- published: 08 Dec 2021
- views: 2
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remove the playlistBlue On Blue (disambiguation)
- remove the playlistBlue On Blue (disambiguation)
Blue on Blue (Under the Dome)
"Blue on Blue" is the fifth episode of the CBS drama Under the Dome. The episode aired on July 22, 2013. It was after this episode that the series was renewed for a second season on July 29, 2013.
The episode was screened at the 2013 Comic-Con, and was received positively by viewers; and was also well received by most critics. Upon airing, the episode was watched by 11.60 million viewers, with an 18-49 rating of 2.8, presenting an increase in ratings from the previous episode.
Plot
Despite finding Angie in the shelter, Jim leaves her locked up, unable to believe his son would do such a thing. Meanwhile, the military has scheduled a "visitors' day" for the residents of Chester's Mill, where family members and friends of people trapped in the dome can come and visit their loved ones. During the event, Linda tells her fiancé about his brother's death, Norrie meets her estranged biological father (Gary Weeks), who her parents had led her to believe she would never be able to find, and Barbie finds out from a soldier stationed outside the dome that the military plans to attempt to destroy the dome with a missile (MOAB), which will likely kill everyone inside. When Barbie relays this to Big Jim, he orders everyone to take shelter in the tunnels underneath the city. He then releases Angie from her captivity, but when Junior finds out, he sets off after her while everyone else takes shelter in the tunnels.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Blue_on_Blue_(Under_the_Dome)
Friendly fire
Friendly fire is an attack by a military force on friendly forces while attempting to attack the enemy, either by misidentifying the target as hostile, or due to errors or inaccuracy. Fire not intended to attack the enemy, such as negligent discharge and deliberate firing on one's own troops for disciplinary reasons, is not called friendly fire. Nor is unintentional harm to non-combatants or structures, which is sometimes referred to as collateral damage.
Use of the term "friendly" in a military context for allied personnel or materiel dates from the First World War, often for shells falling short. The term friendly fire was originally adopted by the United States military. Many North Atlantic Treaty Organization (NATO) militaries refer to these incidents as blue-on-blue, which derives from military exercises where NATO forces were identified by blue pennants and units representing Warsaw Pact forces by orange pennants.
Addressing friendly fire
Friendly fire is often seen as an inescapable result of combat, and because it accounts for a small percentage (estimated 2% to, rarely as high as, 20%) of casualties, can often be dismissed as irrelevant to the outcome of a battle. The effects of friendly fire, however, are not just material. Troops expect to be targeted by the enemy, but being hit by their own forces has a huge negative impact on morale. Forces doubt the competence of their command, and its prevalence makes commanders more cautious in the field.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Friendly_fire
Blue on blue (disambiguation)
Blue on blue refers to an incidence of friendly fire, an inadvertent firing toward one's own or otherwise friendly forces.
Blue on blue may also refer to:
Music
Television
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Blue_on_blue_(disambiguation)
Blue on Blue (song)
"Blue on Blue" is a popular song composed by Burt Bacharach with lyrics by Hal David, first recorded by Bobby Vinton in 1963. Vinton's single spent 13 weeks on the Billboard Hot 100 chart, peaking at No. 3 on July 6, 1963, while reaching No. 2 on Billboard's Middle-Road Singles chart. Vinton's single was a major hit in many other nations as well.
The success of "Blue on Blue" prompted Vinton to record an entire album of blue-themed songs, also titled Blue on Blue, which produced an even bigger hit in the No. 1 "Blue Velvet".
Chart performance
Cover versions
"Blue on Blue" has been recorded by Paul Anka (1963), Percy Faith (1964), Maureen McGovern (1991), and many others. Samples of a cover version of the song by Gals and Pals from 1966 were included Röyksopp's song 'So Easy'. "Blue on Blue" was also covered by Say Lou Lou in 2015 and used in commercials for the Swedish clothing company Gina Tricot.
References
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Blue_on_Blue_(song)
Podcasts:
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Afro Blue (disambiguation)
Afro Blue is a composition by Mongo Santamaría. Afro Blue may also refer to: Afro Blue (Dee Dee Bridgewater album) Afro Blue (Harold Mabern album) Afro Blue (McCoy Tyner album) Afro Blue (choir), a Howard University jazz ensemble Source: https://en.wikipedia.org/wiki/Afro_Blue_(disambiguation) Created with WikipediaReaderReborn (c) WikipediaReader
published: 08 Dec 2021 -
These Statues Have Hidden Bodies 🗿😱 (Moai)
published: 23 Jun 2022 -
Blue Riband (disambiguation) Top # 10 Facts
Blue Riband (disambiguation) Top # 10 Facts
published: 02 Nov 2015 -
Top 10 Episodes That Killed TV Shows
Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at the most infamous episodes of television that damaged their show’s reputation. It goes without saying, but beware of major spoilers ahead. Our countdown includes episodes from "Homeland", "Grey's Anatomy", "Dexter" and more! Did you soldier on after these episodes? Let us know in the comments below! Check out these other tv show themed videos: Top 20 Most Shocking Sitcom Moments: https://youtu.be/YdnHPOp1Ydk Top 20 TV Plot Twists of the Century (So Far): https://youtu.be/QFC8n7u7olk Top 20 Banned TV Episodes: https://youtu.be/i2Ba1p7OARM Become a channel member to get access to special perks: https://www.youtube.com/channel/UCaWd5_7JhbQBe4dknZhsHJg/join Challenge friends and family on our multiplaye...
