• 복식문화연구
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• 제11권2호
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• pp.219-230
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• 2003

The purpose of this study was to analyze the structure of consumption emotions that consumers experienced in the process of consuming apparel products. Data was collected from 144 female college students living in Busan, and analyzed by salience, diversity, H-index, Clamor's V, and multi-dimensional scaling. The results showed as following; 1. The consumption emotions related to apparel products appeared three dimensions; ‘Relaxed-tense’ dimension, ‘Pleasant-unpleasant’ dimension, and ‘Outward-inward’ dimension. Considering elements of consumption system, the dimensions of consumption emotions in relation to apparel performances were 'Pleasant-unpleasant' and ‘Outward-inward’. The dimensions of consumption emotions experienced in usage situations were ‘Relaxed-tense’ and ‘pleasant-unpleasant’. The consumption emotions related to specific products were composed of ‘Pleasant-unpleasant’ dimension and ‘Outward-inward’ dimension. 2. As the multi-dimension map of this study has much space, it suggested that the scope of consumption emotions related to apparel products was more limited than those related to general situations and products. 3. The structure of consumption emotions in relation to apparel performances appeared to be bisected, while those related to usage situations showed relatively to be dispersed. 4. Although Pleasant-unpleasant dimension was consistent with results of prestudies, the dimensions of ‘Relaxed-tense’ and ‘Outward-inward’ were newly confirmed as the dimensions of consumption emotions related to apparel products. Therefore, consumer's consumption emotions of apparel products were composed of three dimensions, tended to be more limited than those of general consumption situations and products, and differentiated across apparel performances, usage situation, and specific products.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.213-234
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• 2024

In recent decades, increasing research attention has been directed toward predicting the price of stocks in financial markets using deep learning methods. For instance, recurrent neural network (RNN) is known to be competitive for datasets with time-series data. Long short term memory (LSTM) further improves RNN by providing an alternative approach to the gradient loss problem. LSTM has its own advantage in predictive accuracy by retaining memory for a longer time. In this paper, we combine both supervised and unsupervised dimension reduction methods with LSTM to enhance the forecasting performance and refer to this as a dimension reduction based LSTM (DR-LSTM) approach. For a supervised dimension reduction method, we use methods such as sliced inverse regression (SIR), sparse SIR, and kernel SIR. Furthermore, principal component analysis (PCA), sparse PCA, and kernel PCA are used as unsupervised dimension reduction methods. Using datasets of real stock market index (S&P 500, STOXX Europe 600, and KOSPI), we present a comparative study on predictive accuracy between six DR-LSTM methods and time series modeling.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 춘계 학술발표회
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• pp.123-131
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• 2009

본 연구에서는 2차원 및 3차원 유한요소 해석을 이용하여 심층혼합처리 공법에 의한 연약지반 개량시 개량 심도를 결정 하였고, 그 결과는 다음과 같았다. 1. 2차원 해석 결과는 3차원 해석 결과 보다 약 10% 정도 크게 해석되었다. 2. 연약지반의 치환율이 5%이하 일 때 침하량은 급격히 증가하였다. 3. 심층혼합공법으로 연약지반 개량시 횡방향 간격 3m, 종방향 간격 6m, 그리고 8m의 심도로 개량하는것이 가장 경제적인 것으로 나타났다. 4. 심층혼합공법으로 연약지반 개량시 2차원 유한요소 해석보다 3차원 유한요소 해석으로 결정되어야 한다.

• 대한수학회지
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• 제36권3호
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• pp.633-648
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• 1999

In this paper, for any two bipartite ordered sets P and Q, we define the convolution P * Q of P and Q. For dim(P)=s and dim(Q)=t, we prove that s+t-(U+V)-2 dim(P*Q) s+t-(U+V)+2, where U+V is the max-mn integer of the certain realizers. In particular, we also prove that dim(P)=n+k- {{{{ { n+k} over {3 } }}}} for 2 k n<2k and dim(Pn ,k)=n for n 2k, where Pn,k=Sn*Sk is the convolution of two standard ordered sets Sn and Sk.

