简答题There are too many ________ of management in this company, which will decrease efficiency and lead to confused management. A、layers B、liars C、lays D、lies简答题The body’s natural rhythms mean we all feel ______ and sleepy between 1 and 3 pm. A、imbecilic B、insensate C、dull D、stolid简答题Unfortunately, most of these efforts were directed towards reducing non-oil imports, which had damaging effects on ______ production. A、interior B、domestic C、internal D、inner判断题A. acceleratesB. adjustingC. artificialD. breakthroughsE. crackingF. flexibleG. forefrontH. inputI. installedJ. intuitionK. inventedL. originatedM. processesN. strategiesO. tackleDriverless vehicles, otherwise known as autonomous, automated or self-driving cars, are no longer science fiction. The technology is here. Google is at the (1)_______ in testing driverless cars. Its self-driving car project (2)_______ from the Darpa Grand Challenges for robotic vehicles in the early 2000s. It has incorporated the latest technological (3)_______ into its design at every phase ever since. A driverless car is a vehicle that is capable of sensing its environment and navigating without human (4)_______. Many tech companies are now homing in on (5)_______ intelligence for the capability. A driverless car needs to have sensors to understand the world around it and a brain that collects, (6)_______ and chooses specific actions, such as (7)_______ speed, based on information gathered. Assuming the various autonomous driving features are safer than relying on driver experience and (8)_______, automobile insurance costs will decline. But the sensors, cameras and complex software providing autonomous driving are far more expensive to replace and repair. Also, these autonomous driving features (9)_______ inside vehicles create new risks: What if the Internet shuts down or hackers attack traffic control systems? Who then pays the damages — the owner, or the car producer? Last year a European research project, RoboLaw, was created to (10)_______ such a legal challenge and will deliver its guidelines on regulations to the European Commission in the spring. One question is whether it’s time to deal with the issue without holding companies back from developing the technology.简答题We emulate these people since they all ______ us and motivate us to reach our own goals as well. A、stimulate B、provoke C、inspire D、exalt简答题Should he aim for approval from his parliamentary colleagues or follow the wishes of the wider public? It was a(an) ______. A、epidemic B、collapse C、dilute D、dilemma多选题0|show" data-onresultcheck="*redo|*.na|hide@*correct|*.na|hide@*reset|*.na|hide"> A major government announcement could dramatically reduce crashes on our roads. Equipping the country’s cars and trucks with the vehicle-to-vehicle technology, or V2V, will essentially allow vehicles to see each other and warn of a potential danger before a driver knows it is there. The Department of Transportation has now taken a key step towards requiring the technology to be in every car in the U.S., reports CBS News correspondent Kris Van Cleave. “Our goal is to see this technology put in place as soon as possible. We know that it has the capability to help us avoid accidents that currently happen today,” said Transportation Secretary Antony Foxx. “We can expect the potential impact of up to 80 percent of crashes today avoided because of this technology.” In 2014 more than 32,600 people died in traffic accidents on U.S. roads. The newly proposed rule will call for standard V2V technology to be adopted in a period of years. 2. What does Transportation Secretary Antony Foxx expect to happen? A、Fewer traffic accidents. B、Increasing sales of cars. C、More parking spaces. D、Improved car designs.简答题Under generally accepted accounting principles, companies may use straight-line or one of the ______ methods of depreciation for financial accounting purposes. A、precipitated B、accelerated C、impelled D、spurred多选题0|show" data-onresultcheck="*redo|*.na|hide@*correct|*.na|hide@*reset|*.na|hide"> The online retail giant Amazon has announced the Amazon Go Store, a new shopping experience that fundamentally changes shopping and payments at the same time. Amazon has combined decades of research with artificial intelligence and machine learning along with image recognition. They have combined all of the knowledge that they’ve gained from the one click buying experience and brought this to the retail store. The new kind of physical store concept was announced in a video published on Monday. The Amazon Go Store doesn’t work like a typical Walmart — instead, shoppers use an app, also called Amazon Go, to scan the products they plan to buy, then they can walk out of the building without waiting in a checkout line. The idea is that Amazon’s machine learning technology can automatically identify when a product is added to your cart, so you don’t have to do it yourself. When you leave the store, Amazon automatically charges your Amazon account. 4. What do shoppers need to do when they want to buy the products? A、Take them to a machine. B、Put them in an automatic cart. C、Scan them before leaving. D、Request a delivery service.