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TOEIC・English Undergraduate

このプリントの穴埋めをして英文和英しなさいという問題です。助けてください

英語2A レポート課題(2026年前期) 以下の英文中の( 内に入れるのに適切と思われる1語を、 下の 入れなさい。 そのうえで全文を和訳しなさい。 の中から選んで ite of national diger Most funny stories are based on comic situations. In spite of national differences, certain funny situations have a ( 1 ) appeal. No matter ( 2 ) you live, you would find (3) difficult not to laugh at, say, Charlie Chaplin's early films. However, a new type of humor, called 'sick humor', has come into fashion. The following example of 'sick humor' will enable you to judge for yourself. A man ( 4 ) had broken his right leg was taken to a hospital a few days before Christmas. From the moment he arrived there, he kept on annoying his doctor to tell him ( 5 ) he would be able to go home. He felt afraid ( 6 ) having to spend Christmas in the hospital. On Christmas Day, the man still had his right leg in plaster. He spent a miserable day in bed thinking of all the ( 7 ) he was missing. The following day, however, the doctor consoled him by telling that his chances of being able to leave the hospital ( 8 ) time for New Year Celebrations were ( 9 ). The man took heart and, sure enough, on New Year's Eve he managed to walk along to a party. To ( 10 ) for his unpleasant experiences in the hospital, the man drank a little more than was good for him. He was still grumbling about hospitals at the end of the party when he slipped on a piece of ice and broke his left leg. blame compensate money yourself where of in at by with fun good whose who it when special universal

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TOEIC・English Undergraduate

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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TOEIC・English Undergraduate

今からこの問題のテストがあります! 答えを教えて頂きたいです!

I. mani"X" bnt Quiz 1al insmatste pniwallolantOpel llsw art no ftel mooooysterio Fill in the blanks with the appropriate words or phrases to match the following statement. 01. インターネットのない生活なんて想像もできない。 ) hardly imagine life without the Internet. ) 1 g to brossert) asyl as all anoutalbBQ rexland bed new pail nail art Innil bonteal V 30 ns ahenda sill lent benelque asinspo dT 80 nuzelmibe jut eg lon ed of ar leum and TO asamem Viimist lie yd have 02. コックピットは安全な場所どころではない。 The cockpit ( ) ( ) ( )( )( ) place. 03. 電話を切るやいなや、 また電話が鳴った。 No sooner ( ( oyoT yd ourpoind aew | 80 beaute all tudominib otomoomin bates Wo Hood art stelgmus al emot ansay wool 1.01 ) hung up than the phone rang again. 04. 愛というものは、言わば、心のための栄養である。LIGHmment na ro Love is, so ( ) ( ), a nutrient for the heart. bongenadyeing alt 05. 彼は毎晩誰かが事務所に残っていたらよいと提案した He ( ) that someone stay in the office every night. Vew art to to slam of soigston art live to draw all Co 06. 担保付きのローンから始めた方がよいと勧めたい。 I would ( ) that you start out with a secured loan. hom yde slevou a to poles conse of categ 07. 「ご用は承っておりますか」 「ありがとう。 ただ、 ぶらりとみているだけです」 "Are you (m) (i)?" "Thanks. I'm just browsing." nort 08. 先生が見えるまで、ロビーでお掛けになってお待ちになってください」 ) in the lobby while you wait for the doctor to arrive!" “Please be ( 09. パソコンがあれば、こんな手間はすべて省けますよ。 (パソコンを使えばこの手間はすべて省ける) Als) (c) you all this (c). A personal computer ( 10. 雨が激しく降っていたにもかかわらず、彼女は仕事に行った。 ) ( ) the heavy rain, she went to work. ( )( TO

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