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Mark the correct option to complete the excerpt below.
Oil spill reported at Golden Ray wreck site
I- __________ Unified Command in charge of II- disposal of III- ________wreck in Golden Ray reported IV- _________oil spill which V- __________ workers were attempting to contain both VI- water and along VII coastline of St. Simons Sound.
(Adapted from https://www.fleetmon.com>oil...)
“For two years Mohammad Aisha has been the lone resident of an abandoned container ship marooned off Egypt in Golf of Suez. If he needs to charge his phone, get drinking water or buy food, he has to row to shore, although he can only stay for two hours at most as the area is a restricted military zone. According to one doctor who examined him, the malnourished sailor has started to exhibit similar symptoms to prisioners held in poor conditions.”
(Adapted from https://www.the guardian.com>19)
Mark the correct option aboutthetext.
Based on the text, answer question.
What the Ever Given can tell us about mental health at sea
Based on the text, answer question.
What the Ever Given can tell us about mental health at sea
Based on the text, answer question.
What the Ever Given can tell us about mental health at sea
Read the sentences and mark the correct option aboutthe text.
1) Captain Lee Clarke reckons that the crew of the Ever Given busted a gut to steer clear ofjeopardies.
Il) The crew”s mental well-being was slighted.
III) Seafarers are usually given the sack for being unwary.
IV) The crew of the Ever Given stood out for being clumsy.
V) It was settled that there was
a female skipper
who rode herd on the Ever Given.
Which option corresponds to the sentences that are grammatically correct?
I) Sue kissed them each on the forehead.
II) My niece has lost nearly each friend she had.
III) I can write with any hand.
IV) They each said what they thought.
V) Paul didn't get on with either parent.
Based on the text, answer question.
First ship tunnel to be constructed in Norway
Based on the text, answer question.
First ship tunnel to be constructed in Norway
Readthe text below and mark the correct option.
Inland cargo ship ran aground, damaged, may break in two, Western Scheldt
Inland cargo ship MVS SOWNENT loaded with soil ran aground at around 1750 UTC April 14 on Western Scheldt near Baalhoek, Netherlands, while sailing downstream. The ship suffered serious damages, hull is breached, understood to get cracks, but there's no immediate danger of breaking. She was refloated and taken below grounding site, to be offloaded and after that, towed to Hansweert.
(Adapted from https://www.fleetmon.com/services/vesselrisk-rating/)
It is possible to infer from the excerpt that
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
How facial recognition technology aids police
Police officers’ ability to recognize and locate individuals with a history of committing crime is vital to their work. In fact, it is so important that officers believe possessing it is fundamental to the craft of effective street policing, crime prevention and investigation. However, with the total police workforce falling by almost 20 percent since 2010 and recorded crime rising, police forces are turning to new technological solutions to help enhance their capability and capacity to monitor and track individuals about whom they have concerns.
One such technology is Automated Facial Recognition (known as AFR). This works by analyzing key facial features, generating a mathematical representation of them, and then comparing them against known faces in a database, to determine possible matches. While a number of UK and international police forces have been enthusiastically exploring the potential of AFR, some groups have spoken about its legal and ethical status. They are concerned that the technology significantly extends the reach and depth of surveillance by the state.
Until now, however, there has been no robust evidence about what AFR systems can and cannot deliver for policing. Although AFR has become increasingly familiar to the public through its use at airports to help manage passport checks, the environment in such settings is quite controlled. Applying similar procedures to street policing is far more complex. Individuals on the street will be moving and may not look directly towards the camera. Levels of lighting change, too, and the system will have to cope with the vagaries of the British weather.
[…]
As with all innovative policing technologies there are important legal and ethical concerns and issues that still need to be considered. But in order for these to be meaningfully debated and assessed by citizens, regulators and law-makers, we need a detailed understanding of precisely what the technology can realistically accomplish. Sound evidence, rather than references to science fiction technology --- as seen in films such as Minority Report --- is essential.
With this in mind, one of our conclusions is that in terms of describing how AFR is being applied in policing currently, it is more accurate to think of it as “assisted facial recognition,” as opposed to a fully automated system. Unlike border control functions -- where the facial recognition is more of an automated system -- when supporting street policing, the algorithm is not deciding whether there is a match between a person and what is stored in the database. Rather, the system makes suggestions to a police operator about possible similarities. It is then down to the operator to confirm or refute them.