简答题Patterns that are invisible on the ground can be the most striking part of an ______ photograph. A、aerial B、antenna C、astronautic D、airy简答题But if the Fed wants to surprise the markets again, a more radical idea would be to _________ with its own mandate. A、interfere B、fiddle C、tangle D、tinker判断题Human memory is notoriously unreliable. Even people with the sharpest facial-recognition skills can only remember so much.It’s tough to quantify how good a person is at remembering. No one really knows how many different faces someone can recall, for example, but various estimates tend to hover in the thousands — based on the number of acquaintances a person might have.Machines aren’t limited this way. Give the right computer a massive database of faces, and it can process what it sees — then recognize a face it’s told to find — with remarkable speed and precision. This skill is what supports the enormous promise of facial-recognition software in the 21st century. It’s also what makes contemporary surveillance systems so scary.The thing is, machines still have limitations when it comes to facial recognition. And scientists are only just beginning to understand what those constraints are. To begin to figure out how computers are struggling, researchers at the University of Washington created a massive database of faces — they call it MegaFace — and tested a variety of facial-recognition algorithms as they scaled up in complexity. The idea was to test the machines on a database that included up to 1 million different images of nearly 700,000 different people — and not just a large database featuring a relatively small number of different faces, more consistent with what’s been used in other research.As the database grew, machine accuracy dipped across the board. Algorithms that were right 95% of the time when they were dealing with a 13,000 — image database, for example, were accurate about 70% of the time when confronted with 1 million images. That’s still pretty good, says one of the researchers, Ira Kemelmacher-Shlizerman. “Much better than we expected,” she said.Machines also had difficulty adjusting for people who look a lot alike — either doppelgangers, whom the machine would have trouble identifying as two separate people, or the same person who appeared in different photos at different ages or in different lighting, whom the machine would incorrectly view as separate people.“Once we scale up, algorithms must be sensitive to tiny changes in identities and at the same time invariant to lighting, pose, age,” Kemelmacher-Shlizerman said.The trouble is, for many of the researchers who’d like to design systems to address these challenges, massive datasets for experimentation just don’t exist — at least, not in formats that are accessible to academic researchers. Training sets like the ones Google and Facebook have are private. There are no public databases that contain millions of faces. MegaFace’s creators say that it’s the largest publicly available facial-recognition dataset out there.“An ultimate face recognition algorithm should perform with billions of people in a dataset,” the researchers wrote. 6. Compared with human memory, machines can _________. identify human faces more efficiently tell a friend from a mere acquaintance store an unlimited number of human faces perceive images invisible to the human eye 7. Why did researchers create MegaFace? To enlarge the volume of the facial-recognition database. To increase the variety of facial-recognition software. To understand computers’ problems with facial recognition. To reduce the complexity of facial-recognition algorithms. 8. What does the passage say about machine accuracy? It falls short of researchers’ expectation. It improves with added computing power. It varies greatly with different algorithms. It decreases as the database size increases. 9. What is said to be a shortcoming of facial-recognition machines? They cannot easily tell apart people with near-identical appearances. They have difficulty identifying changes in facial expressions. They are not sensitive to minute changes in people’s mood. They have problems distinguishing people of the same age. 10. What is the difficulty confronting researchers of facial-recognition machines? No computer is yet able to handle huge datasets of human faces. There do not exist public databases with sufficient face samples. There are no appropriate algorithms to process the face samples. They have trouble converting face datasets into the right format.简答题There is a tight connection between theory and practice that all theories ________ from practice and in return serve practice. A、original B、originality C、origin D、originate简答题All of its attributes, even the most fundamental ones like extension and ______, are attributes as noted by an observer, real or imagined. A、continuance B、continuity C、duration D、endurance简答题________ research has been done into this difficult and complicated case, so we believe someday we can solve it. A、Extensive B、Extinctive C、Executive D、Execrated