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http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
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公安派와 北學派의 尺牘小品文 比較 : 袁宏道와 朴趾源을 중심으로 focusing on Yuan Hong-Dao and Park Ji-Won
李愚一 배화여자대학 2003 培花論叢 Vol.22 No.-
The purpose of this study is to examine the influences between Yuan Hong-Dao(袁宏道)who was the representative of Gong-An School(公安派) in the late Ming Period and Park Gi-Won(朴趾源) who was the representative of Buk-hak school(北學派) in the later period of Joseon Dynasty by analyzing epistolary art's Xiao Pin Wen(尺牘小品文). The results of this comparative study are as follows : Their works had some different or similar things according to their literary theories and backgrounds at that time. That is, there were semblances in their selecting common materials for their works and in their using the literary techniques such as the expression of real emotion(眞情), the good-use of spoken language style(口語體), the good-use of dialogue style(對話體), the expression of humorous style(諧謔體), and the good-use of metaphor style (比喩). However, in the use of language, while Yuan Hong-Dao(袁宏道) used the popular sentence style(通俗體) well in the short and easy sentence, Park Gi-Won(朴趾源) used the relatively long sentence style and wrote the elegant sentence style.
이우일 空軍士官學校 2001 論文集 Vol.48 No.-
Clustering is a property to put the logically related objects, which are likely to be accessed together, in the physically same page, And it is necessary to improve a query processing performance. Also, high storage utilization of the index structure keeps its height low so that the number of pages accessed by a query becomes small. Accordingly, for efficient processing of spatial queries, spatial access methods must not only have the clustering property but also guarantee high storage utilizations. In this paper, we show that the center transformation technique, a kind of SAMs, has the clustering property. Futhermore, we compare the split patterns and storage utilizations of the center transformation technique with those of the corner transformation technique. As a resutl, we show that the center trasnsformation technique is more suitable for uneven distribution of spatial objects such as real data