• Title/Summary/Keyword: metamodel

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Design and Implementation of Sensor Registry Data Model for IoT Environment (IoT 환경을 위한 센서 레지스트리 데이터 모델의 설계 및 구현)

  • Lee, Sukhoon;Jeong, Dongwon;Jung, Hyunjun;Baik, Doo-Kwon
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.5
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    • pp.221-230
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    • 2016
  • With emerging the Internet of Things (IoT) paradigm, the sensor network and sensor platform technologies have been changed according to exploding amount of sensors. Sensor Registry System (SRS) as a sensor platform is a system that registers and manages sensor metadata for consistent semantic interpretation in heterogeneous sensor networks. However, the SRS is unsuitable for the IoT environment. Therefore, this paper proposes sensor registry data model to register and manager sensor information in the IoT environment. We analyze Semantic Sensor Network Ontology (SSNO) for improving the existed SRS, and design metamodel based on the analysis result. We also build tables in a relational database using the designed metamodel, then implement SRS as a web application. This paper applies the SSNO and sensor ontology examples with translating into the proposed model in order to verify the suitability of the proposed sensor registry data model. As the evaluation result, the proposed model shows abundant expression of semantics by comparison with existed models.

A Study for Design Optimization of an Automated Distribution Center using the Simulation and Metamodel (시뮬레이션과 메타모델을 이용한 자동물류센터 설계 최적화)

  • Kang, Jeong-Yun;Lee, Hong-Chul;Um, In-Sup
    • Journal of the Korea Society for Simulation
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    • v.15 no.3
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    • pp.103-114
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    • 2006
  • Now distribution centers include an ASRS (Automated Storage and Retrieving System) and automated transfer systems such as conveyors and AGV (Automated Guided Vehicle). These automated distribution centers have lots of parameters to be considered fur operating performance. The general basic parameters in the distribution centers are specifications of storage equipment, system operating rules, configuration of storage area and unit load features. In this paper, an approach using simulation and metamodeling with response Surface method to optimize the design parameters of an automated distribution center model is presented. The simulation based metamodel will constitute an efficient approximation of the system function, and the approximate function will be used to design rapid optimal parameters of the distribution center model. This paper provides a comprehensive framework for economical material flow system design using the simulation and metamodeling.

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Efficient Robust Design Optimization Using Statistical Moments Based on Multiplicative Decomposition Method (곱분해 기법 기반의 통계 모멘트를 이용한 효율적인 강건 최적설계)

  • Cho, Su-Gil;Lee, Min-Uk;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.10
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    • pp.1109-1114
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    • 2012
  • The performance of a system can be affected by various variables such as manufacturing tolerances, uncertainties of material properties, and environmental factors acting on the system. Robust design optimization has attracted much attention in the design of products because it can find the best design solution that minimizes the variance of the response while considering the distribution of the variables. However, the computational cost and accuracy of optimization have thus far been a challenging problem. In this study, robust design optimization using the multiplicative decomposition method is proposed in order to solve these problems. Because the proposed method calculates the mean and variance of the system directly from the kriging metamodel using the multiplicative decomposition method, it can be used to search for a robust optimum design accurately and efficiently. Several mathematical and engineering examples are used to demonstrate the feasibility of the proposed method.

RBDO of Coil Spring Considering Transversal Direction Mode Tracking (횡방향 모드추적을 고려한 코일스프링의 신뢰성기반 최적설계)

  • Lee, Jin Min;Jang, Junyong;Lee, Tae Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.6
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    • pp.821-826
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    • 2013
  • When the values of design variables change, mode switching can often occur. If the mode of interest is not tracked, the frequencies and modes for design optimization may be miscalculated owing to modes that differ from the intended ones. Thus, mode tracking must be employed to identify the frequencies and modes of interest whenever the values of design variables change during optimization. Furthermore, reliability-based design optimization (RBDO) must be performed for design problems with design variables containing uncertainty. In this research, we perform RBDO considering the mode tracking of a compressive coil spring, i.e., a component of the joint spring that supports a compressor, with design variables containing uncertainty by using only kriging metamodels based on multiple responses approach (MRA) without existing mode tracking methods. The reliability analyses for RBDO are employed using kriging metamodel-based Monte Carlo simulation.

Development of Windows Mobile Applications using Model Transformation Techniques (모델 변환 기법을 활용한 윈도우즈 모바일 어플리케이션 개발)

  • Kim, Woo-Yeol;Son, Hyun-Seung;Kim, Jae-Seung;Kim, R. Young-Chul
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.11
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    • pp.1091-1095
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    • 2010
  • The existing smart-phone software is dependent on the platform, which should be developed per each different platform, Each vendor will develop its own platform such as Apple's Cocoa platform, Google Android, Microsoft Windows Mobile, etc. In this paper, we apply model transformation technique for developing heterogenous software at a time in heterogenous smart phone area. This approach separates the independent model and dependent model. and automatically transforms the difference between them with model transformation language. To execute model transformation, it is required with meta model, model transformation language. In this paper, we are applied to smart-phones as follows: model will be UMLmodel, metamodel be UML metamodel, and choose ATL as Model transformation language. We show examples of the Windows Mobile platform environment to be developed using model transformation. As a result, if we use platform-independent model in this paper and redefine model transformation rules for the iPhone or Android, it will be automatically transformed into heterogenous platforms.

