@import dev.marksman.custombingobuilder.Settings @(settings: Settings)(implicit request: RequestHeader) @main("Custom Bingo Builder - Template Help") {

inside the body that has the class
card-template
. Everything inside this

represents a single card and will be repeated on the output.insert-word
will have its contents replaced with a random item from
the supplied word list. For example:
<!DOCTYPE html>


LED
LED Strip controlled via LAN using a Arduino-based web server.


Quantropy
Fundamental Analysis
Technical Analysis
Charting Basics
Types of Charts
Candlestick Chart
Line Chart
OHLC Chart
Price Action
Support & Resistance
Trend Lines
Channels
Pivot Points
Technical Indicators
Chart Patterns
Candlestick Patterns
Asset Pricing Models
Portfolio Allocation Models
Investment Paradigms
Quantropy
»
Technical Analysis
View page source
Technical Analysis
¶
Charting Basics
¶
Types of Charts
¶
Candlestick Chart
¶
Line Chart
¶
OHLC Chart
¶
Price Action
¶
Support & Resistance
¶
Trend Lines
¶
Channels
¶
Pivot Points
¶
Technical Indicators
¶
Chart Patterns
¶
Candlestick Patterns
¶


I am a backend developer with extensive experience working with PHP, specializing in web services and API integrations. I love a challenge and I enjoy testing new technologies.
I joined the Supercreators Team to provide modern self-service ticketing tools and migrate a legacy service handling over the 40% of the current income in fees.
As part of the Integrations Team, I was responsible to build custom integrations with third-party platforms as well as developing the public API so property management platforms can use it to publish and manage their properties.
Our project helped to improve the acquisition and reduce rejection rates due to outdated occupancies. We also reduced manual work from agents and customer support.
I joined Pingvalue in the first months helping to define workflows, technical requirements and tasks from high level requirements on a SCRUM based development using Jira and Confluence.
We built the platform around the API following the RESTfull principles, using Test Driving Development and Continuous Integration.
We migrated the legacy API removing Google App Engine code dependencies and building a new infrastructure in Kubernetes, allowing us to have more flexibility and proper environments for development, acceptance and production.
As a startup, we have been able to build a strong and collaborative team over 20 developers that supports frequent releases over 3 different platforms, web, iOS and Android.
My main goal was the development of the new features and services for the company and the users of the Embarcadero Developer Network.
We integrated all the different services on the Community, a social network for developers, migrating all the data from legacy databases using custom scripts and building REST APIs to allow integration with core Embarcadero products as Rad Studio.
I was responsible of a 24x7 SMS platform. We integrated multiple providers that allowed us to offer a wide variety of SMS based services with competitive prices as we have multiple choices for our client’s needs.
Our main product was a SMS Chat and other related services for local television broadcasters such as surveys, quiz, new alerts, ring tone downloads, etc.
We also developed marketing tools based on SMS, email and smartphones.
My main tasks were web consulting, basic web management, direct contact with customers and training new employees in the company methodologies.
In the last year of University, I started 2 months of internship and after that I joined the company.
In this time, I worked in web consulting, some internal projects and teaching other students during their internship.


Confirm Deletion of each Flist File
If this checkbox is set, Moderate will ask you to confirm that you want to delete file lines in a file list. Otherwise they will be deleted without warning. Non file lines will always be deleted without confirmation.
This setting is independant of that controlling confirmation of the deletion of the associated file in the topic file directory.


Ping Pong
Begin!
Rules
Numbers divisible by 3 are replaced with "ping"
Numbers divisible by 5 are replaced with "pong"
Numbers divisible by 15 are replaced with "ping-pong"
*You'll get a really long list if you input a number that is more than 3 digits!*
Enter a number here:
Ping Pong!


OBJECTIVES
Almost all Political Parties make the most of their Youth Power
through their ‘Youth Wings’, whose main function is
to organize rallies, picketing, sit in, demonstration, gathering
crowds for electioneering and slogan shouting etc. But, when it
comes to taking decisions, giving tickets for fighting elections
or becoming a minister after elections, youth are neither consulted
nor are they given any important role to play . And if at all, it
is given to youth ! Just think, whom these roles are given to. Have
a close look at the main National Political Parties or State political
parties of today and their Youth Leadership. Look at the background
of their youth leaders, you will be surprised to see that most of
these youth leaders are scion of Chief of the Political Party or
scion of the Top Leaders of these Parties or scion of Prominent
Business Houses of the Country. Now, a real big question comes.
Can a youth having the background of a commoner enter the Parliament
? Can the son of a poor farmer from village cross the doors of Parliament
? Whether Indian Democracy really requires the crutches of economic
prosperity, political background and organized crime. National Youth
Party comes with a visionary answers to all these questions. The
main target of the Party is a Young Parliament or a Parliament full
of young people. The Party has vowed and committed to this pious
goal. Can a common youth without economic prosperity, political
backing, or criminal one-upmanship enter Parliament. Yes, he can
and the National Youth Party aims at sending this common youth to
the Parliament.
Today, Youth look for inspiration to Ideals, at the time of taking
important decisions. National Youth Party has chosen Youth Icon
Swami Vivekananda, who never fails to inspire the Indian Youth and
Guru Govind Singh Ji, who made unparalleled sacrifice as its Ideals
and Inspiring Leaders.
Swami Vivekananda, in his youth made India proud all over the
world by his deep knowledge, character and progressing Nationalism
and inspired Indians to a new Renaissance. He made the Youth of
his day look at their despair, dependency, illiteracy n customs,
suggesting ways and means to counter them.
Guru Govind Singh Ji Maharaj did not accept the sovereignty of
the Moguls nor forsook his society and sacrificed his sons before
his own eyes. Our history is full of people, who sacrificed every
thing for their country, but Guru Govind Singh Ji made the supreme
sacrifice of his sons for the noble cause.  Such sacrifice of Shri Guru Govind Singh
Ji will keep on inspiring Indian Youth always.
National Youth Party has chosen these two great souls as Inspiring
Ideals of the Party.
Work culture of National Youth Party is based on clarity of
thought and friendship. Whosoever is elder in age and responsibility
in the party should be respected, so that the younger in the part
get love, affection and cooperation in return. Making this as
guiding principle, National Youth Party is working from a small
village to the National level. With the expansion of this work
culture, we are trying to unite the Youth of this great Country.
Youth are friendly, who to-gather can solve every problem facing
the Nation. The youth can work towards party’s goal of forming
a Young Parliament. Party is committed to achieve its target within
the given time frame. Whole of the Party work is based on designated
target, designated time and designated person. Party has named
this work culture as ‘Friendly, Frankly, Time Bound and
Result Oriented’.
Membership:
Any young person, believing in the working and politics of the Party,
can join the party by filling up General Membership Form-1. Only a General
Member of the Party can be made an active member of the Party.


module Genlex: sig .. end
This module implements a simple 'standard' lexical analyzer, presented as a function from character streams to token streams. It implements roughly the lexical conventions of OCaml, but is parameterized by the set of keywords of your language.
Example: a lexer suitable for a desk calculator is obtained by
let lexer = make_lexer ["+";"-";"*";"/";"let";"="; "("; ")"]
The associated parser would be a function from token stream
to, for instance, int
, and would have rules such as:
let rec parse_expr = parser | [< n1 = parse_atom; n2 = parse_remainder n1 >] -> n2 and parse_atom = parser | [< 'Int n >] -> n | [< 'Kwd "("; n = parse_expr; 'Kwd ")" >] -> n and parse_remainder n1 = parser | [< 'Kwd "+"; n2 = parse_expr >] -> n1+n2 | [< >] -> n1
One should notice that the use of the parser
keyword and associated
notation for streams are only available through camlp4 extensions. This
means that one has to preprocess its sources e. g. by using the
"-pp"
command-line switch of the compilers.
type token =
| |
Kwd of string |
| |
Ident of string |
| |
Int of int |
| |
Float of float |
| |
String of string |
| |
Char of char |
Int
and Float
for integer and floating-point numbers; String
for
string literals, enclosed in double quotes; Char
for
character literals, enclosed in single quotes; Ident
for
identifiers (either sequences of letters, digits, underscores
and quotes, or sequences of 'operator characters' such as
+
, *
, etc); and Kwd
for keywords (either identifiers or
single 'special characters' such as (
, }
, etc).let make_lexer: (list(string), Stream.t(char)) => Stream.t(token);
s
is returned as Kwd s
if s
belongs to this list, and as Ident s
otherwise.
A special character s
is returned as Kwd s
if s
belongs to this list, and cause a lexical error (exception
Stream.Error
with the offending lexeme as its parameter) otherwise.
Blanks and newlines are skipped. Comments delimited by (*
and *)
are skipped as well, and can be nested. A Stream.Failure
exception
is raised if end of stream is unexpectedly reached.


Calculating frame rate at used by 'requestAnimationFrame'
FPS: 30fps | SPEED: 4000ms
ASC
0
DESC
0
FPS: 60fps | SPEED: 2000ms
ASC
0
DESC
0


This gives reasonably clean and easy way to ccenable only what these chains want in the code. We should use ac_ccenable on all new chains, and also provide a way to activate CCs at a height.
I propose something like ac_ccactivateht=height,ecode,height,ecode....
This should be pretty easy to implement, and as long as all notaries add the new params before the height nothing bad will happen.


