• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.9-19
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• 2013

In this paper, we develop a Spatio-Temporal graph as of a key component of our knowledge representation Scheme. We design an integrated representation scheme to depict not only present and past but future in parallel with the spaces in an effective and intuitive manner. An event in general occupies not only a space but a time. Hence a crucial premise for the simulation of virtual situations is to position events in the multi-dimensional context, that is, 3-D space extended by the temporal dimension. Furthermore an event tends to have physical, social and mental aspects intertwined. As a result we need diverse information structures and functions to model entities and relations associated with events and to describe situations in different stances or perspectives of the virtual agents. These structures and functions are implemented in terms of integrated and intuitive representation schemes at different levels such as Ontology View, Instance View, ST View, Reality View. The resulting multi-dimensional comprehensive knowledge structure accommodates multi-layered virtual world developing in the time to maximize the diversity of situations in the historical context. The viability of this knowledge representation scheme is demonstrated with a typical scenario applied to a simulator implemented based on the ST Graph. The virtual stage based on the ST graph can be used to provide natural contexts for situated learning or next-generation simulation games.

• Journal of Digital Contents Society
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• v.18 no.7
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• pp.1313-1321
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• 2017

In the future society where ICT-based digital convergence creates new value, collaborative skills among experts in various fields and SW based problem solving ability is more emphasized. Non-SW specialists are required to have SW based communication skills to effectively collaborate with SW experts to solve their problems. Therefore, SW programming curriculum for non-major college students should be different from the existing programming education for SW-majors aiming at a high level of coding ability. It is also known that diagram-based visual representation is helpful for productive communication and collaboration. In this study, we defined the SW education objectives for the non-majors as cultivating the visual programming ability for SW based problem solving. In order to accomplish this, we explored SW programming curriculum and content development model for non-majors focusing on visual representation of SW solutions. The results of this paper will help to provide appropriate SW learning model for non-majors and to cultivate practical SW capabilities.

• Journal of the Korean Chemical Society
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• v.67 no.4
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• pp.241-252
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• 2023

This study aims to increase students' understanding of equilibrium, one of the many concepts in chemistry that students find difficult. Dynamic equilibrium must be dealt with at the sub-microscopic level where the real and the representation overlap in order to microscopically understand the constant motion and interaction of particles and to understand the macroscopic characteristics expressed through this. However, as a result of analyzing 9 Chemistry I textbooks, the expression approach for equilibrium had some limitations. As a strategy to understand equilibrium at a sub-microscopic approach, the classes using scratch were consisted of a total of 4 hours, and it was implemented with 56 students. The classes were composed of 6 steps, and it was designed to understand equilibrium step by step. As a result of comparing the pretest and post- test, the number of students who got both the microscopic and macroscopic explanations of chemical equilibrium correct increased largely. Through this, it was possible to get a glimpse of the applicability of classes using scratch as the approach strategy of the sub-microscopic representation.

• Journal of the Korean School Mathematics Society
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• v.23 no.3
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• pp.277-297
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• 2020

The purpose of this study is to understand how the shift of the Pythagorean theorem influenced the representation of irrational numbers in the 3rd grade textbook of 2015 revised mathematics curriculum by textbook analysis. Specifically, the changes in the representation of irrational numbers were examined in two aspects based on the nature of irrational numbers and the teaching and learning methods of the 2015 revised mathematics curriculum. First, we analyzed the learning opportunities related to the existence of irrational numbers that were potentially provided by treating irrational numbers as geometric representations in textbooks, and confirmed that Pythagorean theorem was used. Next, we analyzed opportunities to recognize the necessity of irrational numbers provided by numerical representations of irrational numbers. This study has significance in that it confirmed the possibility and limitation of learning opportunities related to the existence and necessity of irrational numbers that were potentially provided by changes in irrational number representations in the 2015 revised textbooks.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.433-450
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• 2012

As a worker performs a certain operation repeatedly, he tends to become familiar with the job and complete it in a very short time. That means that the efficiency is improved due to his accumulated knowledge, experience and skill in regards to the operation. Investing time in an output is reduced by repeating any operation. This phenomenon is referred to as the learning curve effect. A learning curve is a graphical representation of the changing rate of learning. According to previous literature, learning curve effects are determined by subjective pre-assigned factors. In this study, we propose a new statistical model to clarify the learning curve effect by means of a basic cumulative distribution function. This work mainly focuses on the statistical modeling of binary data. We employ the Newton-Raphson method for the estimation and Delta method for the construction of confidence intervals. We also perform a real data analysis.

