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英語 高校生

準動詞の問題です。 答えがなく丸つけができないため答えを教えて欲しいです。

Further 30 Lessons 準動詞 (不定詞・動名詞 分詞) Exercises 56 1 []から適切な語句を選びなさい。 (1) I heard him [sung/ singing / to sing] a song in the bathroom. (2)My mother made me [ to do / do / doing J the dishes. (3) I'm looking forward to visit / visiting / to visit ] your house. (4) Please remember [turn/turned / to turn ] off the light. (5)He caught a bad cold, so he gave up [ swim / to swim / swimming J in the sea. (6)Susan was worried about [be/being/her] late for the meeting. (7) Meg had her hair [ cut / cutting / to cut] at a beauty salon. (8)[Interesting / Interested ] in animals, he wants to work at the zoo. 2 日本語の意味に合うように、 ( )に適切な語を入れなさい。 (1) どこで勉強するべきか、 私に教えてください。 Please tell me ( -) ( (2) 彼はたまたま私の名前を知っていた。 He ( ) (. (3) 私の両親は私に留学してほしいと思っている My parents ( )me( ) ( ) know my name. ) ( ) abroad. ) table tennis tomorrow afternoon? ) him to say such a thing. ) anything. (4) 明日の午後に卓球をするのはどうですか。 How ( ) ( (5) そんなことを言うなんて, 彼は礼儀正しい。 It ( )( )( (6)リサは何もする気になれなかった。 Lisa didn't ( ) like ( 3 日本語の意味に合うように, [] の語句を並べかえて全文を書きなさい。 (1) 窓を開けてもよろしいでしょうか。 (1語不要) [ the window / mind / would / open / opening / you / my ]? (2) 彼は車の運転に慣れている。 [ is / used / he / driving / to ]. (3) 彼女は自分の犬を店の外に待たせておいた。 [ 'waiting / left / she / outside the shop / her dog ]. (4) その事故でけがをした少女が病院に運ばれた。 [ taken / the girl / the hospital / the accident / injured / was / in / to ]. (5) ケリーは家が買えるくらい十分に裕福だ。 (1語不足) [ is / buy / enough / Kelly/ahouse / rich J.

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TOEIC・英語 大学生・専門学校生・社会人

この長文問題の答えと解説をお願いします。

15 語数: 398 語 出題校 法政大 5 We are already aware that our every move online is tracked and analyzed. But you 2-53 couldn't have known how much Facebook can learn about you from the smallest of social interactions - a 'like'*. (1) Researchers from the University of Cambridge designed (2) a simple machine-learning 2-54 system to predict Facebook users' personal information based solely on which pages they had liked. E "We were completely surprised by the accuracy of the predictions," says Michael 2-55 Kosinski, lead researcher of the project. Kosinski and colleagues built the system by scanning likes for a sample of 58,000 volunteers, and matching them up with other 10 profile details such as age, gender, and relationship status. They also matched up those likes with the results of personality and intelligence tests the volunteers had taken. The team then used their model to make predictions about other volunteers, based solely on their likes. The system can distinguish between the profiles of black and white Facebook users, 15 getting it right 95 percent of the time. It was also 90 percent accurate in separating males and females, Democrats and Republicans. Personality traits like openness and intelligence were also estimated based on likes, and were as accurate in some areas as a standard personality test designed for the task. Mixing what a user likes with many kinds of other data from their real-life activities could improve these predictions even more. 20 Voting records, utility bills and marriage records are already being added to Facebook's database, where they are easier to analyze. Facebook recently partnered with offline data companies, which all collect this kind of information. This move will allow even deeper insights into the behavior of the web users. 25 30 (3) - Sarah Downey, a lawyer and analyst with a privacy technology company, foresees insurers using the information gained by Facebook to help them identify risky customers, and perhaps charge them with higher fees. But there are potential benefits for users, too. Kosinski suggests that Facebook could end up as an online locker for your personal information, releasing your profiles at your command to help you with career planning. Downey says the research is the first solid example of the kinds of insights that can be made through Facebook. "This study is a great example of how the little things you do online show so much about you,” she says. "You might not remember liking things, " but Facebook remembers and (4) it all adds up.", * a 'like': フェイスブック上で個人の好みを表示する機能。 日本語版のフェイスブックでは「いいね!」 と表記される。 2-56 2-57 2-58 36