THE NAKED GUN: FROM THE FILES OF POLICE SQUAD A film review by Randy Parker Copyright 1996 Randy Parker
RATING: **1/2 (out of ****)
(Review written in 1988)
A powerful business tycoon dreams up an ingenious scheme to assassinate the Queen of England at a baseball game. And only one man can stop him. James Bond? Guess again. The Equalizer? Nope! Give up? Try Leslie Nielsen, a.k.a. Frank Drebin, the bumbling cop from the short-lived TV series "Police Squad." That's right, "Police Squad" is back and ready for action, this time as a movie from the team that brought us AIRPLANE, TOP SECRET, RUTHLESS PEOPLE, and--of course--"Police Squad." Their movie THE NAKED GUN: FROM THE FILES OF POLICE SQUAD! reunites most of the original cast from the TV series and features the type of madcap, slapstick humor we've come to expect from Jerry Zucker, Jim Abrahams, and David Zucker.
Although THE NAKED GUN has more laughs than most comedies would dream of, it fails to duplicate the magic of the team's previous efforts. Since AIRPLANE, Abrahams and the Zucker brothers have used the same formula so many times now that it has lost its novelty and become cliched. Many of the jokes in THE NAKED GUN not only lack originality, but also get repeated over and over and over again. The first time Leslie Nielsen pulls up to the curb and crashes into something is mildly amusing, if uninspired; by the seventh time, the gag has grown so stale it makes you want to ... gag.
The first half of the movie strings together a series of non-stop gags one after another, half of which fizzle. The second half, to its credit, slows down and has some extremely inventive and hysterical sequences.
The actors in THE NAKED GUN deserve credit for their solid comic performances in the face of an uneven script. Leslie ("Don't call me Shirley") Nielsen is as loveable and inept as ever as Officer Drebin, Ricardo Montalban is appropriately despicable as the conniving tycoon, and Priscilla Presley as Nielsen's love-interest lights up the screen with her humor and sex appeal. The movie's clever cameos also keep things rolling.
Although it may pale in comparison to a masterpiece such as AIRPLANE, THE NAKED GUN is by no means a failure. The movie easily has enough successful gags and honest laughs for me to recommend it to any fan of the Zuckers/Abrahams sense of humor.
--- Randy Parker<EMAIL_ADDRESS>http://www.shoestring.org
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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Avengers' Chadwick Boseman could have landed Guardians Of The Galaxy's Drax
Avengers’ Chadwick Boseman has revealed that one of the reasons he landed his role in the Marvel franchise was because he actually auditioned for Drax in Guardians Of The Galaxy.
It could have been a very different movie.
While the character, known for his blunt and matter-of-fact comments, ended up being played by Dave Bautista, Chadwick opened up on how the experience helped him.
‘It’s about going in, I didn’t think I was going to get it, and it’s weird too because it’s a testament to Marvel – each film…has a different tone,’ he said on The Tonight Show Starring Jimmy Fallon. ‘We didn’t know what Guardians was going to be.
‘I didn’t know what it was, I only had a few pages at that time so it was good to come in and play to see what they did with it.’
He added to the host: ‘Sometimes that’s the way it works as an actor, you know you’re not going to get it but you’re meeting the people – they might be like, “It’s not this, but we’ll put him in this other thing.”‘
Advertisement Advertisement
Chadwick ended up landing the role of Black Panther so you could definitely say it paid off.
He also became one of the best secret-keepers on set, answering all press questions about Avengers: Endgame with his iconic ‘I’m dead’ line.
Can’t beat it.
Meanwhile, Marvel is set to bless us with a Black Panther sequel following the end of phase three, but we’ve got a while to wait as it’s not expected to land until 2022.
Hang in there guys.
Chatting about what he wants the movie to be, the star explained: ‘Hopefully we can maintain the foundation that we sort of set and build upon it and expand it and explore it. That’s what I hope.’
He added to MTV International: ‘But I think first you have to maintain the foundation. We built a culture and a world, so you have to make sure that you keep that in place.’
Stars including Chadwick, Letitia Wright (Shuri), Lupita Nyong’o (Nakia), and Danai Gurira (Okoye) are expected to return.
Black Panther 2 is released 6 May 2022.
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


Ogun State wins 2019 NNPC science quiz competition
by The Eagle OnlineOgun State has won the 2019 Nigerian National Petroleum Corporation’s Science Quiz Competition for secondary school students across the country.
Ogun state emerged as the winner at the grand finale of the completion held at the NNPC Towers in Abuja on Thursday.
Ojo Oluwatobi from APT. Scholars Universal College, Ota, won the first price for Ogun State with 80 points while Mbazu Justice from CSMT Staff Secondary School, Abakaliki in Ebonyi State, took the second position with 70+points.
Nwachukwu Ugochukwu of Dority International School Aba, Abia State took the third position with 70 points.
The Group Managing Director of NNPC, Malam Mele Kyari, said that the corporation as an enabler company would continue to contribute to education to ensure a greater Nigeria.
He said that the competition was one aspect of the corporation’s effort in supporting nation building.
He said: “Building a successful nation has to deal with talent management and as a corporation we try to recognise them young and help them to development it well.”
Also, President of the Dangote Group, Alhaji Aliko Dangote, urged the students to put in their best in whatever they did in life as leaders of tomorrow.
He commended the NNPC for the initiative adding that it had helped to develop a lot of scientists in the country.
Speaking on behalf of the participants, the 2019 winner, Oluwatobi commended the NNPC for the initiative and thanked all his teachers and parents for their support.
“I am very grateful to the NNPC for the opportunity and the initiatives such as this.
“This competition has made me to read so hard, I am happy to emerge as the winner.
“I am grateful to my teachers, parents and all the oraginsers.
“With this competition, I am very sure to pass all my exams very well,’’ he said.
The corporation, also in its report, said that the competition started at the grassroots level in each of 774 local government areas and best three student proceeded to the state level.
“At the state level, the best student in each state emerges and proceeds to the zonal level and each winner at this level is entitled to a one-off educational grant of N100.000,’’ it said.
It further noted that the states at the geopolitical zones meet at different times to compete among themselves and then determine the best three states to compete at the national grand finale.
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This is the demo frontend for the Button Recipe in the Crossbar.io IoT Cookbook.
| Connected to URL (protocol) | - |
| Joined as authid@realm | - |
| Addressing Pi with serial No.: | - |
| Pi component started (UTC) | - |
Click to test communication with raspberry backend
When the button on the Pi has detected a falling edge, this indicator is flashed for 1 sec.
There are two Buttons to turn the LED on pin 15 on and off


05-Apr-2017 | Milku
If I can’t rely on earth-bound hamsters as potential heroes, perhaps I should look to the skies.
Space hamsters are a rare breed, but they do exist.
The first ones I came across featured in the Philip K Dick short story The Infinites. The story focuses on a spaceship which is scouting asteroid fields for mining opportunities. After landing on an asteroid, the crew use a pack of hamsters to check the radiation levels outside... How cruel is that! Animal rights obviously wasn’t a priority in 1953 when the story was published in Planet Stories.
Not surprisingly, given the high radiation levels on the asteroid, the hamsters don’t fare too well and are lifeless when recovered by the crew. I had less sympathy when I read about the fate of the crew themselves, but I suppose you might be interested. They pass out, waking up days later with their hair and nails falling out, and their heads swelling in size. But at this stage, they still seem to be luckier than the hamsters. It turns out the humans have crammed millions of years of evolution into several days.
Blake, one of the crew members, wants them all to return to Earth and use their advanced intellects to take control. When the others don't agree, a fight ensues and Blake somehow generates a burst of energy that kills his team mate, Silvia. He turns to try to kill the Captain, Crispin Eller, but before he can do so, several large orbs of energy appear... Now, that’d send the Ghost Adventures Crew into overdrive. I’ve watched them get excited about tiny specks of light on the screen that just wiggle about a bit. Just look at any of their shows. Check out the Ghost Adventures website for details. These space energy orbs have the power to destroy Blake. And guess what? The orbs of energy are actually the irradiated hamsters. They evolved even more than the humans and became pure energy. They sound like my kind of guys. Powerful and no fur to wash!
But they stopped being hamsters per se so I continued my quest for a true hamster hero.
It led me to Bounty Hamster, which was an animated children’s TV series made in 2003. If you want to know more, check out the TV Tropes website In this show, a teenage girl, Cassie Harrison, is searching the universe for her father who has been kidnapped by space pirates. She needs help, but is on a budget, so can only afford to recruit a talking blue hamster called Marion. I was a bit cross, after all it suggests hamsters are cheap. But at least he is a professional bounty hunter.
I was impressed to find out that he was inspired by John Wayne. They share a name…no not “John’...  And Marion wears an eye patch just like John Wayne’s character in the film True Grit. For those of you who are concerned, the eyepatch was just for show. Marion had two perfect eyes.
Cassie might complain about Marion being clumsy or forgetful, but really he’s very handy to have around. (The biggest human in my house claims the same thing!) He can store many things in his cheeks for use in an emergency. (That's Marion and not my big human!)
Then he can growl! Don’t tell anyone, but I can only squeak a little.
Even so, some of the other characters in the programme call him 'cute'. But Marion is fierce in his defence of himself and this is when he utters his catchphrase "Don't call me CUTE!" before going berserk.
This is the ideal to which every fictional hamster should aspire. I’m going to try to emulate him as well. Not too sure I can get my paws on some blue fur dye though.


class: center, middle, inverse, title-slide # ETC3250: Introduction ## Semester 1, 2019 ###
Professor Di Cook
Econometrics and Business Statistics
Monash University ### Week 1 (b) --- class: split-30 .column[.pad10px[ ## Outline - .green[Introduction] - Learning from data ]] .column[.top50px[ - .orange[Better understand] or .orange[make predictions] about a certain phenomenon under study

 - .orange[Construct a model] of that phenomenon by finding relations between several variables

 - If phenomenon is complex or depends on a large number of variables, an .orange[analytical solution] might not be available