published: 18 Apr 2023 -
Adjusting sense representations for knowledge-based word sense disambiguation
Speaker: Tristan Miller, Technische Universität Darmstadt (Germany) Abstract: Word sense disambiguation (WSD) – the task of determining which meaning a word carries in a particular context – is a core research problem in computational linguistics. Though it has long been recognized that supervised (i.e., machine learning–based) approaches to WSD can yield impressive results, they require an amount of manually annotated training data that is often too expensive or impractical to obtain. This is a particular problem for under-resourced languages and text domains, and is also a hurdle in well-resourced languages when processing the sort of lexical-semantic anomalies employed for deliberate effect in humour and wordplay. In contrast to supervised systems are knowledge-based techniques, whi...
published: 31 May 2017 -
Mod-01 Lec-30 Wordnet and Word Sense Disambiguation(contd...)
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
published: 03 Jul 2012 -
NWDS Talk - Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Presented by Laurel Orr See more Northwest Database Society talks here: http://db.cs.washington.edu/nwds/nwds.html Abstract: Named Entity Disambiguation (NED) is the task of mapping textual mentions to entities in a database. A key challenge in NED is generalizing to rarely seen entities, termed tail entities. Traditional NED systems use hand-tuned features to improve tail generalization, but these features make the system challenging to deploy and maintain. In 2018, a subset of the authors built and deployed a self-supervised NED system at a major technology company, which improved performance over its hand-tuned predecessor. Motivated to understand the core reasons for this improvement, we introduce Bootleg, a clean-slate, open-source, self-supervised NED system. In this talk, w...
published: 12 Feb 2021 -
Top 10 Worst Final Seasons of TV Shows
These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be looking at beloved TV shows that went out on sour notes. Even if a show received a revival some time later, we still considered it here. Since we’re discussing final plot points, a massive spoiler warning is in effect. Our countdown of the worst final seasons includes “Game of Thrones” (2011-19): Season 8, “That ‘70s Show” (1998-2006): Season 8, “Roseanne” (1988-1997): Season 9, “Heroes” (2006-10): Season 4, and more! Which of these final seasons upset you the most? Are there any that you think get more hate than they deserve? Share your thoughts in the comments! Watch more great TV videos here: Top 10 Shows Cancelled Before Their First Season Ended: https://youtu.be/IcPsE4vS35Y Top 10 Episodes That K...
published: 10 May 2023 -
Whale (disambiguation)Whale" Cthulhu Regio on Pluto, unofficially called Whale Whale
Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungulates). They are related to the Indohyus, an extinct chevrotain-like ungulate, from which they split approximately 48 million years ago.[21][22] Primitive cetaceans, or archaeocetes, first took to the sea approximately 49 million years ago and became fully aquatic 5–10 million years later. What defines an archaeocete is the presence of anatomical features exclusive to cetaceans, alongside other primitive features not found in modern cetaceans, such as visible legs or asymmetrical teeth.[23][24][25][11] Their features became adapted for living in the marine environment. Major anatomical changes included their hearing set-up that channeled vibrations from the jaw to the earbone (Ambulocetus 49 mya), a str...
published: 09 Mar 2023 -
Wikipedia:Disambiguation Top # 9 Facts
Wikipedia:Disambiguation Top # 9 Facts
published: 31 Oct 2015
developed with YouTube
0:23
Afro Blue (disambiguation)
- Order: Reorder
- Duration: 0:23
- Uploaded Date: 08 Dec 2021
- views: 2
Afro Blue is a composition by Mongo Santamaría.
Afro Blue may also refer to:
Afro Blue (Dee Dee Bridgewater album)
Afro Blue (Harold Mabern album)
Afro Blue (M...
Afro Blue is a composition by Mongo Santamaría.
Afro Blue may also refer to:
Afro Blue (Dee Dee Bridgewater album)
Afro Blue (Harold Mabern album)
Afro Blue (McCoy Tyner album)
Afro Blue (choir), a Howard University jazz ensemble
Source: https://en.wikipedia.org/wiki/Afro_Blue_(disambiguation)
Created with WikipediaReaderReborn (c) WikipediaReader
https://wn.com/Afro_Blue_(Disambiguation)
Afro Blue is a composition by Mongo Santamaría.
Afro Blue may also refer to:
Afro Blue (Dee Dee Bridgewater album)
Afro Blue (Harold Mabern album)
Afro Blue (McCoy Tyner album)
Afro Blue (choir), a Howard University jazz ensemble
Source: https://en.wikipedia.org/wiki/Afro_Blue_(disambiguation)
Created with WikipediaReaderReborn (c) WikipediaReader
0:22
These Statues Have Hidden Bodies 🗿😱 (Moai)
- Order: Reorder
- Duration: 0:22
- Uploaded Date: 23 Jun 2022
- views: 9027282
- published: 23 Jun 2022
- views: 9027282
1:21
Blue Riband (disambiguation) Top # 10 Facts
- Order: Reorder
- Duration: 1:21
- Uploaded Date: 02 Nov 2015
- views: 4
Blue Riband (disambiguation) Top # 10 Facts
Blue Riband (disambiguation) Top # 10 Facts
https://wn.com/Blue_Riband_(Disambiguation)_Top_10_Facts
Blue Riband (disambiguation) Top # 10 Facts
- published: 02 Nov 2015
- views: 4
11:06
Top 10 Episodes That Killed TV Shows
- Order: Reorder
- Duration: 11:06
- Uploaded Date: 18 Apr 2023
- views: 354402
Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at the most infamous episodes of television that damaged their show’s reput...
Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at the most infamous episodes of television that damaged their show’s reputation. It goes without saying, but beware of major spoilers ahead. Our countdown includes episodes from "Homeland", "Grey's Anatomy", "Dexter" and more! Did you soldier on after these episodes? Let us know in the comments below!
Check out these other tv show themed videos:
Top 20 Most Shocking Sitcom Moments: https://youtu.be/YdnHPOp1Ydk
Top 20 TV Plot Twists of the Century (So Far): https://youtu.be/QFC8n7u7olk
Top 20 Banned TV Episodes: https://youtu.be/i2Ba1p7OARM
Become a channel member to get access to special perks:
https://www.youtube.com/channel/UCaWd5_7JhbQBe4dknZhsHJg/join
Challenge friends and family on our multiplayer Trivia!
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#tvshows #episodes #worst #walkingdead #sherlock #dexter #homeland
https://wn.com/Top_10_Episodes_That_Killed_Tv_Shows
Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at the most infamous episodes of television that damaged their show’s reputation. It goes without saying, but beware of major spoilers ahead. Our countdown includes episodes from "Homeland", "Grey's Anatomy", "Dexter" and more! Did you soldier on after these episodes? Let us know in the comments below!
Check out these other tv show themed videos:
Top 20 Most Shocking Sitcom Moments: https://youtu.be/YdnHPOp1Ydk
Top 20 TV Plot Twists of the Century (So Far): https://youtu.be/QFC8n7u7olk
Top 20 Banned TV Episodes: https://youtu.be/i2Ba1p7OARM
Become a channel member to get access to special perks:
https://www.youtube.com/channel/UCaWd5_7JhbQBe4dknZhsHJg/join
Challenge friends and family on our multiplayer Trivia!
https://www.watchmojo.com/play/id/62969
Have your idea become a video!
https://wmojo.com/suggest
Subscribe for more great content!
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Visit our shop for awesome merch!
https://shop.watchmojo.com/
Your trusted authority for Top 10 lists, reviews, tips and tricks, biographies, origins, and entertainment news
#tvshows #episodes #worst #walkingdead #sherlock #dexter #homeland
- published: 18 Apr 2023
- views: 354402
1:02:07
Adjusting sense representations for knowledge-based word sense disambiguation
- Order: Reorder
- Duration: 1:02:07
- Uploaded Date: 31 May 2017
- views: 454
Speaker: Tristan Miller, Technische Universität Darmstadt (Germany)
Abstract: Word sense disambiguation (WSD) – the task of determining which meaning a word ca...
Speaker: Tristan Miller, Technische Universität Darmstadt (Germany)
Abstract: Word sense disambiguation (WSD) – the task of determining which meaning a word carries in a particular context – is a core research problem in computational linguistics. Though it has long been recognized that supervised (i.e., machine learning–based) approaches to WSD can yield impressive results, they require an amount of manually annotated training data that is often too expensive or impractical to obtain. This is a particular problem for under-resourced languages and text domains, and is also a hurdle in well-resourced languages when processing the sort of lexical-semantic anomalies employed for deliberate effect in humour and wordplay. In contrast to supervised systems are knowledge-based techniques, which rely only on pre-existing lexical-semantic resources (LSRs) such as dictionaries and thesauri. These techniques are of more general applicability but tend to suffer from lower performance due to the informational gap between the target word's context and the sense descriptions provided by the LSR. In this seminar, we treat the task of extending the efficacy and applicability of knowledge-based WSD, both generally and for the particular case of English puns. In the first part of the talk, we present two approaches for bridging the information gap and thereby improving WSD coverage and accuracy. In the first approach, we supplement the word's context and the LSR's sense descriptions with entries from a distributional thesaurus. The second approach enriches an LSR's sense information by aligning it to other, complementary LSRs. In the second part of the talk, we describe how these techniques, along with evaluation methodologies from traditional WSD, can be adapted for the "disambiguation" of puns, or rather for the automatic identification of their double meanings.
https://wn.com/Adjusting_Sense_Representations_For_Knowledge_Based_Word_Sense_Disambiguation
Speaker: Tristan Miller, Technische Universität Darmstadt (Germany)
Abstract: Word sense disambiguation (WSD) – the task of determining which meaning a word carries in a particular context – is a core research problem in computational linguistics. Though it has long been recognized that supervised (i.e., machine learning–based) approaches to WSD can yield impressive results, they require an amount of manually annotated training data that is often too expensive or impractical to obtain. This is a particular problem for under-resourced languages and text domains, and is also a hurdle in well-resourced languages when processing the sort of lexical-semantic anomalies employed for deliberate effect in humour and wordplay. In contrast to supervised systems are knowledge-based techniques, which rely only on pre-existing lexical-semantic resources (LSRs) such as dictionaries and thesauri. These techniques are of more general applicability but tend to suffer from lower performance due to the informational gap between the target word's context and the sense descriptions provided by the LSR. In this seminar, we treat the task of extending the efficacy and applicability of knowledge-based WSD, both generally and for the particular case of English puns. In the first part of the talk, we present two approaches for bridging the information gap and thereby improving WSD coverage and accuracy. In the first approach, we supplement the word's context and the LSR's sense descriptions with entries from a distributional thesaurus. The second approach enriches an LSR's sense information by aligning it to other, complementary LSRs. In the second part of the talk, we describe how these techniques, along with evaluation methodologies from traditional WSD, can be adapted for the "disambiguation" of puns, or rather for the automatic identification of their double meanings.
