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English Senior High

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SIO 110225) A Exercises 1 下線部が話題の中心となるように, 受動態の文に書きかえなさい。 1. The famous actor wrote the novel. by the famous actor. 2. They closed the airport because of noise pollution. because of noise pollution. 3. The research team solved the problem after many meetings. by the research team after many meetings. <動作主を示さない <動作主をbyで示 表す。 能動態の目的語 芸術家」が話題の中心 Lesson Krab su ustria. <否定文) Yes/No疑問文 で始まる疑問文) □を含む受動態 to the party? ■言葉] 2 M 45 Eddie put the paintings on the walls of his house. by Eddie on the walls of his house. 5. The moon hid the sun this morning. by the moon this morning. 6. People make mistakes when they are careless. when people are careless. 内の指示に従って, 次の英文を書きかえなさい。 B 1. The professionals didn't repair these old pianos. (下線部を主語に) ST 2. Did the children feed the rabbits the day before yesterday? (下線部を主語に) 3. The vase was broken by Ted. (下線部が答えとなる疑問文に) 4. Lisa was greeted by the host of the party. (下線部が答えとなる疑問文に) 344 5. Her suggestion is accepted. (「~されるべきではない」という意味の文に) 6. We ought to obey the laws of the country. (下線部を主語に) )内の語句を並べかえて, 英文を完成させなさい。 1. (has/the new museum/opened/just/ been). 2. C (will/to/ the patient/carried/be/a bigger hospital). 3. By the time he arrived there, (had/taken / the last/been/seat). 4. (will / the song/by/be/a famous singer / sung). 5. (reached/was/cleaned/the room/I/being/when) the hotel. wone 下線部の内容を主語にして,適切な語句を補って英文を完成させなさい。 総合 来を表す 4 進行形 1. 今この瞬間にも, たくさんの水が世界中で使われている around the world at this very moment. 2. 子どもは危険から守られなければならない。 完了形 from danger. BARONG by anybody. qu healnol ed gd 3. 彼の言葉は誰にも信じてもらえないだろう。 Writing Skills] 1. あなたの自転車はいつ修理されたのですか。 2. このドラマの新しいシーズンが今週末, 公開されるはずだ。

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English Senior High

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Lesson 01 演習問題 (want など + (人) +to不定詞) 4) 私 I de nobu ansvare won a adquod ① 日本語に合うように,( Id 内から適切なものを選ぼう。 1)I want ani / ask) Emi to read this booked suse I a 5) あ Dic Dic (私はエミにこの本を読んでほしい。) 2)I wanted / asked my sister to turn off the TV.digianaco (私は妹にテレビを消すように頼んだ。 ) 3) Please ( tell / want) Tom to attend the meeting tomorrow. (トムに明日会議に出席するように言ってください。)sis po 4) I don't ( ask / want ) my son to eat junk food. (私は息子にジャンクフードを食べてほしくない。) 5) Did you ( want / ask) Sam to call me? (私に電話するようにサムに頼みましたか。) ② 日本語に合うように、( 1) I( SHA 内に適切な語を入れよう。 ) Ryota ( ) ( ) here at nine. (私はリョウタに9時にここに来るように言いました。) 2) I ( ) Kate ( (私はケイトにあなたを助けるように頼みました。) 3) Do you ( ) me ( (私にお皿を洗ってほしいのですか。) 4) I( ) my brother ( ) ( ) ( (私は弟にこの部屋を掃除するように言いました。) 5) Mr. Yamada ( ) Kana ( )( (山田先生はカナに窓を開けるように頼みました。) 6) Jiro ( ) us ( ) ( ジロウは私たちにいっしょに遊んでほしかった。) ) you. ) the dishes? (5) ) this room. ) the window. ) with him. ③ 日本語に合うように,[ []内の語句を正しい順に並べかえよう。 1) 私はあなたにこの歌を歌ってほしい。 Ⅰ [ to sing/ want / you ] this song. I this song. 兄は私にテレビをつけるように頼んだ。 My brother [ asked / to turn on / me ] the TV. My brother 3) アツシにチケットを2枚買うように言ってください。 Please [ tell / to buy / Atsushi ] two tickets. Please the TV. two tickets.

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TOEIC・English Undergraduate

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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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