• 한국의류산업학회지
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• 제10권3호
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• pp.298-306
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• 2008

The purpose of this study was to consumer's evaluation toward salesperson attributes, satisfaction of salesperson and apparel store on relationship continuity. To this end, a total of 500 questionnaires were distributed to men and women university students and 443 samples were used for the final analysis. Data were analyzed by using frequency, percentage, factor analysis, cluster analysis, One-way ANOVA, crosstabs, Pearson's correlation analysis, regression analysis. The results of this study were as follows; Looking at the effects of evaluation toward salesperson attributes, satisfaction of salesperson on relationship continuity, they showed satisfaction of salesperson had direct influence on relationship continuity extremely when men and women university students are purchasing their clothing. Uniformity, customer orientation, expertise, kindness were as follows. Looking at the effects of evaluation toward salesperson attributes, satisfaction of apparel store on relationship continuity, it showed uniformity has direct influence on maintaining relations extremely when men and women university students are purchasing their clothing. Customer orientation, satisfaction of apparel store, expertise, kindness were as follows. Through this study, it will be applied into program development data for consumer management and education, and salesperson's efficient consumer response as well.

• 대한가정학회지
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• 제42권3호
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• pp.195-209
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• 2004

The purpose of this study was 1) to examine the usage of mobile internet by cell phone or palm pilot, etc., 2) to analyze mobile users' lifestyles, 3) to examine preferred fashion services according to users' lifestyles and 4) to investigate service satisfaction and preference with the mobile internet. 193 university students in Seoul were randomly selected as subject. The data was analyzed using descriptive statistics (i.e., percentage, frequency), factor analysis, cluster analysis and ANOVA. The results of the study were as follows: first, most mobile users spent 10 min a day for using the mobile internet (i.e., short message service) mainly in transportation vehicles. Secondly, five factors in the mobile users' lifestyle were named as: 'surfer', 'absorber', 'expert', 'accepter' and 'enthusiast'. Thirdly, two factors in the preferences of fashion service on mobile internet were 'customized information service' and 'ordinary information service'. Fourthly, according to the internet lifestyle, mobile users were classified into three groups: 'mania group', 'follower group', and 'veteran group'. The mania group was the highest group in mobile service satisfaction and service preference. Marketing implications are discussed for the successful mobile business in clothing and textile industry.

• 한국정보과학회논문지:시스템및이론
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• 제29권12호
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• pp.648-654
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• 2002

클러스터들을 연결시키는 통신 모델로 업계 표준인 VIA(Virtual Interface Architecture)가 있다. VIA의 소프트웨어적인 구현으로는 M-VIA를 대표적으로 들 수 있다. 본 논문에서는 TCP/IP를 지원하는 기존의 AceNIC 기가비트 이더넷 카드의 디바이스 드라이버에 수정을 가하여 M-VIA를 지원할 수 있도록 구현하였다. 그리고 M-VIA의 데이터 세그멘테이션 과정을 분석하여 기가비트 이더넷 카드가 1514 bytes이상의 MTU를 지원할 경우, 기존의 M-VIA 뎨이터 세그멘데이션 크기가 가지는 문제점을 보이며 이를 개선하기 위해 MTU와 M-VIA 데이터 세그멘테이션 크기를 다르게 해서 실험하였고 그 성능을 비교하였다.

• 한국의류학회지
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• 제35권12호
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• pp.1440-1453
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• 2011

Proper consumer segmentation is receiving more attention from industry professionals as markets become more diverse and consumer-centered. Researchers have recognized the limitations of the traditional cluster analysis technique and this research study analyzes market segmentation using Mixture-model or latent-class segmentation. This study used a questionnaire to determine the characteristics of clothing shoppers using a new technique that proved its superiority over traditional techniques. Questions included items measuring fashion shopping behavior, store choice criteria, apparel consumption styles, price perception by product type, and demographic characteristics. Data were collected from 1074 males and females in their 20s and 30s through an online survey. SPSS 16.0 and Latent GOLD 4.0 were used to analyze the data. The ideal typology of clothing shoppers using the Mixture-model were: 'brand loyalty orientated group', 'group of conservative late 30s', 'group of pleasure-emotion early 20s', 'value oriented consumer product with high-income group', 'group of eco/symbol oriented consumer', and 'group of utility/goal oriented male consumer'. This study showed differences in fashion product purchasing behavior by conducting market segmentation for clothing shoppers using the Mixture-model.

• 한국의류학회지
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• 제37권8호
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• pp.1075-1094
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• 2013

This study analyzed the lower body type of women aged 20 to 30 to understand their respective characteristics. The research method was restricted to the use of direct measurements data and 3D measurements data of the Sixth Size Korea. Factor analysis, cluster analysis, ANOVA, Duncan's test, discriminant analysis, t-test, and ${\chi}^2$-test were performed for the statistical analysis of the data using SPSS Win 20.0 program. The results of this study are as follows. Lower body type based on 3D measurements were classified into 3 types (obese lower body, long lower body, and small lower body). Lower body type based on direct measurements were classified into 3 types (obese lower body, thick and long lower body, and small lower body). Lower body type based on the direct measurement of sitting pose were classified into 3 types (obese lower body, long and thin lower body, and short lower body). The age differences in the lower body types could be analyzed by an evaluation of the 3D simulation of the lower body.

