• Title/Summary/Keyword: model based design

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Comparison of Regression Model Approaches fined to Complex Survey Data (복합표본조사 데이터 분석을 위한 회귀모형 접근법의 비교: 소규모사업체조사 데이터 분석을 중심으로)

  • 이기재
    • Survey Research
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    • v.2 no.1
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    • pp.73-86
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    • 2001
  • In this paper. we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations (GEEs) approach with the model-based approach through the design and weighting effects analysis.

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Extraction of Fuzzy Rules with Importance for Classifier Design

  • Pal, Kuhu
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.725-730
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    • 1998
  • Recently we extended the fuzzy model for rule based systems incorporating an importance factor for each rule. The model permits for both unrestricted as well as non-negative importance factors. We use this extended model to design a fuzzy rule based classifier system which uses both the firing strength of the rule and the importance factor to decide the class label. The effectiveness of the scheme is established using several data sets.

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Detection of Functional Failure and Verification of Safety Requirements Using Meta-Models in the Model-Based Design of Safety-Critical Systems (안전중시 시스템의 모델기반 설계에서 메타모델을 활용한 기능 고장의 탐지 및 안전 요구사항 검증)

  • Kim, Young-Hyun;Lee, Jae-Chon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.9
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    • pp.308-313
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    • 2016
  • Modern systems have become more and more complex due to the ever-increasing user requirements and rapid advance of technology. As such, the frequency of accidents due to system design errors or failure has been increasing. When the damage incurred by accidents to human beings or property is serious, the underlying systems are referred to as safety-critical systems. The development of such systems requires special efforts to ensure the safety of the human beings operating them. To cope with such a requirement, in this paper an approach is employed in which we consider safety starting from the conceptual design phase of the systems. Specifically, a systems design method that can detect functional failure is proposed by utilizing meta-models and M&S methods. To accomplish this, the safety design data from international safety standards are first extracted and also a meta-model is generated using SysML (systems modeling language). Then, a SysML-based system design method is proposed based on the use of the developed meta-model. We also discuss how the safety requirements can be created and verified using a simulation method. Finally, through a case study in automotive design, it is demonstrated that the detection of a functional failure and the verification of a safety requirement can be accomplished using the SysML-based M&S method. This study indicates that the use of meta-models can be useful for collecting and managing safety data and that the meta-model based M&S method can make it possible to satisfy the system requirements by reducing the design errors.

A Conceptual Modeling Tools for the Model Base Design (모델베이스 설계를 위한 개념적 모델링 도구에 관한 연구)

  • 정대율
    • The Journal of Information Systems
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    • v.7 no.1
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    • pp.181-208
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    • 1998
  • In many literatures of model management, various schemes for representing model base schema have proposed. Ultimately, the goal is to arrive at a set of mutually supportive and synergistic methodologies and tools for the modeling problem domain and model base design. This paper focus on how best to structure and represent conceptual model of problem domain and schema of model base. Semantic concepts and modeling constructs are valuable conceptual tools for understanding the structural relationships and constraints involved in an model management environment. To this end, we reviewed the model management literature, and analyzed the constructs of modeling tools of data model management graph-based approach. Although they have good tools but most of them are not enough for the representation of structural relationships and constraints. So we wanted more powerful tools which can represent diverse constructs in a decision support modeling and model base schema design. For the design of a model base, we developed object modeling framework which uses Object Modeling Techniques (OMT). In Object Modeling Framework, model base schema are classified into conceptual schema, logical schema, and physical schema. The conceptual schema represents the user's view of problem domain, and the logical schema represents a model formatted by a particular modeling language. The schema design, this paper proposes an extension of Object Model to overcome some of the limitations exhibited by the OMT. The proposed tool, Extended Object Model(EOM) have diverse constructs for the representation of decision support problem domain and conceptual model base schema.

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Characterization and uncertainty of uplift load-displacement behaviour of belled piers

  • Lu, Xian-long;Qian, Zeng-zhen;Zheng, Wei-feng;Yang, Wen-zhi
    • Geomechanics and Engineering
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    • v.11 no.2
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    • pp.211-234
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    • 2016
  • A total of 99 full-scale field load tests at 22 sites were compiled for this study to elucidate several issues related to the load-displacement behaviour of belled piers under axial uplift loading, including (1) interpretation criteria to define various elastic, inelastic, and "failure" states for each load test from the load-displacement curve; (2) generalized correlations among these states and determinations to the predicted ultimate uplift resistances; (3) uncertainty in the resistance model factor statistics required for reliability-based ultimate limit state (ULS) design; (4) uncertainty associated with the normalized load-displacement curves and the resulting model factor statistics required for reliability-based serviceability limit state (SLS) design; and (5) variations of the combined ULS and SLS model factor statistics for reliability-based limit state designs. The approaches discussed in this study are practical and grounded realistically on the load tests of belled piers with minimal assumptions. The results on the characterization and uncertainty of uplift load-displacement behaviour of belled piers could be served as to extend the early contributions for reliability-based ULS and SLS designs.

