• Title/Summary/Keyword: 패널데이터

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The Effects of AEO Certification on Firm's Performance : Panel Data Analysis (AEO 인증이 기업성과에 미치는 영향 : 패널데이터 분석)

  • Ha, Eui-Hyun
    • Korea Trade Review
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    • v.41 no.4
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    • pp.91-110
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    • 2016
  • AEO certification has a positive effect on firm's performance. Therefore, this study analyzed the effect of AEO certification on firm's performance using panel data analysis for firm to have international competitiveness. It uses the Hausman-Taylor test for effective solutions of endogenous matter. In terms of the result of analysis, AEO certification has a positive effect on domestic and foreign sales, especially direct benefit and business process improvement of AEO certification have a positive effect on domestic and foreign sales through the improvement of international logistics flow. In conclusion, this study proposes the policy of AEO certification by analyzing the effect of AEO certification on firm's performance by using the panel data analysis.

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Backpropagation Algorithm based Fault Detection Model of Solar Power Generation using Weather Data and Solar Power Generation Data (기후데이터와 태양광발전 데이터를 이용한 역전파 알고리즘 기반 패널 결함 검출 방법)

  • Lee, Seung Min;Lee, Woo Jin
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.04a
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    • pp.795-797
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    • 2015
  • 태양광발전의 단점 중 하나인 불규칙 전력 생산문제로 인해, 장비 및 패널 결함에 실시간 대응하지 못하는 문제가 발생한다. 태양광패널 결함을 자동 검출하기 위해 기후데이터 및 패널 정보를 이용하여 신경망에 적용하고 역전과 알고리즘을 통해 학습하는 발전량 예측 및 실시간 결함 검출 모델을 제안한다.

Dynamic Model Considering the Biases in SP Panel data (SP 패널데이터의 Bias를 고려한 동적모델)

  • 남궁문;성수련;최기주;이백진
    • Journal of Korean Society of Transportation
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    • v.18 no.6
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    • pp.63-75
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    • 2000
  • Stated Preference (SP) data has been regarded as more useful than Revealed Preference (RP) data, because researchers can investigate the respondents\` Preference and attitude for a traffic condition or a new traffic system by using the SP data. However, the SP data has two bias: the first one is the bias inherent in SP data and the latter one is the attrition bias in SP panel data. If the biases do not corrected, the choice model using SP data may predict a erroneous future demand. In this Paper, six route choice models are constructed to deal with the SP biases, and. these six models are classified into cross-sectional models (model I∼IH) and dynamic models (model IV∼VI) From the six models. some remarkable results are obtained. The cross-sectional model that incorporate RP choice results of responders with SP cross-sectional model can correct the biases inherent in SP data, and also the dynamic models can consider the temporal variations of the effectiveness of state dependence in SP responses by assuming a simple exponential function of the state dependence. WESML method that use the estimated attrition probability is also adopted to correct the attrition bias in SP Panel data. The results can be contributed to the dynamic modeling of SP Panel data and also useful to predict more exact demand.

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Cloud Computing Adoption Decision-Making Modeling Using CART (CART 방법론을 사용한 클라우드 컴퓨팅 도입 의사 결정 모델링)

  • Baek, Seung Hyun;Chang, Byeong-Yun
    • Journal of the Korea Society for Simulation
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    • v.23 no.4
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    • pp.189-195
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    • 2014
  • In this paper, we conducted a study on place-free and time-free cloud computing (CC) adoption decision-making model. Panel survey data which is collected from 65 people and CART (classification and regression tree) which is one of data mining approaches are used to construct decision-making model. In this modeling, there are 2 steps: In the first step, significant questions (variables) are selected. After that, the CART decision-making model is constructed using the selected variables. In the variable selection stage, the 25 questions are reduced to 5 ones. The benefits of question reduction are quick response from respondent and reducing model-construction time.

Image Generator Design for OLED Panel Test (OLED 패널 테스트를 위한 영상 발생기 설계)

  • Yoon, Suk-Moon;Lee, Seung-Ho
    • Journal of IKEEE
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    • v.24 no.1
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    • pp.25-32
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    • 2020
  • In this paper, we propose an image generator for OLED panel test that can compensate for color coordinates and luminance by using panel defect inspection and optical measurement while displaying images on OLED panel. The proposed image generator consists of two processes: the image generation process and the process of compensating color coordinates and luminance using optical measurement. In the image generating process, the panel is set to receive the panel information to drive the panel, and the image is output by adjusting the output setting of the image generator according to the panel information. The output form of the image is configured by digital RGB method. The pattern generation algorithm inside the image generator outputs color and gray image data by transmitting color data to a 24-bit data line based on a synchronization signal according to the resolution of the panel. The process of compensating color coordinates and luminance using optical measurement outputs an image to an OLED panel in an image generator, and compensates for a portion where color coordinates and luminance data measured by an optical module differ from reference data. To evaluate the accuracy of the image generator for the OLED panel test proposed in this paper, Xilinx's Spartan 6 series XC6SLX25-FG484 FPGA was used and the design tool was ISE 14.5. The output of the image generation process was confirmed that the target setting value and the simulation result value for the digital RGB output using the oscilloscope matched. Compensating the color coordinates and luminance using optical measurements showed accuracy within the error rate suggested by the panel manufacturer.

