• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.2
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• pp.290-294
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• 2002

The aim of this study was to investigate in an in vivo model the effects of ethanol extract and ethyl ether and ethyl acetate fractions of Sedum sarmentosum Bunge (SS). To investigate the effects of ethanol extract and ethyl ether and ethyl acetate fractions, Sprage-Dawley female rats were randomly assigned to groups as follows : Sham, OVX-control and ovariectomized rats supplemented with SS at 50 mg/kg bw/day, with SS at 100 mg/kg bw/day, with SS at 200 mg/kg bw/day, with ethyl ether fraction of SS at 10 mg/ka bw/day and with ethyl acetate fraction of SS at 10 mg/kg bw/day. Food intake and food efficiency ratio were not significantly different in groups. But body weight gain was decreased by supplementation of ethyl acetate fraction of SS compared to OVX-control. The levels of total cholesterol and triglyceride in serum were higher in ovariectomized control rats than Sham-operated rats, but supplementation of SS ethanol extracts at 200 mg/kg bw/day decreased the level of the lipid in serum. The level of HDL-cholesterol in serum increased by supplementation of SS ethanol extracts at 200 mg/kg bw/day (p<0.01). The levels of total cholesterol and triglyceride in serum were decreased by supplementation of ethyl acetate fraction of SS (p<0.01). On the other hand, the level of HDL-cholesterol in serum was increased by supplementation of ethyl acetate fraction of SS (p<0.05). On conclusion, it might be expected that ethanol extract and ethyl acetate fraction of SS is believed to be a possible protective effects for the fatty serum increasing serum lipid.

• Korean Journal of Plant Taxonomy
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• v.40 no.4
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• pp.226-233
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• 2010

An intensive study of the embryology of Gymnospermium microrrhynchum was conducted to provide information regarding a discussion of the phylogenetic relationships of the genus, which is yet unstudied. Our results indicated that Gymnospermium is similar to other genera of Berberidaceae in terms of its embryological features. Nevertheless, newly reported and unique features are the well-developed endothelium and the undifferentiated seed coat type. Until the study of Gymnospermium, it may have been considered to be closer to Caulophyllum and Leontice in the tribe Leonticeae. These three genera share many morphological features as well as molecular similarities, by which they are kept in the same tribe, Leonticeae. However, very little detailed embryological data regarding these genera have been published thus far. Gymnospermium was characterized according to the basic type of anther wall formation as well as its glandular tapetum, successive cytokinesis in the microspore mother cell, two-celled mature pollen grains, anatropous and crassinucellate ovules with a nucellar cap, well-developed endothelium, its Polygonum type of embryo sac formation, its nuclear type of endosperm formation, and its undifferentiated seed coat type. In comparison with Nandina, there are many differences, such as the dehiscence of the anther, the cytokinesis in the microspore mother cells, the shape of the megaspore dyad, and the seed characteristics. Although we had no available detailed embryological information regarding Caulophyllum and Leontice, which are genera that are more closely related to Gymnospermium, we could deduce from the phylogenetic relationship that Gymnospermium, Caulophyllum, and Leontice are more closely related to each other than other genera of Berberidaceae on the basis of the seed characteristics.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.23-37
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• 2013

In this paper, the proposed movie recommender system constructs trust network, which is similar to social network, using user's trust information that users explicitly present. Recommendation on items is performed by using relation degree between users and information of recommended item is provided by a visualization method. We discover the hidden relationships via the constructed trust network. To provide visualized recommendation information, we employ Freebase which is large knowledge base supporting information such as movie, music, and people in structured format. We provide three visualization methods as the followings: i) visualization based on movie posters with the number of movies that user required. ii) visualization on extra information such as director, actor and genre and so on when user selected a movie from recommendation list. iii) visualization based on movie posters that is recommended by neighbors who a user selects from trust network. The proposed system considers user's social relations and provides visualization which can reflect user's requirements. Using the visualization methods, user can reach right decision making on items. Furthermore, the proposed system reflects the user's opinion through recommendation visualization methods and can provide rich information to users through LOD(Linked Open Data) Cloud such as Freebase, LinkedMDB and Wikipedia and so on.

