• Title/Summary/Keyword: 동질성분석

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The Effect of Foreign Crew's Cultural Homogeneity on the Self-efficacy and Organizational Commitment (혼승선박 내 외국인선원의 문화적 동질성이 자기효능감과 조직커미트먼트에 미치는 영향)

  • Chung, Young-Sub;Shin, Yong-John;Pai, Hoo-Seok
    • Journal of Navigation and Port Research
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    • v.30 no.8 s.114
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    • pp.643-648
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    • 2006
  • The primary purpose of this study is to examine empirically the effect of foreign crew's cultural and organizational characteristics on their self-efficacy and organization commitment. Currently, the restrictions on the employment of the foreign crews are being eased in the Korean shipping industry and many problems are occurring consequently. However, specific and empirical studies on the relevancy of cultural characteristics to the crew's self-efficacy and organizational commitment on board the vessels with combined crews have not yet been carried out. To solve these problems, we examined how the cultural characteristics such as acculturation and accommodation of different culture related to the improvement of cultural homogeneity of vessels with combined crews influence on the self-efficacy, job satisfaction and organizational commitment of the foreign crews through SEM analysis. According to the results, hypothesis 1 and 2 were all supported with statistical significance. To conclude, this study suggests that foreign crew's cultural homogeneity and their self-efficacy should be firstly enhanced in order to improve organizational commitment on the vessel with combined crews. Furthermore, a study on self-efficacy of crew organization is urgently needed to enhance the effectiveness of an organization in a vessel with combined crews that has special environment. The result of this study will contribute a lot to the organization management of a vessel with combined crews.

Regional Characterization Analysis of Drought in Korea Using Multivariate Analyses (다변량 분석을 통한 우리나라 가뭄의 지역적 특성 분석)

  • Yoo, Ji-Young;Choi, Min-Ha;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1462-1466
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    • 2009
  • 우리나라 가뭄의 지역적 특성은 수문학적으로 동질한 지역의 구분 결과에 따라 달라진다. 지역의 구분에는 가뭄에 영향을 미치는 다양한 변수들이 사용될 수 있다. 가뭄을 특징짓는 요소로서 지속기간, 심도, 이외의 통계적 특성들이 있으며, 이 변수들을 정보화하여 변수의 유형을 구분지어 모든 변수들을 요약된 정보로 활용하여 가뭄의 특성을 구분할 수 있다. 본 연구에서는 우리나라 기상청 강우자료 75개 관측지점 중 30년 미만의 강우기록이 있는 17개의 지점을 제외한 58개 강우 관측 지점을 대상으로 가뭄지수(SPI)를 산정하여 가뭄사상의 특성을 정량화 과정으로 남한지역 가뭄특성을 분류하였다. SPSS를 활용한 다변량 분석기법인 주성분 분석(principal component analysis)을 통해 가뭄특성인자의 상관관계가 높은 변수들을 조합하여 그 변수들 중 가뭄정보를 가능한 많이 함축하고 있는 새로운 특성 변수를 만들어 내었으며, 선정된 변수들을 바탕으로 요인분석(factor analysis)의 직각회전 방식(Varimax)을 이용하여 변수들의 표준화를 통해 가뭄특성요인을 찾아내었다. 이를 통해 지역간 동질성을 파악하여 K-means기법을 적용하여 군집해석(clustering analysis)을 실시하였다.

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A Study on Ecotope Diversity Improvement effectiveness Analysis in the Middle of Mankyung River Restoration Scenario (만경강 하천공간복원 시나리오의 에코톱 개선효과 분석)

