CEBRASPE/2022 – TRT 8.ª REGIÃO – TÉCNICO JUDICIÁRIO – LÍNGUA INGLESA – TRIBUNAL REGIONAL DO TRABALHO – PROVA COM GABARITO..

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❑ PROVA DE LÍNGUA INGLESA:

• CEBRASPE-2022-TRT 8.ªREGIÃO-TÉCNICO JUDICIÁRIO-05/11/2022.

❑ ESTRUTURA-PROVA:

• 3 MCQs (Multiple Choice Questions) / 5 Options Each Question.
• Texto – | Text 20A12-I | eescorporation.com |

❑ TEXTO:

❑ TRADUÇÃO - TEXTO:

As technology advances, the car industry has developed new ways to improve user experience. À medida que a tecnologia avança, a indústria automobilística desenvolveu novas maneiras de melhorar a experiência do usuário.

One of these ways includes using artificial intelligence to make cars self-driving. Uma dessas maneiras inclui o uso de inteligência artificial para tornar os carros autônomos.

A self-driving car (also known as an autonomous car or driverless car) is a vehicle that uses a different number of sensors, radars, cameras, and artificial intelligence to travel to destinations without needing a human driver. Um carro autônomo (também conhecido como carro autônomo ou carro sem motorista) é um veículo que usa um número diferente de sensores, radares, câmeras e inteligência artificial para viajar até destinos sem a necessidade de um motorista humano.

Many companies have already started to manufacture self-driving cars, which are put through many tests to ensure they are eligible to be on the road without making any errors. Muitas empresas já começaram a fabricar carros autônomos, que são submetidos a diversos testes para garantir que possam circular na estrada sem cometer erros.

To qualify as fully autonomous, a car must navigate routes to predetermined destinations without any human intervention. Para se qualificar como totalmente autônomo, um carro deve percorrer rotas para destinos predeterminados sem qualquer intervenção humana. 

Artificial intelligence powers self-driving vehicle frameworks. A inteligência artificial potencializa estruturas de veículos autônomos.

Self-driving vehicle engineers utilize a great deal of information from image recognition systems, AI and neural networks to assemble frameworks that can drive self-sufficiently. Os engenheiros de veículos autônomos utilizam uma grande quantidade de informações de sistemas de reconhecimento de imagem, IA e redes neurais para montar estruturas que possam dirigir de forma autossuficiente.

The neural networks distinguish patterns in the data, which is fed to the AI calculations. As redes neurais distinguem padrões nos dados, que são alimentados nos cálculos da IA.

That data include images from cameras for self-driving vehicles. Esses dados incluem imagens de câmeras de veículos autônomos.

The neural networks figure out how to recognize traffic lights, trees, pedestrians, road signs, and different parts of any random driving environment. As redes neurais descobrem como reconhecer semáforos, árvores, pedestres, sinais de trânsito e diferentes partes de qualquer ambiente de direção aleatório.

As an example, Google has started to develop self-driving cars, which use a mix of sensors, light detectors, and other technology, like GPS and cameras. Por exemplo, o Google começou a desenvolver carros autônomos, que utilizam uma combinação de sensores, detectores de luz e outras tecnologias, como GPS e câmeras.

All the input data are combined and the artificial system predicts what those objects might do next. Todos os dados de entrada são combinados e o sistema artificial prevê o que esses objetos farão a seguir. 

This whole process happens in a matter of milliseconds. Todo esse processo acontece em questão de milissegundos.

Similar to any human driver, the more experience these systems gain, the better they become at driving. Semelhante a qualquer condutor humano, quanto mais experiência estes sistemas ganham, melhor se tornam na condução.

The more data it deals with in its deep learning algorithms, the more choices it will make and the faster those choices will be. Quanto mais dados ele lidar em seus algoritmos de aprendizado profundo, mais escolhas ele fará e mais rápidas essas escolhas serão.

Internet: <www.eescorporation.com> (adapted). 

