• Smart Structures and Systems
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• v.14 no.6
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• pp.1081-1103
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• 2014

Real-time hybrid simulation (RTHS) has emerged as an important tool for testing large and complex structures with a focus on rate-dependent specimen behavior. Due to the real-time constraints, accurate dynamic control of servo-hydraulic actuators is required. These actuators are necessary to realize the desired displacements of the specimen, however they introduce unwanted dynamics into the RTHS loop. Model-based actuator control strategies are based on linearized models of the servo-hydraulic system, where the controller is taken as the model inverse to effectively cancel out the servo-hydraulic dynamics (i.e., model-based feedforward control). An accurate model of a servo-hydraulic system generally contains more poles than zeros, leading to an improper inverse (i.e., more zeros than poles). Rather than introduce additional poles to create a proper inverse controller, the higher order derivatives necessary for implementing the improper inverse can be calculated from available information. The backward-difference method is proposed as an alternative to discretize an improper continuous time model for use as a feedforward controller in RTHS. This method is flexible in that derivatives of any order can be explicitly calculated such that controllers can be developed for models of any order. Using model-based feedforward control with the backward-difference method, accurate actuator control and stable RTHS are demonstrated using a nine-story steel building model implemented with an MR damper.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.394-406
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• 2015

In this work, an efficient aircraft landing simulation strategy is proposed to develop an efficient and reliable hard-landing monitoring procedure. Landing stage is the most dangerous moment during operation cycle of aircraft and it may cause structural damage when hard-landing occurs. Therefore, the occurrence of hard-landing should be reported accurately to guarantee the structural integrity of aircraft. In order to accurately determine whether hard-landing occurs or not from given landing conditions, full nonlinear structural dynamic simulation can be performed, but this approach is highly time-consuming. Thus, a more efficient approach for aircraft landing simulation which uses a hierarchical aircraft landing model and an extended inertia relief technique is proposed. The proposed aircraft landing model is composed of a multi-body dynamics model equipped with landing gear and tire models to extract the impact force and inertia force at touch-down and a linear dynamic structural model with an extended inertia relief method to analyze the structural response subject to the prescribed rigid body motion and the forces extracted from the multi-body dynamics model. The numerical examples show the efficiency and practical advantages of the proposed landing model as an essential component of aircraft hard-landing monitoring procedure.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.5
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• pp.57-67
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• 2003

Security Policy Model is a structured representation using informal, semiformal or formal method of security policy to be enforced by TOE. It provides TOE to get an assurance to mitigate security flaws resulted from inconsistency between security functional requirements and functional specifications. Therefore, Security Policy Model has been required under an hish evaluation assurance level on an evaluation criteria such as ISO/IEC 15408(Common Criteria, CC). In this paper, we present an evaluation method for security policy model based on assurance requirements for security policy model in Common Criteria through an analysis of concepts, related researches and assurance requirements for security policy model.

• Information Systems Review
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• v.11 no.3
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• pp.147-167
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• 2009

Enterprise architecture is a business transformation effort. In an effort to assess an organization's EA effort and to identify complementary measures, most of countries utilize an EA maturity model. In Korea, the EA maturity model v2.1 has been used for this purpose. Since some limitations in the model were reported recently and there was much change in EA-related policy or approach with the advent of the new government, the need of modifying the current model has occurred. In this regard, our paper proposes an improved EA maturity model. The new model was developed through a series of systematic analysis such as an in-depth comparison of existing EA models, elicitation of alternatives for each decision-making element, and interviewing of experts.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.8
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• pp.721-725
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• 2016

This paper reviews the analysis of a given scenario according to the Hybrid Model, and why accident causation models are necessary in casualty investigations. The given scenario has been analyzed according to the Hybrid Model using its main five components, fallible decisions, line management, psychological precursors to unsafe acts, unsafe acts, and inadequate defenses. In addition, the differences between the SHEL and the Hybrid Model, and the importance of a safety barrier during an accident investigation, are shown in this paper. One unit of SHEL can be linked with another unit of SHEL. However, it cannot be used for the analysis of an accident. Therefore, we must use an accident causation model, which can be a Hybrid Model. This can explain the "How" and "Why" of accident, so it is a suitable model for analyzing them. During an accident investigation, the reason we focus on a safety barrier is to create another safety barrier or to change an existing safety barrier if that barrier fails. Hence, the paper shows how a sea accident can be investigated, and we propose a preventive way of avoiding the accident through combining the methods of different models for the future.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.277-280
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• 2004

As electric shock accident take place frequently, electrical safety is extremely important to prevent them. This paper describes the characteristics of electric shock. In order to examine it, an experimental apparatus including a model of a human body is fabricated and the magnitude of the voltage held by the model is measured under several conditions as follows;(1) the model is not contacted to an electric pole and a step voltage does not exist. (2) the model is not contacted to an electric pole and a step voltage exists. (3) the model is contacted to an electric pole and a step voltage does not exist (4) the model is contacted to an electric pole and a step voltage exists. As a result of the experiment it is found that the voltage held by the model depends on the step voltage as well as the voltages applied to the electric pole.

• Structural Engineering and Mechanics
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• v.61 no.5
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• pp.605-615
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• 2017

Shear failure of reinforced concrete (RC) beams is a major concern for structural engineers. It has been shown through various studies that the shear strength and ductility of RC beams can be improved by adding steel fibers to the concrete. An accurate model predicting the shear strength of steel fiber reinforced concrete (SFRC) beams will help SFRC to become widely used. An artificial neural network (ANN) model consisting of an input layer, a hidden layer of six neurons and an output layer was developed to predict the shear strength of SFRC slender beams without stirrups, where the input parameters are concrete compressive strength, tensile reinforcement ratio, shear span-to-depth ratio, effective depth, volume fraction of fibers, aspect ratio of fibers and fiber bond factor, and the output is an estimate of shear strength. It is shown that the model is superior to fourteen equations proposed by various researchers in predicting the shear strength of SFRC beams considered in this study and it is verified through a parametric study that the model has a good generalization capability.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.347-358
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• 2012

Purpose: Given the mixture components - process variables experimental data, we propose the strategy to find the proper combined model. Methods: Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components - process variables experiments depend on the mixture components - process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. Results: First we choose the reasonable starting models among the class of admissible product models and practical combined models suggested by Lim(2011) based on the model selection criteria and then, search for candidate models which are subset models of the starting model by the sequential variables selection method or all possible regressions procedure. Conclusion: Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. The strategy to find the proper combined model is illustrated with examples in this paper.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.45-53
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• 2003

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the reponse variables have excess zeros, it is not easy to apply the Poisson regression model. In this paper, we study and simulate the zero-inflated Poisson regression model. An real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of zero-inflated Poisson model with the Poisson regression and decision tree model.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.401-409
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• 2006

We consider a generalized partly-parametric additive risk model which generalizes the partly parametric additive risk model suggested by McKeague and Sasieni (1994). As an estimation method of this model, we propose to use the weighted least square estimation, suggested by Huffer and McKeague (1991), for Aalen's additive risk model by a piecewise constant risk. We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least squares method.