Vedanta emerges as the highest bidder for Jamkhani coal block in Odisha
This is the company's second coal block after Chotia coal block in Chhattisgarh that has an annual capacity of 1 million tonne
by Press Trust of IndiaVedanta Ltd on Wednesday said it has emerged as the highest bidder for Jamkhani coal block in Sundargarh district, Odisha, in the 10th tranche of captive coal block auction conducted by the government.
The coal block is in proximity to the company's Jharsuguda aluminium smelter.
The Jamkhani coal block is one of the most attractive coal blocks for the company's Jharsuguda plant in terms of location, annual capacity, reserves and readiness to produce.
The approved per annum capacity of the mine is 2.6 million tonnes, it said in a release.
"It has an extractable reserve of 114 million tonnes. Once operational, it will provide fuel security, improve power availability and further strengthen the company's aluminium operations and performance".
This is the company's second coal block after Chotia coal block in Chhattisgarh that has an annual capacity of 1 million tonne.
Vedanta Limited is a subsidiary of Vedanta Resources Limited.


Born and raised in Berkeley, California, Evan Hughes left for New York in 2007 to begin the jazz studies program at New York University. While at NYU, he worked closely with jazz icons such as Joe Lovano, John Scofield, George Garzone, and Brian Lynch, touring Europe, Asia, and Latin America.
After graduating NYU, Evan worked for three years with multi-grammy winning producer and composer Don Sickler, developing the "Jazz Drum Corner" as a valuable asset and educational tool to Mr. Sickler's already extensive music publications. Evan also taught high school music ensembles at the Calhoun School in New York City, and participated in Jazz at Lincoln Center's "Jazz for Young People" program. Evan has continued to tour with longtime musical partners Julian Waterfall Pollack & Ben Flocks, as well as Juno award winning singer Sophie Milman.
Evan moved back to the Bay Area in 2014 to pursue a career in software engineering. In November 2014, he started at Dev Bootcamp, an 18-week, 1000+ hour intensive course on web-development. At Dev Bootcamp, he focused on Ruby and Javascript, constantly applying his new tools by building real world applications. He learned not only frameworks such as Rails and Sinatra, but practiced standard development strategies such as pair-programming, Test-Driven Development, Git workflow, and Agile development.
Trading Faces is a game of silly selfies.  The best mimic wins!
This app is fully decoupled, including decoupled Oauth through Facebook. The game emphasizes a single-page experience and a carefully crafted game flow which hides game logic to emphasize a positive user experience.
Sous-Chef is an app where online recipe lovers can assemble all their recipes for the week, and have their shopping list texted to their phone.
 Sous-Chef makes this easier by compiling all of the recipes your planning to cook (for the week or so), and texting the ingredient list to your phone.
This app is build on Sinatra, with a Postresql and Active Record database. It uses Yummly and Twilio API's.
Finding attractive solar markets via chloropleth map visualization of utility data and solar irradiance across the US. This project was created in 8 hours as part of SfunCube's Solar Hackathon 2015.
We wanted to create a simple tool for solar companies to target potential solar customers. SolMap pulls data from a variety of sources in order to determine the most attractive solar markets in the country and display it in an attractive way.
Built With: Ruby on Rails, JavaScript, jQuery, D3.js, NREL API, Genability API.
Optimize logistics for resources needed after the earthquake that hit Nepal on April 25, 2015.
This rails app aims to create transparency between donors and beneficiaries(relief centers) in disaster areas. The goal is to allow relief centers list their needs (along with urgency) and have donors claim those needs and find relief centers to donate to and discover what items are most needed.
Built With: Ruby on Rails, JavaScript, jQuery, Mapbox.


Birthday playlist 🔥💯 Happy Birthday BIRTHDAY BITCH🎂👑🤘🏽🎉 Birthday jams Birthday Songs Playlist Happy Birthday 2021 (Best Birthday playlist in the world ) BIRTHDAY PLAYLIST😆💕🎉 Happy Birthday Playlist Birthday Party Music Birthday bitch🍑


Logged in user:
| Roles:
Hello Spring Security
This is an unsecured page, but you can access the secured pages after authenticating.
Go to the
secured pages


The bag tag scanned belongs to the following person:
John Doe
1234 Something Rd, CA 91739
(909)123-4567
<EMAIL_ADDRESS>Edit Contact


Information
RTTrPL is used to stream lighting fixture and DMX information to third parties interested in overwriting fixture DMX values sent from a lighting console, for control over said fixtures. RTTrPL output should be triggered by motion data, DMX input, show starting/stopping, and third party requests. As such, it should not send at a fixed rate like the RTTrPM protocol.
Data Structures
An RTTrPL packet is a list of universes, each of which contains a nested list of spots (fixture IDs), which further contain a nested list of channels and their values:
-
Controlled Universe
-
Controlled Fixtures within each Universe
-
Channels to be controlled
-
DMX Values of controlled channels
General Information
-
In general the Peer is responsible for DMX merging
-
The Peer buffer and RTTrPL generating buffer need to be synchronized
-
Synchronization model: Snapshot / Update, which balances performance and implementation difficulty
-
Snapshot and Update share the same packet format, the type should be indicated by the Action field in the Lighting Output module
-
Snapshot contains all channels of all universes that are being controlled while Update changes only a portion of the buffer
-
An Update may contain one or more universes
-
Hold Time controls when to release the buffer, if a timeout ouccurs, the Peer should release its buffer
-
Out of Sync detection: Lighting Sequence in Lighting Output module is a sequentially increasing number, if the Peer receives packets out of sequence, it should wait for a Snapshot packet from the generator to re-sync
Downloads
The RTTrP Repository has stub code available which contains packet definitions of RTTrPL. Please visit the following for Python and C++ code respecitvely:


We are an alternative rock band just starting out and excited to get our music out. As we were getting ready to start producing songs, the pandemic hit and we were forced to create our music distantly. The result was surprising as we got more motivated and our first EP made its way to completion!
georgeyofficial@gmail.com


Fleet St legend Chris Moncrieff dies aged 88
PA’s former political editor was hailed as “the one journalist who mattered”.
Chris Moncrieff, one of the most respected lobby journalists of his generation, has died. He was 88.
The former political editor of PA, who was hailed as “the one journalist who mattered” by former Prime Minister Tony Blair, died in hospital on Friday morning after a short illness. his family said.
He retired after 32 years at Westminster in 1994, but returned to work the next day and continued to contribute to the agency until his death.
Pete Clifton, PA’s editor-in-chief, said: “Moncrieff was the ultimate news agency journalist – great contacts, always close to the action, working some epic hours and obsessed by getting stories out before everyone else.
“He had no interest in any political agenda or viewpoint, just making sure he was first to write about it.
“On the rare occasion he took a holiday, we could expect him to file news stories he’d picked up on the promenade, and until very recently he was still filing us the ‘quotes of the day’ feature for the newswire, as well as drawing on his extraordinary memory to file a weekly politics column for our regional newspaper subscribers.
“Legend gets overused, but there’s no doubt Moncrieff was a PA legend and a remarkable political reporter.
“We are profoundly sad today, but cheered by the many stories of Moncrieff we can share.”
Described in Westminster as “the man with the lived-in face and slept-in suit”, Moncrieff’s style was classic news reporting and he roamed Westminster with order papers stuffed under his arm and notebooks in his pockets as he encouraged MPs to call him at any time of day or night.
He joined the national news agency’s parliamentary staff in 1962 before becoming a lobby reporter in 1973 and chief political correspondent (later political editor) in 1980.
Westminster’s The House magazine said he was a “one-man dynamo for whom news is food and drink is Guinness”.
The press bar of the House of Commons was named after him in 2007.
He had four children with his late wife Margaret.


A "range" slider is one that has a minimum and maximum handle. In this configuration the slider always has TWO values instead of one.


