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    <title>Repository Collection:</title>
    <link>https://scholarworks.unist.ac.kr/handle/201301/56</link>
    <description />
    <pubDate>Wed, 13 May 2026 05:31:14 GMT</pubDate>
    <dc:date>2026-05-13T05:31:14Z</dc:date>
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      <title>Mandatory disclosure in oligopolistic market making</title>
      <link>https://scholarworks.unist.ac.kr/handle/201301/91673</link>
      <description>Title: Mandatory disclosure in oligopolistic market making
Author(s): Kim, Seongjin; Choi, Jin Hyuk
Abstract: We develop a multi-period Kyle-type model that incorporates both mandatory disclosure of informed trades and imperfect competition among market makers. We prove the existence and uniqueness of a linear equilibrium and show that the liquidity-enhancing effect of disclosure is fundamentally linked to the degree of market-making competition. Disclosure lowers trading costs by reducing price impact, and its marginal benefit is strictly larger when competition is weak. We empirically validate this prediction using the 2002 Sarbanes-Oxley Act disclosure reform as a natural experiment. A difference-in-differences analysis of U.S. equities confirms that the spread reduction following enhanced disclosure is significantly larger for stocks with fewer active market makers.</description>
      <pubDate>Sun, 31 May 2026 15:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.unist.ac.kr/handle/201301/91673</guid>
      <dc:date>2026-05-31T15:00:00Z</dc:date>
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    <item>
      <title>GLOBAL REGULARITY FOR SOME AXISYMMETRIC EULER FLOWS IN Rd</title>
      <link>https://scholarworks.unist.ac.kr/handle/201301/91600</link>
      <description>Title: GLOBAL REGULARITY FOR SOME AXISYMMETRIC EULER FLOWS IN Rd
Author(s): Choi, Kyudong; Jeong, In-Jee; Lim, Deokwoo
Abstract: We consider axisymmetric Euler flows without swirl in Rd with d &gt;= 4, for which the global regularity of smooth solutions is an open problem. When d = 4, we obtain global regularity under the assumption that the initial vorticity satisfies some decay at infinity and is vanishing at the axis. Assuming further that the initial vorticity is of one sign guarantees global regularity for d &lt;= 7.</description>
      <pubDate>Wed, 31 Dec 2025 15:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.unist.ac.kr/handle/201301/91600</guid>
      <dc:date>2025-12-31T15:00:00Z</dc:date>
    </item>
    <item>
      <title>Some applications of the traces of Frobenius of elliptic curves in a certain family</title>
      <link>https://scholarworks.unist.ac.kr/handle/201301/91244</link>
      <description>Title: Some applications of the traces of Frobenius of elliptic curves in a certain family
Author(s): Cho, Peter J.; Yoo, Jinjoo
Abstract: Let J = {a, b} be an unordered pair of elements of Fq and EJ the associated elliptic curve of the form y 3 = (x − a)(x − b) over Fq. Using its trace of Frobenius, we obtain several applications. We first compute the average analytic rank of elliptic curves for our family and generate elliptic curves with designated extremal primes. Furthermore, we determine explicit and average values on class numbers of every constant field extension of KJ := Fq(T, p3 (T − a)(T − b)). Finally, we estimate the exact values and average values on Euler-Kronecker constants of KJ .</description>
      <pubDate>Fri, 31 Jul 2026 15:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.unist.ac.kr/handle/201301/91244</guid>
      <dc:date>2026-07-31T15:00:00Z</dc:date>
    </item>
    <item>
      <title>Valid oversampling schemes to handle imbalance</title>
      <link>https://scholarworks.unist.ac.kr/handle/201301/90577</link>
      <description>Title: Valid oversampling schemes to handle imbalance
Author(s): Kim, Young-geun; Kwon, Yongchan; Paik, Myunghee Cho
Abstract: An imbalance is one of the problems in machine learning. When data are not balanced, the correct specification rate for the minor class suffers even if accuracy is high. The oversampling method has been used to address the issue without consideration about the sacrifice of accuracy. In addition, an arbitrary oversampling scheme may introduce bias. In this paper, we propose principled methods of handling imbalance under user-specified constraints on the sensitivity and specificity. Our work consists of three elements of contributions. First, we provide an optimized target proportion that minimizes the maximum error rate under user-specified constraints on sensitivity and specificity. Second, we introduce the notion of resampling at random (RAR) under which the limit of the estimator is not altered from the original sample. These two elements are relevant to any classification methods. Third, we derive asymptotic properties of selected classifiers when we apply RAR oversampling with the target proportion. Finally, we implement the proposed method in an image recognition context using the extracted feature from the last layer of deep convolutional neural networks (CNNs). We present an analysis of fundus data to classify diabetic retinopathy using the proposed method. (C) 2019 Elsevier B.V. All rights reserved.</description>
      <pubDate>Sun, 30 Jun 2019 15:00:00 GMT</pubDate>
      <guid isPermaLink="false">https://scholarworks.unist.ac.kr/handle/201301/90577</guid>
      <dc:date>2019-06-30T15:00:00Z</dc:date>
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