• Communications of Mathematical Education
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• v.29 no.4
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• pp.589-623
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• 2015

This study is to find out a way to foster self-directed learning math skills for the low-income youth at child care centers. Taking advantage of EBS materials, we found the youth, low-income youth in particular, were positively influenced to learn mathematics in the way of self-directed and action learning. This program gives a model of the self-directed math learning using the EBS mathematics materials. From the survey of this study, we found see that students started to have a positive attitude for learning and they started to gain new mathematical concept, and improved their problem solving, reasoning, communication and representation skills with these new leaning environments. This study tells us that this type of cooperative learning could help them to have an objective assessment, and gave a positive impact on self-directed learning.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.249-259
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• 2006

E-learning objects should be appropriately described and classified using standard metadata for facilitating the processes of e-learning resource description, discovery and reuse. These metadata need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE LOM is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML information model is proposed. The usefulness of standard ebXML registries for sharing e-learning metadata is demonstrated by prototyping an e-learning registry called ebRR4LOM based on the scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.13-21
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• 1996

The necessity and usefulness of higher-order neural networks have been well-known since early days of neurocomputing. However the explosive number of terms has hampered the design and training of such networks. In this paper we present an evolutionary learning method for efficiently constructing problem-specific higher-order neural models. The crux of the method is the neural tree representation employing both sigma and pi units, in combination with the use of an MDL-based fitness function for learning minimal models. We provide experimental results in classification and prediction problems which demonstrate the effectiveness of the method. I. Introduction topology employs one hidden layer with full connectivity between neighboring layers. This structure has One of the most popular neural network models been very successful for many applications. However, used for supervised learning applications has been the they have some weaknesses. For instance, the fully mutilayer feedforward network. A commonly adopted connected structure is not necessarily a good topology unless the task contains a good predictor for the full *d*dWs %BH%W* input space.

• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.754-759
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• 2007

Methodology of ontology building based on Web resources will not only reduce significantly the ontology construction period, but also enhance the quality of the ontology. Remarkable progress has been achieved in this regard, but they encounter similar difficulties, such as the Web data extraction and knowledge acquisition. This paper researches on the characteristics of ontology construction data, including dynamics, largeness, variation and openness and other features, and the fundamental issue of ontology construction - formalized representation method. Then, the key technologies used in and the difficulties with ontology construction are summarized. A software Model-OntoMaker (Ontology Maker) is designed. The model is innovative in two regards: (1) the improvement of generality: the meta learning machine will dynamically pick appropriate ontology learning methodologies for data of different domains, thus optimizing the results; (2) the merged processing of (semi-) structural and non-structural data. In addition, as known to all wetland researchers, information sharing is vital to wetland exploitation and protection, while wetland ontology construction is the basic task for information sharing. OntoMaker constructs the wetland ontologies, and the model in this work can also be referred to other environmental domains.

• Journal of the Korean Society of Radiology
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• v.10 no.8
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• pp.637-643
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• 2016

Due to the popularity of artificial intelligent, medical image processing using artificial neural network is increasingly attracting the attention of academic and industry researches. Deep learning with a convolutional neural network has been proved to very effective representation of images. However, the training process requires high performance H/W platform. Thus, the realtime learning of a large number of high dimensional samples within low-power devices is a challenging problem. In this paper, we attempt to establish this possibility by presenting a realtime neural network method on Raspberry pi using online sequential extreme learning machine. Our experiments on high-dimensional dataset show that the proposed method records an almost real-time execution.