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VOLCANO A film review by Steve Rhodes Copyright 1997 Steve Rhodes
RATING (0 TO ****): ** 1/2
Hollywood's paucity of ideas has given way to a surfeit of twins. This is the year of two movies for every concept. Steve Profantaine's story is being duplicated with PREFONTAINE and PRE. There are two comedies about tenth high school reunions, GROSSE POINTE BLANK and ROMY AND MICHELE'S HIGH SCHOOL REUNION. And in the blockbuster category, we have two disaster movies about volcanoes. One which played close, but not close enough, to parody was called DANTE'S PEAK. The other is the serious, special effects extravaganza known as VOLCANO. It is also the only one of the two volcano movies with decent acting. Be warned, however, the year is early so Hollywood could well turn any or all of these twins into triplets. But let's hope not.
VOLCANO is not about some known volcano in a remote forest. Oh no, this volcano is an unknown one under one of the largest cities in the world -- Los Angeles. The film has easily the best tag line this year: "The Coast is Toast." Only the film industry would equate the destruction of tinseltown as the elimination of the entire West Coast.
Before getting into the heart of the review, let me comment first on the real star -- the spectacular special effects. The river of lava has a realism and a power that needs to be seen to be appreciated.  More interesting, however, is the way in which the movie hints at the volcano's force through steam that blows off the manhole covers.
The story has two acts. The first leads up to the discovery of the exact nature of the disaster under their feet. The film is both involving and intriguing during this whole exploration phase.
Then the script by Jerome Armstrong and Billy Ray makes the classic horror movie mistake, rushing the monster, a. k. a. the lava, onto the screen too quickly because they lack confidence in their ability to hold the audience's attention with mere suspense. Lots of action and big explosions -- now, that will make the audience feel they got their seven bucks worth and make them tell their friends to see that awesome movie. This second act, which takes more than three quarters of the film, outwears its welcome. Periodically fun, but too often tedious.
Tommy Lee Jones (THE FUGITIVE) gives a good, albeit far from his best, performance as Mike Roark, the head of LA's Office of Emergency Management. Better is Anne Heche (DONNIE BRASCO) as scientist Dr. Amy Barnes, who becomes his sidekick. She supplies the scientific insight to what may be happening, and together they devise various schemes to kill the monster, oops, I mean lava. The plausible chemistry between them never becomes overblown, and the usual big fight between the leads never occurs.
The second problem with the script concerns the small human melodramas. Whereas the overall logic of the picture is presented plausibly enough for a movie, the unbelievable heroics of the minor actors begin to take a toll on your brain. Several people agree to certain death only to be a hero. Would you stay with someone in an exploding building just because they were trapped?  The dramatics include those of the mandatory child endangerment scene and the one of the dog about to perish.
Even though director Mick Jackson cannot save the sagging script, the actors and the special effects keep your attention.
Other than the leads, we have Don Cheadle, who was excellent in ROSEWOOD, playing Mike's second-in-command Emmitt Reese. He manages to take the film's mundane dialog and breath life into it. His character becomes at once both funny and strong. The script could have paced the long second act better by feeding him some decent humorous fare.
Jacqui Kim (DISCLOSURE) takes the poorly written role of the noble Dr. Jaye Calder and transform it into a mildly interesting character. Gaby Hoffmann (EVERYONE SAYS I LOVE YOU) plays Mike's scared but ultimately brave daughter.
VOLCANO, despite its faults, does entertain a crowd. Memorable? Hardly, but the main actors are worth seeing, and that first act has so much promise it almost makes you want to forgive them for blowing the second.
VOLCANO runs 1:45. It is rated PG-13 for the intensity of the disaster and the associated injuries. Depending on how well your child can handle disaster movies, the film could be seen by kids as young as 8, but it would be too much for our 8-year-old. The trailers for it scared him badly so we certainly would not take him. I recommend the film for its entertainment value and give it ** 1/2. If you can only see one volcano movie this year, then this is the one to see.
**** = A must see film. *** = Excellent show. Look for it. ** = Average movie. Kind of enjoyable. * = Poor show. Don't waste your money. 0 = Totally and painfully unbearable picture.
REVIEW WRITTEN ON: April 23, 1997
Opinions expressed are mine and not meant to reflect my employer's.
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


Have you discovered the magic of the shower?
There's something about those streams of water that makes it a place where creativity thrives.
Isn't it ironic? For creativity to thrive in a space so confined?
I find most ideas come to me in the shower. Bug fixes for an application, ideas for a short film - anything. Pausing in this confined box as water flows down my cheeks lets me think of thoughts outside (which is why I drew the lightbulb beyond the shower space).
A cup of coffee in a café and a laptop with with a million tabs of design ideas - one can argue that this is sufficient for creativity, for inspiration to flow within.
But it's in the shower where these thoughts are processed, refined, and turned into something uniquely mine.
So whenever I feel lost; whenever a billion browser tabs, or a hundred cups of coffee, or a long stroll in the park don't seem to stimulate my bi-polar brain,
I treat it to some magic in the shower.


Eat Healthy and On Time
Foods which are low in nutritional value and have too many calories can pose serious health problems, including weight gain, cardiovascular problems and diabetes. It is important to stick to a healthy diet and a strict routine.Instead of starchy foods, choose wholegrain variants which contain more fibre, and keep you feeling full.
Avoid processed or packaged foods that contain too much sugar. Excess sugar has been linked to energy spikes followed by a crash, while too much salt can lead to high blood pressure and an increased risk of strokes and heart disease.


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My Bonnie lies over the ocean. My Bonnie lies over the sea. My Bonnie lies over the ocean. Oh, bring back my Bonnie to me.
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Note
Click here to download the full example code
User-defined Custom Stainers¶
This page shows an example of how to create your own user-defined custom stainers, which subclasses from the Stainer class.
from ddf.stainer import Stainer
When creating a new stainer, it needs to inherit from the Stainer class in ddf.stainer.
The initialisation should include the name, row indices (if applicable) and column indices (if applicable). If any other relevant initialisations are required, they can be included as well. If the row or column indices do not apply to the stainer, an empty list can be provided to the superclass init.
When defining the transform, the parameters to be included should be df (the dataframe to be transformed), rng (a RNG Generator), row_idx = None and col_idx = None.
In the transform method, the self._init_transform(df, row_idx, col_idx) method can be called to accurately generate the row_idx and col_idx (This allows the Stainer to work correctly with DDF). The transform method should then implement the Stainer.
To provide relevant statistics to the user, messages and timings can be added. These can be added via self.update_history(message, time)
A row mapping and column mapping are also required. These represent a movement or creation of any row / col in the dataframe. It should be formatted as a dictionary where key = old_row/col_index, value = List of indices of where the corresponding row/col ended up in the new dataframe. For instance, if the index-2 row was duplicated and is now the index-2 and index-3 row, the row_map should contain the entry {2: [2, 3]}. If the rows/columns order were not altered, an empty dictionary should be returned.
The transform function should return a tuple of the new dataframe, row mapping, and the column mapping.
Refer to the sample code below for an example.
class ShuffleStainer(Stainer):
def __init__(self, name = "Shuffle"):
super().__init__(name, [], []) # name, row_idx, col_idx
def transform(self, df, rng, row_idx = None, col_idx = None):
new_df, row_idx, col_idx = self._init_transform(df, row_idx, col_idx)
start = time()
"""
## Implementation of Shuffle ##
Creates new_df
Creates new_idx = Original row numbers, in order of the new row numbers
"""
pass
"""Creates the mapping"""
row_map = {}
for i in range(df.shape[0]):
row_map[new_idx[i]] = [i]
end = time() # Timer to be added into history
self.update_history("Order of rows randomized", end - start) # message, time
return new_df, row_map, {} # new dataframe, row map, column map
Total running time of the script: ( 0 minutes 0.001 seconds)


Sidhpur Foundation is a 501(c)(3) non-profit, non-governmental organization (NGO) incorporated under the laws of the United States. The Foundation's programs primarily target communities originating from Sidhpur and surrounding rural areas of Northern Gujarat, India.


