Most apartments on TV or in movies are more or less the same size; it's often hard to tell the difference between a messy apartment and a rundown one. Showing that the shower or bath doesn't work or the water is cold is an easy way to make the setting more rundown and give it a more "rustic" feel. A way to avoid Informed Poverty.
Subtrope of Shower Scene. Might employ the Flushing Toilet, Screaming Shower, in more modern works. Might also be used to set up a Do-It-Yourself Plumbing Project plotline in a comedic work.
Examples
open/close all folders
Advertising
- A State Farm commercial shows a married couple having just bought a new house, that requires a lot of work to be done with it to make it livable.
Anime and Manga
- In Amagi Brilliant Park, Bathing Beauty Isuzu Sento's apartment doesn't have a bathroom so she had put a clawfoot bathtub in her kitchen that is filled by a hose connected to the sink so she can easily keep up with her 3 baths a day that keep her alive.
- In the Excel Saga manga, they don't take hot baths in their apartment's tub because it costs too much money.
- Near the end of Neon Genesis Evangelion, Asuka, who suffered a mental breakdown after being Mind Raped by an Angel and ceased being able to pilot her Eva, is found by Nerv personnel in a destroyed house sitting in a tub filled with nasty brown water. (Please let that have been rust...) Things just keep getting worse for her from there.
- Priscilla Asagiri from Bubblegum Crisis has an Awkwardly Placed Bathtub clumped into the semi-truck trailer that she lives in.
Comic Books
- In an Archie Comics story set in ancient Egypt we see Queen Veronica taking a luxurious bath with slaves assisting her; we then cut to plebian Betty washing herself in a water puddle having to shoo out miscellaneous fauna.
- A closeup shows Fray having a shower, then a wider shot shows she's standing halfway up a building under a broken water pipe with her feet planted on either side of an air shift.
Fan Works
- A Discworld fic by A.A. Pessimal sees a dirty, muddy and disgruntled Angua von Überwald steeling herself to face a shower at the City Watch base on Pseudopolis Yard. Being a werewolf, she is not comfortable with the idea of any sort of B.A.T.H., which her colleague Sally von Humperdinck takes advantage of. And the shower itself is rudimentary: gravity-fed by water draining down from a tank on the upper floor. Angua's discomfort is intensified by the presence of a male bathroom attendant. Admittedly a male Troll, but still...
Film
- The film of the book Holes shows a cold open shower with the water shutting off halfway through. The context being that Stanley is at a juvenile detention camp in a desert, so the water only flows for 4 minutes. (In the midquel survival guide, it gets reduced to 3 minutes after a backfiring suggestion intended to make the showers last longer.)
- In Kung Fu Hustle, the slum that most of the movie takes place in has a communal fountain that some residents have to use to clean themselves... when the water's even turned on, as the landlady is prone to turning it off on a whim.
- Cry Baby - when the title character's scroungy but good-hearted rockabilly family's home is visited, paterfamilias Iggy Pop is seen bathing in a little metal tub in the yard.
- Withnail & I has an extended establishing scene of the two Starving Out-of-work Actor main characters talking casually, while one is bathing and attempting to shave in a tiny, stained and cracked bathtub in the middle of the floor.
- K-20: Legend of the Mask: When Duchess Yoko is bathing in Genji and Kikuko's home, she keeps asking if they have a shower and shampoo, the sort of thing that the poor circus performers are not be able to afford. They don't even know what shampoo is.
- A downplayed example pops up in Quadrophenia, when we see the protagonist going to a public bath-house to rent a tub instead of bathing at home. This was common for working-class families in Britain until well into the 1970s.
- Moonlight: Early on, Chiron is shown heating water over the stove and using dish detergent for his bath because his mother can't afford hot running water or bath soap.
Literature
- In The Hunger Games at the Capitol there is a panel with more than a hundred options in the shower in comparison to what Katniss is used to: a bucket of water warmed up on the stove.
- In Matilda, Miss Honey divulges that she doesn't have the space or money for a shower or bath in her tiny house, and must wash in the kitchen with a pot of water and a sponge.
- Harry Dresden of the Dresden Files isn't that poor — most of the time anyways — but he can't have a water heater because of his problem with electricity, so he has to make do with cold showers. He's grown used to this, but he occasionally really misses them. When she's living in his head, one of the things Lash does is manipulate his senses so he feels hot water.
- In the Phryne Fisher novels, Phryne loves luxuriating in long hot baths. This is because in her poverty-stricken childhood, she often had to take what she refers to as 'cat baths': standing a basin and wiping herself down with damp flannel.
Live-Action TV
- Inverted in Robin Hood when Much is temporarily made an Earl he gets to have a bath smelling of flowers.
- Happy Endings. The apartment is big but the shower alternates between hot, cold, and brown water.
Max: Dave, it's a shower bud, it's not that hard.  It's like he never showered before.
- Everybody Loves Raymond
- The episode where the Barone family go to spend time with relatives in Italy: Raymond's growing frustration with Italian plumbing and the unpredictable trickle of water coming out of the showerhead is a running joke.
- In "Shower Wars", Frank Barone botches the job of repairing Ray and Debra's shower and makes the problem ten times worse. That it ends up with Ray drenching Debra's top with directed shower water is probably incidental Fanservice.
- Seinfeld In the episode "The Shower Head", low flow shower heads are installed to save money on water, driving Jerry and Kramer crazy.
- How I Met Your Mother: To highlight Lily's utterly abysmal apartment, the most notable part of the apartment was that the stove, oven, sink, and refrigerator (or "stovenkerator") were all one piece of furniture... and located next to the toilet and bathtub.
- On My Name Is Earl, when Earl and Randy move into the trailer, they live in the kitchen. They are told that they have a "half bath" in the form of the sink. Not only that, but Frank uses the rinse hose on the sink to shower after working out by running in place, because the shower is broken and he doesn't even have the money to buy a real treadmill, let alone get the shower fixed.
Theatre
- The song "No More" from tick, tick... BOOM! has Jon and Michael listing things Michael doesn't have to put up with now that he's no longer poor and has moved into a nicer apartment:
No more taking a shower in the kitchenWhile your roommate's eating breakfastAnd you're getting water on his cornflakes!
Video Games
- In The Sims 3, the cheapest shower will sometimes lose heat partway through use, resulting in a "cold shower" negative moodlet.
Webcomics
- In Freefall Florence's first shower scene is outdoors in a scrap metal stall, with Helix pouring a bucket of water over her. She resolves to fix the ship's plumbing next.
Helix: The correct order is "lather, rinse, remove leeches, repeat".
Western Animation
- In Scooby-Doo! Mystery Incorporated, The Fleach family, who runs a failing, local amusement park are forced to bathe in the recycled water they use to cook hot dogs in order to save money. This causes the daughter, Marcie, to be given the nickname by her classmates, "Hot Dog Water", due to her distinct odor.
- Samurai Jack is shown to bathe in waterfalls whenever possible, since he's effectively broke and homeless. Doesn't make it any less enjoyable for him or us.
Real Life
- People without time or access to a full shower will sometimes wet a towel and wipe down their most pertinent areas, such as "pits, tits and naughty bits." This is sometimes called a "whore's bath" on the assumption that prostitutes will only take a few moments to freshen up before seeking their next customer.
- Truth in Television: during World War II, British civilians were restricted to one bath per week in no more than five inches of water. This appalled American servicemen. Soldiers in North Africa had it worse: they were issued with three pints of water per day for all purposes. In order to conserve as much as possible for drinking, new recruits were taught that it was possible to have an all-over wash using a face flannel and a single mess-tin full of water - which was then collected and pooled and used to wash socks and underwear. This is still taught to recruit soldiers today - at least in some training barracks - as part of the softening-up procedure.
- Right up until the 1950's and 1960's in Great Britain, many homes in industrial areas did not have bathrooms as they are known today. "Public Baths" were not just a place to swim. For a few pennies they'd provide a bath or a shower with guaranteed clean towels at an extra price. Working-class Brits in dirty jobs would visit once or twice a week for a thorough scrub. Bathers were segregated by sex, but the bath-tubs would have none or minimal screening from each other. Whole families tended to go together on the same night, seeing it as a family night out. Public baths, as such, declined in numbers and importance as living standards improved and bathrooms were built, as standard, into family homes. Some employers in really dirty jobs, such as iron foundries and coal mines, provided free bathing (communal) as a perk of the job.
- In housing where a water heater is absent or unreliable, the best thing to do is warm a pot of water on the stove (assuming that's an option), wash with soap and minimal amounts of cold water from the faucet, then rinse with the water from the pot—from your head downwards, so you don't waste the warm water.
- New York City still has a few surviving "tenement apartments" featuring a bathtub in the kitchen.


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I am currently learning to code with
Code First: Girls. Going over everything
from how the internet works, to creating
websites and version control with git. A
lot to cover in only 8 weeks! Everyone
should learn to code, here are some
pretty good reasons why...
| A computer | A text editor | A web browser | Some HTML, CSS and JS files |


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new_rscript.Rd
This function will create an object of class sluRm_rscript
that can be used
to write the R component in a batch job.
new_rscript(pkgs = list_loaded_pkgs())
| pkgs | A named list with packages to be included. Each element of the list must be a path to the R library, while the names of the list are the names of the R packages to be loaded. |
|---|
An environment of class sluRm_rscript
. This has the following accesible
components:
add_rds
Add rds files to be loaded in each job.", x
is a named list
with the objects that should be loaded in the jobs. If index = TRUE
the
function assumes that the user will be accessing a particular subset of x
during the job, which is accessed according to INDICES[[ARRAY_ID]]
. The
option compress
is passed to saveRDS.
One important side effect is that when this function is called, the object
will be saved in the current job directory, this is opts_sluRm$get_chdir()
.
append
Adds a line to the R script. Its only argument, x
is a character
vector that will be added to the R script.
rscript
A character vector. This is the actual R script that will be written
at the end.
finalize
Adds the final line of the R script. This function receives a
character scalar x
which is used as the name of the object to be saved.
If missing, the function will save a NULL object. The compress
argument
is passed to saveRDS.
set_seed
Adds a vector of seeds to be used across the jobs. This vector
of seeds should be of length njobs
. The other two parameters of the
function are passed to set.seed.
write
Finalizes the process by writing the R script in the corresponding
folder to be used with Slurm.


