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Questões de Inglês do ENEM

Questões de Inglês, da área de Linguagens, com gabarito em cada página.

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  • 57 assuntos

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    TEXT 5 – Questions 59 and 60

    Imagem da questão de Inglês, UFMG 2006, Interpretação de texto | Reading comprehension

    http://www.cartoonstock.com/directory/b/business_men.asp - Access: Apr. 2006.

    The cartoon shows that a person can go out of prison if he
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    Imagem da questão de Inglês, UNEMAT 2011, Interpretação de texto | Reading comprehension

    Leia as afirmações.

    I. A casa da foto usa todos os tipos de energia.

    II. Trata-se de um estudo longitudinal realizado pela Universidade de Nottingham.

    III. É um tipo de casa em que muitas pessoas irão viver nos próximos 50 anos.

    IV. Durante o dia a casa necessita apenas de luz solar. V. À noite ou durante o dia a casa recebe em cada cômodo uma iluminação especial através de um gás encanado.

    Assinale a alternativa que indica a(s) afirmativa(s) correta(s).
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    Imagem da questão de Inglês, UDESC 2010, Interpretação de texto | Reading comprehension

    According to the text, the Pentagon is going over to the dark side of computer warfare, this means that it is going to:
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    Imagem da questão de Inglês, USP 2009, Interpretação de texto | Reading comprehension

    Segundo o texto, no Japão,

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    Leia o texto a seguir para responder à questão. 

    Artificial intelligence and the future of medicine

    Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.
    In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients—such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.


    Where are the first places we will start to see AI entering medical practice?

    One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these images—subtle changes in breast tissue over several years of mammograms, for example. There has been some interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly trained physician would not see.
    In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a clinician's attention. This is a computer trying to replicate a human being understanding that data and saying, "This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much larger and more complex sources of data, such as the entire electronic health record and perhaps even data pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.


    What effect will this have on how doctors practice medicine?

    It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide assistance, helping care providers see important signals in massive amounts of data that would otherwise remain hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate. To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's values? What does this mean for the patient's life and for his or her family? That's never going to be an AI function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and councilors for patients as they try to navigate their health. 
    Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine. 

    Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
    Considering the ideas expressed in the text, artificial intelligence (AI) systems
    Escolha uma alternativa para a questão 46679978-c3
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    Inglês

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    Leia o texto a seguir para responder à questão. 

    Artificial intelligence and the future of medicine

    Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.
    In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients—such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.


    Where are the first places we will start to see AI entering medical practice?

    One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these images—subtle changes in breast tissue over several years of mammograms, for example. There has been some interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly trained physician would not see.
    In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a clinician's attention. This is a computer trying to replicate a human being understanding that data and saying, "This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much larger and more complex sources of data, such as the entire electronic health record and perhaps even data pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.


    What effect will this have on how doctors practice medicine?

    It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide assistance, helping care providers see important signals in massive amounts of data that would otherwise remain hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate. To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's values? What does this mean for the patient's life and for his or her family? That's never going to be an AI function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and councilors for patients as they try to navigate their health. 
    Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine. 

    Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
    Analisando-se os aspectos linguísticos e estruturais do texto, constata-se que
    Escolha uma alternativa para a questão 466b9498-c3
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    Inglês

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    Leia o texto a seguir para responder à questão. 

    Artificial intelligence and the future of medicine

    Washington University researchers are working to develop artificial intelligence (AI) systems for health care, which have the potential to transform the diagnosis and treatment of diseases, helping to ensure that patients get the right treatment at the right time.
    In health care, artificial intelligence relies on the power of computers to sift through and make sense of reams of electronic data about patients—such as their ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information. AI excels at the complex identification of patterns in these reams of data, and it can do this at a scale and speed beyond human capacity. The hope is that this technology can be harnessed to help doctors and patients make better health-care decisions.


    Where are the first places we will start to see AI entering medical practice?