Class: CrawlerProcessJob::CrawledData
- Inherits:
-
Object
- Object
- CrawlerProcessJob::CrawledData
- Defined in:
- lib/crawler/workers/crawler_process_job.rb
Overview
wrapper class around received content from backend
Instance Attribute Summary (collapse)
-
- (Object) base_url
Returns the value of attribute base_url.
-
- (Object) body
Returns the value of attribute body.
-
- (Object) character_set
Returns the value of attribute character_set.
-
- (Object) crawl_id
Returns the value of attribute crawl_id.
-
- (Object) error
Returns the value of attribute error.
-
- (Object) headers
Returns the value of attribute headers.
-
- (Object) internal_urls
Returns the value of attribute internal_urls.
-
- (Object) length
Returns the value of attribute length.
-
- (Object) links
Returns the value of attribute links.
-
- (Object) location
Returns the value of attribute location.
-
- (Object) mime_type
Returns the value of attribute mime_type.
-
- (Object) redirect_through
Returns the value of attribute redirect_through.
-
- (Object) redis_options
Returns the value of attribute redis_options.
-
- (Object) response_time
Returns the value of attribute response_time.
-
- (Object) source_id
Returns the value of attribute source_id.
-
- (Object) status_code
Returns the value of attribute status_code.
-
- (Object) text_content
Returns the value of attribute text_content.
-
- (Object) url
Returns the value of attribute url.
Instance Method Summary (collapse)
-
- (CrawledData) initialize(params = {})
constructor
A new instance of CrawledData.
Constructor Details
- (CrawledData) initialize(params = {})
Returns a new instance of CrawledData
22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 22 def initialize(params = {}) params.each do |name, value| value = case value when 'http://localhost:7541/' 'diariojaen.es' when 'http://localhost:7542/' 'ideal.es' when 'http://localhost:7543/' 'andaluciainformacion.es' else value end send("#{name}=", value) end end |
Instance Attribute Details
- (Object) base_url
Returns the value of attribute base_url
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def base_url @base_url end |
- (Object) body
Returns the value of attribute body
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def body @body end |
- (Object) character_set
Returns the value of attribute character_set
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def character_set @character_set end |
- (Object) crawl_id
Returns the value of attribute crawl_id
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def crawl_id @crawl_id end |
- (Object) error
Returns the value of attribute error
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def error @error end |
- (Object) headers
Returns the value of attribute headers
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def headers @headers end |
- (Object) internal_urls
Returns the value of attribute internal_urls
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def internal_urls @internal_urls end |
- (Object) length
Returns the value of attribute length
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def length @length end |
- (Object) links
Returns the value of attribute links
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def links @links end |
- (Object) location
Returns the value of attribute location
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def location @location end |
- (Object) mime_type
Returns the value of attribute mime_type
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def mime_type @mime_type end |
- (Object) redirect_through
Returns the value of attribute redirect_through
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def redirect_through @redirect_through end |
- (Object) redis_options
Returns the value of attribute redis_options
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def @redis_options end |
- (Object) response_time
Returns the value of attribute response_time
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def response_time @response_time end |
- (Object) source_id
Returns the value of attribute source_id
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def source_id @source_id end |
- (Object) status_code
Returns the value of attribute status_code
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def status_code @status_code end |
- (Object) text_content
Returns the value of attribute text_content
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def text_content @text_content end |
- (Object) url
Returns the value of attribute url
17 18 19 |
# File 'lib/crawler/workers/crawler_process_job.rb', line 17 def url @url end |


| < Day Day Up > |
8.7 The null Storage SchemeSquid has a fifth storage scheme called null. As the name implies, this is more of a nonstorage scheme. Files that are "written" to a null cache_dir aren't actually written to disk. Most people won't have any reason to use the null storage system. It's primarily useful if you want to entirely disable Squid's disk cache.[4] You can't simply remove all cache_dir lines from squid.conf because then Squid adds a default ufs cache_dir. The null storage system is also sometimes useful for testing and benchmarking Squid. Since the filesystem is typically the performance bottleneck, using the null storage scheme gives you an upper limit of Squid's performance on your hardware.
To use this scheme you must first specify it on the —enable-storeio list when running ./configure: % ./configure --enable-storeio=ufs,null ... You can then create a cache_dir of type null in squid.conf: cache_dir /tmp null It may seem odd that you need to specify a directory for the null storage scheme. However, Squid uses the directory name as a cache_dir identifier. For example, you'll see it in the cache manager output (see Section <IP_ADDRESS>). |
| < Day Day Up > |


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Thriller
If we were villain
Oliver Marks has just served ten years in jail - for a murder he may or may not have committed. On the day he's released, he's greeted by the man who put him in prison. Detective Colborne is retiring, but before he does, he wants to know what really happened a decade ago. [ 4.1\5 ]
Gone Girl
Marriage can be a real killer. On a warm summer morning in North Carthage, Missouri, it is Nick and Amy Dunne’s fifth wedding anniversary. Presents are being wrapped and reservations are being made when Nick’s clever and beautiful wife disappears from their rented McMansion on the Mississippi River. Husband-of-the-Year Nick isn’t doing himself any favors with cringe-worthy daydreams about the slope and shape of his wife’s head, but passages from Amy's diary reveal the alpha-girl perfectionist could have put anyone dangerously on edge. Under mounting pressure from the police and the media—as well as Amy’s fiercely doting parents—the town golden boy parades an endless series of lies, deceits, and inappropriate behavior. Nick is oddly evasive, and he’s definitely bitter—but is he really a killer? [ 4.1\5 ]


Game time!
Kick off!
Start with your first game below, or click one to start any game!
Games
Lon
3
-
4
Agustin
Adam
0
-
0
Elliot
Elliot
0
-
0
Lon
Lon
0
-
0
Adam
Adam
0
-
0
Agustin
Agustin
0
-
0
Elliot
Table
Player
Games Played
Won
Loss
Draw
GD
Lon
0
0
0
0
Elliot
0
0
0
0
Agustin
0
0
0
0
Adam
0
0
0
0


HTMLKit is a WHATWG specification-compliant Objective-C framework for parsing and serializing HTML documents and document fragments for iOS and OSX.
HTMLKit parses real-world HTML the same way modern web browsers would.
HTMLKit comes armed with a CSS3 Selectors engine for querying the DOM.


INTERONET
A Full-Stack-Programmable SDN Testbed leaded by XJTU.
Web UI
A slice including SDN switch and hosts could be created by tenants. Any topology can be customized via simply DRAG and DROP among switches in Web. More fine-grained network control are supported, Comparing OpenStack. Cross-Domain could be released in next generation InterONet.
Switch
FPGA, kernel, filesystem, SDN switch and SDN controller could be programmable. Switch FPGA logic could be dispatched in any switch as you like. Linux Kernel could be re-compile as you like. SDN Switch like OVS, ofsoftswitch13 could be re-build as you like. SDN controller like Ryu, ODL, FloodLight could be provided as you like. Any layer of above feature can be programable as you like. What we would do is giving your a experimental platform.
Virtualization & Physicalization
KVM technology would be used to guarantee the High Availability of InterONet. One Switch would be allocated for ONLY ONE tenant for ensuring network performance.
Open API
KVM technology would be used to guarantee the High Availability of InterONet. One Switch would be allocated for ONLY ONE tenant for ensuring network performance.
Our Services
Create Slice
You can order a slice which include SDN switch and virtual machine
Check Slice
You can check the slices you order that are running or waiting
Update Slice
You can update your running slices
Stop Slice
You can stop your running slices or waiting slice
Log
1
MAY


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Details on how to use the daemon mode can be found in the QF-Test manual.
Note: The daemon has to be started seperately. The plugin will not start or terminate the daemon.


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'), cmap='gray')
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
# Here we create placeholders for real input images (inputs_real), tenzor of z data (inputs_z) and learning rate(lr)
inputs_real = tf.placeholder(tf.float32,
shape=[None,image_width, image_height,image_channels],
name='input_real')
inputs_z = tf.placeholder(tf.float32, (None, z_dim), name='input_z')
lr = tf.placeholder(tf.float32)
return inputs_real, inputs_z, lr
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the generator, tensor logits of the generator).
#declare global var alpha with default value (then we can modify it during hyperparameters tuning)
#we need it to use leak relu
alpha =0.1
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param image: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
with tf.variable_scope('discriminator', reuse=reuse):
# Input layer is 28x28x1/3
x1 = tf.layers.conv2d(images, 56, 5, strides=2, padding='same',
kernel_initializer = tf.random_normal_initializer(mean = 0, stddev = 0.02))
relu1 = tf.maximum(alpha * x1, x1)
# 14x14x32
x2 = tf.layers.conv2d(relu1, 112, 5, strides=2, padding='same',
kernel_initializer = tf.random_normal_initializer(mean = 0, stddev = 0.02))
bn2 = tf.layers.batch_normalization(x2, training=True)
relu2 = tf.maximum(alpha * bn2, bn2)
# 7x7x128
x3 = tf.layers.conv2d(relu2, 224, 5, strides=2, padding='same',
kernel_initializer = tf.random_normal_initializer(mean = 0, stddev = 0.02))
bn3 = tf.layers.batch_normalization(x3, training=True)
relu3 = tf.maximum(alpha * bn3, bn3)
# 4x4x256
# Flatten it
flat = tf.contrib.layers.flatten(relu3)
logits = tf.layers.dense(flat, 1)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variabes in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
with tf.variable_scope('generator', reuse=not is_train):
# First fully connected layer
x1 = tf.layers.dense(z, 7*7*512)
# Reshape it to start the convolutional stack
x1 = tf.reshape(x1, (-1, 7, 7, 512))
x1 = tf.layers.batch_normalization(x1, training=is_train)
x1 = tf.maximum(alpha * x1, x1)
# 7x7x512 now
x2 = tf.layers.conv2d_transpose(x1, 256, 5, strides=2, padding='same')
x2 = tf.layers.batch_normalization(x2, training=is_train)
x2 = tf.maximum(alpha * x2, x2)
# 14x14x256 now
x3 = tf.layers.conv2d_transpose(x2, 256, 5, strides=2, padding='same')
x3 = tf.layers.batch_normalization(x3, training=is_train)
x3 = tf.maximum(alpha * x3, x3)
# 28x28x128 now
# Output layer
logits = tf.layers.conv2d_transpose(x3, out_channel_dim, 5, strides=1, padding='same')
# 28x28x1/3 out_channel_dim now
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
# Smoothing
smooth = 0.1
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real,
labels=tf.ones_like(d_model_real)*(1 - smooth)))
d_loss_fake = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake,
labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_fake,
labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
# Get weights and bias to update
t_vars = tf.trainable_variables()
d_vars = [var for var in t_vars if var.name.startswith('discriminator')]
g_vars = [var for var in t_vars if var.name.startswith('generator')]
# Optimize
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(g_loss, var_list=g_vars)
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1=beta1).minimize(d_loss, var_list=d_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
#initialize global variables
show_every=100
sample_z = np.random.uniform(-1, 1, size=(50, z_dim))
samples, losses = [], []
steps = 0
# Call inputs
input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2],
data_shape[3], z_dim)
# Call Loss
d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
# call Optimizers
d_opt, g_opt = model_opt(d_loss, g_loss, lr, beta1)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
# TODO: Train Model
steps += 1
# rescale from (-0.5, 0.5) to (-1., 1.)
n_batch_images = 2 * np.array(batch_images, np.float32)
# Sample random noise for G
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run optimizers
_ = sess.run(d_opt, feed_dict={input_real: n_batch_images,
input_z: batch_z,
lr: learning_rate})
_ = sess.run(g_opt, feed_dict={input_z: batch_z, input_real: n_batch_images, lr:learning_rate})
#Show statistic and results
if steps % show_every == 0:
show_generator_output(sess, show_n_images, input_z, data_shape[3], data_image_mode)
train_loss_d = d_loss.eval({input_z: batch_z, input_real: n_batch_images})
train_loss_g = g_loss.eval({input_z: batch_z})
print("Epoch {}/{}, batch {}...".format(epoch_i + 1, epochs, steps),
"Discriminator Loss: {:.4f}...".format(train_loss_d),
"Generator Loss: {:.4f}".format(train_loss_g))
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 128
learning_rate = 0.001
beta1 = 0.1
alpha = 0.1
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 216
learning_rate= 0.0005
alpha = 0.1
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