 - However, we can .orange[collect data] and learn a model that .orange[approximates] the true underlying phenomenon ]] --- class: split-30 .column[.pad10px[ ## Outline - .green[Introduction] - Learning from data ]] .column[.top50px[  `\(\mathcal{D} = \{(x_i, y_i)\}_{i = 1}^N, ~~~ \mbox{where}~ x_i = (x_{i1}, \dots, x_{ip})^{T}\)` .boxshadow[.green[Statistical learning] provides a framework for constructing models from the data.] ]] --- class: split-30 .column[.pad10px[ ## Outline - .green[Introduction] - Learning from data - Different learning problems ]] .column[.top50px[ - .green[Supervised] learning, `\(y_i\)` .orange[available] for all `\(x_i\)` - Regression (or prediction) - Classification - .green[Unsupervised] learning, `\(y_i\)` .orange[unavailable] for all `\(x_i\)` - .green[Semi-supervised] learning, `\(y_i\)` available only for few `\(x_i\)` - Other types of learning: reinforcement learning, online learning, active learning, etc. .boxshadow[Being able to .green[identify] which is the type of learning problem you have is important in practice]] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] ]] .column[.top50px[ `\(\mathcal{D} = \{(y_i, x_i)\}_{i = 1}^N\)` where `\((y_i, x_i) \sim P(Y, X) = P(X) \underbrace{P(Y|X)}_{}\)` where `\(P(Y, X)\)` means that these arise from some probability distribution. `\(``\sim"\)` means distributed as, arise from. Typically, we only are interested in `\(P(Y|X)\)`, the distribution of `\(Y\)` conditional on `\(X\)`. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] ]] .column[.top50px[ - `\(Y = (Y_1, \dots, Y_q)\)`: response (output) (could be multivariate, `\(q=1\)` for us) - `\(X = (X_1, \dots, X_p)\)`: set of `\(p\)` predictors (input) We seek a function `\(h(X)\)` for predicting `\(Y\)` given values of the input `\(X\)`. This function is computed using `\(\mathcal{D}\)`. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] ]] .column[.top50px[ `\(\mathcal{D} = \{(y_i, x_i)\}_{i = 1}^N \mbox{ where } (y_i, x_i) \sim P(Y, X)\)` We are interested in minimizing the expected .orange[out-of-sample] prediction error: `\(\mbox{Err}_{\mbox{out}}(h) = E[L(Y, h(X))]\)` where `\(L(y, {\hat{y}})\)` is a non-negative real-valued .orange[loss function], such as `\(L(y, \hat{y}) = (y - \hat{y})^2\)` and `\(L(y, \hat{y}) = I(y \neq \hat{y})\)`. .boxshadow[The goal is that the predictions from the model are accurate for future samples.] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression ]] .column[.top50px[ We often assume that our data arose from a statistical model `\(Y=f(X) + \varepsilon,\)` where `\(f\)` is the true unknown function, `\(\varepsilon\)` is the random error term with `\(E[\varepsilon] = 0\)` and is independent of `\(X\)`. - The additive error model is a useful approximation to the truth - `\(f(x) = E[Y|X = x]\)` - Not a deterministic relationship: `\(Y \neq f(X)\)` ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression ]] .column[.nopadding[    .light-blue[Blue curve] is `\(f(x)\)`, the true functional relationship. .font_tiny[(Chapter2/2.2.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression ]] .column[.nopadding[    .light-blue[Blue surface] is `\(f(x)\)`, the true functional relationship. .font_tiny[(Chapter2/2.3.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression - Why? ]] .column[.top50px[ - **Prediction**: - `\(\hat{y}_{*} = \hat f(x_{*})\)` for a new observation `\(x_{*}\)` - **Inference (or explanation)**: - Which predictors are associated with the response? - What is the relationship between the response and each predictor? ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression - Why? - Estimation ]] .column[.pad10px[       Linear model: `\(\hat f(\mbox{education}, \mbox{seniority}) =\)` `\(~~~~~~~~\hat \beta_0 + \hat \beta_1 \times \mbox{education} + \hat \beta_2 \times \mbox{seniority}\)` .boxshadow[Why would we ever choose to use a **more restrictive method** instead of a **very flexible approach**?] .font_tiny[(Chapter2/2.3.pdf, 2.4.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression - Why? - Estimation ]] .column[.nopadding[             .font_tiny[(Chapter2/2.3.pdf, 2.4.pdf, 2.5.pdf, 2.6.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression - Why? - Estimation - Methods ]] .column[.nopadding[ - .orange[Parametric methods]
 ➕ Assumption about the form of `\(f\)`, e.g. linear
 😄 The problem of estimating `\(f\)` reduces to estimating a set of parameters
 😄 Usually a good starting point for many learning problems
 🙁 Poor performance if linearity assumption is wrong - .orange[Non-parametric methods]
 😄 No *explicit* assumptions about the form of `\(f\)`, e.g. nearest neighbours: `\(\hat Y(x) = \frac1k \sum_{x_i \in N_k(x)} y_i\)`
 😄 High flexibility: it can potentially fit a range of shapes
 🙁 A large number of observations is required to estimate `\(f\)` with good accuracy ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression ]] .column[.top50px[ Suppose we have a regression model `\(y=f(x)+\varepsilon\)`. .orange[Estimate] `\(\hat{f}\)` from some .orange[training data], `\(Tr=\{x_i,y_i\}_{i=1}^n\)`. One common measure of accuracy is: .orange[Training Mean Squared Error] `\(MSE_{Tr} = \mathop{\mbox{Ave}}\limits_{i\in Tr}[y_i-\hat{f}(x_i)]^2 = \frac{1}{n}\sum_{i=1}^n [(y_i-\hat{f}(x_i)]^2\)` ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression ]] .column[.top50px[ Suppose we have a regression model `\(y=f(x)+\varepsilon\)`. .orange[Estimate] `\(\hat{f}\)` from some .orange[training data], `\(Tr=\{x_i,y_i\}_{i=1}^n\)`. One common measure of accuracy is: .orange[Training Mean Squared Error] `\(MSE_{Tr} = \mathop{\mbox{Ave}}\limits_{i\in Tr}[y_i-\hat{f}(x_i)]^2 = \frac{1}{n}\sum_{i=1}^n [(y_i-\hat{f}(x_i)]^2\)` Measure .orange[real accuracy] using .orange[test data] `\(Te=\{x_j,y_j\}_{j=1}^m\)`, .orange[Test Mean Squared Error] `\(MSE_{Te} = \mathop{\mbox{Ave}}\limits_{j\in Te}[y_j-\hat{f}(x_j)]^2 = \frac{1}{m}\sum_{j=1}^m [(y_j-\hat{f}(x_j)]^2\)` ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs ]] .column[.top50px[ - In general, the more .orange[flexible] a method is, the .orange[lower] its .orange[training MSE] will be. i.e. it will “fit” the training data very well. - However, the .orange[test MSE] may be .orange[higher] for a more .orange[flexible] method than for a simple approach like linear regression. - Flexibility also makes interpretation more difficult. There is a trade-off between .orange[flexibility] and .orange[model interpretability]. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - .green[Supervised learning] - Regression - Why? - Estimation - Methods - Interpretability vs flexibility ]] .column[.nopadding[    Simplistic overview of methods on the flexibility vs interpretability scale. Interpretability is when it is clear how the explanatory variable is related to the response, e.g. linear model. .orange[Poor interpretability] is often called a .orange["black box"] method. .font_tiny[(Chapter2/2.7.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example ]] .column[.top50px[ .split-two[ .row[    .font_tiny[(Chapter2/2.9.pdf)] ] .row[ .split-50[ .column[

 .black[true curve]
 .orange[linear regression]
 .green[Smoothing] splines ] .column[

 .gray[Training MSE]
 .red[Test MSE]
 .black[Dashed: Minimum test MSE] ] ] ] ] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example ]] .column[.top50px[ .split-two[ .row[    .font_tiny[(Chapter2/2.9.pdf)] ] .row[ .split-50[ .column[

 .black[true curve]
 .orange[linear regression]
 .green[Smoothing] splines ] .column[

 .gray[Training MSE]
 .red[Test MSE]
 .black[Dashed: Minimum test MSE] ] ] ] ] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example ]] .column[.top50px[ .split-two[ .row[    .font_tiny[(Chapter2/2.11.pdf)] ] .row[ .split-50[ .column[

 .black[true curve]
 .orange[linear regression]
 .green[Smoothing] splines ] .column[