Enhanced Distance Dynamics Model for Community Detection via Ego-Leader

  • Cai, LiJun;Zhang, Jing;Chen, Lei;He, TingQin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2142-2161
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    • 2018
  • Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

An Efficient Heuristic Algorithm of Surrogate-Based Optimization for Global Optimal Design Problems (전역 최적화 문제의 효율적인 해결을 위한 근사최적화 기법)

  • Lee, Se-Jung
    • Korean Journal of Computational Design and Engineering
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    • v.17 no.5
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    • pp.375-386
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    • 2012
  • Most engineering design problems require analyses or simulations to evaluate objective functions. However, a single simulation can take many hours or even days to finish for many real world problems. As a result, design optimization becomes impossible since they require hundreds or thousands of simulation evaluations. The surrogate-based optimization (SBO) strategy became a remedy for such computationally expensive analyses and simulations. A surrogate-based optimization strategy has been developed in this study in order to improve global optimization performance. The strategy is a heuristic algorithm and it exploits not only multiple surrogates, but also multiple optimizers. Multiple optimizations of multiple surrogate models yield multiple candidate design points of optima. During the sequential sampling process, the algorithm ranks candidate design points, selects the points as many as specified, and builds the improved surrogate model. Various mathematical functions with different numbers of design variables are chosen to compare the proposed method with the other most recent algorithm, MSEGO. The proposed method shows superior performance to the other method.

Design of Audit Model in Web-based Information System (웹 기반 정보시스템에서의 감리모형 설계)

  • Ko, Kyung Ei;Choi, Jin Tak;Kim, Dong Soo;Kim, Hee Wan
    • Journal of Digital Convergence
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    • v.10 no.9
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    • pp.123-136
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    • 2012
  • Web applications are widely used by the development of the Internet, but there are no separate audit model for a web-based information systems. Information business has a wide variety of characteristics. So, web-based information system audit model is needed. Therefore, a web-based information system audit model was proposed to enhance the effectiveness of audit and to increase the quality. Audit check lists were applied based on three sets of existing information audit check framework. An audit point of time was defined as analysis, design, and implementation. An audit domain was defined as contents, design, and process. Moreover, audit viewpoint and inspection standards were defined by setting standards of process, product, and performance. Moreover, this paper proposes differences between an existing model of information system development methodology and web-based information system. It also deduced audit checklists according to audit domains for web-based information system audit. The deduced audit checklists were verified for its suitability by conducting surveys, and the modified audit inspection model, in which the deduced audit checklists were applied, was proposed.

An EEG-based Deep Neural Network Classification Model for Recognizing Emotion of Users in Early Phase of Design (초기설계 단계 사용자의 감정 인식을 위한 뇌파기반 딥러닝 분류모델)

  • Chang, Sun-Woo;Dong, Won-Hyeok;Jun, Han-Jong
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.34 no.12
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    • pp.85-94
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    • 2018
  • The purpose of this paper was to propose a model that recognizes potential users' emotional response toward design by classifying Electroencephalography(EEG). Studies in neuroscience and psychology have made an effort to recognize subjects' emotional response by analyzing EEG data. And this approach has been adopted in design since it is critical to monitor users' subjective response in the preface of design. Moreover, the building design process cannot be reversed after construction, recognizing clients' affection toward design alternatives plays important role. An experiment was conducted to record subjects' EEG data while they view their most/least liked images of small-house designs selected by them among the eight given images. After the recording, a subjective questionnaire, PANAS, was distributed to the subjects in order to describe their own affection score in quantitative way. Google TensorFlow was used to build and train the model. Dataset for model training and testing consist of feature columns for recorded EEG data and labels for the questionnaire results. After training and testing, the measured accuracy of the model was 0.975 which was higher than the other machine learning based classification methods. The proposed model may suggest one quantitative way of evaluating design alternatives. In addition, this method may support designer while designing the facilities for people like disabled or children who are not able to express their own feelings toward alternatives.

A Study on the Control Model Identification and H(sub)$\infty$ Controller Design for Trandem Cold Mills

  • Lee, Man-Hyung;Chang, Yu-Shin;Kim, In-Soo
    • Journal of Mechanical Science and Technology
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    • v.15 no.7
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    • pp.847-858
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    • 2001
  • This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

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