When Donald Trump took office on January 20th, 2017, he was already known for his tweeting — Slate even called him the best. Known for his strong interjections and his 140-character feuds with everyone from Rosie O’Donnell to Mac Miller, the now-president always makes the most of his quickly typed messages and his 32.7 million followers, a following which, as the New York Times pointed out, is 1.7 times larger than that of the official @POTUS twitter.
In April, both the Washington Post and the New York Times dove into the President’s tweets over his first 100 days, cataloging and categorizing each, tracking his retweets, emojis, and busiest times, and discussing his repeated yells of “FAKE NEWS!” But I wanted to dive a little deeper into the @realDonaldTrump’s tweets, chirps, and occasional misfires over his first 100 days in office.
This essay visualizes all 501 Trump tweets between January 20th and April 29th to find out what he was saying, how he was saying it, and when he was talking about it. We'll also look at the source of his messages and the tw-entiment (ha, get it?). It works best on Chrome on your desktop, but I won't fault you for scrolling through it on your mobile. We're going to look at this from plenty of different angles, and as such, this essay isn't meant as a full exploration of each, but rather a short and sweet investigation to serve as a jumping off point for a couple of future projects. Full credits are at the end of the article, but I make use of data from the Trump Twitter Archive.
In the 100 days following his inauguration, @realDonaldTrump tweeted exactly 50 times about the media, 46 times about foreign affairs, 41 times about jobs, and 35 times regarding fake news.
He also posted about his immigration ban and Making America Great Again (33 times each), healthcare and unofficial business (28 times each), the democratic party (27), foreign leaders (24), Russia (20), the 2016 election (12), his own republican party (11), and of course, official “Presidential” business (139). More on this later.
These topics are based on a combination of my research and the themes distilled by the New York Times, the Washington Post, CNN, and the Slate.
The President liked to mention his own name. In fact, in a tie with media, he mentioned Trump 27 times. Together, they account for just about 1% all the words he posted on Twitter (including emoji and hashtags). He also likes the words People (26), President (25), me (24), Whitehouse (23), Great (23), FAKE (22), America (21), and Election (21) (let it go!).
You know the saying, “never tweet angry?” Well, neither do I, but it's still a good idea. And it's a truth that is perhaps most important for the leader of the free world. Donald Trump’s angriest (read most negative) tweets were presumably seen by well over the 32.7 million people who follow him — and there were a few of these tweets. For this “twentiment” analysis I ran each tweet through a natural language processor in Python to determine it's score on the polarity scale, with -1 being the most negative and +1 being the most positive. The tweets in the background are coloured according to this scale, with the angriest being darker and the happiest lighter.
In general, and unsurprisingly, the more strongly a tweet aligned to one end of the spectrum or the other, the more subjective — or, the more influenced by his personal feelings — his message was.
The most negative tweet was just two weeks into his tenure as president. This tweet about Iran and some sort of terrible deal clocked in at -1.
Iran has been formally PUT ON NOTICE for firing a ballistic missile.Should have been thankful for the terrible deal the U.S. made with them!
— Donald J. Trump (@realDonaldTrump) February 2, 2017
Equally as negative, this tweet came in a day later — the same day a federal judge in Boston declined to renew the temporary restraining order.
We must keep "evil" out of our country!
— Donald J. Trump (@realDonaldTrump) February 3, 2017
A good chunk of his most neutral tweets was written similarly to this one, almost as though it wasn't actually written by him. In fact, most of these were sent as ads or from an iPhone, whereas his most negative and most positive tweets were sent from an Android device. But more on that in a bit.
Today, I signed an Executive Order @ the U.S. Dept. of @Interior: 'Review of Designations Under the Antiquities Act' https://t.co/590ZX7cUV9 pic.twitter.com/wpqghLqqiF
— Donald J. Trump (@realDonaldTrump) April 26, 2017
While not his most positive tweet, this tweet score pretty high in both polarity and subjectivity, somewhat of a surprise coming from an iPhone. This healthcare tweet came after some bad press.
Despite what you hear in the press, healthcare is coming along great. We are talking to many groups and it will end in a beautiful picture!
— Donald J. Trump (@realDonaldTrump) March 9, 2017
To borrow a line from Polly Higgins of AM New York, Donald Trump may not be a “polished politician,” but he is a longtime English speaker. This fact, however, is far from obvious when we look at his Twitter account. The background now is showing all 9000 words he's tweeted since January 20th, coloured by their part of speech (or POS). While it's been pointed out many times that his grammar and spelling are less than impeccable, he seems to have cleaned it up a bit since becoming President, and unfortunately, we're only looking at his tweets in a very specific timespan, so those will have to wait.
adjectives adverbs interjections nouns pronouns proper nouns verbs WH-words links and others
This chart shows the distribution of Trump's tweets over his first 100 days, coloured by the main topic. Below his tweets are significant events that happened during his first 100 days, from his inauguration to his immigration ban to his order to investigate steel imports. Go ahead and click on a tweet to take a look, filter by category, or hover over an event to see more.
His first tweet, coming mere hours before his inaugural address, was on his first day in office. It was followed by 500 more, coming in fairly consistently over his first 100 days. He tweeted just about once per day from January 20th through Aril 29th
The last tweet of his first 100 days was posted on 9 pm on his final day, in reply to a comment made by Fox Business Network anchor Lou Dobbs. In the time between his first and last tweet, he only missed one day of tweeting. From 5:46 pm on April 14 th until 9:41 am two days later — exactly one day, 15 hours, and 55 minutes,— @realDonaldTrump was Twitter silent, a rare occurrence for the high-profile celebrity.
The first 10% of his tweets were sent in the first week of his presidency. That's 50 tweets in 7 days.
A quarter of them was posted by the 20-day mark. That's 125 in less than three weeks, a rate of 6.25 tweets per day.
By the 75-day mark, he had slowed down to about five tweets per day, or 375 total.
Comparing the timing of some major events with the timing of some popular tweets, we can make a connection between the two. It seems that Trump often takes to Twitter to back himself up, defend himself, vent his frustrations, or maybe just to get some attention.
The day after Donald Trump was sworn in as President, millions of people took to the streets all over the world — some 500,000 in D.C. alone — as part of the International Women's March. The Donald promptly took to Twitter, scorning the protesters and asking why the didn't vote, only to follow it up with a much calmer tweet, this time expressing his appreciation for their right to march.
A week later, a raid was launched against Al-Qaeda in Yemen, a risky and costly mission that led to the death of one American and a number of civilian casualties. The event was discussed at length by the media, and seemingly in response, Trump sent out a tweet saying we cannot allow the horrors in the Middle East to continue.
Only three days later, it was reported that Trump had a heated phone conversation with Australian Prime Minister Malcolm Turnbull about the refugee resettlement deal. Immediately following the conversation, he sent out the following: “Call it what you want, it is about keeping bad people (with bad intentions) out of country!”
Later that week, we saw a series of messages, posted following the temporary block of Trump’s immigration ban by a judge in the district court of Western Washington. Trump went on to question the “so-called” judge’s qualifications and call it a “terrible decision.”
Skipping ahead to the final week of his first 100 days, Trump sends out beautifully-composed and wonderfully-timed tweet discussing/defending his first-100-days accomplishments.
It turns out Donald Trump’s a pretty early riser (as perhaps Presidents should be). He regularly tweets around the 6 am mark, and occasionally tweets late into the night. Interestingly, there are a few trends when it comes to two things: one, what he's tweeting about, and two, what device he’s using. Take a look...
As noted above, he tweeted about the 2016 election twelve times in his first 100 days, and eleven of those tweets came in the AM. 5 of those came from an Android device, which many believe is his personal mobile.
Whether it was to defend it, promote it, or complain about judges being unfair, when it comes to his immigration ban, Trump took to Twitter a lot. 33 times in his first 100 days to be exact. And only five of the 33 came after February 21 st.
As was the case with the 2016 election, Trump generally tweeted about what he dubbed #FakeNews in the mornings. And up until March 15th, generally on his personal Android device.
@realDonaldTrump’s account tweets from two different devices. One is an iPhone and one an Android, and as many have pointed out before me, it's often obvious which one is the real Donald. David Robinson did a comprehensive language analysis, confirming that Trump's angrier tweets, AKA his Android tweets, are coming from the real him.
Highlighted now are the 167 tweets sent from his Android device, all but one of which were posted before March 8th. Click through the filters above the graph to see some trends in particular topics when it comes to what device he's tweeting from, and we'll see, it's almost as though someone took his Android away.
Created with ♥ by Sam Vickars. This project is (obviously) not endorsed by Donald Trump or his administration and is not affiliated with Twitter. Tweet data was provided by the Trump Twitter Archive by Brendan Brown. Inspiration was drawn from posts by Philip Bump of the Washinton Post, Danielle Rindler, also of the Washington Post, and Alicia Parlapiano and Larry Buchanan of the New York Times. Categories and topics are based on my research and those themes distilled by the above articles, while dates and descriptions of major events were sourced from Nick O’Malley’s article in the Sydney Morning Herald.
If you've got any suggestions, corrections, or additions, get in touch here, here, or here.


