Peter Rabbit and Other Stories
by Beatrix Potter
“The Pie and the Patty-Pan”
Additional Information
- Year Published: 0
- Language: English
- Country of Origin: England
- Source: Beatrix Potter, The Great Big Treasury of Beatrix Potter
-
Readability:
- Flesch–Kincaid Level: 4.0
- Word Count: 2,128
- Genre: Fantasy
- ✎ Cite This
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Pussycat sits by the fire—how should she be fair?
In walks the little dog—says “Cat are you there?
How do you do Mistress Kitty? Mistress Cat, how
do you do?”
“I thank you kindly, little dog, I fare as well as you!”
Once upon a time there was a Pussycat called Ribby, who invited a little dog called Duchess to tea.
“Come in good time, my dear Duchess,” said Ribby’s letter, “and we will have something so very nice. I am baking it in a pie-dish—a pie-dish with a pink rim. You never tasted anything so good!  I will eat muffins, my dear Duchess!” wrote Ribby.
“I will come very punctually, my dear Ribby,” wrote Duchess; and then at the end she added—“I hope it isn’t mouse?”
And then she thought that did not look quite polite; so she scratched out “isn’t mouse” and changed it to “I hope it will be fine,” and she gave her letter to the postman.
But she thought a great deal about Ribby’s pie, and she read Ribby’s letter over and over again.
“I am dreadfully afraid it WILL be mouse!” said Duchess to herself—“I really couldn’t, COULDN’T eat mouse pie. And I shall have to eat it, because it is a party. And MY pie was going to be veal and ham. A pink and white pie-dish! And so is mine; just like Ribby’s dishes; they were both bought at Tabitha Twitchit’s.”
Duchess went into her larder and took the pie off a shelf and looked at it.
“Oh what a good idea! Why shouldn’t I rush along and put my pie into Ribby’s oven when Ribby isn’t there?”
Ribby in the meantime had received Duchess’s answer, and as soon as she was sure that the little dog would come—she popped HER pie into the oven. There were two ovens, one above the other; some other knobs and handles were only ornamental and not intended to open. Ribby put the pie into the lower oven; the door was very stiff.
“The top oven bakes too quickly,” said Ribby to herself.
Ribby put on some coal and swept up the hearth. Then she went out with a can to the well, for water to fill up the kettle.
Then she began to set the room in order, for it was the sitting-room as well as the kitchen.
When Ribby had laid the table she went out down the field to the farm, to fetch milk and butter.
When she came back, she peeped into the bottom oven; the pie looked very comfortable.
Ribby put on her shawl and bonnet and went out again with a basket, to the village shop to buy a packet of tea, a pound of lump sugar, and a pot of marmalade.
And just at the same time, Duchess came out of HER house, at the other end of the village.
Ribby met Duchess half-way down the street, also carrying a basket, covered with a cloth. They only bowed to one another; they did not speak, because they were going to have a party.
As soon as Duchess had got round the corner out of sight—she simply ran! Straight away to Ribby’s house!
Ribby went into the shop and bought what she required, and came out, after a pleasant gossip with Cousin Tabitha Twitchit.
Ribby went on to Timothy Baker’s and bought the muffins. Then she went home.
There seemed to be a sort of scuffling noise in the back passage, as she was coming in at the front door. But there was nobody there.
Duchess in the meantime, had slipped out at the back door.
“It is a very odd thing that Ribby’s pie was NOT in the oven when I put mine in! And I can’t find it anywhere; I have looked all over the house. I put MY pie into a nice hot oven at the top. I could not turn any of the other handles; I think that they are all shams,” said Duchess, “but I wish I could have removed the pie made of mouse! I cannot think what she has done with it? I heard Ribby coming and I had to run out by the back door!”

Ribby—having assured herself by careful search that there was really no one hiding in the cupboard or in the larder—went upstairs to change her dress.
She came downstairs again, and made the tea, and put the teapot on the hob. She peeped again into the BOTTOM oven, the pie had become a lovely brown, and it was steaming hot.
She sat down before the fire to wait for the little dog. “I am glad I used the BOTTOM oven,” said Ribby, “the top one would certainly have been very much too hot.”
Very punctually at four o’clock, Duchess started to go to the party.
At a quarter past four to the minute, there came a most genteel little tap-tappity. “Is Mrs. Ribston at home?” inquired Duchess in the porch.
“Come in! And how do you do, my dear Duchess?” cried Ribby. “I hope I see you well?”
“Quite well, I thank you, and how do YOU do, my dear Ribby?” said Duchess.  Yes, it is mouse and bacon!”
“I think it wants another five minutes,” said Ribby. “Just a shade longer; I will pour out the tea, while we wait. Do you take sugar, my dear Duchess?”
“Oh yes, please! My dear Ribby; and may I have a lump upon my nose?”
“With pleasure, my dear Duchess.”
Duchess sat up with the sugar on her nose and sniffed—
“How good that pie smells! I do love veal and ham—I mean to say mouse and bacon—”
She dropped the sugar in confusion, and had to go hunting under the tea-table, so did not see which oven Ribby opened in order to get out the pie.
Ribby set the pie upon the table; there was a very savory smell.
Duchess came out from under the tablecloth munching sugar, and sat up on a chair.
“I will first cut the pie for you; I am going to have muffin and marmalade,” said Ribby.
“I think”—(thought Duchess to herself)—“I THINK it would be wiser if I helped myself to pie; though Ribby did not seem to notice anything when she was cutting it. What very small fine pieces it has cooked into! I did not remember that I had minced it up so fine; I suppose this is a quicker oven than my own.”
The pie-dish was emptying rapidly! Duchess had had four helps already, and was fumbling with the spoon.
“A little more bacon, my dear Duchess?” said Ribby.

“Oh, I didn’t put one in, my dear Duchess,” said Ribby; “I don’t think that it is necessary in pies made of mouse.”
Duchess fumbled with the spoon— “I can’t find it!” she said anxiously.
“There isn’t a patty-pan,” said Ribby, looking perplexed.
“Yes, indeed, my dear Ribby; where can it have gone to?” said Duchess.
Duchess looked very much alarmed, and continued to scoop the inside of the pie-dish.
“I have only four patty-pans, and they are all in the cupboard.”
Duchess set up a howl.
“I shall die! I shall die! I have swallowed a patty-pan!  Fetch Dr. Maggotty, my dear Ribby: he is a Pie himself, he will certainly understand.”
Ribby settled Duchess in an armchair before the fire, and went out and hurried to the village to look for the doctor.
She found him at the smithy.
Ribby explained that her guest had swallowed a patty-pan.
Dr. Maggotty hopped so fast that Ribby had to run. It was most conspicuous. All the village could see that Ribby was fetching the doctor.
But while Ribby had been hunting for the doctor—a curious thing had happened to Duchess, who had been left by herself, sitting before the fire, sighing and groaning and feeling very unhappy.
“How COULD I have swallowed it! Such a large thing as a patty-pan!”
She sat down again, and stared mournfully at the grate. The fire crackled and danced, and something sizz-z-zled!
Duchess started! She opened the door of the TOP oven;—out came a rich steamy flavor of veal and ham, and there stood a fine brown pie,— and through a hole in the top of the pie-crust there was a glimpse of a little tin patty-pan!
Duchess drew a long breath—
“Then I must have been eating MOUSE! . . . No wonder I feel ill. . . . But perhaps I should feel worse if I had really swallowed a patty-pan!” Duchess reflected—“What a very awkward thing to have to explain to Ribby! I think I will put MY pie in the back-yard and say nothing about it. When I go home, I will run round and take it away.” She put it outside the back-door, and sat down again by the fire, and shut her eyes; when Ribby arrived with the doctor, she seemed fast asleep.
“I am feeling very much better,” said Duchess, waking up with a jump.
“I am truly glad to hear it! He has brought you a pill, my dear Duchess!”
“I think I should feel QUITE well if he only felt my pulse,” said Duchess, backing away from the magpie, who sidled up with something in his beak.
“It is only a bread pill, you had much better take it; drink a little milk, my dear Duchess!”
“I am feeling very much better, my dear Ribby,” said Duchess. “Do you not think that I had better go home before it gets dark?”
“Perhaps it might be wise, my dear Duchess.”
Ribby and Duchess said good-bye affectionately, and Duchess started home.  Duchess slipped through the fence, and ran round to the back of Ribby’s house, and peeped into the yard.
Upon the roof of the pig-sty sat Dr. Maggotty and three jackdaws. The jackdaws were eating piecrust, and the magpie was drinking gravy out of a patty-pan.
Duchess ran home feeling uncommonly silly!
When Ribby came out for a pailful of water to wash up the tea-things, she found a pink and white pie-dish lying smashed in the middle of the yard.
Ribby stared with amazement— “Did you ever see the like! so there really WAS a patty-pan? . . . But MY patty-pans are all in the kitchen cupboard. Well I never did! . . . Next time I want to give a party—I will invite Cousin Tabitha Twitchit!”


An eco-friendly building is one that is environmentally responsible, profitable and a healthy place to live and work. With the growing demands of energy and resources, self- sustainable houses are becoming a necessity. MindBend 2012 gives you an opportunity to provide it in an interesting, informative and creative way. .
Participants are required to present their idea of an eco friendly house. Integrate the best ancient practices with modern technology.
i. The online abstract submission
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If the model is presented, then following points should be kept in mind: i. The house should be built within the specified area of 2500 sq cm. ii. No materials will be provided by the organizers, participants can use materials of their own choice. iii. The decision of the judges will not be dependent on the perfectness of the model, but on their idea of the house. 1. Registration fee is Rs. 60/- per team.
2. The abstract should contain team name, members names, Department name and Institute name, and should not be more than 200 words.
3. An abstract should give a basic idea of the house. Images can also be included but it should be original and developed by the team using any software.
4. An abstract needs to be submitted electronically to the MindBend website on or before 20 September 2012.
5. The presentation is to be in a form of ppt. It should clearly mention your proposed ideas and design. The participants are also required to give a basic 3D idea of the house. They can either use 3D software (like autocad) or can also present a model of the house (whichever they find suitable).
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PDFDATA.io is an API providing PDF data extraction as a service. This library, pdfdata-java, is our official Java client, providing an efficient, easy-to-use model for interacting with and using PDFDATA.io from Java, as well as from any JVM-based programming language, including Scala, Clojure, Groovy, Kotlin, JRuby, Jython, and others.
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This week at EDA we dipped our toes into the world of 'JavaScript'. As we know, HTML provides basic content and structure to our webpages and CSS takes care of all the layout and styling, well JavaScript is repsonsible for our webpages interactivity and controlling all the moving parts using a selection of 'control flow statements'.
Control flow statements are sets of rules which tell the browser how to respond when different conditional statements are met. A good example would be the 'if else' statement which works by telling the computer 'if this is true, do this' otherwise, 'do this'; like when you leave the house in the morning and you think 'if it is cold outside, I will put on a jacket', otherwise 'I won't worry about it'.
Javascript stores multiple values of information in 'Objects' and 'Arrays'. The difference between the two being; arrays store all the information in a single variable, whereas objects can use multiple variables.
Another very useful tool in the JavaScript inventory are 'functions'. Functions are step-by-step processes that are saved under particular function names. When the function name is called, the process is initiated. For example, when you have your Cornflakes in a morning, there are very many steps involved; get the bowl out of the cupboard, find the cornflakes, open the box etc. We all know the steps in our head, and so when we decide to have a bowl of Cornflakes, all the steps happen seamlessly. This is 'functions' at work.
JavaScript is more challenging to learn than HTML & CSS, but where comes bigger challenges, comes greater satisfaction and so I am really looking forward to diving deeper into it JavaScript and reporting back to you. Until next time...
Cheers,