  • Kim, Woo Ram;Jeon, Ho Seong;Kim, Ji Sung;Hong, Il;Kim, Kyu Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2018.05a
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    • pp.434-434
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    • 2018
  • 에코톱은 가장 작고 균일하며 도면의 단위로 사용 가능한 토지, 일반적인 구성요소의 상태, 잠재자연식생, 잠재생태계 기능을 최소한의 단위로 균일하게 분류가 가능한 요소로서 천이단계 또는 토지이용이 서로 다른 패치들로 이루어진 무생물과 생물이 결합된 생태공간으로서 일반적으로 세가지 특성을 포함한다. (1) 가장 작은 동질성 가진 지도로 분류 가능한 단위, (2) 일반적인 기질조건, 잠재적 자연식생 및 잠재적 생태계 기능에 대한 동질성, 그리고 (3) 서로 다른 연속적인 토지 이용 단계에서의 패치로 구성 된다. 현재 네덜란드, 스페인을 포함한 유럽국가에서는 에코톱분류를 통한 하천을 관리하는 방안을 제시하고 있으며 이에 대한 많은 연구가 진행되고 있다. 본 연구에서는 만경강 중류 소양천 합류점의 터지네 구간을 대상으로 하천공간의 복원 이후 연중유황에 따른 에코톱의 변화를 예측하고 이에 따른 개선효과를 정량적으로 분석하는 것이 목적이다. 제방 후퇴, 제방후퇴/구하도 복원, 제방 후퇴/습지 조성 세가지 복원 시나리오를 현재지형과 비교하여 연중 유황별 흐름조건에 따라 에코톱을 도식화 하였으며, 이에 따른 에코톱 다양성 지수를 도출하여 비교분석하였다. 복원 대상지의 복원 시나리오 및 흐름조건에 따른 에코톱의 변화를 분석한 결과 '제방 후퇴/구하도 복원' 일 때 자연요소가 현재지형보다 가장 크게 증가되었으며 3가지 복원 유형 간 자연요소를 비교한 결과 '제방 후퇴/구하도 복원' 일 때 수역과 일년생 초본이 가장 많은 면적을 차지하였으며, '제방 후퇴/습지 조성' 일 때 습지와 다년생 초본이 가장 많은 면적을 차지하였다. 복원 유형 별 연중 유황 조건에 따른 에코톱 다양성 지수분석결과 제방후퇴/습지 조성시 에코톱 다양성 개선효과가 가장 큰 것으로 나타났다.

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Regional frequency analysis using spatial data extension method : I. An empirical investigation of regional flood frequency analysis (공간확장자료를 이용한 지역빈도분석 : I. 지역홍수빈도분석의 실증적 검토)

  • Kim, Nam Won;Lee, Jeong Eun;Lee, Jeongwoo;Jung, Yong
    • Journal of Korea Water Resources Association
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    • v.49 no.5
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    • pp.439-450
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    • 2016
  • For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.

Online news-based stock price forecasting considering homogeneity in the industrial sector (산업군 내 동질성을 고려한 온라인 뉴스 기반 주가예측)

  • Seong, Nohyoon;Nam, Kihwan
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.1-19
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    • 2018
  • Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

우리나라 주요항만의 최극해면 재분석

  • 최병호;김동철
    • Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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    • 1996.10a
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    • pp.55-59
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    • 1996
  • 전회의 극치확률모형에 의한 해면분석(최, 1982)은 자료연장이 증가됨에 따라 재분석(update)이 이루어졌다. 검조자료의 연장이 35년 정도로 확장된 시점에서 특히 주요검조소의 인근에서 방조제, 하구둑(군산, 목포), 검조소 이전(인천), 대규모 매립(여수)이 수행되어 조석체계가 변화되는 양상이 있어 년극치 역시 동질성의 확보에 문제가 있어 년조석분석과 동시에 이러한 조석변화를 확인하였다. 더불어 년극치(annual extreme) 역시 그룹핑시켜 이를 분석하였다. (중략)

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Optimum Size Analysis for Dam Rehabilitation Using Reliability Analysis (신뢰성 분석을 통한 기존 댐 재개발의 적정규모 결정의 관한 연구)

  • Kwon, Hyun-Han;Moon, Young-Il;Choi, Byung-Gyu;Yoon, Yong-Nam
    • Journal of Korea Water Resources Association
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    • v.38 no.2
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    • pp.97-110
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    • 2005
  • This paper presents a procedure of evaluation of reservoir capacity for additional water storage for dam rehabilitation. One of the techniques on the extension of rainfall has been developed, and the daily stream flows were simulated by the NWS-PC long-term rainfall-runoff model with the input of the extended daily rainfall which was stochastically generated by the nonhomogeneous markov chain model. We peformed a reliability analysis to Guisan dam about the optimal capacity of dam rehabilitation by using performance criteria that Hashimoto et al. (1982) presented. We estimated that the most suitable water level is approximately 155EL.M. suggested that this method can use supplemental methods to estimate optimum dam scale.

