• 제목/요약/키워드: Data trend analysis

검색결과 3,056건 처리시간 0.031초

체형의 변이 경향에 대한 연구 -우리나라 19~54세 남성을 대상으로- (A Study on the Trend of Bodytype Change -On the adult male between age 19 and 54-)

  • 김구자;이순원
    • 한국의류학회지
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    • 제20권1호
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    • pp.218-227
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    • 1996
  • The purpose of this study was performed to analyze the trend of bodytype change of adult males. Subjects were 1290 Korean adult males and their age range was from 19 to 54 year, ; old. 75 variables(66 variables from the direct anthropometric data and 9 variables from the multiplication method) in total were applied to analyze. The principal component analysis was applied to the data with orthogonal rotation after extraction of major factors. The high factor loading items extracted by factor analysis were analyzed for the trend of bodytype change by the age group respectively. The result of factor analysis indicated that the first factor was composed with about 30 items, girth, depth and width-measures in 4 age groups and was analysed as form factors. Especially, age-related change was caused by increase of waist girth, depth and width. The second factor was composed with about 23 items, length and height-measures in all age groups. Stature has a constant factor loading value in 4 groups. Front and back waist-height and the navel-height have the highest factor loading value. The third, fourth and fifth factors were composed with different variables among the age groups.

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패션브랜드 퍼스낼리티가 소비자의 브랜드 동일시 및 브랜드 충성도에 미치는 영향 (The Effect of Fashion Brand Personality on Consumer's Brand Identification and Brand Loyalty)

  • 장수진;이은영
    • 한국의류학회지
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    • 제32권1호
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    • pp.88-98
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    • 2008
  • The purpose of this study were to examine the effect of fashion brand personality on the consumer's brand loyalty and to investigate the role of brand identification as mediator. The questionnaire data from 218 women who had purchase experience of fashion luxury brands were collected. Factor analysis and multiple regression analysis were used in data analysis. The results of this study were as follows. First, the consumer's fashion brand personality was composed of eight factors; Status-oriented, appearance-oriented, trend-oriented, leisure-oriented, physical activity-oriented, self achievement-oriented, fun-oriented and relation-oriented factor. Second, brand identification had significantly influence on brand loyalty. Third, fashion brand personality significantly influenced on brand loyalty and brand identification. Especially, the status-oriented, appearance-oriented, trend-oriented and self achievement-oriented fashion brand personality was proved to have a crucial role in brand identification and brand loyalty. Fourth, the status-oriented, appearance- oriented, trend-oriented and self achievement-oriented fashion brand personality had both direct and indirect effects on brand loyalty mediated by brand identification.

빅데이터를 이용한 비건 패션 쟁점의 분석 -한국, 중국, 미국을 중심으로- (Perception and Trend Differences between Korea, China, and the US on Vegan Fashion -Using Big Data Analytics-)

  • 정지운;윤소정
    • 한국의류학회지
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    • 제47권5호
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    • pp.804-821
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    • 2023
  • This study examines current trends and perceptions of veganism and vegan fashion in Korea, China, and the United States. Using big data tools Textom and Ucinet, we conducted cluster analysis between keywords. Further, frequency analysis using keyword extraction and CONCOR analysis obtained the following results. First, the nations' perceptions of veganism and vegan fashion differ significantly. Korea and the United States generally share a similar understanding of vegan fashion. Second, the industrial structures, such as products and businesses, impacted how Korea perceived veganism. Third, owing to its ongoing sociopolitical tensions, the United States views veganism as an ethical consumption method that ties into activism. In contrast, China views veganism as a healthy diet rather than a lifestyle and associates it with Buddhist vegetarianism. This perception is because of their religious history and culinary culture. Fundamentally, this study is meaningful for using big data to extract keywords related to vegan fashion in Korea, China, and the United States. This study deepens our understanding of vegan fashion by comparing perceptions across nations.