https://www.softperfect.com/products/networkscanner/
SoftPerfect Network Scanner is a fast universal IPv4/IPv6 scanner with an extensive range of options and advanced features for system administrators and general users interested in computer security. This powerful program can ping computers, scan ports, discover shared folders and comes with flexible filtering and display options. It can retrieve practically any information about network devices via WMI, SNMP, HTTP, SSH and PowerShell.
In addition, it can scan for remote services, registry, files, performance counters and so on. The results can be exported to a variety of formats from XML to JSON.
Key features
Performs a ping sweep and displays live devices.
Fully supports both IPv4 and IPv6 discovery.
Detects hardware MAC-addresses, even across routers.
Detects hidden shared folders and writable ones.
Detects internal and external IP addresses.
Scans for listening TCP ports, some UDP and SNMP services.
Retrieves currently logged-on users, configured user accounts, uptime, etc.
Supports remote SSH, PowerShell and VBScript command execution.
Launches external third party applications.
Exports results to HTML, XML, JSON, CSV and TXT.
Supports Wake-On-LAN, remote shutdown and sending network messages.
Retrieves any system information via WMI, remote registry, file system and service manager.


A tool to help guide people in the direction of meal planning based on current conditions. Patients conditions are automatically pulled from Fast Healthcare Interoperability Resources(FHIR) and available ingredients are entered manually. Then this app provides quick, intermediate, or other meal ideas based on these factors. Recipe results can link users to full recipes as well as display some basic nutritional information.
This solution is a simulation system for a robotic lawnmower. This project started from requirement analysis, creating design documents, implementation the design and multiple layer of testing.
SDPScramble, “An App for Creating, Sharing and Solving Word Scrambles” was developed as an Android app to get experience with a simplified version of the Unified Software Process.
This project aimed to prevent data sniffing from an unexposed remote connection. The product had two major modules. The first was detecting the remote control connection, and the other one was providing several solutions to hide designated files or folders.