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"Code"vid Solutions provides Simple Secure and Free solutions to modern day finance problems. 100% free with no brokerage charges and absolutely safe.
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Check out The Trading Guide for tricks and tips on the stock market and trading. We have compiled resources for YOU ranging from important pointers to courses on the stock market.
The Trading GuideCode"vid" has got the best customer service and the team is very patient, cordial and prompt in their responses. I’ve so far loved the journey with them and hope to do so for many years to come. Good work Code"vid" team!
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The Value of TDD
Debugging the Terror of Errors
7/3/15
It’s no secret that errors can be terrible. No matter how expert you are, no one is exempt from the sinking feeling of encountering an error in your code – especially unexpected errors that are not immediately identifiable. In many ways, by the time you come face-to-face with an error message it is already too late. A mistake has already been made. And the only way to proceed is to backtrack and hope you can recount all of the places the mistake has potentially affected your code. For this reason, writing tests with the intention of staying ahead of potential errors is often a more logical approach. Many consider test-driven development to be a worthwhile safety net that deserves serious consideration from any programmer.
Test-driven development has so many benefits. It can first be used as a good tool for identifying the basics of what you want your program to do. By forcing yourself to articulate these expectations in an explicit way, much like user stories, writing out tests can be a great way to stay true to your original intentions, and guide your start to building.
Tests can also inspire you to identify edge cases without having to learn from them the hard way. This forward thinking and anticipation can aid in thoroughly understanding the problem you’re trying to solve, as well as the behavior of the code you’re using to solve the problem.
And finally, having a testing structure in place makes maintainability and future amendments to your code a much safer endeavor. Whether it be that your code gets passed to someone else, or your user’s needs evolve, code is almost always going to need to be able to adapt and change. Doing what you can now to keep your code from breaking later is often a much more efficient way to approach and skillfully set up your code. So write tests now! They will most certainly benefit you later.


#define ERROR
The error codes used in SNAC (*, 1).
| ERROR_HEADER | 1 |
Invalid SNAC header. | |
| ERROR_RATE_SERVER | 2 |
Server rate limit exceeded. | |
| ERROR_RATE_CLIENT | 3 |
Client rate limit exceeded. | |
| ERROR_OFFLINE | 4 |
Recipient is offline. | |
| ERROR_SERVICE_NA | 5 |
Requested service is not available. | |
| ERROR_SERVICE_UNDEF | 6 |
Requested service is undefined. | |
| ERROR_OBSOLETE | 7 |
The sent SNAC is obsolete. | |
| ERROR_UNSUP_SERVER | 8 |
Not suppoerted by server. | |
| ERROR_UNSUP_CLIENT | 9 |
Not suppoerted by client. | |
| ERROR_REFUSED_CLIENT | 10 (0x0a) |
Refused by client. | |
| ERROR_REPLY_BIG | 11 (0x0b) |
The reply was too big. | |
| ERROR_RESPONSE_LOST | 12 (0x0c) |
Responses lost. | |
| ERROR_REQ_DENIED | 13 (0x0d) |
The request was denied. | |
| ERROR_SNAC | 14 (0x0e) |
Invalid SNAC. | |
| ERROR_RIGHTS | 15 (0x0f) |
Insufficient rights. | |
| ERROR_BLOCKED | 16 (0x10) |
Recipient blocked (in local permit/deny). | |
| ERROR_EVIL_SENDER | 17 (0x11) |
The sender is too evil. | |
| ERROR_EVIL_RECIP | 18 (0x12) |
The recipient is too evil. | |
| ERROR_RECIP_UNAVAIL | 19 (0x13) |
User temporarily unavailable | |
| ERROR_NO_MATCH | 20 (0x14) |
No match found. | |
| ERROR_LIST_OVER | 21 (0x15) |
List overflow. | |
| ERROR_REQ_AMBIG | 22 (0x16) |
Ambiguous request. | |
| ERROR_QUEUE_FULL | 23 (0x17) |
Server queue full. | |
| ERROR_IS_AOL | 24 (0x18) |
Not on AOL. |


--- layout: default title: Sponsors --- {% include nav.html active='Sponsors' %}
Neovim operates a campaign to fund ongoing development. This makes it possible for core developers to work full-time for a month or longer, accelerating projects like Lua stdlib, treesitter parser engine, LSP framework, extended marks, embedded terminal, job control, RPC API, and remote UIs. Sponsorship is also used to maintain (very minimal) infrastructure costs for the Neovim project, such as hosting fees.
Donations are managed via open collective, which provides public tracking for all expenses. Bitcoin transactions are visible on the blockchain explorer. The only donation options for neovim are via GitHub sponsors, open collective, and Bitcoin. All prior funding sources have been transferred into open collective.


Historically, Australian Bushfires have been immensely difficult to control and destroyed various communities and towns. More than 10 million hectares of land was destroyed, burning through vegetation, wildlife, homes and killing many residents. Aqua and Terra Satellites by Nasa present variables correlated with bushfires, particularly the Fire Radiation Point and Brightness. Further studies of climate conditions of different regions prove to be stimulants of this natural disaster.
This presents the distribution of fires across Australia with their respective Brightness Temperature and Fire Radiation Power in each area. Predominantly, the bushfires are distributed along the coastline of Victoria and New South Wales. However, clusters do appear in the Northern and Southern regions of Australia.
Some of the regions most affected by Australian bushfires include; Bairnsdale East, Bendigo, Esperance, Kalgoorie, Kangaroo Island and Mildura. Different climate conditions can prove to be more or less vulnerable to bushfires
An Australian Weather Dataset focusing on the respective areas is used for intricate analysis to determine whether a correlation exists between climate variables and prevalence of bushfires. High temperatures and windspeed are integral factors in stimulating and spreading bushfires. The visualisations below delve deeper into the patterns of temperature and wind speed, annually.
Further analysis of the climate aids in drawing insights of potential causes of fire in such areas. The figure below focuses on two distinct climate variables in tandem; Humidity and Maximum Temperature in notable bushfire locations.
Bushfire and Weather Data is captured through the NASA satellites. Referring to a NASA published article, both Aqua and Terra satellites utilise Moderate Resolution Imaging Spectroradiometer (MODIS) to derive mathematical calculations relating to bushfires in Australia. The level of detection of brightness is prominent in higher magnitudes by the Aqua satellite relative to the Terra satellite.The level of confidence is indicative of the reliability of the values provided by NASA and hence, has been placed in parralel with the heatmap.
The measurements observed by Aqua and Terra Satellite is combined with a confidence level which indicates the precision and certainty of the numerical values of the Fire Radiation Power and Brightness included within the dataset. The scatterplot determined the relationship between Brightness and FRP of the fires across Australia.
Bushfires have been everpresent in Australia and the effects are brutal. There are physical and direct impacts, ecological impacts and economic costs associated with this natural disasters. The distribution of fires across Australia due to its climate will continue to make several towns vulnerable. To learn more about the impacts of bushfires or to make a contribution, head to Impacts of Australian Bushfires.


Giving Document Upload
Use this upload form to quickly update the outreach sheet with new gives.
Don't delete any columns in the files. Script relies on column positioning
The proccess can take several minutes if there are many entries in the spreadsheet. Just let it sit a while.
Currently it looks for:
"Odyssey Unclassified TBD"
"College Fund"
"Dean's Fund for Student Life"
"Jeff Metcalf Internships"
"SCGM |"
Browse…
Submit
{% if worked %}
Succeeded
First Name
Last Name
Email
{% for donor in worked %}
{{ donor['fname'] }}
{{ donor['lname'] }}
{{ donor['email'] }}
{% endfor %}
{% endif %} {% if failed %}
Failed
First Name
Last Name
Email
{% for donor in failed %}
{{ donor['fname'] }}
{{ donor['lname'] }}
{{ donor['email'] }}
{% endfor %}
{% endif %}


Functions for reading and decompressing the DBC (compressed DBF) files. Please note that this is the file format used by the Brazilian Ministry of Health (DATASUS) to publish healthcare datasets. It is not related to the FoxPro or CANdb DBC file formats.
| Version: | 1.0.5 |
| Depends: | R (≥ 3.3.0) |
| Imports: | foreign |
| Published: | 2016-09-16 |
| Author: | Daniela Petruzalek [aut, cre] |
| Maintainer: | Daniela Petruzalek <daniela.petruzalek at gmail.com> |
| BugReports: | https://github.com/danicat/read.dbc/issues |
| License: | AGPL-3 |
| Copyright: | 2016 Daniela Petruzalek |
| URL: | https://github.com/danicat/read.dbc |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | read.dbc results |
| Reference manual: | read.dbc.pdf |
| Package source: | read.dbc_1.0.5.tar.gz |
| Windows binaries: | r-devel: read.dbc_1.0.5.zip, r-release: read.dbc_1.0.5.zip, r-oldrel: read.dbc_1.0.5.zip |
| OS X binaries: | r-release: read.dbc_1.0.5.tgz, r-oldrel: read.dbc_1.0.5.tgz |
| Old sources: | read.dbc archive |
Please use the canonical form https://CRAN.R-project.org/package=read.dbc to link to this page.