- published: 31 May 2017
- views: 454
47:23
Mod-01 Lec-30 Wordnet and Word Sense Disambiguation(contd...)
- Order: Reorder
- Duration: 47:23
- Uploaded Date: 03 Jul 2012
- views: 4659
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
https://wn.com/Mod_01_Lec_30_Wordnet_And_Word_Sense_Disambiguation(Contd...)
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 4659
1:02:06
NWDS Talk - Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
- Order: Reorder
- Duration: 1:02:06
- Uploaded Date: 12 Feb 2021
- views: 121
Presented by Laurel Orr
See more Northwest Database Society talks here:
http://db.cs.washington.edu/nwds/nwds.html
Abstract:
Named Entity Disambiguatio...
Presented by Laurel Orr
See more Northwest Database Society talks here:
http://db.cs.washington.edu/nwds/nwds.html
Abstract:
Named Entity Disambiguation (NED) is the task of mapping textual mentions to entities in a database. A key challenge in NED is generalizing to rarely seen entities, termed tail entities. Traditional NED systems use hand-tuned features to improve tail generalization, but these features make the system challenging to deploy and maintain. In 2018, a subset of the authors built and deployed a self-supervised NED system at a major technology company, which improved performance over its hand-tuned predecessor. Motivated to understand the core reasons for this improvement, we introduce Bootleg, a clean-slate, open-source, self-supervised NED system. In this talk, we'll show how to succeed on the tail by reasoning over structured data. We demonstrate that Bootleg matches or exceeds state-of-the-art performance on three NED benchmarks and that the learned representations from Bootleg demonstrate up to 8% performance lift in a production task. Finally, we observe that embeddings from self-supervised models like Bootleg are increasingly being served to downstream applications, creating an embedding ecosystem. We initiate the study of the data management challenges associated with this ecosystem.
https://wn.com/Nwds_Talk_Bootleg_Chasing_The_Tail_With_Self_Supervised_Named_Entity_Disambiguation
Presented by Laurel Orr
See more Northwest Database Society talks here:
http://db.cs.washington.edu/nwds/nwds.html
Abstract:
Named Entity Disambiguation (NED) is the task of mapping textual mentions to entities in a database. A key challenge in NED is generalizing to rarely seen entities, termed tail entities. Traditional NED systems use hand-tuned features to improve tail generalization, but these features make the system challenging to deploy and maintain. In 2018, a subset of the authors built and deployed a self-supervised NED system at a major technology company, which improved performance over its hand-tuned predecessor. Motivated to understand the core reasons for this improvement, we introduce Bootleg, a clean-slate, open-source, self-supervised NED system. In this talk, we'll show how to succeed on the tail by reasoning over structured data. We demonstrate that Bootleg matches or exceeds state-of-the-art performance on three NED benchmarks and that the learned representations from Bootleg demonstrate up to 8% performance lift in a production task. Finally, we observe that embeddings from self-supervised models like Bootleg are increasingly being served to downstream applications, creating an embedding ecosystem. We initiate the study of the data management challenges associated with this ecosystem.
- published: 12 Feb 2021
- views: 121
11:12
Top 10 Worst Final Seasons of TV Shows
- Order: Reorder
- Duration: 11:12
- Uploaded Date: 10 May 2023
- views: 725284
These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be looking at beloved TV shows that went out on sour notes. Even if a show...
These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be looking at beloved TV shows that went out on sour notes. Even if a show received a revival some time later, we still considered it here. Since we’re discussing final plot points, a massive spoiler warning is in effect. Our countdown of the worst final seasons includes “Game of Thrones” (2011-19): Season 8, “That ‘70s Show” (1998-2006): Season 8, “Roseanne” (1988-1997): Season 9, “Heroes” (2006-10): Season 4, and more! Which of these final seasons upset you the most? Are there any that you think get more hate than they deserve? Share your thoughts in the comments!
Watch more great TV videos here:
Top 10 Shows Cancelled Before Their First Season Ended: https://youtu.be/IcPsE4vS35Y
Top 10 Episodes That Killed TV Shows: https://youtu.be/pI-2R_T8AfI
Top 10 TV Show Finale Happy Endings: https://youtu.be/Fu1Q7Chs3-g
Become a channel member to get access to special perks:
https://www.youtube.com/channel/UCaWd5_7JhbQBe4dknZhsHJg/join
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#TV #Series #Drama #GameofThrones #Streaming #Comedy #Sitcom #Fantasy #SciFi #Television
https://wn.com/Top_10_Worst_Final_Seasons_Of_Tv_Shows
These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be looking at beloved TV shows that went out on sour notes. Even if a show received a revival some time later, we still considered it here. Since we’re discussing final plot points, a massive spoiler warning is in effect. Our countdown of the worst final seasons includes “Game of Thrones” (2011-19): Season 8, “That ‘70s Show” (1998-2006): Season 8, “Roseanne” (1988-1997): Season 9, “Heroes” (2006-10): Season 4, and more! Which of these final seasons upset you the most? Are there any that you think get more hate than they deserve? Share your thoughts in the comments!
