• 한국의류산업학회지
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• 제20권3호
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• pp.293-303
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• 2018

Since 2009, consumers could access a new shopping channel called 'mobile shopping' with the generalization of smartphones. Mobile shopping (based on wireless communication technology), emphasizes convenience differentiated from internet shopping. A recent report introduced fashion products as powerful global drivers for mobile shopping sales. Korea and China have the highest percentage of consumer mobile shopping experiences compared to other countries. This study investigates the effects of cross-over shopping orientation, perception of app attributes, and flow on app loyalty that compared Korean and Chinese consumers. We obtained 652 usable questionnaires from two local college students; subsequently, data were analyzed by using factor analysis, Cronbach's alpha, and regression analysis using SPSS 21.0 Package. The study results showed that the cross-over shopping orientation affected perception of app attributes that included Review/Information, Design, Response and Product. Product only affected Flow, which reflected a high similarity between Korean and Chinese consumers. However, Korean and Chinese consumers showed remarkable differences in the factors related to app loyalty. Therefore, the results indicate that retailers of fashion products have developed strategies to improve mobile sales and increase the app loyalty of cross-over shopping orientation consumers.

• 복식
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• 제60권9호
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• pp.106-119
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• 2010

The purpose of this study is to examine American students' perceptions of contemporary fashion design that incorporates Korean traditional costume. The findings, which are based on a survey of American students' aesthetic response to the fashion designs, are as follows. First, the impressions of American students about the fashion designs were affected by two major factors, Tradition and Trend. The Tradition factor was related to the impressions traditional, formal, elegant, classic, romantic, gorgeous, and natural, but was correlated negatively to the impressions dynamic, modern, and casual. The Trend factor was related to the impressions chic, trendy, and clear but not dandy. Designs with elongated shape had a positive score for the Tradition factor and designs with curvy line had a positive score for the Trend factor. Second, American students gave visual priority to the aspects of shape such as garment type and silhouette when they evaluated the designs. Color was less important than the aspect of shape in their fashion image perception. Therefore, they categorized the designs by similarity of garment types, and then sub-categorized them by color. The meaning of Korean traditional motifs or details was not significant to American students. Third, American students showed the tendency that the more they evaluated the designs to be gorgeous or trendy, the more they liked the designs. Furthermore, they liked the designs which have a positive score for the Trend factor.

• 대한수학교육학회지:수학교육학연구
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• 제17권1호
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• pp.67-90
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• 2007

본 연구의 목적은 문제해결의 결과로 나타나는 성공과 실패에 대한 학생들의 사고 과정을 유사성의 관점에서 이해하고자 하는 것이다. 따라서 사례연구 방법을 사용하여 정답을 제시한 학생들의 사고과정이 반드시 바람직하지 않을 수 있다는 의사(擬似) 분석적 사고와 분석적 사고에 대한 Vinner(1997a, 1997b)의 연구내용을 근거로 학생들의 사고과정을 분석하고자 하였다. 본 사례 연구 분석 결과, 학교 성적이 중상위권인 2명의 연구대상자들은 각각 의사(擬似) 분석적 사고와 분석적 사고를 함으로써 대수 문장제 해결에서 성공하거나 실패하였다. 학생들의 의사(擬似) 분석적 사고와 분석적 사고의 특징은 구조적 유사성의 구성에서 각 연구 대상자들이 인식한 해법 공식이 변형이 가능한 것인가의 여부와 해법을 적용하는 과정에서 학생 자신의 사고를 통제하거나 조절할 수 있는가의 여부에 따라 구분된다는 것이었다. 따라서 본 연구에서는 학생들이 해법으로 인식하는 공식의 형태가 어떠한 것이며, 그러한 해법을 어떻게 적용하는가를 유사성의 관점에서 문제 해결의 성공 여부와 관련하여 분석할 수 있었다.

• 터널과지하공간
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• 제29권4호
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• pp.230-242
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• 2019

신속한 암반 및 암석 균열 조사를 위해서는 자동화된 조사기법이 필요하다. 그러나 자동 조사기법의 균열 지도가 수동으로 조사한 것과 얼마나 일치하는지 표기하는 단일 지표가 없어서 그 정확도를 평가하는데 어려움이 있다. 따라서 본 연구에서는 균열 지도 간의 일치도를 단일 값으로 표현하는 조사선 교차 일치도 (Scanline Intersection Similarity, SIS)라는 지표를 새롭게 제안하였다. 제안된 지표는 두 균열 지도의 균열 빈도를 다수의 조사선 상에서 비교하여 이들 간의 기하학적 일치도를 도출한다. 해당 지표의 적용성을 검토하기 위해 컴퓨터 비전 (Computer Vision) 분야에서 널리 사용하는 일치도 지표인 Intersection Over Union (IoU)과 비교분석하였다. IoU는 균열의 미시적 형태 차이를 과대평가하는 반면에, 제안된 지표의 경우 미시적 형태 차이보다 경사와 같은 거시적 형태 차이를 더 민감하게 반영하였다. 따라서 균열의 거시적 형태가 중요한 암반 공학적 관점에서, 제안된 지표가 IoU 보다 균열 지도의 일치도 지표로써 적합하였다. 더 나아가 제안된 지표를 딥러닝(Deep Learning)을 이용한 균열 조사기법에 적용해본 결과, 해당 기법의 정확도가 조사선 교차 일치도로 0.674 임을 확인하였다.