한국 소프트웨어 기술혁신의 구조 변동

  • Choe, Yong-Jin
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2017.05a
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    • pp.619-619
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    • 2017
  • 현대사회의 제품생산과 기업활동에서 소프트웨어의 중요성과 그 가치가 날로 높아져 가는 가운데 소프트웨어 기술혁신은 과거 소프트웨어 산업 영역에 국한되었던 비교적 작은 구조에서 이제는 다양한 산업 영역에서 다발적으로 일어나는 보다 넓은 구조로 변모하고 있다. 이 연구에서는 한국 출원인이 포함된 약 270만 건의 특허 메타데이터와 기업정보 데이터를 활용한 패널데이터를 구축하여 한국 산업계 전반에 걸쳐 일어나고 있는 소프트웨어 기술혁신의 구조 변동 현상을 밝혀내고, 이를 토대로 정부의 소프트웨어 산업 정책에 관한 함의를 도출하고자 한다. 이 연구는 다음의 네 부분으로 구성이 된다. 첫째, 최근 여러 분야에서 일어나고 있는 소프트웨어와 타 산업 간의 융합 현상과 이에 대한 이론적 논의를 전개한다. 둘째, 연구에 활용 할 데이터와 실증분석 방법론에 관하여 논의한다. 셋째, 패널분석을 기초로 한 실증분석을 수행하고, 그 결과를 제시한다. 넷째, 한국정부의 소프트웨어 산업 정책을 살펴보고, 이를 바탕으로 실증분석 결과가 지니는 함의에 관하여 논의한다.

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A Study on the Influence of the Urban Characteristics on the Incidence of Crime Using Panel Model (패널모형을 이용한 도시특성요소가 범죄 발생에 미치는 영향 분석)

  • Lee, Hyo Jin;Lee, Jae Song;Choi, Yeol
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.6
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    • pp.1439-1449
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    • 2015
  • This study, based on the sociological crime theory, is to examine the relation between urban characteristics and the incidence of crime, helping establish effective crime prevention measures. For doing so, the study employs crime data from the Supreme Prosecutors' Office and socio-demographic data including the regional Statistical Yearbooks -both from 2005 to 2012- to build the study's panel data, and analyzes the panel model on the 16 subordinate districts in the city of Busan. To reduce the incidence of crime and prevent crimes from occurring based on the analysis results, first, prevention measures specific to each region by its attributes are needed rather than general ones; second, new institutional frameworks or policies are required for utilizing accurate crime data; third, interdisciplinary research in which various fields including urban engineering are associated to that of social science is necessary to further the study.

Panel data analysis with regression trees (회귀나무 모형을 이용한 패널데이터 분석)

  • Chang, Youngjae
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1253-1262
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    • 2014
  • Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

Mathematical Algorithms for the Automatic Generation of Production Data of Free-Form Concrete Panels (비정형 콘크리트 패널의 생산데이터 자동생성을 위한 수학적 알고리즘)

  • Kim, Doyeong;Kim, Sunkuk;Son, Seunghyun
    • Journal of the Korea Institute of Building Construction
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    • v.22 no.6
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    • pp.565-575
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    • 2022
  • Thanks to the latest developments in digital architectural technologies, free-form designs that maximize the creativity of architects have rapidly increased. However, there are a lot of difficulties in forming various free-form curved surfaces. In panelizing to produce free forms, the methods of mesh, developable surface, tessellation and subdivision are applied. The process of applying such panelizing methods when producing free-form panels is complex, time-consuming and requires a vast amount of manpower when extracting production data. Therefore, algorithms are needed to quickly and systematically extract production data that are needed for panel production after a free-form building is designed. In this respect, the purpose of this study is to propose mathematical algorithms for the automatic generation of production data of free-form panels in consideration of the building model, performance of production equipment and pattern information. To accomplish this, mathematical algorithms were suggested upon panelizing, and production data for a CNC machine were extracted by mapping as free-form curved surfaces. The study's findings may contribute to improved productivity and reduced cost by realizing the automatic generation of data for production of free-form concrete panels.

Improved Parameter Extraction Algorithm for Photovoltaic Array Circuit Model (태양광 패널의 등가회로 모델링 알고리즘 개선)

  • Park, Jun-Young;Choi, Sung-Jin
    • Proceedings of the KIPE Conference
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    • 2014.07a
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    • pp.369-370
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    • 2014
  • 태양광 PCS개발과정에서는 온도나 방사량 등을 변화시키며 태양전지 패널의 I-V곡선을 모사할 수 있는 태양광 시뮬레이션 모델이 필요하다. 이러한 용도로 볼 때 특히 다이오드 기반의 등가회로 모델은 물리적인 성질을 바탕으로 태양광 패널의 특성을 비교적 정확히 설명할 수 있으나 특유의 비선형성으로 인하여 복잡한 회로 모델 파라미터 추출 기법을 필요로 한다. 본 논문에서는데이터 시트값에 기반한 새로운 태양광 패널 회로 모델링 알고리즘을 제안한다. 제안한 방법의 성능을 검증하기 위해 단결정 태양광 패널의 실제 데이터를 기반으로 최대전력점 ${\pm}10%$부근의 전류오차 적분값을 기준으로 기존 방법과 정확도를 비교한 결과 20%의 정확도 개선을 얻었다.

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