Questões Militares de Inglês

Foram encontradas 4.268 questões

Q1778060 Inglês
   Leia o texto e responda à questão.

     The discussion of the worldliness of English (…) suggests that it is impossible to separate English from its many contexts, and therefore, that the idea that it might be possible to ‘just teach the language’ - is (…) indefensible. (…) To teach is to be caught up in an array of questions concerning curriculum, educational systems and classroom practices: (1) whose knowledges and cultures are given credence? (2) to what extent does an educational system reproduce social and cultural inequalities? And (3) what understandings of language, culture, education, authority, knowledge or communication do we assume in our teaching?

(PENNYCOOK, A. The cultural politics of English as an international language. Adaptado). 
A discussão de Pennycook sobre “just teach the language” vai ao encontro do debate sobre multiletramentos feito por Rojo e Moura em seu livro, uma vez que os autores entendem que, para ensinar na área, é preciso que o(a) professor(a)
Alternativas
Q1778059 Inglês
The term pedagogy of multiliteracies was created in 1996, by the New London Group. According to Rojo and Moura (2012), the group asked themselves questions such as “O que é uma educação apropriada para mulheres, para indígenas, para imigrantes que não falam a língua nacional, para falantes dos dialetos não padrão? (...).”
(ROJO, R.; MOURA, E. (orgs). Multiletramentos na escola.)
Assinale a alternativa que melhor caracteriza a pedagogia dos multiletramentos.
Alternativas
Q1778058 Inglês
   Read the following extract and answer question.

     The disjunction between method as conceptualized by theorists and method as conducted by teachers is the direct consequence of the inherent limitations of the concept of method itself. First and foremost, methods are based on idealized concepts geared toward idealized contexts. Since language learning and teaching needs, wants, and situations are unpredictably numerous, no idealized method can visualize all the variables in advance in order to provide situation-specific suggestions that practicing teachers so clearly need in order to tackle the challenges they confront every day of their professional lives. As a predominantly topdown exercise, the conception and construction of methods have been largely guided by a one-size-fits-all (…) approach that assumes a common clientele with common goals.

(KUMARAVADIVELU, B. Beyond methods:
macrostrategies for language teaching. Adapted)
Kumaravadivelu states that there are over 15 methods for Second and Foreign Language (L2) teaching, which he divides into three categories, i.e. language-centered, learner-centered and learning-centered methods, as seen, respectively, in alternative:
Alternativas
Q1778057 Inglês
   Read the following extract and answer question.

     The disjunction between method as conceptualized by theorists and method as conducted by teachers is the direct consequence of the inherent limitations of the concept of method itself. First and foremost, methods are based on idealized concepts geared toward idealized contexts. Since language learning and teaching needs, wants, and situations are unpredictably numerous, no idealized method can visualize all the variables in advance in order to provide situation-specific suggestions that practicing teachers so clearly need in order to tackle the challenges they confront every day of their professional lives. As a predominantly topdown exercise, the conception and construction of methods have been largely guided by a one-size-fits-all (…) approach that assumes a common clientele with common goals.

(KUMARAVADIVELU, B. Beyond methods:
macrostrategies for language teaching. Adapted)
Considering the excerpt above, it is fair to say that the writer argues for the
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727970 Inglês

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 the first paragraph, the pronoun “it” in “officers believe possessing it” refers to the
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727969 Inglês

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)

The word “while” in “While a number of UK and international police forces have been enthusiastically exploring the potential of AFR” has the same meaning as
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727968 Inglês

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)

The word that may replace “In fact” in “In fact, it is so important”, without change in meaning, is
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727967 Inglês

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 “Until now, however”, the word “however” introduces the notion of
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727966 Inglês

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)

The authors conclude the text by stating that
Alternativas
Ano: 2021 Banca: FGV Órgão: PM-SP Prova: FGV - 2021 - PM-SP - Aluno - Oficial PM |
Q1727965 Inglês

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)

Based on the information provided by Text I, mark the statements below as true (T) or false (F).
( ) 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,
Alternativas
Ano: 2020 Banca: Marinha Órgão: EAM Prova: Marinha - 2020 - EAM - Marinheiro |
Q1696205 Inglês
What sports can you see in the pictures below?
Imagem associada para resolução da questão
Alternativas
Ano: 2020 Banca: Marinha Órgão: EAM Prova: Marinha - 2020 - EAM - Marinheiro |
Q1696204 Inglês
Mark the option that completes the text with the right form of the verbs in parenthesis, respectively.
Betty's doctor told her to exercise more. So she began running. She______ (to enjoy) running. She _____ (to run) almost every day. Betty will run in the marathon next week. A marathon _______(to be) 26 miles. She will run for three hours without stopping. She will try to finish it.
Alternativas
Ano: 2020 Banca: Marinha Órgão: EAM Prova: Marinha - 2020 - EAM - Marinheiro |
Q1696203 Inglês
The Baseball game

Dad took his son Chris to a baseball game. The Los Angeles Dodgers were playing the San Francisco Giants. The Dodgers were the home team. The Giants were the visiting team. Dad and Chris walked into Dodger Stadium. Many people were there. Most of them wanted to see the Dodgers win. They wanted to see the Giants lose. Dad and Chris found their seats. They sat down. Chris told his dad he was hungry. His dad bought two bags of peanuts for Chris. He bought two hot dogs for Chris. He bought a big soda for Chris. A foul ball came their way. People dived for the foul ball. They knocked Chris' soda over. His dad bought him another soda. 

