• School Mathematics
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• v.15 no.4
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• pp.723-742
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• 2013

The purpose of this study was to analyze children's proportional reasoning process on an ill-structured "architectural drawing" problem solving and to investigate their level and characteristics of proportional reasoning. As results, they showed various perspective and several level of proportional reasoning such as illogical, additive, multiplicative, and functional approach. Furthermore, they showed their expanded proportional reasoning from the early stage of perception of various types of quantities and their proportional relation in the problem to application stage of their expanded and generalized relation. Students should be encouraged to develop proportional reasoning by experiencing various quantity in ration and proportion situations.

• Journal of Industrial Technology
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• v.29 no.B
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• pp.17-23
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• 2009

In many cases, clustering algorithms have been used for extracting and discovering useful information from non-linear data. They have made a great effect on performances of the systems dealing with non-linear data. Thus, this paper presents a new approach called hierarchically structured clustering algorithm, and it is applied to the prediction system for non-linear time series data. The proposed hierarchically structured clustering algorithm (called HCKA: Hierarchical Cross-correlation and K-means clustering Algorithms) in which the cross-correlation and k-means clustering algorithm are combined can accept the correlationship of non-linear time series as well as statistical characteristics. First, the optimal differences of data are generated, which can suitably reveal the characteristics of non-linear time series. Second, the generated differences are classified into the upper clusters for their predictors by the cross-correlation clustering algorithm, and then each classified differences are classified again into the lower fuzzy sets by the k-means clustering algorithm. As a result, the proposed method can give an efficient classification and improve the performance. Finally, we demonstrates the effectiveness of the proposed HCKA via typical time series examples.

• Journal of the Korean housing association
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• v.15 no.3
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• pp.83-91
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• 2004

In a planning stage, the assessment system is required to select the proper alternative, reflected the environmental affects such as energy, $CO_2$ and $SO_x$. Unit of energy consumption, $CO_2$ emission and $SO_x$ emission among various assessment systems could be effectively utilized to select the better alternative among various building types. But researches for these areas has not been conducted systematically, but limitedly and sporadically. In this paper, it aimed at providing the unit of energy consumption, $CO_2$ emission and $SO_x$ emission to evaluate the environmental affects between the steel-structured apartment building and wall-typed apartment building. For this, the input-output analysis could be utilized in the construction stage with two-type apartment housing. This approach can be utilized to compare the various alternatives in aspect of the energy consumption and the environment affect, and to select the relatively better alternative. This study found that the unit of energy, $CO_2$ and $SO_x$ of the steel-structured apartment building is lower than that of the wall-typed building

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.384-389
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• 2003

We propose a hierarchically structured navigation algorithm for multiple mobile robots under unknown dynamic environment based on fussy-neural algorithm. The proposed algorithm consists of two basic layers. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. In addition, The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. The efficacy of the proposed method is demonstrated via some simulations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.2
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• pp.59-67
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• 2016

The checklist currently used for Aviation safety inspection performed by ASIs consists of inspection groups and multiple items, it does not have structured hierarchy system which required to efficiently process aviation safety analysis. On this study, through mapping taxonomy of HFACS onto current checklist to secure structured hierarchy system and present a specification on systematic frequency and severity to perform safety risk assessment of detected hazard.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.431-441
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• 1991

A robust H$_{\infty}$ control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multi-parameter variations in the state-space formulation of H$_{\infty}$ control theory. An application of this robust H$_{\infty}$ control synthesis technique to the Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73% in one of the structured uncertainty directions. The performance and stability of this new robust H$_{\infty}$ controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.que.

• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.42-47
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• 1998

The pressure-based methods are very popular in CFD because it requires less computer core memory compared to other coupled or density-based solvers. Currently structured-mesh methodology based on pressure-based algorithm is quite mature to apply to the practical problems. The unstructured mesh method needs much more computer memory than the structured-mesh method. However the pressure-based method utilizing the sequential approach does not require very large memory used for unstructured-mesh density-based solvers. The present study has developed the unstructured grid pressure-based method. Cell-centered finite volume method was selected due to robustness for imposing various boundary conditions and easy implementation of higher-order upwind scheme. The predictive capability of present method has validated against several benchmark problems.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.78-82
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• 1995

In this paper, we consider the robustness analysis problem in state space models with linear time invariant perturbations. Based upon the discrete-time Lyapunov approach, sufficient conditions are derived for the eigenvalues of perturbed matrix to be located in a circle, and robustness bounds on perturbations are obtained. Spaecially, for the case of a diagonalizable hermitian matrix the bound is given in terms of the nominal matrix without the solution of Lyapunov equation. This robustness analysis takes account not only of stability robustness but also of certain types of performance robustness. For two perturbation classes resulting bounds are shown to be improved over the existing ones. Examples given include comparison of the proposed analysis method with existing one.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.601-602
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• 2006

The primary role of MRP(Material Requirement Planning) is to make a production plan so that we have an exact quantity of right materials on needed time at right place. But the ignorance on capacity constraints makes some problems whenever production schedule is established. To increase the performance of MRP system, a novel approach which is based on new input data structure is suggested. The new input data structure includes all the information about Material BOM, Routing and resource data so that we can easily examine the usage of resources and generate higher performance production plans.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.30-33
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• 2002

There are several methods to implement the logical machine reasoning such as a frame theory and a production system of artificial intelligence. And these algorithms can explain the obtained result through the inference processes. However, emotional (KANSEI) patterns are not so easily implement. One of reason is that some emotional expression is the result of process from unconscious level to conscious level, and not easily identified the original unconscious causes. Therefore, a function of KANSEI database needs to structuralize unconscious level. Our approach is to develop the computerized counseling support system which can structuralize the unconscious brain functions from the view point of the psychology with focusing physiological and emotional responses. Especially, development of the algorithm that can form the network from unconscious to conscious using the image recollection is the application of the structured association technique (SAT). The developed system was implemented on the Web using CGI and emotional network database.