• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.24-32
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• 1996

A rigorous theory for modeling, analysis, optimum nonseparable filter bank in multidimensional M-band quantized subband codec are developed in this paper. Each pdf-optimized quantizer is modeled by a nonlinear gain-plus-additive uncorrelated noise and embedded into the subband structure. We then decompose the analysis/synthesis filter banks into their polyphase components and shift the down-and up-samplers to the right and left of the analysis/synthesis polyphase matrices respectively. Focusing on the slow clock rate signal between the samplers, we derive the exact expression for the output mean square quantization error by using spatial-invariant analysis. We show that this error can be represented by two uncorrelated components : a distortion component due to the quantizer gain, and a random noise component due to fictitious uncorrelated noise at the uantizer. This mean square error is then minimized subject to perfect reconstruction (PR) constraints and the total bit allocation for the entire filter bank. The algorithm gives filter coefficients and subband bit allocations. Numerical design example for the optimum nonseparable orthonormal filter bank is given with a quincunx subsampling lattice.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.49-60
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• 2003

The human sensibility product design requires information on consumer's emotions such as vision, auditory, olfactory, gustatory, or tactile perceptions. In this study, tactile sense which has not been well studied compared to other senses, is measured and statistically analysed. The emotional responses of 37 pairs of positive and negative adjectives describing tactile senses are collected and analysed through the questionnaire to find the correlation between adjectives and surface roughness of the sample. Mean ranks for 37 pairs of adjectives on four samples are obtained, and used to cluster these adjectives by factor analysis, multidimensional scaling, or cluster analysis.

• KSTLE International Journal
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• v.1 no.1
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• pp.34-42
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• 2000

A method and results of classification of four different metallic wear debris were presented by using their color features. The color image of wear debris was used far the initial data, and the color properties of the debris were specified by HSI color model. Particles were characterized by a set of statistical features derived from the distribution of HSI color model components. The initial feature set was optimized by a principal component analysis, and multidimensional scaling procedure was used fer the definition of a classification plane. It was found that five features, which include mean values of H and S, median S, skewness of distribution of S and I, allow to distinguish copper based alloys, red and dark iron oxides and steel particles. In this work, a method of probabilistic decision-making of class label assignment was proposed, which was based on the analysis of debris-coordinates distribution in the classification plane. The obtained results demonstrated a good availability for the automated wear particle analysis.

• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.314-327
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• 2005

This paper describes the volumetric data modeling and analysis methods that employ volumetric NURBS or VNURBS that represents heterogeneous objects or fields in multidimensional space. For volumetric data modeling, we formulate the construction algorithms involving the scattered data approximation and the curvilinear grid data interpolation. And then the computational algorithms are presented for the geometric and mathematical analysis of the volume data set with the VNURBS model. Finally, we apply the modeling and analysis methods to various field applications including grid generation, flow visualization, implicit surface modeling, and image morphing. Those application examples verify the usefulness and extensibility of our VNUBRS representation in the context of volume modeling and analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.427-431
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• 2010

Multidimensional scaling (MDS) is a widely used method for dimensionality reduction, of which purpose is to represent high-dimensional data in a low-dimensional space while preserving distances among objects as much as possible. MDS has mainly been applied to data visualization and feature selection. Among various MDS methods, the classical MDS is not readily applicable to data which has large numbers of objects, on normal desktop computers due to its computational complexity. More precisely, it needs to solve eigenpair problems on dissimilarity matrices based on Euclidean distance. Thus, running time and required memory of the classical MDS highly increase as n (the number of objects) grows up, restricting its use in large-scale domains. In this paper, we propose an efficient approximation algorithm for the classical MDS based on divide-and-conquer and CUDA. Through a set of experiments, we show that our approach is highly efficient and effective for analysis and visualization of data consisting of several thousands of objects.