 .gray[Training MSE]
 .red[Test MSE]
 .black[Dashed: Minimum test MSE] ] ] ] ] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example - Bias-variance tradeoff ]] .column[.top50px[ .boxshadow[There are two competing forces that govern the choice of learning method: .orange[bias] and .orange[variance].] .orange[Bias] is the error that is introduced by modeling a complicated problem by a simpler problem. - For example, linear regression assumes a linear relationship when few real relationships are exactly linear. - In general, the .orange[more flexible] a method is, the .orange[less bias] it will have. [This site](https://degreesofbelief.roryquinn.com/bias-variance-tradeoff) has a lovely explanation, if you don't like mine. ]] --- class: split-30 count: false .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example - Bias-variance tradeoff ]] .column[.top50px[ .boxshadow[There are two competing forces that govern the choice of learning method: .orange[bias] and .orange[variance].] .orange[Variance] refers to how much your estimate would change if you had different training data. - In general, the .orange[more flexible] a method is, the .orange[more variance] it has. - The .orange[size] of the training data has an impact on the variance. ]] --- ## MSE decomposition If `\(Y = f(x) + \varepsilon\)` and `\(f(x)=\mbox{E}[Y\mid X=x]\)`, then the expected **test** MSE for a new `\(Y\)` at `\(x_0\)` will be equal to `\(E[(Y-\hat{f}(x_0))^2] = [\mbox{Bias}(\hat{f}(x_0))]^2 + \mbox{Var}(\hat{f}(x_0)) + \mbox{Var}(\varepsilon)\)` Test MSE = Bias `\(^2\)` + Variance + Irreducible variance - The expectation averages over the variability of `\(Y\)` as well as the variability in the training data. - As the flexibility of `\(\hat{f}\)` increases, its variance increases and its bias decreases. - Choosing the flexibility based on average test MSE amounts to a .orange[bias-variance trade-off] --- .nopadding[    .green[squared bias], .orange[variance], Var(ε) (dashed line), and .red[test MSE] for the three data sets shown earlier. The vertical dotted line indicates the flexibility level corresponding to the smallest test MSE. .font_tiny[(Chapter2/2.12.pdf)] ] --- class: split-30 .column[.nopadding[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Regression - Training vs Test MSEs - Example - Bias-variance tradeoff - Optimal prediction ]] .column[.top50px[ The optimal MSE is obtained when `\(\hat{f}=f = \mbox{E}[Y\mid X=x].\)` Then .orange[bias=variance=0] and `\(\mbox{MSE} = \mbox{irreducible variance}\)` This is called the .orange[oracle predictor] because it is not achievable in practice. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification ]] .column[.nopadding[ Here the response variable `\(Y\)` is .orange[qualitative]. - e.g., email is one of `\({\cal C} = (\mbox{spam},\mbox{ham})\)` - e.g., voters are one of `\({\cal C} = (\mbox{Liberal},\mbox{Labor},\mbox{Green},\mbox{National},\mbox{Other})\)` Our goals are: 1. Build a classifier `\(C(x)\)` that assigns a class label from `\({\cal C} = \{\mathcal{C}_1, \dots, \mathcal{C}_K\}\)` to a future unlabeled observation `\(x\)`. 2. Such a classifier will divide the input space into regions `\(\mathcal{R}_k\)` called decision regions, one for each class, such that all points in `\(\mathcal{R}_k\)` are assigned to class `\(\mathcal{C}_k\)` 3. Assess the uncertainty in each classification (i.e., the probability of misclassification). 4. Understand the roles of the different predictors among `\(X = (X_1,X_2,\dots,X_p)\)`. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification ]] .column[.top50px[ Recall that we want to minimize the expected prediction error `\(E_{(Y, X)}[L(Y, C(X))]\)` where `\(L(y, {\hat{y}})\)` is a non-negative real-valued .orange[loss function]. In classification, the output `\(Y\)` is a .orange[categorical variable], and our loss function can be represented by a `\(K \times K\)` matrix `\(L\)`, where `\(K = \mbox{card}(\mathcal{C})\)`. `\(L(k, l)\)` is the cost of classifying `\(C_k\)` as `\(C_l\)`. With zero-one loss, i.e. `\(L(y, \hat{y}) = I(y \neq \hat{y})\)` the cost is equal for mistakes between any class. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Optimal classifier - Error ]] .column[.top50px[ .orange[Compute] `\(\hat{C}\)` from some .orange[training data], `\(Tr=\{x_i,y_i\}_1^n\)`. In place of MSE, we now use the error rate (fraction of misclassifications). *Training Error Rate* `\(\text{Error rate}_{Tr} = \frac{1}{n}\sum_{i=1}^n I(y_i \ne \hat{C}(x_i))\)` Measure .orange[real accuracy] using .orange[test data] `\(Te=\{x_j,y_j\}_1^m\)` *Test Error Rate* `\(\text{Error rate}_{Te} = \frac{1}{m}\sum_{j=1}^m I(y_j \ne \hat{C}(x_j))\)` ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier ]] .column[.top50px[ Let `\({\cal C} = \{\mathcal{C}_1, \dots, \mathcal{C}_K\}\)`, and let `\(p_k(x) = \text{P}(Y = C_k\mid X = x),\qquad k = 1, 2, \dots , K.\)` These are the .orange[conditional class probabilities] at `\(x\)`. Then the .orange[Bayes] classifier at `\(x\)` is `\(C(x) = C_j \quad \mbox{ if } p_j(x) = \max\{p_1(x), p_2(x), \dots, p_K(x)\}\)` *This gives the minimum average test error rate.* ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier ]] .column[.top50px[ `\(1-\text{E}\left(\max_j \text{P}(Y = C_j | X)\right)\)` - The .orange[Bayes error rate] is the lowest possible error rate that could be achieved if we knew exactly the .orange[true] probability distribution of the data. - It is analogous to the irreducible error in regression. - On test data, no classifier can get lower error rates than the Bayes error rate. - In reality, the Bayes error rate is not known exactly. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier ]] .column[.top50px[    .font_tiny[(Chapter2/2.13.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier - kNN ]] .column[.pad10px[ One of the simplest classifiers. Given a test observation `\(x_0\)`, - Find the `\(K\)` nearest points to `\(x_0\)` in the training data: `\({\cal N}_0\)`. - Estimate conditional probabilities `\(=P(Y = C_j \mid X=x_0) = \frac{1}{K}\sum_{i\in {\cal N}_0} I(y_i = C_j).\)` - Classify `\(x_0\)` to class with largest probability. ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier - kNN ]] .column[.top50px[    .font_tiny[(Chapter2/2.14.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier - kNN ]] .column[.top50px[    .font_tiny[(Chapter2/2.16.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier - kNN ]] .column[.top50px[    .font_tiny[(Chapter2/2.15.pdf)] ]] --- class: split-30 .column[.pad10px[ ## Outline - Introduction - Supervised learning - .green[Assessing model accuracy] - Classification - Error - Bayes classifier - kNN ]] .column[.top50px[    .font_tiny[(Chapter2/2.17.pdf)] ]] --- ### A fundamental picture  --- layout: false # 👩💻 Made by a human with a computer ### Slides at [https://monba.dicook.org](https://monba.dicook.org). ### Code and data at [https://github.com/dicook/Business_Analytics](https://github.com/dicook/Business_Analytics).
 ### Created using [R Markdown](https://rmarkdown.rstudio.com) with flair by [**xaringan**](https://github.com/yihui/xaringan), and [**kunoichi** (female ninja) style](https://github.com/emitanaka/ninja-theme).

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


@* * Call the `main` template with two arguments. The first * argument is a `String` with the title of the page, the second * argument is an `Html` object containing the body of the page. *@ @main("Student-Course Application")("students") {
| ID | Name | Courses | Action |
|---|


About
|
|
Hello, I am Manu Singh. My areas of interest is in Computer Vision, Machine Learning and social media data mining. I am an alumni of
IU Computer Vision Lab and Indiana University Bloomington where I received my masters in Computer Science under the guidance of Professor David Crandall. For an overview of my work, check out my projects. If you are interested in Computer Vision and Deep Learning research, then check my reading list and blog.
|
2014 - 2016
- Master of Science (CS), Indiana University Bloomington
Thesis Advisor: Professor David Crandall - Research Assistant at Computer Vision Lab
- Associate Instructor of Introduction to Programming(A201)
Summer 2015
Software Development Intern at Sears Holding
Computer Vision, Deep Learning, Api Development
Computer Vision, Deep Learning, Api Development
2012 - 2014
Software Engineer at Toshiba R&D
Cloud Computing, Virtualization, Software Development
Cloud Computing, Virtualization, Software Development
2010 - 2012
Software Engineer at CGI
Software Development
Software Development
2006-2010
Bachelor of Technology, College of Engineering, Roorkee
Computer Science, Electronics Engineering
Computer Science, Electronics Engineering
| Projects | view all projects» | |
|
Landmark Recognition Tag Selection and Propagation for Large Scale Visual Landmark Recognition. more» |
Bird and Squirrel Alert System A system to recognize birds and squirrel on a bird-feeder from video. more» |
Visual Search Provider for retailers and brands A Convolutional Neural Network model to recognize consumer products. more» |
| Blog Posts | view all posts» |


public abstract class Region
extends java.lang.Object
GLRegion
| Modifier and Type | Field and Description |
|---|---|
java.util.ArrayList<com.jogamp.graph.geom.Triangle> |
triangles |
static int |
TWO_PASS_DEFAULT_TEXTURE_UNIT |
static int |
VARIABLE_CURVE_WEIGHT_BIT
Use non uniform weights [0.0 ..
|
static int |
VBAA_RENDERING_BIT
View based Anti-Aliasing, A Two pass region rendering, slower and more
resource hungry (FBO), but AA is perfect.
|
| Modifier and Type | Method and Description |
|---|---|
void |
addTriangle(com.jogamp.graph.geom.Triangle tri)
Adds a
Triangle object to the Region This triangle will be bound
to OGL objects on the next call to update |
void |
addTriangles(java.util.ArrayList<com.jogamp.graph.geom.Triangle> tris)
Adds a list of
Triangle objects to the Region These triangles are
to be binded to OGL objects on the next call to update |
void |
addVertex(com.jogamp.graph.geom.Vertex vert)
Adds a
Vertex object to the Region This vertex will be bound to
OGL objects on the next call to update |
void |
addVertices(java.util.ArrayList<com.jogamp.graph.geom.Vertex> verts)
Adds a list of
Vertex objects to the Region These vertices are to
be binded to OGL objects on the next call to update |
com.jogamp.opengl.math.geom.AABBox |
getBounds() |
int |
getNumVertices()
Get the current number of vertices associated with this region.
|
int |
getRenderModes()
Get current Models
|
boolean |
isDirty()
Check if this region is dirty.
|
boolean |
isNonUniformWeight()
Check if current instance uses non uniform weights
|
static boolean |
isNonUniformWeight(int renderModes)
Check if render mode capable of non uniform weights
|
boolean |
isVBAA()
Check if current Region is using VBAA
|
static boolean |
isVBAA(int renderModes) |
public static final int VBAA_RENDERING_BIT
public static final int VARIABLE_CURVE_WEIGHT_BIT
public static final int TWO_PASS_DEFAULT_TEXTURE_UNIT
public java.util.ArrayList<com.jogamp.graph.geom.Triangle> triangles
public static boolean isVBAA(int renderModes)
public static boolean isNonUniformWeight(int renderModes)
renderModes
- bit-field of modes, e.g.
VARIABLE_CURVE_WEIGHT_BIT
,
VBAA_RENDERING_BIT
public final int getRenderModes()
public boolean isVBAA()
public boolean isNonUniformWeight()
public final int getNumVertices()
public void addTriangle(com.jogamp.graph.geom.Triangle tri)
Triangle
object to the Region This triangle will be bound
to OGL objects on the next call to update
tri
- a triangle objectupdate(GL2ES2)
public void addTriangles(java.util.ArrayList<com.jogamp.graph.geom.Triangle> tris)
Triangle
objects to the Region These triangles are
to be binded to OGL objects on the next call to update
tris
- an arraylist of triangle objectsupdate(GL2ES2)
public void addVertex(com.jogamp.graph.geom.Vertex vert)
Vertex
object to the Region This vertex will be bound to
OGL objects on the next call to update
vert
- a vertex objectsupdate(GL2ES2)
public void addVertices(java.util.ArrayList<com.jogamp.graph.geom.Vertex> verts)
Vertex
objects to the Region These vertices are to
be binded to OGL objects on the next call to update
verts
- an arraylist of vertex objectsupdate(GL2ES2)
public final com.jogamp.opengl.math.geom.AABBox getBounds()
public final boolean isDirty()
update(GL2ES2)


Another letter arrives from Max Décharné, wit, sage, and originator of the well-known catchphrase “Well, tie me to a tree and call me Barry”. Max writes to say that, in his recent reading, he learned of the now-neglected British surrealist painter Robin Ironside. “When he wasn't designing the four-foot obelisk in Sevenhampton churchyard which commemorates Ian Fleming,” writes Max, “Ironside painted pictures with titles that might appeal to you.” They do, they do. Here are the titles of six paintings from the 1940s:
Street Entertainer Playing Threatening Music To A Cinema Queue
A Picture To Prove That The Greeks Only Painted With Three Colours
Wounded Man In Bed-sitting Room
Crowd Awaiting A Portent
Famous Statues Visiting A Museum Of People
Patients Suffering From Waxy Insensibility
I have not been able to track down any reproductions on the web: perhaps an enthusiastic reader can do further research?