[Erowid Note: 200 mgs of 5-MeO-DiPT is considered an extremely high dose, see 5-MeO-DiPT Dose Chart ]
I have nearly 2 years experience with Foxy, tripping a countless number of times with this wonderful substance in every imaginable setting.
Up until the last month, my Foxy doses ranged from between 20-30mg, which according to most reports, is a pretty hefty dosage. After doing some more research and taking a plunge, I decided to experience what only a few brave/stupid souls have: taking 150+mg of Foxy at once. I had only seen a couple of people who had dared take this amount and the information they provided was very lacking. Anyway.
The most noticeable differences between a normal dose and one in this range are insane visuals, and a complete loss of the annoying body load. For me, the only load I have at this level is an INCREDIBLE body buzz, far surpassing that of MDMA. The visuals at this stage can't really be describe, but I will try my best. Also, lying in a totally darkened roomed will send me on a mind trip like I've never experienced before.
Now. for a brief experience from this past New Year's Eve. As for the setting, from 9-12:30 I was with 3 close friends and afterwards was at a larger party until I returned home at 5:00AM.
I ingested 200mg of 5-MeO-DiPT, dissolved in Ethanol for measurement at 9:30PM. For the first 30 minutes I became extremely nauseous, which I had not experienced at lower doses for quite some time. At the time I had been taking my daily dose of Xanax, but it does not seem to affect the trip at all; however, I have found that Paxil does seem to greatly lessen the entire Foxy experience.
At around 10pm I began to feel the familiar tryptimine-buzz and couldn't wait to begin my experience, especially since the nausea had passed.
10:30PM is when it hit me like a brick wall: I was quickly on my way to a +3.
11:00PM-05:00AM: The peak of the trip (which definitely lasts longer at this dosage). As I mentioned early, the entire experience can't be placed in words... the things I see and hear can't conform with everyday analogies. I've always had visuals with Foxy, but what was happening around me was at a level never before experienced. Curtains were furiously blowing as if a window had been left open. Ceiling fans and light fixtures rotated and descended (they were off of course).
The tracers were to he point where I could see multiple copies of a hand waved in front of my face for seconds (reminded me of a high dose of DXM) and in fact, everything around me that appeared to be moving also had a set of tracers. Never before have a I seen a stationary couch (or wall of that matter) move around my field of vision. At one point I was lost for nearly 30 minutes watching patterned wallpaper with images moving as if they were on television.
Now the only aspect of Foxy I don't absolutely love... the auditory hallucinations. All voices and music slowed down and dropped quite a few octaves. Listening to my stereo was almost not enjoyable. Songs were slow enough where every beat of every instrument could be individually discerned, which made almost all music take on an almost atonal quality. The only artist I could stand listening to was, strangely enough, Hallucinogen.
The trip would have lasted a few more hours (this is about the 5 time I've taken this dosage), but at 5:00AM I took several Klonopin and Ativan to help me come down and fall asleep. For the next hour or two I was in some sort of surreal half awake/half dreaming state that slowly melted away into a deep sleep.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Emergent Interaction
Complexity, Dynamics, and Enaction in HCI
A CHI 2021 Workshop held online, 15th May, 2021
Submissions now open via easychair
About the Workshop
Download the workshop proposal here
There is a long tradition of work in Human Computer Interaction which emphasises the specifically interactive elements of interaction behaviour. This work emphasises the way behaviour arises from ongoing adaptation, and the dynamically varying relationships between interacting elements - the human(s) and the technology(ies), as well as other humans and aspects of the environment. Researchers have used concepts as diverse as affordances, situated-ness, phenomenology, and control theory to understand these situations in which the direction of influence goes both ways. Just as human behaviour moulds and manipulates technology and environment, those same technologies and environments simultaneously condition human behaviour.
Recent work in Human-Computer Interaction (HCI) has framed this old question in a new way - suggesting that interaction is well modelled as a complex dynamical system. This approach brings the tools and concepts of Complexity Science to bear on familiar, but tricky, questions of interactivity and context. In doing so, it points to a range of new theoretical perspectives, modelling techniques, and other quantitative methods. These have the potential to enrich our understanding of interaction across many scales - from moment-to-moment system control, through patterns of engagement, to the behaviours of organisations and social networks.
Some complex dynamical approaches are already found in HCI and there is room to build on this. There are many publications on control theory, but comparatively little work on applications. Ecological Psychology and Enactivism have influenced embodied approaches to interaction since the 1980s, but their influence has been largely theoretical, overlooking recent developments around complex dynamical methodologies, and related theoretical accounts. We see opportunities both to re-engage with these approaches, and also to explore new approaches, such as those applied in the social sciences, bringing new methods and perspectives to bear on common problems within HCI.
This workshop will investigate these opportunities and challenges. Our organising committee brings together established voices from HCI, Control Theory, and Enactivist Cognitive Science, alongside younger researchers. We welcome participation from researchers from a range of disciplines whose work addresses the key topics of the workshop. Attendees will have a chance to present brief introductions to their own interests and positions, before engaging in guided discussions, which will inform a final panel discussion, drawing together the themes of the day.
See our Call for Participation to get involved
Important Information and Dates
Registration information:
Registration for CHI workshops is $30/workshop and attendees must also register for at least one day of the conference. Please note that conference registration increases significantly after the early registration deadline. For more information see here
Dates
-
Final extended Deadline: 28th February. We have extended this considerably. Current conditions (online teaching, childcare, and home working) mean many are overloaded with work. Some have contacted us to say that they would like to be involved but struggled to meet earlier deadlines. Hopefully this will allow more who wish to participate to do so.
-
Notification of Acceptance: We will be contacting authors who already submitted by our original deadline of 21st Feb. We will respond to remaining submissions as soon as possible after submission, to help authors meet the earlybird registration deadline.
- 15th May 2021: Workshop Time: 15 May JST 1300-1700 / 15 May EDT 0000-0400 / 15 May CEST 0600-1000


Type Definitions
argument
- Source:
Properties:
| Name | Type | Attributes | Default | Description |
|---|---|---|---|---|
name |
string | The argument name. This options has two
purposes: to document the command help, and to
identify the option in the |
||
desc |
string |
<optional> |
A description about what the argument is and what information the user is expected to supply. It is used to show the command help to the user. |
|
type |
string | The argument data type, either |
||
required |
boolean |
<optional> |
false
|
Whether or not the argument is required for the command to work. If the user fails to supply every required argument, Clapp will warn them about the problem and redirect them to the command help. |
default |
string | number |
<optional> |
A default value that will be passed into the
|
|
validations |
Array.<validation> |
<optional> |
An array with every validation check that you want to perform on the user provided value. See validation. |
An argument is an option passed to the command. In the CLI sentence (See
App.isCliSentence) /testapp foo bar
, bar
would be the
value of the first argument.
Type:
- Object
Example
var arg = {
name: 'file',
desc: 'The file where the data will be saved',
type: 'string',
required: false,
default: 'defaultfile.dat'
}
argv
Properties:
| Name | Type | Description |
|---|---|---|
args |
Object | An object containing every argument. |
flags |
Object | An object containing every flag. |
For more information, see Defining-the-command-function.
Type:
- Object
Example
{
args: {
myRequiredArg: 'foo',
myOptionalArgWithDefaultValue: 'bar',
},
flags: {
limit: 20,
debug: true
}
}
flag
- Source:
Properties:
| Name | Type | Attributes | Description |
|---|---|---|---|
name |
string | The flag name. This options has two
purposes: to document the command help,
and to identify the option in the
|
|
type |
string | The flag data type, either |
|
desc |
string |
<optional> |
A description about what the flag is and what information the user is expected to supply. It is used to show the command help to the user. |
default |
string | number | boolean |
<optional> |
A default value that will be passed into the
|
alias |
string |
<optional> |
A string of only one character containing
the alias of the flag. If the alias of
|
validations |
Array.<validation> |
<optional> |
An array with every validation check that you want to perform on the user provided value. See validation. |
A flag is an option passed to the command. Unlike arguments, flags are optional by
nature, meaning that you can't require the user to pass a flag. Flags always have a full
name, and may have aliases (i.e: --debug
and -d
). In the CLI sentence (See
App.isCliSentence) /testapp foo --bar
, bar
would be the
flag the user passed, and its value would be true
.
Type:
- object
Example
var flag = {
name: 'limit',
desc: 'The number of items that will be shown. Can\'t be higher than 50',
type: 'number',
alias: 'l',
default: 10
}
onReply()
The onReply function gets called every time Clapp needs to show output to the user. It
receives two parameters: msg
and context
. The msg
parameter is the message that you
need to show to the user. It can be the generated command help, if the user requests
it, an error message if the user doesn't pass a valid cli sentence, or your own message,
returned by the command function.
The context
is anything that you defined when calling App#parseInput, for more
information see Working-with-contexts
Example
function(msg, context) {
createMessage(msg, context.user);
}
validation
- Source:
- Since:
- 1.0.0
Properties:
| Name | Type | Description |
|---|---|---|
errorMessage |
string | A string with the error message shown to the user in case the validation isn't passed. |
validate |
function | The validation function, which follows these rules:
|
A validation is a single check that you want to perform on an user provided value before executing your command. If the validation isn't passed, the command won't be executed at all, and the user will receive an error informing them about the problem.
Type:
- object
Example
var myValidation = {
errorMessage: "The number must be between 1 and 100!",
validate: function (value) {
return value >= 1 && value <= 100;
}
};


