Users can log in, log out and change password from the main menu. In addition an administrator can create new users.
Each user gets a login page and a home page. The login page sets user details and group memberships in the session. The user name above the left navigation tree is also a link to a user home page.
Users can be created in any project, but their access to all project is by group membership, not parent project.


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 1
Preheat the oven to 200C/400F/Gas 6.
Place the haddock fillet into an ovenproof dish, pour over the milk and add the butter, bay leaves and peppercorns.
Transfer to the oven and poach for 10-12 minutes, then remove from the oven and set aside to cool slightly.
Meanwhile, mix the crème fraîche with the lemon zest, grated parmesan and most of the chives. Season, to taste, with salt and freshly ground black pepper.
Heat the butter with half of the oil in a large ovenproof frying pan over a medium heat, and pour in the eggs, stirring slightly as they cook to loosen them from the sides of the pan.
Flake the haddock from the skin while the eggs are cooking, taking care to remove any remaining bones.
When the eggs are still slightly runny on top but have started to set, spread over the crème fraîche mixture, then scatter over the haddock and transfer the omelette to the oven for 4-5 minutes, or until cooked through and slightly risen. Remove from the oven.
To serve, drizzle the remaining oil over the watercress in a small bowl and add the lemon juice, turning to coat the leaves. Slide the omelette onto a serving plate, sprinkle over the remaing chives and arrange the dressed watercress on the side.


< prev index next > modules/javafx.web/src/main/native/Source/ThirdParty/libxml/src/entities.c
Print this page
}
/*
* xmlCreateEntity:
*
- * internal routine doing the entity node strutures allocations
+ * internal routine doing the entity node structures allocations
*/
static xmlEntityPtr
xmlCreateEntity(xmlDictPtr dict, const xmlChar *name, int type,
const xmlChar *ExternalID, const xmlChar *SystemID,
const xmlChar *content) {
* @SystemID: the entity system ID if available
* @content: the entity content
*
* Create a new entity, this differs from xmlAddDocEntity() that if
* the document is NULL or has no internal subset defined, then an
- * unlinked entity structure will be returned, it is then the responsability
+ * unlinked entity structure will be returned, it is then the responsibility
* of the caller to link it to the document later or free it when not needed
* anymore.
*
* Returns a pointer to the entity or NULL in case of error
*/
/**
* xmlEncodeEntitiesInternal:
* @doc: the document containing the string
* @input: A string to convert to XML.
- * @attr: are we handling an atrbute value
+ * @attr: are we handling an attribute value
*
* Do a global encoding of a string, replacing the predefined entities
* and non ASCII values with their entities and CharRef counterparts.
* Contrary to xmlEncodeEntities, this routine is reentrant, and result
* must be deallocated.
< prev index next >


Message to our supporters- information about your data
We have recently been informed by one of our suppliers about a cyber-attack which has affected many organisations and charities worldwide, including RZSS.
ViewYou can help feed our animals at this difficult time by adopting our Sumatran tiger
Adopt todayA message from Andrew, our tiger keeper:
“Dharma our Sumartran tiger is quite elusive so she is used to self-isolation! You’re most likely to see her in the morning or afternoon. It’s a special moment when you see Dharma up close in person or on our cameras – and you can help her at this difficult time by giving a donation.
Sumatran tigers live alone in the wild and are quite shy, so don’t worry if you can’t see her. She’s most likely exploring in the long grass or having a snooze! “If she could, we’re sure even Dharma would like to say a huge tiger-sized thank you to everyone who has donated. Giving a tiger their tea is an amazing gift!"
It’s impossible to overstate the impact of the Covid-19 closure on Edinburgh Zoo. It cut off 90% of the funds needed by our dedicated keepers and vets to care for thousands of animals. If you can, please consider a donation to support our survival fund.
£50 could buy feed Dharma for a week. Please help our animals like Dharma by giving an online donation today. Or you can donate by text.
Simply text ZOO plus the amount you’d like to donate to 70085 (e.g. ZOO5 to donate £5)*.
If you didn't capture a glimpse of the elusive Dharma but did you know our conservation team are using DNA from tiger poo to help protect tigers in Nepal? Tigers are the biggest cats on the planet, but also one of the most threatened. In this episode of #RZSSGoesWild, find out why it's important for us to understand what's on the menu for wild tigers in Nepal, how DNA from poo can help us do this, and how the tigers at our zoos helped us to refine our tiger poo detective skills. Why not catch up on all episodes of #RZSSGoneWild and find out about the wider work of RZSS?
Donate to support RZSS projects in the wild
We would like to say thank you to IndigoVision for their generous support of our Tiger Tracks enclosure. Without their expertise we would not have been able to provide this incredible 24 hour live view of the tigers. If you would like to find out more about IndigoVision and their Intelligent Video Solutions please visit www.indigovision.com.
We would also like to say thank you to Camvista who provide their expert video streaming services for all of our webcams.
We have recently been informed by one of our suppliers about a cyber-attack which has affected many organisations and charities worldwide, including RZSS.
ViewThese last few months has shown how much people love Edinburgh Zoo and Highland Wildlife Park and today we launch our survival fund to help ensure we can realise shared aspirations for generations to come and play our essential role in protecting our beautiful planet.
ViewSupport Edinburgh Zoo's Survival Fund
I want to helpThe survival of endangered animals depends on the survival of your zoo.
Donations from thousands of people like you have kept our animals well fed and safe while we were closed and had no visitor income. We were grateful for every gift during those challenging times.
But while we can now welcome you back, our visitor numbers are greatly reduced and the future of your zoo is at risk.
Every month, we need thousands of pounds just to feed and care for the animals you love.
If you can, please help your zoo survive long into the future by giving a donation today.


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| Overview | Module | Use | Devguide | Index |
| Methods' Summary | Attributes' Summary | Methods' Details | Attributes' Details |
| interface XStorageBasedDocument |
|
| Methods' Summary | |
| loadFromStorage | lets the document load itself using provided storage. |
| storeToStorage | lets the document store itself to the provided storage. |
| switchToStorage | allows to switch the document to the provided storage. |
| getDocumentStorage | allows to get the storage the document is based on. |
| addStorageChangeListener | allows to register a listener that will be notified when another storage is set to the document. |
| removeStorageChangeListener | allows to deregister the listener. |
| Methods' Details | |||||||||||||
loadFromStorage
|
|||||||||||||
storeToStorage
|
|||||||||||||
switchToStorage
|
|||||||||||||
getDocumentStorage
|
|||||||||||||
addStorageChangeListener
|
|||||||||||||
removeStorageChangeListener
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Why create an Admin Controller?
It is easy enough to use something like CanCanCan to implement authorization, so why then would you need a separate Admin Controller for your application?
While CanCanCan provides a good base, adding an Admin Controller provides another layer of protection, as the routes you are trying to protect simply do not exist unless you are properly authenticated as an Admin.
It is easy to leave a route unprotected or make a mistake if your edit/create/update/destroy routes are in your public controllers, and having an Admin Controller helps prevent mistakes.
Implementation
- Within app/controllers, create another directory called ‘admin’ and create an
admin_controller.rb
in that new directory. - Create each individual controller that you want in the admin namespace. For example, if you would like to only allow an admin to edit or delete an item, create a new Items Controller with those actions inside of the controllers/admin folder.
- Remove the newly protection actions from the old Items Controller, leaving only those actions that you’d like users to access (e.g. show and index).
- Add the admin namespace to your routes file:
1 2 3 4 5 |
|
Notice that our old Item Controller still maintains it’s own routes, which we specify with :index
and :show
.
Now when we rake routes
, you’ll see the newly created namespaced routes:
Terminal
|
Sticking Point
Note that you will have to customize the POST from your admin forms:
<%= form_for(@item, :url => admin_item_path(@item) ) do |f| %>
Authored by Ian Andersen (@ianderse27). The original post is available here.


Welcome to Shoreditch, the East side of London!
Whether you’re adamant that ‘west is best’, vote north or back south London
all the way, it’s likely that you’ll still have been lured east a fair bit over the years.
You can’t argue with the evidence – east London is the scenesters’ paradise. Adult ball-pits,
niche cafés, ping pong bars – Shoreditch has them all.
The trending district for everything from French Bulldogs, to 'Hipster' fashion statements and
some of the most expensive gyms you'll never set foot in, Shoreditch is the place we love to hate
(to love). With urban art spaces, hidden speakeasies, rooftops, pop ups and underground dens, bars in
Shoreditch have got a rep for being some of the coolest in the city. Want a slice of the best places
to drink in East London?