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英語 高校生

線を引いたところの訳し方を丁寧に教えて頂きたいです🙇‍♀️

L American poet Ralph Waldo Emerson once said, "Every artist was first an amateur." He likely never thought those words would apply to machines. Yet artificial intelligence (AI) has demonstrated a growing talent for creativity, whether writing a heavy-metal rock album or producing an original portrait that is strikingly similar to a Rembrandt. Applying AI to the art world might seem unoriginal; there are, of course, plenty of humans delivering awe-inspiring work. Supporters say, however, the real beauty of training AI to be creative does not lie in the end product-but rather in the technology's potential to expand on its own machine-learning education, and to solve problems by thinking in different ways far faster and better than humans can. For example, creative problem-solving AI could someday make snap decisions that save the lives of the passengers in a self-driving car if its sensors fail. AI with a creative component will be essential in developing highly automated systems that can respond appropriately to human life, says Mark Riedl, an associate professor at Georgia Institute of Technology's School of Interactive Computing. "The fact is, we do lots of little bits of creativity every single day; lots of problem-solving goes on," Riedl says. "If my son gets a toy stuck under the couch, I have to devise a tool from a hanger to get it out." Riedl points out human creativity is also important in human social interactions, even telling a well-timed joke or recognizing a pun. Computers struggle with such subtleties. An incomplete understanding of how humans construct metaphors, for example, was all it took for an experiment in Al-generated literature to compose a new Harry Potter chapter filled with nonsensical sentences such as, "The floor of the castle seemed like a large pile

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TOEIC・英語 大学生・専門学校生・社会人

英語の問題です。 教えて欲しいです🙇‍♀️

(2) I had my teeth 1 check 1( )に入る最も適切な語句を ① ~ ④から選びなさい。 (1) He went on speaking as if she ( 1 can't 2 hasn't ) there. Son 3 wouldn't ) by a dentist this morning. ult niles 3 checking wahiwon (青山学院大 ) ④weren't pomibinand (岩手医科大) 24 to check 2 checked (3) You should not keep any pets ( 1 after 2 unless ) you can take good care of them. 3 when (中央大) ④which 1 as 2 in ) all be correct. ②anytime (6) If the weather ( ①must have been (4) This town will change ( ) another ten years. (5) Those may not ( 1 absolute ) fine yesterday, I would have done the laundry. 2 is (7) Studying takes up a lot of my time during the week, ( ) little time for hobbies. (芝浦工業大) since 3 of (國學院大) 3 everything ④necessarily (関西学院大 ) ③ wasn't 4 had been (皇學館大) ①1 has left (8) Have you heard the rumors ( 1 that 2 what leaves leaving 4 left ) Susan has returned to this town? ③ which (麗澤大) ④ who 1 by (9) What was found in this experiment is ( 2 for (10)( ) what to say, she remained silent. ) great importance to researchers. 3 in (立命館大) 4 of (愛知工業大) 1 Not knowing 2 Being not knowing ③No knowing ④Knowing no (11) I tried to ( 1 have 2 make ) her to tell me what happened last night. 3 get (十文字学園女子大) 4 let How gimon and (12) Do what you like, as ( 1 far 2 much B in 1 in 2 with bnat am ) as you leave me alone. 3 long (13) This tool is dangerous. Please read the instructions ( (14) If I hadn't drunk so much last night, I ( 1 feel (15) I wish you 1 attend (16) If I ( 1 were ) 2 will feel ) the party yesterday. 2 were attending ) much better than I do right now. ③ would feel ③ have attended (中京大) 4 would have felt (目白大) ④had attended ) in your situation, I would be more careful about what you post on social media. (フェリス女学院大) 4 many ) care. (聖隷クリストファー大) at ④take gwol 3 will be (南山大) ④would be

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