FROM RUSSIA WITH LOVE A Film Review Copyright Dragan Antulov 2000
In the last decade of its existence Soviet Union was desperately trying to counter overwhelming Western efforts on the propaganda front of Cold War. That effort, among other things, consisted in the multitude of explicitly anti-Soviet spy and action thrillers like RED DAWN or RAMBO 2, so Soviets had to produce novels, movies and television shows that would give their side of the story. One of such examples was 1984 mini-series TASS IS AUTHORISED TO DECLARE..., aired on former Yugoslav television in mid 1980s. The series was boring as hell, but those viewers patient enough to sit through it in its entirety were rewarded with occasional hilarious moment or too. One of them was the scene featuring KGB agent leisurely discussing James Bond movies with his CIA counterpart and mentioning FROM RUSSIA WITH LOVE. The author of this review is unaware whether Soviet citizens in 1984 were able to watch that particular film, but the citizens of former Yugoslavia were not. That 1963 Bond film, second in the row, was unofficially banned by former Yugoslav authorities not because of anti-Soviet content, but because the part of the plot takes place in former Yugoslavia, and the original novel by Ian Fleming had painted quite unflattering picture of Zagreb, then one of major cities of former federation. Ironically, it was video distributor from Zagreb that introduced the film to the audience only few years later. It's quite a shame, because for many critics view FROM RUSSIA WITH LOVE as the best Bond film.
The plot of the film begins when the anonymous head of SPECTRE organisation authorises very complex plan that would utilise Cold War rivalry between Britain and USSR. At first, British secret agent James Bond (played by Sean Connery) is sent to Istanbul in order to meet Tatiana Romanova (played by Daniela Bianchi), young and beautiful deciphering clerk in Soviet Consulate. Romanova is offering her services in obtaining precious decoding device Lektor from the Consulate in exchange for meeting with handsome British agent she had allegedly fallen in love by watching his photos in KGB files. Bond suspects a trap, and he is right, since Romanova's actions have been actually directed by KGB spymaster Rosa Klebb (played by Lotte Lenya). But Romanova is deceived too, since her boss has just defected to SPECTRE and the ultimate goal of the operation is to bring Lektor to SPECTRE and kill Bond in the process.
One of the reasons why FROM RUSSIA WITH LOVE happens to be one of the most popular Bond films is the fact that it remains the closest to the original vision of the character creator Ian Fleming (who also got cameo role in the film). In this film Bond doesn't have to save the world from evil megalomaniacs and their underground armies. The story revolves around rather minor Cold War skirmish, hardly relevant in the general scheme of things, an episode that could be inspired by Ian Fleming's real life adventures during his career in British intelligence. The lack of spectacle usually associated with Bond films is compensated with the complex and intriguing, yet understandable plot. Although the intrigue involves double deception, the scriptwriters Johanna Harwood and Richard Maibum didn't left audience in the dark - from the opening scenes viewers are told about all major details of the conspiracy. That provides additional suspense, because audience knows that Bond is about to face the danger. Even if we are aware of the unwritten rules that mandate Bond winning at the end of the day, the film still remains interesting. Realism of the film is underlined with scriptwriters' efforts to provide some continuity to the series (unlike the rest of Bond movies that usually start from scratch). Events of the previous movie (DR. NO) are referenced, and Sylvia (played by Eunice Grayson) is the only Bond girl who was romantically involved with Bond in two separate Bond films.
Despite the higher dosage of realism, FROM RUSSIA WITH LOVE still follows the escapist formula of Bond movies. Bond still gets it on with beautiful women and locations of Istanbul are quite exotic (although Wales locations are poor substitute for the coast of Istria, and Venice scenes are even poorer example of blue screen techniques) and Bond still flirts with Moneypenny. The action is not that spectacular, except in the last scenes of the film (where Bond uses some rather crude tools to deal with villains, instead of his favourite gadgets), but the fight scene in train is one of the best in the history of Bond films. Finally, legendary Bond gadgets are introduced, as well as their inventor, Major Boothroyd a.k.a. Q (played by recently deceased Desmond Llewelyn). Another Bond movie ingredient - cool opening titles - seem somewhat inferior compared with the similar scenes in latter Bond films.
The acting is superb, as usual. Connery again proves that he was born to play James Bond and that nobody could do it any better. He is especially good in this film, where the script his usual cockiness confronts with the realities of world where even the heroes might lose a fight or two and let the villains, at least for a while, to have the upper hand. Connery's role is very good, but his partners also did a very good job. Pedro Armendariz as his Istanbul sidekick Karim Bey is especially interesting to watch, since he plays the character who actually shares Bond's hedonism - we might see Karim Bey as some kind of local James Bond. That role is even more powerful when we consider that Armendariz shot this film while being terminally ill. Daniela Bianchi, Italian model and Miss Universe 1960, does more than decent, actually very good job as Bond girl, at least for someone who got the role on the basis of a good look. Robert Shaw as villain is also impressive - Bond films rarely featured truly psychopathic, yet efficient and realistic baddies like this one. Another impressive villain is Lotte Lenya as Klebb; she even manages to bring some interesting subtexts to her role - I wonder why the makers of CELLULOID CLOSET missed the scenes that feature Klebb and Romanova together.
Of course, those who like to nit-pick would find some flaws. My major complaint is somewhat too romantic and rather unrealistic portrayal of Gypsies and terribly fake "catfight" in Gypsy camp. But, generally speaking, FROM RUSSIA WITH LOVE should be praised as rarely intelligent, yet still entertaining Bond film, one of the shiniest examples of Bonds from golden Connery era. All those who like to truly appreciate Bond phenomenon should watch it.
RATING: 8/10 (+++)
Review written on February 14th 2000
Dragan Antulov a.k.a. Drax Fido: 2:381/100 E-mail<EMAIL_ADDRESS>E-mail<EMAIL_ADDRESS>E-mail<EMAIL_ADDRESS>Filmske recenzije na hrvatskom/Movie Reviews in Croatian http://film.purger.com
The review above was posted to the
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Awesome Threat Detection and Hunting
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- 👩🎓 Trainings
- 👩💻 Labs
Tools
- MITRE ATT&CK Navigator (source code) - The ATT&CK Navigator is designed to provide basic navigation and annotation of ATT&CK matrices, something that people are already doing today in tools like Excel.
- HELK - A Hunting ELK (Elasticsearch, Logstash, Kibana) with advanced analytic capabilities.
- DetectionLab - Vagrant & Packer scripts to build a lab environment complete with security tooling and logging best practices.
- Revoke-Obfuscation - PowerShell Obfuscation Detection Framework.
- Invoke-ATTACKAPI - A PowerShell script to interact with the MITRE ATT&CK Framework via its own API.
- Unfetter - A reference implementation provides a framework for collecting events (process creation, network connections, Window Event Logs, etc.) from a client machine and performing CAR analytics to detect potential adversary activity.
- Flare - An analytical framework for network traffic and behavioral analytics.
- RedHunt-OS - A Virtual Machine for Adversary Emulation and Threat Hunting. RedHunt aims to be a one stop shop for all your threat emulation and threat hunting needs by integrating attacker's arsenal as well as defender's toolkit to actively identify the threats in your environment.
- Oriana - Lateral movement and threat hunting tool for Windows environments built on Django comes Docker ready.
- Bro-Osquery - Bro integration with osquery
- Brosquery - A module for osquery to load Bro logs into tables
- DeepBlueCLI - A PowerShell Module for Hunt Teaming via Windows Event Logs
- Uncoder - An online translator for SIEM saved searches, filters, queries, API requests, correlation and Sigma rules
- CimSweep - A suite of CIM/WMI-based tools that enable the ability to perform incident response and hunting operations remotely across all versions of Windows
- Dispatch - An open-source crisis management orchestration framework
- EQL - Event Query Language
- EQLLib - The Event Query Language Analytics Library (eqllib) is a library of event based analytics, written in EQL to detect adversary behaviors identified in MITRE ATT&CK™.
- BZAR (Bro/Zeek ATT&CK-based Analytics and Reporting) - A set of Zeek scripts to detect ATT&CK techniques
- Security Onion - An open-source Linux distribution for threat hunting, security monitoring, and log management. It includes ELK, Snort, Suricata, Zeek, Wazuh, Sguil, and many other security tools
- Varna - A quick & cheap AWS CloudTrail Monitoring with Event Query Language (EQL)
- BinaryAlert - Serverless, real-time & retroactive malware detection
- hollows_hunter - Scans all running processes, recognizes and dumps a variety of potentially malicious implants (replaced/implanted PEs, shellcodes, hooks, in-memory patches).
- ThreatHunting - A Splunk app mapped to MITRE ATT&CK to guide your threat hunts
- Sentinel Attack - A repository of Azure Sentinel alerts and hunting queries leveraging sysmon and the MITRE ATT&CK framework
- Brim - A desktop application to efficiently search large packet captures and Zeek logs
- YARA - The pattern matching swiss knife
- Intel Owl - An Open Source Intelligence, or OSINT solution to get threat intelligence data about a specific file, an IP or a domain from a single API at scale.
- Capa - An open-source tool to identify capabilities in executable files.
- Splunk Security Content Splunk-curated detection content that can easily be used accross many SIEMs (see Uncoder Rule Converter.)
- Threat Bus - Threat intelligence dissemination layer to connect security tools through a distributed publish/subscribe message broker.
- VAST - A network telemetry engine for data-driven security investigations.