Generate an ArUco marker by ID
Marker ID:
Marker size:
Units:
px
mm
in
Generate a random ArUco marker
Marker size:
Units:
px
mm
in
Generate a collection of ArUco markers
Number of markers:
250
A
R
U
CO-
G
EN
dummy marker ID and size info
Download
dummy spacer
Download
.SVG
.PNG
.JPEG


COPY THE KEY TO A SERVER
Once an SSH key has been created, the ssh-copy-id command can be used to install it as an authorized key on the server. Once the key has been authorized for SSH, it grants access to the server without a password.
This logs into the server host, and copies keys to the server, and configures them to grant access by adding them to the authorized_keys file. The copying may ask for a password or other authentication for the server.
Only the public key is copied to the server. The private key should never be copied to another machine.
Use a command like the following to copy SSH key:
ssh-copy-id -i ~/.ssh/mykey.pub user@host
or
cat ~/.ssh/id_rsa.pub | ssh<EMAIL_ADDRESS>"mkdir -p ~/.ssh && cat >> ~/.ssh/authorized_keys"
AUTHORIZED_KEYS
Configures permanent access using SSH keys
Configured separately for each user
Default location: /home/<user>/.ssh/authorized_keys
Default name: authorized_keys or authorized_keys2
Each line contains a SSH public key


Legalised cannabis tax confirmed by Lib Dems would raise £1.5bn to fight crime
The Liberal Democrats General Election manifesto includes a pledge to create a 'regulated cannabis market' - and slams Labour and the Tories' 'prohibitionist attitude to drug use'
by Mikey Smith, https://www.mirror.co.uk/authors/mikey-smith/A legalised cannabis tax would draw £1.5 billion to fight crime, the Lib Dems have said.
Jo Swinson's party confirmed they would create a regulated cannabis market if they won the election - as they slammed Labour and the Tories' "prohibitionist attitude to drug use."
The Liberal Democrats ' manifesto, launched today, says the party would draw on emerging evidence on models from the US and Canada.
The Department of Health would lead on drugs policy, rather than the Home Office - and the party pledged to invest more cash in addiction services and support for drug users.
Licensed outlets would be permitted to sell cannabis to adults over the age of 18, with limits placed on how strong the weed can be.
The party say this would help to "break the grip of the criminal gangs" on drug distribution.
Launching the manifesto, Ms Swinson said: "This manifesto is a bold plan to build a brighter future for our country, and that starts with stopping Brexit .
“Labour and the Conservatives can’t offer the country a brighter future because they both want Brexit.
“We know that will be bad for our economy, bad for our NHS and bad for our environment."
She added: “Liberal Democrats will stop Brexit and invest in our mental health services, give free childcare to working parents, put 20,000 more teachers into classrooms and take ambitious action to tackle the climate emergency.
“Our politics has been dominated by the two, tired old parties for too long.
“This election provides an opportunity to change the future of our country and build a brighter future with the Liberal Democrats.”


We help teams everywhere succeed at their digital marketing using easy-to-use workflows.
Automate repetitive tasks and improve time management with marketing automation.
Better organize and reuse your marketing assets by creating and sharing different versions.


A secure and open source 2 factor authentication token.
Designed to be affordable and reliable.
U2F Zero is a USB token that works with any service that supports U2F, like Google services. It works for 2 factor authentication or sometimes even password replacement. No drivers needed. Just plug it in and press a button.
Buy (U.S.) Buy (EU)A TRNG is used on chip to ensure high entropy keys get generated during registration.
Keys are generated on an off chip peripheral and live in write only memory. Nothing can read them except the peripheral itself.
Atmel secure chip includes temperature and voltage tampering sensors.
Because the source is open, there is confidence there are no backdoors in the source code.
Have any questions or ideas?
For any sales/refund/product issues, please email<EMAIL_ADDRESS>Make sure Firefox is updated to the latest version (at least FF60). If it still does not work, email support and you will be refunded. There was a faulty batch made around start of 2018 that has this issue. U.S. market is fine but EU market is still being replaced.
Note that stock in U.S. and EU is currently up-to-date and working.
Yes, refer to the wiki on the Github repository.


MergeSort
Mergesort algorithm without recursion, using cached binary trees 👇
- Generating a tree beforehand, divides the problem in half, where the first part can be calculated once and reused for arrays with same size.
- Lack of recursion avoids functions calls, making the algorithm perform as close as possible to natively compiled vendor implementations.
For larger arrays (> 1M) it performs faster than native solutions (around %25-%50 faster). For smaller arrays performs comparable or slower (around %25 slower).
| milliseconds | 1M * | 10M **† | 100K † | 100K |
|---|---|---|---|---|
| Mergesort | 34900 | 229000 | 11000 | 10900 |
| Chrome | 35200 | 326000 | 10200 | 10200 |
†: Instance created using size
option
*: 50 iterations
**: 30 iterations
Documentation
For a list of config options, see here.
For directly embedding to html, if you are using a browser with compatibility > ie11, use the file ending with ...evergreen.min.js
in the dist
folder. Otherwise, you can fall back to ...es5.min.js
. To read the entire build, refer to the files without the .min.
part.
Usage
let instance = Mergesort(),
array = Array.from({length:100}).map(d => Math.random());
instance(array, (a,b) => a - b);
Installation
npm install @ibowankenobi/mergesort
Build
npm run build
You will end up with 4 files in the dist
folder, an es5 version, an es6 version and minified versions of both.
Browser
<script src="https://cdn.jsdelivr.net/npm/ibowankenobi-mergesort"></script>
The contents of the request above is the same as ./dist/mergesort.x.y.z.evergreen.min.js
.
If you want to request a particular version, check instructions at jsdelivr.


box-sizing
display
direction
writing-mode
flex-direction
flex-wrap
justify-content
align-items
align-content
flex-basis
width
height
flex-items
Multiline flexitem(s)
For flex item(s)
append the following text
align-self
For flex item(s)
set align-self to
Flexitem order
For flex item(s)
set order to
flex-grow
For flex item(s)
set flex-grow to
flex-shrink
For flex item(s)
set flex-shrink to
transform


@(games: List[((String, String, Long, Long, Long, Long, java.sql.Timestamp))])(implicit flash: Flash) @rating(Messages("players.history")) {
| Player A | Player B | A's win | B's win | Elo of Player A after this match | Elo of Player B after this match | Timestamp |
|---|---|---|---|---|---|---|
| @game._1 | @game._2 | @game._3 | @game._4 | @game._5 | @game._6 | @game._7 |


WELCOME TO FLASH. LIGHTS.
HOW MUCH CAN YOU REMEMBER?
YOU WILL BE SHOWN A RANDOM PATTERN OF FLASHING LIGHTS AND THEN ASKED TO
RECREATE IT BY CLICKING ON THE TILES IN THE SAME ORDER SHOWN.
BE CAREFUL! IF YOU GET THE PATTERN WRONG, YOU'LL HAVE TO START THE ROUND
AGAIN.
GET IT WRONG 10 TIMES AND YOU'LL HAVE TO RESTART THE GAME!
GET IT RIGHT 5 TIMES AND YOU ADVANCE TO THE NEXT LEVEL!

CLICK ME TO START!


Sayak Khatua
EO Staff Meeting April 15, 2021
reveal.js enables you to create beautiful interactive slide decks using HTML. This presentation will show you examples of what it can do.


