• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Education of Primary School Mathematics
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• v.16 no.3
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• pp.193-209
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• 2013

This study was designed to identify how teachers and students solve problems and communicate with each other during the course of study through application of PBL questions that can be utilized in math ratio and graph sections of the 6th-grade elementary school curriculum in class. Therefore we haved figure it out that through pbl class student acquired a propound knowledge in math and showed self-directed learning through various communication activities, and that they finally showed positive attitude and confidence in this subject.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.19-45
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• 2010

This research has analyzed the differentiated influence of organizational variables(an organization's learning culture and organizational support networks) and personal variables(the individual's motivation to learn and self-efficacy) on the process of gaining and using of knowledge. These two variables have been regarded as the major variables for the successful learning of 6Sigma, according to Social Cognitive Theory. In addition, this research has proven the role structure of the abovementioned two variables through a suitable methodology(Hierarchical Linear Model). In regard to this methodology, the different hierarchical level of the personal variable and organizational variable was especially focused on, and the effect of interaction between the high level and the low level was considered in detail. Considering the current situation, in that the importance of organizational factor and personal factor has been emphasized but the accurate role of each variable has not been verified, the research model is thought to help to establish an effective strategy to implement 6 Sigma.

• Journal of Power Electronics
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• v.2 no.4
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• pp.250-257
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• 2002

This paper introduces the Interactive Power Electronics Seminar - iPES - a new software package for teaching of fundamentals of power electronic circuits and systems. iPES is constituted by HTML text with Java applets for interactive animation, circuit design and simulation and visualization of electromagnetic fields and thermal issues in power electronics. It does comprise an easy-to-use self-explaining graphical user interface. The software does need just a standard web-browser, i.e. no installations are required. iPES can be accessed via the World Wide Web or from a CD-ROM in a stand-alone PC by students and professionals. Due to the underlying software technology iPES is very flexible and could be used for on-line learning and could easily be integrated into an e-learning platform. The aim of this paper Is to give an introduction to the iPES-project and to show the different areas covered. The e- learning software is available at no costs at $\underline{www.ipes.ethz.ch}$ in English, German, Japanese, Korean, Chinese and Spanish. The project is still under development and the web page is updated in about 4 weeks intervals.

• Korean Medical Education Review
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• v.15 no.1
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• pp.19-24
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• 2013

In medicine, rapid changes in information, technology, socio-economic interests, and globalization affect the medical education focused on the competencies of doctors, and the number of medical schools that are adopting an outcome-based curriculum (OBC) is increasing worldwide. This paper introduces the OBC model of 5 trailblazing medical schools from the UK, US, and Australia, comparing their unique features, followed by brief comment about Canada and the EU as well. On developing an OBC, the process of establishing the top outcomes for graduates is similar and the outcomes comprise knowledge, skills, and attitudes about science, patients, colleagues, society, and themselves. Implementing the outcomes down into the sub-levels of the curriculum is much more complicated and time-consuming. Assessing the achievement of every outcome is essential and requires the use of many tools in addition to the traditional written examination. From the perspective of adult learning theory, self-directed learning, team-learning, and individual and flexible achievement are tested and executed in an OBC. The gradual expansion and further innovation of an OBC is expected so that tomorrow's doctors will be able to meet the challenges of the future.

• Herbal Formula Science
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• v.29 no.4
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• pp.253-266
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• 2021

Objective : This is to analyze the factors affecting the satisfaction of curriculum at korean medicine college and suggest the direction of the curriculum reformation of korean medicine colleges. Method : The collected data were conducted multiple linear regression analysis using the SPSS ver.26 statistical program, using 'curriculum satisfaction' as a dependent variable after analyzing the frequency of each variable. Result : The average score for curriculum satisfaction at Korean Medicine college was 2.87 points, which was relatively low. The factors affecting the satisfaction of the curriculum were 'A favorable impression of Korean Medicine College of W University' β=0.351(p<.001), 'connectivity between major subjects' β=0.312(p<.001), 'duplex between major subjects' β=-0.163(p<.05), 'recognition of the importance of Chinese characters' β=0.114(p<.0.5). Conclusion : The curriculum of Korean Medicine College should first, be organized to allow students to be proud of themselves, second, the goal of education should set goals optimized for job competency, third, the content of learning should be consisted of student led problem based learning, fourth, the link between major subjects should be intensified, fifth, the clinical practice time should be expanded significantly and lastly the assessment evaluates the performance process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.277-283
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• 2018

Some innovative researchers have had a dream of self-thinking intelligent computer. Alphago, at last, showed its possibility. With it, most computer engineers including even students can learn easily how to do it. As the interest to the deep learning has been growing, people's expectation is also naturally growing. In this research, we tried to enhance the game ability of a 7-poker system by applying machine learning techniques. In addition, we also tried to apply emotion analysis of a player to trace ones emotional changes. Methods and outcomes are to be explained in this paper.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.45-53
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• 2019

The purpose of this study is to provide a brief overview of the helicopter pilot training system applied to the Army, and to examine what factors positively affect the successful flight training of helicopter pilots. For this purpose, we analyzed the correlations between various factors such as individual characteristics, selection factors, flight aptitude evaluation, theoretical subjects test, and self-life evaluation. As a result, it was found that only the flight experience was influential on the individual characteristics at the beginning of the training course, and the learning achievement represented by the test of theoretical subjects was positively influenced throughout the flight training course. This reaffirms the fact that an individual's high level of motivation or effort influences his flight training performance. These results are expected to be useful indicators for future development of pilot selection system and pilot training system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.283-284
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• 2019

In the last decades patient's suffering with Parkinson's disease is increasing at a rapid rate and as per prediction it will grow more rapidly as old age population is increasing at a rapid rate through out the world. As the performance of wearable sensor based approach reached to a new height as well as powerful machine learning technique provides more accurate result these combination has been widely used for assessment of various neurological diseases. ON state is the state where the effect of medicine is present and OFF state the effect of medicine is reduced or not present at all. Classification of ON/OFF state for the Parkinson's disease is important because the patients could injure them self due to freezing of gait and gait related problems in the OFF state. in this paper wearable sensor based approach has been used to collect the data in ON and OFF state and machine learning techniques are used to automate the classification based on the gait pattern. Supervised machine learning techniques able to provide 97.6% accuracy while classifying the ON/OFF state.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.546-557
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• 2022

Recently, the demand to interpret image data with artificial intelligence in various fields is rapidly increasing. Object recognition and detection techniques using deep learning are mainly used, and video integration analysis to determine unstructured object recognition is a particularly important problem. In the case of natural disasters or social disasters, there is a limit to the object recognition structure alone because it has an unstructured shape. In this paper, we propose intelligent video integration analysis system that can recognize unstructured objects based on video turning point and object detection. We also introduce a method to apply and evaluate object recognition using virtual augmented images from 2D to 3D through GAN.