Minutes for 2015-08-12
Venue brainstorming
Since we can’t use TSL, ideas for possible rooms:
- Brian’s room (though we want to avoid due to distruption - missing machines)
- Convergence lab (missing machines)
- Games lab (small, but has machines and is well speced)
- Psychology computer labs (great)
James to check on games lab, Siobhan to check on psyche lab.
Surveys
In the proposal, we focussed on the three Bowman metrics: user comfort, learnability and presence. Since we’re not doing VR, the idea of user comfort isn’t really relevant. James notes that presence is a bit of a nebulous measure, Siobhan says she’ll take some of the questions desired from a presence survey and send the relevant ones across.
In terms of general usability, Siobhan found two surveys: USE and SUS. Agreed that we will use SUS, in the interests of time. In terms of getting triangulation with qualitative feedback, Siobhan suggests using the presence questionnaire questions rephrased to be open ended.
Software
Steven demo’d his latest software responding to the heuristic feedback about task difficult. There are now three orientation matching models which have no colours and just wireframes. The inspection tasks now use concavity with colour rather than just colour.
James asks if the models are symmetric, as that would be problematic as that would mean there’s multiple correct orientations. We confirmed they aren’t. James and Brian both noted that the inspection model would be easy to get lost on, so some landmarks need to be added.
Stats consultancy
We are awaiting the results of this, due to the address on the consulting page being incorrectly specified. Steven will follow up.
Deliverables
- James: speak to Sonia and Patrick about Games Lab
- Siobhan: ask about using Psyche lab
- Siobhan: pick the questions for presence and send them through
- Steven (14/08/15): follow up on stats consulting


Learning New Build Systems
I do a lot of devops automation for work. This gives me a lot of opportunity to touch the build systems of many different languages. I have a professional background with Python, and a lot of experience building C/C++ with make.
I most recently got to play with Java/Maven, and NodeJS/Gulp.
--
The project I was building has a UI written in node, and built into an npm module with gulp. There are also maven pom files that describe the build with gulp using npm run build. This was done so everything could be orchestrated for building into a java jar.
Things I thought were neat about maven is the plugin system.
I'm not a huge fan of the pom files using xml, but it is really nice to be able to configure dependencies, and dynamically define build artifacts. The local maven repo is still a little confusing at times, but with more time I think it'll make more sense.
--
The UI build with gulp was more unfamiliar. The build instructions are in javascript, naturally. You can use gulp.task()
and define a list of dependencies. But I had some experiences where my dependency lists were not made explicit enough. I suppose this is not much different than makefiles.


{% extends "master.html" %} {% block title %} What is a CRS Report? {% endblock %} {% block head %} {% endblock %} {% block body %}
The Congressional Research Service is a legislative branch agency, housed inside the Library of Congress, charged with providing the United States Congress non-partisan advice on issues that may come before Congress. CRS creates a number of written work products, but generally speaking they are (1) CRS reports, (2) CRS general distribution memoranda, and (3) CRS memoranda. This website contains CRS reports only. Most reports are written at the initiative of a CRS analyst, although some reports can be prompted by a request from a staffer. Alas, the reports are not comprehensively published, which is why this website exists
CRS reports are published on CRS’s internal website and made are available by CRS to thousands of legislative staff, as well as to people in other branches of government and journalists on request. They are not classified, nor confidential, and routinely are made available to public as a matter of course. In fact, it’s the policy of the Senate to encourage its members to release the reports to the public.
CRS general distribution memoranda are also intended to general use, but they are not published on CRS’s website. Staffers must call up and ask for them. They do not contain classified material and they are not confidential. CRS memoranda are written at the request of an individual Member of Congress or staffer. They are considered confidential, and may be released to the public only by the Member of Congress who requested the document. They do not contain classified information.
Information in a CRS report should not be relied upon for purposes other than public understanding of information that has been provided by CRS to Members of Congress in connection with CRS’s institutional role.
More information than anyone could ever want about CRS and CRS reports is available on Daniel’s wiki page.
CRS reports are regularly revised by CRS staff. Sometimes there are major revisions to a report, other times it can be as trivial as adding a footnote and fixing a typo. Where possible, we indicate how much of a report has changed from its prior version so that users can know whether it’s worth re-reading. Ultimately, we would like to provide track changes so you can see exactly what has changed, but we aren’t there (yet).
CRS reports, as works of the United States Government, are not subject to copyright protection in the United States. Any CRS report may be reproduced and distributed in its entirety without permission from CRS. However, as a CRS report may include copyrighted images or material from a third party, you may need to obtain the permission of the copyright holder if you wish to copy or otherwise use copyrighted material.
{% endblock %}


It is alleged that, in 1993 Donald Trump raped a 13 year old girl, Katie Johnson, at an Epstein party in Manhattan. This accusation comes from the woman who says she was raped, along with TWO independent sworn affidavits with one being from a known Epstein employee! Don't believe me? Have a look:
There's another affidavit from a friend of Katie Johnson that swears Katie told her about the rape when it allegedly happened in 1993. Think this is fake news? Here, you can see the court documents all posted publicly at courtlistener.com
Trump is, and has always been a powerful man. He may have silenced Katie Johnson, and now he's trying to silence YOU by taking away your right to vote by mail. A right Americans have enjoyed since the Civil War. You can have your voice heard as an American though if you follow these basic steps:
Not from


Some content or other. This is pretty much fluff
More content because whatevs.
whatever indeed
some testing


Public loos to double up as sex cabins to 'improve' prostitutes' working conditions
Authorities in Berlin, Germany, say the move will give prostitutes along the Kurfürstenstrasse street better working conditions
by Bradley Jolly, https://www.mirror.co.uk/authors/bradley-jolly/Public toilets in Berlin will double as sex cabins for prostitutes in a bid to improve their working conditions.
But residents and politicians in the city have blasted the move as grotesque.
Two cabins are to be installed in a trial along Kurfürstenstrasse, the city's largest street prostitution area.
Each will have two doors to make it easier for prostitutes to leave if clients become abusive or violent.
"We know they have two functions. But the second function doesn't have to be pointed out," said one official.
But it is said prostitutes in the city are running out of secluded open-air spaces in which to work.

Michael Ruthenbeck, a member of a neighbourhood association, has called for Berlin to have an official red light district outside the city centre and away from residential areas.
He said: "These [new] measures won't help residents at all."
And local MP Marcel Luthe told the Berliner Zeitung newspaper: "The authorities in Berlin are merely organising crime instead of fighting human trafficking and forced prostitution."
However, groups campaigning for prostitutes have largely welcomed the decision.
But Olga, one of these groups, said it had hoped the cabins would be for sex only.
It was concerned that the cabins would be cleaned only once a day and would not have alarm buttons.
"We would have preferred cleaner and safer locations for the women," said Lonneke Schmidt-Bink, a member of the group.
Prostitution is legal in Germany and was recognised as a profession in 2002, allowing workers to register for social insurance.
Germany has an estimated 400,000 prostitutes. Most come from eastern European countries.


Application root
New application
Application infos
Application name
Application address
Application fees
Transaction fees
Locked
Total fees
Selected addrs:
create app
Applications