Variogram Estimation of Tropospheric Delay by Using Meteorological Data

  • Kim, Bu-Gyeom;Kim, Jong-Heon;Kee, Changdon;Kim, Donguk
    • Journal of Positioning, Navigation, and Timing
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    • 제10권4호
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    • pp.271-278
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    • 2021
  • In this paper, a tropospheric delay error was calculated by using meteorological data collect from weather station and Saastamoinen model, and an empirical variogram of the tropospheric delay in the Korean peninsula was estimated. In order to estimate the empirical variogram of the tropospheric delay according to weather condition, sunny day, rainy day, and typhoon day were selected as analysis days. Analysis results show that a maximum correlation range of the empirical variogram on sunny day was about 560 km because there is overall trend of the tropospheric delay. On the other hand, the maximum correlation range of the empirical variogram on rainy was about 150 km because the regional variation was large. Although there is regional variation when the typhoon exists, there is a trend of the tropospheric delay due to a movement of the typhoon. Therefore, the maximum correlation range of the empirical variogram on typhoon day was about 280 km which is between sunny and rainy day.

스캠퍼 기법에 따른 여성 테일러드 재킷의 디자인 경향 (The Design Trend of Women's Tailored Jacket According to SCAMPER Method)

  • 이경림
    • 한국의상디자인학회지
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    • 제25권1호
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    • pp.133-152
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    • 2023
  • The purpose of this study is to provide basic data to assist students and designers in the fashion industry by examining the trend of designing women's wear using the SCAMPER method. In the research, five SCAMPER methods for fashion design were classified based on the previous studies. From 2018 S/S to 2022 F/W, data from 3,512 photographs were collected and checked for overlapping and were then classified by SCAMPER method. Data analysis was performed using SPSS 26 for frequency analysis. As a result, the most common application of the SCAMPER method was in 2022. First, the most used SCAMPER method for design was the "modify" method, changing details into various forms. The second method was the "adapt" method in which parts of the design or details were added and connected. The third mehtod was the "magnify" method of enlarging the length of the jacket. The fourth method was the "eliminate" method, removing parts of the jacket bodice, collar, or sleeves.

A Study on the Development of LDA Algorithm-Based Financial Technology Roadmap Using Patent Data

  • Koopo KWON;Kyounghak LEE
    • 한국인공지능학회지
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    • 제12권3호
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    • pp.17-24
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    • 2024
  • This study aims to derive a technology development roadmap in related fields by utilizing patent documents of financial technology. To this end, patent documents are extracted by dragging technical keywords from prior research and related reports on financial technology. By applying the TF-IDF (Term Frequency-Inverse Document Frequency) technique in the extracted patent document, which is a text mining technique, to the extracted patent documents, the Latent Dirichlet Allocation (LDA) algorithm was applied to identify the keywords and identify the topics of the core technologies of financial technology. Based on the proportion of topics by year, which is the result of LDA, promising technology fields and convergence fields were identified through trend analysis and similarity analysis between topics. A first-stage technology development roadmap for technology field development and a second-stage technology development roadmap for convergence were derived through network analysis about the technology data-based integrated management system of the high-dimensional payment system using RF and intelligent cards, as well as the security processing methodology for data information and network payment, which are identified financial technology fields. The proposed method can serve as a sufficient reason basis for developing financial technology R&D strategies and technology roadmaps.

빅데이터 분석 기반의 메타스터디를 통해 본 공유경제에 대한 학술연구 동향 분석 (Trends Analysis on Research Articles of the Sharing Economy through a Meta Study Based on Big Data Analytics)