58 – (CEBRASPE/2022-TRT-8ªREGIÃO-TÉCNICO JUDICIÁRIO)

According to text 20A12-I,

(A) only with the advances in AI has the car industry been able to develop new ways to enhance user experience.

(B) another name for a self-driving car is an “autonomous car”, which is not the same as a “driverless car”.

(C) self-driving cars will only be made after they have been put through various tests.

(D) image recognition systems are the most important type of technology used to manufacture self-driving vehicles.

(E) a self-driving car can only be qualified as a fully autonomous vehicle after navigating routes without any human intervention.

      Comentários e Gabarito    E  
TÓPICO - RELAÇÃO SEMÂNTICA COM TRECHO DO TEXTO:

De acordo com o texto 20A12-I,

(A) only with the advances in AI has the car industry been able to develop new ways to enhance user experience. somente com os avanços na IA a indústria automobilística foi capaz de desenvolver novas formas de melhorar a experiência do usuário.

(B) another name for a self-driving car is an “autonomous car”, which is not the same as a “driverless car”. outro nome para carro autônomo é “carro autônomo”, que não é o mesmo que “carro sem motorista”.

(C) self-driving cars will only be made after they have been put through various tests. os carros autônomos só serão fabricados depois de terem passado por diversos testes.

(D) image recognition systems are the most important type of technology used to manufacture self-driving vehicles. os sistemas de reconhecimento de imagem são o tipo mais importante de tecnologia usada para fabricar veículos autônomos. autônomos.

(E) a self-driving car can only be qualified as a fully autonomous vehicle after navigating routes without any human intervention. um carro autônomo só pode ser qualificado como veículo totalmente autônomo após percorrer rotas sem qualquer intervenção humana.

➭ TRECHO QUE JUSTIFICA:

• "[...] To qualify as fully autonomous, a car must navigate routes to predetermined destinations without any human intervention." 

• Para se qualificar como totalmente autônomo, um carro deve percorrer rotas para destinos predeterminados sem qualquer intervenção humana.

59 – (CEBRASPE/2022-TRT-8ªREGIÃO-TÉCNICO JUDICIÁRIO)

The main purpose of the second paragraph of text 20A12-I is to explain

(A) why AI is important to make autonomous cars more powerful.

(B) how self-driving cars work through artificial intelligence.

(C) how AI helps to recognize elements like traffic signs, trees, and any other random changes in the driving environment.

(D) what kinds of networks are used to feed the AI calculations.

(E) how crucial images captured by cameras are for autonomous vehicles.

      Comentários e Gabarito    B  
TÓPICO - RELAÇÃO SEMÂNTICA COM TRECHO DO TEXTO:

O principal objetivo do segundo parágrafo do texto 20A12-I é explicar

(A) why AI is important to make autonomous cars more powerful. por que a IA é importante para tornar os carros autônomos mais potentes.

(B) how self-driving cars work through artificial intelligence. como funcionam os carros autônomos por meio da inteligência artificial.

(C) how AI helps to recognize elements like traffic signs, trees, and any other random changes in the driving environment. como a IA ajuda a reconhecer elementos como sinais de trânsito, árvores e quaisquer outras mudanças aleatórias no ambiente de condução.

(D) what kinds of networks are used to feed the AI calculations. que tipos de redes são usadas para alimentar os cálculos da IA.

(E) how crucial images captured by cameras are for autonomous vehicles. quão cruciais são as imagens capturadas por câmeras para veículos autônomos.

➭ TRECHOS QUE JUSTIFICAM:

• "[...] The neural networks distinguish patterns in the data, which is fed to the AI calculations." As redes neurais distinguem padrões nos dados, que são alimentados nos cálculos da IA.

• "[...] That data include images from cameras for self-driving vehicles." Esses dados incluem imagens de câmeras de veículos autônomos.

