• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.129-141
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• 2022

The purpose of this study is to reveal the variables that affect learning immersion, in real-time non-face-to-face classes. To this end, a survey was conducted from November 22, 2021 to December 5, 2021 for students with experience in zoom classes. Excluding incorrect questionnaire, 117 copies were analyzed using a structural equation model. The results show that 'interest' and 'interaction level' influenced 'learning immersion', and 'learning immersion' had a positive effect on 'learning outcome'. The contribution of this study is that it empirically analyzed variables affecting learning immersion in real-time non-face-to-face classes. In the follow-up study, it is necessary to verify variables that affect learning immersion in various platforms, including zoom.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4621-4631
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• 2015

The purpose of this study is to find the grounds for nursing students and teaching professors to confirm the importance of planning and preparing academic careers according to proper time management by determining the learning style exactly for themselves. For this purpose we investigated the learning style and time management behavior of the nursing student in university. The data was collected for 1 months from Nov. 1 to Dec. 2, 2013 in four universities which located in D city and C province. The research tool were used to measure of the learning style, time management behavior and self-directed learning. The participants were 246 nursing students at university who understand the purpose of study and agree to answer it. The data was analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation, stepwise regression using the IBMSPSS/WIN 19.0 program. The result of this study was that the predicting factors for self-directed learning were time management behavior(${\beta}=.629$, p<.001) and adjustment to university life(${\beta}=.153$, p<.001). The variables explained the self-directed learning by 51.4%. This study shows that professors have to encourage students to realize the importance of effective time management for planning, performing and evaluating the academic career for themselves and take into account the related programs about self-directed learning.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.161-169
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• 1997

A variety of learning methods are used for neural networks. Among them, the backpropagation algorithm is most widely used in such image processing, speech recognition, and pattern recognition. Despite its popularity for these application, its main problem is associated with the running time, namely, too much time is spent for the learning. This paper suggests a method which maximize the convergence speed of the learning. Such reduction in e learning time of the backpropagation algorithm is possible through an adaptive adjusting of the slope of the activation function depending on total errors, which is named as the variable slope algorithm. Moreover experimental results using this variable slope algorithm is compared against conventional backpropagation algorithm and other variations; which shows an improvement in the performance over pervious algorithms.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• Journal of KIBIM
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• v.9 no.1
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

• Journal of Ginseng Research
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• v.18 no.1
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• pp.39-43
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• 1994

This study was performed to investigate the effect of ginseng saponin from Korean red ginseng on the learning and memory. Total (50, 100 mg/kg, bw) and panaxadiol saponin (15, 30 mg/kg, bw) treated groups did not show the difference of the time score and the number of error in comparison with control group. Panaxatriol saponin (15, 30 mg/kg, bw) significantly decreased both the time score and the number of error in water maze test. These results indicate that panaxatriol saponin from Korean red ginseng may improve the learning ability of rat in water multiple T-maze.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• Journal of the Ergonomics Society of Korea
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• v.11 no.2
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• pp.47-56
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the fi- nger's reaction time. The model is a logarithmic linear type which represents a lear- ning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can easily computed in the mathematical model. This quantitative approach provieds an important information to be used fot the working capqbility qualification of re-employment as well as the adaptability estimation of aged workers.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.355-360
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• 2021

COVID-19 has brought major changes to school education. Although it was attempted to guarantee students' right to learn through romote learning, the limitations of remote learning compared to face-to-face classes were clear. Nevertheless, the method of remote learning is undoubtedly a learning method that needs to be continuously developed in terms of being able to consider separated time and space and enabling learners to learn individually and autonomously. Therefore, in this study, real-time romote learning cases were analyzed at the elementary school stage, and problems in real-time remote classes were discovered and improved through teacher interviews. The problems with real-time remote classes in elementary school unit classes examined through examples are: First, that the proportion of teacher activity is high due to the anxiety of the unfamiliar environment of remote classes, and second, even though it is a real-time interactive class, it It was impossible to provide feedback. As a solution to this, it is necessary to consider the basic class steps (introduction-deployment-organization) and the use of class tools to provide appropriate communication and feedback was suggested.