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{% extends "layout.html" %} {% block head %}
{{ message }} You will be redirected to homepage in 2 seconds


Looks like someone left you a tip :) You can withdraw your tip or use it to tip others by Authenticating via Twitter


Cultural Reflections
Reflection Blog
Time and Habits
Emotional Intelligence
Meditation Process
Mindful Conversations
Self-Confidence
Control
Motivation
Connecting
Leadership
Technical Reflections
DOM Part 1
DOM Part 2
Design to Web Blog
JavaScript Basics
Problem-Solving
JavaScript Lingo
Scope


Try writing in the input field:
The input's valid state is:
The input field must not contain a future date to be considered valid.


A timeseries widget is, as its name suggests, used for visualizing changes in one or more numeric values over a specified period of time. It essentially brings a second dimension to the KPI widget use-case of displaying values of one or more metrics at a specific moment in time, i.e. the present. The following example exhibits an admittedly contrived scenario of comparing the reported primary leisure activity of Solarians over a seven-day period. The data is made up and makes absolutely no sense, but it's all in good fun.
The default visualization for the timeseries widget is Line. To change the visualization presented by the widget,
set the widget's pizzagna.configuration.chart.properties.configuration.preset
property to a value of type
TimeseriesChartPreset
.
For a look at how to configure it in the context of a functioning widget, see the widget configurations in the
source expanders of the examples on this page.
Continuous numeric values can be visualized as lines, areas, or bars along a time progression. Data
sources for these visualizations should provide series data that conform to the
ITimeseriesWidgetSeriesData
interface in their output. Open the source expander of the following example to see how this looks.
Discrete state values can be visualized as horizontal bars of variable length and color along a time
progression. Data sources for the Status Bar visualization must provide their series data in a
slightly different format from that of the other timeseries visualization types shown above. In this
case, the series data should conform to the
ITimeseriesWidgetStatusData
interface which extends
ITimeseriesWidgetSeriesData
with three additional properties:
color
: string or css variable for the color to use for the fill color of the associated baricon
: string value for the name of the icon to display on the bar as well as the legendthick
: boolean for whether or not to display a "thick" bar ("false" is typically used for an "ok" status)TimeseriesScaleType.Time
)
applyStatusEndpoints
function to prepend and append the filtered status data with endpoints that match the start
and end datetimes of the zoomed time period. This will ensure that each status visualization has
valid start and end values after the chart is zoomed.
TimeseriesScaleType.TimeInterval
)
applyStatusEndpoints
function
mentioned for continuous scales above does not need to be used.
For better clarity on these usage notes, see the inline comments in the source expander of the example below.
The line chart below show how to use the UrlInteractionHandler
to handle interactions that occur on the legend when the chart is set to interactive.
The stacked bar chart below shows how individual series can be interactive when the series data has value for:
link
: string used for the legends label link.secondaryLink
: string used for the legends secondary description link.Look at the inline comments in the source expander to see how the UrlInteractionHandler
is set up and configured.
The code listings below are the source files for the Timeseries widget definition with inline comments describing the parts that compose the standard Timeseries widget type. It includes the widget's definition as well as its corresponding configurator form for defining how to configure (create/edit) the widget.
This part shows the actual widget definition. It includes, among other things, the components and providers that compose the widget itself.
This part shows the form that's used for configuring (creating/editing) the widget.
chartColors
property on the widget's
configuration
input
(ITimeseriesWidgetConfig
).
For how to do this, take a look at the inline comment in the example's source expander above.
scales
property of the configuration
input. Supported scales are enumerated in the
TimeseriesScaleType
type.


EBD - Easton Bible DIctionary
Widows
WIDOWS
"WIDOWS "to be treated with kindness (
Exodus 22:22
;
Deuteronomy 14:29
;
16:11, 14
;
24:17, 19-21
;
26:12
;
27:19
, etc.). In the New Testament the same tender regard for them is inculcated (
Acts 6:1-6
;
1 Timothy 5:3-16
) and exhibited.
"WIDOWS "to be treated with kindness (Exodus 22:22; Deuteronomy 14:29; 16:11, 14; 24:17, 19-21; 26:12; 27:19, etc.). In the New Testament the same tender regard for them is inculcated (Acts 6:1-6; 1 Timothy 5:3-16) and exhibited.


Blockchain Length:
{{.BlockchainLength}}
Highest Block Length Received:
{{.HighestBlockLengthReceived}}
Epoch Duration:
{{.EpochDuration | formatMilliSeconds}}
Slot Duration:
{{.SlotDuration | formatMilliSeconds}}
Slots Per Epoch:
{{.SlotsPerEpoch}}
Ledger Merkle Root:
{{.LedgerMerkleRoot}}
Accounts:
{{.NumAccounts}}
Peers:
{{range $peer := .Peers}}
- {{$peer}} ({{ipToCountry $peer}})
{{end}}
Peer Count:
{{.PeersCount}}
Sync Status:
{{.SyncStatus}}
Uptime:
{{.Uptime | formatSeconds}}


#include <ParticleUniverseJetAffector.h>
Public Member Functions | |
| JetAffector (void) | |
| virtual | ~JetAffector (void) |
| DynamicAttribute * | getDynAcceleration (void) const |
| void | setDynAcceleration (DynamicAttribute *dynAcceleration) |
| virtual void | _affect (ParticleTechnique *particleTechnique, Particle *particle, Ogre::Real timeElapsed) |
| virtual void | copyAttributesTo (ParticleAffector *affector) |
Static Public Attributes | |
| static const Ogre::Real | DEFAULT_ACCELERATION = 1.0f |
Protected Attributes | |
| Ogre::Real | mScaled |
| DynamicAttribute * | mDynAcceleration |
| DynamicAttributeFactory | mDynamicAttributeFactory |
| ParticleUniverse::JetAffector::JetAffector | ( | void | ) |
| ParticleUniverse::JetAffector::~JetAffector | ( | void | ) | [virtual] |
| DynamicAttribute* ParticleUniverse::JetAffector::getDynAcceleration | ( | void | ) | const [inline] |
| void ParticleUniverse::JetAffector::setDynAcceleration | ( | DynamicAttribute * | dynAcceleration | ) |
| void ParticleUniverse::JetAffector::_affect | ( | ParticleTechnique * | particleTechnique, | |
| Particle * | particle, | |||
| Ogre::Real | timeElapsed | |||
| ) | [virtual] |
Affect a particle.
| particle | Pointer to a ParticleTechnique to which the particle belongs. | |
| particle | Pointer to a Particle. | |
| timeElapsed | The number of seconds which have elapsed since the last call. |
Implements ParticleUniverse::ParticleAffector.
| void ParticleUniverse::JetAffector::copyAttributesTo | ( | ParticleAffector * | affector | ) | [virtual] |
Copy attributes to another affector.
Reimplemented from ParticleUniverse::ParticleAffector.
Ogre::Real ParticleUniverse::JetAffector::mScaled [protected] |
Dynamic attribute used to generate the velocity of a particle.
Helper factory
const Ogre::Real ParticleUniverse::JetAffector::DEFAULT_ACCELERATION = 1.0f [static] |


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Vidyo technology is end-point aware and understands the impact of network speed, screen resolution, and CPU load on the service.
The technology also actively optimises the video stream for each device to produce the best possible experience, and it is also completely platform agnostic.
This means it supports virtually any device with a camera and Internet connection.
Quick and affordable
What makes Connection Telecom’s video conferencing solution particularly attractive to businesses is its cost-effective scalability.
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A video conference can be set up in moments and accepting meeting requests can be done via email.
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For more information, visit: Connection Telecom Cloud Video Conferencing
This article was published in partnership with Connection Telecom.


Dry,
Tomorrow, we’ll be joined by hundreds of activists outside the Supreme Court to support the Affordable Care Act’s birth control benefit, which is being challenged by two for-profit companies trying to get out of providing contraception to their employees. We’ll also be delivering thousands of petitions to the Court [ http://feminist.org/blog/index.php/2014/03/24/feminist-majority-foundation-to-deliver-thousands-of-petitions-to-the-supreme-court-tomorrow-in-support-of-the-aca-birth-control-benefit/?preview=true&preview_id=10517&preview_nonce=07fcc93803 ] supporting birth control access for millions of women.
*RSVP for the rally today* [ http://org.salsalabs.com/o/1400/p/salsa/event/common/public/?event_KEY=81499 ]* and **sign the petition now* [ http://www.change.org/petitions/tell-the-supreme-court-let-women-not-bosses-decide ]* to be among the thousands of voices heard at the Supreme Court tomorrow!*
[ http://org.salsalabs.com/o/1400/p/salsa/event/common/public/?event_KEY=81499 ]
The ACA birth control benefit requires insurance companies to cover all FDA-approved contraceptives as part of preventive care, meaning millions of women can now access birth control without having to pay copays, coinsurance, or deductibles. But tomorrow, the Court will hear from two for-profit companies that claim they should not have to follow the law because they disagree with some forms of contraception.
*Women, not bosses, should make their own personal decisions about birth control. **RSVP today to join [ http://org.salsalabs.com/o/1400/p/salsa/event/common/public/?event_KEY=81499 ] us outside the Court tomorrow and stand up for contraceptive access [ http://org.salsalabs.com/o/1400/p/salsa/event/common/public/?event_KEY=81499 ]. (*If you’re not able to make it, take a minute to sign our petition to the Court [ http://www.change.org/petitions/tell-the-supreme-court-let-women-not-bosses-decide ] and tell your story on Twitter using the hashtag!)
1600 Wilson Boulevard, Suite 801, Arlington, VA, 22209 |<PHONE_NUMBER> |<EMAIL_ADDRESS>You have received this e-mail because of your interest in women’s issues. To unsubscribe, please click here. [ http://org.salsalabs.com/o/1400/p/salsa/supporter/unsubscribe/public/index.sjs?unsubscribe_page_KEY=494 ]