• "[...] The neural networks figure out how to recognize traffic lights, trees, pedestrians, road signs, and different parts of any random driving environment". As redes neurais descobrem como reconhecer semáforos, árvores, pedestres, sinais de trânsito e diferentes partes de qualquer ambiente de direção aleatório.

60 – (CEBRASPE/2022-TRT-8ªREGIÃO-TÉCNICO JUDICIÁRIO)

From the excerpt “The more data it deals with in its deep learning algorithms, the more choices it will make and the faster those choices will be” (last paragraph of text 20A12-I), it can be concluded that

(A) if a self-driving car deals with more data in its deep learning algorithms, it will make more but slower choices.

(B) the speed at which self-driving cars make choices is mostly affected by the number of dates on which these vehicles are put to use.

(C) the large amount of data available in deep learning algorithms can undermine the quality of the choices made by self-driving cars.

(D) self-driving cars will have more data in its deep learning algorithms if they make faster choices.

(E) the technology in self-driving cars will make more and faster choices as it deals with more data in its deep learning algorithms.

      Comentários e Gabarito    E  
TÓPICO - RELAÇÃO SEMÂNTICA COM TRECHO DO TEXTO:

Do trecho “Quanto mais dados ele tratar em seus algoritmos de aprendizagem profunda, mais escolhas ele fará e mais rápidas serão essas escolhas” (último parágrafo do texto 20A12-I), pode-se concluir que

(A) if a self-driving car deals with more data in its deep learning algorithms, it will make more but slower choices. se um carro autônomo lidar com mais dados em seus algoritmos de aprendizado profundo, ele fará mais escolhas, porém mais lentas.

(B) the speed at which self-driving cars make choices is mostly affected by the number of dates on which these vehicles are put to use. a velocidade com que os carros autônomos fazem escolhas é afetada principalmente pelo número de datas em que esses veículos são colocados em uso.

(C) the large amount of data available in deep learning algorithms can undermine the quality of the choices made by self-driving cars. a grande quantidade de dados disponíveis em algoritmos de aprendizagem profunda pode prejudicar a qualidade das escolhas feitas pelos carros autônomos.

(D) self-driving cars will have more data in its deep learning algorithms if they make faster choices. os carros autônomos terão mais dados em seus algoritmos de aprendizado profundo se fizerem escolhas mais rápidas.

(E) the technology in self-driving cars will make more and faster choices as it deals with more data in its deep learning algorithms. a tecnologia nos carros autônomos fará mais escolhas e mais rápidas à medida que lida com mais dados em seus algoritmos de aprendizagem profunda.

➭ TRECHOs QUE JUSTIFICAm:

• "[...] Similar to any human driver, the more experience these systems gain, the better they become at driving." Semelhante a qualquer condutor humano, quanto mais experiência estes sistemas ganham, melhor se tornam na condução.

• "[...] The more data it deals with in its deep learning algorithms, the more choices it will make and the faster those choices will be". Quanto mais dados ele lidar em seus algoritmos de aprendizado profundo, mais escolhas ele fará e mais rápidas essas escolhas serão.

CESPE – CEBRASPE – 2014 – TJ/SE – TÉCNICO JUDICIÁRIO (Cargo 20) – LÍNGUA INGLESA – CONCURSO PÚBLICO – TRIBUNAL DE JUSTIÇA DE SERGIPE – PROVA COM GABARITO.

Welcome back to another post!

➧ PROVA DE LÍNGUA INGLESA: CEBRASPE-2014-TJ/SE- TÉCNICO JUDICIÁRIO (Cargo 20).

➧ BANCA/ORGANIZADOR:

➧ PADRÃO/COMPOSIÇÃO DA PROVA: 09 questões do tipo  CORRETA (C) ou ERRADA (E).

➧ GABARITO:

01-C, 02-C, 03-E, 04-E, 05-C

06-C, 07-E, 08-C, 09-E

➧ VOCABULÁRIO:

• Verbo (to assess=avaliar) ➝ assessed = avaliada. 
• Verbo (to access=acessar) ➝ accessed = acessada.
• An information security assessment - Uma avaliação de segurança da informação.

