• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.2
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

• Steel and Composite Structures
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• v.46 no.1
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• pp.107-114
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• 2023

A new intelligent adaptive control scheme was proposed that combines observer disturbance-based adaptive control and fuzzy adaptive control for a composite structure with a mass-adjustable damper. The most important advantage is that the control structures do not need to know the uncertainty limits and the interference effect is eliminated. Three adjustable parameters in LMI are used to control the gain of the 2D fuzzy control. Binary performance indices with weighted matrices are constructed to separately evaluate validation and training performance using the revalidation learning function. Determining the appropriate weight matrix balances control and learning efficiency and prevents large gains in control. It is proved that the stability of the control system can be ensured by a linear matrix theory of equality based on Lyapunov's theory. Simulation results show that the multilevel simulation approach combines accuracy with high computational efficiency. The M-TMD system, by slightly reducing critical joint load amplitudes, can significantly improve the overall response of an uncontrolled structure.

• Journal of Korea Society of Industrial Information Systems
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• v.7 no.1
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• pp.10-15
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• 2002

It is presented to extended to an interaction matrix formulation to the problem of system and disturbance identification for a plant that is corrupted by both process and output disturbances. With only an assumed upper bound on the order of the system and an assumed upper bound on the number of disturbance frequencies, it is shown that both the disturbance-free model and disturbance effect can be recovered exactly from disturbance-corrupted input-output data without direct measurement of the periodic disturbances. The rich information returned by the identification can be used by an iterative learning or repetitive control system to eliminate unwanted periodic disturbances. Those can be helped to apply to the multiple dynamic systems for precision quality assurance.

• Journal of Elementary Mathematics Education in Korea
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• v.19 no.3
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• pp.323-345
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• 2015

This study is intended to establish and apply a program created with RME for mathematising instruction and learning and identify how it influences on the mathematical thinking process in the field. In order to deal with this study inquiries, related theories have been analyzed establishing a program for mathematising instruction and learning method based on a model of them and RME theory principles and re-organizing education courses for instruction on the fields concerned. Study subjects were limited to two classes consisting of fifth graders in S elementary school located in the city of Daegu and divided them in an experiment group and a control group. An experiment group was given a mathematising learning method applied with RME, while a control group had a class with regular methods of learning and instruction during the period of experiment. As a summary of aforementioned results of the study, mathematising learning method applied with RME had an effect on improving mathematical thinking ability for students and also on promoting mathematising outcome through a repetitive experience in each procedure obtained on a regular basis.

• The Korean Journal of Emergency Medical Services
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• v.15 no.2
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• pp.43-54
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• 2011

Purpose: The purpose of this study was to explore EMT-paramedic students' experience of simulation education and analyze the confidence before and after education, learning attitude and course evaluation. Method: Research survey was conducted on 38 EMT-paramedic students during November, 2011 and EMT-paramedic students' experience of simulation education was analyzed after applying head, spinal, and chest injury scenario. The confidence before and after education, learning attitude and course evaluation in gender were analyzed by Mann-Whitny U test and the difference of confidence before and after education was analyzed by Wilcoxon signed rank test and learning attitude & course evaluation were analyzed by evaluating frequency, percentage, mean, standard deviation by using SPSS WIN 17.0 program. Results: 1. Students experienced various advantages such as increasing interest and self-reflection on learning, critical thinking ability, and EMT-paramedic-role experience and recognition of importance of teamwork. Students also pointed out disadvantages such as gap between real situation and simulation, limit of time and equipments, and burden of demonstration. 2. The confidence between before and after education, learning attitude and course evaluation in gender were not significant different statistically. 3. Confidence mean score elevated from 5.53(before education) to 5.87(after education), but the difference in their confidence did not show significant difference statistically. 4. Total mean score in learning attitude after simulation education was 3.70 out of 5.00, which is considerably very high. 5. Total mean score in course evaluation was 3.89 with score of 3.83 in evaluation in learning environment and 3.99 in evaluation of debriefing. Conclusion: The finding of this study demonstrate that the simulation education can provide a safe and repetitive practice environment, improve problem-solving ability and critical thinking, and increase the confidence in prehospital emergency care; therefore, simulation may be the new effective EMT-paramedic education strategy.