• Journal of Information Processing Systems
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• 제13권4호
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• 한국컴퓨터산업학회논문지
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• 제6권3호
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• pp.391-400
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• 2005

최근 몇 년 사이 컴퓨터와 초고속 통신망의 대중적인 보급으로 인하여 인터넷 사용 인구가 급격하게 증가하였고 인터넷 사용량 또한 폭발적으로 증가하였다. 이와 같이 막대한 양으로 늘어난 트래픽은 서버에 과도한 양의 부하를 발생시켜 서비스 전반에 걸친 성능 저하를 가져왔다. 따라서 서버에 많은 양의 트래픽이 발생하더라도 정상적인 서비스를 제공할 수 있도록 하는 것이 필요하다. 본 논문에서는 이러한 서버의 트래픽 폭주로 인한 서버 과부하 문제를 해결하기 위해 수락 제어 알고리즘을 이용한다. 수락 제어 기법은 컨텐츠 변환이나 로드 밸런싱과 같이 수동적으로 부하를 덜어주거나 분산시키는 방식이 아닌 트래픽에 제한을 가하여 능동적으로 서버의 부하를 조절하는 방식이다. 클라이언트에 의한 연결 요청이 이루어질 때 서버의 부하 상태를 평가한 후 서버가 수용 가능한 수준이면 클라이언트 새로운 연결 요청을 수락하여 이를 서비스할 수 있도록 한다. <중략> 또한 서비스 요청에 제한적인 정책을 따를 경우 서버의 부하 변화에 빠르게 반응하지만 QoS(Quality of Service)의 향상을 얻을 수 있는 반면 더 많은 서비스 요청을 수용하는 정책을 취할 경우 서버의 부하 변화에 대한 반응이 느리지만 throughput이 증가하는 이득을 얻을 수 있게 된다. QoS와 throughput가 서로 tradeoff 관계에 있다는 것을 알 수 있다. 또한 요구되는 서비스의 성격에 따라 즉 더 높은 수준의 QoS 보장이 중요한 서비스인가 아니면 더 높은 수준의 throughput 보장이 요구되는 서비스인가에 따라 다른 수락 제어 정책을 적용하는 것이 가능하게 된다.

• The Journal of Asian Finance, Economics and Business
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• 제8권5호
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• pp.345-354
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• 2021

With the evolution of containerization and globalization of supply chains, aspects of port functions have made the transition from the sea to the inland region that forms the dry port. To explore the relationship between dry ports and regional economic development, this study uses a gravity model and forecast model to analyze 1,040 observations in 104 cities (22 dry port cities) along the Yangtze River Economic Belt (YREB) from 2008 to 2017. The model includes economic variables, logistics variables, foreign relations variables, and human capital variables. It was found that the dry port is positively correlated with trade volume. Compared with a city without a dry port, the trade volume of a city with a dry port will increase 0.099 times. It can be concluded that a dry port is crucial for the economic development of the YREB. It was also found that per capita GDP as an economic variable, road area and rail number as logistics variables, and foreign relation variables are positively correlated with trade volume, while the human capital variable has no significant effect on trade volume. In addition, governmental policy implications are addressed from the aspects of dry port and industry cluster caused by foreign investment.

• International Journal of Advanced Culture Technology
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• 제7권2호
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• pp.238-243
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• 2019

Recently, the importance of big data continues to be emphasized, and it is applied in various fields based on data mining techniques, which has a great influence on the health care industry. There are many healthcare industries, but only home health care is considered here. However, applying this to real problems does not always give perfect results, which is a problem. Therefore, data mining techniques are used to solve these problems, and the algorithms that affect performance are evaluated. This paper focuses on the effects of healthcare services on patient satisfaction and satisfaction. In order to use the CVParameterSelectin algorithm and the SMOreg algorithm of the classify method of data mining, it was evaluated based on the experiment and the verification of the results. In this paper, we analyzed the services of home health care institutions and the patient satisfaction analysis based on the name, address, service provided by the institution, mood of the patients, etc. In particular, we evaluated the results based on the results of cross validation using these two algorithms. However, the existence of variables that affect the outcome does not give a perfect result. We used the cluster analysis method of weka system to conduct the research of this paper.

• 농촌계획
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• 제25권3호
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• pp.1-9
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• 2019

Population is important as a fundamental element of local industry and economy, and census data is essential to regional planning and policy making. Although there have been many researches on population and regional planning, there are few studies on population considering spatial unit. In this study, the population of three spatial scales were compared in order to establish the spatial unit suitable for the rural planning. The study area is Gangwon, Chungcheong-Nam, Chungcheong-Buk, Jeolla-Nam, Jeolla-Buk, Gyeonsang-Nam, Gyeonsang-Buk and Jeju province. Population were compared using statistical data analysis, GIS visualization, and spatial statistics. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. As the results, the census output area unit is difficult to interpret spatial analysis results. Administrative district unit has the limit that includes areas where the population does not live. The grid unit is well suited to the geographical characteristics but has many disadvantages of the grid with small population. Therefore, It is necessary to complement the limits of the Eup and Myeon-dong administrative district through the grid unit data.