➧ TEXTO 1:

An information security assessment is the process of determining how effectively an entity being assessed (e.g., host, system, network, procedure, person — known as the assessment object) meets specific security objectives. Three types of assessment methods can be used to accomplish this — testing, examination, and interviewing. Testing is the process of exercising one or more assessment objects under specified conditions to compare actual and expected behaviors. Examination is the process of checking, inspecting, reviewing, observing, studying, or analyzing one or more assessment objects to facilitate understanding, achieve clarification, or obtain evidence. Interviewing is the process of conducting discussions with individuals or groups within an organization to facilitate understanding, achieve clarification, or identify the location of evidence. Assessment results are used to support the determination of security control effectiveness over time.

Technical guide to information security testing and assessment. Internet: <http://csrc.nist.gov> (adapted).

Based on the above text, judge the following items.

01. In the text, the word “accomplish” (l.5) has the same meaning as “achieve” (l.11).

02. Testing, examination and interviewing are methods which can result in effective assessments of people.

03. In the text, “used to” (l.15) could be correctly replaced by accustomed, without changing the meaning of the text.

04. In the text, the word “assessed” (l.2) is synonymous with the word accessed.

➧ TEXTO 2:

Facebook wasn’t the first to offer security researchers bounties for reporting vulnerabilities — but the social network reports it paid out $1.5m in 2013 for bug reports, and says it is increasing the amount of cash on offer in the coming year.

According to the advertising giant, it received 14,763 reports of suspected flaws last year, an increase of 246 per cent on the 2012 figure. Unfortunately for Facebook’s security team there were a lot of false positives in there, and only 687 write-ups turned out to be worth paying for — and, thankfully, roughly six per cent were classified as high-severity issues.

3

US researchers found 92 correct flaws, with an average payday of $2,272 each, while the British contingent sent in valid bugs each worth $2,950 on average. Facebook’s highest payout went to Brazilian researcher Reginaldo Silva, who earned $33,500 for finding an XML external entity vulnerability within a PHP page.

Iain Thomson. How much is a security bug report

worth to Facebook? About $2,100. Internet:

<www.theregister.co.uk> (adapted)

Based on the text, judge the items that follow.

05. The word “figure” (l.7) means number.

06. The smallest amount Facebook paid for a bug report wasn’t for Brazilian Reginaldo Silva.

07. In 2013, Facebook paid about 2,100 dollars for each of the 14,763 bug reports.

08. The expression “social network” (l.2) refers to “Facebook” (l.1).

09. Facebook didn’t pay some of the 687 write-ups.

IADES-2014-TRE/PA-LÍNGUA INGLESA - Técnico Judiciário TRIBUNAL REGIONAL ELEITORAL DO PARÁ - Prova com gabarito.

Welcome back to another post!

➧ PROVA DE LÍNGUA INGLESA: CONCURSO PÚBLICO TRE/PA(TRIBUNAL REGIONAL ELEITORAL DO PARÁ) - TÉCNICO JUDICIÁRIO - Aplicada em 23/02/2014.

➧ BANCA/ORGANIZADOR: IADES (Instituto Americano de Desenvolvimento) - https://www.iades.com.br/.

➧ PADRÃO/COMPOSIÇÃO DA PROVA: 03 questões do tipo (A,B,C,D,E).

➧ GABARITO:

01-C,  02-A,  03-E

• Texto para responder as questões de 01 a 03(IADES-2014-TRE/PA):

Electronic vote in Brazil

       

Brazilians have been voting electronically for more than a decade. The digital ballot was first introduced in 1996 and by the year 2000, a hundred percent of the country’s elections were done by means of voting ballots. When they were first launched, many voting machines could be found in schools and public areas so that the general public and potential voters could learn how to use them. In October of voting years, thousands of voting machines are taken to schools and libraries around the country so that about a hundred and twenty million people can vote for their candidates. Nowadays, over four hundred and fifty thousand digital ballot boxes are used in Brazil, and there is an increasing demand for those machines, since the number of voters have been increasing around six percent every election.
       