Watch more great TV videos here:
Top 10 Shows Cancelled Before Their First Season Ended: https://youtu.be/IcPsE4vS35Y
Top 10 Episodes That Killed TV Shows: https://youtu.be/pI-2R_T8AfI
Top 10 TV Show Finale Happy Endings: https://youtu.be/Fu1Q7Chs3-g
Become a channel member to get access to special perks:
https://www.youtube.com/channel/UCaWd5_7JhbQBe4dknZhsHJg/join
Challenge friends and family on our multiplayer Trivia!
https://www.watchmojo.com/play/id/63514
Have your idea become a video!
https://wmojo.com/suggest
Subscribe for more great content!
https://wmojo.com/watchmojo-subscribe
Visit our shop for awesome merch!
https://shop.watchmojo.com/
Your trusted authority for Top 10 lists, reviews, tips and tricks, biographies, origins, and entertainment news
#TV #Series #Drama #GameofThrones #Streaming #Comedy #Sitcom #Fantasy #SciFi #Television
- published: 10 May 2023
- views: 725284
0:11
Whale (disambiguation)Whale" Cthulhu Regio on Pluto, unofficially called Whale Whale
- Order: Reorder
- Duration: 0:11
- Uploaded Date: 09 Mar 2023
- views: 31
Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungulates). They are related to the Indohyus, an extinct chevrotain-like ung...
Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungulates). They are related to the Indohyus, an extinct chevrotain-like ungulate, from which they split approximately 48 million years ago.[21][22] Primitive cetaceans, or archaeocetes, first took to the sea approximately 49 million years ago and became fully aquatic 5–10 million years later. What defines an archaeocete is the presence of anatomical features exclusive to cetaceans, alongside other primitive features not found in modern cetaceans, such as visible legs or asymmetrical teeth.[23][24][25][11] Their features became adapted for living in the marine environment. Major anatomical changes included their hearing set-up that channeled vibrations from the jaw to the earbone (Ambulocetus 49 mya), a streamlined body and the growth of flukes on the tail (Protocetus 43 mya), the migration of the nostrils toward the top of the cranium (blowholes), and the modification of the forelimbs into flippers (Basilosaurus 35 mya), and the shrinking and eventual disappearance of the hind limbs (the first odontocetes and mysticetes 34 mya).[26][27][28]
Whale morphology shows several examples of convergent evolution, the most obvious being the streamlined fish-like body shape.[29] Other examples include the use of echolocation for hunting in low light conditions — which is the same hearing adaptation used by bats — and, in the rorqual whales, jaw adaptations, similar to those found in pelicans, that enable engulfment feeding.[30]
Today, the closest living relatives of cetaceans are the hippopotamuses; these share a semi-aquatic ancestor that branched off from other artiodactyls some 60 mya.[11] Around 40 mya, a common ancestor between the two branched off into cetacea and anthracotheres; nearly all anthracotheres became extinct at the end of the Pleistocene 2.5 mya, eventually leaving only one surviving lineage – the hippopotamus.[31]
Whales split into two separate parvorders around 34 mya – the baleen whales (Mysticetes) and the toothed whales (Odontocetes).[32][33][34]Whales have torpedo-shaped bodies with non-flexible necks, limbs modified into flippers, non-existent external ear flaps, a large tail fin, and flat heads (with the exception of monodontids and ziphiids). Whale skulls have small eye orbits, long snouts (with the exception of monodontids and ziphiids) and eyes placed on the sides of its head. Whales range in size from the 2.6-metre (8.5 ft) and 135-kilogram (298 lb) dwarf sperm whale to the 34-metre (112 ft) and 190-metric-ton (210-short-ton) blue whale. Overall, they tend to dwarf other cetartiodactyls; the blue whale is the largest creature on Earth. Several species have female-biased sexual dimorphism, with the females being larger than the males. One exception is with the sperm whale, which has males larger than the females.[35][36]
Odontocetes, such as the sperm whale, possess teeth with cementum cells overlying dentine cells. Unlike human teeth, which are composed mostly of enamel on the portion of the tooth outside of the gum, whale teeth have cementum outside the gum. Only in larger whales, where the cementum is worn away on the tip of the tooth, does enamel show. Mysticetes have large whalebone, as opposed to teeth, made of keratin. Mysticetes have two blowholes, whereas Odontocetes contain only one.[37]
Breathing involves expelling stale air from the blowhole, forming an upward, steamy spout, followed by inhaling fresh air into the lungs; a humpback whale's lungs can hold about 5,000 litres (1,300 US gal) of air. Spout shapes differ among species, which facilitates identification.[38][39]
All whales have a thick layer of blubber. In species that live near the poles, the blubber can be as thick as 11 inches (28 cm). This blubber can help with buoyancy (which is helpful for a 100-ton whale), protection to some extent as predators would have a hard time getting through a thick layer of fat, and energy for fasting when migrating to the equator; the primary usage for blubber is insulation from the harsh climate. It can constitute as much as 50% of a whale's body weight. Calves are born with only a thin layer of blubber, but some species compensate for this with thick lanugos.[40][41]
Whales have a two- to three-chambered stomach that is similar in structure to those of terrestrial carnivores. Mysticetes contain a proventriculus as an extension of the oesophagus; this contains stones that grind up food. They also have fundic and pyloric chambers.[42]
https://wn.com/Whale_(Disambiguation)Whale_Cthulhu_Regio_On_Pluto,_Unofficially_Called_Whale_Whale
Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungulates). They are related to the Indohyus, an extinct chevrotain-like ungulate, from which they split approximately 48 million years ago.[21][22] Primitive cetaceans, or archaeocetes, first took to the sea approximately 49 million years ago and became fully aquatic 5–10 million years later. What defines an archaeocete is the presence of anatomical features exclusive to cetaceans, alongside other primitive features not found in modern cetaceans, such as visible legs or asymmetrical teeth.[23][24][25][11] Their features became adapted for living in the marine environment. Major anatomical changes included their hearing set-up that channeled vibrations from the jaw to the earbone (Ambulocetus 49 mya), a streamlined body and the growth of flukes on the tail (Protocetus 43 mya), the migration of the nostrils toward the top of the cranium (blowholes), and the modification of the forelimbs into flippers (Basilosaurus 35 mya), and the shrinking and eventual disappearance of the hind limbs (the first odontocetes and mysticetes 34 mya).[26][27][28]
Whale morphology shows several examples of convergent evolution, the most obvious being the streamlined fish-like body shape.[29] Other examples include the use of echolocation for hunting in low light conditions — which is the same hearing adaptation used by bats — and, in the rorqual whales, jaw adaptations, similar to those found in pelicans, that enable engulfment feeding.[30]
Today, the closest living relatives of cetaceans are the hippopotamuses; these share a semi-aquatic ancestor that branched off from other artiodactyls some 60 mya.[11] Around 40 mya, a common ancestor between the two branched off into cetacea and anthracotheres; nearly all anthracotheres became extinct at the end of the Pleistocene 2.5 mya, eventually leaving only one surviving lineage – the hippopotamus.[31]
Whales split into two separate parvorders around 34 mya – the baleen whales (Mysticetes) and the toothed whales (Odontocetes).[32][33][34]Whales have torpedo-shaped bodies with non-flexible necks, limbs modified into flippers, non-existent external ear flaps, a large tail fin, and flat heads (with the exception of monodontids and ziphiids). Whale skulls have small eye orbits, long snouts (with the exception of monodontids and ziphiids) and eyes placed on the sides of its head. Whales range in size from the 2.6-metre (8.5 ft) and 135-kilogram (298 lb) dwarf sperm whale to the 34-metre (112 ft) and 190-metric-ton (210-short-ton) blue whale. Overall, they tend to dwarf other cetartiodactyls; the blue whale is the largest creature on Earth. Several species have female-biased sexual dimorphism, with the females being larger than the males. One exception is with the sperm whale, which has males larger than the females.[35][36]
Odontocetes, such as the sperm whale, possess teeth with cementum cells overlying dentine cells. Unlike human teeth, which are composed mostly of enamel on the portion of the tooth outside of the gum, whale teeth have cementum outside the gum. Only in larger whales, where the cementum is worn away on the tip of the tooth, does enamel show. Mysticetes have large whalebone, as opposed to teeth, made of keratin. Mysticetes have two blowholes, whereas Odontocetes contain only one.[37]
Breathing involves expelling stale air from the blowhole, forming an upward, steamy spout, followed by inhaling fresh air into the lungs; a humpback whale's lungs can hold about 5,000 litres (1,300 US gal) of air. Spout shapes differ among species, which facilitates identification.[38][39]
All whales have a thick layer of blubber. In species that live near the poles, the blubber can be as thick as 11 inches (28 cm). This blubber can help with buoyancy (which is helpful for a 100-ton whale), protection to some extent as predators would have a hard time getting through a thick layer of fat, and energy for fasting when migrating to the equator; the primary usage for blubber is insulation from the harsh climate. It can constitute as much as 50% of a whale's body weight. Calves are born with only a thin layer of blubber, but some species compensate for this with thick lanugos.[40][41]
Whales have a two- to three-chambered stomach that is similar in structure to those of terrestrial carnivores. Mysticetes contain a proventriculus as an extension of the oesophagus; this contains stones that grind up food. They also have fundic and pyloric chambers.[42]
- published: 09 Mar 2023
- views: 31
1:13
Wikipedia:Disambiguation Top # 9 Facts
- Order: Reorder
- Duration: 1:13
- Uploaded Date: 31 Oct 2015
- views: 198
Wikipedia:Disambiguation Top # 9 Facts
Wikipedia:Disambiguation Top # 9 Facts
https://wn.com/Wikipedia_Disambiguation_Top_9_Facts
Wikipedia:Disambiguation Top # 9 Facts
- published: 31 Oct 2015
- views: 198
0:23
Afro Blue (disambiguation)
Afro Blue is a composition by Mongo Santamaría.
Afro Blue may also refer to:
Afro Blue (D...
published: 08 Dec 2021
Afro Blue (disambiguation)
Afro Blue (disambiguation)
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Afro Blue is a composition by Mongo Santamaría.
Afro Blue may also refer to:
Afro Blue (Dee Dee Bridgewater album)
Afro Blue (Harold Mabern album)
Afro Blue (McCoy Tyner album)
Afro Blue (choir), a Howard University jazz ensemble
Source: https://en.wikipedia.org/wiki/Afro_Blue_(disambiguation)
Created with WikipediaReaderReborn (c) WikipediaReader
0:22
These Statues Have Hidden Bodies 🗿😱 (Moai)
published: 23 Jun 2022
These Statues Have Hidden Bodies 🗿😱 (Moai)
These Statues Have Hidden Bodies 🗿😱 (Moai)
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- published: 23 Jun 2022
- views: 9027282
1:21
Blue Riband (disambiguation) Top # 10 Facts
Blue Riband (disambiguation) Top # 10 Facts
published: 02 Nov 2015
Blue Riband (disambiguation) Top # 10 Facts
Blue Riband (disambiguation) Top # 10 Facts
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Blue Riband (disambiguation) Top # 10 Facts
11:06
Top 10 Episodes That Killed TV Shows
Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at th...
published: 18 Apr 2023
Top 10 Episodes That Killed TV Shows
Top 10 Episodes That Killed TV Shows
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Sometimes, TV writers just seem to run out of ideas! For this list, we’ll be looking at the most infamous episodes of television that damaged their show’s reputation. It goes without saying, but beware of major spoilers ahead. Our countdown includes episodes from "Homeland", "Grey's Anatomy", "Dexter" and more! Did you soldier on after these episodes? Let us know in the comments below!