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Sick Instagram TV show boasts of Louis Vuitton model who murdered fashion rival
EXCLUSIVE: The ex-girlfriend of murdered model Harry Uzoka has slammed George Koh after he claimed he would appear on an ITV documentary after being interviewed by Ross Kemp
by Rosaleen FentonA male model jailed for life for stabbing to death his fashion rival after a row on Instagram has used the social media app to boast about an ITV Ross Kemp show he claims he will be appearing on.
George Koh knifed model Harry Uzoka in the heart after he became "obsessed" with Harry's success.
A row developed after Koh, who had modelled for Louis Vuitton, bragged he had slept with Harry's model girlfriend Ruby Campbell.
Now a post from the lag - who is behind bars at notorious Belmarsh - has been uploaded to his Instagram account in which he speaks about an ITV show.
It's his first post since December 10, 2017 and urges people to "please watch" it.
The jailbird even asks people to book a visit with him by through the Belmarsh Prison website.
The photo - uploaded on October 23 - has 113 likes.
In it, Koh wrote: "I will be going on tv @itv in early December via Belmarsh prison.
" @rosskemptv will be interviewing me in my cell. You’ll get to see my cell, questioning about my charge and simply how life is like for me in prison.
"Please watch it if you get the time or online on @itv repeat.
"I also will be launching my book and artwork to stop the young generation getting caught up in crime and instead focus on their pathways.
"I really believe it’s my must to bring back to the community, world. I’m so so sorry. Rest in peace."
Koh's boasts have been slammed by supermodel Leomie Anderson, who had previously dated Harry.
Victoria's Secret model and fashion designer, Leomie, wrote on Twitter : The boy who murdered my ex and close friend Harry Uzoka should NOT be given air time.
"Have you no respect for his family?? Please retweet to have this stopped, his family have suffered enough.
Sorry but he hasn’t even been in jail 2 years yet he’s allowed to paint himself as reformed???
"He killed him out of pure obsession and jealousy so him even speaking on the situation makes no sense to me as it’s not a path many can even relate to."
Cheyenne Joseph replied: “Book a visit to see me” like if he’s some celeb doing meet and greet. This is making me SICK."
Actor Monel Bailey added: "This is terrible. They need to have some decency and compassion for him and everyone that’s been affected.
"It’s not fair on the family and friends that new him just for to create a story line . @ITV have some respect!"
Kiss FM presenter Tinea Taylor blasted: "W** is this s***! Disgusting."
Koh and accomplice Merse Dikanda were found guilty of stabbing the model to death following a trial at the Old Bailey in August.
Koh was handed a minimum life sentence of just over 24 years in jail while Dikanda was told he must serve almost 22 years.
A third man, Jonathan Okigbo, who was convicted of manslaughter, received 14 years in prison.
Tragic Harry Uzoka, 25, died at the scene in Old Oak Road, Shepherd's Bush, London, at around 3.55pm on January 11, following the violent stabbing.
He had previously been described as 'Britain's most famous black model' and modelled for GQ and Zara.
But after Koh, who worked for Louis Vuitton, bragged he had slept with Harry's girlfriend, model Ruby Campbell, Harry said he wanted to settle the row "face to face".
The pair then arranged to meet in Shepherd's Bush, West London, on the afternoon of January 11.
Prosecutor Richard Horwell QC, said Koh and pals Jonathan Okigbo and Merse Dikanda, both 24, were armed with at least two knives and a "particularly large" machete-style blade.
During the meeting, the court heard that Koh said "are you mad?", produced two knives and stabbed Harry in the heart.
Following the trio's sentencing, grieving mum Josephine Jackson said her son's death had left a "gaping hole."
In an written statement read to the court, Miss Jackson said: "I have so much pain for the death of my Harry and I find it difficult these days to go on without him.
"His departure has left a gaping hole, a gap, a void in the family that we are all finding hard to contend with.
"He was due to start acting in a couple of upcoming movies but that chance has been take away from him.
"My son was a beautiful boy. I would give anything to change places with Harry, to take away the horror and pain that he suffered that day.
"Harry, your short life enriched the lives of many, you inspired so many people and touched them with your love.
"You will never be forgotten my wonderful boy."
The Ministry of Justice and ITV has been contacted for comment.


One of the best ways to analyze these is to view the hex of the data. Google or wikipedia the first "magic bytes" to get an idea of what the data might be.
Use strings on the data to see if there is any plain text keywords that you can Google. Example below.
Magic Byte examples
Example in Bandit 12.
Example in 21ltr: If we hexedit the file, we see a header of 1f 8b 08 00. A quick google search will show us that this is a GZ/TGZ file.
You can either use vi and go into hex mode with: :%!xxd (and go back with :%!xxd -r)
Strings Encrypted example
Example in De-Ice:
The file command told me it was just data, which didn’t help me much, so I tried strings to see if I could find anything readable in there: The string “Salted__n” looked interesting. I did a bit of Googling and found that “Salted__” is the first 8 bytes in an encrypted file created by the openssl command.


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We’re a team of passionate students and faculty staff from Belgrade, who are looking to promote the core values of EMSA. We organize various events, workshops, and lectures throughout the year with the goal of engaging students and the general populace.
Interested in working with us? We’re actively looking for partners that would be interested in organizing student exchange programs, conferences, and workshops.
Belgrade is a beautiful city located on the confluence of the Danube and Sava rivers. It is a Global City with a rich cultural heritage. Belgrade features diverse architecture, a charming Old Town district, beautiful churches and temples, many museums and important historical monuments.
The city is also famous for its vibrant nightlife. Many clubs and river barges are open until dawn and can be found throughout the city. There are rarely any significant language barriers and visitors always talks about the friendly atmosphere.
EMSA Belgrade’s base of operation is located near the heart of the city, within the Faculty of Medicine.
The University of Belgrade is one of the oldest universities in the region. The origin of the University of Belgrade can be tracked down to the beginning of the 19th century, when Dositej Obradović founded the College in 1808. Today, University of Belgrade is amongst the top 400 universities in the world, according to the most recent ranking carried out by the Shanghai Jiao Tong University, better known as the Shanghai List.
The Faculty of Medicine is one of the oldest faculties of the University of Belgrade. It was founded on December 9, 1920. Nine decades later, with 37,225 MD, 3,529 magister and 2,626 PhD obtained degree, the Faculty of Medicine is the leading institution for medical educational in Serbia and a significant player in regional terms.
Numerical data show that about 40% of Serbian medical students are taught at the Faculty, that two-thirds of clinical specialists and subspecialists diplomas are from the Faculty, and that over 60% of biomedical research projects funded by Ministry of Science are carried out at the Faculty.
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I am Shaoke Xu. I am a front-end developer, also use nodejs to develop server side. I am interesting to try new technologies. I made all the examples I did before online also checked in to github. Feel free to use it.
This website includes all the examples I did before use ReactJS and NodeJS.
This is the official Tutorial provided by ReactJS. You can get more information from tutorial
After this tutorial you should know following knowledge
// CommentBox is Custom React Class/Component name let CommentBox = React.createClass({ render(){ return (
 Hello, world! I am a CommentBox.
 ); } });
// Use <Comment author="Pete Hunt">This is my first comment</Comment> // Access this.props.author this.props.children
You can use lodash to encode or decode HTML Entity. _.escape
_.unescape
// Get inner html function getInnerHTML(){ return {__html: "
Inner HTML
"} } // Use


| scale_colour_continuous_qualitative {colorspace} | R Documentation |
Continuous ggplot2 color scales using the color palettes generated by qualitative_hcl
. These scales are provided
for completeness. It is not normally a good idea to color a continuous variable using a qualitative scale.
scale_colour_continuous_qualitative( palette = NULL, c1 = NULL, l1 = NULL, h1 = NULL, h2 = NULL, alpha = 1, rev = FALSE, begin = 0, end = 1, na.value = "grey50", guide = "colourbar", aesthetics = "colour", n_interp = 11, ... ) scale_color_continuous_qualitative( palette = NULL, c1 = NULL, l1 = NULL, h1 = NULL, h2 = NULL, alpha = 1, rev = FALSE, begin = 0, end = 1, na.value = "grey50", guide = "colourbar", aesthetics = "colour", n_interp = 11, ... ) scale_fill_continuous_qualitative(..., aesthetics = "fill")
palette |
The name of the palette to be used. Run |
c1 |
Chroma value, used for all colors in the scale. |
l1 |
Luminance value, used for all colors in the scale. |
h1 |
Beginning hue value. |
h2 |
Ending hue value. |
alpha |
Numeric vector of values in the range |
rev |
If |
begin |
Number in the range of |
end |
Number in the range of |
na.value |
Color to be used for missing data points. |
guide |
Type of legend. Use |
aesthetics |
The ggplot2 aesthetics to which this scale should be applied. |
n_interp |
Number of discrete colors that should be used to interpolate the continuous color scale. 11 will work fine in most cases. |
... |
common continuous scale parameters: 'name', 'breaks', 'labels', and 'limits'. See
|
If both a valid palette name and palette parameters are provided then the provided palette parameters overwrite the parameters in the named palette. This enables easy customization of named palettes.
library("ggplot2") # none of these examples are necessarily good ideas gg <- ggplot(iris, aes(x = Species, y = Sepal.Width, color = Sepal.Length)) + geom_jitter(width = 0.3) + theme_minimal() gg + scale_color_continuous_qualitative(palette = "Warm") gg + scale_color_continuous_qualitative(palette = "Cold", l1 = 60) gg + scale_color_continuous_qualitative(palette = "Harmonic", rev = TRUE) nx = 87 ny = 61 df <- data.frame(height = c(volcano), x = rep(1:nx, ny), y = rep(1:ny, each = nx)) ggplot(df, aes(x, y, fill=height)) + geom_raster() + scale_fill_continuous_qualitative(palette = "Dark 3") + coord_fixed(expand = FALSE)