Adapted from: <https://www.eslfast.com/supereasy/se/supereasy134.htm>
How many sodas did Dad buy?
Alternativas
Ano: 2020 Banca: Marinha Órgão: EAM Prova: Marinha - 2020 - EAM - Marinheiro |
Q1696202 Inglês
The Baseball game

Dad took his son Chris to a baseball game. The Los Angeles Dodgers were playing the San Francisco Giants. The Dodgers were the home team. The Giants were the visiting team. Dad and Chris walked into Dodger Stadium. Many people were there. Most of them wanted to see the Dodgers win. They wanted to see the Giants lose. Dad and Chris found their seats. They sat down. Chris told his dad he was hungry. His dad bought two bags of peanuts for Chris. He bought two hot dogs for Chris. He bought a big soda for Chris. A foul ball came their way. People dived for the foul ball. They knocked Chris' soda over. His dad bought him another soda. 

Adapted from: <https://www.eslfast.com/supereasy/se/supereasy134.htm>
Read the following sentence.
"They wanted to see the Giants lose." (line 6)
The pronoun THEY refers to:
Alternativas
Ano: 2020 Banca: Marinha Órgão: EAM Prova: Marinha - 2020 - EAM - Marinheiro |
Q1696201 Inglês
The Baseball game

Dad took his son Chris to a baseball game. The Los Angeles Dodgers were playing the San Francisco Giants. The Dodgers were the home team. The Giants were the visiting team. Dad and Chris walked into Dodger Stadium. Many people were there. Most of them wanted to see the Dodgers win. They wanted to see the Giants lose. Dad and Chris found their seats. They sat down. Chris told his dad he was hungry. His dad bought two bags of peanuts for Chris. He bought two hot dogs for Chris. He bought a big soda for Chris. A foul ball came their way. People dived for the foul ball. They knocked Chris' soda over. His dad bought him another soda. 

Adapted from: <https://www.eslfast.com/supereasy/se/supereasy134.htm>
What did Chris and Dad do?
Alternativas
Q1695790 Inglês
Mark the option that completes the paragraph below correctly.
The Russian Vostok weather station in Antarctica has recorded temperatures as ______ as -89.2ºC (-128.6ºF). Here, the _______ temperature ever measured is -14ºC (7ºF).

Adapted from <https://www.climatestotravel.com/clîmate/antarctica>)
Alternativas
Q1695789 Inglês
Which option completes the paragraph below correctly?
Speak, FIDO!

Imagine you're out for a walk with your family when a strange dog approaches. The dog isn't aggressive, but it seems ______ something because it nudges you with its snout, and barks. What you don't know is that this dog is trained _______ a person with a medical condition. Around the corner, the doq's owner has collapsed, and the dog instinctively runs off _____ help. That's you! But how can the dog make you _______ what's wrong?
(Adapted from https://www.timeforkids.com)
Alternativas
Q1695788 Inglês
Read the sentences below.
I- People shouldn't drive so ____.
II- I need to see a doctor because I haven't been feeling well _____.
III- Although she's tried _______ to find a new job, she's still unemployed.

Which option completes the sentences correctly?
Alternativas
Q1695787 Inglês
Which option completes the paragraph below correctly?

If your child has no symptoms of vision problems and no family history of vision problems, ________ every one to two years. Otherwise, schedule eye exams based on the advice of your eye doctor.
(Adapted from https://www.mayoclinic.org)

Alternativas
Q1695786 Inglês
Which option completes the text correctly? A dash (-) indicates that no article is used.
_______ China's first autonomous cargo ship, named Jin Dou Yun O Hao, has made its first voyage in Zhuhai. Yunzhou Tech, ______ technology company based in Zhuhai, developed ______ ship in collaboration with Wuhan University of Technology and CCS. _______ autonomous cargo ship will reduce 20°/o construction cost, 20% operation cost and 15% fuel consumption.

(Adapted from https://www.seatrade-maritime.com)
Alternativas
Respostas
661: C
662: D
663: B
664: E
665: A
666: C
667: E
668: B
669: D
670: A
671: C
672: C
673: B
674: D
675: E
676: C
677: D
678: D
679: B
680: B