- zeek2es - An open source tool to convert Zeek logs to Elastic/OpenSearch. You can also output pure JSON from Zeek's TSV logs!
- LogSlash: A standard for reducing log volume without sacrificing analytical capability.
- SOC-Multitool: A powerful and user-friendly browser extension that streamlines investigations for security professionals.
- Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark.
- ProcMon for Linux
- Synthetic Adversarial Log Objects (SALO) - A framework for the generation of log events without the need for infrastructure or actions to initiate the event that causes a log event.
Detection, Alerting and Automation Platforms
Check out the Detection and Response Pipeline repository for more resources. The repo contains a compilation of suggested tools/services for each component in a detection and response pipeline, along with real-world examples. The purpose is to create a reference hub for designing effective threat detection and response pipelines.
- ElastAlert - A framework for alerting on anomalies, spikes, or other patterns of interest from data in Elasticsearch
- StreamAlert - A serverless, realtime data analysis framework which empowers you to ingest, analyze, and alert on data from any environment, using datasources and alerting logic you define
- Matano: An open source security lake platform (SIEM alternative) for threat hunting, detection and response on AWS. Matano lets you write advanced detections as code (using python) to correlate and alert on threats in realtime.
- Shuffle: A general purpose security automation platform.
- Sublime: An open platform for detection, response, and threat hunting in email environments. Sublime lets you write advanced detections as code to alert and remediate threats like phishing in real-time.
- Substation - A cloud native data pipeline and transformation toolkit for security teams.
Endpoint Monitoring
- osquery (github) - SQL powered operating system instrumentation, monitoring, and analytics
- Kolide Fleet - A flexible control server for osquery fleets
- Zeek Agent - An endpoint monitoring agent that provides host activity to Zeek
- Velociraptor - Endpoint visibility and collection tool
- Sysdig - A tool for deep Linux system visibility, with native support for containers. Think about sysdig as strace + tcpdump + htop + iftop + lsof + …awesome sauce
- go-audit - An alternative to the Linux auditd daemon
- Sysmon - A Windows system service and device driver that monitors and logs system activity to the Windows event log
- Sysmon for Linux
- OSSEC - An open-source Host-based Intrusion Detection System (HIDS)
- WAZUH - An open-source security platform
Configuration
- sysmon-DFIR - Sources, configuration and how to detect evil things utilizing Microsoft Sysmon.
- sysmon-config - Sysmon configuration file template with default high-quality event tracing.
- sysmon-modular - A repository of sysmon configuration modules. It also includes a mapping of Sysmon configurations to MITRE ATT&CK techniques.
- auditd configuration
- osquery-configuration - A repository for using osquery for incident detection and response.
Network Monitoring
- Zeek (formerly Bro) - A network security monitoring tool
- ntopng - A web-based network traffic monitoring tool
- Suricata - A network threat detection engine
- Snort (github) - A network intrusion detection tool
- Joy - A package for capturing and analyzing network flow data and intraflow data, for network research, forensics, and security monitoring
- Netcap - A framework for secure and scalable network traffic analysis
- Moloch - A large scale and open source full packet capture and search tool
- Stenographer - A full-packet-capture tool
Fingerprinting Tools
- JA3 - A method for profiling SSL/TLS Clients and Servers
- HASSH - Profiling Method for SSH Clients and Servers
- RDFP - Zeek Remote desktop fingerprinting script based on FATT (Fingerprint All The Things)
- FATT - A pyshark based script for extracting network metadata and fingerprints from pcap files and live network traffic
- FingerprinTLS - A TLS fingerprinting method
- Mercury - Network fingerprinting and packet metadata capture
- GQUIC Protocol Analyzer for Zeek
- Recog - A framework for identifying products, services, operating systems, and hardware by matching fingerprints against data returned from various network probes
- Hfinger - Fingerprinting HTTP requests
- JARM - An active Transport Layer Security (TLS) server fingerprinting tool.
Email Monitoring
- Sublime Platform - An email threat detection engine
Detection Rules
- Sigma - Generic Signature Format for SIEM Systems
- Splunk Detections and Analytic stories
- Elastic Detection Rules
- MITRE CAR - The Cyber Analytics Repository is a knowledge base of analytics developed by MITRE based on the Adversary Tactics, Techniques, and Common Knowledge (ATT&CK™) adversary model.
- Awesome YARA Rules
- Chronicle Detection Rules - Collection of YARA-L 2.0 sample rules for the Chronicle Detection API.
- GCP Security Analytics - Community Security Analytics provides a set of community-driven audit & threat queries for Google Cloud.
- Sublime Detection Rules - Email attack detection, response, and hunting rules.
Dataset
- Mordor - Pre-recorded security events generated by simulated adversarial techniques in the form of JavaScript Object Notation (JSON) files. The data is categorized by platforms, adversary groups, tactics and techniques defined by the Mitre ATT&CK Framework.
- SecRepo.com(github repo) - Samples of security related data.
- Boss of the SOC (BOTS) Dataset Version 1
- Boss of the SOC (BOTS) Dataset Version 2
- Boss of the SOC (BOTS) Dataset Version 3
- EMBER (paper) - The EMBER dataset is a collection of features from PE files that serve as a benchmark dataset for researchers
- theZoo - A repository of LIVE malwares
- CIC Datasets - Canadian Institute for Cybersecurity datasets
- Netresec's PCAP repo list - A list of public packet capture repositories, which are freely available on the Internet.
- PCAP-ATTACK - A repo of PCAP samples for different ATT&CK techniques.
- EVTX-ATTACK-SAMPLES - A repo of Windows event samples (EVTX) associated with ATT&CK techniques (EVTX-ATT&CK Sheet).
- Public Security Log Sharing Site
- attack_data - A repository of curated datasets from various attacks.
Resources
- Huntpedia - Your Threat Hunting Knowledge Compendium
- Hunt Evil - Your Practical Guide to Threat Hunting
- The Hunter's Handbook - Endgame's guide to adversary hunting
- ThreatHunter-Playbook - A Threat hunter's playbook to aid the development of techniques and hypothesis for hunting campaigns.
- The ThreatHunting Project - A great collection of hunts and threat hunting resources.
- CyberThreatHunting - A collection of resources for threat hunters.
- Hunt-Detect-Prevent - Lists of sources and utilities to hunt, detect and prevent evildoers.
- Alerting and Detection Strategy Framework
- Generating Hypotheses for Successful Threat Hunting
- Expert Investigation Guide - Threat Hunting
- Active Directory Threat Hunting
- Threat Hunting for Fileless Malware
- Windows Commands Abused by Attackers
- Deception-as-Detection - Deception based detection techniques mapped to the MITRE’s ATT&CK framework.
- On TTPs
- Hunting On The Cheap (Slides)
- Threat Hunting Techniques - AV, Proxy, DNS and HTTP Logs
- Detecting Malware Beacons Using Splunk
- Data Science Hunting Funnel
- Use Python & Pandas to Create a D3 Force Directed Network Diagram
- Syscall Auditing at Scale
- Catching attackers with go-audit and a logging pipeline
- The Coventry Conundrum of Threat Intelligence
- Signal the ATT&CK: Part 1 - Building a real-time threat detection capability with Tanium that focuses on documented adversarial techniques.
- SANS Summit Archives (DFIR, Cyber Defense) - Threat hunting, Blue Team and DFIR summit slides
- Bro-Osquery - Large-Scale Host and Network Monitoring Using Open-Source Software
- Malware Persistence - Collection of various information focused on malware persistence: detection (techniques), response, pitfalls and the log collection (tools).
- Threat Hunting with Jupyter Notebooks
- How Dropbox Security builds tools for threat detection and incident response
- Introducing Event Query Language
- The No Hassle Guide to Event Query Language (EQL) for Threat Hunting (PDF)
- Introducing the Funnel of Fidelity (PDF)
- Detection Spectrum (PDF)
- Capability Abstraction (PDF)
- Awesome YARA - A curated list of awesome YARA rules, tools, and resources
- Defining ATT&CK Data Sources - A two-part blog series that outlines a new methodology to extend ATT&CK’s current data sources.
- DETT&CT: MAPPING YOUR BLUE TEAM TO MITRE ATT&CK™ - A blog that describes how to align MITRE ATT&CK-based detection content with data sources.
- Detection as Code in Splunk Part 1, Part 2, and Part 3 - A multipart series describing how detection as code can be successfully deployed in a Splunk environment.
- Lessons Learned in Detection Engineering - A well experienced detection engineer describes in detail his observations, challenges, and recommendations for building an effective threat detection program.
- A Research-Driven process applied to Threat Detection Engineering Inputs.
- A video series focused on malware execution and investigations using Elastic Security.
Frameworks
- MITRE ATT&CK - A curated knowledge base and model for cyber adversary behavior, reflecting the various phases of an adversary’s lifecycle and the platforms they are known to target.
- Alerting and Detection Strategies Framework - A framework for developing alerting and detection strategies.
- A Simple Hunting Maturity Model - The Hunting Maturity Model describes five levels of organizational hunting capability, ranging from HMM0 (the least capability) to HMM4 (the most).
- The Pyramic of Pain - The relationship between the types of indicators you might use to detect an adversary's activities and how much pain it will cause them when you are able to deny those indicators to them.
- A Framework for Cyber Threat Hunting
- The PARIS Model - A model for threat hunting.
- Cyber Kill Chain - It is part of the Intelligence Driven Defense® model for identification and prevention of cyber intrusions activity. The model identifies what the adversaries must complete in order to achieve their objective.
- The DML Model - The Detection Maturity Level (DML) model is a capability maturity model for referencing ones maturity in detecting cyber attacks.
- NIST Cybersecurity Framework
- OSSEM (Open Source Security Events Metadata) - A community-led project that focuses on the documentation and standardization of security event logs from diverse data sources and operating systems.