File: src/away/controllers/SpringController.ts
///<reference path="../_definitions.ts" /> module away.controllers { /** * Uses spring physics to animate the target object towards a position that is * defined as the lookAtTarget object's position plus the vector defined by the * positionOffset property. */ export class SpringController extends LookAtController { private _velocity:away.geom.Vector3D; private _dv:away.geom.Vector3D; private _stretch:away.geom.Vector3D; private _force:away.geom.Vector3D; private _acceleration:away.geom.Vector3D; private _desiredPosition:away.geom.Vector3D; /** * Stiffness of the spring, how hard is it to extend. The higher it is, the more "fixed" the cam will be. * A number between 1 and 20 is recommended. */ public stiffness:number; /** * Damping is the spring internal friction, or how much it resists the "boinggggg" effect. Too high and you'll lose it! * A number between 1 and 20 is recommended. */ public damping:number; /** * Mass of the camera, if over 120 and it'll be very heavy to move. */ public mass:number; /** * Offset of spring center from target in target object space, ie: Where the camera should ideally be in the target object space. */ public positionOffset:away.geom.Vector3D = new away.geom.Vector3D(0, 500, -1000); constructor(targetObject:away.entities.IEntity = null, lookAtObject:away.base.DisplayObject = null, stiffness:number = 1, mass:number = 40, damping:number = 4) { super(targetObject, lookAtObject); this.stiffness = stiffness; this.damping = damping; this.mass = mass; this._velocity = new away.geom.Vector3D(); this._dv = new away.geom.Vector3D(); this._stretch = new away.geom.Vector3D(); this._force = new away.geom.Vector3D(); this._acceleration = new away.geom.Vector3D(); this._desiredPosition = new away.geom.Vector3D(); } public update(interpolate:boolean = true) { var offs:away.geom.Vector3D; if (!this._pLookAtObject || !this._pTargetObject) return; offs = this._pLookAtObject.transform.matrix3D.deltaTransformVector(this.positionOffset); this._desiredPosition.x = this._pLookAtObject.x + offs.x; this._desiredPosition.y = this._pLookAtObject.y + offs.y; this._desiredPosition.z = this._pLookAtObject.z + offs.z; this._stretch = this._pTargetObject.transform.position.add(this._desiredPosition); this._stretch.scaleBy(-this.stiffness); this._dv.copyFrom(this._velocity); this._dv.scaleBy(this.damping); this._force.x = this._stretch.x - this._dv.x; this._force.y = this._stretch.y - this._dv.y; this._force.z = this._stretch.z - this._dv.z; this._acceleration.copyFrom(this._force); this._acceleration.scaleBy(1/this.mass); this._velocity.incrementBy(this._acceleration); this._pTargetObject.transform.position = this._pTargetObject.transform.position.add(this._velocity); super.update(); } } }


{% extends "template.html" %} {% block head %} {% endblock %} {% block main %}
readEntity
and buffer options. Closing the response no longer throws an exception.MuServer.rateLimiters()
returns an empty list (instead of throwing an exception).explode
was incorrectly set sometimes
causing queries from UIs such as swagger to add commas into array values rather than having multiple parameters.//
the request gets redirected with
the extra slash removed, rather than the previous behaviour where the first path segment would be ignored.connection
headers, as per HTTP2 spec.MuServerBuilder
, ResourceHandlerBuilder
,
RestHandlerBuilder
and Http2ConfigBuilder
to expose the current values
on those builders.0.73.1 and 0.73.2 were not released.
Mutils.pathAndQuery(URI)
method to quickly get the path with
querystring from a URI.video/mp4
content typejavax.ws.rs.ext.RuntimeDelegate.createHeaderDelegate
now supports
java.util.Date
io.muserver.rest.CORSConfigBuilder.toHandler
so that CORS handlers can
be more conveniently created from CORS config.There were no releases for 0.72.18, and 0.72.19.
UriBuilder.uri()
method to handle encoded paths and query string valuesX-Forwarded-*
headers to
Forwarded
headersMuRequest.clientIP()
to get an IP address taking into account forwarded headers.SseSinks
) detect
client disconnections and mark the publisher as closedUploadedFile
objects in JAX-RS method parameters to be
wildcard types, primarily to make it work with Kotlin listsMuServerBuilder.withExceptionHandler
to allow custom exception handlersisLast
parameter has been added to onBinary
and onText
. This is non-breaking to
existing implementations in that they will just ignore the isLast
flag. The existing
callback functions are marked as deprecated and so implementers should move to the versions with the
isLast
parameter.toString()
methods to various classes just to make logging and debugging a bit nicerThere was no releases for 0.72.3.
Versions from 0.71.4 to 0.72.0 included a change to enabled OCSP staping which was subsequently rolled back due to the reasons described here so this 0.72.1 release includes changes from 0.71.x.
Headers.toString()
no longer prints the values of cookie
,
set-cookie
or authorization
headers in order to reduce the chance of accidentally
logging potentially sensitive information (the header names are still printed however the value printed
will be (hidden)
). To customize (or disable) value redaction,
Headers.toString(Collection<String> toSuppress)
can be used.Response.variant
and
Response.variants
. Also, selectVariant
allows qs
parameters to
specify server-preferred types and uses same sorting algorithm as the JAX-RS method matching algorithmJaxRSResponse
set (rather than add) headers which should only ever have
one value, such as content-language
SPLIT_ON_COMMA
is on and an empty string is given an empty list
(rather than a list with an empty string) is returned for collection parametersRestHandlerBuilder#withCollectionParameterStrategy
method.QueryParam
and HeaderParam
annotations in resource methods@CookieParam Cookie
cookie
The 0.70.x releases contained a breaking change that was reverted in 0.71.0 and so these releases should be skipped and ignored.
Request
objects to be injected to methods with the @Context
annotation0.62.3 and 0.62.4 were not released.
RestHandlerBuilder
This includes changes in the 0.62.0 release which was not published.
/components/schemas
section of the JSON (although it is not currently referenced elsewhere).ResourceInfo
objects from properties.
Example: ResourceInfo resourceInfo = (ResourceInfo) requestContext.getProperty(MuRuntimeDelegate.RESOURCE_INFO_PROPERTY);
(or use MuRuntimeDelegate.MU_REQUEST_PROPERTY
to get the Mu Request).0.61.14 was not released
content-length
header won't clash with the response body size).0.61.11 was not released
0.61.6, 0.61.7 and 0.61.8 were not released.
0.61.4 was not released.
This includes changes from the unpublished 0.61.0 release
abortWith(Response)
an exception mapper is no
longer invoked with that Response mapped in a WebApplicationException
.content-type
set was throwing a Server exception.0.60.7 was not released.
0.60.5 and 0.60.4 were not released.
Integer.MAX_VALUE
bytes)This includes changes from the unpublished 0.60.0 version.
~_-.
) are not percent encoded when passed to handlers.
This allows non-urlencoded route declarations such as /~home
image/avif
as a supported mime typeFile
objects can be @FormParam
parameters in JAX RS methods0.56.1 contained changes in test code only.
LocalDate
, LocalDateTime
,
LocalTime
, OffsetDateTime
, OffsetTime
, ZonedDateTime
Year
and YearMonth
objects in JAX RS methods. For example you can use parameters such as @QueryParam("date") LocalDate date


Survey Form
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Ping-Pong Test
Think this is boring? Me too. Click here to see the improved version (still tweaking).


Hi, I'm Jordan Patton! I'm a user experience researcher, designer, and developer. For a sample of my work, please see my portfolio.
(Contact me for the password.)
Hi, I'm Jordan Patton! I'm a user experience researcher, designer, and developer. For a sample of my work, please see my portfolio.
(Contact me for the password.)


Mapletree Commercial Trust's preferential offering 1.45 times subscribed
by Marissa LeeMAPLETREE Commercial Trust (MCT) has raised S$460.5 million in gross proceeds from its preferential offering, which was 1.45 times subscribed, it said on Monday night.
Some 205.6 million new units will be issued on the basis of 71 new units for every 1,000 existing units in MCT. The issue price for the new units is S$2.24 apiece. They will begin trading on the main board of the Singapore Exchange with effect from 9.00 a.m. on Nov 15.
Together with the gross proceeds of S$458 million raised from the private placement, MCT has raised gross proceeds of S$918.5 million from the equity fund raising exercise.