  • 김기연
    • 인터넷정보학회논문지
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    • 제21권4호
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    • pp.97-107
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    • 2020
  • 본 연구의 목적은 빅데이터 분석기법을 활용하여 공유경제 관련 국내 학술연구 동향을 탐색하기 위해 내용분석 관점에서 종합적 메타스터디를 수행하는데 있다. 종합적 메타분석 연구방법론은 일련의 전체 연구결과물들을 역사적으로 그리고 포괄적으로 살펴봄으로써 전체 연구동향의 규칙성이나 특성을 조명하여, 이를 통해 향후 연구에 대해 방향성을 제시할 수 있다. 공유경제를 주제로 하는 국내 학술연구는 Lawrence Lessig 교수가 2008년에 공유경제의 개념을 세상에 소개한 해에 등장하였으나, 본격적인 연구는 2013년부터 진행되었다. 특히, 2006~2008년 사이에 국내 공유경제 관련 학술연구는 양적으로 급격히 증가하였다. 본 연구는 2013년부터 현재까지 약 8년간의 논문들을 분석 논문으로 선정하고, 전자저널의 학술논문검색 및 원문서비스를 이용하여 제목, 키워드, 초록을 중심으로 텍스트 데이터를 수집하였다. 수집된 데이터를 정제, 분석, 시각화의 순서로 빅데이터 분석을 실시하여, 추출된 핵심어들을 통해 연도별 및 문헌 유형별 연구동향 및 인사이트를 도출하였다. 데이터 전처리 및 텍스트 마이닝, 메트릭스 빈도분석을 위해 Python3.7과 Textom 분석도구를 활용하였고, 핵심어 노드 간의 구조적 연관성을 파악하기 위해 UCINET6/NetDraw, Textom 프로그램 기반의 N-gram 차트, 중심성 및 소셜네트워크 분석, 그리고 CONCOR 클러스터링 시각화를 통해 8개로 군집화 한 키워드들을 토대로 연구동향의 유형별 특성을 발견하였다. 아직까지 사회과학적 관점에서 공유경제 관련 학술연구 동향에 관한 조사가 이루어진 바가 없기 때문에, 본 연구의 결과물은 선행연구로서 후속 연구들에게 이론적 고찰 및 향후 연구방향에 대해 유용한 정보를 제공하는 초석의 역할을 기대할 수 있다.

가스터빈 엔진의 손상 진단을 위한 퍼지 경향감시 방법에 관한 연구 (A Study on Fuzzy Trend Monitoring Method for Fault Detection of Gas Turbine Engine)

  • 공창덕;고성희;기자영;오성환;김지현;고한영
    • 한국추진공학회지
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    • 제12권6호
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    • pp.1-6
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    • 2008
  • 본 연구에서는 계측 데이터의 성능 추이를 분석하여 가스터빈 엔진의 결함 여부를 탐지하기 위한 퍼지 경향감시 방법을 제안하였다. 제안된 경향감시 방법은 연료유량, 배기가스 온도, 로터회전수, 진동수와 같은 중요 엔진 파라미터를 모니터링 하여 시간에 따른 변화를 분석하여 엔진 상태를 진단하는 것이다. 이를 위해 먼저 선형회귀분석을 통해 엔진 상태 변화를 수식화하고 퍼지 로직을 통해 진단 결과를 분석하여 예측되는 손상 원인을 제시한다.

Trend Monitoring of A Turbofan Engine for Long Endurance UAV Using Fuzzy Logic

  • Kong, Chang-Duk;Ki, Ja-Young;Oh, Seong-Hwan;Kim, Ji-Hyun
    • International Journal of Aeronautical and Space Sciences
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    • 제9권2호
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    • pp.64-70
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    • 2008
  • The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results. it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

2020년 재난적 의료비 경험률 현황 및 추이 (Catastrophic Health Expenditure and Trend of South Korea in 2020)

  • 정성훈;강수현;박은철
    • 보건행정학회지
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    • 제32권1호
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    • pp.107-112
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    • 2022
  • Catastrophic healthcare expenditure refers to out-of-pocket spending for healthcare exceeding a certain proportion of a household's income and can lead to subsequent impoverishment. The aim of this study was to investigate the proportion of South Korean households that experienced catastrophic healthcare expenditure between 2006 and 2020 using available data from the National Survey of Tax and Benefit (NaSTaB), Korea Health Panel (KHP), and Households Income and Expenditure Survey (HIES). Trend test was used to analyze the proportion of household with catastrophic healthcare expenditure. In the NaSTaB 2020 data, households who experienced catastrophic health expenditure was 1.73%. Trend analysis was significant with the decreasing trend (annual percentage change [APC], -5.55; p<0.0001) in the proportion of households with the catastrophic health expenditure. Also, in the 2018 KHP and the 2016 HIES, households who experienced catastrophic health expenditure was 2.21% and 2.92% respectively. In contrast, the trend was significantly increased in the KHP (APC, 0.55; p<0.0001) and the HIES (APC, 1.43; p<0.0001). Therefore, the findings suggest the need to strengthen public health care financial support and monitor catastrophic healthcare expenditures, especially for low-income group.