In just about all programming languages a program consists of a number of definitions of procedures or functions. Among them is one, called "main" in C, or an anonymous one in Pascal, which is the starting point. The same pattern occurs in grammars, which consist of definitions of non-terminals, including one that is called "start" or whatever. The pattern is also used in most macro expanders in which a collection of macro definitions is processed.
Any one of the definitions consists of two parts: 1) a name, and 2) a body obeying a syntax very specific to the language. In procedural languages like C or Pascal the body is a statement sequence. In functional languages the body is an applicative expression. In grammars the body is a regular expression over terminals and non-terminals. In macro expanders the body consists of literal text. In each case the body may contain calls to items defined elsewhere.
A definition contains a body as a part. The body must satisfy certain syntactic rules, and so must the whole definition. But in all cases the syntax for a whole definition is different from that of its largest part, the body. In procedural languages the body is a statement sequence, but a definition is not. In functional languages a body is an applicative expression, but a definition is not. In grammars a body is a regular expression, but a definition is not. In macro expanders a body is just text, but a definition is not. Lisp looks like an exception, because both bodies and definitions are symbolic expressions, written in a minimal syntax. But there are restrictions on definitions that are not imposed on bodies.
Definitions and bodies play very different roles. The difference is most conspicuous in fully compiled implementations. During compilation definitions produce entries in a symbol table, and the bodies are translated into directly executable machine language, but the bodies are not executed. The resulting compiled program contains no trace of the symbol table (except when it has been compiled for a run with a symbolic debugger).When the compiled program is run, a new structure appaears, typically at least a run-time stack, which did not exist during compilation. Now the body of the main program and any other called bodies can be executed.
The compilation stage need not translate bodies into directly executable machine language. The target language is some idealised machine language which needs to be interpreted. When such a program is run, there will be a run-time stack and in addition a software interpreter. (The portable Pascal implementation P4 works like this.)
Even if the compiler and the interpreter are in the same program, there still are these two stages: 1) reading a program, processing definitions and compiling bodies into some internal form, and 2) running a program by interpreting the internal form. When the program is run, the symbol table is still there, but no new definitions are entered. The run-time stack and other structures are present during reading, but only used now when the translated bodies are executed by the interpreter.
Numerous variations are possible, but the difference between the two stages is always present. So there is no reason to use the same syntax for definitions and bodies. The same applies to Joy.
The syntax for definitions in Joy is
name == bodywhere the body is a concatenative expression. The symbol "==" could even be left out altogether. A definition sequence consists of one or more definitions separated by semicolons. Importantly, unlike "==", the semicolon could not be left out. Definition sequences are headed by "LIBRA" or "DEFINE" and terminated by a period. But none of the the symbols "LIBRA", "DEFINE", "==", ";" and "." denote run-time operations like "+", "cons" or "map" do. The same is true for "HIDE", "IN" and "END" in local definitions.
So, "==" is not a postfix operator because it is not a run-time operator any more that the other symbols used in definitions.
For the sake of having a concrete example, consider the ordinary definition
cube == dup dup * *that is normally processed at compile-time. If such a definition is to be entered into the symbol table at run-time, then the two parts must be available: 1) the name "cube", and 2) the body "dup dup * *". Clearly none of the following will do
cube == dup dup * * cube dup dup * * == cube [dup dup * *] DEFbecause the initial occurence of "cube" will at run-time produce a call to that function which has not yet been defined. So the name of the function being defined has to be expressed in a way that prevents a call and instead produces an entry into the symbol table. Furthermore, the two occurrences of "dup" and of "*" in the first two candidates also have to be prevented from producing a call, as indeed they are in the third candidate.
This suggest the other notation
"cube" [dup dup * *] DEFIn other words, "DEF" would expect a string and a quotation on top ot the stack, it would pop these off and enter the definition. In that case the following would produce the same result:
"uc" reverse "xbe" rest concat [dup dup * *] DEFHowever it is dubious whether such freedom to construct names by string manipulation can do anything but obfuscate a program. Other possibilities are these:
[cube] first [dup dup * *] DEF1 [cube dup dup * *] DEF2In both cases the new symmbol being defined occurs inside a quotation so it is not being executed. In the first case the symbol even ends up on the Joy stack just on its own, but again it is not executed. The two styles are essentially equivalent, although DEF1 and DEF2 have different expectations as to what has to be on top of the stack. Their equivalence can be seen by the mutual definitions - ordinary definitions, that is -
DEF1 == cons DEF2 DEF2 == uncons DEF1Both styles lend themselves to program manipulation before the definitions are entered, for example
[cube] first [* * dup dup] reverse DEF1 [* *] [dup dup] concat [cube] swoncat DEF2Note that this is quite different from the construction of quotations that is often used in Joy before the quotations are processed by a combinator. For example, it is now possible to initialise a definition, say of "current-item", by
[current-item 1] DEF2and to update it with, say an increment of 3, by
current-item 3 + [] cons [current-item] swoncat DEF2This means that the name "current-item" is actually the name of a variable which can be updated in all manners of ways. Hence the language would have assignment statements (with a terrible syntax). But assignment statements are what Joy and all purely functional languages try to avoid.
In the above example, current-item is an integer variable. Clearly one could have string or set or list variables, too. One could also have operator variables, or combinator variables, or quotation variables, or variables that start their life as integer variables and then become all sorts of other kinds of variables. So, allowing definitions to be entered at run-time would open all the possibilities of programs that constantly modify themselves. But it is widely agreed that this is a bad idea.
[dup *] first ==> dup [dup *] second ==> * [dup *] uncons ==> dup [*]Does this make any sense at all? What can one do with such an unadorned unquoted operator?
There are many things one can do with an unadorned operator. Like any other item on the stack, it can be popped, swapped or duped. It can be printed either by an explicit put or, if the setautoput flag is set to 1 or 2, automatically after the execution of the current program. Of course it can also be read back. What is written or read is of course the sequence of 3 characters, d-u-p, in the first case. More interestingly, the unadorned operator can be made part of another quotation, as in
[dup *] first [] cons ==> [dup]The resulting quotation [dup] can become a parameter for a combinator, for example the i-combinator which will just execute what is inside the quotation. So we have
[dup *] first [] cons i == dupIf the operator or combinator is not a primitive, but defined by the user, then one can get the body of its definitions as a quotation. For example, in the current implementation first is a primitive, but second is defined in the initial library inilib.joy:
second == rest firstThe body of that definition is accessible by
[second] first bodywhich will leave the quotation [rest first] on top of the stack.
A: In the 70's it was recognised that programs using structured IFs and WHILEs are easier to get right and easier to read than programs which use GOTOs and in which the pattern of the flow of control has to be inferred by laborious analysis. One reason for adding CASE, REPEAT and FOR was that they make programs even more explicit and easier to understand.
In the functional languages which use lists a lot much of list processing falls into a few recursion patterns which are often abstracted as combinators such as map, filter and fold, and also a few variants such as zipwith. Programs which use these combinators by name are easier to write and easier to read than programs in which the pattern of recursion on lists has to be inferred.
Joy takes this idea a step further by combinators for recursion patterns that are independent of any particular datatype such as lists above. For linear recursion there is the combinator linrec, its special case tailrec, and even more special case while. There is also the more flexible condlinrec. For binary recursion there is the combinator binrec, but so far no more special or more flexible versions. For recursion with arbitrary n-ary branching there is the combinator genrec, so far with no variants. For recursion on trees of any type other than lists there are several combinators. For nested recursion (as in the Ackermann function) there will soon be two combinators nestrec and condnestrec. So far there are no combinators for mutual recursion. All these combinators are more intuitive and descriptive than the well-known "paradoxical" all-purpose recursion combinators (Curry's) Y and (Turing's) T which are frequently defined but never used because they are all-purpose and hence not descriptive.
Of course the execution of programs without explicit GOTOs typically involves its use internally. Similarly, the execution of programs with recursion combinators but without explicit recursion typically involves its use internally. But programs using combinators are easier to write and read than ones using explicit recursion and in which the pattern of all, not just list, recursions has to be inferred. So, if you like, "Recursion considered harmful".
As a bonus, at least for the current implementation, programs using recursion combinators are more efficient than programs using explicit recursion.
1. Joy combinators take quotations as arguments. Other languages would have to use lambda abstractions instead. But many have no way of capturing the current environments.
2. Apart from this, many languages could not even define a lambda counterpart of Joy's simple i combinator - the "dequotation combinator". This rules out most mainstream languages. Some counterpart might be definable in the Lisps, ML, Haskell and Prolog/
3. Again indpendently, there will be a problem about Joy's simple branching combinator ifte. With "eager" evaluation it is not possible to define an ordinary function for branching, as Eva Lou Ator will tell you, in SICP p 23. Branching has to be done with "special forms" cond or if. To define them one needs delayed evaluation or macros. Since the recursion combinators all involve branching they need the same.
4. The next hurdle concerns the number of extra parameters apart from the quotation parameters for combinators. In Joy all parameters, including extra ones just sit on the stack. A different language might do one of the following: (a) Have several versions of combinators for each possible number of extra parameters. (b) If possible, use whatever facility the language has for optional parameters, and put the extras there. (c) Rewrite all functions including combinators as taking a stack (a list) as their sole parameter.
5. Some languages are strongly statically typed, perhaps in a polymorphic way. Finite unions can then solve the problem that combinators are supposed to take as parameters functions of all sorts of base types but also lists of these and lists of lists of base types and so on. But I don't know whether this can handle lists of mixtures of lists of mixtures when the entire mix is unknowable at compile time.
There are languages in which the Y or T combinators can be defined, or at least collections of variants for different number of parameters of the recursing function. Presumably using similar techniques it is possible to define in these languages counterparts of the recursion combinators of Joy. But I have never seen such definitions, and hence never their routine use.
Combinators take functions as parameters, so combinators are second order functions. Are there any second order combinators, functions which take first order combinators as parameters - in other words third order functions? Are there any functions that take as parameters functions which take as parameters functions?
The quick answer is NO, it stops at second order functions.
The more considered answer is that combinators do not take functions as parameters but they take quoted programs as parameters. It is indeed possible to write programs with combinators which take quoted programs as parameters, where the quoted program, when executed, will execute another combinator taking as parameter another quoted program as parameter, and so on. But such apparent higher order examples are just higher order uses of the combinator, they are not examples of higher order combinators.
The following are some examples, all involving the simple i combinators. All just compute the same squaring function. The examples are here grouped according whether the use of the right-most i combinator is first order, second order or third order.
first order use second order use third order use [dup *] i [[dup *] i] i [dup *] [i] i [[[dup *] i] i] i [[dup *] i] [i] i [dup *] [i] [i] i
A less contrived example is the following, used to compute the list comprising the successor, the double and the square of a given number, for example 7.
7 [[succ] [2 *] [dup *]] [i] map ==> [8 14 49]The map combinator is mostly used with a quotation parameter that computes a first order function, but as this example shows, the quotation can also be a combinator. As a final example, here is the ifte combinator used to branch depending on whether the second item on the stack is a leaf (not a list), or a list. In the first case the top quotation will be called with the i combinator, and in the second case with the map combinator:
[pop leaf] [i] [map] ifteNo Joy example is known where a combinator can only be used with quoted combinators as parameters. (This includes, for example, the operations in Church arithmetic.)
[MYNOTES: higher-order-combs continuations oo mess-pass lazy need-stack why-postix reflective get-put-funct cat-theory]
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Dan is currently a Lambda School student and he lives in New Jersey. His experience and skill-set are what makes forLife Fitness possible. He is part of the Front End Development team.
Brandon is currently a Lambda School student and he lives in Utah. He is an integral part of forLife Fitness and his contributions are evident throughout our organization. He is part of the team that designs our gorgeous landing and marketing pages.
Judy is currently a Lambda School student and she lives in the UK. Her designs are what make our application so intuitive and pleasant. She has been designing beautiful User Interfaces for forLife Fitness since 2017.
Samir is currently a Lambda School student and he lives in North Carolina. His energy and desire to learn is paramount to forLife Fitness' growth. He is part of the team that designs our gorgeous landing and marketing pages.
Tatiana is currently a Lambda School student and she lives in California. Her dedication and experience have helped forLife Fitness grow and expand. She is part of the Front End Development team.
Brandon is currently a Lambda School student and he lives in Utah. His dedication and experience have allowed us to deliver quality applications since 2016. He is part of the Front End Development team.
Matt is currently a Lambda School student and he lives in the UK. He is the most experienced member of our team and serves as a mentor to our Junior Developers. He is part of the Back End Development team.