Swift Server Generator models automatically have a standard set of HTTP endpoints that provide REST APIs for create, read, update and delete (CRUD) operations on model data.
The REST APIs are mounted to the plural model name in the Model definition JSON file. For example, a model named location with plural locations has its REST API mounted on /api/locations.
The REST API is as follows:
| Operation | OpenAPI (Swagger 2.0) operationID | HTTP method | Path | Corresponding SQL | Example path |
|---|---|---|---|---|---|
| Create | create | POST | /api/{modelPlural} | INSERT | /api/locations |
| Index | findAll | GET | /api/{modelPlural} | SELECT | /api/locations |
| Delete (destroy) | deleteAll | DELETE | /api/{modelPlural} | DELETE | /api/locations |
| Read | findOne | GET | /api/{modelPlural}/{id} | SELECT | /api/locations/1 |
| Update (modify) | update | PATCH | /api/{modelPlural}/{id} | UPDATE | /api/locations/1 |
| Update (modify) | replace | PUT | /api/{modelPlural}/{id} | UPDATE | /api/locations/1 |
| Delete (destroy) | delete | DELETE | /api/{modelPlural}/{id} | DELETE | /api/locations/1 |
For POST, PUT and PATCH requests, the request body is in JSON format, and the Content-Type header set to application/json.
The response format for all requests is typically a JSON object/array in the body, and a set of headers. Some responses have an empty body.
For example:
Date: Tue, 15 Nov 2016 11:13:07 GMT
Content-Type: application/json
Content-Length: 59
Connection: Keep-Alive
Keep-Alive: timeout=60, max=99
[
{
"title":"MyNote",
"content":"This is my first note",
"id":"1":
}
]
The HTTP status code indicates whether a request succeeded, as follows:
| Status code | Meaning |
|---|---|
| 2xx | Success |
| 4xx | There are problems with the request |
| 5xx | There are server-side problems |
The response for an error is in the following JSON format:
error: {String_error_message}
For example:
{
"error": "Provided value (1234) for property 'type' has type (number) which is not compatible with the property type (string)"
}


hsqldb - 100% Java DatabaseLightweight 100% Java SQL Database Engine |
|
There is a built-in security system using users, passwords and access rights. There exists by default a 'System Administrator' with the user name 'sa' and the password '' (empty password). This special user can create new users, drop users and grant and revoke access rights for tables or stored procedures to other users. The general users can only change their own password and connect as another user. All this user administration can be done by SQL scripts (GRANT, REVOKE). Access can be granted also to PUBLIC.
Identity (autoincrement) column type
Identity columns can be used to serve as automatic unique row identifier for a table. When a new row is added to the table and the identity column is not inserted (or a NULL value is inserted), then HSQLDB provides a unique, incremental value for the column. The identity column is automatically the primary key of the table. Only one identity column can be created per table. In HSQLDB, any value can be used for updating or inserting in an identity column provided it does not violate the primary key constraint.
HSQLDB supports extensive system tables that are build dynamically when a query is made to them. These tables provide database metadata. The names of the tables are 'SYSTEM_' followed by the corresponding JDBC DatabaseMetaData method. For example the methode 'getColumns(...)' queries the table 'SYSTEM_COLUMNS'. There are several other system tables reporting on database tables, indexes, primary keys, foreign keys etc.
Readonly connection and database support
Connections can be set to readonly using the command SET READONLY [TRUE|FALSE] or using the method Connection.setReadOnly(boolean readonly). Additionally the whole database can be put in read-only mode by manually adding the line 'readonly=true' to the .properties file. All connections are then automatically readonly. The database files will then be opened in readonly mode, and it is thus possible to create a CD with this database. Other variations, allow modifiable readonly database (changes are discarded at shutdown) or inclusion of a database in the application JAR.
Selecting big results / Scanning big tables
One limitation of HSQLDB is that it currently does not support server side cursors. This means the result of a query must always fit in memory, otherwise an OutOfMemory error occurs. In the rare situation that a huge resultsets must be processed, then the following workaround can be used:
Limit the ResultSet using Statement.setMaxRows(1024), and select multiple 'smaller' blocks. If the table is for example 'CREATE TABLE Test(Id INT IDENTITY PRIMARY KEY, Name VARCHAR)' then the first block can be selected using 'SELECT * FROM Test ORDER BY Id' and the next block using 'SELECT * FROM Test WHERE Id>(biggest_id) ORDER BY Id' until no more records are returned. Don't forget to switch of the limit using setMaxRows(0).
The database file should grow automatically, empty space (after deleting records) should be reused automatically, and the file should shrink finally if data is deleted.
In HSQLDB, not all of these features are currently implemented for the .data file. In most cases empty space (caused by deleted records) is reused, because a list of 1024 free blocks is kept. But this list is lost when the database is closed. In one case (DROP TABLE) the space is not reclaimed.
To shrink all files to the minimum size, use the SQL command 'CHECKPOINT DEFRAG' and continue using the database or use 'SHUTDOWN COMPACT' when closing the database. It is a good idea to run this command also before creating a read-only database.
Java Stored Procedures / Functions
Stored procedures are Java functions that are called directly from the SQL language or using an alias. Calling Java functions (directly or using the alias) requires that the Java class can be reached by the database (server). User defined stored procedures / functions must be places where the database server runs. For HSQLDB, stored procedures and functions are equal. The syntax for calling functions and stored procedures (inside a SELECT statement for example) is:
SELECT Value, "java.lang.Math.sqrt"(Value) AS SQRT FROM Test
It can be called also without the SELECT, using the command CALL. This makes more sense for 'Stored Procedures' but works for functions, too:
CALL "java.lang.Math.sqrt"(2.0)
The package must be provided, and the name must be written as one word, and inside " because otherwise it is converted to uppercase (and not found).
An alias can be created using the command CREATE ALIAS:
CREATE ALIAS SQRT FOR "java.lang.Math.sqrt"
When an alias is defined, then the function can be called additionally using this alias:
CALL SQRT(2.0)
SELECT Value, SQRT(Value) AS SQRT FROM Test
This are the rules when creating user defined functions / stored procedures:
There is also a security mechanism provided: Access to each class can be granted / revoked to a user:
GRANT ALL ON "java.lang.Math" TO PUBLIC
By default, all users have access to java.lang.Math and org.hsqldb1.Library.
This text is based on HypersonicSQL documentation, updated
to reflect the latest version of HSQLDB


This cookie and privacy policy is for website (hereinafter “website”) witch operated by Etna Development OÜ (hereinafter “Company”, “we” or “us”) and governs the privacy of its users who choose to use it (hereinafter ‘User’ or ‘you’).
Company's activities are conducted in accordance with legislation of the Republic of Estonia and European Union law, and their provisions have to be taken into account.
The Company encourage You to read this Cookie and Privacy Policy carefully when using our website or services or transacting business with us. By using website, you are accepting the practices described in this Cookie and Privacy Policy.
If you have any questions about our privacy practices, please refer to the end of this Cookie and Privacy Policy for information on how to contact us.
We are legally obliged to collect personal information that can identify you such as your name and email address and other information that identify you. When you provide personal information through our website, the information will be sent to our servers.
We may collect and store any personal information you enter on our website or provide to us in some other manner. This includes identifying information, such as your name, address, e-mail address, birth data and telephone number, financial information such as your payment method (valid credit card number, type, expiration date or other financial information). We also may request information about your interests and activities, your gender and age, other demographic information and other information like this;
We can keep all files you upload to our website, including images.
We may also periodically obtain both personal and non-personal information about you from other sources like networks business partners, contractors and other third parties and add it to our account information or other information we have collected. Examples of information that we may receive include: updated delivery and address information, purchase history, and additional demographic information.
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Through the use of a cookie, we also may automatically collect information about your online activity on our website, such as the web pages you visit, the links you click, and the searches you conduct on our site.
Most browsers automatically accept cookies, but you can usually modify your browser setting to decline cookies. If you choose to decline cookies please note that you may not be able to sign in or use some of the interactive features offered on our website.
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You may delete or decline cookies by changing your browser settings. (Click "Help" in the toolbar of most browsers for instructions.) If you do so, some of the features and services of our website may not function properly;
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Web beacons may be used to deliver or communicate with cookies, to count users who have visited certain pages and to understand usage patterns. We also may receive an anonymous identification number if you come to our site from an online advertisement displayed on a third-party website.
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We want you to feel confident using our website to transact business. However, no system can be completely secure. Therefore, although we take steps to secure your information, we do not promise, and you should not expect, that your personal information, searches, or other communications will always remain secure. Users should also take care with how they handle and disclose their personal information and should avoid sending personal information through insecure email.
We will occasionally update this Privacy Policy to reflect changes in our practices and services.
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Popular Energy Drinks:
Red Bull
Rock Star
Monster
Energy drinks are good because they give you energy. Blah, blah, blah.
Blah, blah, blah. Blah, blah, blah. Blah, blah, blah. Blah, blah, blah. Blah, blah, blah. Blah, blah, blah.
I'm drinking a Rock Star energy drink right now, simply because it was on sale at Walgreens.
I'm drinking a Rock Star energy drink right now, simply because it was on sale at Walgreens.
I'm drinking a Rock Star energy drink right now, simply because it was on sale at Walgreens.


fun makeTile(tileId: Int, attendeeId: String?): VideoTile
Make a VideoTile
tileId - : Int - Tile ID
tileId
attendeeId - : String? - Attendee ID
attendeeId
Return VideoTile to use with VideoTileController


Open VIrus
Open Virus
Dashboard
Diseases per country
Diseases Plot
Diseases
Drugs
Disease representation
Influenza as described in papers
Drugs on map


Retired Navy explosive detection dog honored at Los Alamitos Race Course
CYPRESS, Calif. (KABC) -- A special honor was bestowed on a retired Navy explosive detection dog at the Los Alamitos Race Course on Saturday evening.
Talpi's service was recognized as part of the track's Honoring Our Veterans event.
The canine helped to keep our military members safe from 2009 to 2017.
He was based in San Diego, was deployed to Africa several times, and often helped the Secret Service.
Talpi now lives with his first Navy handler, Krystal Tronboll, who was able to adopt him with the help of the nonprofit group Mission K9 Rescue.


