学年

質問の種類

英語 高校生

答えあっていますでしょうか😭😭 特に23番と26番が分かっていないです😭😭

1 with 私は1日おきにあるく 20. I work every ( 19. The conference is held (i) three years in Rome. (every ②every 3 each 4 at ) day. every other 単数名詞 1つおきの<名詞>で ごと ningys 〈神奈川工科大〉 1 twice half (③other 4 much J0 〈東京工芸大〉 21. ( ) the members were against his proposal. 1 Most of 2 Most of esw adol. .TE 3 Almost Call of) Almost of oblead (1) 4 Most of 3 愛知医科 22.( ) the children in this school speak two languages. Almost all 2 Almost all of 3 Each (4 all women el 〈関西外国語大〉 23. Those present at the concert were almost ( ). the women 2 of all women 3 all of women 24. I'm surprised that you went there. (f) don't visit that part of town. od T ① Most of tourists the が必要 2 Most the tourists gnibusqebardinom 4 The most tourists 10 owi eriały 2 other D 3 Most tourists 25. I have two computers. One is a laptop, and ( ) is a desktop. 1 each other 3 some other have ( 26. I ha (*)Danother Lec 〈慶應義塾大〉 2つのとき、1つをone 他方を the other で表す 4the other D09 M ) book to finish before the examination. 2 any 3 other 4 others 19 〈 京都女子大 〉 T S☐ 〈名古屋市立大〉 27. English is one of the six official languages of the United Nations, ( ) being French, Russian, Spanish, Chinese, and Arabic. (複数個)のこり全部 1 another 2 others (3 the other 28. Some boys are playing baseball, and ( 1 other 2 the other ) are playing 3 another the others basketball. Some... others ・・・の人もいれば~の人もいる 4 others <福岡大〉 <東京薬科大〉 ~

解決済み 回答数: 1
英語 中学生

これわかんない笑笑 7時までに誰かといてー

科書 P.58 学習日 ◆ 英東・2 月 Lv2 Lv2 ょう。 Lv2 ③2 (4) You (am you study. 3125 Must イ Can No, you don't have to. 2(6) You (ア can イ may it's cold today. ◆英東・2 イ was ウ must I have) not play the game when ↓ [ ] 例文 ウ May Will)I_go there? P ] 例文 should Q will) wear a sweater because 例文 2 次の日本語に合うように、 に適当な語を書きなさい。 す。) 1年 Unit 2 Lv2 きません。) 1年 Unit 2 You mugn4 run きますか。) 1年 Unit 2 もいいですか。 ) Lv2 32(2) may not Unit 1 she ③2 (1) あなたたちはここで走ってはいけません。 2 (2) 彼は今日の午後、ベッキーを訪問しないかもしれません。 He Lv ③12 (3) 彼女は3時に家にいるでしょうか。 Lv ③12 (4) 彼はこの重いコンピュータを運ぶことができます。 He 3 次の日本語に合うように、 ( 例文 carry this heavy computer. 日 内の語を並べかえ、正しい英文にしなさい。 Lv1 1 32(1)彼らは10時前に寝なければなりません。 例文① (to / before / they / ten / go / must / bed). 例文 here. 例文 visit Becky this afternoon. 例 at home at three? Lv2 (2)私たちは今日の午後、公園に行くべきです。 例文の いかもしれません。) (the / go / afternoon/to/park/we / should / this か。) ません。) P.8 Lv2 P.8 ③32(3) 授業中にスマートフォンを使ってもよいですか。 (smartphone/I/class/ may / my / in / use )? 例文 さい。 norrow. ] [例文 4 次の英文を ( 内の指示にしたがって書きかえなさい。 なりませんか。) Lv1 です。) I his feelings. What can say when he's giving mel Lv1 Lv1 2 (1) Jane plays tennis well. (「・・・できない」 という文に 例文 〇 ⑩ and gead/valbat) ③2 (2) We can play soccer after school. (「…してもいいですか」という文に 下部の ③2 (3) He makes dinner this evening. (「・・・かもしれない」という文 Gakes Lv3 L ? かな? 例文 ② 例文 0 ③2 (4) Do I have to open the window? (助動詞を使ってほぼ同じ意味の文に) 例文1 luestion? ]JXO Lv2 ③12 (5) She is going to visit your house. (助動詞を使ってほぼ同じ意味の文に) 例文 6 Lv1 [ 例文 ③12 (6) Naoki may listen to music. (否定文に) 例文① -25-

未解決 回答数: 1
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

回答募集中 回答数: 0