Analysis of Yelp 'Elite' reviewers in Toronto
For all the source material used, check out the GitHub respository
For the detailed analysis and Python 3 source code, check out the explainer-notebook
Introduction
Yelp is a company founded in 2004 that allows users of its website, Yelp.com, or its mobile app to review and rate businesses ranging from restaurants to home services. It has become extremely popular, with over 100 million unique users visiting its services per month during Q3 2018 and generating more than 171 million reviews. Businesses have profiles and can respond to reviews but cannot influence nor change the content of the reviews. Yelp recommends the reviews it deems best and most reliable and has become a strong influence on the success of restaurants [3].
Yelp’s goal is ‘to connect people with great local businesses.’ To better achieve this, they established the Yelp Elite Squad (YES), composed of the most avid of Yelp’s users. In order to join, an individual must be nominated and then selected, on the basis of a set of nondescript and subjective criteria. They must then maintain this status, as it only is guaranteed for a year [5].
Data Story and Aims of the Analysis
The purpose of our project is to supplement Yelp’s subjective description of the of an elite user with quantitative analysis. Yelp states that elite users are “people who are active in the Yelp community and role models” and that selection is based on “well-written reviews, high quality tips, a detailed personal profile, an active voting and complimenting record, and a history of playing well with others” [4]. There are not many further descriptions of what it takes to be selected as an elite user, and no specific quantitative thresholds or measures to meet.
The first aspect of our analysis attempts to quantify the description of elite users being “active in the Yelp community” and “playing well with others” [4]. To do so, we examine the role of elite users in the friendship network of Yelp. Yelp users can “friend” other users on the site and these connections can be modeled in a graph. We hypothesize that elite users will display a greater number of connections and a greater degree of centrality and importance in the graph, characteristics that reflect Yelp’s subjective description.
The second aspect of our analysis attempts to quantify aspects of the description that elite users have “well-written reviews” [4]. Although this is quite broad, we attempt to quantify some aspects of it by examining the sentiment expressed in the reviews as well as how the use of language differs. We hypothesize that elite users will use more descriptive and sophisticated language as well as show more measured emotion in their words.
For this project, the focus was on restaurants in Toronto as Toronto is a big city with more than a sufficient amount of data to perform a serious analysis, but small enough for various graph algorithms to be carried out. The reviews and users considered in this project were those pertaining to a restaurant in Toronto.
The Dataset Used
The dataset is a subset of the YELP dataset challenge 2018 dataset and contains YELP review data from the period 2004 to 2018, where the majority of the reviews are made in North America.
The datasets are split into 3, namely the review, user and restaurant dataset, which can be downloaded via the links below (right click, and select "Save link as"). The review dataset had to split into 4 subsets, in order for GitHub to host it, since individual file sizes may not exceed 100 MB.
Link(s) to Toronto review dataset
Link to Toronto user dataset: Full dataset
Link to Toronto restaurants dataset: Full dataset
Brief Overview for the Toronto Dataset
- Period: March 1st, 2008 to August 1st, 2018
- Reviews: ~380,000
- Users: ~95,000
- Elite users hereof: ~7500
- Restaurants: ~10,000
Prior Work
This analysis of elite users in the Yelp community is largely inspired by a technical report from Stanford [1] which investigated elite users in Phoenix, Arizona, and included, what they called, a ‘taste’ network which grouped Yelp users based on their taste in restaurants. Our analysis will not include this feature, but it will, however, draw from some of their points, such as investigating how big of a role the elite users play in the social network, as well in a network of Yelp reviews.
Yelp's Social Network in Toronto
Two users may choose to become on Yelp, for example, if they share interests. This feature is very analogous to that of the social network of Facebook, and even has the same limit on the number of friends each user can have, which is 5000.
A big part of this analysis involves analyzing the influence of Elite users in Yelp’s social network. A social graph was built from the review dataset, with all the users who left one or more reviews on a Toronto restaurant's Yelp page. These users were inserted in a network, as well as all the users appearing in their respective friendlists, and an edge was drawn between each pair of friends. The resulting network is an undirected social graph, with a total of 95,000 nodes and 380,000 edges. The size of the network meant that some of the algorithms took a considerable amount of time to run. An alternative to including all of the 95,000 nodes would be to only consider the nodes which had left a review in Toronto, even for the friendlist, which was also done but will in the groups opinion less success. The resulting network of including only friends who left a review in Toronto was a network with Nodes: 13,600 nodes and 9,400 edges.
Social Network Degree Distribution
The nodes of the social network all represent Yelp users, which are either regular users or Elite users. For understanding how the distribution of friends looks like, the degree distribution for all nodes, Elite nodes and regular user nodes was plotted. From the distributions it becomes apparent that a power law governs the number of friends of the Yelp users; an exponentially large part of the users have very few friends, and for the regular users this number is down to one single friend.
Tip: Use the arrows to navigate the plots
Tip: Use the arrows to navigate the plots
Centrality Measures for the Social Network
For understanding the roles of the nodes in the network, two centrality measures were used: degree centrality and eigenvalue centrality. The degree centrality speaks to how popular a node is in the network, in this case, how many friends a user has. The eigenvalue centrality represents how popular the friends of a particular node is, i.e. their friend count.
For the social network, these two measures are for the most part correlated, which makes intuitive sense since having more friends increases the chance of having popular friends.
Tip: Use the arrows to navigate the plots
Robustness Analysis
To quantify the influence of the Elite users in the social network, an experiment was conducted wherein a fraction of users corresponding to 1 percent of the Elite user base was removed in each iteration, until a number of users equal to the number of Elite users, was removed. The social network contained just under 7500 Elite users, meaning that 75 users were removed in each iteration. The largest connected component was calculated for each iteration, which tells us how many users are actually part of the social network, and those that were only connected to the social network via an Elite user which was removed will no longer be part of the largest connected component.
The figure tells us that by removing all Elite users from the network, the total number of nodes in the social network drops to around 65% of the original size, while only around 0.5% of the total number of nodes were removed. For removing regular users only, we see that the network size drops by around 4% after removing 7500 users, and for random users, i.e. a mix of both Elite and regular users, the resulting loss of network size is around 5%.
Robustness Analysis of the Smaller Social Network
The aforementioned smaller social network was also run through the robustness analysis, and the results were very analogous to those of the bigger network, except the smaller network was more susceptible to sudden huge losses in network size.
Yelp Review Network Analysis
A review is made when a user reviews a business, a business referring to a restaurant and other service places. A review contains a rating of 1 to 5 stars, as well as a written statement, which is used to clarify the given rating.
For our analyses, we aim to build a network of reviews and a social network of who are friends with who on Yelp, as well as analyze the review text to discern what, if any, differences exist between Elite and regular users as well as between reviews of different stars.
Review Degree Distribution
Tip: Use the arrows to navigate the plots
Very clear example of a power law, with the overwhelming majority of users having reviewed extremely few restaurants. Users are only included if they have in fact reviewed a restaurant in Toronto, meaning the spike is likely at 1 single review. The degree distribution for the Elite users in Toronto is unsurprisingly also a power law, with most users having left a single review. However, the distribution is somewhat less dense around one single review, compared to the review distribution for overall users. Below is shown the distrubtion, but on a logarithmic scale.
Tip: Use the arrows to navigate the plots
Eigenvalue Centrality for Toronto Restaurants
Tip: Use the arrows to navigate the plots
Concrete Differences in Ratings Between Elite- and Regular Users
Tip: Use the arrows to navigate the plots
Elite users are somewhat representative of the reviews made by all users, of which they make up a 38 percent. This means the data set is only reduced by less than a third, however, the user count is reduced from 95k to 7.5k. This may be useful if one were to perform trend analyses, and the task of tracking all users in the network was overwhelming - instead it would make a lot of sense to start looking at the Elite users, first and foremost.
Rating Distribution
The second component of our work was analyzing the text present in the reviews. As previously states, there are approximately 380,000 reviews of Toronto restaurants. These reviews are dated and thus we can determine if a user was Elite when they made a review. Before beginning with any text analysis, it is relevant to check how Elite and regular users differ in the distribution of the number of stars they award. If one assumes that most restaurants are in some middle tier, with some much better and some worse, we would expect to see a distribution resembling a bell curve.
As we can see, the Elite users mostly give four or three-star reviews, although the distribution is shifted to the higher reviews. In contrast, we notice that the regular users have a rating distribution more resembling an inverse bell curve. The highest fraction comes from five-star reviews and then it decreases down to two stars and finally rises slightly with one-star reviews having a greater fraction than two-star reviews. This may indicate, or conform to preconceived notions, that regular users are not as good at distinguishing mid-tier restaurants and are so skew their ratings higher or lower.
Review Text Analysis
Beginning our text analysis, we investigated how word choice compares between Elite and non-Elite users and across star ratings using TF-IDF scores. A TF-IDF (term frequency-inverse document frequency) score for a given word and the document is large if the word appears frequently in the document but infrequently across all documents. Thus, the higher the TF-IDF score, the more important and unique a word is to the specific document. The TF-IDF results are visualized in the generated word clouds.
Reviews by Elite-users
Figure: TF-IDF wordclouds for elite reviewers, for 1, 2, 3, 4, and 5 stars respectively.
Tip: Use the arrows to navigate the plots
Reviews by Regular Users
Figure: TF-IDF wordclouds for regular reviewers, for 1, 2, 3, 4, and 5 stars respectively.
Tip: Use the arrows to navigate the plots
As we can see, words of praise and negativity strongly associate with 5 star and 1 star reviews, respectively.
We also examined the length of the reviews written, excluding common English stopwords such as ‘as’, ‘the’, etc. There is clearly a slight downward trend, with lower ratings yielding longer reviews. The Elite users also clearly write more than the regular users, which makes sense given their status.
Sentiment Analysis
A sentiment analysis aims to determine the attitude of a speaker, writer, or other subject with respect to some document of words, where each word maps to a given sentiment score. For our sentiment analysis, the sentiment score used, was the labMT 1.0 dictionary, containing sentiment scores for over 10,000 words [2].
For the Yelp reviews, the sentiment score seems to be correlated with the review length, but what we are more interested in are the trends in review sentiment. Therefore, the reviews were partitioned on their average sentiment into three categories:
- Those below one standard deviation of the average sentiment
- Those above one standard deviation
- Those in between
Firstly, it appears that the low sentiment decreases and the high sentiment increases as the number of stars of a review increases, which is unsurprising given the previous word cloud analysis.
Furthermore, the above figure also reveals that the mid-tier sentiment decreases, which would indicated that high star reviews yield more extreme sentiment. However, there does not appear to be a significant difference between the sentiment per star when comparing the elite to the regular users. Thus, there do seem to be some global trends in sentiment, but the trends are global and don’t discriminate between the two user types.
Results and Conclusion
As stated earlier, the first goal of this project was to test Yelp’s claims about the characteristics of their Elite users. One claim that they made was that Elite users have high social connectivity. Our results validate this claim with reasonable confidence. On the social network, Elite users are greatly overrepresented among the top degree nodes: 57% of Elite nodes are in the top 20% of nodes in terms of degree. Also, the average degree of Elite nodes (8.58) is significantly higher than the network average (2.46). Another claim that they made is that Elite users contribute greatly to the site. Our results validate this claim with very high confidence. Elite users are greatly overrepresented among the top reviewers: about 80% of Elite users are in the top 20% of users in terms of reviews written. In addition, the average number of reviews written for Elite users is significantly higher than Yelp users as a whole (250 vs. 36).
The last claim we tested was that the Elite users make up the “heart of the Yelp community.” From both a social and taste perspective, our results also validate this claim with reasonable confidence. First of all, the robustness of the social network is much more affected by removing Elite nodes than random nodes (the size of the largest CC decreased more than twice as fast), which suggests that these Elite nodes are important for maintaining the structure of the social network. In addition, the Elite nodes are overrepresented among the top users in terms of being central to the graph (betweenness centrality), being an “important” node in the sense of having high PageRank, and also being directly connected to multiple communities. The fact that Elite nodes have much greater values for these properties than the network as a whole further substantiates the claim. In the taste network, though, removing Elite nodes had a much smaller effect on the robustness of the graph. This indicates that Elites are more vital to the social network than the taste network. However, Elites are still more important to the structure of the taste network than non-Elites. The importance of Elites were verified by our results for PageRank, betweenness centrality, and direct connectedness to communities. Elites were over-represented among the top percentiles for these three measures. In general, the values of these properties were significantly higher for Elites than non-Elites.
The second goal of our project was to determine which property was the most indicative of Elite status. As mentioned earlier, the Elite users were greatly overrepresented in the top reviewers on Yelp, much more so than for any of the other properties. In addition, Elite users post on average seven times as many reviews as the average user. This very strong association suggests that out of the properties we have measured, having a very large number of reviews is the best indication of Elite status. This conclusion implies that the number of reviews a user has written would likely be a good predictor of Eliteness. In addition, writing many reviews could be a good objective for those who are looking to become Elite.
References
[1] Crain, Heh, Winston (2014) An Analysis of the “Elite” Users on Yelp-.com, Stanford University, CA.
[2] Dodds PS, Harris KD, Kloumann IM, Bliss CA, Danforth CM (2011) Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter. PLoS ONE 6(12): e26752. https://doi.org/10.1371/journal.pone.0026752
[3] Yelp Inc. (2018) YES! Yelp Elite Squad. https://www.yelp.com/about
[4] Yelp Inc. (2018) What is Yelp's Elite Squad? https://www.yelp-support.com/article/What-is-Yelps-Elite-Squad?l=en_US
[5] Yelp Inc. (2018) YES! Yelp Elite Squad. https://www.yelp.com/elite
Authors
Thomas Nilsson (Danmarks Tekniske Universitet)
Asge Darr (Danmarks Tekniske Universitet)
Ronan Perry (Johns Hopkins University)