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Katie Carroll (my bride-to-be) has been writing an ongoing series on modesty. Most recently she has written a two-part post on a highly controversial topic - swimsuits.
For the past year, Katie has been seriously following the Lord and seeking His will on the modesty issue. When she concludes the series, I will link back to all the posts. For now, we will look at the swimsuit posts.
- "Let's Talk About Swimsuits!"
In this first post, Katie asks and answers the question: Are modern female swimsuits appropriate to be worn in the presence of men? - "Modest Swimsuits 101"
In this second post, Katie describes what she has decided to wear for a swimsuit, and her experience with it on a trip to the beach.
I highly recommend these posts to all Christian females - and guys should find them interesting too.
I pray that other girls / women will follow Katie's example in this area.
-PJ


NetBeans itself implements two filesystems: a local filesystem, which encapsulates access to the operating system's normal files; and a JAR filesystem, which allows users to mount Java Archive Files as if they were read-only directories.
Using the Filesystems API, third parties may add support for access to file-like objects stored in some different manner - for example, in a database or proprietary object storage system. More commonly, module authors should use this API whenever they need access to files; then their module should work automatically with any filesystem supported by NetBeans.
Other capabilities provided by the Filesystems API include locking files during write operations; listening for changes in a file's status, so that another part of NetBeans may reflect that change; and providing support for including the filesystem in the runtime class path of an external compiler or executor.


# -*- coding: utf-8 -*-
# Copyright (C) 2004-2018 by
# Aric Hagberg<EMAIL_ADDRESS># Dan Schult<EMAIL_ADDRESS># Pieter Swart<EMAIL_ADDRESS># All rights reserved.
# BSD license.
#
# Authors:
# Aric Hagberg<EMAIL_ADDRESS># Pieter Swart<EMAIL_ADDRESS># Dan Schult<EMAIL_ADDRESS># Loïc Séguin-C<EMAIL_ADDRESS>"""
**********
Exceptions
**********
Base exceptions and errors for NetworkX.
"""
__all__ = [
'HasACycle',
'NodeNotFound',
'PowerIterationFailedConvergence',
'ExceededMaxIterations',
'AmbiguousSolution',
'NetworkXAlgorithmError',
'NetworkXException',
'NetworkXError',
'NetworkXNoCycle',
'NetworkXNoPath',
'NetworkXNotImplemented',
'NetworkXPointlessConcept',
'NetworkXUnbounded',
'NetworkXUnfeasible',
]
[docs]class NetworkXException(Exception):
"""Base class for exceptions in NetworkX."""
[docs]class NetworkXError(NetworkXException):
"""Exception for a serious error in NetworkX"""
[docs]class NetworkXPointlessConcept(NetworkXException):
"""Raised when a null graph is provided as input to an algorithm
that cannot use it.
The null graph is sometimes considered a pointless concept [1]_,
thus the name of the exception.
References
----------
.. [1] Harary, F. and Read, R. "Is the Null Graph a Pointless
Concept?" In Graphs and Combinatorics Conference, George
Washington University. New York: Springer-Verlag, 1973.
"""
[docs]class NetworkXAlgorithmError(NetworkXException):
"""Exception for unexpected termination of algorithms."""
[docs]class NetworkXUnfeasible(NetworkXAlgorithmError):
"""Exception raised by algorithms trying to solve a problem
instance that has no feasible solution."""
[docs]class NetworkXNoPath(NetworkXUnfeasible):
"""Exception for algorithms that should return a path when running
on graphs where such a path does not exist."""
[docs]class NetworkXNoCycle(NetworkXUnfeasible):
"""Exception for algorithms that should return a cycle when running
on graphs where such a cycle does not exist."""
[docs]class HasACycle(NetworkXException):
"""Raised if a graph has a cycle when an algorithm expects that it
will have no cycles.
"""
[docs]class NetworkXUnbounded(NetworkXAlgorithmError):
"""Exception raised by algorithms trying to solve a maximization
or a minimization problem instance that is unbounded."""
[docs]class NetworkXNotImplemented(NetworkXException):
"""Exception raised by algorithms not implemented for a type of graph."""
[docs]class NodeNotFound(NetworkXException):
"""Exception raised if requested node is not present in the graph"""
[docs]class AmbiguousSolution(NetworkXException):
"""Raised if more than one valid solution exists for an intermediary step
of an algorithm.
In the face of ambiguity, refuse the temptation to guess.
This may occur, for example, when trying to determine the
bipartite node sets in a disconnected bipartite graph when
computing bipartite matchings.
"""
[docs]class ExceededMaxIterations(NetworkXException):
"""Raised if a loop iterates too many times without breaking.
This may occur, for example, in an algorithm that computes
progressively better approximations to a value but exceeds an
iteration bound specified by the user.
"""
[docs]class PowerIterationFailedConvergence(ExceededMaxIterations):
"""Raised when the power iteration method fails to converge within a
specified iteration limit.
`num_iterations` is the number of iterations that have been
completed when this exception was raised.
"""
def __init__(self, num_iterations, *args, **kw):
msg = 'power iteration failed to converge within {} iterations'
exception_message = msg.format(num_iterations)
superinit = super(PowerIterationFailedConvergence, self).__init__
superinit(self, exception_message, *args, **kw)


--- title: "Contact" author: "" type: "" date: 2020-03-09T15:51:17-07:00 subtitle: "" image: "" tags: [] --- Please feel free to contact me about anything (software, D&D, MTG, cocktails). I usually reply within 24 hours.


- Free setup
- Custom sub-domain
- Standard customer support
- 1GB file storage
- 1 database
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- Free setup
- Custom sub-domain
- Standard customer support
- 1GB file storage
- 1 database
- Unlimited bandwidth
- Free setup
- Custom sub-domain
- Standard customer support
- 1GB file storage
- 1 database
- Unlimited bandwidth


Before Change
votes = [clf.predict(query)[0] for clf in ensemble]
counter = collections.Counter(votes)
predicted_label = counter.most_common()[0][0]
return predicted_label
After Change
predicted_label : The label of the query sample, predicted by the majority voting rule
// Check if a single sample was passed down to the function. In this case the sample must be converted to a 2D array.
if query.ndim == 1:
query = np.atleast_2d(query)
n_samples = query.shape[0]
votes = np.zeros((n_samples, len(classifier_ensemble)))
for clf_index, clf in enumerate(classifier_ensemble):
votes[:, clf_index] = clf.predict(query)


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| prefix | resourcemonitor |
| namespace | urn:eu:virtuwind:resourcemonitor |
| revision | 2016-10-17 |
| description | Resource Manager configuration |
| yang-version | 1 |
| imports | topo:network-topology 2013-10-21; |
| Name | Description |
|---|---|
| link-qos |
| Name | Description |
|---|---|
| linkChanged | A Link was changed |
| Name | Description |
|---|---|
| get-stats | |
| get-number-of-packets |


This 10-year-old girl’s Christmas list is blowing people’s mind online
Some of the requests were pretty standard at per with her age like dolls and bunnies but things went tad bit far when she included extravagant gifts like an iPhone 11 and a Macbook Air. And if that wasn't enough she cheekily also included whopping $4000 in her demands!
by Trends DeskChristmas may be more than a month away but this little girl’s long list of items for the festive day has left all quite shocked online.
Christmas wish-list put out by little children may be an innocent way to ask Santa for things they simply want as presents from parents, but this 10-year-old girl’s list with scores of expensive items has left people divided on Twitterverse.
Some of the requests were pretty standard for her age such as dolls and bunnies but things went a bit far when she included extravagant gifts like an iPhone 11 and a Macbook Air. And if that wasn’t enough she cheekily also included whopping $4,000 in her list of demands!
But what really baffled many online were items like “Gucci slides”, “Chanel purse” and a “Hydro Flask”!
While most were amazed with her knowledge of fashion and make-up, others wondered what she was going to do with all that cash. While most were left in splits saying that her list is “goals” and they would totally use her list for their own, others reminisced about their childhood when the most expensive thing would probably be a Lego set or a video game.
Here’s how people are reacting to the list:


Safety Explorer Charts with Queries
AE Table
AE Timelines
Results over Time
Histogram
Outlier Explorer
Shift Plot


How it works
-
1
Take a sample of anyone's voice
-
2
Make your own voice recording in high quality
-
3
Add effect and sound like other people
AnyVoice is an awesome app that allows you change your voice to anyone else’s in the world. App will be released sometime in 2050
Voice Recording
Change Voice
Have Fun
Take a sample of anyone's voice
Make your own voice recording in high quality
Add effect and sound like other people
AnyVoice uses an artificially intelligent system that learns a person’s voice by analyzing speech recordings and audio files / video files as well as identifying the relationships between them.
AnyVoice uses an artificially intelligent system that learns a person’s voice by analyzing speech recordings and audio files / video files as well as identifying the relationships between them.
Get notified about the app release


The 2020 Women in Data Science Symposium, jointly organized by the Michigan State University (MSU) and the University of Michigan (U-M) will take place on April 17 at MSU. We invite abstract submissions for lightning talks and poster presentations.
The symposium provides a platform for all practicing and aspiring data scientists, but especially women and gender minority participants, to discuss cutting-edge research, explore resources for research and career advancement, and network with other attendees. Everyone is welcome to contribute and attend.
We invite abstracts in all of the following areas:
- Theoretical foundations
- Methodology and tools
- Real-world applications in any research domain
- Ethics, fairness, and societal impact of data science
- Emerging research areas
Submission Deadline: Feb. 29, 2020
Notification: March 15, 2020
Submission Instructions:
- Submit your abstract through the online form.
- Include a title, list of authors/presenters and their affiliations.
- To recognize women and gender minority data scientists on your team, please indicate their roles in the project (securing research funding, project design, data collection, analysis and interpretation, writing, project management, project supervision).
- We strongly encourage the women and gender minority members of your team to be the presenters of the talks or posters.
- The main body of the abstract should be no more than 300 words and should include a brief summary of the research, methods, main results and impact.
- Please do not include figures, tables or bibliography in the abstract.
- Please indicate whether you prefer an oral presentation or poster. Oral presentations will be 10 minutes in length. The review committee will try its best to accommodate your preferences.