This is a [[StateBuilder.builder]] function for ngModule lazy loading in Angular.
When the [[StateBuilder]] builds a [[State]] object from a raw [[StateDeclaration]], this builder
decorates the lazyLoad property for states that have a [[Ng2StateDeclaration.ngModule]] declaration.
If the state has a [[Ng2StateDeclaration.ngModule]], it will create a lazyLoad function
that in turn calls loadNgModule(loadNgModuleFn).
This is a [[StateBuilder.builder]] function for ngModule lazy loading in Angular.
When the [[StateBuilder]] builds a [[State]] object from a raw [[StateDeclaration]], this builder decorates the
lazyLoad
property for states that have a [[Ng2StateDeclaration.ngModule]] declaration.If the state has a [[Ng2StateDeclaration.ngModule]], it will create a
lazyLoad
function that in turn callsloadNgModule(loadNgModuleFn)
.Example:
A state that has a
ngModule
var decl = { ngModule: () => import('./childModule.ts') }
would build a state with a
lazyLoad
function like:import { loadNgModule } from "@uirouter/angular"; var decl = { lazyLoad: loadNgModule(() => import('./childModule.ts') }
If the state has both a
ngModule:
and alazyLoad
, then thelazyLoad
is run first.Example:
var decl = { lazyLoad: () => import('third-party-library'), ngModule: () => import('./childModule.ts') }
would build a state with a
lazyLoad
function like:import { loadNgModule } from "@uirouter/angular"; var decl = { lazyLoad: () => import('third-party-library') .then(() => loadNgModule(() => import('./childModule.ts')) }


puppet agent
Retrieves the client configuration from a Puppet server and applies it to the local host.
More information: home page
- Register a node at a Puppet server and apply the received catalog:
puppet agent --test --server puppetserver_fqdn --serverport port --waitforcert poll_time
- Run the agent in the background (uses settings from `puppet.conf`):
puppet agent
- Run the agent once in the foreground, then exit:
puppet agent --test
- Run the agent in dry-mode:
puppet agent --test --noop
- Log every resource being evaluated (even if nothing is being changed):
puppet agent --test --evaltrace
- Disable the agent:
puppet agent --disable "message"
- Enable the agent:
puppet agent --enable


