• Journal of Digital Contents Society
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• v.9 no.4
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• pp.625-633
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• 2008

Recently, the participation, opening and joint ownership of the users are important issue. The users want professional and accurate information from web. But users often suffer from retrieving accurate information. Even though the users find information they want, it is not guaranteed that the information is reliable since there are too much information placed on the web. Thus, we propose the novel rank metric to promote reliability and efficiency in information retrieval. In order to verify our approach, we implement a web site based on the proposed rank metric for nonofficial medical science information. The proposed rank metric based on user's level. This is to give score of text through differential rate depending on the user's level. The proposed rank metric enhances the reliability of text which is reflecting the user's mental factor. Thus, this method can be used for enhancing the reliability of text.

• Bulletin of the Korean Mathematical Society
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• v.56 no.5
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• pp.1219-1233
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• 2019

Let $E{\rightarrow}M$ be an arbitrary vector bundle of rank k over a Riemannian manifold M equipped with a fiber metric and a compatible connection $D^E$. R. Albuquerque constructed a general class of (two-weights) spherically symmetric metrics on E. In this paper, we give a characterization of locally symmetric spherically symmetric metrics on E in the case when $D^E$ is flat. We study also the Einstein property on E proving, among other results, that if $k{\geq}2$ and the base manifold is Einstein with positive constant scalar curvature, then there is a 1-parameter family of Einstein spherically symmetric metrics on E, which are not Ricci-flat.

• Journal of the Korean Society for information Management
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• v.30 no.1
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• pp.179-191
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• 2013

Since information scientists have begun trying to quantify significant research trends in scientific publications, '-metrics' research such as 'bibliometrics', 'scientometrics', 'informetrics', 'webometrics', and 'citation analysis' have been identified as crucial areas of information science. To illustrate the dynamic research activities in these areas, this study investigated the major contributors of '-metrics' research for the last decade at three levels: nations, institutions, and documents. '-metrics' literature of this study was obtained from the Science Citation Index for the years 2001-2011. In this analysis, we used Pathfinder network, PNNC algorithm, PageRank and several indicators based on h-index. In terms of international collaborations, USA and England were identified as major countries. At the institutional level, Katholieke University, Leuven and the University of Amsterdam in Europe and Indiana University and the Office of Naval Research in the USA have led co-research projects in informetrics areas. At the document level, Hirsch's h-index paper and Ingwersen's web impact factor paper were identified as the most influential work by two methods: PageRank and single paper h-index.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.43-51
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• 2006

This paper proposes a metrics for example matching under the example-based machine translation for English-Korean machine translation. Our metrics served as similarity measure is based on edit-distance algorithm, and it is employed to retrieve the most similar example sentences to a given query. Basically it makes use of simple information such as lemma and part-of-speech information of typographically mismatched words. Edit-distance algorithm cannot fully reflect the context of matched word units. In other words, only if matched word units are ordered, it is considered that the contribution of full matching context to similarity is identical to that of partial matching context for the sequence of words in which mismatching word units are intervened. To overcome this drawback, we propose the context-weighting scheme that uses the contiguity information of matched word units to catch the full context. To change the edit-distance metrics representing dissimilarity to similarity metrics, to apply this context-weighted metrics to the example matching problem and also to rank by similarity, we normalize it. In addition, we generalize previous methods using some linguistic information to one representative system. In order to verify the correctness of the proposed context-weighted metrics, we carry out the experiment to compare it with generalized previous methods.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.656-661
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• 2015

The goal of this paper is to analyze the performance of a word autocomplete system for mobile devices such as smartphones, tablets, and PCs. The proposed system automatically completes a partially typed string into a full word, reducing the time and effort required by a user to enter text on these devices. We collect a large amount of data from Twitter and develop both unigram and bigram dictionaries based on the frequency of words. Using these dictionaries, we analyze the performance of the word autocomplete system and devise a keystroke profit rate and recovery rate as new evaluation metrics that better describe the characteristics of the word autocomplete problem compared to previous measures such as the mean reciprocal rank or recall.