• Journal of the Korean Society of Clothing and Textiles
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• v.14 no.2
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• pp.129-136
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• 1990

The purpose of the study was to develope brand positioning map for ladies' ready-to-wear, to find out evaluative criteria in perception and preference to brands, and to persent the relationship between consumer's characteristics and brand preference. Subjects were selected for the housewives of middle and high socioeconomic classes living in Seoul area. A questionnaire including items of life style, self image, similarity between brands, preference degree to brands, and demographic variables was developed for the empirical study. The questionnaire was administrated to 137 housewives during fall in 1989. Data were analyzed by cluster analysis and multidimensional scaling method. The study had two research problems. The first research problem was to construct a brand perceptual map for ladies' ready-to-wear brands, selected for the study The perceptual map was constructed on the basis of brand similarity scores by multidimensional scaling method. As a result, brands were grouped into 4 clusters, and evaluative criteria for perceptual map were found to be fashionability (classic- fashionable) and familiarity (familiar-unfamiliar). The second problem was to construct a brand preference map for ladies' ready-to-wear brands, selected for the study. The preference map was constructed on the basis of brand preference scores by multidimensional scaling method. As a result, the brands were grouped into 4 clusters and evaluative critiera for preference map were found to be fashionability (unfashionable-fashionable) and image to age (mature-young directed). Also was shown the relationship among self image, age, socioeconomic class, and brand preference. The multidimensional scaling method was found to be useful as well as valid instrument for brand positioning research and the result can be utilized for establishing strategies for ladies' ready-to-wear brands.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.257-274
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• 2015

The purpose of the current study was to validate Fetzer Institute & National Institute on Aging Working Group[NIA](1999)'s Brief-Multidimensional Measure of Religiousness/Spirituality Scale (BMMRS) in Korean adults. The Korean version of BMMRS, Spiritual Well-Being Scale(SWS), Korean Sprituality Scale(KSS), Penn State Worry Questionnaire(PSWQ), and Intolerance of uncertainty Scale(IUS) were administered to the 286 students and community samples. A principle axis factoring analysis with direct oblimin rotation and Kaiser normalization identified a six-factor solution accounting for 66.24% of the variance in scores, labeled as: positive spiritual experience, negative spiritual experience, forgiveness, religious practices, negative congregational support, and positive congregational support. Confirmatory factor analysis results showed that 6 factor model of BMMRS have a good fitness. Also, the internal consistency(.64~.97) and the test-retest reliablity was adequate.(.72~.88) Korean version of BMMRS has adequate psychometric characteristics so it can be used to verify the effects of various compassion-related psychotherapeutic approaches.

• Proceedings of the Korean Nuclear Society Conference
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• 2003.10a
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• pp.115.2-115.2
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• 2003

• Journal of Environmental Science International
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• v.16 no.5
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• pp.549-559
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• 2007

Vegetation surveys were performed at 45 plots along 10 highways cut slopes in South Korea. Total floral inventory, species richness and exotic plant percentage were obtained within each plot. Life history and life form of each species appeared were analyzed. Community types were classified using hierarchical cluster analysis and detrended correspondence analysis and non-metric multidimensional scaling were conducted from vegetation matrix. 292 species of vascular plants were discovered and the number of natives and exotics were 226 and 66, respectively. There were no significant differences of species richness and exotic plant percentage between cut slopes and rest areas. Hierarchical cluster analysis indicated five clear vegetation associations in cut slopes and rest areas. Detrended correspondence analysis indicated that species composition of total and native plants were similar along the highway cut slopes whereas exotic plants were distributed differentially along the highway cut slopes. in non-metric multidimensional scaling, the studied sites were more separated from each other on the basis of their species composition than the results of detrended correspondence analysis with respect to total, native and exotic plants. The both ordination represented that exotic plants have not been made uniform yet on cut slopes and rest areas by highway corridor in spite of diverse chronosequences after highway construction termination (1 to 22 years). This study showed that the distribution of species composition in exotic plants was different and localized on cut slopes and rest areas of highway in this representative peninsula area of North East Asia and the invasion of exotic plants can retard the process of plant species homogenization.