• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.744-748
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• 2008

In this paper, we propose a novel technique that generate a new song with given example songs. Our system use k-th order Markov chain of which each state represents notes in a measure. Because we have to consider very high-dimensional space if we use notes in a measure as a state of Markov chain directly, we exploit a hierarchical clustering technique for given example songs to use each cluster as a state. Each given examples can be represented as sequences of cluster ID, and we use them for training data of the Markov chain. The resulting Markov chain effectively gives new song similar to given examples.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.301-309
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• 2009

Multidimensional scaling(MDS) is a statistical multivariate analysis technique that is often used in information visualization for exploring similarities or dissimilarities in data. In order to analyse and visualize data, MDS measures the dissimilarities between objects and uses them or their mean if they are repeatedly measured. When there exist outliers or when the variation of data is too large, we can hardly get reliable results on the research using MDS. In this paper, we consider the MDS based on bootstrap method when the variation of data is large. Standardized residual sum of squares is considered as measuring goodness-of-fit of the model. A real data analysis is include to examine our approach.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.4
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• pp.447-456
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• 2020

Peanut is an allotetraploid derived from a single recent polyploidization. Polyploidization has been reported to have caused significant loss in genetic diversity during the domestication of cultivated peanuts. Single nucleotide polymorphism (SNP)-based markers such as cleaved amplified polymorphic sequences (CAPS) derived from next-generation sequencing (NGS) have been developed and widely applied for breeding and genetic research in peanuts. This study aimed to identify the genetic diversity and population structure using 30 CAPS markers and 96 peanut accessions from five different origins. High genetic dissimilarities were detected between the accessions from Korea and those from the other three South American origins generally regarded as the origin of peanuts, while the accessions from Brazil and Argentina presented the lowest genetic dissimilarity. Based on the results of the present study, accessions from Korea have unique genetic variation compared to those from other countries, while accessions from the other four origins are closely related. Our study identified the genetic differentiation in 96 peanut accessions from five different origins, and this study also showed the successful application of SNP information derived from re-sequencing based on NGS technology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4386-4404
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• 2016

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q's adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

• School Mathematics
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• v.15 no.1
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• pp.15-35
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• 2013

The purpose of the research is to categorize math learners into pattern through those tools that distinguish math learning style for middle school students. On the ground of survey for 976 middle school students, the fact that there are 16 different math learning style at the result of cluster analysis is confirmed and the results are compared and analyzed previous research. Also according to the each constituent of math learning style, dissimilarity of distribution about learner of different sexes and grades are analyzed. It's helpful to understanding the whole characteristics of learners regarding math learning to figure out their cognitive and affective learning styles through the tools to distinguish their math learning styles.

• Steel and Composite Structures
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• v.15 no.5
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• pp.519-538
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• 2013

The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.99-110
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• 2007

A single slab concrete pavement has been modeled and analyzed by ABAQUS program. The stress and displacement of the JCP slab under traffic load with frictionless contact interaction between slab and base calculated by ABAQUS program have been compared with the results obtained by KENSLABS program. The results of the stresses of the two modeling show similar tendency and the difference of the two modeling is very small however the results of the displacement of the two modeling show some dissimilarity. In order to analyze the effects of material and geometric properties on the responses of slab, some varying parameters were chosen as input for the modeling. The changing parameters include the thickness and elastic modulus of the concrete slab, the thickness and elastic modulus of base and the elastic modulus of the subgrade. The contact interaction between the slab and base layer had been also studied and different friction coefficient 0, 2.5, 6.6, 7.5, 8.9 had been used to simulate the different friction interface condition. The results of the analysis showed that the responses of the concrete slab vary with the material and geometric properties of the pavement structure and the slab-base friction condition.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.1
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• pp.123-129
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• 2020

Intra-industry trade (IIT) has played an important role in international trade of Vietnam as a result of rapid growth of the country. This article investigates the level of IIT between Vietnam and 11 trading partners in Trans-Pacific Partnership (TPP) over the period 2000-2014. Although there have been a large number of empirical researches contributed to the determinants of IIT, most of them only pay attention on developed countries where the trade flows are similar due to similar demand structure and production technology. Until now, there is no study on intra-industry trade between Vietnam and countries in TPP that Vietnam recently signed a trade agreement in early 2016. IIT is measured by the Grubel-Lloyd index. The index shows that the extent of intra-industry trade between Vietnam and the trading countries is not high due to the level of economic development and the market size. The determinants of IIT are examined using a panel regression model. In the empirical analysis, the results indicate that Vietnam's intra-industry trade is positively correlated with country size, while it is negatively correlated with income dissimilarity, the trade openness, and geographical distance. This study contributes to the new theoretical trade theory on the evidence of developing country's IIT.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.877-881
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• 2005

In this paper, a novel method for analyzing a textile fabric structure is proposed to segment each yarn of the textile fabric from voxel data made out of its X-ray computed tomography (CT) images. In order to segment the each yarn, directions of fibers, of which yarn consists, are firstly estimated by correlating the voxel with a fiber model. Second, each fiber is reconstructed by clustering the voxel of the fiber using the estimated fiber direction as a similarity. Then, each yarn is reconstructed by clustering the reconstructed fibers using a distance which is newly defined as a dissimilarity. Consequently, each yarn of the textile fabric is segmented from the voxel data. The effectiveness of the proposed method is confirmed by experimentally applying the method to voxel data of a sample plain woven fabric, which is made of polyester two folded yarn. The each two folded yarn is correctly segmented by the proposed method.

• East Asian Journal of Business Economics (EAJBE)
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• v.7 no.2
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• pp.21-30
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• 2019

Purpose - In this work, we categorize the 21 shopping items which foreign tourists purchase in South Korea and monitor the level of dissimilarity (or similarity) between each item by utilizing distance matrix, and both hierarchical and k-means cluster analyses, respectively, based on several purpose of visit attributes in 2017. In addition, multidimensional scaling (MDS) method is applied for mining visual appearance of proximities among shopping items based on purpose of visit attributes. Research design and methodology - This study is carried out in 2017 by Ministry of Culture, Sports and Tourism and conduct a face-to-face survey of foreign tourists from 20 countries who purchase shopping items in South Korea. CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0 are used to perform this work. Results - We ascertain that 21 shopping items can be classified into five similar groups which have homogeneous traits by going through two-step cluster analysis. We can position homogeneous places of cluster and shopping items joining each cluster. Conclusions - We can relatively assess patterns and characteristics of each shopping item, come by useful information in activating shopping tour based on the actual state of recognition of foreign tourists and practically apply to each tourism industry on underlying results.