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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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Physics Senior High

(3)で運動方程式に重力が入っていないのであれっ?となったのですが…入ってなくて大丈夫なのですか?

82 亀場中の荷電粒 次の文の に適当な式を記入せよ。 真空の空間に。 図に示すように間隔d, 長さ1の平行板電極を置く。 電極と平行 に軸、垂直に軸をとり, 原点Oは図 のように電極の左端とする。 電極の中心 からしだけ離れてx軸に垂直に蛍光面を 置く。 下の電極を接地し,上の電極に正 電子 V mc -e YA 電極 TA + + + + + d ・L・ 5 蛍光面 V の電圧Vを加え,質量m,電荷 -e である電子をx軸上で正の方向に速さ が電場から受ける力はy軸の正の向きで大きさ (2) となり, 電子の加速 でうちこむ。電極間の電場はy軸の負の向きで強さは (1) である。電子 (3) となる。 電極間ではこの加速度は一定である。 電子が電極間を 度は 通過する時間は 1/3となるから、電極間を通過する間のy軸方向の変位は (4) となる。 電極間を出た後,電子は電極間を出るときの速度の成分 たがって電極の間にうちこまれてから蛍光面に達するまでのy 軸方向の変位 と成分からなる等速直線運動をし,変位 y2 だけ上方で蛍光面に至る。し となり, m, e, V, d, l, L およびぃの関数で与えら はy=y+y2=(5) れる。 また,紙面に垂直に適当な大きさの磁場をかけると電子は等速直線運動を して, 蛍光面上の y=0 の点に達するようになる。 このとき、電子が電場か ら受ける力と磁場から受ける力のつりあいより, 磁束密度の強さは (6) (法政大) (7) に向かう向きである。 であり,その向きは紙面に垂直で

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