Raheem Sterling’s emotional speech at Great Gatsby themed 25th birthday party
by Alicia AdejobiRaheem Sterling threw a lavish Great Gatsby themed party to celebrate his 25th birthday this weekend and, of course, it looked like no expenses were spared to make it a night to remember.
The Manchester City player, who earns an estimated £300,000 per week, hosted the bash at Manchester’s Hilton Hotel on Sunday night.
Posing on the red carpet with his fiancee Paige Milian, Raheem looked particularly dapper as he channelled 1920s dress in a white suit with a waistcoat and a fur-trimmed coat. Paige, with whom he shares two children, looked stunning in a champagne-coloured flapper-style gown with a white feather in her hair.
Among the A-listers in attendance including rap duo Krept & Konan, and Raheem’s Man City teammates including Gabriel Jesus who arrived with his model girlfriend Fernanda Queiroz, Fernandinho and his wife Glaucia Roza, Ederson and his pregnant wife Lais, and Ilkay Gundogan and Kyle Walker.
Inside the bash, photos from Raheem’s memorable photoshoot with GQ magazine decorated the venue, while waiters and waitresses dressed in flapper-style outfits were on-hand to dish out the bubbles. Guests could also entertain themselves in the casino room.
Joining the DJ in one room was a violinist while a live band with trumpets and drums performed on the dancefloor as Raheem showed his famous dance moves.
Somehow, he managed to avoid knocking over his nearby four-tier birthday cake while dancing and picking up money which had been sprayed on the dancefloor.
Later, the footballer delivered a speech thanking his nearest and dearest for having his back.
‘I swear to god I thank the Lord for my life, I thank the Lord for my kids’ life, Thiago, Melody, Thai-Cruz, Paige Milian, big p your bumbaclart,’ Raheem said mentioning his immediate family.
He added: ‘Of course, like everybody else, your mums are the most important thing.
‘My mum showed me the way, how to be strong, how to be wise, how to live up. Hold your way.’
Despite Man City’s defeat earlier in the day, Raheem has lots to celebrate as he and Paige recently announced they had secretly welcomed their second child together, Thai-Cruz, 11 months ago.
The couple is also parents to their eldest son Thiago, three, while Raheem has a daughter, Melody, from a previous relationship.
In a sweet tribute to her fiance on his birthday, Paige posted on Instagram: ‘HAPPY 25TH BIRTHDAYYYY BABE @sterling7 no need for a paragraph yuh done know how di ting go already. LOVE YOU MORE THAN YOU’LL EVER KNOW [sic].’
The pair got engaged in 2018 and are expected to get married in 2020.
Got a showbiz story?
If you've got a celebrity 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.


Samples for Sequence Diagram
See: Sequence Diagram syntax and features
Configuration of skinparams
skinparams.iuml
Actors and Participants
Arrows
Grouping
- alt/else
- opt
- loop
- par
- break
- critical
- group (other label)
Create and Destroy
Title & Note
Bookmarks


Using with other frameworks / libraries
Web Components built with Polymer behaves like normal HTML tags and can be used in new or existing projects regardless the JavaScript framework or library in use.
Here are some example and advice for having the Contactlab Pattern Library components working with the most common frontend solutions.
(vanilla) Javascript
This is the most simple case of use, just use any JavaScript DOM selector to get the element (like querySelector()
,
getElementByID()
, ecc.. ) and then you have access to all of the properties and methos described in the documentation.
jQuery
When accessing a DOM element using jQuery selector ( $('selector')
) it will become wrapped inside the jQuery Object, which makes easy to work with
all of the jQuery methods but since that is not a standard JavaScript API all native methods and properties of the component are not available.
You can still
"extract" the element from the jQuery Object since its basically an extended array, using the array index syntax:
On the other hand, by "extracting" the element from the jQuery Object you lose the access to the jQuery methods... so maybe it will be useful to work with vanilla Javascript :) .
React
As the official documentation points out, React and Web Components can be complimentary technologies. Since the latest version of React you can just add the component you need inside your JSX file to see it rendered and working as HTML element, if you need (as in most of the cases) to have the component to interact with React for data-bind to attributes and listen events you will need the rect-polymer NPM module to bridge between the different data models, and then you can have a full integration like this
Angular 2
We didn't tested Angular 2 with Web Components but the Vaadin team has developed an Angular directive for making easier to bridge these two libraries.


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Select the newsletter you would like to recieve
Newsletter Format


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|
VirtualSCADA
1.0
VirtualSCADA Senior Design Project
|
Public Member Functions | |
| canCollectCodeCoverage () | |
| getBinary () | |
| getNameWithVersion () | |
| getName () | |
| getVendorUrl () | |
| getVersion () | |
| hasXdebug () | |
| isHHVM () | |
| isPHP () | |
Definition at line 22 of file Runtime.php.
| canCollectCodeCoverage | ( | ) |
Returns true when the runtime used is HHVM or the runtime used is PHP + Xdebug.
Definition at line 35 of file Runtime.php.
| getBinary | ( | ) |
Returns the path to the binary of the current runtime. Appends ' –php' to the path when the runtime is HHVM.
Definition at line 46 of file Runtime.php.
| getName | ( | ) |
Definition at line 113 of file Runtime.php.
| getNameWithVersion | ( | ) |
Definition at line 105 of file Runtime.php.
| getVendorUrl | ( | ) |
Definition at line 125 of file Runtime.php.
| getVersion | ( | ) |
Definition at line 137 of file Runtime.php.
| hasXdebug | ( | ) |
Returns true when the runtime used is PHP and Xdebug is loaded.
Definition at line 151 of file Runtime.php.
| isHHVM | ( | ) |
Returns true when the runtime used is HHVM.
Definition at line 161 of file Runtime.php.
| isPHP | ( | ) |
Returns true when the runtime used is PHP.
Definition at line 171 of file Runtime.php.


Mary McKeever Carter
Republican
Retired Dexcel Composites - family-owned electronic and composite small business.
BBS - University of St Thomas, Houston, Texas. Business and Economics 1983 Certified Forms Consultant (CFC) 1981 Career in Business Forms Management in Houston for Uniroyal Merchandising (seven years) and Occidental Petroleum (10 years). Sales and consulting in business forms industry for another ten years. Small retail business owner for 17 years in Houston, Texas. Moved to Pueblo in 2005.
81007
Gave less than $100 to Trump campaign in 2016. Gave time as volunteer for Pueblo Republican County Party off and on since 2016. Volunteered for the Trump Victory office for about four hours a week for the past few months.
I am active and have served as an officer and board member for Pueblo Newcomers for over 10 years. I am a member of Pueblo West Sportsman’s Association. I am a member of the Experimental Aircraft Association and volunteer at the annual Airventure air show in Oshkosh Wisconsin. I am a Pueblo County election judge. I was an election supervisor for both 2916, 2018 and 2020. I scanned ballots for the 2018 primary as well as being a machine judge a time or two.
As a forms management analyst, my job was to create paper flow systems that met the needs of the user while providing clear data for the the emerging computer technology. My career was in Texas. Since moving to Colorado, I have used my skills within my social associations as needed.
I believe in accurate and fair elections. Good district allocation is the first step in policies that meet citizens’ needs.
I have good listening skills honed by my career. It is my personality that allows me to see an issue from all sides. I know I would be an asset to the commission.
My education, career path as an analyst, salesman, consultant and business owner have provided years of experience that will benefit the Commission.  That job requires skill!
Female


assoc(x, xys)
Return the first element from the association list xys
whose head is equivalent to x
.
Return false
if the element is not found.
An association list is a proper list whose elements are pairs of the
form key:value
.
The equivalence test for assoc
is is_equal
.
assoc("b", ["a":1, "b":2, "c":3])
// b:2


This Eukaryotic sequence matches a Bacterial Rfam family
This sequence contains a possible ORF
This sequence matches only part of Rfam model
This sequence does not match the expected Rfam family
Learn more →


| Total net profit | -51.95 | Gross profit | 26.94 | Gross loss | -78.89 |
| Profit factor | 0.34 | Expected payoff | -0.23 | ||
| Absolute drawdown | -51.95 | Maximal drawdown (%) | 51.16 (-6475.95%) | ||
| Total trades | 227 | Profit trades (% of total) | 51 (22.47%) | Loss trades (% of total) | 176 (77.53%) |
| Long positions (won %) | 111 (26.13%) | Short positions (won %) | 116 (18.97%) | ||
| Largest | profit trade | 2.53 | loss trade | -1.31 | |
| Average | profit trade | 0.53 | loss trade | -0.45 | |
| Minimum | profit trade | 0.0 | loss trade | -0.01 | |
| Maximum | take profit in pips | 194.1 | stop loss in pips | -99.5 | |
| Average | take profit in pips | 50.3 | stop loss in pips | -37.8 | |
| Minimum | take profit in pips | -18.8 | stop loss in pips | -18.3 | |
| Maximum | Reward-Risk | 8.8 | Duration in minutes | 645 | |
| Average | Reward-Risk | 1.5 | Duration in minutes | 36.2 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0 | |
| Maximum | consecutive wins (profit in money) | 3.0 (0.59) | consecutive losses (loss in money) | 12.0 (-6.18) | |
| Average | consecutive wins | 1.0 | consecutive losses | 4.0 |
| Total net profit | -27.15 | Gross profit | 13.59 | Gross loss | -40.74 |
| Profit factor | 0.33 | Expected payoff | -0.24 | ||
| Absolute drawdown | -27.43 | Maximal drawdown (%) | 26.64 (-3372.15%) | ||
| Total trades | 111 | Profit trades (% of total) | 29 (26.13%) | Loss trades (% of total) | 82 (74.77%) |
| Largest | profit trade | 2.39 | loss trade | -0.86 | |
| Average | profit trade | 0.47 | loss trade | -0.5 | |
| Minimum | profit trade | 0.0 | loss trade | -0.02 | |
| Maximum | take profit in pips | 184.8 | stop loss in pips | -74.2 | |
| Average | take profit in pips | 43.5 | stop loss in pips | -45.6 | |
| Minimum | take profit in pips | -18.8 | stop loss in pips | -25.6 | |
| Maximum | Reward-Risk | 4.3 | Duration in minutes | 645.0 | |
| Average | Reward-Risk | 1.0 | Duration in minutes | 51.1 | |
| Minimum | Reward-Risk | 0.0 | Duration in minutes | 0.0 | |
| Maximum | consecutive wins (profit in money) | 3.0 (1.18) | consecutive losses (loss in money) | 10.0 (-5.42) | |
| Average | consecutive wins | 1.0 | consecutive losses | 3.0 |
| Total net profit | -24.8 | Gross profit | 13.35 | Gross loss | -38.15 |
| Profit factor | 0.35 | Expected payoff | -0.21 | ||
| Absolute drawdown | -24.8 | Maximal drawdown (%) | 25.7 (2855.56%) | ||
| Total trades | 116 | Profit trades (% of total) | 22 (18.97%) | Loss trades (% of total) | 94 (81.03%) |
| Largest | profit trade | 2.53 | loss trade | -1.31 | |
| Average | profit trade | 0.61 | loss trade | -0.41 | |
| Minimum | profit trade | 0.0 | loss trade | -0.01 | |
| Maximum | take profit in pips | 194.1 | stop loss in pips | -99.5 | |
| Average | take profit in pips | 56.7 | stop loss in pips | -30.4 | |
| Minimum | take profit in pips | -3.4 | stop loss in pips | -18.3 | |
| Maximum | Reward-Risk | 8.8 | Duration in minutes | 544.0 | |
| Average | Reward-Risk | 2.0 | Duration in minutes | 21.9 | |
| Minimum | Reward-Risk | Duration in minutes | 0.0 | ||
| Maximum | consecutive wins (profit in money) | 2.0 (1.46) | consecutive losses (loss in money) | 15.0 (-5.96) | |
| Average | consecutive wins | 1.0 | consecutive losses | 5.0 |


