Questões de Concurso Comentadas sobre inglês
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Read the text to answer the question.
With the rising complexity of modern information systems and the resulting ever increasing flow of big data, the benefits of Artificial Intelligence (AI) are now widely recognized. Specifically, Machine Learning (ML) methods are already deployed to solve diverse real-world tasks – especially with the advent of deep learning. Fascinating examples of practical achievements of ML are machine translation, travel and vacation recommendations, object detection and tracking, and even various applications in healthcare. Furthermore, ML is rightly considered to be a technology enabler, as it has shown great potential in the context of telecommunication systems or autonomous driving.
Nevertheless, modern society is increasingly relying on Information Technology (IT) systems – including autonomous ones – which are also actively leveraged by malicious entities. Digital threats are, in fact, continuously evolving, and some researchers believe attackers will have sufficient capabilities to harm or kill humans by 2025. To prevent such incidents and mitigate the plethora of risks that can target current and future IT systems, defensive mechanisms require the capability to quickly adapt to the (i) mutating environments and (ii) dynamic threat landscape. Coping with such a twofold requirement via static and human-defined methods is clearly unfeasible, and deployment of Machine Learning in cybersecurity is inescapable.
(https://dl.acm.org. Adaptad)
The word “Nevertheless”, which connects the two paragraphs, indicates
Read the text to answer the question.
With the rising complexity of modern information systems and the resulting ever increasing flow of big data, the benefits of Artificial Intelligence (AI) are now widely recognized. Specifically, Machine Learning (ML) methods are already deployed to solve diverse real-world tasks – especially with the advent of deep learning. Fascinating examples of practical achievements of ML are machine translation, travel and vacation recommendations, object detection and tracking, and even various applications in healthcare. Furthermore, ML is rightly considered to be a technology enabler, as it has shown great potential in the context of telecommunication systems or autonomous driving.
Nevertheless, modern society is increasingly relying on Information Technology (IT) systems – including autonomous ones – which are also actively leveraged by malicious entities. Digital threats are, in fact, continuously evolving, and some researchers believe attackers will have sufficient capabilities to harm or kill humans by 2025. To prevent such incidents and mitigate the plethora of risks that can target current and future IT systems, defensive mechanisms require the capability to quickly adapt to the (i) mutating environments and (ii) dynamic threat landscape. Coping with such a twofold requirement via static and human-defined methods is clearly unfeasible, and deployment of Machine Learning in cybersecurity is inescapable.
(https://dl.acm.org. Adaptad)
The second paragraph states that information technology
Read the text to answer the question.
With the rising complexity of modern information systems and the resulting ever increasing flow of big data, the benefits of Artificial Intelligence (AI) are now widely recognized. Specifically, Machine Learning (ML) methods are already deployed to solve diverse real-world tasks – especially with the advent of deep learning. Fascinating examples of practical achievements of ML are machine translation, travel and vacation recommendations, object detection and tracking, and even various applications in healthcare. Furthermore, ML is rightly considered to be a technology enabler, as it has shown great potential in the context of telecommunication systems or autonomous driving.
Nevertheless, modern society is increasingly relying on Information Technology (IT) systems – including autonomous ones – which are also actively leveraged by malicious entities. Digital threats are, in fact, continuously evolving, and some researchers believe attackers will have sufficient capabilities to harm or kill humans by 2025. To prevent such incidents and mitigate the plethora of risks that can target current and future IT systems, defensive mechanisms require the capability to quickly adapt to the (i) mutating environments and (ii) dynamic threat landscape. Coping with such a twofold requirement via static and human-defined methods is clearly unfeasible, and deployment of Machine Learning in cybersecurity is inescapable.
(https://dl.acm.org. Adaptad)
In the excerpt from the first paragraph – Furthermore, ML is rightly considered to be a technology enabler –, the word in bold can be replaced, with no change in meaning, by
Read the text to answer the question.
With the rising complexity of modern information systems and the resulting ever increasing flow of big data, the benefits of Artificial Intelligence (AI) are now widely recognized. Specifically, Machine Learning (ML) methods are already deployed to solve diverse real-world tasks – especially with the advent of deep learning. Fascinating examples of practical achievements of ML are machine translation, travel and vacation recommendations, object detection and tracking, and even various applications in healthcare. Furthermore, ML is rightly considered to be a technology enabler, as it has shown great potential in the context of telecommunication systems or autonomous driving.
Nevertheless, modern society is increasingly relying on Information Technology (IT) systems – including autonomous ones – which are also actively leveraged by malicious entities. Digital threats are, in fact, continuously evolving, and some researchers believe attackers will have sufficient capabilities to harm or kill humans by 2025. To prevent such incidents and mitigate the plethora of risks that can target current and future IT systems, defensive mechanisms require the capability to quickly adapt to the (i) mutating environments and (ii) dynamic threat landscape. Coping with such a twofold requirement via static and human-defined methods is clearly unfeasible, and deployment of Machine Learning in cybersecurity is inescapable.
(https://dl.acm.org. Adaptad)
In the fragment from the first paragraph – the resulting ever increasing flow of big data –, the terms in bold mean that the flow of big data is
1 - Skimming
2 - Scanning
3- Close Reading
4 - Inference
5 – Summarizing
( ) Condensing the essential information in a text, usually in your words, to capture the main points.
( ) When using this strategy, you search for specific information in the text, such as dates, names, or keywords.
( ) This strategy requires a thorough and analytical examination of the text, paying attention to details, language, and tone.
( ) This involves reading quickly to get a general sense of the text's main ideas without focusing on details.
() Making educated guesses based on the information provided in the text, even if it's not explicitly stated.
Mark the option that contains the correct and respective association.
A) Communicative Approach
B) Audiolingual Approach
C) Grammar-Based Approach
D) Lexical Approach
E) Direct Approach
1 - Emphasis on learning grammatical patterns.
2 - Focus on vocabulary and collocations acquisition.
3 - Promotion of interaction and oral communication.
4 - Repetition and memorization of dialogues.
5 - Exclusive use of English in the classroom.
Correct Association:
(I) William Shakespeare
(II) Charles Dickens
(III) James Joyce
(IV) Emily Bronte
(V) T. S. Eliot
A) "A Tale of Two Cities"
B) "Dubliners"
C) "The Wasteland"
D) "Romeo and Juliet"
E) "Wuthering Heights"
Choose the correct option that makes the appropriate association.
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