A sample that creates a component that will increase an internal number when you click in the button from ribbon button. When you click an internal function is called
The view of the component is the following:
And the typescript of the component:
async function executorConstructor(el: HTMLElement, app: DrapoApplication): Promise< Executor>
{
//Initialize
let instance: Executor = new Executor(el, app);
await instance.Initalize();
return (instance);
}
class Executor {
//Field
private _el: HTMLElement = null;
private _app: DrapoApplication;
private _sector: string = null;
//Properties
//Constructors
constructor(el: HTMLElement, app: DrapoApplication) {
this._el = el;
this._app = app;
}
public async Initalize(): Promise< void>
{
this._sector = this._app.Document.GetSector(this._el);
}
public async Increment(value : string): Promise< string>
{
let valueNumber: number = this._app.Parser.GetStringAsNumber(value) + 1;
return (valueNumber.toString());
}
}


| ActivityDescriptionTest |
A test case for the model object 'Activity Description'.
|
| ActivityTest |
A test case for the model object 'Activity'.
|
| ApplicableMetaClassInfoTest |
A test case for the model object 'Applicable Meta Class Info'.
|
| ArtifactDescriptionTest |
A test case for the model object 'Artifact Description'.
|
| ArtifactTest |
A test case for the model object 'Artifact'.
|
| BreakdownElementDescriptionTest |
A test case for the model object 'Breakdown Element Description'.
|
| BreakdownElementTest |
A test case for the model object 'Breakdown Element'.
|
| CapabilityPatternTest |
A test case for the model object 'Capability Pattern'.
|
| ChecklistTest |
A test case for the model object 'Checklist'.
|
| ClassifierTest |
A test case for the model object 'Classifier'.
|
| CompositeRoleTest |
A test case for the model object 'Composite Role'.
|
| ConceptTest |
A test case for the model object 'Concept'.
|
| ConstraintTest |
A test case for the model object 'Constraint'.
|
| ContentCategoryTest |
A test case for the model object 'Content Category'.
|
| ContentDescriptionTest |
A test case for the model object 'Content Description'.
|
| ContentElementTest |
A test case for the model object 'Content Element'.
|
| ContentPackageTest |
A test case for the model object 'Content Package'.
|
| CoreSemanticModelBridgeTest |
A test case for the model object 'Core Semantic Model Bridge'.
|
| CustomCategoryTest |
A test case for the model object 'Custom Category'.
|
| DeliverableDescriptionTest |
A test case for the model object 'Deliverable Description'.
|
| DeliverableTest |
A test case for the model object 'Deliverable'.
|
| DeliveryProcessDescriptionTest |
A test case for the model object 'Delivery Process Description'.
|
| DeliveryProcessTest |
A test case for the model object 'Delivery Process'.
|
| DescribableElementTest |
A test case for the model object 'Describable Element'.
|
| DescriptorDescriptionTest |
A test case for the model object 'Descriptor Description'.
|
| DescriptorTest |
A test case for the model object 'Descriptor'.
|
| DiagramElementTest |
A test case for the model object 'Diagram Element'.
|
| DiagramLinkTest |
A test case for the model object 'Diagram Link'.
|
| DiagramTest |
A test case for the model object 'Diagram'.
|
| DimensionTest |
A test case for the model object 'Dimension'.
|
| DisciplineGroupingTest |
A test case for the model object 'Discipline Grouping'.
|
| DisciplineTest |
A test case for the model object 'Discipline'.
|
| DomainTest |
A test case for the model object 'Domain'.
|
| ElementTest |
A test case for the model object 'Element'.
|
| EllipseTest |
A test case for the model object 'Ellipse'.
|
| EstimationConsiderationsTest |
A test case for the model object 'Estimation Considerations'.
|
| ExampleTest |
A test case for the model object 'Example'.
|
| FulfillableElementTest |
A test case for the model object 'Fulfillable Element'.
|
| GraphConnectorTest |
A test case for the model object 'Graph Connector'.
|
| GraphEdgeTest |
A test case for the model object 'Graph Edge'.
|
| GraphElementTest |
A test case for the model object 'Graph Element'.
|
| GraphicPrimitiveTest |
A test case for the model object 'Graphic Primitive'.
|
| GraphNodeTest |
A test case for the model object 'Graph Node'.
|
| GuidanceDescriptionTest |
A test case for the model object 'Guidance Description'.
|
| GuidanceTest |
A test case for the model object 'Guidance'.
|
| GuidelineTest |
A test case for the model object 'Guideline'.
|
| ImageTest |
A test case for the model object 'Image'.
|
| IterationTest |
A test case for the model object 'Iteration'.
|
| KindTest |
A test case for the model object 'Kind'.
|
| LeafElementTest |
A test case for the model object 'Leaf Element'.
|
| MethodConfigurationTest |
A test case for the model object 'Method Configuration'.
|
| MethodElementPropertyTest |
A test case for the model object 'Method Element Property'.
|
| MethodElementTest |
A test case for the model object 'Method Element'.
|
| MethodLibraryTest |
A test case for the model object 'Method Library'.
|
| MethodPackageTest |
A test case for the model object 'Method Package'.
|
| MethodPluginTest |
A test case for the model object 'Method Plugin'.
|
| MethodUnitTest |
A test case for the model object 'Method Unit'.
|
| MilestoneTest |
A test case for the model object 'Milestone'.
|
| NamedElementTest |
A test case for the model object 'Named Element'.
|
| NamespaceTest |
A test case for the model object 'Namespace'.
|
| OutcomeTest |
A test case for the model object 'Outcome'.
|
| PackageableElementTest |
A test case for the model object 'Packageable Element'.
|
| PackageTest |
A test case for the model object 'Package'.
|
| PhaseTest |
A test case for the model object 'Phase'.
|
| PlanningDataTest |
A test case for the model object 'Planning Data'.
|
| PointTest |
A test case for the model object 'Point'.
|
| PolylineTest |
A test case for the model object 'Polyline'.
|
| PracticeDescriptionTest |
A test case for the model object 'Practice Description'.
|
| PracticeTest |
A test case for the model object 'Practice'.
|
| ProcessComponentDescriptorTest |
A test case for the model object 'Process Component Descriptor'.
|
| ProcessComponentInterfaceTest |
A test case for the model object 'Process Component Interface'.
|
| ProcessComponentTest |
A test case for the model object 'Process Component'.
|
| ProcessDescriptionTest |
A test case for the model object 'Process Description'.
|
| ProcessElementTest |
A test case for the model object 'Process Element'.
|
| ProcessFamilyTest |
A test case for the model object 'Process Family'.
|
| ProcessPackageTest |
A test case for the model object 'Process Package'.
|
| ProcessPlanningTemplateTest |
A test case for the model object 'Process Planning Template'.
|
| ProcessTest |
A test case for the model object 'Process'.
|
| PropertyTest |
A test case for the model object 'Property'.
|
| ReferenceTest |
A test case for the model object 'Reference'.
|
| ReportTest |
A test case for the model object 'Report'.
|
| ReusableAssetTest |
A test case for the model object 'Reusable Asset'.
|
| RoadmapTest |
A test case for the model object 'Roadmap'.
|
| RoleDescriptionTest |
A test case for the model object 'Role Description'.
|
| RoleDescriptorTest |
A test case for the model object 'Role Descriptor'.
|
| RoleSetGroupingTest |
A test case for the model object 'Role Set Grouping'.
|
| RoleSetTest |
A test case for the model object 'Role Set'.
|
| RoleTest |
A test case for the model object 'Role'.
|
| SectionTest |
A test case for the model object 'Section'.
|
| SemanticModelBridgeTest |
A test case for the model object 'Semantic Model Bridge'.
|
| SimpleSemanticModelElementTest |
A test case for the model object 'Simple Semantic Model Element'.
|
| StepTest |
A test case for the model object 'Step'.
|
| SupportingMaterialTest |
A test case for the model object 'Supporting Material'.
|
| TaskDescriptionTest |
A test case for the model object 'Task Description'.
|
| TaskDescriptorTest |
A test case for the model object 'Task Descriptor'.
|
| TaskTest |
A test case for the model object 'Task'.
|
| TeamProfileTest |
A test case for the model object 'Team Profile'.
|
| TemplateTest |
A test case for the model object 'Template'.
|
| TermDefinitionTest |
A test case for the model object 'Term Definition'.
|
| TextElementTest |
A test case for the model object 'Text Element'.
|
| ToolMentorTest |
A test case for the model object 'Tool Mentor'.
|
| ToolTest |
A test case for the model object 'Tool'.
|
| TypeTest |
A test case for the model object 'Type'.
|
| UmaAllTests |
A test suite for the 'Uma' model.
|
| UmaExample |
A sample utility for the 'uma' package.
|
| UMASemanticModelBridgeTest |
A test case for the model object 'UMA Semantic Model Bridge'.
|
| UmaTests |
A test suite for the 'uma' package.
|
| VariabilityElementTest |
A test case for the model object 'Variability Element'.
|
| WhitepaperTest |
A test case for the model object 'Whitepaper'.
|
| WorkBreakdownElementTest |
A test case for the model object 'Work Breakdown Element'.
|
| WorkDefinitionTest |
A test case for the model object 'Work Definition'.
|
| WorkOrderTest |
A test case for the model object 'Work Order'.
|
| WorkProductDescriptionTest |
A test case for the model object 'Work Product Description'.
|
| WorkProductDescriptorTest |
A test case for the model object 'Work Product Descriptor'.
|
| WorkProductTest |
A test case for the model object 'Work Product'.
|
| WorkProductTypeTest |
A test case for the model object 'Work Product Type'.
|