The evaluation of aid effectiveness using the input-output analysis: the case of Vietnam (산업연관분석을 활용한 원조의 국가단위 효과 평가 - 한국 유상원조의 베트남 지원효과를 중심으로 -)

  • Park, Bokyeong;An, Jiyoun
    • International Area Studies Review
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    • v.22 no.2
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    • pp.211-218
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    • 2018
  • The evaluation of aid effectiveness at the national level has mostly focused on qualitative evaluation. This paper attempts to quantitatively evaluate EDCF 's support for Vietnam in 1995 ~ 2016 on the economy. First, we compare the strengths and weaknesses of various methodologies that can be used for quantitative assessment: panel analysis based on growth theory, input-output analysis, social account matrix analysis, CGE model, DSGE model, and time series analysis. Using the input-output analysis, we estimate that total output and value added have been generated about $5.9 billion and $1.7 billion in Vietnam, respectively. The increase in income per capita from the support was estimated to have contributed to a 0.21%p reduction in the poverty rate in Vietnam.

Study on Scaling Exponent for Classification of Regions using Scaling Property (스케일 성질을 이용한 군집 지역에서의 스케일 인자에 대한 연구)

  • Jung, Younghun;Kim, Sunghun;Ahn, Hyunjun;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.504-504
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    • 2015
  • 수공구조물을 설계하기 위해서는 설계수문량을 빈도해석을 통해 산정할 수 있다. 빈도해석 중 지점빈도해석을 보완한 지역빈도해석을 적용하기 위해서는 군집분석을 통한 지역구분이 무엇보다 중요하다. 또한 스케일 성질(scaling property)은 강우의 시 공간적 특성을 지속기간별 관측된 강우자료를 이용하여 재현기간에 대한 지속기간의 함수로 강우의 IDF곡선을 제시할 수 있는 방법이다. 따라서 스케일 성질을 통해 군집된 지역에서의 강우자료에 적용하여 스케일 인자(scaling exponent)를 추정한 후 수문학적 동질성을 통계적 특성으로 설명하고자 한다. 본 연구를 수행하기에 앞서 군집 분석은 4개의 군집방법(평균연결법, Ward방법, Two-Step방법, K-means방법)을 적용하였고, 한강유역에 위치한 104개의 강우지점은 4개의 지역으로 구분하는 것이 적절하다고 판단되어 비계층적 방법인 k-means방법을 이용하여 지역을 구분하였다. 본 연구에서는 군집된 결과를 바탕으로 4개의 지역으로 구분된 지역에 포함된 강우지점을 대상으로 스케일 인자를 추정하고 수문학적 동질성을 통계적 방법으로 제시하고자 한다.

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Case analysis for constructing a homogeneous learning group in programming lessons for non-specialists (비전공자를 대상으로 한 프로그래밍 수업에서 동질적 학습 집단 구성을 위한 사례 분석)

  • Lee, Kyung-Sook
    • Journal of Digital Convergence
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    • v.17 no.12
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    • pp.59-65
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    • 2019
  • The purpose of this study is to investigate the effects of the learning environment on the learning achievement of the learners and to improve the learning achievement of the learners while accepting the fact that it is difficult to change the class environment in which the middle and large group. Among the learner's positive and cognitive factors, we examined the factors that can classify learners into homogeneous groups in programming learning. The difficulty level of the learning contents influenced factors that classify the homogeneous group, and the factors were analyzed by dividing the intermediate difficulty and the final achievement. In addition, we examined the factors that affect the difference between two grades in order to analyze factors affecting steady learning regardless of difficulty level. It was found that the learners' personal motivation influenced the learning achievement of easy learning contents, and the performance self - efficacy had influence on the learning achievement and achievement of difficult learning contents.