• 디자인학연구
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• 제20권3호
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• pp.247-256
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• 2007

본 연구는 인간이 일상생활을 영위하는데 중요한 역할을 하는 눈이 노화되어 감으로서 노인의 시각 노화과정에서 보이는 시지각과 관련된 정보습득 및 해석상의 색지각을 통한 특징을 반영하여 노인의 주 생활환경인 유료 노인주거 시설의 실내 공용공간의 설계지침을 제시하는 것을 목적으로 한다. 일반시각과 70세와 80세 후반까지를 모의 수정체를 이용하여 각 세대별 시지각을 통한 색채의 오류판단을 파악하였다. 노화에 따른 노인의 황변화 및 색지각 특성을 바탕으로 실내 공용공간의 색채 설계 계획을 위한 기초자료로 사용하고자 한다. 본 연구의 결과로 인지 배색으로 유사조화 보다 대비조화를, 한색보다 난색계열을 사용함를 파악하였으며, 노인의 황변화에 따른 색지각 특성의 기초자료로서 활용될 수 있다.

• 한국의류학회지
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• 제40권1호
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• pp.41-55
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• 2016

This study analyzed the influence of other customers' perception (similarity, physical attraction, and suitable behavior) of the fashion retail environment on male customers' store attitude and behavioral response. In addition, comparing the effect of store type, this study comprehensively provides the effect of other customers' perception in fashion retailing. In order to investigate research questions, an online survey was conducted and 220 responses were analyzed using AMOS 18.0. The results of this research were as follow. First, the dimensions of physical attraction and suitable behavior of other customers influenced toward target customer's fashion store attitude. Second, the effect of store attitude towards the perceiver's behavioral response was proven. Third, customers established their store attitude by other customers' physical attraction in luxury stores, while others' behavior was meaningful in SPA store. Fourth, other customer's similarity dimension did not influence the male customers' store attitude. This study contributes to a comprehensive understanding of other customer's effect in fashion stores by examining different store types. In addition, managers may establish a customer portfolio strategy and training based on this research.

• 한국항행학회논문지
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• 제15권5호
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• pp.913-924
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• 2011

본 논문에서 항공사와 여행사 직원들을 대상으로 하여 유통경로상의 관계특성이 갈등에 미치는 영향 관계를 검증한 결과 항공사 측에서는 경쟁력, 전문성, 환경의 불확실성, 접촉빈도, 상호의존이 갈등에 부(-)의 영향을 여행사 측에서는 환경의 동태성, 유사성, 경쟁력, 접촉빈도, 전문성이 갈등에 부(-)의 영향을 미치는 것으로 나타났으며, 두 변수에 대한 항공사와 여행사의 인식 차이 분석 결과 관계특성 중 경쟁력, 유사성, 접촉빈도와 지각차이갈등, 의사소통장애갈등에서 모두 유의한 차이가 있는 것으로 나타났다. 이러한 연구 결과로 검증된 관계특성 요인들은 항공사와 여행사간의 갈등을 감소시켜 긍정적인 관계로 발전시키는데 중요한 역할을 할 수 있을 것이다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.177-182
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• 2003

This study is directed toward determining the number and characteristics of psychologically meaningful perceptual dimensions required for assessing the sound Ouaiity with respect to vehicle interior and/or exterior noises. and toward identifying the acoustical or psychoacoustical bases underlying the perception. By nonmetric MDS and clustring analysis of sound quality data sets on our own, of critical importance are two perceptual dimensions for which subjective verdicts can be interpreted as loudness and sharpness. The perceptual dimensions based upon similarity judgments could be accounted for 48% and 24% of the variance. each of which might be a match for the acoustic parameter "A-weighted maximum pressure level"(r= .85) and for the psychoacoustic parameter "sharpness" (r= .65), respectively. On the other hand, the perceptual dimensions based upon preference ratings could explain 66% and 10% of the variance. where the acoustic parameter "A-weighted maximum pressure leve"(r= .92) might be taken to be a best predictor, but sharpness appeared to be less suitable for the description of Preference behavior. Linked to the results, the problems of quantitative modelling of subjective sound quality evaluation and also of implementing corresponding cognitive combination rule for technical and industrial applications, say having "winner-sound qualify" according to preference criteria will be shortly in discussion.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.55-66
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• 2023

Community portraits can deeply explore the characteristics of community structures and describe the personalized knowledge needs of community users, which is of great practical significance for improving community recommendation services, as well as the accuracy of resource push. The current community portraits generally have the problems of weak perception of interest characteristics and low degree of integration of topic information. To resolve this problem, the reader community portrait method based on the thematic and timeliness characteristics of interest labels (UIT) is proposed. First, community opinion leaders are identified based on multi-feature calculations, and then the topic features of their texts are identified based on the LDA topic model. On this basis, a semantic mapping including "reader community-opinion leader-text content" was established. Second, the readers' interest similarity of the labels was dynamically updated, and two kinds of tag parameters were integrated, namely, the intensity of interest labels and the stability of interest labels. Finally, the similarity distance between the opinion leader and the topic of interest was calculated to obtain the dynamic interest set of the opinion leaders. Experimental analysis was conducted on real data from the Douban reading community. The experimental results show that the UIT has the highest average F value (0.551) compared to the state-of-the-art approaches, which indicates that the UIT has better performance in the smooth time dimension.

• Journal of information and communication convergence engineering
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• 제22권1호
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.