In Andaman & Nicobar, IndiGo flies to Port Blair.
Health Screening:
Quarantine:
Passenger Obligation:
In Andhra Pradesh, IndiGo flies to Kurnool, Rajahmundry, Tirupati, Vijayawada, Visakhapatnam.
Health Screening:
Domestic: Thermal screening shall be done for all passengers.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines https://www.goindigo.in/information/international-travel-guidelines.html
Quarantine:
International Passengers: For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
International Passengers: For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Domestic:
All passengers are required to register themselves on Spandana website www.spandana.ap.gov.in
All passengers must download Aarogya Setu App.
In Assam, IndiGo flies to Dibrugarh, Guwahati, Jorhat, Silchar.
Health Screening:
Thermal screening will be conducted upon arrivals
COVID swab test will be conducted upon arrivals. Antigen test available in GAU.
Quarantine:
Thermal screening will be conducted upon arrivals
COVID swab test will be conducted upon arrivals. Antigen test available in GAU.
Passenger Obligation:
Exception to Quarantine and COVID test:
In Bihar, IndiGo flies to Gaya, Patna.
Health Screening:
Thermal screening will be conducted upon arrivals
Passengers arriving from Maharashtra, Kerala and Punjab will require RT-PCR/RAT negative report from ICMR accredited labs done within last 72hrs. RT-PCR timeline starts from the swab collection time.
Passengers without RT-PCR report will be tested at the airport.
RTPCR/RAT test will be free of cost at arrivals.
Random RAT test will be done for other sector passengers.
Quarantine:
Quarantine will be determined based on the test results.
Passenger Obligation:
All passengers must download Aarogya Setu App.
Passengers arriving from Maharashtra/Kerala and Punjab will require RT-PCR/RAT negative report from ICMR accredited labs done within last 72hrs. RT-PCR timeline starts from the swab collection time.
In Chandigarh, IndiGo flies to Chandigarh
Health Screening:
Thermal screening will be done for all passengers
Quarantine:
No quarantine.
Passenger Obligation:
Passenger is required to fill up Health Declaration form upon arrival
All passengers must download Aarogya Setu App
All passenger must register on COVA Punjab App before commencing their journey
In Chhattisgarh, IndiGo flies to Raipur.
Health Screening:
Health Profiling will be conducted upon arrivals
Quarantine:
7 days home quarantine for passengers who are residents of Chhattisgarh, Raipur. Passengers having return tickets are exempted from quarantine rule.
Passenger Obligation:
Contact details & Journey details to be shared at Covid desk.
ITS NOT MANDATORY to apply for epass.
In Delhi, IndiGo flies to Delhi.
Health Screening:
COVID Test is not required.
Thermal screening will be done for all passengers upon arrival.
Quarantine:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Domestic Passengers: 07 days of Home Quarantine.
Constitutional & Govt. functionaries and their staff members are exempted from 7 days of home quarantine.
Passenger Obligation:
Domestic Passengers:
All passengers must download Aarogya Setu App.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
In Goa, IndiGo flies to Goa.
Health Screening: None
Quarantine: None
Passenger Obligation:
All passengers must download Aarogya Setu App.
In Gujarat, IndiGo flies to Ahmedabad, Rajkot, Surat, Vadodara.
Ahmedabad:
Health Screening:
Thermal screening shall be done for all passengers
It is mandatory for passengers arriving in Surat from other states/UT to carry a negative RT-PCR report not earlier than 72 hours from an ICMR approved laboratory. RT-PCR timeline starts from the swab collection time.
For AMD, BDQ & RAJ it is mandatory for passengers arriving from Maharashtra to carry a negative RT-PCR report not earlier than 72 hours from an ICMR approved laboratory. RT-PCR timeline starts from the swab collection time.
From 12 Oct 20, AMC has started a counter at arrivals for Antigen test. This is optional and free of cost. Passengers can opt for this in case they wish to.
Quarantine:
Domestic travelers:
For Surat (STV) only: Passengers arriving from other states/UT not carrying a negative RT-PCR report will be subject to Rapid Antigen Test upon arrival (free of charge).
All travelers have to undergo mandatory quarantine at home for 7 days and to monitor their health for 14 days.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guiedlines
https://www.goindigo.in/information/international-travel-guidelines.html
It is mandatory for all international passengers arriving at Surat to fill online "Novel corona self-reporting form" and to download "SMC COVID-19 Tracker" app by clicking on below mentioned links:
Step 1(fill online self-reporting form and generate traveler ID): https://www.suratmunicipal.gov.in/EServices/Covid19SelfReporting
Step 2( download SMC covid-19 tracker app and enter traveler ID):
Passenger Obligation
All passengers must download Aarogya Setu App
For Surat (STV) only: Carry a negative RT-PCR report not earlier than 72 hours from an ICMR approved laboratory. RT-PCR timeline starts from the swab collection time.
Domestic travelers from other states arriving at Surat have to fill online "Novel corona self-reporting form" and to download "SMC COVID-19 Tracker" app.
Step 1 (Instructions for Individuals Planning to travel to Surat City): https://www.suratmunicipal.gov.in/EServices/NoteForTravellersToSuratCity
Step 2 (fill online self-reporting form and generate traveler ID: https://www.suratmunicipal.gov.in/EServices/Covid19SelfReporting
Step 3 (download SMC covid-19 tracker app and enter traveler ID): http://office.suratmunicipal.org/SMCCOVID19/Guest
Airlines Obligation
Airlines have to ensure that all passengers fill online self-declaration form prior to arrival at Surat airport.
Ensure the availability of arriving passenger data to SMC Officers.
Providing the hard copy of Passenger Manifest to on duty SMC officers at Surat Airport regarding arriving passengers on timely manner.
Sending soft copy of Passenger Manifest to SMC commissioner on daily basis on below mail:
Airport/State obligation
Thermal screening shall be done for all passengers
For Surat (STV) only :Test passengers without RT-PCR report for Rapid Antigen Test.
Health Screening:
Quarantine:
No Quarantine
Passenger Obligation:
All passengers must download Aarogya Setu App.
Health Screening
Quarantine
No quarantine
Passenger Obligation
All passengers must download Aarogya Setu App.
In Jammu & Kashmir, IndiGo flies to Jammu, Srinagar.
Health Screening:
RT-PCR test is mandatory for all passengers, except
Quarantine:
No institutional quarantine now. Pax if tested positive will be sent for 14 days home quarantine.
Please visit State Government’s website for detailed Quarantine Regulations.
Passenger Obligation:
In Jharkhand, IndiGo flies to Ranchi.
Health Screening:
Mandatory thermal screening will be conducted for all passengers arriving from Maharashtra, Kerala & Telangana.
Symptomatic passengers will be tested for RT-PCR/TRUENAT & if found positive will be home isolated.
Passengers arriving from Maharashtra, Kerala & Telangana are advised to carry a RT-PCR/TRUENAT negative report from ICMR approved lab not earlier than 72 hours. RT-PCR timeline starts from the swab collection time. Passengers arriving without negative RT-PCR report will be subject to RT-PCR report / fill up self-declaration form.
Quarantine:
Symptomatic passengers will be tested for RT-PCR/TRUENAT and if found positive will be advised for home isolation.
Passenger Obligation:
In Karnataka, IndiGo flies to Belagavi, Bengaluru, Hubli, Mangaluru, Mysuru.
Passenger Obligation: It is MANDATORY for passengers arriving from Kerala, Maharashtra, Punjab & Chandigarh to carry a COVID negative report from an ICMR approved lab not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Health Screening: It is MANDATORY for passengers arriving from Kerala, Maharashtra, Punjab & Chandigarh to carry a COVID negative report from an ICMR approved lab not earlier than 72 hours. RT-PCR timeline starts from the swab collection time. This is a requirement by the Govt. of Karnataka.
Quarantine: None
All passengers shall be required to register their details on Generate e-Pass
In Kerala, IndiGo flies to Kannur, Kochi, Kozhikode, Thiruvananthapuram
Health Screening:
Quarantine:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Domestic Passengers:
14 days of Home Quarantine for all passengers
Exception to Quarantine:
Passengers who visit the State for a short period for purposes like business, official, trade, medical, court cases, property management or any like purposes will be exempted. Government have allowed them to visit the State for a period up to 7 days without mandatory quarantine ONLY after obtaining entry passes through covid19jagratha portal. They shall provide the details of local itinerary along with the purpose of visit and local accommodation and contact person. Any deviations from this, during visit, shall be informed to the authorities with valid reasons.
Passenger Obligation:
In Ladakh, IndiGo flies to Leh.
Health Screening:
Thermal screening shall be done for all passengers.
Negative RT-PCR report on arrival (not earlier than 96 hours prior to arrival) is required for all passengers arriving into Leh. RT-PCR timeline starts from the swab collection time.
Quarantine:
If passengers are not carrying negative RT-PCR report, then mandatory 7 days of home quarantine. COVID test may be conducted at the end of quarantine period.
Passengers may have to be tested for COVID & if tested positive, passengers will be transferred to COVID facility for further processing.
If test report is negative then the passengers shall be released from mandatory quarantine.
Exception: Personal of Defense & Central Armed Police are exempted from above provisions.
Passenger Obligation:
All passengers must download Aarogya Setu App
COVID negative report (not earlier than 72 hours of arrival) are MANDATORY for entry into Ladakh.
In Madhya Pradesh, IndiGo flies to Bhopal, Indore, Jabalpur.
Indore:
Health Screening:
Quarantine:
Passenger Obligation:
Airlines Obligation: None.
Airport/State obligation:
Bhopal:
Health Screening:
Quarantine :
Passenger Obligation:
Airlines Obligation: None.
Airport/State obligation:
In Manipur, IndiGo flies to Imphal.
Health Screening:
Thermal screening will be conducted for all passengers
COVID test will be done free of cost for all passengers arriving from the states of Maharashtra, Kerala, Chhattisgarh, MP and Gujarat.
Quarantine:
COVID protocols will be followed for passengers testing positive.
Passenger Obligation:
All passengers must download Aarogya Setu App
For latest update on guidelines click here
In Maharashtra, IndiGo flies to Aurangabad, Kolhapur, Mumbai, Nagpur, Pune, Shirdi.
Aurangabad:
Health Screening:
Thermal screening shall be done for all passengers
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
No quarantine & hand stamping for asymptomatic passenger
Passenger Obligation
All passengers must download Aarogya setu App
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours before scheduled time of landing. RT-PCR timeline starts from the swab collection time.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
Pune:
Health Screening:
Thermal screening shall be done for all passengers.
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
No quarantine & hand stamping for asymptomatic passenger
Passenger Obligation:
All passengers must download Aarogya setu App
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
Shirdi:
Health Screening:
Thermal screening shall be done for all passengers.
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
Passenger Obligation:
All passengers must download Aarogya setu App
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
Nagpur:
Health Screening:
Thermal screening shall be done for all passengers
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
Passenger Obligation:
All passengers must download Aarogya setu App
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
Mumbai:
Health Screening:
Thermal screening shall be done for all passengers.
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Domestic Passengers: No quarantine & hand stamping for asymptomatic passenger
Passenger Obligation:
All passengers must download Aarogya setu App
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours before scheduled time of landing.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Kolhapur:
Health Screening: None
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine: No quarantine & hand stamping for asymptomatic passenger
Passenger Obligation:
All passengers must download Aarogya setu App.
Mandatory for passengers arriving from NCR/DELHI, Kerala, Rajasthan, Gujarat & Goa to carry RT-PCR report not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Passenger not having RT-PCR report must undergo RT-PCR test at the airport at their own expense.
Submit contact details with authorities, in case the test result come positive the state officials will contact.
In Meghalaya, IndiGo flies to Shillong.
Health Screening:
RT-PCR test for all arriving passengers on chargeable basis incase passenger is not carrying a negative COVID-19 report on arrival not earlier than 72 hours. RT-PCR timeline starts from the swab collection time.
Quarantine:
If tested positive, passengers will be transferred to COVID facility for further processing.
Passenger Obligation:
All Passengers need to have valid m-pass which can be obtained by applying online on State website: Generate m-Pass
In Mizoram, IndiGo flies to Aizawl.
Aizawl:
Health Screening:
Quarantine:
Passenger Obligation:
Airlines Obligation: Simplification process is being drafted by Govt. of Mizoram & till the time is not rolled out commercial airlines operating to AJL airport are requested to allow their passengers holding a valid ticket to board the flight even if they do not have a valid mPASS.
In Nagaland, IndiGo flies to Dimapur.
Health Screening:
Thermal screening will be conducted for all passengers
Quarantine:
07 days of Institutional Quarantine followed by 14 days of Home Quarantine for all passengers
Exception to Institutional Quarantine:
Below categories of passengers shall be exempted from Institutional Quarantine subject to 28 days of Home Quarantine with active surveillance
Passenger Obligation:
All passengers must download Aarogya Setu App.
In Odisha, IndiGo flies to Bhubaneswar.
Health Screening:
Mandatory Antigen test for all passengers above the age of 55 years.
Screening as per COVID protocol & on-site Rapid Antigen Test for all symptomatic passengers arriving from the states of Maharashtra, Kerala, Tamilnadu, Chhattisgarh, Maharashtra, Kerala, Madhya Pradesh, Punjab & Chhattisgarh.
Quarantine: 7 days of mandatory home isolation for all passengers arriving from the states of Maharashtra, Kerala, Madhya Pradesh, Punjab & Chhattisgarh.
Exception: For asymptomatic passengers who have a RT-PCR negative report not earlier than 72 hours or a COVID vaccination Final Certificate. RT-PCR timeline starts from the swab collection time.
Passenger Obligation:
All passengers must download Aarogya Setu App.
In Punjab, IndiGo flies to Amritsar.
Amritsar:
Health Screening:
Thermal screening will be conducted for all passengers
Quarantine:
Domestic Passengers: No Quarantine.
International Passengers:
International travelers arriving in Punjab to be tested by RAT kits at airport in case of unavailability of RTPCR report for test conducted within 96hrs of arrival (Pax travelling to India).Home quarantine will be there for next 07 days.
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
Domestic Passengers :
All passengers must download Aarogya Setu App
All passenger must register on COVA Punjab App before commencing their journey
In Rajasthan, IndiGo flies to Jaipur, Jodhpur, Udaipur.
Jaipur, Jodhpur & Udaipur:
Health Screening:
Quarantine:
Passenger Obligation:
All passengers travelling to Tamil Nadu shall be required to register on State website and obtain TN e-pass- Generate e-Pass
In Tamil Nadu, IndiGo flies to Chennai, Coimbatore, Madurai, Tiruchirappalli, Tuticorin.
Health Screening:
Domestic & International:
For passenger arriving in CJB, following shall apply
Customers who undergo test on arrival and are.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
The State Government has clarified that RT PCR test is mandatory on arrival airport to the passenger's (Including Air Crews) who are arriving from United Kingdom to Tamilnadu
Quarantine:
Domestic:
07 days of Home Quarantine & 07 days of self monitoring for all passengers arriving into Tamil Nadu from Maharashtra & Kerala.
14 days of self monitoring for all passengers arriving into Tamil Nadu from other states/UT.
Business travelers coming to Tamil Nadu for short stay (less than 72 hours) are exempted from home quarantine. Not applicable for passengers arriving into CJB.
Symptomatic passengers will be required to go for Institutional Quarantine till the time COVID test results are available, at the discretion of Health Officials. Post which they will be required to complete remaining period of Home Quarantine.
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
Domestic:
All customers coming from other states/UTs/countries are mandatorily required to obtain auto generated e-Pass through https://tnepass.tnega.org/#/user/pass
All passengers must download Aarogya Setu App
International:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
In Telangana, IndiGo flies to Hyderabad.
Health Screening:
Thermal screening shall be done for all passengers.
Quarantine:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
In Tripura, IndiGo flies to Agartala.
Health Screening :
Quarantine :
All Symptomatic passenger shall undergo 14 days Quarantine.
Asymptomatic passengers are exempted from quarantine.
Passenger Obligation:
In Uttarakhand, IndiGo flies to Dehradun.
Dehradun:
Health Screening:
Quarantine:
No quarantine for travelers coming to Uttarakhand with stay less than 7 days. Visitors will provide residence/stay address to authorities.
Home quarantine for visitors coming for more than 7 days.
10 days of Institutional quarantine for Army & paramilitary personal.
Govt official from state & center, Judges of Supreme & High court and other judicial officers, MP’s & MLA of Utarakhand & support staff are exempted from quarantine.
All passengers will be exempted from home quarantine if they arrive with RT-PCR/TrueNAT/CBNAAT/Antigen test with negative report mot more than 96hrs before arrival. This is not mandatory.
If the passenger is found positive necessary protocols laid down by state authorities will be followed.
Passenger Obligation:
In Uttar Pradesh, IndiGo flies to Agra, Gorakhpur, Lucknow, Prayagraj, Varanasi.
Health Screening:
Thermal screening will be done for all passengers.
Passengers arriving from Kerala and Maharashtra will require RT-PCR negative report from ICMR accredited labs done within last 72hrs. RT-PCR timeline starts from the swab collection time.
Varanasi : For passengers arriving in Varanasi from Maharashtra & Kerala below shall apply.
If the passengers are not carrying the RT-PCR negative report, then they will undergo the “RAPID ANTIGEN TEST” at Varanasi Airport.
Any passengers found with SYMPTOMS and not carrying the RT-PCR negative report will only undergo “RT-PCR test” at Varanasi Airport.
Both RAPID ANTIGEN & RT-PCR test will be free of cost by the state authorities.
Quarantine:
Domestic passengers: 14 days of Home Quarantine
Exception to Quarantine:
Passengers exiting Uttar Pradesh within 7 days of arrival shall be exempted from mandatory quarantine subject to validation of return/onward travel.
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
Passengers arriving from Kerala and Maharashtra will require RT-PCR negative report from ICMR accredited labs done within last 72hrs. RT-PCR timeline starts from the swab collection time.
Passenger will need to register on state website before they exit the arrival hall using below web link or phone number
Web Link : https://reg.upcovid.in or call 1800-180-5145
Passengers exiting Uttar Pradesh within 7 days of arrival shall be exempted from mandatory quarantine subject to validation of return/onward travel
All passengers must download Aarogya Setu App
In West Bengal, IndiGo flies to Bagdogra, Durgapur, Kolkata.
Bagdogra & Kolkata:
Health Screening:
Quarantine:
14 days of Self-monitoring for all asymptomatic passengers is advised.
For symptomatic passengers, the Health Authorities will decide the Quarantine requirement on case basis
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html
Passenger Obligation:
Domestic Passengers
All passengers must download Aarogya Setu App
All passengers must fill up and submit the declaration form using Sandhane App developed by H&FW Department West Bengal.
It is MANDATORY for passengers arriving from Kerala, Maharashtra, Karnataka & Telangana to carry a RT-PCR negative report from an ICMR approved lab not earlier than 72 hours into the state of West Bengal. RT-PCR timeline starts from the swab collection time.
App can be downloaded through this link http://<IP_ADDRESS>/systems/Sandhane/1.2/Sandhane_Gen.apk
International Passengers:
For international arrivals (foreign country to India) please visit the following link for detailed guidelines
https://www.goindigo.in/information/international-travel-guidelines.html


