• Speech Sciences
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• v.8 no.2
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• pp.181-191
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• 2001

The acoustic quality of a vowel is known to be mostly determined by the frequencies of the first formant(Fl) and the second formant(F2). The perceptual(or psychological) dimensions of vowel perception were examined in this study. Also the relationships among perceptual dimensions, acoustical dimensions(Fl & F2), and articulatory gestures of vowel were discussed. Using multi-dimensional scaling(MDS) technique, the experiment was performed in order to identify the perceptual dimensions of the perception of Korean vowel. In the experiment 8 Seoul standard speakers performed the similarity rating task of 10 synthesized Korean vowels. Two-dimensional MDS solution based. on the similarity rating scores was obtained. The results showed that two perceptual dimensions, D1 and D2 were correlated strongly with F2 and F1(r = -.895 and .878 respectively), and were so interpreted as 'vowel advancement' and 'vowel height' respectively. The relationship between the perceptual dimensions of vowel and the articulatory positions of tongue suggested that perception may be directly linked to production. Further research problems were discussed in the .final section.

• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2433-2442
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• 2011

The three dimensional quantitative structure activity relationship (3D QSAR) models were developed using Comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and docking studies. The fit of Quinazolinone antifolates inside the active site of modeled bovine dihydrofolate reductase (DHFR) was assessed. Both ligand based (LB) and receptor based (RB) QSAR models were generated, these models showed good internal and external statistical reliability that is evident from the $q^2_{loo}$, $r^2_{ncv}$ and $r^2_{pred}$. The identified key features enabled us to design new Quinazolinone analogues as DHFR inhibitors. This study is a building bridge between docking studies of homology modeled bovine DHFR protein as well as ligand and target based 3D QSAR techniques of CoMFA and CoMSIA approaches.

• Journal of Ocean Engineering and Technology
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• v.23 no.4
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• pp.32-37
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• 2009

An analytic similarity shape solution was studied for a two-dimensional floating and fluid-filled membrane structure. The static shape of a membrane structure can be expressed as a set of nonlinear ordinary differential equations. The integration of curvature leads to an analytic solution for the shape, which contains unknown boundary values. Matching the upper and lower shapes at the free surface incorporated with their buoyancy allowed the unknowns to be determined. Some characteristic values of similarity shapes were evaluated and shapes are illustrated for various density ratios and volume efficiency ratios.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.65
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• pp.41-50
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• 2001

Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and intercluster similarity is minimized. The discovered clusters from clustering process are used to explain the characteristics of the data distribution. In this paper we propose a new methodology for clustering related transactions with categorical attributes. Our approach starts with transforming general relational databases into a transactional databases. We make use of inter-dimensional association rules for composing hypergraph edges, and a hypergraph partitioning algorithm for clustering the values of attributes. The clusters of the values of attributes are used to find the clusters of transactions. The suggested procedure can enhance the interpretation of resulting clusters with allocated attribute values.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.221-223
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• 2010

Considering the similarity between fluid vortex and arrhythmogenic reentrant waves in heart, we applied the non-dimensionalization method in fluid dynamics to arrhythmia analysis and discovered a new non-dimensional simulation results, there was a threshold value of the number that resulted in the induction of a reentrant wave.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.556-561
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• 2009

In this paper, we propose new method to calculate the distance between intuitionistic fuzzy sets(IFSs) based on the three dimensional representation of IFSs and analyze the relations of similarity measure and distance measure of IFSs. Finally, we apply the proposed measures to pattern recognitions.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.269-280
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• 2004

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expresses it as a B+-tree. By solving the problem of search time complexity the pyramid technique also prevents the effect of "phenomenon of dimensional curse" which is caused by treatment of hypercube range query in n-dimensional data space. The SPY-TEC applies the space division strategy in pyramid method and uses spherical range query suitable for similarity search so that Improves the search performance. However, nearest neighbor query is more efficient than range query because it is difficult to specify range in similarity search. Previously proposed index methods perform well only in the specific distribution of data. In this paper, we propose an efficient searching technique for nearest neighbor object using PdR-Tree suggested to improve the search performance for high dimensional data such as multimedia data. Test results, which uses simulation data with various distribution as well as real data, demonstrate that PdR-Tree surpasses both the Pyramid-Technique and SPY-TEC in views of search performance.rformance.

• Journal of KIISE:Databases
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• v.37 no.2
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• pp.71-81
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• 2010

The problem of finding clusters is widely used in numerous applications, such as pattern recognition, image analysis, market analysis. The important factors that decide cluster quality are the similarity measure and the number of attributes. Similarity measures should be defined with respect to the data types. Existing similarity measures are well applicable to numerical attribute values. However, those measures do not work well when the data is described by categorical attributes, that is, when no inherent similarity measure between values. In high dimensional spaces, conventional clustering algorithms tend to break down because of sparsity of data points. To overcome this difficulty, a subspace clustering approach has been proposed. It is based on the observation that different clusters may exist in different subspaces. In this paper, we propose a new similarity measure for clustering of high dimensional categorical data. The measure is defined based on the fact that a good clustering is one where each cluster should have certain information that can distinguish it with other clusters. We also try to capture on the attribute dependencies. This study is meaningful because there has been no method to use both of them. Experimental results on real datasets show clusters obtained by our proposed similarity measure are good enough with respect to clustering accuracy.

• Transactions of the Korean hydrogen and new energy society
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• v.26 no.4
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• pp.386-392
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• 2015

Flow characteristics inside a 10 inch ball valve have been analyzed using three-dimensional numerical analysis and experiments. Continuity and three-dimensional Reynolds-averaged Navier-Stokes equations have been used as governing equations for the numerical analysis. The numerical model has been constructed through the grid dependency test and validation with the results of experiments to ensure reliability and numerical effectiveness. The shear stress transport (SST) model has been used as the turbulence closure. The experimental test-rig has been constructed to measure pressure, temperature and flow rate along the pipeline. Some valve opening angles have been tested to evaluate the flow characteristics inside the ball valve and pipeline. The results show that the rapid pressure variations is observed while the valve opening angle decreases, which caused by flow separation at the downstream of the ball valve.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.79-88
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• 2024

The information retrieval domain deals with the retrieval of unstructured data such as text documents. Searching documents is a main component of the modern information retrieval system. Locality Sensitive Hashing (LSH) is one of the most popular methods used in searching for documents in a high-dimensional space. The main benefit of LSH is its theoretical guarantee of query accuracy in a multi-dimensional space. More enhancement can be achieved to LSH by adding a bit to its steps. In this paper, a new Dynamic Locality Sensitive Hashing (DLSH) algorithm is proposed as an improved version of the LSH algorithm, which relies on employing the hierarchal selection of LSH parameters (number of bands, number of shingles, and number of permutation lists) based on the similarity achieved by the algorithm to optimize searching accuracy and increasing its score. Using several tampered file structures, the technique was applied, and the performance is evaluated. In some circumstances, the accuracy of matching with DLSH exceeds 95% with the optimal parameter value selected for the number of bands, the number of shingles, and the number of permutations lists of the DLSH algorithm. The result makes DLSH algorithm suitable to be applied in many critical applications that depend on accurate searching such as forensics technology.