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| 共计 9 道试题
1 . 有天分的音乐家在任何情况下都不会放弃为《罗密欧与朱丽叶》作曲。(In no case)(汉译英)
2023-07-24更新 | 36次组卷 | 1卷引用:Test for Unit 3 选择性必修第二册(上教版2020)
语法填空-单句语填(约20词) | 适中(0.65) |
2 . He was very ______ (gift) as a child and by the age of eight he had ______ (compose) a piece of music. (所给词的适当形式填空)
2023-07-09更新 | 53次组卷 | 1卷引用:Unit8 单元同步练-2021-2022学年高中英语北师大版(2019)必修第三册
单词拼写-根据首字母填空 | 适中(0.65) |
3 . Mozart c________ his last opera shortly before he died. (根据首字母单词拼写)
2023-06-26更新 | 3次组卷 | 1卷引用:Unit 7 单词练习一 -2022-2023学年高中英语北师大版(2019)必修第三册
完成句子-根据汉语提示填空 | 适中(0.65) |
4 . The famous poet began to ________ ________ (创作诗歌) at the age of 10. (根据汉语提示完成句子)
智能选题,一键自动生成优质试卷~
文章大意:本文是一篇说明文。主要介绍的是为了帮助一些学生戒掉一些坏习惯而采取的一些措施。
5 . 选词填空

When I saw some students dominated by alcohol,tobacco or drug,I made up my mind to help them “delete” the bad habits.To facilitate a positive change was why I set up a team which was     1    of surgeons,specialists in psychology,consultants and dentists,who would regularly deliver speeches to     2    these students’ awareness of physical health.Students were repeatedly informed of some tips on how to get out of a pessimistic or negative state,how to stay dynamic and how to get     3    when they were stressed out or worn out.To these students,to be examined on a monthly basis was necessary.They were also advised to participate in bowling matches,go to skateboarding or go to see a comedy to stimulate their enthusiasm in life.Students were given sugary cookies or nuts straight away if they felt     4    or got the flu.Through these activities,most students     5     changing their bad habits in reward for our help.They would rely on self-discipline to govern themselves and could be     6    in studying instead of skipping classes.They promised to behave themselves in response to our patient guidance.

完成句子-根据中文句子补全英文 | 适中(0.65) |
7 . There are various reasons ________________________.
这有很多人们为什么写诗歌的原因。
2023-02-04更新 | 69次组卷 | 7卷引用:北师大2019版选择性必修三Unit8 Topic talk:Literature单元测试
8 . 在你做陈述之前,深呼吸并镇定下来。(compose oneself,presentation)(汉译英)
9 . Directions: Fill in each blank with a proper word chosen from the box. Each word can be used only once. Note that there is one word more than you need.
A. consisted  B. composing  C. measures  D. account  E. patterns  F. limitations
G. moderately  H. progressed  I. distribution  J. significantly  K. complement

AI can distinguish between bots and humans based on Twitter activity

Artificial intelligence is being used to spot the difference between human users and fake accounts on Twitter.

Emilio Ferrara at the University of Southern California in the US, and his colleagues have trained an AI to detect bots on Twitter based on differences in     1     of activity between real and fake accounts.

The team analysed two separate datasets of Twitter users, which had been classified either manually or by a pre-existing algorithm as either bot or human.

The manually verified dataset     2     of 8.4 million tweets from 3500 human accounts, and 3.4 million tweets from 5000 bots.

The researchers found that human users replied four to five times more often to other tweets than bots did. Real users gradually become more interactive, with the fraction of replies increasing over the course of an hour-long session of Twitter use.

The length of tweets by human users also decreased as sessions     3    . “The amount of information that is exchanged diminishes,” says Ferrara. He believes that the change may result from a cognitive depletion over time, in which people become less likely to expend mental effort    4     original content.

Bots, on the other hand, show no changes in their interactivity or the length of information they tweet over time.

The team also analysed the amount of time between any two consecutive (连读的) tweets from a single user. When this     5     is plotted, bots showed spikes for certain time gaps, such as tweeting at 30-minute or 60-minute intervals.

The team then combined these     6     to train an existing bot-detection algorithm, called Botometer, on the difference in activity patterns. The AI was     7     more likely to accurately detect to fake accounts than when it was not taking into     8     the timing of posts.

The algorithm could be used to     9     other bot-detection tools that analyse the language within posts, says Ferrara.

One of the study’s     10     is that the Twitter data the team analysed is from three years ago. In that time, it’s possible that bots have become more human-like in their activity patterns.

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