• The Journal of Korean Physical Therapy
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• v.21 no.1
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• pp.81-87
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• 2009

Purpose: Human brain was lateralized to dominant or non-dominant hemisphere, and could be reorganized by the processing of the motor learning. We reported four cases which showed the changes of the cortical activation patterns resulting from two weeks of training with the serial reaction time task. Methods: Four right-handed healthy subjects were recruited, who was equally divided to two training conditions (right hand training or left hand training). They were assigned to train the serial reaction time task for two weeks, which should press the corresponding four colored buttons as fast as accurately as possible when visual stimulus was presented. Before and after two weeks of training, reaction time and function magnetic resonance image (fMRI) was acquired during the performance of the same serial reaction time task as the training. Results: The reaction time was significantly decreased in all of subjects after training. Our fMRI result showed that widespread bilateral activation at the pre scanning was shifted toward the focused activation on the contralateral hemisphere with progressive motor learning. However, the bilateral activation was still remained during the performance of the non-dominant hand. Conclusion: These findings showed that the repetitive practice of the serial reaction time task led to increase the movement speed and accuracy, as described by motor learning. Such motor learning induced to change the cortical activation pattern. And, the changed pattern of the cortical activation resulting from motor learning was different each other in accordance with the hand dominance.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Korea Journal of Hospital Management
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• v.9 no.2
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• pp.1-22
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• 2004

This study was designed to suggest a learning organization in a medical center by examining the factors to influence effectiveness of the learning organization. We collected the data of 586 persons who participated once or more times in the learning organization managed from 2000 to 2002 by Y Medical Center located in Seoul, and included the data of 285 persons in the final analysis. The results of the study are summarized as follows. First, as the results of examining the regression coefficients to predict the effectiveness of and satisfaction with the learning organization through the learning level, learning method and learning organization constructing level as the general variables, the important influential factors were shown as follows: 1)knowledge creation, knowledge storing, private learning, organizational learning, and learning organization construction of occupational and human levels as the factors to predict the working competency; 2) learning organization construction of the human level as the factors to assume the duty satisfaction; 3) gender, working years, private learning, team learning and organizational construction level for the prediction of the organizational commitment; and 4) medical technical service, knowledge creation, organization learning, and constructing level of the environmental and human levels for the assumption of the satisfaction with experience in the learning organization. Based on the study results of the effects in managing the learning organization, we can conclude the followings. First, the members who are in various working positions and occupations need to continuously participate in the learning organization. Second, to raise the organizational outcome from the management of the learning organization, it is necessary to establish systematic concepts in the constituents of the organizational effectiveness such as working competency improvement, duty satisfaction and organizational commitment, and the experience satisfaction of the learning organization. Finally, the future of the organization depends on the learning competencies of the organization members. To continuously exist and develop the organization, the private learning of the organizational members should be constantly spread and shared over the organizational level, and the usual innovations such as repetitive and habitual organizational learning should be generally tried out throughout the whole field of the management.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.633-635
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• 2016

Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The basic pipeline for transfer learning is to first train a ConvNet on a large dataset (source task) and then use feed-forward units activation of the trained ConvNet as image representation for smaller datasets (target task). Our key contribution is to demonstrate superior performance of multiple ConvNet layer features over single ConvNet layer features. Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form of feature selection. We use AdaBoost with single stumps to implicitly select only distinct features that are useful towards classification from concatenated ConvNet features. Experimental results show that using multiple ConvNet layer activation features instead of single ConvNet layer features consistently will produce superior performance. Improvements becomes significant as we increase the distance between source task and the target task.