    One of the first applications of AI in patient care that we currently see is in imaging, to help improve the diagnosis of cancer or heart problems, for example. There are many types of imaging tests —X-rays, CT scans, MRIs and echocardiograms. But the underlying commonality in all those imaging methods is huge amounts of high-quality data. For AI to work well, it's best to have very complete data sets—no missing numbers, so to speak—and digital images provide that. Plus, the human eye is often blind to some of the patterns that could be present in these images—subtle changes in breast tissue over several years of mammograms, for example. There has been some interesting work done in recognizing early patterns of cancer or early patterns of heart failure that even a highly trained physician would not see.
    In many ways, we already have very simple forms of AI in the clinic now. We've had tools for a long time that identify abnormal rhythms in an EKG, for example. An abnormal heartbeat pattern triggers an alert to draw a clinician's attention. This is a computer trying to replicate a human being understanding that data and saying, "This doesn't look normal, you may need to address this problem." Now, we have the capacity to analyze much larger and more complex sources of data, such as the entire electronic health record and perhaps even data pulled from daily life, as more people track their sleep patterns or pulse rates with wearable devices, for example.


    What effect will this have on how doctors practice medicine?

    It's important to emphasize that these tools are never going to replace clinicians. These technologies will provide assistance, helping care providers see important signals in massive amounts of data that would otherwise remain hidden. But at the same time, there are levels of understanding that computers still can't and may never replicate. To take a treatment recommendation from an AI, even an excellent recommendation, and decide if it's right for the patient is inherently a human decision-making process. What are the patient's preferences? What are the patient's values? What does this mean for the patient's life and for his or her family? That's never going to be an AI function. As these AI systems slowly emerge, we may start to see the roles of physicians changing—in my opinion, in better ways. Doctors' roles may shift from being data collectors and analyzers to being interpreters and councilors for patients as they try to navigate their health. 
    Right now, the challenges we need to address as we try to bring AI into medical practice include improving the quality of the data that we feed into AI systems, developing ways to evaluate whether an AI system is actually better than standard of care, ensuring patient privacy and making sure not only that AI doesn't disrupt clinical work flow but in fact improves it. But if doctors do their jobs right and build these systems well, much of what we have described will become so ingrained in the system, people won't even refer to it separately as informatics or AI. It will just be medicine. 

    Disponível em: https://medicalxpress.com/news/2018-12-artificial-intelligence-future-medicine.html. Acesso em: 02 maio 2019.
    De acordo com o texto, em termos de sentido, verifica-se que o trecho
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    Imagem da questão de Inglês, UEG 2019, Sinônimos | Synonyms

    Disponível em: https://www.who.int/mediacentre/events/2015/world-antibiotic-awareness-week/infographics/en/. Acesso em: 02 maio 2019.

    Considering the linguistics aspects presented in the infographic, we verify that
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    Imagem da questão de Inglês, UEG 2019, Interpretação de texto | Reading comprehension

    Disponível em: https://www.who.int/mediacentre/events/2015/world-antibiotic-awareness-week/infographics/en/. Acesso em: 02 maio 2019.

    Considerando-se os elementos de escritura e forma da língua inglesa, constata-se que
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    Imagem da questão de Inglês, UERJ 2009, Interpretação de texto | Reading comprehension The article includes multiple text types.

    The three most prominent intents of the author, reflected in the structure of the text, are:
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    Imagem da questão de Inglês, UNEMAT 2010, Interpretação de texto | Reading comprehension

    Fonte:http://www.nytimes.com/2010/03/18/world/americas/18brazil (acessado e adaptado em 03/04/10) 

    Considere as afirmações abaixo.


    I. Para Sérgio Cabral, a divisão dos royalties do petróleo entre os Estados brasileiros poderia comprometer a realização das obras necessárias para que o Rio de Janeiro realize a Copa do Mundo de 2014 e as Olimpíadas em 2016.

    II. O presidente do Brasil, Luiz Inácio Lula da Silva, é um aliado político do governador do Rio de Janeiro.

    III. A passeata para protestar contra a Lei foi realizada nas ruas da cidade do Rio, em uma terça-feira chuvosa. IV. As milhares de pessoas presentes na passeata provocaram um grande congestionamento na cidade do Rio de Janeiro.

    V. A Lei proposta por Ibsen Pinheiro e Humberto Souto tem efeito retroativo, ou seja, incidirá sobre os contratos firmados no passado.


    Assinale a alternativa correta.

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    Imagem da questão de Inglês, UNEMAT 2010, Interpretação de texto | Reading comprehension

    Fonte:http://www.nytimes.com/2010/03/18/world/americas/18brazil (acessado e adaptado em 03/04/10) 

    O Pré-sal, como é conhecida a reserva de petróleo descoberta pela Petrobrás, é uma das mais importantes descobertas do mundo.