• 패션비즈니스
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• 제22권1호
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• pp.135-147
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• 2018

Since the 20th century, there has been a growing interest in the new concept of fractals, a combination of mathematics and art, and the attempt to study the creative spatial aspects of the concept is being made. The purpose of this research is to examine artistic characteristics of fractal dimension and then analyze the types of fractal dimensions expressed in the fashion. Previous literature on fractals and dimension, and visual data on art and fashion collected over the Internet were used for analysis. Fractal dimension refers to the spatial concept of structural dimension of geometrical self-similarity. An analysis of the types of fractals seen in fashion revealed spatial expansion, the repetition in continual figures, superposition accordant to different sizes, and shades of different shapes. The aesthetic characteristics of fractal dimension appearing in fashions were examined based on analyses of fractal dimension types; the inherent characteristics of self-similarity, superimposition, and atypicality were found. Results obtained from this study are expected to be used as basic materials for the application of the design of fractal dimension into various perspectives of fashion.

• 대한치과보철학회지
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• 제30권1호
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• pp.43-54
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• 1992

The purpose of this study was to obtain the guides of establishing vertical dimension by analyzing the facial and oral landmarks of Korean adults. The following conclusions were obtained from this study. 1. The ratio of bizygomatic width to dental arch width was 3.26 : 1 in male and 3.21 : 1 in female, and the ratio of vertical dimension to dental arch length was 2.49 : 1 in male and 2.39 : 1 in female. 2. It was obtained by analysis of multiple regression that the corelative formula, vertical dimension$=23.37+0.24{\times}bizygomatic$ $width+0.29{\times}dental$ arch length. 3. There was no statistically significant difference between the results of vertical dimension acquired by means of Hayakawa's prediction($68.04{\pm}3.16mm$ in male, $64.38{\pm}3.00mm$ in female) and that of vertical dimension by this study.

• 한국수자원학회논문집
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• 제31권5호
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• pp.587-597
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• 1998

기존의 연구자들은 하천길이의 프랙탈 차원은 유역내 전체 하천에 대해 균일하며 그 수치도 1.09~1.13로 상당히 크게 보았다. 그렇지만 국제수문개발계획의 대표유역중 하나인 평창강수계내 이목정 소유역을 대상으로 1/50,000, 1/25,000, 1/5,000의 3개 축척 지형도를 이용하여 프랙탈 차원을 산정한 결과 하천차수별로 서로 다른 프랙탈 차원을 갖는 것을 발견하였고, 또한 전체 하천으로 보아도 기존 연구자들이 제안한 수치보다 작은 수치를 보였다. 이목적 소유역내 하천의 프랙탈 차원을 산정한 결과에 의하면 기존의 국내외의 연구가 전체 하천을 균일한 프랙탈 차원을 갖는 것으로 보는 것과 달리 1차, 2차 하천은 1.033, 이보다 하천차주가 높은 3차, 4차 하천을 1.014의 값을 보이는 등 하천차수별로 프랙탈 차원이 다르게 산정되었다. 또한 전체적인 하천길이에 대한 프랙탈 차원도 1.027로서 국내외에서 제시된 기존의 하천길이에 대한 프랙탈 차원인 1.09~1.13 사이의 수치는 실제보다 너무 과대평가된 것으로 추정된다.

• 조명전기설비학회논문지
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• 제30권2호
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• pp.37-42
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• 2016

This paper proposes a method to develop a high-precision dimension measurement system using a linear variable differential transformer sensor. The Dimension targets for measurement is carbon material vanes of key element in the rotating parts within vehicle circulating pump. Data acquisition system for dimension measurement is designed using the NI Compact RIO. And the program applying the dimension measurement algorithm is built using NI LabVIEW. The dimension measuring program is composed of a FPGA program, Real Time program and Host program. The method of the experiment compares master vane with target vane for measure the length of the carbon material vane. The experimental results confirmed the usefulness of the accuracy within ${\pm}4um$.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.205-215
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• 2021

Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.

• Communications for Statistical Applications and Methods
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• 제31권2호
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• pp.191-202
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• 2024

The goal of this paper is to show how multivariate regression analysis with high-dimensional responses is facilitated by the response dimension reduction. Multivariate regression, characterized by multi-dimensional response variables, is increasingly prevalent across diverse fields such as repeated measures, longitudinal studies, and functional data analysis. One of the key challenges in analyzing such data is managing the response dimensions, which can complicate the analysis due to an exponential increase in the number of parameters. Although response dimension reduction methods are developed, there is no practically useful illustration for various types of data such as so-called large p-small n data. This paper aims to fill this gap by showcasing how response dimension reduction can enhance the analysis of high-dimensional response data, thereby providing significant assistance to statistical practitioners and contributing to advancements in multiple scientific domains.