If you deployed your website on Heroku but you get an Application Error when you visit the website on the browser, then you probably did something wrong during the deployment.
No worries, you can see what you did wrong by looking at the server logs. You can do that by running the following in your terminal:
heroku logs
That will show a series of messages. Try to read them carefully to understand what has gone wrong. In case you have troubles understanding the logs, feel free to post them in the Q&A.


Recursive partitioning based on psychometric models,
employing the general MOB algorithm (from package partykit) to obtain
Bradley-Terry trees, Rasch trees, rating scale and partial credit trees, and
MPT trees.
| Version: |
0.15-1 |
| Depends: |
R (≥ 2.15.0), partykit (≥ 0.8-4), psychotools (≥ 0.4-0) |
| Imports: |
graphics, grDevices, grid, stats, Formula |
| Suggests: |
colorspace, strucchange |
| Published: |
2016-09-09 |
| Author: |
Achim Zeileis [aut, cre],
Carolin Strobl [aut],
Florian Wickelmaier [aut],
Basil Komboz [aut],
Julia Kopf [aut] |
| Maintainer: |
Achim Zeileis <Achim.Zeileis at R-project.org> |
| License: |
GPL-2 | GPL-3 |
| NeedsCompilation: |
no |
| Citation: |
psychotree citation info |
| Materials: |
NEWS |
| In views: |
Psychometrics |
| CRAN checks: |
psychotree results |


I am a developer with a history of working in the various services industries.
I am passionate about all aspects of software development, for instance, architecture, database
design, large-scale web applications, and service applications.
Some of my skills
Thank you for stopping by.
Feel free to reach out!


Silk Road, Revolutions and Systems
May 26, 2019
Today, I read the story of Silk Road: how the young idealist Ross Ulbricht, tired of chasing success the old school way, found his way around the darkweb to create an online As a part of the darkweb, it was operated as a Tor hidden service which protected the personal privacy of users by concealing their details from anyone - from the Government to their ISP - conducting network surveillance. Additionally, all payments were made using Bitcoin , a cryptocurrency which provides a certain degree of anonymity. bazaar for the trading of illicit materials, mainly drugs, which he named Silk Road.
The aim behind writing this blog post is to think out loud and try to gain insight into the oversights made by some of the most prominent revolutionaries in history.
When operating his online empire, Ross would take on the identity of Dread Pirate Roberts (~DPR) (borrowing the name from “The Princess Bride”, in which the pirate was a mythical character, inhabited by the wearer of the mask).
Ross (aka DPR) was having trouble switching back-and-forth between these different personalities, the many different facets of which were penned down beautifully in the original article :
To Alex, Ross was the cool new roommate; to Julia [his on-and-off girlfriend], a passionate lover and inspiration; to his family, the perpetual Eagle Scout; to Force [undercover DEA Agent posing as a Puerto Rican cartel middlemen], an unlikely friend in the night; to Tarbell [FBI Agent investigating his case], a smart kid defeated by his own arrogance. To the Southern District of New York US attorney’s office, Ross was simply the criminal conspirator Dread Pirate Roberts.
The likeliest reality is that Ross was all of those things. The open-minded seeker who conscientiously tried to pluck trash from a tree was Ross. As was the feverish visionary creating a virtual empire at any cost. Neither truth invalidated the other. Ross and DPR can (and did) coexist.
Ross didn’t exactly dream of building this huge empire of illicit business, but it was essentially all baby steps, As B.J. Neblett said “We are the sum total of our experiences. Those experiences – be they positive or negative – make us the person we are, at any given point in our lives. And, like a flowing river, those same experiences, and those yet to come, continue to influence and reshape the person we are, and the person we become. None of us are the same as we were yesterday, nor will be tomorrow.” stemming from the influence Ludwig von Mises - an Austrian economist described in the story as “a totem of the modern American libertarian orthodoxy” - had on Ross. According to von Mises, a citizen must have economic freedom to be politically and morally free.
If you haven’t read the story yet, please do and then come back! It might easily be one of the most riveting cyber-criminology reports you ever read.
Joseph Stalin, Adolf Hitler and Ludwig von Mises, they all had an ideology - a vision of the ideal world, and a way of bringing peace to world. For them, it embodied an expression which society must adhere to lead them towards utter completeness and happiness.
The ideology of Hitler was an ideology of conquest: the “manifest destiny” of a superior race to conquer, occupy, and control lands of the “lesser” people - the Untermenschen - for the sole benefit of the superior race.
The ideal society for Stalin was one in which people contribute to it because they feel it is their pleasure and responsibility to do so, and in which people only consume what they need while being mindful of the needs of others.
And they executed their ideas, bringing about their ‘revolution’!
Both regimes - the Third Reich and Stalinism - were responsible for millions of deaths and untold amounts of suffering.
Although one can argue that Ross Ulbricht’s ‘revolution’ was nowhere near that scale, but that is immaterial to our discussion. It followed the same pattern which was summed up by Bearman rather well in the original story:
It’s an age-old story, the bloom and wilt of revolution. After tearing down the establishment’s walls, the new regime soon realizes the rubble would make a fine set of gallows. Just as Tarbell thought, all systems are the same. At the beginning of Silk Road, what Ross created was just a system. Then, at a certain point, it became his system—at which moment the system was doomed.
Isn’t it strange - How we become the very thing we fight against!
Gazing into Abyss
“Beware that, when fighting monsters, you yourself do not become a monster… for when you gaze long into the abyss. The abyss gazes also into you.”
― Friedrich W. Nietzsche
For people who prefer examples in fiction over history, what happened with the finale of Game of Thrones is a prime example of this pattern. [Spoilers Ahead] In light of everything Daenerys [one of show’s main protagonists] accomplished — birthing dragons out of stone, freeing thousands of slaves, helping the Starks defeat an army of ice-zombies — the viewers first handedly experienced the mindset of a revolutionary who believed that it was incumbent upon her to liberate the entire world. Yet it was when she failed to draw a line between herself and her vision The time when she succumbed to her temptations, burning alive and hence killing thousands of people in King’s Landing that she failed as a ruler, becoming exactly what she had hoped to abolish: tyranny. It is worth noting here that all the while she unapologetically burnt the innocent, she was fueled by the exact same idea - to liberate the innocents of the world from tyranny.
In Ross’s case, the fact that he was feeling uneasy even as DPR (who was a rather confident and eloquent character); that he had already begun failing at what he had intended to do was the first clue that the shadows of doom had already fallen upon him. But he deceived himself in the name of his idea - in the belief that he was doing the right thing.
Is it really this belief and total devotion to our idea that blinds us, or is it the power and the riches which corrupts us? Or maybe it is a fundamental misunderstanding of our very own conceived idea? Perhaps it might be a skewed combination of all of the above.
I do not claim to know the answers to any of the above questions.
But let’s look at another revolutionary: Mahatma Gandhi and the revolution he brought about in India.
Mahatma Gandhi was
called Bapu (Father) by many, including Jawaharlal Nehru
In response to the Rowlatt Act imposed by the British and the Jallianwala Bagh Massacre, Gandhi lead the non-cooperation movement, appealing to the masses to adopt swadeshi goods and local handicrafts to boycott British goods. The movement was based on the principle of Ahimsa (Non-Violence), and after two years of hard work, it gained full momentum in 1922. It seemed that the dream of Swaraj (self-governance) was finally turning to reality.
But giving a face to Gandhi’s fears, cases of violence were reported from all over the nation, and after the Chauri-Chaura A large group of protesters participating in the Non-cooperation movement clashed with the police, who opened fire. In retaliation, the demonstrators attacked and set fire to a police station, killing all of its occupants. incident, he decided to call off the protest indefinitely. This was indeed a very difficult and brave decision on his part - he could have gotten what he wanted and ignored the ‘milder’ cases of violence for the nation, but his moral caliber was defiant of such behavior and he chose to voice it.
It was perhaps because he believed in a perpetual fight - a fight we all have to fight against our own moral demons - in which the nation must not succumb to the demon of violence.
Subsequently, Gandhi launched many campaigns perfecting the concept of Satyagrah सत्याग्रह (Satyagrah): सत्य (Truth) + आग्रह (insistence) - सत्य के लिए आग्रह - The truth force, is a particular form of non-violent civil resistance , finally leading the nation to independence in 1947.
I guess we all get to play Ross sometimes, and I believe that creating barriers, as Gandhi did, to encourage the higher moral stance of one’s own values - be it by ruthless questioning of one’s own beliefs and biases, or having an external support mechanism for keeping oneself on track - would help us dodge the doom of our system.
But I do find it very interesting to ponder upon how ‘easy’ it is to be lost, to be engrossed so deeply into our visions to forget what it stood for in the first place; to cross the rather fine line drawn between us and the monster, and how tools like identities and the different masks we wear make it all the more easier.
Special thanks to Abhipsha for proofreading and making this article readable!