Classic Cocktails
Home
Spirits
Ingredients
Archive
Choose Your Ingredients
Liqour
Pick Your Poison
Gin
Whiskey
Vodka


Module: ActionView::Layouts
| Child Modules: | ClassMethods |
| Extended by: | ActiveSupport::Concern |
| Includes: | Rendering |
| Included in: | ActionMailer::Base |
| Defined in: |
Overview
Layouts reverse the common pattern of including shared headers and footers in many templates to isolate changes in repeated setups. The inclusion pattern has pages that look like this:
<%= render "shared/header" %>
Hello World
<%= render "shared/footer" %>
This approach is a decent way of keeping common structures isolated from the changing content, but it's verbose and if you ever want to change the structure of these two includes, you'll have to change all the templates.
With layouts, you can flip it around and have the common structure know where to insert changing content. This means that the header and footer are only mentioned in one place, like this:
// The header part of this layout
<%= yield %>
// The footer part of this layout
And then you have content pages that look like this:
hello world
At rendering time, the content page is computed and then inserted in the layout, like this:
// The header part of this layout
hello world
// The footer part of this layout
Accessing shared variables
Layouts have access to variables specified in the content pages and vice versa. This allows you to have layouts with references that won't materialize before rendering time:

<%= @page_title %>

<%= yield %>
…and content pages that fulfill these references at rendering time:
<% @page_title = "Welcome" %>
Off-world colonies offers you a chance to start a new life
The result after rendering is:

Welcome

Off-world colonies offers you a chance to start a new life
Layout assignment
You can either specify a layout declaratively (using the #layout
class
method) or give it the same name as your controller, and place it in
app/views/layouts
. If a subclass does not have a layout
specified, it inherits its layout using normal Ruby inheritance.
For instance, if you have PostsController and a template named
app/views/layouts/posts.html.erb
, that template will be used
for all actions in PostsController and controllers inheriting from
PostsController.
If you use a module, for instance Weblog::PostsController
, you will need
a template named app/views/layouts/weblog/posts.html.erb
.
Since all your controllers inherit from ApplicationController, they will
use app/views/layouts/application.html.erb
if no other layout
is specified or provided.
Inheritance Examples
class BankController < ActionController::Base
# bank.html.erb exists
class ExchangeController < BankController
# exchange.html.erb exists
class CurrencyController < BankController
class InformationController < BankController
layout "information"
class TellerController < InformationController
# teller.html.erb exists
class EmployeeController < InformationController
# employee.html.erb exists
layout nil
class VaultController < BankController
layout :access_level_layout
class TillController < BankController
layout false
In these examples, we have three implicit lookup scenarios:
-
The BankController uses the “bank” layout.
-
The ExchangeController uses the “exchange” layout.
-
The CurrencyController inherits the layout from BankController.
However, when a layout is explicitly set, the explicitly set layout wins:
-
The InformationController uses the “information” layout, explicitly set.
-
The TellerController also uses the “information” layout, because the parent explicitly set it.
-
The EmployeeController uses the “employee” layout, because it set the layout to nil, resetting the parent configuration.
-
The VaultController chooses a layout dynamically by calling the
access_level_layout
method. -
The TillController does not use a layout at all.
Types of layouts
Layouts are basically just regular templates, but the name of this template needs not be specified statically. Sometimes you want to alternate layouts depending on runtime information, such as whether someone is logged in or not. This can be done either by specifying a method reference as a symbol or using an inline method (as a proc).
The method reference is the preferred approach to variable layouts and is used like this:
class WeblogController < ActionController::Base
layout :writers_and_readers
def index
# fetching posts
end
private
def writers_and_readers
logged_in? ? "writer_layout" : "reader_layout"
end
end
Now when a new request for the index action is processed, the layout will vary depending on whether the person accessing is logged in or not.
If you want to use an inline method, such as a proc, do something like this:
class WeblogController < ActionController::Base
layout proc { |controller| controller.logged_in? ? "writer_layout" : "reader_layout" }
end
If an argument isn't given to the proc, it's evaluated in the context of the current controller anyway.
class WeblogController < ActionController::Base
layout proc { logged_in? ? "writer_layout" : "reader_layout" }
end
Of course, the most common way of specifying a layout is still just as a plain template name:
class WeblogController < ActionController::Base
layout "weblog_standard"
end
The template will be looked always in app/views/layouts/
folder. But you can point layouts
folder direct also.
layout "layouts/demo"
is the same as layout
"demo"
.
Setting the layout to nil forces it to be looked up in the filesystem and fallbacks to the parent behavior if none exists. Setting it to nil is useful to re-enable template lookup overriding a previous configuration set in the parent:
class ApplicationController < ActionController::Base
layout "application"
end
class PostsController < ApplicationController
# Will use "application" layout
end
class CommentsController < ApplicationController
# Will search for "comments" layout and fallback "application" layout
layout nil
end
Conditional layouts
If you have a layout that by default is applied to all the actions of a
controller, you still have the option of rendering a given action or set of
actions without a layout, or restricting a layout to only a single action
or a set of actions. The :only
and :except
options can be passed to the layout call. For example:
class WeblogController < ActionController::Base
layout "weblog_standard", except: :rss
# ...
end
This will assign “weblog_standard” as the WeblogController's layout for
all actions except for the rss
action, which will be rendered
directly, without wrapping a layout around the rendered view.
Both the :only
and :except
condition can accept
an arbitrary number of method references, so #except: [ :rss,
:text_only ] is valid, as is except: :rss
.
Using a different layout in the action render call
If most of your actions use the same layout, it makes perfect sense to
define a controller-wide layout as described above. Sometimes you'll
have exceptions where one action wants to use a different layout than the
rest of the controller. You can do this by passing a :layout
option to the render
call. For example:
class WeblogController < ActionController::Base
layout "weblog_standard"
def help
render action: "help", layout: "help"
end
end
This will override the controller-wide “weblog_standard” layout, and will render the help action with the “help” layout instead.
Instance Method Summary collapse
-
#action_has_layout? ⇒ Boolean
Controls whether an action should be rendered using a layout.
Methods included from ActiveSupport::Concern
append_features, class_methods, .extended, included
Methods included from Rendering
#process, #render_to_body, #rendered_format, #view_context, #view_context_class, #view_renderer
Methods included from ViewPaths
#_prefixes, #append_view_path, #details_for_lookup, #lookup_context, #prepend_view_path
Instance Method Details
#action_has_layout? ⇒ Boolean
Controls whether an action should be rendered using a layout. If you want
to disable any layout
settings for the current action so that
it is rendered without a layout then either override this method in your
controller to return false for that action or set the
action_has_layout
attribute to false before rendering.
364 365 366
# File 'actionview/lib/action_view/layouts.rb', line 364 def action_has_layout? @_action_has_layout end


You ever notice that about pages are almost worthless and say only things like version 2.3.43.
About my portfolio
This is designed to be an e-portfolio. An electronic version of the standard portfolio if you catch my drift. It better helps to demonstrate programming code for perspective employers, clients, etc.. Hopefully it helps you to get a good feel of my tanlents and potential talents.
About me
Me, well I am currently a student at the OWATC. I am in the process of getting a software development and web design certificates. When I have finished this process I hope to find a job that allows me to stretch my creative and intellectual muscles.
Below you will find a button written in javascript to add a little fun to my about page. Click it and enter a color name to see what happens.


---
title: |
Ladder Bookshelf & Writing Desk
year: 2017
description: Sun-tanned poplar, walnut, and brass pins.
---
{% include resimg.html src="bookshelf/joint.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-level.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-rear.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-side.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/detail-front.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/detail-top.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-joint.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-bottom.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-open.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/full-vert.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/surface.jpg" class="with-viewer" %}
{% include resimg.html src="bookshelf/drawer-top.jpg" class="with-viewer" %}


Co-founder of Orlando Magic announces plan for MLB team
by WFTS Digital StaffORLANDO, Fla. --- Pat Williams, co-founder of the Orlando Magic, announced an effort to bring an MLB team to Orlando.
Williams revealed the team would be named the Dreamers, according to the team's website . It will be named the Dreamers after the visionaries who helped develop the area, like Walt Disney and Arnold Palmer.
The plan was announced on Wednesday to get community support from Central Florida baseball fans. The plan is similar to the one he made in the 1980s to get the Orlando Magic started.
Williams is hoping the community will rally behind the MLB team by going to their website .
Those interested in the team will get ticket information before it goes public, according to the website.