• The KIPS Transactions:PartA
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• v.18A no.1
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• pp.11-18
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• 2011

Cloud computing is a new computing paradigm for sharing resources. Various applications used for cloud services are represented as workflows. These workflow applications must be appropriately allocated to resources or services in cloud. In this paper, a new scheduling algorithm is proposed for multiple workflow applications considering cloud computing environment. The cost-based rank scheduling algorithm considers not only multiple workflow applications, but various QoS metrics for evaluating services. Simulation results show that the proposed algorithm can improve the mean makespan and the availability significantly over two well-known algorithms.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.160-160
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• 2023

Generally, Global Climate Models (GCM) cannot be used directly due to their inherent error arising from over or under-estimation of climate variables compared to the observed data. Several bias correction methods have been devised to solve this problem. Most of the traditional bias correction methods are one dimensional as they bias correct the climate variables separately. One such method is the Quantile Mapping method which builds a transfer function based on the statistical differences between the GCM and observed variables. Laux et al. introduced a copula-based method that bias corrects simulated climate data by employing not one but two different climate variables simultaneously and essentially extends the traditional one dimensional method into two dimensions. but it has some limitations. This study uses objective functions to address specifically, the limitations of Laux's methods on the Quantile Mapping method. The objective functions used were the observed rank correlation function, the observed moment function and the observed likelihood function. To illustrate the performance of this method, it is applied to ten GCMs for 20 stations in South Korea. The marginal distributions used were the Weibull, Gamma, Lognormal, Logistic and the Gumbel distributions. The tested copula family include most Archimedean copula families. Five performance metrics are used to evaluate the efficiency of this method, the Mean Square Error, Root Mean Square Error, Kolmogorov-Smirnov test, Percent Bias, Nash-Sutcliffe Efficiency and the Kullback Leibler Divergence. The results showed a significant improvement of Laux's method especially when maximizing the observed rank correlation function and when maximizing a combination of the observed rank correlation and observed moments functions for all GCMs in the validation period.

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.168-180
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• 2002

This paper proposes a novel method to detect unauthorized copies of digital images. This copy detection scheme can be used as either an alternative approach or a complementary approach to watermarking. A test image is reduced to 8$\times$8 sub-image by intensity averaging, and the AC coefficients of its discrete cosine transform (DCT) are used to compute distance from those generated from the query image, of which a user wants to find copies. Copies may be Processed to avoid copy detection or enhance image quality. We show ordinal measure of DCT coefficients, which is based on relative ordering of AC magnitude values and using distance metrics between two rank permutations, are robust to various modifications of the original image. The optimal threshold selection scheme using the maximum a posteriori (MAP) criterion is also addressed.

• Bulletin of the Korean Mathematical Society
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• v.29 no.1
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• pp.9-13
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• 1992

In this paper, we consider the function related with almost hermitian structure on a copact complex manifold. More precisely, on a 2n-diminsional complex manifold M admitting 2-form .ohm. of rank 2n everywhere, assume that M admits a metric g such that g(JX, JY)=g(X,Y), that is, assume that g defines an hermitian structure on M admitting .ohm. as fundamental 2-form-the 'almost complex structure' J being determined by g and .ohm.:g(X,Y)=.ohm.(X,JY). We consider the function I(g):=.int.$_{M}$ $N^{2}$d $V_{g}$, where N is the norm of Nijenhuis tensor N defined by (J,g). by (J,g).

• The Korean Journal of Ecology
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• v.10 no.2
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• pp.91-107
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• 1987

This study is concerned with some methods and applications, used as a basis on information and entropy analysis of vegetation data. These methods are adopted for the evaluating the effect of sampling intensity on information, which repersnets the departure of observed variable from standard component. Classes on the data matrix are caluculated by using marginal dispersion array for rank and weighting information program. Finally the information and entropy are computed by applying seven options. On the application of vegetation studies, two models for cluster analysis and analysis of concentration are explained in detail. Cluster analysis is based on use of equivocation information and Rajski's metrics. The analysis of concentration utilizes coherence coefficience being transformed values, which has been adjusted from blocks and entropy values. The relationship btween three begetation clusters and four stands of Naejangsan data is highly significant in 79% of total variance. Cluster A relatively tends to prefer north side, and cluster C south side.