The machine has both made voting easier for Brazilians and reduced the number of errors that can crop up when ballot papers are used. It has an easy interface, where voters use a numeric keyboard to type in the numbers of their candidates and they are also able to see the picture of the person they are voting for. Another advantage of such voting machines is that they function for approximately twenty hours on regular batteries. Moreover, it is an independent system, working with no Wi-Fi connection, thus making it impossible to be hacked remotely. The electronic ballot is believed to be reliable, easy to use, low cost and have a tenyear life span. Due to its success, the digital ballot has been improved along the years: now it also has fingerprint identification.

Adapted from: BBC News, How Brazil has put an "e" in vote.

Available at: http://news.bbc.co.uk/2/hi/7644751.stm

Accessed on January:19th, 2014.

01 – (IADES-2014-TRE/PA) 

Based on the text above, choose the correct alternative.

(A) It is about the advantages and disadvantages of voting through electronic ballots.
(B) It is about the people who voted for their candidates in 1996 and 2000.
(C) It is about the advantages of the electronic vote in Brazil.
(D) It is about the disadvantages of electronic voting in Brazil.
(E) It is about the use of Wi-Fi connection in schools and libraries.

02 – (IADES-2014-TRE/PA)

Considering the text, it’s correct to say that the electronic ballot

(A) is cheap and trustworthy.
(B) uses internet connection.
(C) has a twenty-hour life span.
(D) might be hacked remotely.
(E) increases six percent every election.

03 – (IADES-2014-TRE/PA)

According to the text, choose the correct alternative.

(A) 120,000 ballot boxes are available nowadays.
(B) 450,000 are used in Brazil.
(C) 100% of the country’s elections were done by balloons.
(D) 112,000,000 people vote for their candidates.
(E) 100% of the country’s elections are done through voting ballots.

FCC-2013-TRT/13ª Região -Técnico Judiciário(TI) - LÍNGUA INGLESA - Concurso Público do Tribunal Regional do Trabalho 11° Região (TRT-11ª) - Banca Fundação Carlos Chagas - Prova com gabarito.

Welcome back to another post!

➧ PROVA DE LÍNGUA INGLESA: Concurso do TRT(Tribunal Regional do Trabalho 11° Região)-Técnico Judiciário-Tecnologia da Informação-Prova aplicada em 2013.

➧ BANCA/ORGANIZADOR:

➧ PADRÃO/COMPOSIÇÃO DA PROVA: 05 questões do tipo (A,B,C,D,E).

➧ GABARITO:

01-A,  02-C,  03-B,  04-A,  05-E

Atenção: Considere o texto a seguir para responder as questões de números 56 a 60.

December 12, 2012

If It's for Sale, His Lines Sort It

By MARGALIT FOX         

It was born on a beach six decades ago, the product of a pressing need, an intellectual spark and the sweep of a young man's fingers through the sand.
        
The result adorns almost every product of contemporary life, including groceries, wayward luggage and, if you are a traditionalist, the newspaper you are holding.
        
The man on the beach that day was a mechanical-engineer-in-training named N. Joseph Woodland. With that transformative stroke of his fingers − yielding a set of literal lines in the sand − Mr. Woodland, who died on Sunday at 91, conceived the modern bar code.
        
Mr. Woodland was a graduate student when he and a classmate, Bernard Silver, created a technology, based on a printed series of wide and narrow striations, that encoded consumer-product information for optical scanning.
        
Their idea, developed in the late 1940s and patented 60 years ago this fall, turned out to be ahead of its time, and the two men together made only $15,000 from it, when they sold their patent to Philco. But the curious round symbol they devised would ultimately give rise to the universal product code, or U.P.C., as the staggeringly prevalent rectangular bar code (it graces tens of millions of different items) is officially known.