• Korean Journal of Microbiology
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• v.32 no.4
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• pp.258-263
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• 1994

Genomic Southern hybridization of Frankia EuIKl strain, a nitrogen fixing symbiont of Elaeagnus umbellate root nodules, with nifH,D of K. pneumoniae as a probe, showed that 3.2 Kb and 5.5 Kb of BamHI fragments and 15 Kb PstI fragment were strongly hybridized with the probe, indicating nifH,D are located on these fragments. Using the same probe, one clone(pEuNIF) was isolated from the genomic library constructed into pWE15 cosmid vector by colony hybridization. The 3.2 Kb and 5.5 Kb BamHI fragments of this clone were hybridized with the same probe and this result corresponds to the genomic Southern hybridization data. However, using nifH of Frankia FaCl strain as a probe, only the 3.2 Kb BamHI fragment showed hybridization signal. Amino acid sequence deduced from nucleotide sequence of 3' terminus of the 3.2 Kb and 5' terminus of the 5.5 Kb fragments showed that the former was highly homologous with that of ArI3 nifD from 182nd to 240th amino acids, while the latter was from 241st to 282nd amino acids. These results show that nifH and partial nifD sequences are located on the 3.2 Kb fragment and residual sequences of nifH on the 5.5 Kb fragment which is contiguous to the 3.2 Kb fragment.

• Journal of Conservation Science
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• v.28 no.4
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• pp.367-376
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• 2012

The ironware production technology is a measure to fathom the society's level of development in time. To understand iron-manufacure methods in the past, various investigations on the fine structures and additions of ironware remains and Iron ingot have been conducted in a way of natural science. This study metallurgically reclassifies remains excavated in iron-manufacture remains located in Beokje, Goyang, which are thought to be in time of Goryeo Dynasty, and draws an inference from the element analysis on the iron-manufacture and smelting technology. Iron ingot samples with a cast iron structure are divided into those with a white cast iron structure and those with a grey cast iron rich in P. The P content of grey cast iron appeared to be the result of adding a flux agent like lime, iron ingot and carbon steel iron ingot with a cast iron structure excavated in the area is regarded as pig iron which was made without a refining process. In this study it seems that two methods of making ironware were used in the area; one is the method of making ironware by pouring cast iron to the casting, and the other is the method of making carbon steel through the refinement of pig iron. It appears that highly even steel structure of carbon steel and a small amount of MnS inclusion are very similar with that of the modern steel to which Mn is artificially added. Nevertheless, these data alone cannot be used to determine the source of Mn in the carbon steel of the excavated from the iron-manufacture remains, which raises the need for further studies on the source and the possibility of carbon steel via the iron-manufacture process of cast iron.

• Journal of Educational Research in Mathematics
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• v.23 no.3
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• pp.335-351
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• 2013

This research assumes that abduction is so important as much as all the creative plausible reasoning to be based upon. We expect it to be deeply appreciated and be taught positively in school mathematics. We are noticing that every problem solving process must contain some steps of abduction and thus, we believe that those who are afraid of abduction cannot solve any newly faced problem. Upon these thoughts, we are looking into the middle school mathematics textbooks to see that how strongly various abductions are emphasized to solve problems in it. We modified types of abduction those were suggested by Eco(1983) or by Bettina Pedemonte, David Reid (2011) and investigated those books to see if, we may regard, various types of abduction be intended to be used to solve their problems. As a result of it, we found that more than 92% of the problems were not supposed to use creative abduction necessarily to solve it. And we interpret this as most authors of the textbooks have emphasis more on the capturing and understanding of basic knowledge of school mathematics rather than the creative reasoning through them. And we believe this need innovation, otherwise strong debates are necessary among the professionals of it.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.595-604
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• 2004

Automatic analysis of concepts or semantic relations from text documents enables not only an efficient acquisition of relevant information, but also a comparison of documents in the concept level. We present a multiple cause model-based approach to text analysis, where latent topics are automatically extracted from document sets and similarity between documents is measured by semantic kernels constructed from the extracted topics. In our approach, a document is assumed to be generated by various combinations of underlying topics. A topic is defined by a set of words that are related to the same topic or cooccur frequently within a document. In a network representing a multiple-cause model, each topic is identified by a group of words having high connection weights from a latent node. In order to facilitate teaming and inferences in multiple-cause models, some approximation methods are required and we utilize an approximation by Helmholtz machines. In an experiment on TDT-2 data set, we extract sets of meaningful words where each set contains some theme-specific terms. Using semantic kernels constructed from latent topics extracted by multiple cause models, we also achieve significant improvements over the basic vector space model in terms of retrieval effectiveness.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.156-172
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• 2003