Meta-Validation for Consistency between UML Structural Diagram and Behavioral Diagram (UML 구조 다이어그램과 행위 다이어그램의 일관성 메타검증)

  • 하일규;강병욱
    • Journal of KIISE:Software and Applications
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    • v.30 no.12
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    • pp.1158-1171
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    • 2003
  • The UML is a widely accepted standard in object-oriented modeling. As the UML is semantically rich, we can describe in detail the system that will be developed, but we cannot guarantee the correctness and consistency of the designed model. Therefore, it is important to minimize the error by verifying user models in an early stage. In this paper, we propose a method for verifying the consistency of UML structural diagrams and behavioral diagrams using OCL verification rules and meta-metamodel. The consistency is a nature for checking whether the structural diagrams and behavioral diagrams are coherently designed according to a specific requirement. First we build meta-metamodels of the structural diagram and behavioral diagram that are described with the UML diagrams and the related elements, we derive rules for verifying the consistency from each meta-metamodels, and then formally specify with the language such as OCL for automatic verification. Finally, we verify the usefulness of the rule through a case study.

Adaptively selected autocorrelation structure-based Kriging metamodel for slope reliability analysis

  • Li, Jing-Ze;Zhang, Shao-He;Liu, Lei-Lei;Wu, Jing-Jing;Cheng, Yung-Ming
    • Geomechanics and Engineering
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    • v.30 no.2
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    • pp.187-199
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    • 2022
  • Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

Optimal Rotor Structure Design of Interior Permanent Magnet Synchronous Machine based on Efficient Genetic Algorithm Using Kriging Model

  • Woo, Dong-Kyun;Kim, Il-Woo;Jung, Hyun-Kyo
    • Journal of Electrical Engineering and Technology
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    • v.7 no.4
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    • pp.530-537
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    • 2012
  • In the recent past, genetic algorithm (GA) and evolutionary optimization scheme have become increasingly popular for the design of electromagnetic (EM) devices. However, the conventional GA suffers from computational drawback and parameter dependency when applied to a computationally expensive problem, such as practical EM optimization design. To overcome these issues, a hybrid optimization scheme using GA in conjunction with Kriging is proposed. The algorithm is validated by using two mathematical problems and by optimizing rotor structure of interior permanent magnet synchronous machine.

Computational design of an automotive twist beam

  • Aalae, Benki;Abderrahmane, Habbal;Gael, Mathis
    • Journal of Computational Design and Engineering
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    • v.3 no.3
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    • pp.215-225
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    • 2016
  • In recent years, the automotive industry has known a remarkable development in order to satisfy the customer requirements. In this paper, we will study one of the components of the automotive which is the twist beam. The study is focused on the multicriteria design of the automotive twist beam undergoing linear elastic deformation (Hooke's law). Indeed, for the design of this automotive part, there are some criteria to be considered as the rigidity (stiffness) and the resistance to fatigue. Those two criteria are known to be conflicting, therefore, our aim is to identify the Pareto front of this problem. To do this, we used a Normal Boundary Intersection (NBI) algorithm coupling with a radial basis function (RBF) metamodel in order to reduce the high calculation time needed for solving the multicriteria design problem. Otherwise, we used the free form deformation (FFD) technique for the generation of the 3D shapes of the automotive part studied during the optimization process.

A Study on 2-D Airfoil Design Optimization by Kriging (Kriging 방법을 이용한 2차원 날개 형상 최적설계에 대한 연구)

  • Ka Jae Do;Kwon Jang Hyuk
    • Journal of computational fluids engineering
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    • v.9 no.1
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    • pp.34-40
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    • 2004
  • Recently with growth in the capability of super computers and Parallel computers, shape design optimization is becoming easible for real problems. Also, Computational Fluid Dynamics(CFD) techniques have been improved for higher reliability and higher accuracy. In the shape design optimization, analysis solvers and optimization schemes are essential. In this work, the Roe's 2nd-order Upwind TVD scheme and DADI time march with multigrid were used for the flow solution with the Euler equation and FDM(Finite Differenciation Method), GA(Genetic Algorithm) and Kriging were used for the design optimization. Kriging were applied to 2-D airfoil design optimization and compared with FDM and GA's results. When Kriging is applied to the nonlinear problems, satisfactory results were obtained. From the result design optimization by Kriging method appeared as good as other methods.