        
Here is part of the story behind the invention:       
To represent information visually, he realized, he would need a code. The only code he knew was the one he had learned in the Boy Scouts.
        
What would happen, Mr. Woodland wondered one day, if Morse code, with its elegant simplicity and limitless combinatorial potential, were adapted graphically? He began trailing his fingers idly through the sand.
       
"What I'm going to tell you sounds like a fairy tale," Mr. Woodland told Smithsonian magazine in 1999. "I poked my four fingers into the sand and for whatever reason − I didn't know − I pulled my hand toward me and drew four lines. I said: ‘Golly! Now I have four lines, and they could be wide lines and narrow lines instead of dots and dashes.’
        
” That consequential pass was merely the beginning. “Only seconds later,” Mr. Woodland continued, “I took my four fingers − they were still in the sand − and I swept them around into a full circle.”
        
Mr. Woodland favored the circular pattern for its omnidirectionality: a checkout clerk, he reasoned, could scan a product without regard for its orientation.
        
But that method − a variegated bull’s-eye of wide and narrow bands − , which depended on an immense scanner equipped with a 500-watt light, was expensive and unwieldy, and it languished for years.
        
The two men eventually sold their patent to Philco for $15,000 − all they ever made from their invention.
        
By the time the patent expired at the end of the 1960s, Mr. Woodland was on the staff of I.B.M., where he worked from 1951 until his retirement in 1987.
        
Over time, laser scanning technology and the advent of the microprocessor made the bar code viable. In the early 1970s, an I.B.M. colleague, George J. Laurer, designed the familiar black-and-white rectangle, based on the Woodland-Silver model and drawing on Mr. Woodland’s considerable input.

(Adapted from http://www.nytimes.com/2012/12/13/business/n-joseph-woodland-inventor-of-the-bar-code-dies-at-91.html?nl=todaysheadlines &emc=edit_th_20121214&_r=0)

01 – (FCC-2013-TRT/13ª Região-Técnico Judiciário-TI)

O pronome "It", no início do texto,

refere-se a

(A) bar code.
(B) young man.
(C) beach.
(D) sand.
(E) luggage.

02 – (FCC-2013-TRT/13ª Região-Técnico Judiciário-TI)

A ideia de Woodland e Silver foi patenteada em

(A) 1960.
(B) 1940.
(C) 1952.
(D) 2000.
(E) 2012

03 – (FCC-2013-TRT/13ª Região-Técnico Judiciário-TI)

Infere-se do texto que

(A) o formato digital do jornal atrai os tradicionalistas.
(B) pessoas conservadoras lêem o jornal em formato impresso.
(C) cada vez mais pessoas estão voltando a ler o jornal impresso.
(D) um dos motivos para não se ler jornal no formato impresso é o fato de sujar as mãos.
(E) apesar da comodidade de se ler as notícias em formato digital, o jornal impresso ainda conta com um público maior.

04 – (FCC-2013-TRT/13ª Região-Técnico Judiciário-TI)

Dentro do contexto, a tradução correta para o significado de

"it languished for years"

é

(A) não saiu do papel por anos.
(B) foi aprimorado ao longo dos anos.
(C) passou por revisões durante anos.
(D) foi resgatado há alguns anos.
(E) foi superado após alguns anos.

05 – (FCC-2013-TRT/13ª Região-Técnico Judiciário-TI)

De acordo com o texto,

(A) Woodland trabalhava na I.B.M. quando criou sua invenção.
(B) Woodland e Silver lucraram US$15.000 cada um com sua invenção.
(C) o código de barras atual tem o mesmo formato da criação de Woodland e Silver.
(D) George J. Laurer patenteou um novo código de barras em 1970.
(E) Woodland se inspirou no código Morse para criar seu método.