- Open Cybersecurity Schema Framework (OCSF) - A framework for creating schemas and it also delivers a cybersecurity event schema built with the framework (schema browser).
- MITRE Engage - A framework for planning and discussing adversary engagement operations that empowers you to engage your adversaries and achieve your cybersecurity goals.
- MaGMa Use Case Defintion Model - A business-centric approach for planning and defining threat detection use cases.
Windows
- Threat Hunting via Windows Event Logs
- Windows Logging Cheat Sheets
- Active Directory Threat Hunting
- Windows Hunting - A collection of Windows hunting queries
- Windows Commands Abused by Attackers
- JPCERT - Detecting Lateral Movement through Tracking Event Logs
Sysmon
- Splunking the Endpoint: Threat Hunting with Sysmon
- Threat Hunting with Sysmon: Word Document with Macro
- Chronicles of a Threat Hunter: Hunting for In-Memory Mimikatz with Sysmon and ELK
- Advanced Incident Detection and Threat Hunting using Sysmon (and Splunk) (botconf 2016 Slides, FIRST 2017 Slides)
- The Sysmon and Threat Hunting Mimikatz wiki for the blue team
- Splunkmon — Taking Sysmon to the Next Level
- Sysmon Threat Detection Guide (PDF)
PowerShell
- Revoke-Obfuscation: PowerShell Obfuscation Detection Using Science (Paper, Slides)
- Hunting the Known Unknowns (With PowerShell)
- HellsBells, Let's Hunt PowerShells!
- Hunting for PowerShell Using Heatmaps
MacOS
Osquery
- osquery Across the Enterprise
- osquery for Security — Part 1
- osquery for Security — Part 2 - Advanced osquery functionality, File integrity monitoring, process auditing, and more.
- Tracking a stolen code-signing certificate with osquery
- Monitoring macOS hosts with osquery
- Kolide's Blog
- The osquery Extensions Skunkworks Project
DNS
- Detecting DNS Tunneling
- Hunting the Known Unknowns (with DNS)
- Detecting dynamic DNS domains in Splunk
- Random Words on Entropy and DNS
- Tracking Newly Registered Domains
- Suspicious Domains Tracking Dashboard
- Proactive Malicious Domain Search
- DNS is NOT Boring - Using DNS to Expose and Thwart Attacks
- Actionable Detects - Blue Team Tactics
Fingerprinting
- JA3: SSL/TLS Client Fingerprinting for Malware Detection
- TLS Fingerprinting with JA3 and JA3S
- HASSH - a profiling method for SSH Clients and Servers
- Finding Evil on the Network Using JA3/S and HASSH
- RDP Fingerprinting - Profiling RDP Clients with JA3 and RDFP
- Effective TLS Fingerprinting Beyond JA3
- TLS Fingerprinting in the Real World
- HTTP Client Fingerprinting Using SSL Handshake Analysis (source code: mod_sslhaf
- TLS fingerprinting - Smarter Defending & Stealthier Attacking
- JA3er - a DB of JA3 fingerprints
- An Introduction to HTTP fingerprinting
- TLS Fingerprints collected from the University of Colorado Boulder campus network
- The use of TLS in Censorship Circumvention
- TLS Beyond the Browser: Combining End Host and Network Data to Understand Application Behavior
- HTTPS traffic analysis and client identification using passive SSL/TLS fingerprinting
- Markov Chain Fingerprinting to Classify Encrypted Traffic
- HeadPrint: Detecting Anomalous Communications through Header-based Application Fingerprinting
Data Science
- data_hacking - Examples of using IPython, Pandas, and Scikit Learn to get the most out of your security data.
- Reverse engineering the analyst: building machine learning models for the SOC
- msticpy - A library for InfoSec investigation and hunting in Jupyter Notebooks.
Research Papers
- Intelligence-Driven Computer Network Defense Informed by Analysis of Adversary Campaigns and Intrusion Kill Chains
- The Diamond Model of Intrusion Analysis
- EXPOSURE: Finding Malicious Domains Using Passive DNS Analysis
- A Comprehensive Approach to Intrusion Detection Alert Correlation (Paper, Dissertation)
- On Botnets that use DNS for Command and Control
- Intelligent, Automated Red Team Emulation
- Machine Learning for Encrypted Malware Traffic Classification
Blogs
- David Bianco's Blog
- DFIR and Threat Hunting Blog
- CyberWardog's Blog (old)
- Chris Sanders' Blog
- Kolide Blog
- Anton Chuvakin
- Alexandre Teixeira
Related Awesome Lists
- Awesome Kubernetes Threat Detection
- Awesome Incident Response
- Awesome Forensics
- Awesome Honeypots
- Awesome Malware Analysis
- Awesome YARA
- Awesome Security
- Awesome Cloud Security
Podcasts
- Google Cloud Security Podcast by Anton Chuvakin and Timothy Peacock.
- Detection: Challenging Paradigms by SpecterOps
- Darknet Diaries by Andy Greenberg - True stories from the dark side of the Internet.
- Risky Business by Patrick Gray
Newsletters
- Detection Engineering Weekly by Zack 'techy' Allen
- This Week in 4n6 - A weekly roundup of digital forensics and incident response news.
Videos
- SANS Threat Hunting and IR Summit 2017
- SANS Threat Hunting and IR Summit 2016
- BotConf 2016 - Advanced Incident Detection and Threat Hunting using Sysmon and Splunk
- BSidesCharm 2017 - Detecting the Elusive: Active Directory Threat Hunting
- BSidesAugusta 2017 - Machine Learning Fueled Cyber Threat Hunting
- Toppling the Stack: Outlier Detection for Threat Hunters
- BSidesPhilly 2017 - Threat Hunting: Defining the Process While Circumventing Corporate Obstacles
- Black Hat 2017 - Revoke-Obfuscation: PowerShell Obfuscation Detection (And Evasion) Using Science
- DefCon 25 - MS Just Gave the Blue Team Tactical Nukes
- BSides London 2017 - Hunt or be Hunted
- SecurityOnion 2017 - Pivoting Effectively to Catch More Bad Guys
- SkyDogCon 2016 - Hunting: Defense Against The Dark Arts
- BSidesAugusta 2017 - Don't Google 'PowerShell Hunting'
- BSidesAugusta 2017 - Hunting Adversaries w Investigation Playbooks & OpenCNA
- Visual Hunting with Linked Data
- RVAs3c - Pyramid of Pain: Intel-Driven Detection/Response to Increase Adversary's Cost
- BSidesLV 2016 - Hunting on the Endpoint w/ Powershell
- Derbycon 2015 - Intrusion Hunting for the Masses A Practical Guide
- BSides DC 2016 - Practical Cyborgism: Getting Start with Machine Learning for Incident Detection
- SANS Webcast 2018 - What Event Logs? Part 1: Attacker Tricks to Remove Event Logs
- Profiling And Detecting All Things SSL With JA3
- ACoD 2019 - HASSH SSH Client/Server Profiling
- QueryCon 2018 - An annual conference for the osquery open-source community (querycon.io)
- Visual Hunting with Linked Data Graphs
- SecurityOnion Con 2018 - Introduction to Data Analysis
- Insider Threats Detection at Airbus – AI up Against Data Leakage and Industrial Espionage
- Cyber Security Investigations with Jupyter Notebooks
Trainings
- Applied Network Defense courses by Chris Sanders
- Investigation theory, Practical threat hunting, Detection engineering with Sigma, etc.
- Security Blue Team (BTL1 and BTL2 certificates)
- LetsDefend - Hands-On SOC Analyst Training
- TryHackMe - Hands-on cyber security training through real-world scenarios.
- 13Cubed, Investigating Windows Endpoints by Richard Davis
- HackTheBox - While not directly related to threat detection, the website features training modules on general security and offensive topics that can be beneficial for junior SOC analysts.
Labs
- DetectionLab - Vagrant & Packer scripts to build a lab environment complete with security tooling and logging best practices.
- Splunk Boss of the SOC - Hands-on workshops and challenges to practice threat hunting using the BOTS and other datasets.
- HELK - A Hunting ELK (Elasticsearch, Logstash, Kibana) with advanced analytic capabilities.
- BlueTeam Lab - A detection lab created with Terraform and Ansible in Azure.
- attack_range - A tool that allows you to create vulnerable instrumented local or cloud environments to simulate attacks against and collect the data into Splunk.
- "Awesome Detection" Twitter List - Twitter accounts that tweet about threat detection, hunting and DFIR.
Threat Simulation Tools
- MITRE CALDERA - An automated adversary emulation system that performs post-compromise adversarial behavior within Windows Enterprise networks.
- APTSimulator - A Windows Batch script that uses a set of tools and output files to make a system look as if it was compromised.
- Atomic Red Team - Small and highly portable detection tests mapped to the Mitre ATT&CK Framework.
- Network Flight Simulator - flightsim is a lightweight utility used to generate malicious network traffic and help security teams to evaluate security controls and network visibility.
- Metta - A security preparedness tool to do adversarial simulation.
- Red Team Automation (RTA) - RTA provides a framework of scripts designed to allow blue teams to test their detection capabilities against malicious tradecraft, modeled after MITRE ATT&CK.
- SharpShooter - Payload Generation Framework.
- CACTUSTORCH - Payload Generation for Adversary Simulations.
- DumpsterFire - A modular, menu-driven, cross-platform tool for building repeatable, time-delayed, distributed security events.
- Empire(website) - A PowerShell and Python post-exploitation agent.
- PowerSploit - A PowerShell Post-Exploitation Framework.
- RedHunt-OS - A Virtual Machine for Adversary Emulation and Threat Hunting. RedHunt aims to be a one stop shop for all your threat emulation and threat hunting needs by integrating attacker's arsenal as well as defender's toolkit to actively identify the threats in your environment.
- Infection Monkey - An open source Breach and Attack Simulation (BAS) tool that assesses the resiliency of private and public cloud environments to post-breach attacks and lateral movement.
- Splunk Attack Range - A tool that allows you to create vulnerable instrumented local or cloud environments to simulate attacks against and collect the data into Splunk.
Threat Simulation Resources
- MITRE's Adversary Emulation Plans
- Awesome Red Teaming - A list of awesome red teaming resources
- Red-Team Infrastructure Wiki - Wiki to collect Red Team infrastructure hardening resources.
- Payload Generation using SharpShooter
- SpecterOps Blog
- Advanced Threat Tactics - A free course on red team operations and adversary simulations.
- Signal the ATT&CK: Part 1 - Modelling APT32 in CALDERA
- Red Teaming/Adversary Simulation Toolkit - A collection of open source and commercial tools that aid in red team operations.
- C2 Matrix (Google Sheets)
- adversaryemulationlibrary - An open library of adversary emulation plans designed to empower organizations to test their defenses based on real-world TTPs.
Contribute
Contributions welcome! Read the contribution guidelines first.
License
To the extent possible under law, Adel "0x4D31" Karimi has waived all copyright and
related or neighboring rights to this work.


