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TOEIC・英語 大学生・専門学校生・社会人

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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物理 大学生・専門学校生・社会人

どうして153番では1番最初の位置エネルギーを考えないのですか?152番では最初の位置エネルギーをUaと置いているので、153でもそのようにやろうと思ったらうまく行きませんでした。

[知識] 第Ⅰ章 運動とエネルギー 152. 連結された物体と摩擦 図のように,粗い水平 A 面上に置かれた質量Mの物体Aが,なめらかな滑車 を介して,質量mの物体Bと軽い糸でつながれている。 Bを静かにはなすと, Aが距離Dだけすべり, 水平面 M 10000000 D→ B m 上に固定された軽いばねと衝突して, ばねをxだけ押し縮め, 物体A,Bの運動が停止 した。 Aと面との間の動摩擦係数をμ, 重力加速度の大きさをg とする。 Aがばねと衝突する直前の, 物体AとBの運動エネルギーの和と速さを求めよ。 (2)Aがばねと衝突してから停止するまでの間において, ばねの弾性力による位置エ ネルギーの変化を, m, M, D, x, μg を用いて表せ。 思考 記述 三角比 (和歌山大 改) 20.M A B m 153. 動摩擦力と仕事図のように,水平とのなす角が 0の粗い板の上に、質量Mの物体Aを置き, 軽いひもの 一端をAにつなぐ。 ひもは板と平行に張って滑車にかけ, ひもの他端に質量 m (m <M)の物体Bを鉛直につり下 げる。 この状態から物体Bを静かにはなしたところ, 物 体Aは板に沿って下向きにすべり始めた。 Aが板の上を 距離すべりおりたときについて,次の各問に答えよ。 ただし,重力加速度の大きさをg, 板と物体Aとの間の動摩擦係数をμ'とし, 滑車はな めらかに回転できるものとする。 (1) 距離すべりおりたときの物体Aの速さを”とする。 A, B 全体の力学的エネル ギーの変化量 4Eを, M, m, 1, 0, vg を用いて表せ。 (2) 物体Aの速さ”を,M,m, 1, 0,μg を用いて表せ。 ach (3)この運動における物体Aの力学的エネルギーの変化量 ⊿EAは,正,負, 0 のいず れか。 理由とともに答えよ。 ( 12. 奈良女子大改) 例題10

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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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