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Top 20 Most Shocking Sitcom Moments: https://youtu.be/YdnHPOp1Ydk
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Top 20 Banned TV Episodes: https://youtu.be/i2Ba1p7OARM
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1:02:07
Adjusting sense representations for knowledge-based word sense disambiguation
Speaker: Tristan Miller, Technische Universität Darmstadt (Germany)
Abstract: Word sense ...
published: 31 May 2017
Adjusting sense representations for knowledge-based word sense disambiguation
Adjusting sense representations for knowledge-based word sense disambiguation
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- published: 31 May 2017
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Speaker: Tristan Miller, Technische Universität Darmstadt (Germany)
Abstract: Word sense disambiguation (WSD) – the task of determining which meaning a word carries in a particular context – is a core research problem in computational linguistics. Though it has long been recognized that supervised (i.e., machine learning–based) approaches to WSD can yield impressive results, they require an amount of manually annotated training data that is often too expensive or impractical to obtain. This is a particular problem for under-resourced languages and text domains, and is also a hurdle in well-resourced languages when processing the sort of lexical-semantic anomalies employed for deliberate effect in humour and wordplay. In contrast to supervised systems are knowledge-based techniques, which rely only on pre-existing lexical-semantic resources (LSRs) such as dictionaries and thesauri. These techniques are of more general applicability but tend to suffer from lower performance due to the informational gap between the target word's context and the sense descriptions provided by the LSR. In this seminar, we treat the task of extending the efficacy and applicability of knowledge-based WSD, both generally and for the particular case of English puns. In the first part of the talk, we present two approaches for bridging the information gap and thereby improving WSD coverage and accuracy. In the first approach, we supplement the word's context and the LSR's sense descriptions with entries from a distributional thesaurus. The second approach enriches an LSR's sense information by aligning it to other, complementary LSRs. In the second part of the talk, we describe how these techniques, along with evaluation methodologies from traditional WSD, can be adapted for the "disambiguation" of puns, or rather for the automatic identification of their double meanings.
47:23
Mod-01 Lec-30 Wordnet and Word Sense Disambiguation(contd...)
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...
published: 03 Jul 2012
Mod-01 Lec-30 Wordnet and Word Sense Disambiguation(contd...)
Mod-01 Lec-30 Wordnet and Word Sense Disambiguation(contd...)
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- published: 03 Jul 2012
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Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
1:02:06
NWDS Talk - Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Presented by Laurel Orr
See more Northwest Database Society talks here:
http://db.cs.w...
published: 12 Feb 2021
NWDS Talk - Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
NWDS Talk - Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
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- published: 12 Feb 2021
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Presented by Laurel Orr
See more Northwest Database Society talks here:
http://db.cs.washington.edu/nwds/nwds.html
Abstract:
Named Entity Disambiguation (NED) is the task of mapping textual mentions to entities in a database. A key challenge in NED is generalizing to rarely seen entities, termed tail entities. Traditional NED systems use hand-tuned features to improve tail generalization, but these features make the system challenging to deploy and maintain. In 2018, a subset of the authors built and deployed a self-supervised NED system at a major technology company, which improved performance over its hand-tuned predecessor. Motivated to understand the core reasons for this improvement, we introduce Bootleg, a clean-slate, open-source, self-supervised NED system. In this talk, we'll show how to succeed on the tail by reasoning over structured data. We demonstrate that Bootleg matches or exceeds state-of-the-art performance on three NED benchmarks and that the learned representations from Bootleg demonstrate up to 8% performance lift in a production task. Finally, we observe that embeddings from self-supervised models like Bootleg are increasingly being served to downstream applications, creating an embedding ecosystem. We initiate the study of the data management challenges associated with this ecosystem.
11:12
Top 10 Worst Final Seasons of TV Shows
These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be l...
published: 10 May 2023
Top 10 Worst Final Seasons of TV Shows
Top 10 Worst Final Seasons of TV Shows
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These TV shows disappointing fans thanks to awful final seasons. For this list, we’ll be looking at beloved TV shows that went out on sour notes. Even if a show received a revival some time later, we still considered it here. Since we’re discussing final plot points, a massive spoiler warning is in effect. Our countdown of the worst final seasons includes “Game of Thrones” (2011-19): Season 8, “That ‘70s Show” (1998-2006): Season 8, “Roseanne” (1988-1997): Season 9, “Heroes” (2006-10): Season 4, and more! Which of these final seasons upset you the most? Are there any that you think get more hate than they deserve? Share your thoughts in the comments!