By Bethan Davies, Andrew Dawson, Martin Innes
(Source: https://gcn.com/articles/2018/11/30/facial-recognitionpolicing.aspx, accessed May 30th, 2020)
( ) In relation to AFR, ethical and legal implications are being brought up. ( ) There is enough data to prove that AFR is efficient in street policing.
( ) AFR performance may be affected by changes in light and motion.
The statements are, respectively,
I. No primeiro verso, também seria correta a forma singular do verbo (“posta-se”), por haver sujeito indeterminado. II. No nono verso, o verbo “empunhar” poderia estar flexionado também no plural (“empunharmos”). III. O adjetivo “vis”, no décimo primeiro verso, está corretamente concordando com o substantivo a que se refere (“hostes”) em número e gênero.
Está correto o que se afirma em
À proporção que alguns locatários abandonavam a estalagem, muitos pretendentes surgiam disputando os cômodos desalugados. Delporto e Pompeo foram varridos pela febre amarela e três outros italianos estiveram em risco de vida. O número dos hóspedes crescia, os casulos subdividiam-se em cubículos do tamanho de sepulturas, e as mulheres iam despejando crianças com uma regularidade de gado procriador. Uma família, composta de mãe viúva e cinco filhas solteiras, das quais destas a mais velha tinha trinta anos e a mais moça quinze, veio ocupar a casa que Dona Isabel esvaziou poucos dias depois do casamento de Pombinha.
Agora, na mesma rua, germinava outro cortiço ali perto, o “Cabeça-de-Gato”. Figurava como seu dono um português que também tinha venda, mas o legítimo proprietário era um abastado conselheiro, homem de gravata lavada, a quem não convinha, por decoro social, aparecer em semelhante gênero de especulações. E João Romão, estalando de raiva, viu que aquela nova república da miséria prometia ir adiante e ameaçava fazer-lhe à sua perigosa concorrência. Pôs-se logo em campo, disposto à luta, e começou a perseguir o rival por todos os modos, peitando fiscais e guardas municipais, para que o não deixassem respirar um instante com multas e exigências vexatórias; enquanto pela sorrelfa* plantava no espírito dos seus inquilinos um verdadeiro ódio de partido, que os incompatibilizava com a gente do “Cabeça-de-Gato”. Aquele que não estivesse disposto a isso ia direitinho para a rua, “que ali se não admitiam meias medidas a tal respeito! Ah! ou bem peixe ou bem carne! Nada de embrulho!”.
AZEVEDO, Aluísio. O Cortiço, 1890. Disponível em: http://www.dominiopublico.gov.br/download/texto/bv000015.pdf. Acesso em 27 jul. 2020.
* sorrelfa: dissimulação silenciosa para enganar ou iludir.
À proporção que alguns locatários abandonavam a estalagem, muitos pretendentes surgiam disputando os cômodos desalugados. Delporto e Pompeo foram varridos pela febre amarela e três outros italianos estiveram em risco de vida. O número dos hóspedes crescia, os casulos subdividiam-se em cubículos do tamanho de sepulturas, e as mulheres iam despejando crianças com uma regularidade de gado procriador. Uma família, composta de mãe viúva e cinco filhas solteiras, das quais destas a mais velha tinha trinta anos e a mais moça quinze, veio ocupar a casa que Dona Isabel esvaziou poucos dias depois do casamento de Pombinha.
Agora, na mesma rua, germinava outro cortiço ali perto, o “Cabeça-de-Gato”. Figurava como seu dono um português que também tinha venda, mas o legítimo proprietário era um abastado conselheiro, homem de gravata lavada, a quem não convinha, por decoro social, aparecer em semelhante gênero de especulações. E João Romão, estalando de raiva, viu que aquela nova república da miséria prometia ir adiante e ameaçava fazer-lhe à sua perigosa concorrência. Pôs-se logo em campo, disposto à luta, e começou a perseguir o rival por todos os modos, peitando fiscais e guardas municipais, para que o não deixassem respirar um instante com multas e exigências vexatórias; enquanto pela sorrelfa* plantava no espírito dos seus inquilinos um verdadeiro ódio de partido, que os incompatibilizava com a gente do “Cabeça-de-Gato”. Aquele que não estivesse disposto a isso ia direitinho para a rua, “que ali se não admitiam meias medidas a tal respeito! Ah! ou bem peixe ou bem carne! Nada de embrulho!”.
AZEVEDO, Aluísio. O Cortiço, 1890. Disponível em: http://www.dominiopublico.gov.br/download/texto/bv000015.pdf. Acesso em 27 jul. 2020.
* sorrelfa: dissimulação silenciosa para enganar ou iludir.
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