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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

テストの過去問に解答がなく、答えがわからないので英語得意な方教えていただきたいです🤲明日がテストなので早めに解答をいただけるとありがたいです🙇‍♀️

Ⅱ 次の英文を読み, 問に答えよ。 2.2.2. Consumer test それぞれ異なる容量の1つのキューブ (10) Consumers were recruited among workers from the Instituto de Agroquímica y Tecnología de Alimen- tos, Valencia, Spain. Thirty persons, 22-60 years old, approximately half female, half male, who consumed apples frequently, were used for the study. Consumers received one cube from each different storage time fol-following lowing a balanced complete block experimental design. For each sample they had to score global acceptability of the product using a nine-box) scale labeled on the left with “dislike very much', in the middle with indiffer- ent" and on the right with "like very much". They also answered the question “Would you normally consume this product?" with a yes or a no (Hough et al., 2003; Gámbaro et al., 2004a,b). ロロロ B 問1. 本文中に記載されている試験方法は, 何を何するかどうかを問うものである。 "( A ) ( )する場合の試験” と答える場合に, (A) と(B)に当てはまる単語を英語で答えよ。 問2. 何人のパネルに試験しているのかを答えよ。 問3.ここで示されている食品の官能評価法をもっとパネルが評価しやすく回答しやす いようにするには, どうしたらよいか答えよ。 問4. パネルの男女比はどの程度であると述べているか答えよ。 5. この英文に書かれている内容に沿った官能評価シートを作成せよ。 以上

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