This project consists of 3 standalone API’s and 2 shared libraries all written in golang:1.14.
The API’s are users-api
, oauth-api
, items-api
The shared libraries are oauth-client
, utils
It explores three different types of databases which are MySql
, Cassandra
and elasticSearch
, and uses the most starred go clients
for each of them.
The bookstore project offers following features:
- Create, Update, Delete, Get User.
- User data protection with
X-Public
header check. - Issue access token if user exists.
- Use access token to communicate with main items api (validating token).
- Create, Get Item.
The project structure of the bookstore api’s follows strict MVC architecture principles, which makes the code highly readable and configurable.
For shipping the api’s, we use docker.
Below is the flow of request from client:
Components
Bookstore_users-api
Users-api
revolves around the domain user
whose definition is as follows:
1
2
3
4
5
6
7
8
9
type User struct {
Id int64 `json:"id"`
FirstName string `json:"first_name"`
LastName string `json:"last_name"`
Email string `json:"email"`
DateCreated string `json:"date_created"`
Status string `json:"status"`
Password string `json:"password"`
}
It offers the following endpoints:
| Http_Method | Endpoint | Function |
|---|---|---|
| GET | “/ping” | returns “pong” |
| POST | “/users” | creates new user |
| GET | “/users/:user_id” | get user by user_id |
| PUT | “/users/:user_id” | update user with user_id |
| PATCH | “/users/:user_id” | update user with user_id (ignore empty) |
| DELETE | “/users/:user_id” | delete user with user_id |
| GET | “/internal/users/search” | returns active user |
| POST | “/users/login” | if user exists, returns user |
It uses a Mysql database for its persistance layer. After setting up MySql we need to make a database named userDB
, and create a table users
with the following schema.
1
2
3
4
5
6
7
8
9
10
11
+--------------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------------+-------------+------+-----+---------+----------------+
| id | bigint | NO | PRI | NULL | auto_increment |
| first_name | varchar(45) | YES | | NULL | |
| last_name | varchar(45) | YES | | NULL | |
| email | varchar(45) | NO | UNI | NULL | |
| date_created | varchar(45) | NO | | NULL | |
| status | varchar(45) | NO | | NULL | |
| password | varchar(32) | NO | | NULL | |
+--------------+-------------+------+-----+---------+----------------+
Bookstore_oauth-api
Oauth-api
revolves around the domain access-token
and access-token-request
whose definition is as follows:
1
2
3
4
5
6
type AccessToken struct {
AccessToken string `json:"access_token"`
UserId int64 `json:"user_id"`
ClientId int64 `json:"client_id"`
Expires int64 `json:"expires"`
}
1
2
3
4
5
6
7
8
9
10
11
12
type AccessTokenRequest struct {
GrantType string `json:"grant_type"`
Scope string `json:"scope"`
// Used for password grant type
Username string `json:"username"`
Password string `json:"password"`
// Used for client_credentials grant type
ClientId string `json:"client_id"`
ClientSecret string `json:"client_secret"`
}
It offers the following endpoints:
| Http_Method | Endpoint | Function |
|---|---|---|
| GET | “/oauth/access_token/:access_token_id” | returns access token |
| POST | “/oauth/access_token” | creates new access token |
If an oauth client sends a GET request with an access_token_ID, the API checks it the access token exists and then returns the corresponding AccessToken struct(id, userid, client_id, expires).
If an oauth client sends POST request with access_token_request , the API creates a new access_token with corresponding user
It uses a Cassandra database for its persistance layer. After setting up Cassandra we need to make a keyspace named oauth
, and create a table access_tokens
with the following schema.
1
2
3
4
5
6
CREATE TABLE oauth.access_tokens (
access_token text PRIMARY KEY,
client_id bigint,
expires bigint,
user_id bigint
)
Bookstore_items-api
items-api
revolves around the domain Item
and queries
.
whose definition is as follows:
1
2
3
4
5
6
7
8
9
10
11
12
type Item struct {
Id string `json:"id"`
Seller int64 `json:"seller"`
Title string `json:"title"`
Description Description `json:"description"`
Pictures []Picture `json:"pictures"`
Video string `json:"video"`
Price float32 `json:"price"`
AvailableQuantity int `json:"available_quantity"`
SoldQuantity int `json:"sold_quantity"`
Status string `json:"status"`
}
1
2
3
4
5
6
7
8
type EsQuery struct {
Equals []FieldValue `json:"equals"`
}
type FieldValue struct {
Field string `json:"field"`
Value interface{} `json:"value"`
}
It offers the following endpoints:
| Http_Method | Endpoint | Function |
|---|---|---|
| GET | “/ping” | returns “pong” |
| POST | “/items” | creates new item |
| GET | “/items/{id}” | get item by item_id |
| POST | “/items/search” | search item with queries |
It uses Elasticsearch for its persistance layer. After setting up Elasticsearch, we need to configure the shards
for out database, which can be done by making a POST request to database i.e. <IP_ADDRESS>:9200/items
with following body:
1
2
3
4
5
6
7
8
{
"settings": {
"index" : {
"number_of_shards" : 4,
"number_of_replicas" : 2
}
}
}
Bookstore_utils-go
This is a shared package for our bookstore project which consists of custom logger
and error
interface. It is not only limited to this project, and can be used in any golang project.
Bookstore_oauth-go
A client package to interact with Oauth API, it can simply be imported in any API and use Oauth functions like validation, login_request etc. ***


Dallinger for Programming Novices¶
- Introducing the Players
- Experiment structure
- The Database
- Nodes
- Vectors
- Infos
- Transmissions
- Transformations
- Networks
- Participants
- Questions
- The Experiment Class
- Demo Experiment Classes
- Communication between the Server and Participants
- Server Routes
- Front end files
- Dallinger’s Javascript library
- Demo Front Ends


Background Music
Pizzicato
play
pause
resume
stop
rewind
toggle
Sample
play
pause
resume
stop
rewind
toggle
All
play
pause
resume
stop
rewind
toggle


{%extends 'base.html'%} {% load static %} {% block content %} {{block.super}}
location: {{ neighbourhood.location }}


| DOSE: |
25 mg |
smoked |
5-MeO-DMT |
(powder / crystals) |
9/16/05 - 11:00pm
The first time I smoked 5-MeO-DMT, almost 4 years ago, I was quite shaken. My total annihilation and subsequent reaction of shock and horror ended up scaring me off from pretty much all psychedelics for a couple of years. Recently however, I came across a small quantity of the rare magical powder and I suspected that today, in a more prepared self, I might react to the intensity of the experience more out of love than fear. So one Friday night alone at my apartment, I smoked 25mg split between 15-20mg vaporized in a DMT pipe and then, when this only got me halfway through, the remainder sprinkled on top of some cannabis.
As I was ascending I became increasingly more aware of my breath. It seemed like such a large part of me; my life force. In fact, now that I thought of it I was my breath, and I existed as nothing else. My sphere of my consciousness had contracted to encompass only what was occurring in my lungs.  I was the chaotic, probabilistic quantum mechanical gurglings that underlie all of reality. I was the vast enormous galactic meta-dimensional everything. There was no fundamental difference between myself and anything in the universe. In a kind of harmonic resonance, I vibrated in peace with all the forces playing out around me. Visuals were either absent or unimportant compared to the overarching feeling of divine connectivity.
This time there was no hint of a fear reaction, because, if fear is just an evolutionary product of self-preservation then what is there to be afraid of when you are everything? The experience was, by far, the most beautiful thing I have ever felt.
The feeling of unity stayed with me for a while. Even 60 minutes later I was still basking in the temporal reflection of the awe felt at that moment of cosmic union. As I wrote down some reactions to the experience on paper, it felt like the pen was writing me; the words that were coming out were completely outside of conscious control and rather a direct manifestation of the galactic energies I was a part of. Moving to some music on the stereo required no decision on my part; it felt like the music was dancing me. I was so absorbed in being that even the simple planning of action and thought did not exist. Everything that existed at that exact moment existed as everything forever.
The next day felt like a glistening sheen of love and acceptance was thrown over all people, objects, and events in the new world. The feeling was beautifully slow to dissolve, and will probably (hopefully) never leave me completely. Even though it will surely take some time to fully absorb and process this experience, at this point I seem to have discovered what Iíve been looking for - the universe is now perceived as utterly complete.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