FancyBox Plus has project page where you can feel free to discuss and ask questions. In order to submit a question raise an issue at.
Issues page: https://github.com/igorlino/fancybox-plus/issues
Lightbox effect with youtube videos
Fancybox API – Using Callbacks


Motivation:
The two main goals created for this project go hand in hand, and fit together efficiently throughout the progress of this project. Based on the trends found in the data, our goal was to create the most effective model to predict pokemon based on variables in the dataset. Secondly, to create best application for users to pull information from our database based on specific variables of their choice. These goals are one that can actually be put to use, which is one of the stronger motivators. The application is very appealing because not only is it an applications that users could use, it is something that users would want to use, this is because it is a helpful tool that could help users to advance in the game. The goals fit together nicely because they both stem from finding useful trends or patterns in the data in order for them to be effective, this is the first step that will need to occur. Along with using previously discovered trends, the goals will prove helpful to find new trends in the data as well. For example, once a model is fit, it will uncover trends, some of which may have been known, others could be new. On the other side, the model could show a lack of tends, which is equally as helpful because this brings new information and ideas to the surface, providing additional motivation in contradicting popular beliefs. Pokemon creators state that different areas or conditions will cause specific pokemon to spawn, and this is something that would be very interesting to consider. If this is true, it will be interesting to see the relationships, and how effectively a predictive model can be, if it is false, the consideration of why it does not follow the pattern can be analyzed. These goals and ideas combined will tell a story about the data, and how pokemon interacted in the time period of the dataset.
Data Collection:
The data was collected from Kaggle.com, in CSV format, which made it easy to download. This dataset consists of roughly 293,000 pokemon captures, having coordinates, time, weather, population density, etc. as features. They were all captured over the first week of August 2016, and includes five full days, with two partial days. The data records each pokemon capture around the entire world in this time period. This time period is soon after the game was released in July of 2016.
Data Cleaning:
The data was in very good shape when we acquired it, which was very helpful during the data cleaning process. We had to change a few variables regarding north and south America, as they were all classified into the same category. This was done by using latitude to classify the difference. The excessive size of the file caused issues and could not be read directly into r. The file was stripped of unnecessary variables, such as ‘distance from a pokestop’ and the capture ID, along with being split up into multiple files by day. These could then all be read into r separately and then merged together. Overall the data cleaning process was very simple.
Results:
From looking at visuals and simple statistics many new things were learned. Some things were displayed as expected, and others showed things that brought new ideas to light about how the game was created and how it is being played. Any person who has played pokemon go, knows that some pokemon are far more popular than others, this was showcased in the bar chart of pokemon id by count, it revealed that a small number of pokemon are very popular and other are far less common. This was something that was expected, and can be properly analyzed. However, when doing that it is important to keep in mind that this was in a early stage of the game, when there were fewer experienced players, which means that there were fewer rare pokemon to begin with. The description of the dataset explained that it included all catches between August 2-8, when actually looking at the breakdown of the data, it looks like the data capturing started somewhere late on the second and was stopped early into the 8th, this means that there was only five full days of data collected, meaning that the description was misleading. May pokemon players believe that different pokemon will spawn under different weather conditions, we found that the most common weather condition was clear, both during the day, and at night. The fact that 100% of this data was from August should be taken into consideration when analyzing this. When looking at the distribution of pokemon caught over different hours, may patterns are shown. It is a fairly even distribution, meaning that there is not much difference between the hours. This goes to show that many pokemon go players are choosing to play at night. Using a time lapse may we were able to see how this changed around the world, and when the game was being played relative to all players around the world. A definition of time in categories was also involved, the categories of morning, afternoon, evening and night went to show that the number of players at night is almost equal to those during the day. Where the game is played most is also an interesting concept to consider, the visual shows that America and Europe have the most documented captures, although this is true, this is in an early stage of the game where the game was not released in some areas yet.
Analysis:
The creation of a machine learning model, capable of predicting a specific pokemon, or group of pokemon through the final variables latitude and longitude, minutes since sunrise/sunset, terrain, close to water, weather/ weather icon and rural/urban ended up not being as accurate as we would have hoped. Throughout the creation of many models, changing the predictive outcome and specific variables, the highest AUC was .62, which is not a great model. Although it was not as accurate of a model as we would have hoped for, it does do a better job than just a guess. The ROC curve plots true positive rate versus the false positive rate, and visualizes what the tpr and fpr will be for any cutoff value. Essentially meaning, that for however many pokemon that are guessed correctly, it will display the amount that are chosen incorrectly for that cutoff value. The results of these models lead us to believe that there is no specific pattern related to where and when pokemon appear, or if there is a pattern, it is much weaker than advertised.
The visualizations and the map provide one main trend that was slightly unexpected, pokemon players play 24/7, throughout the night. Coming in we knew that many pokemon players choose to play at night, what was surprising was that the number of captures at night were similar to captures numbers in the day. There are a few reasons behind this trend, starting with the time frame of the data. This data was collected in early August, this is a time where it is fairly warm outside in many areas, meaning that it would be appealing to play at night, when it is cooler out. Secondly, many people work during the day, only leaving the night time for leisure activities, such as playing pokemon. Practically, many people may think that less people will be playing at night, making the chances of catching pokemon will increase, pushing these people to play at night as well. Along with these basic ideas is the concept of gaming culture. Many typical gamers choose to play late at night, and this is no different for this game.
Conclusion:
At the conclusion of this project, trends occurred that were to our surprise, ranging from the type of pokemon, to when they are captured, and how pokemon explains the game. The type of pokemon differs in popularity, this is well known, and was confirmed by our dataset. However, the popularity of the pokemon does not change how well the models predicted, as it was predicted that they would. Many pokemon are caught at night, similar to the amount that are caught during the day, meaning that there is no significant downfall when there are less players. This is something that was surprising, we understood that their were players who choose to play at night, but no that there are similar numbers of night players as day players. Pokemon creators claim that there are significant places, times, and variables that control where pokemon spawn, leading to where they are caught. This is something that we feel is not true, or is not as powerful as advertised, due to the fact that these exact variables could not predict the pokemon, or even the type of pokemon.
Future Work:
In order to take this project further, the most important aspect would be to gather more data. It is predicted that if data for a larger period of time, and for a more condensed area was captured, then predictive models would become more accurate. The longer time span would allow for more trends to be captured in the data. If a smaller area such as a city was analyzed, this could make locational data, such as lat & lon, and close to water better predictors, this could also take into account other landmarks and terrain types. These things being much more specific can help to make the model far more accurate. As far as the Application goes, real time inputs would made it much more applicable for users. It would then be possible to search for what pokemon have been spawning lately, or even what are spawning now. This would increase the application value immensely.


