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TOEIC・英語 大学生・専門学校生・社会人

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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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物理 大学生・専門学校生・社会人

A.Bの電流がcにつくる磁場はなぜ図のようになるのか教えてください。 右ねじの法則をどう使えば図のようになるんですか?

例題43 平行電流がおよぼしあう力 図のように, 3本の平行で十分に長い直線状の導線A, B, とBに紙面の表から裏の向きに, Cには逆向きに,いずれも cを, 一辺10cmの正三角形の頂点に, 紙面に垂直に置く。 A 12.0Aの電流を流す。 真空の透磁率を4×10-7 N/A とする。 (1) A,Bの電流が,Cの位置につくる磁場の向きと強さはい くらか。 (2)導線Cの長さ 0.50mの部分が受ける, 力の向きと大きさはいくらか。 指針 (1) ねじの法則を用いて, A, B の電流がCの位置につくる磁場を図示し, それ らのベクトル和を求める。 磁場の強さは. H=I/(2πr) の式を用いて計算する。 (2) フレミングの左手の法則から力の向きを, 磁場 261 発展問題 524 10cm B ので,Ha=H, である。 合成磁場は,図の右 向きとなる。 H, HB は, I 2.0 10 H=HB= = = - [A/m〕 2лr 2×0.10 π 合成磁場の強さHは, F=1JHI の式から力の大きさを求める。H=2×Hacos30°=2x10x1 08 π =5.50A/m 5.5A/m 10/3 = π 解説 F30° 電流の大きさは等しく, Cまでの距離も等しい (1)A,Bの電流がC の位置につくる磁場 A,Bは,右ねじの 法則から、図のように なる。HA,HB は,そ れぞれ AC, BC と垂直である。また,A,Bの -HB CQ H (2) フレミングの左手の法則から, 導線Cが受 ける力の向きは,AB と垂直であり,図の上 HA 向きとなる。 力の大きさFは, AQ &B 10√3 F=μolHl=(4×10-7) x2.0x -×0.50 π =6.92×10-N 6.9×10-N

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