• Korean System Dynamics Review
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• v.15 no.4
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• pp.129-159
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• 2014

This Study discuss exploring normative-prescriptive factors after the themes on Organizational learning categorize two descriptive/explanatory-perspectives, prescriptive/normative dimension. The former would contain information processing model, theory of action, organizing in organization, while Senge's suggestion on Learning Organization may compose the latter. Each perspective is reconstructed and reinterpreted into the causal mapping relationship founded on system thinking and SD. Underlying on the former try to discovery validities of the latter. But this study only put forward the integral-dynamic model of organizational learning without empirical simulation.

• Journal of the Ergonomics Society of Korea
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• v.32 no.1
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.447-453
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• 2003

Emotion Technology is used in many field such as computer A.I., graphics, robot, and interaction with agent. We focus on the theory, the technology and the features in emotion application. Firstly in the field of theory, there are psychological approach, behavior-based approach, action-selection approach. Secondly in the field of implementation technologies use the learning algorithm, self-organizing map of neural network and fuzzy cognition maps. Thirdly in the field of application, there are software agent, agent robot and entrainment robot. In this paper, we research the case of application and analyze emotion architecture.

• Journal of IKEEE
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• v.24 no.4
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• pp.1039-1049
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• 2020

Neural decoding is important to recognize the user's intention for controlling a neuro-prosthetic hand. This paper proposes a real-time decoding method for multi-channel peripheral neural activity. Peripheral nerve signals were measured from the median and radial nerves, and motion artifacts were removed based on locally fitted polynomials. Action potentials were then classified using a k-means algorithm. The firing rate of action potentials was extracted as a feature vector and its dimensionality was reduced by a self-organizing feature map. Finally, a multi-layer perceptron was used to classify hand motions. In monkey experiments, all processes were completed within a real-time constrain, and the hand motions were recognized with a high success rate.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.4
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• pp.45-55
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• 1997

According to the increase of factory-automation in the field of production, the importance of autonomous guided vehicle's(AGV) role is also increased. The study about an active and effective controller which can flexibly prepare for the changeable circumstance is in progressed. For this study, the research about action base system to evolve by itself is also being actively considered. In this paper, we composed an active and effective AGV fuzzy controller to be able to do self-organization. For composing it, we tuned suboptimally membership function using genetic algorithm(GA) and improved the control efficiency by the self-correction and generating the control rules. Self-organizing controlled(S0C) fuzzy controller proposed in the paper is capable of self-organizing by using the characteristics of fuzzy controller and genetic algorithm. It intuitionally controls AGV and easily adapts to the circumstance.

• Journal of the Korean Society of Food Culture
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• v.34 no.3
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• pp.325-333
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• 2019

This study was a qualitative investigation of the process of adaptation of nutrition education programs by marriage immigrant women who completed education programs for training of food citizen leaders. Focus group interviews of seven marriage immigrant women from Vietnam, China, Mongolia and Russia were conducted and analyzed based on the Normalization Process Theory (NPT). Participants were aware of the purpose of the education program (coherence) and their confidence in organizing and reconstructing the knowledge of nutrition was increased after education (reflexive monitoring). However, they had difficulties attending long-term education programs (cognitive participation) and overcoming language barriers (collective action). Although the program was beneficial for the participants in that they could apply acquired nutrition knowledge to their everyday life as food citizen leaders, the continuous monitoring and feed-back system (management), customized application, and consideration of personal and social factors need to be developed and facilitated. In addition, various programs targeting marriage immigrant women may increase economic independence of these women. The NPT proved beneficial in conceptualizing the barriers and facilitators to implementing nutrition education. The successful implementation of nutrition intervention needs special support to overcome barriers to cognitive participation and collective action.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1054-1061
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• 2003

Q-Learning, a representative algorithm of reinforcement learning, experiences repeatedly until estimation values about all state-action pairs of state space converge and achieve optimal policies. When the state space is high dimensional or continuous, complex reinforcement learning tasks involve very large state space and suffer from storing all individual state values in a single table. We introduce Q-Map that is new function approximation method to get classified policies. As an agent learns on-line, Q-Map groups states of similar situations and adapts to new experiences repeatedly. State-action pairs necessary for fine control are treated in the form of rule. As a result of experiment in maze environment and mountain car problem, we can achieve classified knowledge and extract easily rules from Q-Map

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1287-1290
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• 2003

Generally, it is known that human beings have both emotion and rationality. Especially, emotion is so subjective that human beings might act in different way for the same environment according to their own emotion. Emotion also plays very important role in communication with someone else For an agent, even though it is designed to act delicately, when it is designed without internal emotion, it can not interact dynamically just like human beings. In this paper, we suggest an agent which action is effected by not only rationality but also emotion to make it interact with human beings dynamically. It is composed of supervised learning, SOM (Self-Organizing Map) and fuzzy decision.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.276-279
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• 2003

Generally, it is known that human beings have both emotion and rationality. Especially, emotion is so subjective that human beings might act in different way for the same environment according to their own emotion. Emotion also plays very important role in communication with someone else. For an agent, even though it is designed to act delicately, when it is designed without internal emotion, it can not interact dynamically just like human beings. In this paper, we suggest an agent which action is effected by not only rationality but also emotion to make it interact with human beings dynamically. It is composed of supervised learning, SOM (Self-Organizing Map) and fuzzy decision.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2004.05a
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• pp.176-179
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• 2004

Space is comprised by the movements of human beings, and draws a complex locus within it. That form seems to be complex of movement around in all directions of space axis, and be ever-changing process as time goes by. Although Human are able to move uninhibitedly, the movements are restricted to a narrow sphere during locomotion. However, the pattern of these movements delineates a certain frame within the space, and provides not only visual effects but also relevance tomovement itself. Also, critically dividing and organizing this sphere is what is realized into this tangible indoor space. This study recognized importance of human being as a core of making indoor space and brought out experimental approach on relationship human with space, and visually perceptual standpoint. And this presented the recent possibility of action and attitude though sight and walking by arranging space on the basis of modern artists' perception of human body.