Class ProtocolState
Inheritance
System.Object
ProtocolState
Assembly: Sensus.Shared.NuGet.dll
Syntax
public sealed class ProtocolState : Enum
Fields
Paused
The protocol has been paused, which means that it is not storing data and is not registered as Running, but is
active in other ways (e.g., surveys will fire, push notifications will be received, data will be transmitted to the
remote data store.
Declaration
public const ProtocolState Paused
Field Value
Running
Declaration
public const ProtocolState Running
Field Value
Starting
Declaration
public const ProtocolState Starting
Field Value
Stopped
Declaration
public const ProtocolState Stopped
Field Value
Stopping
Declaration
public const ProtocolState Stopping
Field Value
value__
Declaration
Field Value
| Type |
Description |
| System.Int32 |
|


| Package | Description |
|---|---|
| net.glowstone.entity | |
| net.glowstone.entity.physics |
| Modifier and Type | Method and Description |
|---|---|
List<org.bukkit.entity.Entity> |
EntityManager.getEntitiesInside(BoundingBox searchBox,
GlowEntity except)
Returns all entities that are inside or partly inside the given bounding box, with optionally
one exception.
|
boolean |
GlowEntity.intersects(BoundingBox box) |
| Modifier and Type | Class and Description |
|---|---|
class |
BlockBoundingBox |
class |
EntityBoundingBox
A BoundingBox which changes position over time as an entity moves.
|
| Modifier and Type | Method and Description |
|---|---|
static BoundingBox |
BoundingBox.copyOf(BoundingBox original)
Returns a deep copy of a BoundingBox.
|
static BoundingBox |
BoundingBox.fromCorners(org.bukkit.util.Vector a,
org.bukkit.util.Vector b)
Converts two Vector instances to a BoundingBox.
|
static BoundingBox |
BoundingBox.fromPositionAndSize(org.bukkit.util.Vector pos,
org.bukkit.util.Vector size)
Creates a bounding box given its minimum corner and its size.
|
| Modifier and Type | Method and Description |
|---|---|
static BoundingBox |
BoundingBox.copyOf(BoundingBox original)
Returns a deep copy of a BoundingBox.
|
boolean |
BoundingBox.intersects(BoundingBox other)
Tests whether this intersects another bounding box.
|
static boolean |
BoundingBox.intersects(BoundingBox a,
BoundingBox b)
Tests whether two bounding boxes intersect.
|
Copyright © 2021. All rights reserved.


Photo Staff
05.28.20
Ohio University is home to many resources for students, faculty, staff, and Athens residents. These resources range from professional and academic assistance, to mental health and emotional assistance. No matter the focus, various campus centers work to make OU and Athens as successful as possible.
Several resources reside right under the roof of Baker University Center, like the Women’s Center, the LGBT Center and the Multicultural Center.
The Women’s Center (Baker 403) provides opportunities for personal and professional empowerment through an intersectional, gendered lens. Though the name indicates a resource for women, the center is open to anyone and provides programming that reflects the diversity of women’s experiences in a way that’s educational to allies as well.
Geneva Murray, director of the Women’s Center, loves to empower everyone and takes pride in engaging with visitors to the center.
“We want people to feel like when they walk into the Women’s Center, there’s a sense of calm and peace, and also fun,” Murray said. “When people engage with us, they feel like they can come in and study, hang out, make friends and anything else.”
A lot of the Women’s Center program focuses on body positivity and individual empowerment. The center’s staff also brings in domestic violence awareness speakers and annually hosts Take Back the Night, a march to end sexual violence. The center also has a wide variety of leadership development programs including the ALAANA+ Women’s Leadership Cohort, as well as women’s mentoring programs and other workshops.
The LGBT Center (Baker 354) has a similar mission to the Women’s Center and provides inclusive programming and endless opportunities for its members. The LGBT Center seeks to affirm all expressions of identity, be it gender or sexuality and encourages spreading that acceptance throughout campus.
“I think if we’re going to make our campus inclusive and safe for everybody, then it’s really allies who are part and parcel of that. Our programs are there for anybody who’s interested, and that is completely independent of individual people.”Jan Huebenthal, Assistant Director of the LGBT Center
Jan Huebenthal, the assistant director of the LGBT Center, appreciates that people feel comfortable coming into the center and hanging out. People come in and do homework, make new friends and help create a safe environment in which people can thrive.
“We practice what we call ‘radical inclusion,’ which means that when somebody walks through our door, we don’t ask questions or ask people to identify themselves,” Huebenthal said. “We’re really hoping to create a space where everyone feels safe and welcome.”
Most of the center’s programming is aimed toward educating LGBTQ+ people, allies, campus and Athens as a whole. The center does programs with Alden Library, HIV and AIDS education, and more.
The Multicultural Center (Baker 205) is another resource on campus, geared toward increasing understanding and appreciation of cultural differences by familiarizing OU and Athens with African American, Hispanic/Latino American, Asian American and Native American cultures. The center also acts as a safe space for people of those cultures. Like the LGBT Center and Women’s Center, allies are encouraged to get involved.
Winsome Chunnu-Brayda, the director of the Multicultural Center, takes pride in the programming provided through the center and space for people to come in and talk about any challenges they’re facing. Her goal is to act as an ally for those utilizing the center.
“We describe our center as a place for teaching and learning, and we provide programming training for faculty, staff and students around microaggression and implicit bias,” Chunnu-Brayda said.
Chunnu-Brayda and the Multicultural Center staff bring in speakers and performers and collaborate with other centers, as well as academic departments and local organizations, for events. The staff especially likes to provide programming revolving around specific heritage months like Hispanic Heritage Month, American Indian Heritage Month, Black History Month Asian Pacific Islander Heritage Month and others.
Though most of the programming from each center is geared toward the groups it represents, each center prides itself on being inclusive toward all people, especially allies. Anyone is welcome and encouraged to participate in and support these centers.
“I think if we’re going to make our campus inclusive and safe for everybody, then it’s really allies who are part and parcel of that,” Huebenthal said. “Our programs are there for anybody who’s interested, and that is completely independent of individual people.”
These centers are just three examples of a plethora of resources within Baker and on campus. Whether someone is a part of a group a center represents, allies or just curious, Murray, Huebenthal and Chunnu-Brayda all encourage people to get involved.
“In the beginning of the school year, I’m always so excited to see our incoming class,” Chunnu-Brayda said. “But also our students who are in their second, third, fourth or even fifth year, who have never been to the center, so I am always particularly excited in the fall to see all of the new faces and the excitement around people coming into the space. I’m hoping that people will come in.”
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Just write code in the editor, that you can access through the navigation pane in the left sidebar, and then parse it using the parse button in the same sidebar.
The resulting graph will be displayed, accessible through the navigation pane too.


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While reading the Tao Te Ching, I found that certain chapters connect very well with running. In order to further connect with these chapters myself, I “translated” them into a form that directly connects with running, which is a fundamental part of my life.
This is from Chapter 2 of the Tao Te Ching; translated by Stephen Mitchell:
Seeing some runs as beautiful
makes other runs ugly
Seeing some runs as good
makes other runs bad
Running and non-running create each other
Difficult and easy runs support each other
Long and short runs define each other
A runner’s highs and lows depend on each other
The time before and after running follow each other
Therefore the Master
runs without doing anything
and instructs without saying anything
Things arise and she lets them come
Things disappear and she lets them go
She has ability without possessing it
runs without expectation
When her run is finished, she forgets it
that is why it lasts forever


This is my Project 0 Website. This has all of my classwork I think is super important that I have learned in CIT 82. I chose Github/VSCode, Search Engine Optimization, Web Development, and Bootstrap. These categories were chosen because I think that they focus on the main topics from start to finish when it comes to learning, building a site, and sharing it to the world. I chose Github/VSCode because all of my work is done on Visual Studio Code and uploaded onto Github. Bootstrap is an important topic because for this website I am using a really basic template for bootstrap and I think that its a very helpful tool to have. Web development gave me training on how to read and code using html. I also shared my work on Search Engine Optimization because I know we can make a lot of site and never publish them. I truly believe that this talks about real world problems and challenges. If you want to take a look at my work and my thought process this is the place to be! Take a look at my Github linked below to see all the code I have used to build this site!


Simplistic site to improve the way we can organise our saved repositories and keep up-to-date with important changes. Also consolidates code from various online hosting services for ease of use.
List of Libraries Used
{% for repository in used %}
{% if repository.host == 'github' %}


Remove a package
npm rm <name> npm r <name> npm uninstall <name> npm un <name>
This uninstalls a package, completely removing everything npm installed on its behalf.
npm-rm — npm@1.4.4