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0:11
Whale (disambiguation)Whale" Cthulhu Regio on Pluto, unofficially called Whale Whale
Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungula...
published: 09 Mar 2023
Whale (disambiguation)Whale" Cthulhu Regio on Pluto, unofficially called Whale Whale
Whale (disambiguation)Whale" Cthulhu Regio on Pluto, unofficially called Whale Whale
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Whales are descendants of land-dwelling mammals of the artiodactyl order (even-toed ungulates). They are related to the Indohyus, an extinct chevrotain-like ungulate, from which they split approximately 48 million years ago.[21][22] Primitive cetaceans, or archaeocetes, first took to the sea approximately 49 million years ago and became fully aquatic 5–10 million years later. What defines an archaeocete is the presence of anatomical features exclusive to cetaceans, alongside other primitive features not found in modern cetaceans, such as visible legs or asymmetrical teeth.[23][24][25][11] Their features became adapted for living in the marine environment. Major anatomical changes included their hearing set-up that channeled vibrations from the jaw to the earbone (Ambulocetus 49 mya), a streamlined body and the growth of flukes on the tail (Protocetus 43 mya), the migration of the nostrils toward the top of the cranium (blowholes), and the modification of the forelimbs into flippers (Basilosaurus 35 mya), and the shrinking and eventual disappearance of the hind limbs (the first odontocetes and mysticetes 34 mya).[26][27][28]
Whale morphology shows several examples of convergent evolution, the most obvious being the streamlined fish-like body shape.[29] Other examples include the use of echolocation for hunting in low light conditions — which is the same hearing adaptation used by bats — and, in the rorqual whales, jaw adaptations, similar to those found in pelicans, that enable engulfment feeding.[30]
Today, the closest living relatives of cetaceans are the hippopotamuses; these share a semi-aquatic ancestor that branched off from other artiodactyls some 60 mya.[11] Around 40 mya, a common ancestor between the two branched off into cetacea and anthracotheres; nearly all anthracotheres became extinct at the end of the Pleistocene 2.5 mya, eventually leaving only one surviving lineage – the hippopotamus.[31]
Whales split into two separate parvorders around 34 mya – the baleen whales (Mysticetes) and the toothed whales (Odontocetes).[32][33][34]Whales have torpedo-shaped bodies with non-flexible necks, limbs modified into flippers, non-existent external ear flaps, a large tail fin, and flat heads (with the exception of monodontids and ziphiids). Whale skulls have small eye orbits, long snouts (with the exception of monodontids and ziphiids) and eyes placed on the sides of its head. Whales range in size from the 2.6-metre (8.5 ft) and 135-kilogram (298 lb) dwarf sperm whale to the 34-metre (112 ft) and 190-metric-ton (210-short-ton) blue whale. Overall, they tend to dwarf other cetartiodactyls; the blue whale is the largest creature on Earth. Several species have female-biased sexual dimorphism, with the females being larger than the males. One exception is with the sperm whale, which has males larger than the females.[35][36]
Odontocetes, such as the sperm whale, possess teeth with cementum cells overlying dentine cells. Unlike human teeth, which are composed mostly of enamel on the portion of the tooth outside of the gum, whale teeth have cementum outside the gum. Only in larger whales, where the cementum is worn away on the tip of the tooth, does enamel show. Mysticetes have large whalebone, as opposed to teeth, made of keratin. Mysticetes have two blowholes, whereas Odontocetes contain only one.[37]
Breathing involves expelling stale air from the blowhole, forming an upward, steamy spout, followed by inhaling fresh air into the lungs; a humpback whale's lungs can hold about 5,000 litres (1,300 US gal) of air. Spout shapes differ among species, which facilitates identification.[38][39]
All whales have a thick layer of blubber. In species that live near the poles, the blubber can be as thick as 11 inches (28 cm). This blubber can help with buoyancy (which is helpful for a 100-ton whale), protection to some extent as predators would have a hard time getting through a thick layer of fat, and energy for fasting when migrating to the equator; the primary usage for blubber is insulation from the harsh climate. It can constitute as much as 50% of a whale's body weight. Calves are born with only a thin layer of blubber, but some species compensate for this with thick lanugos.[40][41]
Whales have a two- to three-chambered stomach that is similar in structure to those of terrestrial carnivores. Mysticetes contain a proventriculus as an extension of the oesophagus; this contains stones that grind up food. They also have fundic and pyloric chambers.[42]
1:13
Wikipedia:Disambiguation Top # 9 Facts
Wikipedia:Disambiguation Top # 9 Facts
published: 31 Oct 2015
Wikipedia:Disambiguation Top # 9 Facts
Wikipedia:Disambiguation Top # 9 Facts
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Wikipedia:Disambiguation Top # 9 Facts
Blue on Blue (Under the Dome)
"Blue on Blue" is the fifth episode of the CBS drama Under the Dome. The episode aired on July 22, 2013. It was after this episode that the series was renewed for a second season on July 29, 2013.
The episode was screened at the 2013 Comic-Con, and was received positively by viewers; and was also well received by most critics. Upon airing, the episode was watched by 11.60 million viewers, with an 18-49 rating of 2.8, presenting an increase in ratings from the previous episode.
Plot
Despite finding Angie in the shelter, Jim leaves her locked up, unable to believe his son would do such a thing. Meanwhile, the military has scheduled a "visitors' day" for the residents of Chester's Mill, where family members and friends of people trapped in the dome can come and visit their loved ones. During the event, Linda tells her fiancé about his brother's death, Norrie meets her estranged biological father (Gary Weeks), who her parents had led her to believe she would never be able to find, and Barbie finds out from a soldier stationed outside the dome that the military plans to attempt to destroy the dome with a missile (MOAB), which will likely kill everyone inside. When Barbie relays this to Big Jim, he orders everyone to take shelter in the tunnels underneath the city. He then releases Angie from her captivity, but when Junior finds out, he sets off after her while everyone else takes shelter in the tunnels.
This page contains text from Wikipedia, the Free Encyclopedia - https://wn.com/Blue_on_Blue_(Under_the_Dome)
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