others involved in this family law case also involved with child protection services? | {% checkbox involved_with_child_protective_services='YES' %} | {% checkbox involved_with_child_protective_services='NO' %} |
|
If you answered yes, provide more detail: {{ child_protective_services_details|linebreaksbr }} |
| [Criminal offences are offences under the Criminal Code and other federal laws, including the Controlled Drugs and Substances Act (Canada). Criminal offences or matters do not include bylaw offences, traffic tickets, or consumer issues.] | ||
| YES | NO | |
| Are you or others involved in this family law case facing a criminal charge? | {% checkbox criminal_charge_facing='YES' %} | {% checkbox criminal_charge_facing='NO' %} |
| Are you or others involved in this family law case required to follow a court order because of a criminal matter? (Such as release / bail order, probation order, peace bond/ recognizance, parole order, warrant, or required to follow conditions) | {% checkbox criminal_charge_court_order='YES' %} | {% checkbox criminal_charge_court_order='NO' %} |
| Are you or others involved in this family law case required to follow demands because of a criminal matter? (Such as a promise to appear or a summons) | {% checkbox criminal_charge_demands='YES' %} | {% checkbox criminal_charge_demands='NO' %} |
| Are you or others involved in this family law case in prison? | {% checkbox criminal_charge_prison='YES' %} | {% checkbox criminal_charge_prison='NO' %} |
|
If you answered yes, provide more detail: {{ criminal_charge_details|linebreaksbr }} |
| Date: | |||
| [dd/mmm/yyyy] |
Signature of {{ responses.which_claimant }} {% if responses.which_claimant == 'Claimant 1' %} {{ responses|name_you }} {% else %} {{ responses|name_spouse }} {% endif %} |


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