    Essa reserva encontra-se embaixo de:

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    Imagem da questão de Inglês, UNEMAT 2010, Interpretação de texto | Reading comprehension

    Fonte:http://www.nytimes.com/2010/03/18/world/americas/18brazil (acessado e adaptado em 03/04/10) 

    A frase dita por Carlos Lupi, ministro do Trabalho, No one has the right to take away that which nature has put within the limits of Rio de Janeiro (ℓ 33 a 35), pode ser traduzida por:

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    Imagem da questão de Inglês, UNEMAT 2010, Interpretação de texto | Reading comprehension

    Fonte: http://news.bbc.co.uk/2/hi/uk_news/scotland/edinburgh_and_east/8639 283.stm (acessado e adaptado em 22/04/10)  

    Considere as afirmações abaixo.


    I. Cientistas irão examinar as fezes de animais domésticos e selvagens que vivem no Pantanal.

    II. O banco de dados, com os resultados da investigação, poderá ajudar os fazendeiros no gerenciamento de suas terras para tornar o m2 ainda mais caro.

    III. A pesquisa pode contribuir para que haja diminuição dos impactos da agropecuária na região do Pantanal.

    IV. Mais de duas centenas de espécies de plantas já foram identificadas, fotografadas e caracterizadas como parte da investigação.

    V. 95% da área do Pantanal são de propriedade de fazendeiros, e segundo o Dr. Arnaud Desbiez, é importante trabalhar para preservar os 15% da área que restam desse lugar incrível.


    Assinale a alternativa correta.

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    Imagem da questão de Inglês, UNEMAT 2010, Interpretação de texto | Reading comprehension

    Fonte: http://news.bbc.co.uk/2/hi/uk_news/scotland/edinburgh_and_east/8639 283.stm (acessado e adaptado em 22/04/10)  

    Segundo os pesquisadores, através da avaliação da composição botânica das fezes dos herbívoros domésticos e selvagens, será possível identificar:
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    TEXTO:


    Can animals predict natural disasters?


    Imagem da questão de Inglês, Universidade Estadual de Feira de Santana 2010, Interpretação de texto | Reading comprehension



    CAN, animals predict natural disasters? Disponível em: <http://english.pravda.ru/science/tech/8178-1/Adaptado. Acesso em: 20 dez.2009.

    According to the text, the tsunami disaster killed
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    TEXTO:


    Can animals predict natural disasters?


    Imagem da questão de Inglês, Universidade Estadual de Feira de Santana 2010, Interpretação de texto | Reading comprehension



    CAN, animals predict natural disasters? Disponível em: <http://english.pravda.ru/science/tech/8178-1/Adaptado. Acesso em: 20 dez.2009.

    About the sharks mentioned in the text, it’s correct to say that they
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    TEXTO:


    Can animals predict natural disasters?


    Imagem da questão de Inglês, Universidade Estadual de Feira de Santana 2010, Interpretação de texto | Reading comprehension



    CAN, animals predict natural disasters? Disponível em: <http://english.pravda.ru/science/tech/8178-1/Adaptado. Acesso em: 20 dez.2009.

    The text says scientists have found out that
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    Inglês

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    TEXTO:


    Can animals predict natural disasters?


    Imagem da questão de Inglês, Universidade Estadual de Feira de Santana 2010, Interpretação de texto | Reading comprehension



    CAN, animals predict natural disasters? Disponível em: <http://english.pravda.ru/science/tech/8178-1/Adaptado. Acesso em: 20 dez.2009.

    Fill in the parentheses with True or False.

    The text contains answers to the following questions:

    ( ) How many animals of an Indian reserve survived the 2004 tsunami disaster?
    ( ) How long did the fourteen sharks stay away from their natural habitat?
    ( ) Where did ancient people use to hide during volcano eruptions?
    ( ) Why are domestic animals better equipped than wild ones to handle disasters?

    According to the text, the correct sequence, from top to bottom, is
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    Inglês

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    TEXTO:


    Can animals predict natural disasters?


    Imagem da questão de Inglês, Universidade Estadual de Feira de Santana 2010, Vocabulário | Vocabulary



    CAN, animals predict natural disasters? Disponível em: <http://english.pravda.ru/science/tech/8178-1/Adaptado. Acesso em: 20 dez.2009.

    The only alternative in which there is not a pair of opposites is
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