Version 0.21.0¶
In development
Changed models¶
The following estimators and functions, when fit with the same data and parameters, may produce different models from the previous version. This often occurs due to changes in the modelling logic (bug fixes or enhancements), or in random sampling procedures.
- please add class and reason here (see version 0.20 what’s new)
- Decision trees and derived ensembles when both
max_depth
andmax_leaf_nodes
are set. (bug fix)
Details are listed in the changelog below.
(While we are trying to better inform users by providing this information, we cannot assure that this list is complete.)
Changelog¶
Support for Python 3.4 and below has been officially dropped.
- An entry goes here
- An entry goes here
sklearn.cluster
¶
- Major Feature A new clustering algorithm:
cluster.OPTICS
: an algoritm related tocluster.DBSCAN
, that has hyperparameters easier to set and that scales better, by Shane, Adrin Jalali, and Erich Schubert.
sklearn.linear_model
¶
- Fix Fixed a bug in
linear_model.MultiTaskElasticNet
andlinear_model.MultiTaskLasso
which were breaking whenwarm_start = True
. #12360 by Aakanksha Joshi.
sklearn.ensemble
¶
- Efficiency Make
ensemble.IsolationForest
prefer threads over processes when running withn_jobs > 1
as the underlying decision tree fit calls do release the GIL. This changes reduces memory usage and communication overhead. #12543 by Isaac Storch and Olivier Grisel.
sklearn.metrics
¶
- Feature Added the
metrics.max_error
metric and a corresponding'max_error'
scorer for single output regression. #12232 by Krishna Sangeeth. - Feature Add
metrics.multilabel_confusion_matrix
, which calculates a confusion matrix with true positive, false positive, false negative and true negative counts for each class. This facilitates the calculation of set-wise metrics such as recall, specificity, fall out and miss rate. #11179 by Shangwu Yao and Joel Nothman.
sklearn.neighbors
¶
- API Change Methods in
neighbors.NearestNeighbors
:kneighbors
,radius_neighbors
,kneighbors_graph
,radius_neighbors_graph
now raiseNotFittedError
, rather than AttributeError, when called before fit #12279 by Krishna Sangeeth.
sklearn.pipeline
¶
- API Change
pipeline.Pipeline
now supports using'passthrough'
as a transformer. #11144 by Thomas Fan.
sklearn.preprocessing
¶
- Efficiency Make
preprocessing.MultiLabelBinarizer
to cache class mappings instead of calculating it every time on the fly. #12116 by Ekaterina Krivich and Joel Nothman. - Efficiency
preprocessing.PolynomialFeatures
now supports compressed sparse row (CSR) matrices as input for degrees 2 and 3. This is typically much faster than the dense case as it scales with matrix density and expansion degree (on the order of density^degree), and is much, much faster than the compressed sparse column (CSC) case. #12197 by Andrew Nystrom. - Efficiency API Change Speed improvement in
preprocessing.PolynomialFeatures
, in the dense case. Also added a new parameterorder
which controls output order for further speed performances. #12251 by Tom Dupre la Tour.
sklearn.tree
¶
- Decision Trees can now be plotted with matplotlib using
tree.plot_tree
without relying on thedot
library, removing a hard-to-install dependency. #8508 by Andreas Müller. - Feature
get_n_leaves()
andget_depth()
have been added totree.BaseDecisionTree
and consequently all estimators based on it, includingtree.DecisionTreeClassifier
,tree.DecisionTreeRegressor
,tree.ExtraTreeClassifier
, andtree.ExtraTreeRegressor
. #12300 by Adrin Jalali. - Fix Fixed an issue with
tree.BaseDecisionTree
and consequently all estimators based on it, includingtree.DecisionTreeClassifier
,tree.DecisionTreeRegressor
,tree.ExtraTreeClassifier
, andtree.ExtraTreeRegressor
, where they used to exceed the givenmax_depth
by 1 while expanding the tree ifmax_leaf_nodes
andmax_depth
were both specified by the user. Please note that this also affects all ensemble methods using decision trees. :pr:`12344` by Adrin Jalali.
Multiple modules¶
Changes to estimator checks¶
These changes mostly affect library developers.
- Add
check_fit_idempotent
tocheck_estimator
, which checks that whenfit
is called twice with the same data, the ouput ofpredict
,predict_proba
,transform
, anddecision_function
does not change. #12328 by Nicolas Hug


Preparation time
less than 30 mins
Cooking time
10 to 30 mins
Serves
Serves 4
Warm the oil in a pan large enough to accommodate the fish fillets in a single layer.
Season the fillets with salt and pepper and place in the pan.
Seal on both sides over a low heat, without colouring the flesh.
Add the zest, chilli and garlic, and fry gently to allow the flavours to develop, about 1-2 minutes.
Add the wine and milk, increase the heat and bring to the boil. Reduce to a very gentle simmer and cover, with the lid gaping slightly.
Poach the fillets until just cooked through, 4-8 minutes, depending on their thickness. When done, the flesh will flake when pressed gently. The sauce will appear slightly curdled.
Remove from the heat and transfer the fish to warm serving plates. Gently pull off the skin. 8. Add the mascarpone to the pan and stir into the sauce.
Taste for seasoning and add the basil at the last minute.
Serve the cod with creamy mash and plenty of sauce spooned over the top.


Enquiry
Name:
Postal Address:
Gender:
Male:
Female:
City:
Choose..
Mumbai
Surat
State:
Choose..
Maharashtra
Pincode:
Email ID:
Number:
Submit
Reset


Go beyond the headlines with Google News
by Raffaele ColellaLast year, we redesigned Google News with one goal in mind: to help people understand the world through quality, trustworthy and enjoyable news. Today, we’re expanding on that mission by surfacing more in-depth content that highlights and explores key issues in our society.
With Beyond the Headlines in Google News, we want to recognize publishers that are investing in diving deeper into the headlines and moving past the who, what and when to explore the why and how. Keeping these stories visible beyond the fast daily news cycle, Beyond the Headlines connects readers with in-depth articles exploring important issues such as healthcare, the environment, education and more.
Whether you’re short on time or ready to dive deep into a topic, Beyond the Headlines will help you manage your time with an estimated read-time feature, letting you know how long it takes to read a story.
The stories are surfaced and organized using our Google News algorithms. Users can find the feature on the right side of news.google.com, and it is now available on desktop globally in U.S. English. More languages and a mobile version are planned for 2020.


Bus driver shot dead by gunman posing as passenger
by Tammy PetersenA man posing as a passenger fired three shots at a bus driver in Redcliffe, KwaZulu-Natal, on Tuesday, killing him instantly.
Provincial police spokesperson Captain Nqobile Gwala said the 31-year-old driver had been driving on Buffelsdraai Road when an unknown man shot him.
The gunman fled in a getaway car.
Gwala said the motive for the shooting had not yet been established.
Reaction Unit South Africa spokesperson Prem Balram said the private security company responded to the scene just after 07:00 where its officers found the man slumped in the driver's seat with three gunshot wounds to his head.
According to witnesses on the bus, a passenger entered the vehicle, drew a handgun and shot the driver in the head, Balram said.
"The suspect had been picked up as a passenger a short distance from the scene.
"Witnesses informed reaction officers that the bus was in motion when the driver was attacked. The vehicle then rolled back for a short distance before coming to a standstill in the centre of the road."

Three spent 9mm cartridges were found inside the bus.
Attempts to reach the bus company were unsuccessful.