In this paper we identify that there are High Higher surfaces(HH-surface) around Jeongdongjin and Daejin area where Higher surfaces(H-surface) of marine terrace are formed on a large scale. On the basis of an altitude of the ancient shoreline of the marine terraces, geomorphic surfaces can be classified into HH I (140m a.s.l), HH II (110m a.s.l), H I (90m a.s.l), H II (70m a.s.l), M (40m a.s.l), L I (25m a.s.l) and L II (10m a.s.l). Besides, we identify that the lowest surfaces(5~6m a.s.l) are found extensively in the research area which are assumed to be formed in the Holocene. Considering that the formation mechanism of the marine terraces in the research area is similar to that of the marine terraces at both Campo area in the south east coastal region of Korea md the thalassostatic terraces of Osip River in Samchuk in a short distance from the research area, we can assume that the HH-surfaces in both areas were formed in the same period. Based on the fact that L I- surface was formed on the Last Interglacial Stage of MIS 5, we can infer that M- was formed in MIS 7, H I- in MIS 9, H II- in MIS 11, HH I- in MIS 13 and HH II- in MIS 15. The reason for that H-surfaces, similar to those at Gampo area, to remain on a large scale is that the Holsteinian Interglacial continued for a long period of time and at that time there was a large wave-cut platform in the vicinity of the shoreline.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1314-1323
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• 1999

컴퓨터의 사용이 일반화됨에 따라 데이타를 생성하고 수집하는 것이 용이해졌다. 이에 따라 데이타로부터 자동적으로 유용한 지식을 얻는 기술이 필요하게 되었다. 데이타 마이닝에서 얻어진 지식은 정확성과 이해성을 충족해야 한다. 본 논문에서는 데이타 마이닝을 위하여 퍼지 결정트리에 기반한 효율적인 퍼지 규칙을 생성하는 알고리즘을 제안한다. 퍼지 결정트리는 ID3와 C4.5의 이해성과 퍼지이론의 추론과 표현력을 결합한 방법이다. 특히, 퍼지 규칙은 속성 축에 평행하게 판단 경계선을 결정하는 방법으로는 어려운 속성 축에 평행하지 않는 경계선을 갖는 패턴을 효율적으로 분류한다. 제안된 알고리즘은 첫째, 각 속성 데이타의 히스토그램 분석을 통해 적절한 소속함수를 생성한다. 둘째, 주어진 소속함수를 바탕으로 ID3와 C4.5와 유사한 방법으로 퍼지 결정트리를 생성한다. 또한, 유전자 알고리즘을 이용하여 소속함수를 조율한다. IRIS 데이타, Wisconsin breast cancer 데이타, credit screening 데이타 등 벤치마크 데이타들에 대한 실험 결과 제안된 방법이 C4.5 방법을 포함한 다른 방법보다 성능과 규칙의 이해성에서 보다 효율적임을 보인다.Abstract With an extended use of computers, we can easily generate and collect data. There is a need to acquire useful knowledge from data automatically. In data mining the acquired knowledge needs to be both accurate and comprehensible. In this paper, we propose an efficient fuzzy rule generation algorithm based on fuzzy decision tree for data mining. We combine the comprehensibility of rules generated based on decision tree such as ID3 and C4.5 and the expressive power of fuzzy sets. Particularly, fuzzy rules allow us to effectively classify patterns of non-axis-parallel decision boundaries, which are difficult to do using attribute-based classification methods.In our algorithm we first determine an appropriate set of membership functions for each attribute of data using histogram analysis. Given a set of membership functions then we construct a fuzzy decision tree in a similar way to that of ID3 and C4.5. We also apply genetic algorithm to tune the initial set of membership functions. We have experimented our algorithm with several benchmark data sets including the IRIS data, the Wisconsin breast cancer data, and the credit screening data. The experiment results show that our method is more efficient in performance and comprehensibility of rules compared with other methods including C4.5.