@since SDL 7.0.0
- (nonnull instancetype)initWithApproximatePosition:(UInt8)approximatePosition
deviation:(UInt8)deviation;
init(approximatePosition: UInt8, deviation: UInt8)
- The approximate percentage that the window is open - 0 being fully closed, 100 being fully open
- The percentage deviation of the approximatePosition. e.g. If the approximatePosition is 50 and the deviation is 10, then the window’s location is somewhere between 40 and 60.
A SDLWindowState object
The approximate percentage that the window is open - 0 being fully closed, 100 being fully open
Mandatory, Integer, 0 - 100
@property (nonatomic, strong) NSNumber<SDLUInt> *_Nonnull approximatePosition;
var approximatePosition: NSNumber & SDLUInt { get set }
The percentage deviation of the approximatePosition. e.g. If the approximatePosition is 50 and the deviation is 10, then the window’s location is somewhere between 40 and 60.
Mandatory, Integer, 0 - 100
@property (nonatomic, strong) NSNumber<SDLUInt> *_Nonnull deviation;
var deviation: NSNumber & SDLUInt { get set }


Title
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Description
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Open your console or developer tools to see it work!
You will see only one message even when we add thre different message.
The reason is because only one message has DEBUG Level


This is a tools to generate the bash script and use rofi
to generate a menu by pipe the text into rofi.
Once you generate a menu, make the script executable and run.
This tools only generate a menu.
For rofi theme, please goto this link
For further information, see a git repository


Contructor: circle(radius)
After .move(100,100); Note: not relative
after off-center rotate: circle.transform({ rotation: 45, cx: 30, cy: 30 });
after skew: circ.transform({ skewX: 10; });
after scale: circ.transform({ scaleX: 10 });


5 January 2012 - The Ministry of Health and Population of Egypt has notified WHO of a case of human infection with avian influenza A (H5N1) virus.
The case is a 42 year-old male from Menofia Governorate. He developed symptoms on 16 December 2011 and was admitted to hospital on 21 December 2011, where he received oseltamivir treatment. He was in critical condition and died on 22 December 2011.
The case was confirmed by the Central Public Health Laboratories, a National Influenza Centre of the WHO Global Influenza Surveillance Network, on 24 December 2011.
Investigations into the source of infection indicated that the case had exposure to sick and dead backyard poultry.
Of the 157 cases confirmed to date in Egypt, 55 have been fatal.


Want to try again?
We're using the Watson Visual Recognition service to analyze the content of a picture


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| Packages that use com.google.gson | |
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| com.google.gson | This package provides the Gson class to convert Json to Java and
vice-versa. |
| Classes in com.google.gson used by com.google.gson | |
|---|---|
| ExclusionStrategy
A strategy (or policy) definition that is used to decide whether or not a field or top-level class should be serialized or deserialized as part of the JSON output/input. |
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| FieldAttributes
A data object that stores attributes of a field. |
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| FieldNamingPolicy
An enumeration that defines a few standard naming conventions for JSON field names. |
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| FieldNamingStrategy
A mechanism for providing custom field naming in Gson. |
|
| Gson
This is the main class for using Gson. |
|
| GsonBuilder
Use this builder to construct a Gson instance when you need to set configuration
options other than the default. |
|
| JsonArray
A class representing an array type in Json. |
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| JsonDeserializationContext
Context for deserialization that is passed to a custom deserializer during invocation of its JsonDeserializer.deserialize(JsonElement, Type, JsonDeserializationContext)
method. |
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| JsonElement
A class representing an element of Json. |
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| JsonIOException
This exception is raised when Gson was unable to read an input stream or write to one. |
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| JsonNull
A class representing a Json null value. |
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| JsonObject
A class representing an object type in Json. |
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| JsonParseException
This exception is raised if there is a serious issue that occurs during parsing of a Json string. |
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| JsonPrimitive
A class representing a Json primitive value. |
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| JsonSerializationContext
Context for serialization that is passed to a custom serializer during invocation of its JsonSerializer.serialize(Object, Type, JsonSerializationContext) method. |
|
| JsonSyntaxException
This exception is raised when Gson attempts to read (or write) a malformed JSON element. |
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| LongSerializationPolicy
Defines the expected format for a long or Long type when its serialized. |
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| TypeAdapter
Converts Java objects to and from JSON. |
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Creates type adapters for set of related types. |
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{{ desc }}
Zoinks! The playlist is empty.
Refer to the commands list for commands you can use to play music.


ASCII is a code used by computers to represent characters as numbers. This allows computers to store a letter as one byte of information. One byte of information allows you to represent 256 different values, which is enough to encode all the letters (uppercase and lowercase) as well as the numbers 0-9 and other special characters such as the @ symbol.


[gecode-users] Problem to formulate a constraint
Christian Schulte
cschulte at kth.se
Thu May 23 17:49:07 CEST 2013
Hi,
Did you try reification? While not great, it should not be too hard to pull
this off. Or am I missing something here?
Best
Christian
--
Christian Schulte, Professor of Computer Science, KTH,
www.ict.kth.se/~cschulte/
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Uwe Nowak
Sent: Thursday, May 23, 2013 3:40 PM
To: users at gecode.org
Subject: [gecode-users] Problem to formulate a constraint
I am a beginner with gecode and have a problem to formulate a constraint.
I was looking through all channel constraints, however they do not seem to
fit my needs, or I am unable to formulate my needs in the language of the
channel constraints.
I have the following variables
*an IntVar c with a finite set of values {A_1,...,A_n} *an IntVarArray p
I have the following fixed parameters
For each value A_t I have a finite set of fixed indexed values I_t (e.g, an
std::set<int>)
A constant B
Now I want to formulate the following constraints for(t = 1...n){
c=A_t ==> for all I in I_t: p[i]=B
}
I thought to create an IntVarArgs of the subset of p with the indices I_t
However, than I have tor formulated for an IntVarArgs q_t:
for(t = 1...n){
c=A_t ==> For all elements q_t[i]=B
}
However, I do not find the right expressions to formulate this in gecode...
_______________________________________________
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Methods
- C
- D
- F
- N
- U
Attributes
| [RW] | notify | |
| [RW] | notify_author |
Class Public methods
create_status_change_note(noteable, author, status)
Link
Source: show
# File app/models/note.rb, line 53 def self.create_status_change_note(noteable, author, status) create({ noteable: noteable, project: noteable.project, author: author, note: "_Status changed to #{status}_" }, without_protection: true) end
Instance Public methods
downvote?()
Link
Returns true if this is a downvote note, otherwise false is returned
Source: show
# File app/models/note.rb, line 125 def downvote? note.start_with?('-1') || note.start_with?(':-1:') end
for_commit?()
Link
Source: show
# File app/models/note.rb, line 101 def for_commit? noteable_type == "Commit" end
for_diff_line?()
Link
Source: show
# File app/models/note.rb, line 105 def for_diff_line? line_code.present? end
noteable()
Link
override to return commits, which are not active record
Source: show
# File app/models/note.rb, line 71 def noteable if for_commit? project.commit(commit_id) else super end # Temp fix to prevent app crash # if note commit id doesnt exist rescue nil end
noteable_type_name()
Link
Source: show
# File app/models/note.rb, line 129 def noteable_type_name if noteable_type.present? noteable_type.downcase else "wall" end end


