• Korean System Dynamics Review
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• v.9 no.1
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1521-1528
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• 2010

This paper examines technical writing and teaching methods based on the perspectives of the complex learning system theory. So, the paper first discusses the constituent elements and characteristics of the complex learning system theory and continues to examine the potential of applying the complex learning system theory to new teaching methods. As a result, not only did the research expand the approach methods of providing technical writing education but also confirmed the potential of actual implementation. Such results will provide a leeway to start applying new teaching methods for technical writing education. Furthermore, the paper proposes more detailed case studies related to this topic as well as development of this research to produce textbooks and other higher level researches.

• Korean Educational Research Journal
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• v.41 no.1
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• pp.59-79
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• 2020

Men learning has no fixed route. In other words, any route can be taken, which can also be seen in the structure of other "complex systems" discussed in modern society. It can also be examined through Yang's long-standing classic, The Book of Changes Men learning itself started from informal learning to become today's formal learning. As we look at the stages of human civilization's progress, we can quickly discover these stages of development. The issue of human beings has always been a topic of discussion, and these discussions are ongoing. Men learn through language and tools, technology and culture, and through philosophy, art, and religion to deal with their complex and diverse mental world. Through these various activities, learning is accomplished. This is not limited to the physical processes of one generation learning through inheriting knowledge; men's learning, a kind of mental process, has extended our life. This is why there is no other reason that men's minds and learning are always developing. This study is about how to learn in a complex and diversified modern society and to find out how to coexist with the principles of the "complex system" and The Book of Changes.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.75-77
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• 1998

Perhaps one of the most versatile approaches to learning in practical domains lies in case based reasoning. To date, however, most case based reasoning systems have tended to focus on relatively simple domains. The current study involves the development of a decision support system for a complex production process with a limited database. This paper presents a set of critical issues underlying CBR, then explores their consequences for a complex domain. Finally, the performance of the system is examined for resolving various types of quality control problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.97-97
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• 2021

Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.128-137
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• 2018

In the programming education, there is a great need of a teaching support system that can support the learner in the programming process regardless of the computer language due to instructor's difficulty of checking the progress of learners in real-time. Its importance is especially important in lower grade coding classes such as in K-12 education because they are not used to coding and so simple problems can be regarded as complex problems. For this, a pilot coding education support system based on Levenshtein distance algorithm which shows learners' progress to given solution in real-time was developed in order to help learners to solve complex problems easily, and the learners' motivation and self-efficacy was measured for estimating the usefulness of developed system targeting elementary school students. When the learners use the developed system, it was found that a statistically significant difference appears in the sub-factors of learning motivation compared with traditional class teaching environments. Among the sub-factors of self-efficacy, the efficacy dimension showed statistically significant difference too.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.771-779
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• 2010

Sketch-based interface is used more and more in developing animation contents. Particularly, there has been a system where the user's sketch inputs are interpreted and presented as live motions. In this study¸ it is to design an animated flight learning system using sketch-based interface. Most of the flights include movements in three-dimensional space and have unique and complex flight patterns. In other words, the actual flight movements not only include acceleration and deceleration, rising and falling, straight or circular flying, but also may include combinations of two or more movements as they simultaneously occur such as accelerating while falling, or slowing down while rising, and so forth. And, currently existing flight learning animation system cannot present such complex flight patterns to the pilots of aircrafts or to those personnel for air-traffic controllers. Hence, it is to be shown in this study that unit-path sketch animation method can support quicker ways to create animations to present those complex flight movements, and requires lesser inputs compared to the existing frame-based animation method. Also, the flight learning system suggested uses the flight-route realization tasks to reflect complex flight patterns, and therefore creates animations close to real as possible.

• Smart Media Journal
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• v.12 no.11
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• pp.36-47
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• 2023

Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1464-1468
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• 2004

This paper presents a learning controller for repetitive gait control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured according to the walking period through the iterative learning, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of learning control to biped robotic motion is shown via dynamic simulation with 12-DOF biped walking robot.