• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.949-954
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• 2009

The autoregressive process is applied in this paper to kernel regression in order to infer nonlinear models for predicting responses. We propose a kernel method for the autoregressive data which estimates the mean function by kernel machines. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which affect the performance of kernel regression. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of mean function in the presence of autocorrelation between data.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.81-90
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• 2018

The 'Hyper-connected society' in which all objects such as people, device, place are connected via networks and share information being realized. As the information and communication environment changes, spatial information also faces a significant challenge. Korean government is striving to meet the social demand for spatial information that will bring 'Hyper-connectivity' such as autonomous vehicles, drones. Until now, however, it has only partially responded to urgent demand and has not prepared a fundamental countermeasure. In order to effectively and actively respond to the demand for spatial information that is needed in the Hyper-connected society, a strategy that can lead to mid- to long-term fundamental changes is needed. The purpose of this study is to analyze the future demand and application characteristics of spatial information confronted with a big paradigm shift called 'Hyper-connected society', and to search spatial information strategy that can cope with the demand of spatial information in future society.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.442-445
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• 1997

We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.204-211
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• 2020

The era of the 4th industrial revolution is a complex environment in which the cyber world and the physical world are integrated and interacted. In order to successfully implement and be sustainable the 4th industrial revolution of hyper-connectivity, hyper-convergence, and hyper-intelligence, not only the technological aspects that implemented digitalization but also the social aspects must be recognized and dealt with as important. There are socio-technical systems and socio-technical systems theory as concepts that describe systems involving complex interactions between the environmental aspects of human, mechanical and tissue systems. This study confirmed how the Socio-technical System was applied in the research literature for the last 10 years through machine learning-based analysis. Eight clusters were derived by performing co-occurrence keywords network analysis, and 13 research topics were derived and analyzed by performing a structural topic model. This study provides consensus and insight on the social and technological perspectives necessary for the sustainability of the 4th industrial revolution.

• Korean Institute of Interior Design Journal
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• no.34
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• pp.3-9
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• 2002

Entering into the 21st century, digital culture and the innovation of media technology have drastically changed our understanding of the concept of space. Increased availability of information made possible by technological advancement has, directly or indirectly, contributed to the development of space design, which, in turn, offers a possibility for a new paradigm in space design. Given these fundamental changes, this study seeks to explore how to understand the expansion of the concept of space. In order to answer this question, this study investigates de-materialization tendency in modern architectural design such as transparency, anti-gravity, complexity and simultaneity of space. It examines the interaction-oriented nature of space among human, information and time. Finally, based on concepts such as new hyper-surface, which transcend the limitations of space and time, it explores new emerging trends in space design.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.124-127
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• 2007

In this study, we focused on investigation of governing parameters affected on the fatigue properties in the hyper-eutectoid steel wires used for TBR tires. Steel wires are fabricated under different drawing strain from 3.36 to 3.80. Their diameters are 0.21 mm and 0.185mm, respectively. The fatigue properties was measured by hunter rotating beam tester, specially designed thin-sized steel wires. The results showed that the fatigue properites of steel wire, marked as A-1, were greater than the others, due to the low value of residual stress. In order to elucidate the variations of fatigue properties, the microstructure, surface defect and residual stress were observed and measured by useful analysis technique, such as TEM, 3D profiler and FIB.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.59-65
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• 2003

In order to achieve the desired lightweight and robust design of a structure, it is preferable to design a structure and its control system, simultaneously, which is termed the combined optimal design. A constant-cross-sectional area cantilever beam was chosen as the optimum design method, An initial load and a time-varying disturbance were applied at the free end of the beam. Sliding mode control was selected, due to its insensitivity to the disturbance, compared with other modes. It is known that the sliding mode control is robust to the disturbance and is uncertain, only if a matching condition is met, after giving a switching hyper plane. In this study, the optimum method was used for the design of the switching hyper plane, and the objective function of the optimum switching hyper plane was assumed to be the objective of the control system. The total weight of the structure was treated as a constraint, and the cross sectional areas of the beam were considered as design variables, the result being a nonlinear programming problem. To solve it, the sequential linear programming method was applied. As a result of the optimum design, the effect of attenuating vibrations has been substantially improved. Moreover, the lightweight design of the structure became possible as a result of the relationship of the weight of the structure to the control objective function.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.1
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• pp.17-27
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• 2014

In order to study the propagation of singularities for solutions to second order quasilinear strictly hyperbolic equations with boundary, we have to consider the regularity of solutions of first order nonlinear equations satisfied by a characteristic hyper-surface. In this paper, we study the regularity compositions of the form v(${\varphi}$(x), x) with v and ${\varphi}$ assumed to have limited Sobolev regularities and we use it to prove the regularity of solutions of the first order nonlinear equations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.391-398
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• 2023

In this paper, a penalized maximum likelihood estimation (PMLE) method that applies a penalty to increase the accuracy of a basis-screening-based Kriging model (BSKM) is introduced. The maximum order and set of basis functions used in the BSKM are determined according to their importance. In this regard, the cross-validation error (CVE) for the basis functions is employed as an indicator of importance. When constructing the Kriging model (KM), the maximum order of basis functions is determined, the importance of each basis function is evaluated according to the corresponding maximum order, and finally the optimal set of basis functions is determined. This optimal set is created by adding basis functions one by one in order of importance until the CVE of the KM is minimized. In this process, the KM must be generated repeatedly. Simultaneously, hyper-parameters representing correlations between datasets must be calculated through the maximum likelihood evaluation method. Given that the optimal set of basis functions depends on such hyper-parameters, it has a significant impact on the accuracy of the KM. The PMLE method is applied to accurately calculate hyper-parameters. It was confirmed that the accuracy of a BSKM can be improved by applying it to Branin-Hoo problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.