• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.109-117
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• 2006

E-learning method has many advantages that supplement the shortfalls of offline education. For this reason, today's offline educational institutions adopted the online education technique to improve learning effectiveness. Recently, general universities have partially adopted online learning. As a result, a study is searching for ways to improve the effectiveness of education by copying the merits of the existing offline education onto the online education. Thus a proper evaluation of learners and a feedback provision are considered necessary to improve the effectiveness of online learning. This study aims to suggest a model that will improve learning efficiency by adapting the advantages of offline education to online learning. To evaluate properly, this study conducted Item Response Test to examine the learners and finally ensure them an adequate level of education. Also, this study suggested a way to enhance learning efficiency by finding out each learner's study habits and to address the weaknesses of online learning. It is expected that the suggested method would be helpful in bettering learner's ability to study in school environment.

• Journal of Elementary Mathematics Education in Korea
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• v.11 no.2
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• pp.161-176
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• 2007

It is useless to say that time is precious and important. So it does when we emphasize the importance of studying the quality and efficiency of time in learning, especially in the learning of Mathematics. In this respect, this study aims to examine the overall structure of time application in the learning of Mathematics, understanding the state and problems of Mathematics education in respect of time application, and finally seeking to find the solutions for the problems. As a first step, the items below were examined for the solutions: First, the eight viewpoints of time in Mathematics education was examined and the meaning of each viewpoint was analysed. Second, the variables resulting from teachers was examined. The preconditions for mathematics education, the attitude towards Mathematics classes, viewpoints of mathematics, the forms of self-expression, the way of utterance can be considered as the variables mentioned above. Third, the variables resulting from students was examined. Learning attitude, specific activity(both meaningful and meaningless), practical uses of teaching tools, game activities, the ways of communication and problem solving can be examined as well. In conclusion, it needs to be stressed that Mathematics class should be the meaningful time for learners, parents, and teachers. The class should guarantee the satisfaction of the learners. In other words, even if physical time is applied the same to everyone, it may differ in degree of quality and value of time application according to the way one spends the time.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.5
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• pp.407-415
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• 2016

Recent wireless communication trends have emphasized the importance of energy-efficient transmission. In this paper, link adaptation with machine learning mechanism for maximum energy efficiency in multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) wireless system is considered. For reflecting frequency-selective MIMO-OFDM channels, two-dimensional capacity(2D-CAP) feature space is proposed. In addition, machine-learning-based bit and power adaptation(ML-BPA) algorithm that performs classification-based link adaptation is presented. Simulation results show that 2D-CAP feature space can represent channel conditions accurately and bring noticeable improvement in link adaptation performance. Compared with other feature spaces, including ordered postprocessing signal-to-noise ratio(ordSNR) feature space, 2D-CAP has distinguished advantages in either efficiency performance or computational complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.213-214
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• 2017

This study was conducted to analyze the relevant of the self-regulated learning capability and learning effectiveness based on the type of e-learning contents and learner's preference, academic achievement according to enhancement of K-MOOC. The results of this study will present the effectiveness of e-learning contents type, and expect to suggest to develop effective contents type for various courses.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.169-180
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• 2021

Since machine learning was invented, there have been many different machine learning-based algorithms, from shallow learning to deep learning models, that provide solutions to the classification tasks. But then it poses a problem in choosing a suitable classification algorithm that can improve the classification/detection efficiency for a certain network context. With that comes whether an algorithm provides good performance, why it works in some problems and not in others. In this paper, we present a data-centric analysis to provide a way for selecting a suitable classification algorithm. This data-centric approach is a new viewpoint in exploring relationships between classification performance and facts and figures of data sets.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.420-426
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• 2022

Developing a machine learning model and putting it into production goes through a number of steps. Automated Machine Learning(AutoML) appeared to increase productivity and efficiency by automating inefficient tasks that occur while repeating this process whenever machine learning is applied. The high degree of automation of AutoML models allows non-experts to use machine learning models and techniques without the need to become machine learning experts. Automating the process of applying machine learning end-to-end with AutoML models has the added benefit of creating simpler solutions, generating these solutions faster, and often generating models that outperform hand-designed models. In this paper, the AutoML data is collected and AutoML's Color Petri net model is created and analyzed based on it.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.91-99
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• 2024

In this paper, machine learning models were applied to predict the seismic response of steel frame structures. Both geometric and material nonlinearities were considered in the structural analysis, and nonlinear inelastic dynamic analysis was performed. The ground acceleration response of the El Centro earthquake was applied to obtain the displacement of the top floor, which was used as the dataset for the machine learning methods. Learning was performed using two methods: Decision Tree and Random Forest, and their efficiency was demonstrated through application to 2-story and 6-story 3-D steel frame structure examples.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2614-2616
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• 2002

According to the appearance of various virtual websites using multimedia technologies for engineering education, the internet applications in engineering education have drawn much interests. But unidirectional communication, simple text/image based webpages and tedious learning process without motivation etc. have made the lowering of educational efficiency in cyberspace. Thus, to cope with these difficulties this paper presents a web-based educational Flash movies based on ActionScript language for understanding the principles of the computer system architecture. The proposed Flash movies provides the improved learning methods which can enhance the interests of learners. The results of this paper can be widely used to improve the efficiency of cyberlectures in the cyber university. Several sample Flash movies are illustrated to show the validity of the proposed learning method.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2490-2492
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• 2001

According to the appearance of various virtual websites using multimedia technologies for engineering education, the internet applications in engineering education have drawn much interests. But unidirectional communication, simple text/image-based webpages and tedious learning process without motivation etc. have made the lowering of educational efficiency in cyberspace. Thus, to cope with these difficulties this paper presents a web-based educational Java applets for understanding the principles or conceptions of digital logic systems. The proposed Java applets provides the improved learning methods which can enhance the interests of learners. The results of this paper can be widely used to improve the efficiency of cyberlectures in the cyber university. Several sample Java applets are illustrated to show the validity of the proposed learning method.

• Computers and Concrete
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• v.30 no.1
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• pp.33-42
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• 2022

Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a time-consuming and laborious process. The present study aims to propose surrogate models based on Support Vector Machine (SVM) and Gaussian Process Regression (GPR) machine learning techniques, which can predict the CS of concrete containing nano-silica. Content of cement, aggregates, nano-silica and its fineness, water-binder ratio, and the days at which strength has to be predicted are the input variables. The efficiency of the models is compared in terms of Correlation Coefficient (CC), Root Mean Square Error (RMSE), Variance Account For (VAF), Nash-Sutcliffe Efficiency (NSE), and RMSE to observation's standard deviation ratio (RSR). It has been observed that the SVM outperforms GPR in predicting the CS of the concrete containing nano-silica.