THAT'S THE WAY I LIKE IT
Reviewed by Harvey Karten, Ph.D. Miramax Films Director: Glen Goei Writer: Glen Goie Cast: Adrian Pang, Madeline Tan, Pierre Png, Anna Bell Francis, Dominic Pace
The ayatollahs, the Saddamites, and the French nationalists can holler from the rooftops all they want about the influence of American culture on their traditional values. Ultimately these spokesmen will not prevail. From at least 1945, when the Yanks captured the hearts and minds of Europeans with their generous offerings of chewing gum to war-torn youngsters, American culture has triumphed big time. In the Far East, for example, tensions between the majority ethnic Chinese and Malaysians in the Malaysian city of Singapore led to a pact granting Singapore the full status of an independent country in 1965. But the nationalism of Singapore's largely Chinese population did not stop that small nation from copying and maintaining Western culture from Burger King to the English language itself. In fact in director Glen Goei's semi-autobiographical movie "That's the Way I Like It"--which gets the title from one of the songs on the soundtrack--the characters speak English 95% of the time using the local Malay and Chinese dialects only occasionally with no rhyme or reason. In the director's words, the story "captures my own journey from an Asian culture to a Western one," the action taking place in the year 1977.
During the year that the Son of Sam was creating mayhem in New York City, forcing people in some neighborhoods to lock their doors and avoid city streets at night, the folks in Singapore had other ideas. While New York was suffering from feverish heat during that summer, a large percentage of young Singaporean people were suffering from a fever of their own--their passion for disco music and dance and their appetite for the style of John Travolta as shown in his groundbreaking "Saturday Night Fever." Though the government of Singapore--like many ruling forces throughout the world today--may have made every effort to hold on to traditional values, the death of Bruce Lee led the young to search for a new hero. Travolta was their man and at least one film featuring a Western dancer with an all-purpose southern accent captured the notice of sizable audiences of young people. The lead character (Dominic Pace) steps out of his movie in a touch of magic realism to become a guardian angel to one Ah Hock.
Ah Hock (Adrian Pang) is a young man who would not have dreamed of being taken in by the dance. A 20- something guy with a dead-end supermarket job, a provincial family, and a vivid imagination, hangs out at night with a typical bunch, including Hock's childhood friend Ah Mei (Madeline Tan). They bowl, they brag, they act in much the way young adults behave almost everywhere. Hock's life turns around when, inspired by the Travolta-like hero of the movie, he and Mei take dance lessons, later to enter a competition whose prize money could allow him to buy the motorcycle of his dreams. When the beautiful Julie (Anna Belle Francis) becomes attracted to Hock, Julie's rich and abusive boy friend Richard (Pierre Png) becomes enraged and takes steps to break up the budding romance.
In a subplot that further shows the freedoms that these Singaporeans are reaching for, Hock's 21-year-old brother, Leslie (Caleb Goh) shocks his family by expressing his desire for a sex change operation, which wholly alienates the lad's father while delighting his pulp fiction-addicted kid sister.
In writing and directing the film, Goei was obviously inspired in part by "Saturday Night Fever," but a good deal of his stimulus comes from the Australian cinema, particularly from the movie "Strictly Ballroom." In Baz Luhrmann's 1992 entry, a young ballroom dancer outrages his mother and the establishment by insisting on dancing his own provocative steps. He takes on a homely partner who blossoms under his guidance. By contrast, Hock appears to break his partner's heart by ditching her for a more sophisticated and accomplished dancer, thereby inciting violence against himself.
By the conclusion of "That's the Way I Like It," young Hock comes to regret his lack of ethics and good common sense, demonstrating his born-again ways in a remarkable show of altruism. The film challenges credibility by its view that a fellow with no interest in anything besides bowling, stacking cans in a supermarket, and dreaming of taking the place of Bruce Lee, could even think of entering a major nationwide competition with only a few weeks of lessons. Yet Adrian Pang convinces us that the experience of entering the contest has transfigured him from an unambitious wastrel frequently late to his dead-end job to a celebrity who learns the meaning of love and commitment.
Since Pang is not a professional dancer, the movie features abrupt editing (also an attribute of "Saturday Night Fever") and the scenes of violence are particularly unconvincing--as though the performers had to pull their punches at a performance on a live stage. A slight film throughout, "That's the Way I Like It" may lack the charm of Masayuki Suo's "Shall We Dance?" but profiles a dynamic, if familiar, soundtrack, with the repeated, obligatory rendering of the Gibbs' "Staying Alive." Brian Breheny's photography barely exploits the city-state's topography, his camera concentrating on indoor locations like Hock's household, a bowling alley, and a disco. Should any viewer be tempted to travel to Singapore, the film may dissuade him: what we see of that major port is little more than a modern metropolis devoid of Far Eastern exoticism.
Rated PG-13. Running Time: 95 minutes. (C) 1999 Harvey Karten
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


In this document we describe PSKOV dependencies and how to get them.
Estimated completion time: 5 minutes.
Table of contents
We designed PSKOV to run inside web browsers. Here is what you need to run PSKOV:
| № | PSKOV dependency | Notes |
|---|---|---|
| 1 | Web browser of 2010 or newer | PSKOV needs ECMAScript 5 (2009), any modern web browser should work |
| 2 | Local file system access | LFSA gives PSKOV access to your local file system. Install LFSA to be able to use PSKOV. |
Note: install LFSA to be able to use PSKOV.
PSKOV:
LFSA:


{{ relationshipPg | predicateIn:['foaf:name','foaf:nick','foaf:givenName'] }}
{{ relationshipPg | predicate:'foaf:nick' }}
{{ 'TodoCompany' }}
Last message from Edward: three days ago
Hey, how was the play? I hope you enjoyed it. Let's talk about it this week...


I was born in Kentucky, but was raised across the Ohio river in Southern Indiana. I have yet to leave the Hoosier State, but love to travel this country whenever possible to experience all of it's many gems.
My passion: I LOVE classic movies! I can't seem to get enough of the old style dress and talk. Whether it's the classy feel, or the well-written storylines, I would trade watching a classic movie over a new one any day.
A fun fact: Between my purchases and the gifts from others, I have an extensive necktie collection. Ranging in all colors and styles, some more flattering than others, I could wear a different tie for many weeks and never repeat one!


The sub-window that gives you the top-level view of a definitions file is called a Grammar Editor (since this allows you to define vocabulary, synonyms and valid phrases for use in calls). The Grammar Editor is shown as an outline. The image at right shows how this outline appears when you have closed all the outline items except the top-level filename line itself. As you can see, small boxes contain either a minus or plus sign. Each such box can be clicked to alter how the outline is displayed.
Clicking on a minus box will close that item and contract everything under it. The box itself then changes into a plus box. Clicking on a plus box will expand the underlying outline items and change the box to a minus box.
If no further outline items exist under a given level, no box will be drawn next to the item. Currently, each synonym, definition and formation are the lowest levels of this outline.
Currently there is nothing you can do with synonyms, formations or dancer designations. This will be remedied in a future release.
When you expand outline, if there is not enough room, scrollbars will be included to allow you to adjust the portion of the list that is visible.
The definitions are labeled with the first phrase used to call that definition. As you change the phrases for a call, the list of definitions will not be re-sorted until you re-start the program.
If you right-click on the title 'Definitions' it offers you a menu with a single item on it: Create New Definition. Selecting that menu item will create a new definition that is completely empty and ready to be filled in. It is added to the end of the list of definitions in the current file. The definition will be opened in a Definition Editor in the left-hand side of the main window, covering the outline view. You can return to the outline by clicking on the tab marked either 'Definitions' or 'My Definitions' (depending on which you want to see).
If you click on a definition in the outline, a Definition Editor for that call will be opened in the left-hand pane of the main window.
Notice that in the default Definitions list, most words are in lower case. As a convention to help read the definitions, I capitalize built-in terms like FRACTION or P_C. As noted elsewhere, the program is not case sensitive, so you do not have to follow this convention if you prefer to write your definitions differently. The exact capitalization is only used in displaying the name of a call back to you.


Employee Mangement System
Firstname
Lastname
EmpolyeeID
Email
MobileNumber
Age
Hiredate
Salary
Departmetn
Delete
Mohammed
Alsalm
1
moh@gmila
0323425354
25
01/01/2020
2000
IT
Delete
Tala
alkhalid
2
tal@gmail
0353728936
23
03/04/2019
3000
IT
Delete
Abdullah
AlDaiy
3
abd@gmail@gmail
0534032403
28
04/05/2018
7000
IT
Delete
Firstname
Lastname
EmpolyeeID
Email
MobileNumber
Age
Hiredate
Salary
Departmetn
Delete
Firstname
Lastname
EmpolyeeID
Email
MobileNumber
Age
Hiredate
Salary
Departmetn
Delete
Add
Update


Candidate Profile
| Name | Judy Maciejowska |
| Party | Green Party |
| Address | 57 Haliburton Road |
|<EMAIL_ADDRESS>| |
| phone | 07977 079 269 |
Background
Tell us about your education?
St. Agnes, Isles of Scilly primary school, then Truro High School, Cornwall, then an MA European Politics, Brunel University.
What are three jobs you have held?
- Present – Chair of Richmond Environmental Information Centre (Voluntary)
- 2000/2002 – GLA, Research & Support Officer for Darren Johnson AM (Green Assembly Member)
- 1998/2000 - London Green Party, Election Campaign Manager
What are you links to the North Twickenham/St Margarets community?
Lived in St. Margarets for 27 years (Richmond for ten years before that); children went to Maria Grey Nursery, Orleans Infants, St. Stephens, Waldegrave and then Richmond College. I worked for West London Institute and then Brunel University in St. Margarets. Now active with North St. Margarets Residents’ Association
Why did/do you want to be a councilor?
To give local people a committed representative on the Council, and to give Green issues a strong voice locally
Issues
What do you think are the top three issues for North Twickenham/St Margarets and what do you should be done about them?
- Community – without a doubt the most important issue, from which all others stem
- Local schools should be available for local children so that primary school children can attend their community school with their friends and without having to travel by car
- Local businesses – support should be given to help local businesses survive the onslaught of the Superdrugs and Tescos.
What areas are you passionate about and what committees would you like to sit on?
Planning, there is so much potential for good planning and, unfortunately some opportunities for abuse.
Also, Education – I’m still not convinced that the need for a local primary school has diminished
Are there any big things you are looking to achieve or change?
Unfortunately even the majority party is unable to change much in four years, but I will certainly give the leading administration a headache as I rattle cages for the community, e.g. on a local school for primary children; the Mogden pong; Heathrow 3rd runway; support for local shops and businesses
If elected, how will you keep in-touch with your constituents?
I will hold regular surgeries; I will visit local people and shopkeepers; I will always be accessible by e-mail and phone
Fun
What is your favorite musical group/band/cd?
Bessie Smith, Anonymous Four, Madeleine Peyroux, Patsy Kline, Ella Fitzgerald, Bach, Mozart, Beethoven, Thomas Tallis, Purcell and loads more.
What is your favorite book?
Impossible to say – Maybe Jung Chang’s Wild Swans, or Mary Stewart’s Merlin Trilogy.
What is the last book you read?
Currently reading The Kite Runner, by Khaled Hosseini
What are three places you have lived?
- Isles of Scilly
- Rabat, Malta
- Haliburton Road, St. Margarets
What is your favorite meal?
Sunday lunch (I don’t eat the meat!), good veggie curry, pasta and red wine
What is your favorite place to take a holiday?
St. Agnes, Isles of Scilly


Interface: SplitControl
interface SplitControl
Please refer to TEP 115 for more information about this interface and its
intended use.
This is the split-phase counterpart to the StdContol interface. It
should be used for switching between the on and off power states of
the component providing it. For each start()
or
stop()
command, if the command returns SUCCESS, then a
corresponding startDone()
or stopDone()
event
must be signalled.
- Author:
-
Joe Polastre
-
Kevin Klues<EMAIL_ADDRESS>Commands
command error_t start()
command error_t stop()
Events
event void startDone(error_t error)
event void stopDone(error_t error)
Commands - Details
start
command error_t start()
- Returns:
-
SUCCESS if the device is already in the process of
starting or the device was off and the device is now ready to turn
on. After receiving this return value, you should expect a
startDone
event in the near future.
EBUSY if the component is in the middle of powering down
i.e. a stop()
command has been called,
and a stopDone()
event is pending
EALREADY if the device is already on
FAIL Otherwise
stop
command error_t stop()
- Returns:
-
SUCCESS if the device is already in the process of
stopping or the device was on and the device is now ready to turn
off. After receiving this return value, you should expect a
stopDone
event in the near future.
EBUSY if the component is in the middle of powering up
i.e. a start()
command has been called,
and a startDone()
event is pending
EALREADY if the device is already off
FAIL Otherwise
Events - Details
startDone
event void startDone(error_t error)
- Parameters:
-
error -- SUCCESS if the component was successfully
turned on, FAIL otherwise
stopDone
event void stopDone(error_t error)
- Parameters:
-
error -- SUCCESS if the component was successfully
turned off, FAIL otherwise