A fun app that pulls travel information based on a Place Pin from Pinterest. Uses Pinterest REST API and OAuth2 to grab Rich Pins with Javascript.


--- title: Merge Stats Canada keywords: fastai sidebar: home_sidebar summary: "Merge scraped stats Canada data based on region." description: "Merge scraped stats Canada data based on region." nb_path: "core.ipynb" ---
Reading in the config parameters as variables. \ When building the package with
nbdev_build
anything cells with the#export
tag will be exported to the default script which iscore.py
.
Otherwise a module name can be specified.Note:the module being exported to must already exist. However it can be just a template.
First use the logging
module to set create a logger.
The _map_target_polygons
and get_target_df
functions are the main methods to create the final poly-mapped target dataframes.
Example of documentation:
The show_doc
function will give a sample of how the documentation will look with the current doc strings.
Example of exploratory testing \
\
We are able to experinment with and visually validate the modules, similarly to EDA code where the ML dev is constantly iterating. This will not be exported to a .py
file during the build.
You can export the notebook to a package with the following function
from nbdev.export import notebook2script
notebook2script()


mixtools: Tools for Analyzing Finite Mixture Models
Analyzes finite mixture models for various parametric and semiparametric settings. This includes mixtures of parametric distributions (normal, multivariate normal, multinomial, gamma), various Reliability Mixture Models (RMMs), mixtures-of-regressions settings (linear regression, logistic regression, Poisson regression, linear regression with changepoints, predictor-dependent mixing proportions, random effects regressions, hierarchical mixtures-of-experts), and tools for selecting the number of components (bootstrapping the likelihood ratio test statistic and model selection criteria). Bayesian estimation of mixtures-of-linear-regressions models is available as well as a novel data depth method for obtaining credible bands. This package is based upon work supported by the National Science Foundation under Grant No. SES-0518772.
| Version: |
1.1.0 |
| Depends: |
R (≥ 3.2.0) |
| Imports: |
MASS, segmented, stats, survival |
| Published: |
2017-03-10 |
| Author: |
Derek Young [aut, cre],
Tatiana Benaglia [aut],
Didier Chauveau [aut],
David Hunter [aut],
Ryan Elmore [ctb],
Thomas Hettmansperger [ctb],
Hoben Thomas [ctb],
Fengjuan Xuan [ctb] |
| Maintainer: |
Derek Young <derek.young at uky.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| Citation: |
mixtools citation info |
| Materials: |
NEWS |
| In views: |
Cluster, Distributions |
| CRAN checks: |
mixtools results |
Downloads:
Reverse dependencies:
| Reverse depends: |
iNOTE, pheno2geno |
| Reverse imports: |
adeba, AFM, ddpcr, enviGCMS, ggrasp, kernplus, l1kdeconv, nmfem, Seurat, Surrogate |
| Reverse suggests: |
icamix, mable, rebmix |
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Sumpter Wharf inspected
by Hamish MacLeanThe 1884 Sumpter Wharf in Oamaru Harbour, home to the world’s largest colony of Otago shags, has been inspected by Bluff-based Bay Underwater Services NZ, the Waitaki District Council has confirmed.
Council assets group manager Neil Jorgensen said on Friday the construction crew stabilising piles under Holmes Wharf had also inspected Sumpter Wharf .
"Nothing at this stage to report," he said in an email. "We are currently focusing on Holmes."
Sumpter Wharf was closed to traffic in 2004. In 2014, Otago’s only endemic seabird, the Otago shag, began nesting on the 200m-long wharf.
It has since become home to the largest colony of the species, an estimated 650 nests — a 58% increase from last year and an estimated 40% to 50% of the entire species.
In July last year, the council approved a $35,000 budget for a dedicated viewing area.


[gecode-users] interval domains at run time
Chd Orti
richard.portell at gmail.com
Thu Sep 11 15:40:23 CEST 2014
Dear all,
I have the following problem:
Array of 100 numbers with sum = 500;
At run time, the user can decide in how many intervals he cuts the 100
numbers. Lets say 4 for the example.
For all the parts, he can give a domain for example :
>From 0 to 24 -> the integers can only take values 0 or 1
>From 25 to 49 -> the integers can only take values 5, 6 or 1,
etc ...
I can't find a good way to restrict the domain by intervals, I guess I am
missing something here ...
Thanks for your help,
Best regards,
Richard
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DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
Michael Gove accepts all the recommendations of Lord Bew’s independent review of testing, assessment and accountability at the end of primary school.
Education Secretary Michael Gove today accepted all the recommendations of Lord Bew’s independent review of testing, assessment and accountability at the end of primary school.
Key changes to the Key Stage 2 system will make it fairer for all and more effective in raising standards.
Michael Gove said the substantial reforms would ensure that heads, teachers, pupils and parents would be able to have confidence in the new system.
Currently there is statutory teacher assessment in every core subject - maths, reading, writing, speaking and listening, and science. There are also external tests in maths, writing and reading, and a sample test in science.
The changes include:
Maths and reading tests will continue to be externally tested but will be refined over time. Teacher assessment of science, with a sample test monitoring national standards, will continue. Speaking and listening will continue to be teacher assessed.
Education Secretary Michael Gove thanked the panel for their report. He said:
These changes represent an educationally sound approach and substantial reform. The system in future will be fairer for teachers and pupils. It will give parents the vital information they need and will hold schools accountable.
I have always been clear that external accountability is essential if we are to drive up standards, and Lord Bew’s report recognises this. Publishing a greater range of data will be fairer for schools - schools should not be judged on one measure alone.
There has been criticism that the current writing test encourages drilling. It is clear that elements of writing where there are right and wrong answers - spelling, punctuation and grammar - lend themselves to external testing. But writing composition is better suited to teacher assessment. We will trust teachers to judge their pupils’ abilities.
The changes will be introduced as quickly as possible, most from 2012. In 2012 interim arrangements for writing assessment will be required. Those arrangements should be in line with the principles in Lord Bew’s report and ensure that results are as reliable and robust as possible. We believe some external testing will be required alongside teacher assessment. We will discuss the detailed arrangements for 2012 with the profession and confirm them to schools at the start of the new school year.
This will allow for the new spelling, punctuation, grammar and vocabulary test to be designed and properly piloted, and ensure the moderation of teacher assessment is robust, ready for full implementation from 2013.
The review was chaired by the cross-bench peer Lord Bew and consisted of headteachers and education experts. Michael Gove set up the review last year. He said external accountability at Key Stage 2 was vital because it was shown to drive up standards but agreed the current system was flawed and could be improved.
Lord Bew said today:
I am pleased that all our recommendations have been accepted. This is a complex area and many conflicting views were presented to us. But this package will lead to a better system, one that will do the jobs everyone wants it to do and which will have the confidence of all parties involved.
You can download Lord Bew’s final report from the Bew Review website.
Read the Government’s response to the review.
The panel received nearly 4000 online responses and about 100 written submissions, and took evidence directly from around 50 stakeholders, during a 12-week call for evidence.
Lord Bew is a cross-bench peer, Professor of Irish Politics at Queen’s University in Belfast, and a Member of Royal Irish Academy (MRIA). He was a historical adviser to the Saville Inquiry from 1998 to 2001.
Membership of the panel in full is:
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Website: www.education.gov.uk/help/contactus
Published: 18 July 2011


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