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Korean 8m Class Optical Facility: Gemini Observatory

  • Hwang, Narae;Kim, Minjin;Yang, Soung-Chul;Lee, Ho-Gyu;Lee, Jae-Joon;Yuk, In-Soo;Sheen, Yun-Kyeong;Park, Byeong-Gon
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.2
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    • pp.43.4-43.4
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    • 2018
  • As of July 24th 208, Korea Astronomy and Space Science Institute (KASI) has entered into a formal partnership with the Gemini Observatory. The Gemini Observatory has been operated by Association of Universities for Research in Astronomy (AURA) on behalf of the International Partnership that includes Argentina, Brazil, Canada, Chile, United States, and Korea as the new partner country. Effective from the 209A Call for Proposals (CfP), any researchers affiliated with Korean institutes are eligible to apply for various observing opportunities in both hemispheres covered by Gemini North in Hawaii and by Gemini South in Chile. We are going to share the importance and long-term perspectives of the KASI-Gemini Partnership in the context of the next decade of Korean optical astronomy researches.

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Overview of MPEG Dynamic Mesh Coding (DMC) for Volumetric Video (볼류메트릭 비디오를 위한 MPEG Dynamic Mesh Coding (DMC) 표준화 동향)

  • Choi, YiHyun;Jeong, Jong-Beom;Lee, Soonbin;Ryu, Eun-Seok
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.261-264
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    • 2022
  • MPEG 에서는 frame-based animated mesh compression(FAMC)와 같은 동적 메쉬를 압축하는 기준을 만들어왔다. 그러나 이러한 동적 메쉬 압축 표준은 시변 연결성(time-varying) 정보가 아닌 일정한 연결성 정보를 가진 메쉬를 기준으로 개발되었기 때문에 실시간 스트리밍에서 사용하기 부적합하다. 따라서, moving picture experts group(MPEG)에서는 시변 연결성 정보를 사용하는 동적 메쉬 압축에 대한 새로운 표준을 제안하였는데, 본 논문에서는 MPEG 이 제의한 call for proposals (CfP)에 대해 여러 기관들이 제안한 메쉬 압축 기술들을 소개한다.

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Ideology, Politics, and Social Science Scholarship on the Responsibility of Intellectuals

  • Koerner, E.F.K.
    • Lingua Humanitatis
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    • v.2 no.2
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    • pp.51-84
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    • 2002
  • The 1990s have seen the publication of many books devoted to Language and Ideology (cf. Joseph & Taylor 1990. for one of the early ones) even though the term 'ideology' itself has remained ill-defined (Woolard 1998). The focus of attention has usually been placed on the particular use of language and often for some kind of 'political' ends, not on linguistic or other scholarship which might have been driven by some sort of ideology, i.e., a bundle of assumptions which themselves were taken as given. At least since Edward Said's 1978 book Orientalism, it has been clear to everyone that scholars construct their conceptualization of things in line with their understanding of the cultural, social, and political world in which they live, and that this often unreflected 'pre-understanding' effects their view of cultures that are different from theirs and more often than not geographically and temporally distant from theirs. This recognition has had a sobering effect no doubt, and Said's book has long since become 'mainstream.' Much more disturbing to the scholarly profession has been the publication of Martin Bernal's Black Athena in 1987, since it went much further, going beyond accusations of colonialism and cultural bias, in suggesting that the Western representation of Classical Greece over the past two hundred years was false and that what had been accepted until now about occidental antiquity must now be seen derived from African-Asiatic cultures of the Near East, notably that of the Ancient Egyptians, and that no other than Socrates should be seen as black man. While we may understand the intellectual climate in the United States that led academics to present 'myth as history' (Lefkowitz 1996), it is obvious that lines of regular scholarly principles of investigation have been crossed (cf Lefkowitz & Rogers 1996). The present paper investigates what may be seen as the ideological underpinnings of such work. After reviewing some recent scholarship in the area of linguistic historiography that have shown that academic work has never been 'value-neutral' (as may have been assumed or has been claimed by some practitioners), it is argued that in effect one must be aware of what Clemens Knobloch has recently termed Resonanzbedarf, i.e., the desire, whether conscious or not, of scholars-and probably scientists, too-to have their work recognized by the educated public and that, in so doing, their discourses tend to pick up on contemporary popular notions. These efforts may be harmless if everyone was to recognize these allusions and adoption of certain lexical. items(buzz words) as props or what Germans call Versatzstiicke, but history tells us that this has not always been the case. Still, as Hutton (1999) has shown, not all scholarship during the Third Reich for example can simply be dismissed as worthless because it was conducted in under a prevailing political ideology. Indeed, in seemingly innocent times, linguists can be shown to frame their argument in a way that makes them appear so utterly superior to their predecessors (cf. Lawson 2001). Upon closer inspection, those discourses turn out to be much like those of scholars in nationalistic environments that have tended to select their 'facts' to prove a particular hypothesis (cf., e.g., Koerner 2001). The article argues for scholars to take a more active role in exploding myths, scientifically unfounded claims, and ideologically driven distortions, especially those that are socially and politically harmful.

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Data BILuring Method for Solving Sparseness Problem in Collaborative Filtering (협동적 여과에서의 희소성 문제 해결을 위한 데이타 블러링 기법)

  • Kim, Hyung-Il;Kim, Jun-Tae
    • Journal of KIISE:Software and Applications
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    • v.32 no.6
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    • pp.542-553
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    • 2005
  • Recommendation systems analyze user preferences and recommend items to a user by predicting the user's preference for those items. Among various kinds of recommendation methods, collaborative filtering(CF) has been widely used and successfully applied to practical applications. However, collaborative filtering has two inherent problems: data sparseness and the cold-start problems. If there are few known preferences for a user, it is difficult to find many similar users, and therefore the performance of recommendation is degraded. This problem is more serious when a new user is first using the system. In this paper we propose a method of integrating additional feature information of users and items into CF to overcome the difficulties caused by sparseness and improve the accuracy of recommendation. In our method, we first fill in unknown preference values by using the probability distribution of feature values, then generate the top-N recommendations by applying collaborative filtering on the modified data. We call this method of filling unknown preference values as data blurring. Several experimental results that show the effectiveness of the proposed method are also presented.