Analyze This (Reviewed on March 7/99)
Starring Robert DeNiro, Billy Crystal, Lisa Kudrow
When I originally saw the trailer for "Analyze This" a few months ago, I must admit, I thought it looked kind of lame. And then when the commercials started popping up a week or two ago, I thought it looked outright bad. But then when "Analyze This" finally opened a few days ago, an odd thing happened. It got great reviews. Critics were proclaiming it "hilarious" and a "dead-on parody of mob movies". Well, with praise like that, I figured, it must be good and so I headed off to the theater. You know that expression that says always trust your gut instincts? Well, turns out that expression is more valid than I ever gave it credit for.
"Analyze This" is slow, unfunny, and badly acted. Don't get me wrong, I think that DeNiro is one of the top ten greatest actors of the century, but he is just out of his league here. I think the problem is he didn't quite know how to approach this material. He plays his character, mob boss Paull Vitti, somewhere in between the realm of comedy and drama. If he had played the character straight, along the lines of Leslie Nielson in the "Naked Gun" series, he probably would have been a lot more successful. As it is, though, he plays the character completely serious at some moments, and for laughs at others. This doesn't work. It creates an uneven character that never breaks out of the DeNiro mold; you always know it's him.
And the movie is badly paced, too. It never takes off. It just crawls from one scene to another without any forward momentum. I think the blame for this should be placed on the script. It's obvious the writer had a good idea for a movie, mob boss faces breakdown and needs the services of a psychiatrist, but once this is established, the movie doesn't really go anywhere. The formula of the film seems to be this: Billy Crystal says no to DeNiro, DeNiro forces him, and much wackiness ensues. This formula of sorts is repeated several times throughout the movie.
I've said it before and I'll say it again: The only thing that matters to me in a comedy is whether or not it's funny. If "Analyze This" had been funny, the pacing and bad acting wouldn't have bothered me. I would have been too busy laughing to notice. But as it is, I only chuckled a few times. The only really funny scene is a dead-on parody of "The Godfather". Sadly, though, I don't think anyone in the audience I saw it with realized it was a parody, because I was the only one laughing.
But my sense of humour, I have come to realize, is vastly different from the general population. I loathed "There's Something About Mary", yet loved "BASEketball". Now, if you want a movie that *I* think is funny, go out and see "Office Space". It's full of genuine laughs and won't leave you glancing at your watch every 10 minutes, as "Analyze This" did.
* out of ****
--
David Nusair http://chat.carleton.ca/~dnusair
"As I have pointed out before, Andre Rousimoff's portrayal of a giant in
"The Princess Bride", Richard Dawson's portrayal of an obnoxious game show
host in "The Running Man", and Courtney Love's portrayal of a junkie hooker
in "The People vs Larry Flynt"."
-R. Wiley on the all-time biggest Oscar snubs
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