15. Probabilistic Reasoning over Time
Exercise 15.1 [state-augmentation-exercise]
Show that any second-order Markov process can be rewritten as a first-order Markov process with an augmented set of state variables. Can this always be done parsimoniously, i.e., without increasing the number of parameters needed to specify the transition model?
Exercise 15.2 [markov-convergence-exercise]
In this exercise, we examine what happens to the probabilities in the umbrella world in the limit of long time sequences.
-
Suppose we observe an unending sequence of days on which the umbrella appears. Show that, as the days go by, the probability of rain on the current day increases monotonically toward a fixed point. Calculate this fixed point.
-
Now consider forecasting further and further into the future, given just the first two umbrella observations. First, compute the probability $P(r_{2+k}|u_1,u_2)$ for $k=1 \ldots 20$ and plot the results. You should see that the probability converges towards a fixed point. Prove that the exact value of this fixed point is 0.5.
Exercise 15.3 [island-exercise]
This exercise develops a space-efficient variant of the forward–backward algorithm described in Figure forward-backward-algorithm (page forward-backward-algorithm). We wish to compute for . This will be done with a divide-and-conquer approach.
-
Suppose, for simplicity, that $t$ is odd, and let the halfway point be $h=(t+1)/2$. Show that can be computed for $k=1,\ldots ,h$ given just the initial forward message , the backward message , and the evidence .
-
Show a similar result for the second half of the sequence.
-
Given the results of (a) and (b), a recursive divide-and-conquer algorithm can be constructed by first running forward along the sequence and then backward from the end, storing just the required messages at the middle and the ends. Then the algorithm is called on each half. Write out the algorithm in detail.
-
Compute the time and space complexity of the algorithm as a function of $t$, the length of the sequence. How does this change if we divide the input into more than two pieces?
Exercise 15.4 [flawed-viterbi-exercise]
On page flawed-viterbi-page, we outlined a flawed procedure for finding the most likely state sequence, given an observation sequence. The procedure involves finding the most likely state at each time step, using smoothing, and returning the sequence composed of these states. Show that, for some temporal probability models and observation sequences, this procedure returns an impossible state sequence (i.e., the posterior probability of the sequence is zero).
Exercise 15.5 [hmm-likelihood-exercise]
Equation (matrix-filtering-equation) describes the filtering process for the matrix formulation of HMMs. Give a similar equation for the calculation of likelihoods, which was described generically in Equation (forward-likelihood-equation).
Consider the vacuum worlds of Figure vacuum-maze-ch4-figure (perfect sensing) and Figure vacuum-maze-hmm2-figure (noisy sensing). Suppose that the robot receives an observation sequence such that, with perfect sensing, there is exactly one possible location it could be in. Is this location necessarily the most probable location under noisy sensing for sufficiently small noise probability $\epsilon$? Prove your claim or find a counterexample.
Exercise 15.7 [hmm-robust-exercise]
In Section hmm-localization-section, the prior distribution over locations is uniform and the transition model assumes an equal probability of moving to any neighboring square. What if those assumptions are wrong? Suppose that the initial location is actually chosen uniformly from the northwest quadrant of the room and the action actually tends to move southeast[hmm-robot-southeast-page]. Keeping the HMM model fixed, explore the effect on localization and path accuracy as the southeasterly tendency increases, for different values of $\epsilon$.
Exercise 15.8 [roomba-viterbi-exercise]
Consider a version of the vacuum robot (page vacuum-maze-hmm2-figure) that has the policy of going straight for as long as it can; only when it encounters an obstacle does it change to a new (randomly selected) heading. To model this robot, each state in the model consists of a (location, heading) pair. Implement this model and see how well the Viterbi algorithm can track a robot with this model. The robot’s policy is more constrained than the random-walk robot; does that mean that predictions of the most likely path are more accurate?
We have described three policies for the vacuum robot: (1) a uniform random walk, (2) a bias for wandering southeast, as described in Exercise hmm-robust-exercise, and (3) the policy described in Exercise roomba-viterbi-exercise. Suppose an observer is given the observation sequence from a vacuum robot, but is not sure which of the three policies the robot is following. What approach should the observer use to find the most likely path, given the observations? Implement the approach and test it. How much does the localization accuracy suffer, compared to the case in which the observer knows which policy the robot is following?
This exercise is concerned with filtering in an environment with no landmarks. Consider a vacuum robot in an empty room, represented by an $n \times m$ rectangular grid. The robot’s location is hidden; the only evidence available to the observer is a noisy location sensor that gives an approximation to the robot’s location. If the robot is at location $(x, y)$ then with probability .1 the sensor gives the correct location, with probability .05 each it reports one of the 8 locations immediately surrounding $(x, y)$, with probability .025 each it reports one of the 16 locations that surround those 8, and with the remaining probability of .1 it reports “no reading.” The robot’s policy is to pick a direction and follow it with probability .8 on each step; the robot switches to a randomly selected new heading with probability .2 (or with probability 1 if it encounters a wall). Implement this as an HMM and do filtering to track the robot. How accurately can we track the robot’s path?
This exercise is concerned with filtering in an environment with no landmarks. Consider a vacuum robot in an empty room, represented by an $n \times m$ rectangular grid. The robot’s location is hidden; the only evidence available to the observer is a noisy location sensor that gives an approximation to the robot’s location. If the robot is at location $(x, y)$ then with probability .1 the sensor gives the correct location, with probability .05 each it reports one of the 8 locations immediately surrounding $(x, y)$, with probability .025 each it reports one of the 16 locations that surround those 8, and with the remaining probability of .1 it reports “no reading.” The robot’s policy is to pick a direction and follow it with probability .7 on each step; the robot switches to a randomly selected new heading with probability .3 (or with probability 1 if it encounters a wall). Implement this as an HMM and do filtering to track the robot. How accurately can we track the robot’s path?
Exercise 15.12 [switching-kf-exercise]
Often, we wish to monitor a continuous-state system whose behavior switches unpredictably among a set of $k$ distinct “modes.” For example, an aircraft trying to evade a missile can execute a series of distinct maneuvers that the missile may attempt to track. A Bayesian network representation of such a switching Kalman filter model is shown in Figure switching-kf-figure.
-
Suppose that the discrete state $S_t$ has $k$ possible values and that the prior continuous state estimate is a multivariate Gaussian distribution. Show that the prediction is a mixture of Gaussians—that is, a weighted sum of Gaussians such that the weights sum to 1.
-
Show that if the current continuous state estimate is a mixture of $m$ Gaussians, then in the general case the updated state estimate will be a mixture of $km$ Gaussians.
-
What aspect of the temporal process do the weights in the Gaussian mixture represent?
The results in (a) and (b) show that the representation of the posterior grows without limit even for switching Kalman filters, which are among the simplest hybrid dynamic models.
Exercise 15.13 [kalman-update-exercise]
Complete the missing step in the derivation of Equation (kalman-one-step-equation) on page kalman-one-step-equation, the first update step for the one-dimensional Kalman filter.
Exercise 15.14 [kalman-variance-exercise]
Let us examine the behavior of the variance update in Equation (kalman-univariate-equation) (page kalman-univariate-equation).
-
Plot the value of $\sigma_t^2$ as a function of $t$, given various values for $\sigma_x^2$ and $\sigma_z^2$.
-
Show that the update has a fixed point $\sigma^2$ such that $\sigma_t^2 \rightarrow \sigma^2$ as $t \rightarrow \infty$, and calculate the value of $\sigma^2$.
-
Give a qualitative explanation for what happens as $\sigma_x^2\rightarrow 0$ and as $\sigma_z^2\rightarrow 0$.
Exercise 15.15 [sleep1-exercise]
A professor wants to know if students are getting enough sleep. Each day, the professor observes whether the students sleep in class, and whether they have red eyes. The professor has the following domain theory:
-
The prior probability of getting enough sleep, with no observations, is 0.7.
-
The probability of getting enough sleep on night $t$ is 0.8 given that the student got enough sleep the previous night, and 0.3 if not.
-
The probability of having red eyes is 0.2 if the student got enough sleep, and 0.7 if not.
-
The probability of sleeping in class is 0.1 if the student got enough sleep, and 0.3 if not.
Formulate this information as a dynamic Bayesian network that the professor could use to filter or predict from a sequence of observations. Then reformulate it as a hidden Markov model that has only a single observation variable. Give the complete probability tables for the model.
Exercise 15.16 [sleep1-exercise]
A professor wants to know if students are getting enough sleep. Each day, the professor observes whether the students sleep in class, and whether they have red eyes. The professor has the following domain theory:
-
The prior probability of getting enough sleep, with no observations, is 0.6.
-
The probability of getting enough sleep on night $t$ is 0.8 given that the student got enough sleep the previous night, and 0.2 if not.
-
The probability of having red eyes is 0.2 if the student got enough sleep, and 0.7 if not.
-
The probability of sleeping in class is 0.1 if the student got enough sleep, and 0.3 if not.
Formulate this information as a dynamic Bayesian network that the professor could use to filter or predict from a sequence of observations. Then reformulate it as a hidden Markov model that has only a single observation variable. Give the complete probability tables for the model.
For the DBN specified in Exercise sleep1-exercise and for the evidence values
perform the following computations:
-
State estimation: Compute for each of $t = 1,2,3$.
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Smoothing: Compute for each of $t = 1,2,3$.
-
Compare the filtered and smoothed probabilities for $t=1$ and $t=2$.
Suppose that a particular student shows up with red eyes and sleeps in class every day. Given the model described in Exercise sleep1-exercise, explain why the probability that the student had enough sleep the previous night converges to a fixed point rather than continuing to go down as we gather more days of evidence. What is the fixed point? Answer this both numerically (by computation) and analytically.
Exercise 15.19 [battery-sequence-exercise]
This exercise analyzes in more detail the persistent-failure model for the battery sensor in Figure battery-persistence-figure(a) (page battery-persistence-figure).
-
Figure battery-persistence-figure(b) stops at $t=32$. Describe qualitatively what should happen as $t\to\infty$ if the sensor continues to read 0.
-
Suppose that the external temperature affects the battery sensor in such a way that transient failures become more likely as temperature increases. Show how to augment the DBN structure in Figure battery-persistence-figure(a), and explain any required changes to the CPTs.
-
Given the new network structure, can battery readings be used by the robot to infer the current temperature?
Exercise 15.20 [dbn-elimination-exercise]
Consider applying the variable elimination algorithm to the umbrella DBN unrolled for three slices, where the query is ${\textbf{P}}(R_3|u_1,u_2,u_3)$. Show that the space complexity of the algorithm—the size of the largest factor—is the same, regardless of whether the rain variables are eliminated in forward or backward order.