The cost function used in Linear Regression is the LMS Function. In the Matrix form, this function is: \[ J(\theta) = \frac{1}{2m}(X\theta - \vec{y})^{T}(X\theta - \vec{y}) \] In Normal form, this function is \[J(\theta) = \frac{1}{2m} \sum_{i=1}^{m}(h_{\theta}(x^{(i)}) - y^{(i)})^2\]


Collection :
Description :
Total run duration:
Total data received:
Average response time:
Executed Time :
JPT_Automation_Verison_Mgmt
This is a sample API testing collection to validate the API test automation
1221ms
1.16KB
115ms(approx)
Thu May 09 2019 15:18:05 GMT-0400 (Eastern Daylight Time)
|
|
Total | Failed |
|---|---|---|
| Iterations | 4 | 0 |
| Requests | 8 | 0 |
| Prerequest Scripts | 8 | 0 |
| Test Scripts | 8 | 0 |
| Assertions | 16 | 4 |
Name : http://localhost:8082/rel?nAppId=1
| Passed | Fail |
|---|---|
| 8 | 0 |
| Name | Pass count | Fail count |
|---|---|---|
| response is ok | 4 | 0 |
| returns valid Front End Version | 1 | 0 |
| returns valid API Version | 1 | 0 |
| returns valid release Version | 2 | 0 |
Name : https://jsonplaceholder.typicode.com/posts/1
| Passed | Fail |
|---|---|
| 4 | 4 |
| Name | Pass count | Fail count |
|---|---|---|
| Status code is 200 | 4 | 0 |
| Valid UserId & PostId Returned. User Id: 1 Post Id:1 | 0 | 4 |


{#include base.html} {#title}Fight Between {game.playerOne.name} and {game.playerTwo.name} deck {game.deck.id}{/title} {#body}


Recent updates
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This is a wider card with supporting text below as a natural lead-in to additional content. This content is a little bit longer.
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Hey Everyone Here is Raneem Abdulaziz and here is about me page!
Education
- Software develpment from Abdulaziz Alghurir School for advanced Computing
- Commuincations and Electronics Engineering form Philadelphia University
Experience
- Robotics Coach at Bright Engineers
- Volunteer at Noor Alhussien
Hobbies
- playing chess
- swimming
TOP 10 food for me
- pizza
- pasta
- Chicken
- Eggs
- Wild Salmon
- Oatmeal
- Watermelon
- Leafy Greens
- Lean beef
- Oats


Pro Finance
Cover Management Solution
Home
Admin
Employees
Employees
Admin
Employee Details
Personal Details
Physical Address
Postal Address
Contact
Banking
Dashboard
Branch Code
{% for branch in branches %} {% if vstrBranchCode == branch.strCompanyBranchCode %}
{{ branch.strCompanyBranchCode }}
{% else %}
{{ branch.strCompanyBranchCode }}
{% endif %} {% endfor %}
Employee Code
Employment Contract
{% if vstrContractType == "Permanent" %}
Permanent
{% else %}
Permanent
{% endif %} {% if vstrContractType == "Temporary" %}
Temporary
{% else %}
Temporary
{% endif %} {% if vstrContractType == "Affiliate" %}
Affiliate
{% else %}
Affiliate
{% endif %}
Basic Salary
Date of Employment
Title
{% if vstrTitle == "MR" %}
MR
{% else %}
MR
{% endif %} {% if vstrTitle == "Mrs" %}
Mrs
{% else %}
Mrs
{% endif %} {% if vstrTitle == "Miss" %}
Miss
{% else %}
Miss
{% endif %}
Fullnames
Surname
ID Number
Date of Birth
Nationality
Physical Address Line 1
Physical Address Line 2
City/Town
Province
Postal Code
Box
City/Town
Province
Postal Code
Cell
Tel
Email
Account Holder
Bank Name
Account Type
Savings
Cheque
Transmission
Account Number
Branch Code
Delete Employee
{% if vstrSuspendOnPay == 'True' or vstrSuspend == 'True' %}
Stop Suspension
{% else %}
Suspend Employee
{% endif %} {% if vstr24HourLock == 'True' or vstrLockIndefinite == 'True' %}
Remove Employee Lock
{% else %}
Lockout Employee
{% endif %}
Lock Funeral Cover Form
Send Message
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Save
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This Will Delete The Present Employee Record
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This Will Suspend The Present Employee Record
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Lockout Employee
This Will Lock ALL System Access for this Employee Until Unlocked
×
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Create Employee Task
Used to send Tasks to Employees
Quick Task
×
Close
Send Messages
Used to send messages to employees
Quick Email
×
Close
Lock Funeral Cover
Use this Dialog to Lock Access to the Funeral Cover Editor for Employee
Quick Lock
24 Hour Lock
12 Hour Lock
Lock indefinitely


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MEET connects, educates and empowers the next generation of young Israeli and Palestinian socially minded entrepreneurs to make a positive social and political impact in the Middle East.
MEET is a registered not-for-profit organization with innovation hubs in Jerusalem and Nazareth.


An overview of the hosts, server groups and servers defined in your domain with the server groups as columns and the hosts as rows. The servers are displayed according to their status: error or timed out, needs reload / restart, suspended, up and running and stopped or disabled.
Click on a host, server group or server to see additional information or execute operations.
| Server Groups → Hosts ↓ |
development | staging | qa-server-group-used-for-testing-our-applications | production |
|---|---|---|---|---|
| master | ||||
| slave1 | ||||
| slave2-which-contains-lots-of-servers-with-all-kind-of-states | ||||
| slave3 |


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L
L_DATA
(in
mmLib.CIF
)
library_is_nucleic_acid()
(in
mmLib.Library
)
load_file()
(in
CIFFile
)
L_EOF
(in
mmLib.CIF
)
library_is_standard_residue()
(in
mmLib.Library
)
load_file()
(in
PDBFile
)
L_GLOBAL
(in
mmLib.CIF
)
library_is_water()
(in
mmLib.Library
)
load_file()
(in
mmCIFFile
)
L_LOOP
(in
mmLib.CIF
)
library_open_monomer_lib_directory()
(in
mmLib.Library
)
load_sequence()
(in
StructureBuilder
)
L_SAVE
(in
mmLib.CIF
)
library_open_monomer_lib_file()
(in
mmLib.Library
)
load_sites()
(in
StructureBuilder
)
L_STOP
(in
mmLib.CIF
)
library_open_monomer_lib_zipfile()
(in
mmLib.Library
)
load_structure_id()
(in
StructureBuilder
)
L_TAG
(in
mmLib.CIF
)
library_use_monomer_zipfile()
(in
mmLib.Library
)
load_supported()
(in
TLSFileFormat
)
L_VALUE
(in
mmLib.CIF
)
LINK
(in
mmLib.PDB
)
load_supported()
(in
TLSFileFormatPDB
)
left_shift
(in
mmLib.NumericCompat
)
load()
(in
TLSFile
)
load_supported()
(in
TLSFileFormatPHENIX
)
length()
(in
mmLib.AtomMath
)
load()
(in
TLSFileFormat
)
load_supported()
(in
TLSFileFormatPHENIXOUT
)
less
(in
mmLib.NumericCompat
)
load()
(in
TLSFileFormatPDB
)
load_supported()
(in
TLSFileFormatPureTLSOUT
)
less_equal
(in
mmLib.NumericCompat
)
load()
(in
TLSFileFormatPHENIX
)
load_supported()
(in
TLSFileFormatTLSOUT
)
Lexer
(in
mmLib.CIF
)
load()
(in
TLSFileFormatPHENIXOUT
)
load_unit_cell()
(in
StructureBuilder
)
Library
(in
mmLib
)
load()
(in
TLSFileFormatPureTLSOUT
)
LoadStructure()
(in
mmLib.FileIO
)
library_construct_element_desc()
(in
mmLib.Library
)
load()
(in
TLSFileFormatTLSOUT
)
log
(in
mmLib.NumericCompat
)
library_construct_monomer_desc()
(in
mmLib.Library
)
load_alpha_helicies()
(in
StructureBuilder
)
log10
(in
mmLib.NumericCompat
)
library_get_element_desc()
(in
mmLib.Library
)
load_atom()
(in
PDBStructureBuilder
)
logical_and
(in
mmLib.NumericCompat
)
library_get_monomer_desc()
(in
mmLib.Library
)
load_atom()
(in
StructureBuilder
)
logical_not
(in
mmLib.NumericCompat
)
library_guess_element_from_name()
(in
mmLib.Library
)
load_beta_sheets()
(in
StructureBuilder
)
logical_or
(in
mmLib.NumericCompat
)
library_is_amino_acid()
(in
mmLib.Library
)
load_bonds()
(in
StructureBuilder
)
logical_xor
(in
mmLib.NumericCompat
)
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Python Macromolecular Library
Generated by Epydoc 3.0.1 on Mon Jun 27 14:43:13 2011
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Requires the comments plugin.
This plugin comes with Pyblosxom. To install, do the following:
Add Pyblosxom.plugins.akismetcomments to the load_plugins list in your config.py file.
Install the akismet library. You can get it at http://www.voidspace.org.uk/python/modules.shtml#akismet
Set up a Wordpress.com API key. You can find more information from http://faq.wordpress.com/2005/10/19/api-key/ .
Use this key to put put the following line into your config.py file:
py['akismet_api_key'] = 'MYKEYID'
Add $(comment_message) to the comment-form template if it isn’t there already.
When akismetcomments rejects a comment, it’ll populate that variable with a message explaining what happened.
This plugin merges the work done on the akismetComments.py plugin by Blake Winton with the the akismet.py plugin by Benjamin Mako Hill.
Plugin is distributed under license: GPLv2
acronyms - Marks acronyms and abbreviations in...
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{% extends 'admin/my_base.html' %} {% block body %} {% if form %}
Here definitions for clades need to be provided, along with newick trees to show on the website. This needs to be done as a JSON object. For each clade (containing at least one species), the included species need to be provided as an array of their codes.
{ "Arabidopsis": { "species": ["ath"], "tree": null }, "Poplar": { "species": ["ptr"], "tree": null }, "Rice": { "species": ["osa"], "tree": null }, "Rosids": { "species": ["ptr", "ath"], "tree": "(ptr:0.01, ath:0.01);" }, "Angiosperms": { "species": ["ptr", "ath", "osa"], "tree": "((ptr:0.03, ath:0.03):0.01, osa:0.04);" } }{% endif %} {% endblock %} {% block tail %} {{ super() }} {% endblock%}


