• Title/Summary/Keyword: Measurement Model

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Performance Measurement Model for Open Big Data Platform (공공 빅데이터 플랫폼 성과평가 모형)

  • RHEE, Gyuyurb;Park, Sang Cheol;Ryoo, Sung Yul
    • Knowledge Management Research
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    • v.21 no.4
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    • pp.243-263
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    • 2020
  • The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of open big data. Our proposed model consists of five key building blocks for measuring performance of open data platform as follows: stakeholder contribution, big data governance capabilities, big data service capabilities, big data IT capabilities, and stakeholder satisfaction. In addition, our proposed model have twenty four evaluation indices and seventy five measurement items. We believe that our model could offer both research and practical implications for relevant research.

Development of Composite Load Models of Power Systems using On-line Measurement Data

  • Choi Byoung-Kon;Chiang Hsiao Dong;Li Yinhong;Chen Yung Tien;Huang Der Hua;Lauby Mark G.
    • Journal of Electrical Engineering and Technology
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    • v.1 no.2
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    • pp.161-169
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    • 2006
  • Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.

Fuzzy-Model-Based Kalman Filter for Radar Tracking

  • Lee, Bum-Jik;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.311-314
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    • 2003
  • In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

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Comparative Study on Proposed Simulation Based Optimization Methods for Dynamic Load Model Parameter Estimation (동적 부하모델 파라미터 추정을 위한 시뮬레이션 기반 최적화 기법 비교 연구)

  • Del Castillo, Manuelito Jr.;Song, Hwa-Chang;Lee, Byong-Jun
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.187-188
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    • 2011
  • This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

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Measurement Error Model with Skewed Normal Distribution (왜도정규분포 기반의 측정오차모형)

  • Heo, Tae-Young;Choi, Jungsoon;Park, Man Sik
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.953-958
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    • 2013
  • This study suggests a measurement error model based on skewed normal distribution instead of normal distribution to identify slope parameter properties in a simple liner regression model. We prove that the slope parameter in a simple linear regression model is underestimated.

Measurement-Based Propagation Channel Characteristics for Millimeter-Wave 5G Giga Communication Systems

  • Lee, Juyul;Liang, Jinyi;Kim, Myung-Don;Park, Jae-Joon;Park, Bonghyuk;Chung, Hyun Kyu
    • ETRI Journal
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    • v.38 no.6
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    • pp.1031-1041
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    • 2016
  • This paper presents millimeter-wave (mmWave) propagation characteristics and channel model parameters including path loss, delay, and angular properties based on 28 GHz and 38 GHz field measurement data. We conducted measurement campaigns in both outdoor and indoor at the best potential hotspots. In particular, the model parameters are compared to sub-6 GHz parameters, and system design issues are considered for mmWave 5G Giga communications. For path loss modeling, we derived parameters for both the close-in free space model and the alpha-beta-gamma model. For multipath models, we extracted delay and angular dispersion characteristics including clustering results.

Development of Performance Measurement Model for Cloud Companies (클라우드 기업의 성과측정모형 개발)

  • Seo, Kwang-Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.20 no.3
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    • pp.39-44
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    • 2021
  • Since the recent Corona 19, the importance of cloud computing is increasing, and at the same time, competition among clouds is intensifying. Cloud companies are competing for survival by promoting various management innovation methods for continuous growth and development amid a rapidly changing business environment. They are also increasingly interested in performance management in their operations and growth. In this paper, we propose Cloud BSC, an IT BSC-based performance measurement model for cloud enterprise performance management. The validity of the proposed model is verified through statistical analysis and causal analysis. Eventually, the proposed model is expected to be utilized as a management evaluation tool that can provide useful performance analysis information to cloud companies.

The Study on Intellectual Assets Measurement Model of Construction Corporation (건설기업 지적자산 측정모델에 관한 연구)

  • Son Young-Chan;Baik Jong-Keon;Kim Jae-Jun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • autumn
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    • pp.257-260
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    • 2002
  • Performance measurement in corporation administration is very important. Though there is measurement, grasp problem, and because can improve. Corporation's tangible measuring is possible by specific amount of money of financial statement or loss and gain statement etc. but corporation's intangible property measurement isn't objective and there is no quantitative measurement method. So this research presents model which can do size of construction corporation's intangible property(Intellectual Assets) through model that measure corporation's intellectual assets to do quantification objectively and wish to present development direction of measurement method.

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A Study on the Modeling and Propagation to Evaluate Uncertainties in Measurement Results (측정결과의 불확도산정을 위한 모델링과 불확도 전파에 관한 연구)

  • 김종상;조남호
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.4
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    • pp.165-175
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    • 2003
  • The concept of measurement uncertainty has been recognised for many years since "Guide to the Expression of Uncertainty in Measurement" was published 1993 by ISO. This study firstly propose the mathematical model to evaluate uncertainty considering the dispersion of samples because the mathematical model of a measurement is an important to evaluate uncertainty, and it must contains every quantify which contribute significantly to uncertainty in the measurement result. Secondly the standard uncertainty of the result of a measurement, namely combined standard uncertainty is evaluated using the law of propagation of uncertainty, what is termed in GUM method. In GUM method, a measurand is usually approximated by a linear function of its variables by the transforming its input quantities. Furthermore central limit theorem is applied to the input quantity. However the mathematical model of a measurement is generally not always a linearity function, and a distribution function of input or output quantity is not necessarily normal distribution. Then, in some cases GUM method is not favorable to evaluate a measurement uncertainty. Therefore this study propose a new method and its algorithm which use the Monte-carlo simulation to evaluate a measurement uncertainty in both case of linearity or non-linearity function. function.

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An Experimental Study on Generation and Measurement Method of EG/AD Model Ice at Cold Room for Improvement of Its Properties (EG/AD 모형빙 정도 향상을 위한 콜드룸에서의 생성기법 및 계측기법 연구)

  • Cho, Seong-Rak;Jeong, Seong-Yeob;Ha, Jung-Seok;Kang, Kuk-Jin
    • Journal of the Society of Naval Architects of Korea
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    • v.50 no.6
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    • pp.414-420
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    • 2013
  • Generation and measurement methods of EG/AD model ice, which is used in KIOST ice model basin are investigated for improvement of its properties. Temperature of seed water, air temperature in the freezing phase and the target air temperature in the tempering phase were changed in the cold room, and the properties of model ice was measured in this conditions. We also verified a conventional measuring method of flexural strength of model ice caused a little measuring error in cold room, so that we suggested a new measuring method that must be used higher supports than double the thickness of the model ice. In this study, we improved the generation and measurement technique of EG/AD model ice, and the developed procedure at cold room can be applied to the KIOST ice model basin.