• The Journal of the Acoustical Society of Korea
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• 제15권2E호
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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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• 제22권3호
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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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• 제10권1호
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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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• 제1권1호
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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.

• 한국CDE학회논문집
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• 제10권5호
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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.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권4호
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• pp.427-431
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• 2010

다차원 척도법(multidimensional scaling)은 고차원의 데이터를 낮은 차원의 공간에 매핑(mapping)하여 데이터 간의 유사성을 표현하는 방법이다. 이는 주로 자질 선정 및 데이터를 시각화하는 데 이용된다. 그러한 다차원 척도법 중, 전통 다차원 척도법(classical multidimensional scaling)은 긴 수행 시간과 큰 공간을 필요로 하기 때문에 객체의 수가 많은 경우에 대해 적용하기 어렵다. 이는 유클리드 거리(Euclidean distance)에 기반한 $n{\times}n$ 상이도 행렬(dissimilarity matrix)에 대해 고유쌍 문제(eigenpair problem)를 풀어야 하기 때문이다(단, n은 객체의 개수). 따라서, n이 커질수록 수행 시간이 길어지며, 메모리 사용량 증가로 인해 적용할 수 있는 데이터 크기에 한계가 있다. 본 논문에서는 이러한 문제를 완화하기 위해 GPGPU 기술 중 하나인 CUDA와 분할-정복(divide-and-conquer)기법을 활용한 효율적인 다차원 척도법을 제안하며, 다양한 실험을 통해 제안하는 기법이 객체의 개수가 많은 경우에 매우 효율적일 수 있음을 보인다.

• 한국의류학회지
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• 제14권2호
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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.

• 한국융합학회논문지
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• 제6권5호
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• pp.257-274
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• 2015

본 연구는 Fetzer/NIA(1999)에서 개발한 다차원적 종교성/영성 척도-단축형(Brief-Multidimensional Measure of Religiousness/Spirituality Scale; BMMRS)의 신뢰도와 타당도를 평가하기 위해서 실시되었다. 대학생, 대학원생과 종교를 믿는 일반 성인 286명을 대상으로 BMMRS 영적 웰빙척도(Spiritual Well-Being Scale, SWS), 한국판 영성 척도(Korean Sprituality Scale, KSS), 펜실베니아 걱정질문지(Penn State Worry Questionnaire, PSWQ), 불확실성에 대한 인내력 부족 척도(Intolerance of uncertainty Scale, (IUS)를 실시하였다. BMMRS의 요인구조를 주축분해법, 사각 회전으로 분석한 결과, 기존 연구에서 제안되었던 긍정적 영적 경험, 부정적 영적 경험, 용서, 종교활동, 긍정적인 종교지지, 부정적인 종교지지 6요인 구조가 확인되었고 확인적 요인분석 결과 모형 적합도도 만족할 만한 수준이었다. 각 소척도의 내적일관성(.64~.97)과 검사-재검사 신뢰도(.72~.88) 역시 적절하였다. 이 결과는 한국판 BMMRS가 적절한 심리 측정적 지표를 나타내고 있음을 보여주고 있으며, 이에 향후 영성과 종교성 및 정신건강의 관련성 연구에 사용될 수 있음을 시사하였다.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2003년도 추계학술발표대회 요약집
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• pp.115.2-115.2
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• 2003

• 한국환경과학회지
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• 제16권5호
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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.