The back of my neck feels all hot and boggy when I wake up. I hate that. The air conditioner in this motel room makes a lot of noise, but it's just a big show. I close my eyes and hope sleep takes me away somewhere dark and cool, but it doesn't. Reality persists.
I have been tapering off booze for the past few days. It's amazing how timid and jittery I become when the alcohol is oozing its way out of me.  To think, I lived for years in this helpless, reclusive state.  The whole time, I though the alcohol was giving me courage when it was stealing it from me.
I can't drink anymore. I need courage.
I'm down to my last two hundred dollars. I could call good ol' mom and dad and ask them for some help. But what kind of conversation would that be? "Why am I broke? Well, I took some time off work so I could write a book. About what?
No, I'm not going to call ol' mom and dad. I'm not going back to the sober house either. I'm going to get some answers. I'm going to call Shawn.
Shawn shows up at the motel right after he gets off of work. I'm surprised because we had gotten into a lot of little arguments towards the end, and I left on pretty bad terms with him. I'm standing in the parking lot when his black truck pulls up, and my paranoia starts to flare. Maybe he saw the story online and was outraged. Maybe he's been looking for me.
He strides up to me and gives me a quick hug, patting me stiffly on the back. He steps back and squints at the dingy face of the motel.  "Come on, man. Let's get your stuff."
"Get my stuff?"
"You said you're sober, right? I already talked to the house manager. He'll take you back. We got a bed," he says.
"I'm not going back to the house. I asked you to come here because I... I want to know where that warehouse is. The one downtown."
Shawn turns and looks me in the eye.
I tell him the story. I tell him about Mother Horse Eyes, the Nazis, the CIA, the LSD, the experiments, most of the stuff that I've told you. I leave out some parts, like the fact that he is in the story. That we are in the story. That all of this in the story right now. He listens to me, but his face darkens.
"Listen to me," I say, working myself up to deliver my big speech. "I have lived things which are impossible. Which could not have happened. So have you. Those tunnels, those cages, the bones, none of it should exist. But you saw it. I've seen things too. We have to find out what it is. I lived with that monster for a whole summer. I know she's down there. And I want to find her."
Shawn narrows his eyes as he stares at me. "What's down there is the devil, Nick.
"I want to see her. I want to know. Please," I say to him, my voice breaking.
 And you got character defects. Like me. And everybody else. That's it."
"Don't you want to know what's going on down there? You're not curious? "
"No."
"It doesn't eat at you? You don't need any answers?"
He shakes his head. "God doesn't promise answers. God gave us all the answers we need in the Bible. That's all we get. I don't ask him what's going to happen in the future. I don't do horoscopes. I don't practice witchcraft. God's not going to come down and give me the answers to everything. All he wants from me is obedience."
"Oh, come on. So we shouldn't try to figure things out? We shouldn't ask questions? That's just some anti-intellectual, anti-science bullshit."
When we were roommates and got into disagreements, he would start quoting the Bible at me, and I would start picking at him with snide intellectual arguments, using as many big words as I could. We're falling back into the same dynamic.
"Anti-science?" he says. "Shit, I'm not saying don't be a scientist.
I find myself laughing at this. He smiles with me.
"For real though, man. It's dangerous," he says, the smile fading
I look out across the crumbling parking lot. Long evening shadows are drawn across the asphalt. "Man, I don't know. I just feel like if I could figure out what happened during that summer, then maybe I wouldn't be so fucked up.
"Just let it go."
"No. No, there has to be an ending. There has to be some kind of... pay-off."
"Moses and the people wandered the desert for 40 years looking for the promised land. One day the Lord took him up to a mountaintop and showed him all the promised land, and Moses died right there, without ever setting his foot in the land. Do you know what kind of Lord does that?"
"A messed up one," I muttered.
"The Lord knows that we are generations. Man is of few days. Generations might pass before we get any answers. For the last ten years, I've been living like the world might end any day, but I'm not doing that anymore. I have to remember that we know neither the day nor the hour wherein the Son of man cometh. That's why I'm going back to school and all that."
I nod. Through the course of our little debates, I had told him many times that the world wasn't going to end anytime soon.  Maybe some of it rubbed off on him. Maybe some of it should be rubbing off on me now.
"I need answers," I told him. "I've tried just accepting the mystery and whatever, but at this point I just need to know why I'm all fucked up, why I can't stop drinking, why I can't be normal."
"Man, I could tell you where the warehouse is. But what are you going to do when you go down there? What are you going to do when you meet the devil?"
I haven't told him that part of the story. It's a part that I'm not sure I really believe myself.
"I think... I have been given reason to believe... that whatever is down there... I can destroy it."


Dashboard
Today Revenue
$2189
Product Sold
1200
New Customer
2000
New Visitors
720
Sales By Category
Targets
Notifications
Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Draft the new contract document for sales team
Due on 24 Aug, 2019Overview
121,000
Total Visitors21,000
Total Product Views$21.5
Revenue Per VisitorRevenue
2015 - 2019 © demo theme by Arka Softwares


Gets an X-address in Testnet/Mainnet format.
A tag to be included within the X-address.
A boolean to indicate if X-address should be in Testnet (true) or Mainnet (false) format.
An X-address.
Signs a transaction offline.
A transaction to be signed offline.
Options to include for signing.
A signed transaction.
Verifies a signed transaction offline.
A signed transaction (hex string of signTransaction result) to be verified offline.
Returns true if a signedTransaction is valid.
Derives a wallet from an entropy (array of random numbers).
An array of random numbers to generate a seed used to derive a wallet.
The digital signature algorithm to generate an address for.
A Wallet derived from an entropy.
Derives a wallet from a mnemonic.
A string consisting of words (whitespace delimited) used to derive a wallet.
The path to derive a keypair (publicKey/privateKey) from a seed (that was converted from a mnemonic).
A Wallet derived from a mnemonic.
Derives a wallet from a seed.
A string used to generate a keypair (publicKey/privateKey) to derive a wallet.
The digital signature algorithm to generate an address for.
A Wallet derived from a seed.
Generates a new Wallet using a generated seed.
The digital signature algorithm to generate an address for.
A new Wallet derived from a generated seed.
Generated using TypeDoc
A utility for deriving a wallet composed of a keypair (publicKey/privateKey). A wallet can be derived from either a seed, mnemnoic, or entropy (array of random numbers). It provides functionality to sign/verify transactions offline.


Objectives
This Application replaces certain numbers in the array as shown below.
Numbers divisible by 3 are replaced with "ping".
Numbers divisible by 5 are replaced with "pong" .
Numbers divisible by 15 are replaced with "pingpong"
Play Now
Results


|
2NVIDIA Research |
Multi objective optimization problems are prevalent in machine learning. These problems have a set of optimal solutions, called the Pareto front, where each point on the front represents a different trade-off between possibly conflicting objectives. Recent optimization algorithms can target a specific desired ray in loss space, but still face two grave limitations: (i) A separate model has to be trained
for each point on the front; and (ii) The exact trade-off must be known prior to the optimization process. Here, we tackle the problem of learning the entire Pareto front, with the capability of selecting a desired operating point on the front after training. We call this new setup Pareto-Front Learning (PFL).
We describe an approach to PFL implemented using HyperNetworks, which we term Pareto HyperNetworks (PHNs). PHN learns the entire Pareto front simultaneously using a single hypernetwork, which receives as input a desired preference vector, and returns a Pareto-optimal model whose loss vector is in the desired ray. The unified model is runtime efficient compared to training multiple models, and generalizes to new operating points not used during training. We evaluate our method on a wide set of problems, from multi-task learning, through fairness, to image segmentation with auxiliaries. PHNs learns the entire Pareto front in roughly the same time as learning a single point on the front, and also reaches a better solution set. PFL opens the door to new applications where models are selected based on preferences that are only available at run time.
The goal of Multi-Objective Optimization (MOO) is to find Pareto optimal solutions corresponding to different trade-offs between objectives.
Pareto dominance: Solution A (i.e. model) is said to dominate solution B if it is not worst on all objective, and improves B on at least one objective.
Pareto optimality:A point that is not dominated by any other point is called Pareto optimal.
Pareto front:The set of all Pareto optimal points is called the Pareto front.
In this work, we propose using a single hypernetwok, termed Pareto HyperNetwork (PHN), to learn the entire Pareto front. PHN acts on a preference vector, that represent a desired trade-off between tasks, to produce the weights of a target network. PHN is optimized to output weights that are (i) Pareto optimal, and; (ii) corresponds to the preference vector.
Pareto front (solid line) for 2D loss space and several rays (colored dashed lines) representing various possible preferences. Unlike other approaches that train a model per-ray, a single PHN model converges to the entire Pareto front, mapping any given preference ray to its corresponding solution on the front.
We evaluated PHN using the three Multi-MNIST datasets, a commonly used MOO benchmarks. PHN achives better performance with significantly less training time, compared with baseline methods. The above figure presents the learned Pareto front and corresponding accuracies thought the training process, over the Multi-Fashion + MNIST test set.
Fairness has become a popular topic in machine learning in recent years, and numerous approaches have been proposed for modeling and incorporating fairness into ML systems. Here, we tackle a 3-dimensional optimization problem, with classification objective, and two fairness objectives: False Positive (FP) fairness, and False Negative (FN) fairness. As before, PHN outperform all baselines, in terms of objective space coverage (measured by Hypervolume), with reduuced training time.
PHN learns the entire front in a single model, but the competing methods need to train multiple models to cover the pareto front. As a result, these methods have clear trade off between performance and runtime. We find that PHN can achieve superior overall solutions while being \(10 \sim 50\) times faster.


- 1966 Ford Galaxie XL
- 1966 Ford Galaxie XL (Pro Street)
- 1966 Ford LTD
- 1966 Ford Galaxie 7 Litre convertible
- 1966 Ford Fairlane XL
- 1973 Mercury Montego GT
- Galaxie
-
Ford's full-size car from 1959-1974. Some additional names would be applied in different years, like "Starliner" and "LTD", but mostly they're known as "Galaxie" (note the non-standard spelling).
- LTD
-
In 1966, although the "LTD" was technically a different model, it's really just a Galaxie with "luxury" trim.


{% extends "bank/base.html" %} {% load crispy_forms_tags %} {% block body %}
You should receive a Discord DM from the Democraciv Discord Bot in about 30 seconds with a link to reset your password.
Do not share that link with anyone else.
If you did not connect your Discord Account prior to this, please contact DerJonas#8036 on Discord.


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In this page you will see css animation, transition and transform combine together
Animation
Transition
Transform


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Public bigint amount_cents |
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Public timestamp with time zone(0) archived_at |
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«table» receipts Table «FK» |
Name: receipt_buckets_receipt_id_foreign |
Name: receipts_pkey |
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| Owner | public |
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| isFinalSpecialization: | 0 |