class: center, middle, inverse, title-slide # Geography 13 ## Lecture 20: K-means Clustering ### Mike Johnson ---  # Raster Data Model  --- # Raster Data (Values) ```r (v = c(1:8)) ``` ``` [1] 1 2 3 4 5 6 7 8 ``` -- ```r dim(v) = c(2,4) v ``` ``` [,1] [,2] [,3] [,4] [1,] 1 3 5 7 [2,] 2 4 6 8 ``` --- ```r dim(v) = c(2,2,2) v ``` ``` , , 1 [,1] [,2] [1,] 1 3 [2,] 2 4 , , 2 [,1] [,2] [1,] 5 7 [2,] 6 8 ``` --- # Map Algebra: 2 maps ```r AOI = USAboundaries::us_states() %>% filter(name == "California") ca = getTerraClim(AOI, c("tmax", "srad"), startDate = "2018-08-01") ``` ``` Spherical geometry (s2) switched off Spherical geometry (s2) switched on ``` ```r s = stack(ca) %>% setNames(c("tmax", "srad")) plot(s) ```  --- # Local ```r tmax = s$tmax / 10 plot(tmax) ```  --- # Focal ```r tmax_smooth = focal(tmax, w = matrix(1, 11,11), mean) plot(tmax_smooth) ```  --- # Zonal ```r tmax_agg = aggregate(tmax, 10) plot(tmax_agg) ```  --- # Global ```r cellStats(tmax, fivenum) ``` ``` [1] 24.60276 28.95835 29.91061 31.33901 32.46972 ``` --- # Reclassification: Local operation via global persepctive ```r #global f = cellStats(s$srad, fivenum) # matrix rcl = data.frame(f[1:4], f[2:5], 1:4) #local out = reclassify(s$srad, rcl,include.lowest = TRUE) plot(out, col = RColorBrewer::brewer.pal(4, "Spectral")) ```  --- ### Apply map algrbras over layers of a stack ```r reclassQuarts = function(x){ f = cellStats(x, fivenum) rcl = data.frame(f[1:4], f[2:5], 1:4) reclassify(x, rcl,include.lowest = TRUE) } out = stack(lapply(ca, reclassQuarts)) plot(stack(out), col = viridis::viridis(4)) ```  --- ### Naive Interaction between Classifications: Multiplicative - Relationship between tmax and solar radiation ```r out2 = out$terraclim_srad * out$terraclim_tmax plot(out2, col = viridis::viridis(16)) ```  --- ### Naive Interaction between Classifications: Bivariate - Geography 183 type cartography ```r plot(out$terraclim_srad, col = viridis::viridis(4, alpha = .5), legend = FALSE) plot(out$terraclim_tmax, col = viridis::inferno(4, alpha = .25), add = TRUE, legend = FALSE) ```  --- class: center, middle # Moving beyond "additive" associations --- # Clustering - Clustering is a broad set of techniques for finding subgroups of observations within a data set. - K-means - Decision-tree - Random Forest - Hierarchical -- - When we cluster observations, we want to place similar observations in the same category, and dissimilar observations in others. -- - The amount of variance allowed in each group depends on how many categories you select -- - Clustering is an **unsupervised** method, which implies that it seeks to find relationships between "n" observations without being trained by a response variable or a "truth" --- # K-means K-means clustering is the simplest and the most commonly used clustering method for splitting a dataset into "k" groups. --- # K-means - Valuable, particularly for geodata -- - Basis of clustering and a lot of "machine learning" -- - Can be abused... --  ^this study is without a doubt morally questionable and even methodologically questionable as it supporting a positive feedback loop. It is also based on the idea that arrests are a good proxy for crime... --- # Data Preparation To perform a cluster analysis your data should be prepared as follows: - **Rows** are observations and **columns** are variables (tidy data) -- - *All* missing values (`NA`, `NULL`) must be removed or estimated. -- - The data should be standardized (i.e., scaled) to make variables comparable. -- - standardization consists of transforming the variables such that they have mean zero and standard deviation one. -- - In R, base `scale` does the following: `$$\frac{x - mean(x)}{sd(x)}$$` -- scaling makes sense when you have multiple variables at different magnitudes (e.g. temperature and PRCP). --- # Toy Data We will use the wine dataset from the UCI Machine Learning Repository. The wine dataset contains the results of a chemical analysis of wines grown in a specific area of Italy. Three types of wine are represented in the 178 samples, with the results of 13 chemical analyses recorded for each sample. ```r library(rattle.data) data = dplyr::select(wine, "Alcohol", "Malic", "Ash") dim(data) ``` ``` [1] 178 3 ``` ```r head(data) ``` ``` Alcohol Malic Ash 1 14.23 1.71 2.43 2 13.20 1.78 2.14 3 13.16 2.36 2.67 4 14.37 1.95 2.50 5 13.24 2.59 2.87 6 14.20 1.76 2.45 ``` --- # Preparing Data - We should always ensure there is no missing data (`NA` values are "infectious") ```r data <- na.omit(data) ``` -- - The data should be standardized so that the clustering algorithm is not influenced by an arbitrary variable unit -- - In our data we see Alcohol is a magnitude larger then Malic and Ash -- ```r (data <- scale(data)) ``` ``` Alcohol Malic Ash 1 1.51434077 -0.56066822 0.23139979 2 0.24559683 -0.49800856 -0.82566722 3 0.19632522 0.02117152 1.10621386 4 1.68679140 -0.34583508 0.48655389 5 0.29486844 0.22705328 1.83522559 6 1.47738706 -0.51591132 0.30430096 7 1.71142720 -0.41744613 0.30430096 8 1.30493643 -0.16680747 0.88751034 9 2.25341491 -0.62332789 -0.71631546 10 1.05857838 -0.88291793 -0.35180959 11 1.35420804 -0.15785609 -0.24245783 12 1.37884384 -0.76654998 -0.16955666 13 0.92308146 -0.54276546 0.15849862 14 2.15487169 -0.54276546 0.08559744 15 1.69910930 -0.41744613 0.04914686 16 0.77526663 -0.47115441 1.21556562 17 1.60056608 -0.37268923 1.28846679 18 1.02162467 -0.68598755 0.92396093 19 1.46506916 -0.66808479 0.41365272 20 0.78758453 0.68357369 0.70525741 21 1.30493643 -0.63227927 -0.31535901 22 -0.08698653 1.31017034 1.03331269 23 0.87380985 -0.42639751 -0.02375431 24 -0.18552975 -0.65913341 0.55945507 25 0.61513390 -0.47115441 0.88751034 26 0.06082829 -0.25632128 3.11099611 27 0.47963697 -0.50695994 0.92396093 28 0.36877585 -0.55171684 -0.82566722 29 1.07089628 -0.39059199 1.58007149 30 1.25566482 -0.58752236 -0.57051311 31 0.89844565 -0.74864721 1.21556562 32 0.71367712 -0.60542512 -0.02375431 33 0.83685614 -0.45325165 -0.02375431 34 0.93539936 -0.72179307 1.21556562 35 0.62745180 -0.48010579 1.03331269 36 0.59049809 -0.47115441 0.15849862 37 0.34414005 -0.62332789 1.72587383 38 0.06082829 -0.61437650 0.66880683 39 0.08546410 -0.74864721 -0.97146956 40 1.50202286 1.48024658 0.52300448 41 0.68904131 -0.56066822 -0.20600725 42 0.50427278 1.34597587 -0.89856839 43 1.08321419 -0.39954337 0.81460917 44 0.29486844 1.47129519 -0.27890842 45 0.06082829 -0.50695994 -0.97146956 46 1.48970496 1.52500348 0.26785038 47 1.69910930 1.12219135 -0.31535901 48 1.10784999 -0.58752236 -0.89856839 49 1.35420804 -0.28317542 0.12204803 50 1.15712160 -0.54276546 -0.35180959 51 0.06082829 -0.54276546 -1.19017308 52 1.02162467 -0.61437650 0.85105976 53 1.00930677 -0.52486270 0.19494920 54 0.94771726 -0.39059199 1.14266445 55 0.91076355 -0.59647374 -0.42471076 56 0.68904131 -0.54276546 0.34075155 57 1.50202286 -0.56961960 -0.24245783 58 0.35645795 -0.32793232 1.14266445 59 0.88612775 -0.81130688 0.48655389 60 -0.77678907 -1.24992453 -3.66881295 61 -0.82606067 -1.10670244 -0.31535901 62 -0.44420570 -0.87396654 -1.26307425 63 0.82453824 -0.97243173 -1.62758012 64 -0.77678907 -1.07984830 -0.75276604 65 -1.02314711 -0.79340412 0.59590565 66 -0.77678907 -1.00823725 0.70525741 67 0.13473571 -1.18726487 -2.42949302 68 -0.77678907 -1.04404278 -1.62758012 69 0.41804746 -1.24992453 -0.02375431 70 -0.97387550 -1.02614002 -2.24724008 71 -0.87533228 -0.65018203 -0.57051311 72 1.05857838 -0.73969583 1.10621386 73 0.60281600 -0.60542512 -0.46116135 74 -0.01307912 -0.59647374 0.85105976 75 -1.28182306 -1.11565382 -0.24245783 76 -1.65136013 -0.40849475 -1.62758012 77 0.03619249 -1.28573006 -2.39304243 78 -1.42963789 0.49559470 -0.49761194 79 -0.82606067 -1.20516763 -1.51822836 80 -0.37029829 1.37283001 0.12204803 81 -1.23255145 -1.26782729 -1.33597542 82 -0.34566248 -0.47115441 -0.60696370 83 -1.13400823 -1.07984830 0.52300448 84 0.06082829 1.36387863 -0.16955666 85 -1.42963789 -1.29468144 0.77815859 86 -0.40725200 -1.21411901 -0.46116135 87 -1.03546501 -0.65018203 -0.20600725 88 -1.66367803 -0.59647374 0.92396093 89 -1.67599593 -0.24736990 0.34075155 90 -1.13400823 -0.90082069 -0.24245783 91 -1.13400823 -0.45325165 -0.16955666 92 -1.23255145 -0.73969583 0.19494920 93 -0.38261619 -0.72179307 -0.38826018 94 -0.87533228 0.44188642 -0.53406252 95 -1.70063174 -0.31002956 -0.31535901 96 -0.65361004 -0.73074445 -0.60696370 97 -1.46659160 -0.19366161 1.36136797 98 -0.87533228 -0.82920964 -1.40887660 99 -0.77678907 -1.13355658 -0.97146956 100 -0.87533228 0.74623336 -0.57051311 101 -1.13400823 -0.22946714 -2.42949302 102 -0.49347731 -0.89186931 -1.70048129 103 -0.81374277 0.10173395 0.34075155 104 -1.45427369 -0.55171684 -1.77338246 105 -0.60433843 -0.54276546 -1.40887660 106 -0.71519955 0.19124776 -0.35180959 107 -0.92460389 -0.54276546 -0.89856839 108 -0.34566248 -0.52486270 -0.31535901 109 -0.96155760 -0.93662621 -1.55467894 110 -1.71294964 -0.88291793 1.21556562 111 -1.89771818 1.25646206 -1.99208598 112 -0.59202053 0.08383119 -0.71631546 113 -1.52818111 0.30761571 2.01747852 114 -1.95930769 -1.42895215 0.48655389 115 -1.13400823 -0.84711240 0.48655389 116 -2.42738798 -0.73969583 -0.60696370 117 -1.45427369 -0.77550136 -1.37242601 118 -0.71519955 -0.65018203 -0.64341428 119 -0.28407297 0.97896926 -1.40887660 120 -1.23255145 0.97896926 -1.33597542 121 -1.91003608 0.05697705 0.19494920 122 -1.77453915 -0.25632128 3.14744670 123 -0.71519955 1.87410733 1.32491738 124 0.06082829 3.10044648 -0.86211780 125 -1.39268418 1.76669076 0.08559744 126 -1.14632613 -0.15785609 -0.71631546 127 -0.70288165 -0.72179307 -0.27890842 128 -1.49122740 -0.18471023 1.50717031 129 -0.77678907 -0.63227927 -0.24245783 130 -1.18327984 1.75773938 0.04914686 131 -0.17321185 -0.88291793 -0.16955666 132 -0.14857605 0.58510851 0.12204803 133 -0.23480136 -0.02358538 0.12204803 134 -0.37029829 1.08638583 -0.02375431 135 -0.60433843 -0.98138311 -0.42471076 136 -0.49347731 0.11068533 -0.60696370 137 -0.92460389 2.13369737 0.63235624 138 -0.57970263 2.84085644 0.99686210 139 0.60281600 1.12219135 -0.64341428 140 -0.19784766 0.55825437 0.88751034 141 -0.08698653 0.42398365 1.21556562 142 0.44268327 0.20019914 -0.06020490 143 0.63976970 0.74623336 1.28846679 144 0.76294873 2.33957912 -0.06020490 145 -0.92460389 1.38178139 -0.60696370 146 0.19632522 1.10428859 -0.78921663 147 1.08321419 2.42014155 -0.49761194 148 -0.16089395 2.03523218 0.41365272 149 0.39341166 0.80889302 0.04914686 150 0.09778200 1.39968415 -0.02375431 151 0.61513390 0.70147646 0.92396093 152 -0.25943717 0.29866433 0.41365272 153 0.13473571 -0.39059199 1.39781855 154 0.28255053 0.86260131 -0.31535901 155 -0.51811312 -0.93662621 -0.97146956 156 0.20864312 2.55441226 -0.16955666 157 1.03394258 1.59661452 0.04914686 158 -0.67824585 0.62091403 0.99686210 159 1.64983769 -0.58752236 1.21556562 160 0.59049809 -0.59647374 0.99686210 161 -0.78910697 1.33702448 0.04914686 162 0.84917404 0.82679579 0.63235624 163 -0.18552975 0.83574717 0.77815859 164 -0.05003283 0.99687202 -0.06020490 165 0.96003516 0.37922675 -0.24245783 166 0.89844565 1.81144766 -0.38826018 167 0.55354439 1.22065654 0.85105976 168 -0.22248346 0.92526097 -0.24245783 169 0.71367712 0.21810190 1.17911504 170 0.49195487 2.02628080 1.79877500 171 -0.98619340 0.62091403 -0.16955666 172 -0.28407297 0.04802567 -0.31535901 173 1.42811545 0.15544223 0.41365272 174 0.87380985 2.96617577 0.30430096 175 0.49195487 1.40863553 0.41365272 176 0.33182214 1.73983662 -0.38826018 177 0.20864312 0.22705328 0.01269627 178 1.39116174 1.57871176 1.36136797 attr(,"scaled:center") Alcohol Malic Ash 13.000618 2.336348 2.366517 attr(,"scaled:scale") Alcohol Malic Ash 0.8118265 1.1171461 0.2743440 ``` --- # Distance Measures - The classification of "n" observations requires some method for computing the distance between each pair of observations. -- - The result of this distance calculation is known as a `distance` matrix. -- - There are **many** methods to calculate distance and the choice is a critical step in clustering. --- The classical methods for distance measures are Euclidean and Manhattan distances defined as follow: $$ euclid = \sqrt{\sum(x_i - y_i)^2} $$ -- $$ man = \sum |x_i - y_i| $$ where `\(x\)` and `\(y\)` are two vectors of length `\(n\)` --- - For most common clustering software, the default distance measure is the `Euclidean` method -- - Depending on the type of the data and the research questions, other dissimilarity measures might be preferred and you should be aware of the options. -- - the `dist` function in the `stats` package is able to compute the distance matrix -- - The default method is 'euclidean' with support for "*euclidean*", "*maximum*", "*manhattan*", "*canberra*", "*binary*" or "*minkowski*" calculations -- - Within R it is simple to compute and visualize the distance matrix using the functions `get_dist` and `fviz_dist` from the `factoextra` package. ```r dist <- dist(data) length(dist) ``` ``` [1] 15753 ``` --- - Visualization tools, like those found in `factoextra` can help visualize a distance matrix -- ```r library(factoextra) fviz_dist(dist) ```  -- - This visualization begins to illustrate which wines have large dissimilarities (blue) and those that are fairly similar (red). - The red diagonal across the middle is the comparison of each wine to itself, thus the perfect similarity! --- # Categorizing your distance matrix - K-means clustering is the most common unsupervised machine learning algorithm for partitioning a given data set into a set of k groups (i.e. k clusters) -- - k represents the number of groups pre-specified by the analyst. -- - It classifies objects in multiple groups (i.e., clusters), such that objects within the same cluster are as similar as possible (i.e., high intra-class similarity), and objects from different clusters are as dissimilar as possible (i.e., low inter-class similarity). -- - In k-means clustering, each cluster is represented by its `center` (i.e, centroid) which corresponds to the `mean` of values assigned to the cluster. ---  --- # Determining Cluster Variation - k-means clustering defines clusters so that the total `intra-cluster` variation (total within-cluster variation) is `minimized.` -- - There are several k-means algorithms available. -- - The standard algorithm is the Hartigan-Wong algorithm (1979), which defines the total within-cluster variation as the sum of squared Euclidean distances between items and the corresponding centroid: $$ W(C_k) = \sum(x_i - \mu_k)^2$$ where: `\(x_i\)` is a data point belonging to the cluster `\(C_k\)` `\(\mu_k\)` is the mean value of the points assigned to the cluster `\(C_k\)` --- Each observation ( `\(x_i\)` ) is assigned to a given cluster ( `\(k\)` ) such that the sum of squares (SS) distance of the observation to their assigned cluster centers ( `\(\mu_k\)` ) is minimized. -- The **total** within-cluster variation of the clustering is defined as: $$ total.withiness = \sum_{k=1}^k W(C_k)$$ -- - The _total_, -- _within-cluster_, -- _sum of square_, measures the compactness of the clustering -- - We want it to be as **small** as possible. --- # Implementing the Algorithm K-means algorithm can be summarized as follows: - Specify the number of clusters (k) to be created - User choice .. say we pick 5  --- - Select randomly k objects from the data set as the initial cluster `centers` or `means`  --- - Assigns each observation to their closest centroid, based on the Euclidean distance between the object and the centroid  --- - For each of the `k` clusters, the cluster centroid is updated by calculating the new mean of all the data points assigned to that cluster.  --- - Iteratively _minimize_ the total within sum of square. That is, iterate the assignment and centroid updating until the cluster assignments stop changing - or - the maximum number of iterations is reached. - Repeat until no observations change cluster  --- # Making 2 clusters! ```r set.seed(09032020) # random process becomes repeatable k2 <- kmeans(data, centers = 2) str(k2) ``` ``` List of 9 $ cluster : Named int [1:178] 1 2 1 1 1 1 1 1 1 1 ... ..- attr(*, "names")= chr [1:178] "1" "2" "3" "4" ... $ centers : num [1:2, 1:3] 0.576 -0.849 0.363 -0.535 0.441 ... ..- attr(*, "dimnames")=List of 2 .. ..$ : chr [1:2] "1" "2" .. ..$ : chr [1:3] "Alcohol" "Malic" "Ash" $ totss : num 531 $ withinss : num [1:2] 238 120 $ tot.withinss: num 358 $ betweenss : num 173 $ size : int [1:2] 106 72 $ iter : int 1 $ ifault : int 0 - attr(*, "class")= chr "kmeans" ``` --- ```r names(k2) ``` ``` [1] "cluster" "centers" "totss" [4] "withinss" "tot.withinss" "betweenss" [7] "size" "iter" "ifault" ``` -- The output of kmeans is a _list_ with several elements. The most important being: -- **cluster**: A vector of integers (from 1:k) indicating the cluster to which each point is allocated. -- **centers**: A matrix of cluster centers. -- **totss**: The total sum of squares. -- **withinss**: Vector of within-cluster sum of squares, one component per cluster. -- **tot.withinss**: Total within-cluster sum of squares, i.e. sum(withinss). -- **betweenss**: The between-cluster sum of squares, i.e. `\(totss-tot.withinss\)`. -- **size**: The number of points in each cluster.  - Install `climateR` (remotes::install_github("mikejohnson51/climateR")) - Pick 2-4 climate variables for a state of your choice for one month of your choice (winter,summer, spring, etc) - Pick your climate variables based on the state and month you choose - You can find available climate variables using (`param_meta$terraclim`) (use the `call` column) ```r param_meta$terraclim ``` ``` common.name call 1 aet aet 2 water_deficit def 3 palmer PDSI 4 pet pet 5 prcp ppt 6 q q 7 soilm soil 8 srad srad 9 swe swe 10 tmax tmax 11 tmin tmin 12 vp vap 13 vpd vpd 14 wind ws description units 1 Actual Evapotranspiration mm 2 Climatic Water Deficit mm 3 Palmer Drought Severity Index 4 Reference Evapotranspiration mm 5 Accumulated Precipitation mm 6 Runoff mm 7 Soil Moisture at End of Month mm 8 Downward Shortwave Radiation Flux at the Surface W/m2 9 Snow Water Equivalent at End of Month mm 10 Maximum 2-m Temperature C 11 Minimum 2-m Temperature C 12 2-m Vapor Pressure kPa 13 Mean Vapor Pressure Deficit kPa 14 Wind Speed at 10-m m/s ``` --- - Implement a k-means classification for your state and your variables. - Plot your final image using a nice color palette --- # Submission Submit your knit document to Gauchospace