C:\Windows\System32\eula.txt Will show at the top
C:\Windows\inf\layout.inf Will show at bottom (cdname/productname)
C:\Windows\System32\license.rtf Originally installed OS
Grab any executable and check it's properties:
4.x: NT 4.x
5.0: Windows 2000
5.1: Windows XP
5.2: Windows 2003 Server or Windows XP-64-bit
6.0: Windows Vista
6.1: Windows 7
6.2; Windows 8
6.3: Windows 8.1
This does not however tell you which flavor of those systems (Pro, Home, etc).


Wetator / Anchor Inside Page
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Pferde fressen keinen Gurkensalat.
Chapter 2
Esel fressen auch keinen Gurkensalat.
Tests
jump to 'Chapter 1'
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jump to duplicate anchor
open popup and jump to 'Chapter 1'
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Technical Metadata
Security (Concerns)
Metamodel Specification
Revised Metamodel Overview
FMDR Grammar
Minimum Viable Product (MVP) : Implementation
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Search through a gallery of my past work, or check out my instagram for updates on the latest content.
@kenna.customs Starwars Custom Shoes ##fyp ♬ drivers license x ocean eyes - carneyval
Starwars Custom Shoes ##fyp ♬ drivers license x ocean eyes - carneyval


Gregory W Shirk
Democrat
Management Analyst Team Lead, US Food and Drug Administration; Statistician, US Food and Drug Administration; Industrial Engineer, MAI; Consultant, The Beacon Group
BS in Industrial Engineer, MS in Applied Economics
80205
Joe Biden, Elizabeth Warren
As a member of the LGBTQIA+ community I endeavor to learn about the issues affecting my community and ways we can make political change to create a more safe, inclusive and caring environment.
It is important that the people of Colorado feel their voices are heard at all legislative levels. A key component of this is ensuring the legislative and congressional district maps are fairly and consistently drawn. To achieve this we must reflect Colorado's racial, ethnic, gender, and geographic diversity. I seek to serve on the commission to provide my expertise and work toward these goals.
It's critical to get input from a diverse set of perspectives in an undertaking as large as this. I think there's a distinct benefit to having different approaches to solving a problem because there is no one right way and that a collaborative approach yields the strongest outcome. I strongly believe even if we have differing political view, when working in good faith and begin fair to all viewpoints we can achieve our objective.
As a Statistician at the FDA my job is to take complex data sets and dispersed information and distill it down to provide clear analyst and conclusions that are consumable for my audience. Recently I led my office's reorganization of 5000 staff members across the country into 6 specialized commodities based on staff proficiency, national workloads and financial constraints. And while I primarily rely on my quantitative analysis, I recognize this task also requires considerations of qualitative inputs too to successful solve complex problems.
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I'm Miguel Ocampo-Gooding.
I'm currently working as a front-end developer at The Pixel Shop Flixel
You can reach me at<EMAIL_ADDRESS>I'm also over on Github, Twitter, and Linkedin.


Lebesgue integral
The Lebesgue integral applies to a much wider class of functions than the Riemann integral (but there are riemann-integrable functions that are not lebesgue-integrable)
and is better behaved with respect to pointwise convergence.
The Riemann integral is predicated on the idea of breaking up the domain of the function \(f\).
By contrast, the Lebesgue integral is predicated on the idea of breaking up the range of the function \(f\).
Since Lebesgue's original exposition a number of different approches to the theory have been discovered,
some of them having attractions of simplicity or generality. It is possible to arrive
quickly at the integral without any stress on the idea of measure.


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Recreating Straits
Straits is a chess-like game created by Anne Marriott Watson and patented in 1893 (now in the public domain). Not much is known about Anne Marriott Watson other than what is in the first paragraph of the patent:
“Be it known that I, Anne Marriott Watson, a gentlewoman, a subject of the Queen of Great Britain, residing at Parkins’ Land, Eastleigh, Southampton, in the county of Hants, England, have invented a new or Improved Game, or which the following is a specification.”
I discovered Straits perusing boardgamegeek.com and was immediately fascinated by the hourglass shaped board and pieces.
The rules are fairly simple and there are only 4 types of pieces.
- 1 Flag ship - moves like queen in chess (figure 2).
- 7 Turret ships - moves like a rook in chess (figure 3).
- 8 Torpedo boats - moves like a bishop in chess (figure 5).
- 3 Gun boats - (a pawn-like piece) moves 1 square any direction but can only capture diagonally (figure 4).
The winning condition is to either move your Flag ship into the center square or checkmate the other player’s Flag ship.
With a desire to recreate this game, I started modeling the pieces in Tinkercad so that I could 3D print them.
It was this process where I started noticing some interesting similarities with the piece’s chess counterparts. For example, the Gun boat with its sphere top resembles a pawn. The Flag ship is a tallest piece which makes it easy to remember as the most important. The Turret ship with it’s cylindrical flat top looks almost like a rook piece. And finally the Torpedo comes to a point at the top much like a bishop. It’s impossible to say if these designs were done this way intentionally. But I can imagine a game designer thinking of a way to provide visual clues to remember how each piece moves. In fact, this is how I remember when playing the game.
Next, I needed the board. I did a quick sketch using Excalidraw. It does the job, but at some point I would love to have a nicer looking board.
With the pieces and board printed, I was able to play a few rounds and really enjoyed it! Before discovering Straits, I had no idea who Anne Marriott Watson. Recreating her game almost felt like a journey of getting to know her. It’s amazing to think that this game may not of been played in over 100 years, but with a little curiosity and modern day technology, I was able to bring it back from the forgotten depths of expired patents.
Feel free to grab all the files from the Straits BoardGameGeek page. I hope you enjoy it as much as I did.


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Man braid celiac synth twee, ennui pork belly butcher jean shorts try-hard you probably haven't heard of them air plant crucifix. Meggings blue bottle meditation, gluten-free tofu roof party vexillologist tacos succulents sustainable hammock 3 wolf moon synth. Venmo pop-up vape, kale chips letterpress banh mi hot chicken. Messenger bag austin waistcoat brunch fashion axe. Freegan lo-fi godard fashion axe stumptown tumeric. Pabst crucifix whatever master cleanse, occupy poutine umami plaid narwhal 8-bit chia truffaut.


With the entire campus and beyond being abuzz with excitement we are sure that all of you have registered and are super excited to participate in Virtual Stock Simulation. Pantheon' 18 puts an end to your wait as the real game is about to begin.  Last but not the least, the most important rule to be followed is BET HARD>>>GAIN HARD. So venture forth in the world of virtual trading and show off your flair in handling the stock market affairs before the game ends on 5th October, 2018.
1. Go to https://www.marketwatch.com/game/vss-pantheon18
2. The password for VSS is: pantheontrade
3. If you aren’t registered on MarketWatch, then register yourself using FB, GMail Account or creating a new one.
4. Once you are registered, click on TRADE NOW!
5. Enter the name/symbol of the company you wish to invest on (though Symbols are more precise and fast. Example: WMT for Walmart).
6. Further details and instructions are explained in the following video about the basics of VSS on MarketWatch: https://youtu.be/epxncLNeoDk
7. If you have earlier played a game on MarketWatch, you may need to switch the game to the VSS Pantheon18 by going to the Games menu.
Remember : that the timings of NYSE in India are 7:00 pm to 1:30 am. So you can trade anytime between these trading hours. The market remains closed on weekends.
Rahul –<PHONE_NUMBER>


Be a thinker, be a Do-er, be a Donor, you could change 9 lives. This website is to inform all people that we need to help each other to fight against novel corona virus disease, especially at this kind of crisis and in any calamity.
Currently v1.1.2 BETA
Land, air, and sea travel of uniformed personnel for official business, especially those transporting medical supplies, laboratory specimens, related to COVID-19, and other humanitarian assistance, shall be allowed.
For more infoThe Philippine leader spent a good portion of the three minutes allotted to him talking about COVID-19 vaccines, urging APEC members to "ensure the unimpeded flow of medical supplies and technologies."
For more infoHow should I greet another person to avoid catching new
coronavirus?
To prevent COVID-19 it is safest to avoid physical
contact when greeting. Safe greetings include a wave, a nod, or a bow.
Most people who become ill with COVID-19 will be able to recover at home. Some of the same things you do to feel better if you have the flu getting enough rest, staying well hydrated, and taking medications to relieve fever and aches and pains also help with COVID-19.
COVID-19 (more specifically, a coronavirus) is the disease identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China.
People with COVID-19 have had a wide range of symptoms reported ranging from mild symptoms to severe illness. Symptoms may appear 2-14 days after exposure to the virus. People with these symptoms may have COVID-19:


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AFFORDABLE PARIS TOURS
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Contains a general model for code completion which will be usable for
Generated - see
Gradle DSL xml structure
Maybe a bridge to Java and Groovy parts as well


MigLayout is a Layout Manager for Swing and SWT created to replace all current layout managers and introduces a very easy to understand yet powerful syntax that resembles CSS.
This is the first posting in a series that will introduce MigLayout and show how easy it is to use.
If you want to start using MigLayout, just head over to www.miglayout.com and everything is there for you, including more examples. Miglayout is 100% free and Open Source (BSD).
The simplest mode of operation is the default grid-like layout. Every component added to the container ends up in the next cell, which by default is to the right. When you want to wrap to the next line just add a "wrap" and the next component will be on the next line. A lot can be configured and tweaked but for the most part it just works.
For instance the code below produces the panels in the screen shots. Note that the white spacing is larger on OS X, just as is recommended by the OS X style guide. You don't have to think about this, MigLayout does that for you.
JPanel panel = new JPanel(new MigLayout());
panel.add(new JLabel("First Name"));
panel.add(new JTextField(15));
panel.add(new JLabel("Surname"), "gap unrelated"); // Unrelated size is resolved per platform.
panel.add(new JTextField(15), "wrap"); // Wraps to the next row in the grid.
panel.add(new JLabel("Address"));
panel.add(new JTextField(), "span, growx"); // Spans the rest of the cells in the row
// and grows to fit that space.


05 September 2001
Disease Outbreak Reported
As of 4 September, WHO has reported a total of 3557 cases, including 113 deaths, with a case-fatality rate of 3.2% in the south-western part of the country.
Please note that the increase in the total number of cases (1099) from the last report on 21 August does not necessarily indicate that the increase occurred during this two-week period. Rather, it is the result of late reporting of data.
The Ministry of Health, with the assistance of WHO and Médecins sans Frontières, is continuing its surveillance efforts.
There is an ongoing outbreak of cholera across Chad's border, in the northern part of Cameroon. The Ministry of Health of Cameroon has reported a total number of 158 cases, including 3 deaths.


Study sets are a way of managing groups of features. The study sets can be accessed by opening the StudySet window from the Window menu.
What can I do with my study sets?
Right-clicking any study set will bring up the available options to analyze and
view the details that study set.
Once a detail view is opened, the view can be updated by selecting other study
sets.
Creating a study set:
Study sets can be created in the Parallel Sets view. A set can be created in the
Parallel Sets view by right-clicking a ribbon.


Rune 2 PC Performance Analysis
by John PapadopoulosRagnarok Game released last week Rune 2 on the PC platform. As we’ve already said, this is timed-exclusive on the Epic Games Store and its development team has closed down. While Ragnarok Game is currently looking to build a new team that will support the game, it’s time to benchmark it and see how it performs on the PC platform.
For this PC Performance Analysis, we used an Intel i9 9900K with 16GB of DDR4 at 3600Mhz, AMD’s Radeon RX580 and RX Vega 64, NVIDIA’s RTX 2080Ti, GTX980Ti and GTX690. We also used Windows 10 64-bit, the GeForce driver 441.20 and the Radeon Software Adrenalin 2019 Edition 19.11.2 drivers. NVIDIA has not included any SLI profile for this title, meaning that our GTX690 performed similarly to a single GTX680.
Human Head Studios has added a few graphics settings to tweak. PC gamers can adjust the quality of Anti-aliasing, Post-Process, Shadows and Textures. There are also options for View Distance, Foliage and Effects. Furthermore, the team has added a Field of View slider and a Resolution Scale option.
Rune 2 does not have any built-in benchmark tool. As such, we’ve benchmarked the game’s starting area. Rune 2 uses Unreal Engine 4 and only supports DirectX 11. Thankfully, though, the game does not require a high-end CPU.
In order to find out how the game scales on multiple CPU threads, we simulated a dual-core, a quad-core and a hexa-core CPU. And we are happy to report that even our simulated dual-core system was able to offer a 60fps experience. Now the reason I’m saying “60fps experience” is because the game is locked at 60fps. Unfortunately, we could not unlock the framerate from its .ini file.
While our average framerate was at 60fps, we did notice some stuttering issues. This is something from which a lot of Unreal Engine 4 games suffer, and Rune 2 is no exception to it. These stutters occur when the game is loading new areas, similarly to the stutters of Star Wars Jedi: Fallen Order.
Moreover, Rune 2 appears to be running great on older CPUs. Our Intel i7 4930K was running the game similarly to the Intel i9 9900K. As such, owners of older PC systems will not encounter any CPU limitation.
Contrary to its CPU requirements, Rune 2 requires high-end GPUs. Seriously, this game is perhaps the most GPU demanding title we’ve seen in 2019.
At 1080p/Cinematic settings, the only GPU that was able to offer a 60fps experience was the NVIDIA GeForce RTX2080Ti. The AMD Radeon RX580 was running the game with 25fps, whereas the AMD Radeon RX Vega 64 could push an average of 45fps. So yeah, don’t expect to be running the Cinematic settings on anything other than the latest and fastests GPUs.
Thankfully, the game can scale on older graphics cards. For instance, we were able to run the game with constant 60fps at 1080p/High on the AMD Radeon RX580. Therefore, we strongly suggest using the High settings (with Cinematic Textures) on most GPUs. The only downside here is that you’ll then have a lot of pop in issues with grass and foliage.
At 1440/Cinematic settings, our NVIDIA GeForce RTX 2080Ti was unable to offer a 60fps experience. As for 4K/Cinematic, the AMD Radeon RX Vega 64 was running the game with 6fps. Oh, and the NVIDIA GeForce RTX2080Ti was pushing 18fps. Let that sink in. 6fps on the Vega 64 and 18fps on the RTX2080Ti. Ouch.
Graphics wise, Rune 2 looks great but it unquestionably does not justify its enormous GPU requirements on Cinematic settings. For the most part, Human Head Studios has used a lot of high-resolution textures. There are some low-res textures here and there, and you will notice some texture alignments issues. The main character is highly detailed and the environments are rich with foliage and grass. Speaking of foliage, players can bend all bushes and grass blades, thus giving the game a more dynamic feeling to it. So yeah, while the game does not justify its huge GPU requirements, it can still look great… at least for a current-gen title.
All in all, Rune 2 is a mixed bag. On one hand, it can run really smooth on older CPUs. On the other hand, its Cinematic settings do not justify their GPU requirements. Thankfully, PC gamers can improve performance by lowering their settings to Epic or High. Unfortunately, there are A LOT OF pop in issues on High settings, so that’s something that will disappoint a lot of PC gamers. So yeah, Rune 2 definitely needs a performance optimization patch.
Enjoy!


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 8
Dietary
These flavoursome aubergines are the perfect accompaniment to sweet or fruity main courses.
Heat two tablespoons of the oil in a frying pan over a medium heat. Add the chopped onions, garlic and peppers and fry in the oil, stirring well, until softened, about 3-4 minutes.
Meanwhile, heat the remaining oil in a sauté pan or casserole and fry the aubergine cubes, in batches, for 4-6 minutes, or until golden-brown all over. Remove from the pan using a slotted spoon and set aside on a warmed plate. Repeat the process with the remaining batches of aubergine cubes.
Stir the hot paprika, sweet paprika and cumin into the onion mixture and cook for one minute, or until the spices are fragrant. Add the canned tomatoes, sugar and cooked aubergines, and season, to taste, with salt and freshly ground black pepper.
Pour 350ml/12½fl oz water into the pan, stir well and bring to the boil, then reduce the heat until the mixture is simmering. Simmer for 15-20 minutes, or until the mixture has thickened and is cooked through.
Serve the Creole aubergines sprinkled with chopped parsley and garnished with wedges of lime.


Press any letter key (a-z) to get started! Wins: Losses: Guesses remaing: Word to Guess: Letters already guessed: Click for a Hint


This test checks if doing a var define in a module file is hoisted and if it causes any problems in a way that would shadow the real define.
Check the console for output
If you see "BAD DEFINE" in the output, then it means there is a problem, and the real define was shadowed by something else.


//This html page is currently depreciated. It doesn't go anywhere or do anything, or included in the router directory. //You can safely ignore it!


Battery indicator
Install app on device
Lightning Bolt
designed by
Frontera Taller de Arquitectura
from The Noun Project.


Weight initialization
Zero initialization
- \(W = 0\)
- never used
- all neurons will react the same way
- learn the same function
- output the same gradient
- update in the same way
Random initialization
- \(W = 0.01 * np.random.randn(n^{[l-1]},\ n^{[l]})\)
- small random numbers; gaussian with zero mean and \(1\mathrm{e}^{-2}\) standard deviation
- works okay for small networks
- problems with deeper networks
- standard deviation drops to zero
- activations become zero
- no update
Xavier initialization
- \(W = \frac{np.random.rand(n^{[l-1]},\ n^{[l]})}{np.sqrt(n^{[l-1]})}\)
- works with tanh activation
- does not work well with ReLU activation
MSRA initialization
- \(W = \frac{np.random.rand(n^{[l-1]},\ n^{[l]})}{np.sqrt(\frac{n^{[l-1]}}{2})}\)
- works better with ReLU activation


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