2019年中国工商银行春季招聘考试试题（精选）

13、What does Adam Schickedanz think of ACE（    ）.

A、It needs to be investigated nationally

B、It is highly prevalent among children

C、It is a common public health problem

D、It will lead to obesity or hypertension

14、What can we learn from the passage（    ）.

A、There are gender differences in the effect of ACES

B、Genetics play an important role in health outcomes

C、Middle class families are more likely to have more ACES

D、ACES can exert lifelong impact on people’s mental health

15、What will most probably be done according to the current study（    ）.

A、Identifying the group of people who are at greatest risk

B、Exploring the social and biological mechanisms behind

C、Developing programs that can reduce or mitigate adversity

D、Teaching children how to deal with adversity in a healthy way

材料

Passage 2

A start up company in California is using machine learning and artificial intelligence to advise fire departments about how to plan for earthquakes and respond to them. The company hopes its algorithms can take a lot of the guesswork out of the planning process for disaster response by making accurate predictions about earthquake damage. It’s one of a handful of companies rolling out artificial intelligence and machine learning systems that could help predict and respond to floods, cyber-attacks and other large-scale disasters.

Nicole Hu, the company’s chief technology officer, says the key is to feed the computers three mam categories of data. The first is data about homes and other buildings, such as what materials they’re made of, when they were built and how likely they are to collapse when the ground starts shaking. The next category is data about the natural environments. For example: “What is the soil like? What is the elevation like? What is the general humidity like?” explains Hu. “The third thing we look at is live instant data.” she says, such as the magnitude of the quake, the traffic in the area of the quake and the weather at the time of the quake. The computer uses the information to make predictions about what would happen if an earthquake occurred in a particular area. It then uses data from past earthquakes to see whether its predictions are any good, and revises its predictive models accordingly. In other words, it learns as it goes, which is basically how machine learning works.

Stanford University earthquake engineer Gregory Deierlein consulted for the company. He says one of the most remarkable things about the company’s software is its ability to incorporate data from an earthquake as its happening, and to adjust its predictions in real time. “Those sort of things used to be research projects." says Deierlein “After an event, we would collect data and a few years later we’d produce new models.” Now the new models appear in a matter of minutes. He note the company’s exact methods are opaque. “Like many start up companies they’re not fully transparent in everything they’re doing." He says. “I mean, that’s their proprietary knowledge that they’re proprietary knowledge that they’re bringing to it.”

Nonetheless, some first responders are already convinced the software will be useful. Fire chief Dan Ghiorso leads the Woodside Fire Protection District near San Francisco, which covers 32 square miles. The San Andrea’s fault is only a couple hundred feet behind the firehouse. Ghiorso says in the past, when an earthquake hit, he’d have to make educated guesses about what parts of his district might have suffered the most damage, and then drive to each place to make a visual inspection. He hopes the company’s software will change that, although he has yet to put it to the test during an actual quake. “Instead of driving thirty two square miles, in fifteen minutes on a computer I can get a good idea of the concerns.” he says, “instead of me, taking my educated guess, they’re putting science behind it, so I’m very confident.” Unfortunately, it’s going to take a natural disaster to see if his confidence is justified.

16、What can be the best title of the passage?（    ）

A、Using Artificial Intelligence to Guide Earthquake Response.

B、Comparing Different Earthquake Predicting Software.

C、Challenges for Making Accurate Predictions about Earthquakes.

D、Causes of Naturally Occurring Earthquakes

17、 What is NOT needed for training the earthquake predicting software?（    ）

A、Data about past earthquakes

B、Data about human impacts

C、Data about the geographic conditions

D、Data about the buildings

18、What can we learn about the earthquake-predicting software?

A、It can incorporate live instant date to adjust its predictions.

B、It can measure and locate earthquakes efficiently.

C、It has proved to be useful in Woodside Fire Protection District.

D、It algorithms have made known to the public.

19、How does Dan Ghlorso view the software?（    ）

A、It saves both money and labor.

B、It helps improve the situation

C、It relies too much on past data.

D、It needs more attention.

20、What is the author’s attitude towards the software?（    ）

A、Pessimistic

B、Positive

C、Ambiguous

D、Critical

材料

Passage 3

If you use your commute to catch up on work email, that time “should be counted as part of the working day,” according to a new study by researchers who analyzed thousands of commuters’ online habits. “If travel time were to count as work time, there would be many social and economic impacts.” said Juhet Jain, one of the academics from the University of the West of England who surveyed several thousand commuters on trains in and out of London.

“Most respondents expressed how they consider their commute as time to‘catch up’with work, before or after their traditional working day," according to a summary of the study. “This transitional time also enabled people to switch roles, for example from being a parent getting the kids ready for school in the morning to a business director during the day”The study quotes a working mother named Katheryn saying. “It's really important to my sanity that I can get work done on the tram. I am a busy mum and I rely on that time, so I can get things done" Another commuter, Andrew, told the researchers. “It's dead time in a way so what it allows me to do is finish stuff and not work in the evenings.” The study notes that while work rules vary around the world, some commuters in Norway are already “able to count travel time as part of their working day."

The findings on workers’ use of smartphones and other devices to stay plugged in highlight the importance of providing Wi-Fi to commuters, according to the academics, who presented their study at the Royal Geographical Society. To collect the data, they focused on two train lines that boosted the amount of free Wi-Fi they offered. On the Birmingham to London line, 60 percent of commuters connected to the enhanced network. The results hint at what are likely to be increasingly complicated work-life discussions, in which employees and their bosses debate what qualifies as “work” and where the line between personal and professional time should be drawn. Discussing the results in a news release, Jain said, “It may ease commuter pressure on peak hours and allow for more comfort and flexibility around working times. However, it may also demand more surveillance and accountability for productivity."

In addition to potential ramifications for mass transit that the British researchers highlighted, the idea of claiming commuting time on the clock could also appeal to workers who use other means of travel. Take, for instance, people who rely on ride-share companies to get to their jobs .And the discussion seems certain to widen in the near future, to include a looming wave of self-driving cars that-in theory, at least-promises to free up more travel time for drivers.

As for rail commuters, the researchers said their work shows it’s important that trains “offer a good working environment including tables, power, space and good continuous connectivity for internet and phone calls.”