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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

<p><strong>Online Nursing Class Course Design Principles</strong></p> <p>In the rapidly evolving landscape of education, online nursing ... 続きを読む

【複素積分】(1)の解き方を教えていただけないでしょうか。

正の方向のジョルダン曲線 (Jordan curve) C の上と内部で複素関数f(z) が正則である とき、 曲線Cの内部の任意の点で、 f(20) = が成立する。 これをコーシーの積分公式という｡ f'(zo) 問題 2.3 次の複素積分の値を求めよ。 ただし、 閉曲線は正の方向に1周するものとする。 3 2 (1) Long [(z − 1)² + z ²³ ; − (2 ² ¡js) dz dz (2) √₁41-2 (3) Sal= dz (4) √121-3 |z|=3 (-2)(z +4) f" (20) 1 f(z) 2mi JcZ0 f(n) (zo) 22-9 dz コーシーの微積分公式 (Cauchy's differentiation formula) 正の方向のジョルダン曲線Cの上と内部で複素関数f(z) が正則であるとき、 任意の階 数の導関数はこの領域で正則であり、 次式で与えられる。 = = dz 1 f(z) 2πi Jc (z-zo)² n! maile dz 2! 27i Sc (z=-²20) ³ f(z) (20)n+1 (5) dz (6) (7) (8)

すみません。なにも理解していません。教えていただけると嬉しいです。

n 30%の確率で不良品を作ってしまう工作機械があるとする.この機械が製品を4個作った とき,そのうち2個が不良品である確率はいくつ また,不良品が2個以下である確率はいくつか。 演習問題 六郎で、通続型 十 類の回さ) 不良品が2個の確率 本ロ p n

定積分の計算で∫∂/∂x～～～dxというような形の式があるのですが、この場合 ∂/∂xがあるので先に～～～の部分をxで微分してからxで定積分するということでしょうか。

This assumption may be valid because the air column being considered is deeper than the nocturnal turbulent boundary layer. QE is the latent heat flux which is released into the air column with the phase change of water vapor. When there is no phase change of water vapor, QE=0. QR is the heat flux of the long wave radiation and defined by QR=pC * a 0z where (30 /a1), s the warming rate of air due to convergence of long wave radiation, L t(z) and L(2) are the upward and downward long wave radiation at a height of z respectively. Among several kinds of calculation methods for long wave radiation (Stephens, 1984), formulae

多様体の接空間に関する基底定理の証明です。g(q)=∫〜と定義した関数を微積分学の基本定理を用いながら変形してg(q)=g(0)+∑gᵢuⁱと導出するのですが、これがうまくいきません。 自分は、g(q)の式をまず両辺tで微分して、次に両辺uⁱで積分して、最後に両辺tで積分... 続きを読む

12. Theorem.If{ = (x', , x") is a coordinate system in M at p, then its coordinate vectors d, lp, …… 0,l, forma basis for the tangent space T,(M); and D= E(x) 。 i=1 for all ve T(M). Proof. By the preceding remarks we can work solely on the coordinate neighborhood of G. Since u(c) = Othere is no loss of generality in assuming ど(p) = 0eR". Shrinking W if necessary gives E(W) = {qe R":|q| < } for some 8. Ifg is a smooth function on E(W) then for each 1 <isndefine og (tq) dt du g(9) = for all qe {(W). It follows using the fundamental theorem of calculus that g= g(0) + E&,u' on (W). Thus if fe &(M), setting g = f。' yields f= f(P) + Ex on U. Applying d/ax' gives f(p) = (f /0x)(P). Thus applying the tangent vector e to the formula gives (f) = 0+ E(x'(p) + E Ap)u(x) = E(Px). ず ax Since this holds for all f e &(M), the tangent vectors v and Z Ux') d,l, are equal. It remains to show that the coordinate vectors are linearly independent. But if ) a, o.l, = 0, then application to x' yields dxi 0=24 (P) = 2q d」= 4. In particular the (vector space) dimension of T,(M) is the same as the dimension of M.

この図が理解できません。真ん中のp53とmdm2の図の次に矢印が二手に分かれてるのはなぜですか？

Oncogenic Stimulation (E1A, c-Myc,E2F-1, Ras) DNA Damage ,UV Hypoxia Hypoglycemia BRCA1 (ATM, DNA-PK. ATR) P19ARF HIF1a p53 p53 Degraded acetylat ion Stable dephosphorylation mdm2 is an ubiquitin ligase targeting P53 to proteolytic degradation p53 Stable and Active Transactivation of target genes PAG608 IGF-BP3 PIG3 KILLER/DR5 P21(WAF1) GADD45 14-3-36 BAX FAS/APO1 CKI Repair Apoptosis 00 Eom2

アルファベットとひらがなを組み合わせるのですが… 英語を訳してもなかなか対にすることができず困っています。生物や英語が得意な方力を貸してください。

Xの語群を正しく並べなさい。 a)Unmyelinated fiber 呆條人 b)Betz cell > c)Auditory system 但 Perception Deafness 受 eのWada method ws WW (2 Eye ball movement AD g)Nervus chorda tympani 代訂0 [4 h)Pyramidaltract 殺人 1)Primary motor area -を3 1)Right parietal cortex 7才 k)Cerebrocerebellum [2 Endolymph 骨- 。 m)Olfactory bulb # n)Inferior oiive でポイ o)Archicerebellum 只 p)Deep Brain Stimulation 2半 g)Autosomal dominant inheritancei *) Hippocampus 半ち 9)ERlectromyograph 昨史 t) Reticular activating sy8temm