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I have worked with a wide variety of technologies and langauges.
Currently building solutions with C#, MVC, MySQL, Javascript, Bootstrap & jQuery.
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Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Target range: 225 - 275
Tappecue is a wireless, Internet connected thermometer. This panel displays your cook data, so you can stop checking your phone and focus on your work. Simply start your cook with your Tappecue app on your device, then log in here. Your current cook data will display here while you're logged in.
We hope you like it!
This panel was made by James Lockman. He doesn't have any connection to Tappecue, but he is an enthusiastic Tappecue customer and Creative Cloud extensions tinkerer.


Lifetracker is an application where a user can track their progress
of self defined, periodic goals. Whenever a user accomplishes one of their goals,
they can mark it as complete. Every 24 hours, the internal clock resets, and the
user's goals will be made available again to mark as complete.


Works best with Google Chrome or Safari. You may experience issues when using Firefox.
For more details, visit https://record3d.app/features


Proportion can be used to make animations. This is mostly a JavaScript trick:
set up a routine to draw, and tell JavaScript to call it over and over. Use a global variable to
keep track of the frame number, and use the frame number to change what is drawn.
Please look at the source code of this page for more information.


| 1 | package fr.sii.ogham.core.resource.resolver; | |
| 2 | ||
| 3 | import fr.sii.ogham.core.exception.resource.ResourceResolutionException; | |
| 4 | import fr.sii.ogham.core.resource.Resource; | |
| 5 | import fr.sii.ogham.core.resource.path.ResolvedPath; | |
| 6 | import fr.sii.ogham.core.resource.path.ResolvedResourcePath; | |
| 7 | import fr.sii.ogham.core.resource.path.ResourcePath; | |
| 8 | ||
| 9 | /** | |
| 10 | * Decorates an {@link AbstractPrefixedLookupPathResolver} to manage a default | |
| 11 | * case (no lookup found). | |
| 12 | * | |
| 13 | * @author Cyril Dejonghe | |
| 14 | * | |
| 15 | */ | |
| 16 | public class DefaultResourceResolver implements DelegateResourceResolver { | |
| 17 | /** | |
| 18 | * The delegate resolver that will do the real resource resolution | |
| 19 | */ | |
| 20 | private AbstractPrefixedLookupPathResolver delegate; | |
| 21 | ||
| 22 | /** | |
| 23 | * Initialize the resolver with the mandatory delegate. | |
| 24 | * | |
| 25 | * @param delegate | |
| 26 | * the resolver that will do the real resource resolution | |
| 27 | */ | |
| 28 | public DefaultResourceResolver(AbstractPrefixedLookupPathResolver delegate) { | |
| 29 | super(); | |
| 30 | this.delegate = delegate; | |
| 31 | } | |
| 32 | ||
| 33 | @Override | |
| 34 | public ResolvedPath resolve(ResourcePath path) { | |
| 35 | ResolvedPath result = delegate.resolve(path); | |
| 36 |
1
1. resolve : negated conditional → NO_COVERAGE |
if (result == null) { |
| 37 | result = new ResolvedResourcePath(path, null, path.getOriginalPath()); | |
| 38 | } | |
| 39 |
1
1. resolve : replaced return value with null for fr/sii/ogham/core/resource/resolver/DefaultResourceResolver::resolve → NO_COVERAGE |
return result; |
| 40 | } | |
| 41 | ||
| 42 | @Override | |
| 43 | public boolean supports(ResourcePath path) { | |
| 44 |
1
1. supports : replaced boolean return with false for fr/sii/ogham/core/resource/resolver/DefaultResourceResolver::supports → NO_COVERAGE |
return true; |
| 45 | } | |
| 46 | ||
| 47 | @Override | |
| 48 | public Resource getResource(ResourcePath path) throws ResourceResolutionException { | |
| 49 |
1
1. getResource : replaced return value with null for fr/sii/ogham/core/resource/resolver/DefaultResourceResolver::getResource → NO_COVERAGE |
return delegate.getResource(resolve(path)); |
| 50 | } | |
| 51 | ||
| 52 | @Override | |
| 53 | public ResourceResolver getActualResourceResolver() { | |
| 54 |
2
1. getActualResourceResolver : negated conditional → NO_COVERAGE 2. getActualResourceResolver : replaced return value with null for fr/sii/ogham/core/resource/resolver/DefaultResourceResolver::getActualResourceResolver → NO_COVERAGE |
return delegate instanceof DelegateResourceResolver ? ((DelegateResourceResolver) delegate).getActualResourceResolver() : delegate; |
| 55 | } | |
| 56 | } | |
Mutations | ||
| 36 |
1.1 |
|
| 39 |
1.1 |
|
| 44 |
1.1 |
|
| 49 |
1.1 |
|
| 54 |
1.1 2.2 |


Sectors
The classic month-to-month payrolls number is a strong indicator of the health of the economy, but it doesn't capture the fact that, even in the depths of a recession, some sectors thrive, while others aren 't adding jobs even during a sustained recovery.
Piecemeal Recovery
Below, the economy broken down into eighteen large, identifiable sectors, sorted by how each sector has performed in a given month. Click on any month for a snapshot of each sector's performance.
Number of sectors gaining or losing jobs in a given month
Display change since
Order boxes by
Color boxes by


HBLOHandler
@interface HBLOHandler : NSObject
A handler is a class that is consulted by Opener when the system is about to open a URL. If a handler returns an NSURL from openURL:sender:, this URL will be used instead. If the handler doesn’t want to replace the URL, it returns nil.
Opener handles enabling and disabling of the handler for you. If you would like to override this and provide your own preferences, you can set preferencesBundle and preferencesClass.
-
Name of the handler, shown in Settings.
Declaration
Objective-C
@property (readwrite, retain, nonatomic) NSString *_Nonnull name;
Swift
var name: String { get set }
-
Identifier of the handler, used internally by Opener.
To prevent conflicts, use a reverse DNS name, such as your package’s identifier. If your handler previously supported Opener versions prior to 2.0, use the name you passed to -[HBLibOpener registerHandlerWithName:block:] so the user’s preferences are retained.
Declaration
Objective-C
@property (readwrite, retain, nonatomic) NSString *_Nonnull identifier;
Swift
var identifier: String { get set }
-
Custom Preferences list controller bundle.
If nil, a switch will be shown in Settings, and enabled/disabled state is handled by Opener. Otherwise, tapping the cell will push your list controller, and enabled state is handled by your code.
See
preferencesClassDeclaration
Objective-C
@property (readwrite, retain, nonatomic, nullable) NSBundle *preferencesBundle;
Swift
var preferencesBundle: Bundle? { get set }
-
Custom Preferences list controller class.
Refer to preferencesBundle for more details. If this is nil, the principal class of the bundle will be used.
See
preferencesBundleDeclaration
Objective-C
@property (readwrite, retain, nonatomic, nullable) NSString *preferencesClass;
Swift
var preferencesClass: String? { get set }
-
Called when a URL is opened in order to check if your handler has an override of the URL.
Declaration
Objective-C
- (nullable id)openURL:(nonnull NSURL *)url sender:(nullable NSString *)sender;
Swift
func open(_ url: URL, sender: String?) -> Any?
Parameters
url
The original URL that the user wants to open.
sender
The bundle identifier of the app that invoked the URL open request. If the request was invoked through SpringBoard or a non-graphical program such as
uiopen
, this argument is nil. @returns An NSURL that will be opened instead of the original, an NSArray of NSURLs for multiple apps, or nil to not change the URL.


--- layout: docs category: api title: Mapbox GL JS API navtitle: API permalink: /api navigation: <%= toc %> ---
mapbox-gl-js
mapbox-gl-cocoa


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--- layout: page title: About Me description: Welcome to my blog, where I document my learning. background: '/img/bg-about.jpg' ---
Topics are about native, cross platform native mobile app development and automation testing.


Imray and Adlard Coles Pilot Books are available at a discounted price for Noonsite.com users via World Cruising Club
Grenada to The Virgin Islands
By Jacques Patuelli
Published by Imray 3rd Edition 2014
ISBN:<PHONE_NUMBER>818
Fully illustrated with plans and photos, many of which are new for this third edition, the guide is packed with interesting and useful background information on the Caribbean; its history, tourism, geography and details on sailing in the islands.
Noonsite welcomes information and updates especially regarding clearance, customs and immigration procedures from cruisers visiting this country.
Please E-mail noonsite with any new information, updates or corrections. Even just a short email confirming that the current data is accurate would be most helpful.