Output below comes from main.dart
Click below to make GET with the browser to /v1/vane
/v1/vane
Click below to make GET with the browser to /v1/vane/myNameIs
/v1/vane/myNameIs


MVP v1 Prototype
{#
{{ button({
"text": "Research Flow - Invite",
"href": "research-flow-bob"
}) }}
{{ button({
"text": "Research Flow - Add",
"href": "research-flow-alice"
}) }}
#}
Primary user adds a delegate
Alice has an NHS login account and has no delegate for myHealth
Journey starts with Alice adding a delegate.
{{ button({
"text": "Add delegate flow",
"href": "research-flow-alice"
}) }}
{#
{{ button({
"text": "Start flow as Alice",
"href": "alice-adds-bob-as-delegator"
}) }}
#}
Emails
Security ("someone has been invited, if this wasn't you contact us")
NHS success ("someone has been added and accepted as a delegate to your NHS login account - add another / see all delegates")
Service success ("someone has been added and accepted to act on behalf within [SERVICE] - add another / see all delegates")
Delegate user accepts invitation
Bob has been invited to act on behalf of Alice as a delegate on myHealth
Bob has not agreed to consent
Bob may or may not have an NHS login account already
Journey starts with Bob receiving an email inviting him to be a delegate
{{ button({
"text": "Accept invite flow",
"href": "research-flow-bob"
}) }}
{#
{{ button({
"text": "Start flow as Bob",
"href": "alice-nominates-bob"
}) }}
#}
Emails
Invite ("someone has added you to their account, this means you can do this, this and this, click here to accept invite")
NHS success ("you have been connected to someone's nhs login - see all people you can act on behalf of")
Service success ("you have been added as a delegate to someone's [SERVICE] account - see all people you can act on behalf of")
Consent
Consent to be added/connected to the user's NHS login account
Consent for the specific service that they have been allocated to
{#
Bob has been added as a delegate for Alice and can now log into myHealth on her bahalf
Enter myHealth on behalf of Alice
Modules
Nominated delegate is sent an email which they can follow to accept/reject the access within account management
Confluence
Accept a nomination - option 2 -
Nominated delegate is sent and email in which they can accept/reject the invitation within from the email - this is currently not being prototyped
Confluence
Information is added about the nominated delegate, the delegated is matched against the information submitted and then added to a service
Confluence
The service is selected first and then the user added the nominated delegate information before matching
The service select page needs creating for this
Confluence
Authenticating and switching to delegated account
Confluence
Switch roles in NHS login
to do
The user is asked if they want to log in as themselves or as a delegated
login via OICD - option 1
to do
login via OICD - option 1
to do
login via OICD - option 1
to do
#}


Survey managers interact with users–that is, supervisors and interviewers–throughout the lifecycle of a survey.
Before the survey starts, they create accounts, designating field staff as supervisors and interviewers. During survey operations, they may may need to modify accounts, archiving and unarchiving user accounts. During that same period, they may need to monitor users, through data on user attributes and actions. Similarly, they may want to compile a list of all users–all supervisors, all interviewers, or both–for other monitoring scripts.
create_user(
user_name = "TestSup000",
user_password = "Test!Sup!000!",
role = "Supervisor"
)
create_user(
user_name = "TestInt007",
user_password = "Test!Int!007!",
role = "Interviewer",
supervisor = "TestSup000"
)
# suppose you have a dataframe of user details
# this might be drawn from an external file
users <- data.frame(
user_name = c("TestSup123", "TestInt123", "TestInt456"),
user_password = c("Test!Sup!123!", "Test!Int!123!", "Test!Int!456!"),
role = c("Supervisor", "Interviewer", "Interviewer"),
supervisor = c(NA_character_, "TestSup123", "TestSup123")
)
# create each user in the dataframe
# looping over users
purrr::pwalk(
.l = users,
.f = create_user
)
During data collection, user accounts may need to be decommissioned if associated field staff leave the survey–for example, get sick, are fired, or find another job. In Survey Solutions’ terminology, managers may archive an account.
Similarly, those who leave the survey may come back in some capacity, and consequently need their account reactivated. In the jargon of Survey Solutions, managers may need to unarchive an account.
See below how to accomplish action.
archive_user(id = "cf3134dc-83da-42b4-8671-37ccb598d9be")
unarchive_user(id = "cf3134dc-83da-42b4-8671-37ccb598d9be")
To monitor users, managers may want to access their user profile or to view their activity on the tablet. Here is how to accomplish those actions
# get user profile on the server
# this includes account details and personal details
get_user_details(user_id = "cf3134dc-83da-42b4-8671-37ccb598d9be")
# collect a log of activity on the tablet within specified dates
get_user_action_log(
user_id = "cf3134dc-83da-42b4-8671-37ccb598d9be",
start = "2020-02-15",
end = "2020-03-15"
)
To produce monitoring reports–for example, response rate by team–survey managers may need a list of all supervisors or all interviewers.
# collect the list of all supervisors and their user profile info
get_supervisors()
# collect the list of all interviewers and their user profile info,
# including the supervisor for each interviewer
get_interviewers()


A story about man's best friend
Her name is Nala. Always excited when i see her or rather when we see each other
She keeps the compound safe and my heart warm.
Procedure on cleaning her
- Tie her using a chain
- Open the tap
- Close your ears and heart cause she will cry
- Fire away :)
- Dont forget to use shampoo and a brush


LGPMA: Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment
Abstract
Table structure recognition is a challenging task due to the various structures and complicated cell spanning relations. Previous methods handled the problem starting from elements in diferent granularities (rows/columns, text regions), which somehow fell into the issues like lossy heuristic rules or neglect of empty cell division. Based on table structure characteristics, we find that obtaining the aligned bounding boxes of text region can effectively maintain the entire relevant range of different cells. However, the aligned bounding boxes are hard to be accurately predicted due to the visual ambiguities. In this paper, we aim to obtain more reliable aligned bounding boxes by fully utilizing the visual information from both text regions in proposed local features and cell relations in global features. Specifically, we propose the framework of Local and Global Pyramid Mask Alignment (LGPMA), which adopts the soft pyramid mask learning mechanism in both the local and global feature maps. It allows the predicted boundaries of bounding boxes to break through the limitation of original proposals. A pyramid mask re-scoring module is then integrated to compromise the local and global information and refine the predicted boundaries. Finally, we propose a robust table structure recovery pipeline to obtain the final structure, in which we also effectively solve the problems of empty cells locating and division. Experimental results show that the proposed method achieves competitive and even new state-of-the-art performance on several public benchmarks. [Paper]Highlights Contributions
❃ We propose a novel framework called LGPMA Network that compromises the visual features from both local and global perspectives. The model makes full use of the information from the local and global features through a proposed mask re-scoring strategy, which can obtain more reliable aligned cell regions.
❃ We introduce a uniform table structure recovering pipeline, including cell matching, empty cell searching, and empty cell merging. Both non-empty cells and empty cells can be located and split effcaciously.
❃ Extensive experiments show that our method achieves competitive and even state-of-the-art results on several popular benchmarks.
This paper obtains the reward of ICDAR 2021 best industry paper!
Recommended Citations
If you find our work is helpful to your research, please feel free to cite us:@inproceedings{qiao2021lgpma, author = {Liang Qiao and Zaisheng Li and Zhanzhan Cheng and Peng Zhang and Shiliang Pu and Yi Niu and Wenqi Ren and Wenming Tan and Fei Wu}, title = {{LGPMA:} Complicated Table Structure Recognition with Local and Global Pyramid Mask Alignment}, booktitle = {ICDAR}, volume = {12821}, pages = {99--114}, year = {2021}, }


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{% extends 'layout.html' %} {% block content %} Are you sure you want to delete "{{ entry.title }}"? {% endblock %}


This will be my new proffesional website, easily navigated and showcase my abilities, achievements, and hopefully help me standout.
The Field Overview page will give a look into the field of Civil Engineering.
The Work Place Analysis Page will give insight into the job opening Intern/Co-op – Transportation and Logistics Engineering–Marathon.
After the completion of this project I created a Reflective Memo.
If interested here are a couple links of my work/capabilities in mapping and programming.GIS/Property EvaluationVirtual Mapping with Javascript


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import models.CheckYourAnswersRowModel @this(mainTemplate: MainTemplate, formWithCSRF: FormWithCSRF, govukButton: GovukButton) @(answers: Seq[CheckYourAnswersRowModel])(implicit user : User[_], messages: Messages, appConfig: config.AppConfig) @answerRow(answerModel: CheckYourAnswersRowModel) = {
} @mainTemplate(pageTitle = messages("checkYourAnswers.title")) {


It analyzes matchups for League of Legends
Select your lane:
| Item | Description | % Played | Score differential |
| Item | Description | % Played | Score differential |
Your Champs Stats:
| Kills | Deaths | Assists | Lane Kills | Lane Deaths | Lane Assists | Towers Destroyed | Cs | Gold |
Your Opponent's Stats:
| Kills | Deaths | Assists | Lane Kills | Lane Deaths | Lane Assists | Towers Destroyed | Cs | Gold |
Opponent's Marksman Stats:
| Kills | Deaths | Assists | Lane Kills | Lane Deaths | Lane Assists | Towers Destroyed | Cs | Gold |
Opponent's Support Stats:
| Kills | Deaths | Assists | Lane Kills | Lane Deaths | Lane Assists | Towers Destroyed | Cs | Gold |


--- # Feel free to add content and custom Front Matter to this file. # To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults layout: home --- {% for collection in site.collections %} {% if site.[collection.label].size > 0 %}