• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.293-307
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• 2004

The SMIL(Synchronized Multimedia Integration Language) documents are represented as logical structure information, spatial layout structure information, temporal synchronization structure information and hyperlink structure information, according as the structural characteristics of SMIL documents based on XML. This paper proposes the effective modeling and query method for the multi -structure information of inherent SMIL documents. In particular, we present the object-oriented modeling by using UML class diagram in order to represent the objects classes for the structured information of SMIL documents, and the hierarchical structure and the relationships for the objects classes. In addition, the objects classes definition is specified in compliance with SQL3 for database standard language. We also propose the access method and the query representation for hierarchical structure in order to retrieve efficiently the structural objects of SMIL documents.

• The Mathematical Education
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• v.57 no.4
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• pp.393-412
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• 2018

Teacher quality is a key factor that determines quality of education. Being aware of this, the Korean government and teachers have been striving to improve teachers' professionalism. Research about the impacts of efforts to enhance teacher professionalism on students' academic achievement and course satisfaction, however, is extremely limited. This study sought to advance our understanding of the relationship between these factors by analyzing what teacher characteristics impact students' achievement and satisfaction. To this end, the study drew on the middle and high school data from 3rd to 6th year survey of the Seoul Educational Longitudinal Study. Structural equational modeling were used as the main approach. Latent profile analysis, a kind of mixture modeling analysis, were used as needed. This study found that teachers' participation in instruction enhancement activity and professional development impact students' attitude toward mathematics lessons and their perception on class atmosphere, and ultimately impact their academic achievement as well as their overall satisfaction in the course. In addition, teachers' use of EBS textbooks and videos impact 3rd grade high schoolers' academic achievement. These findings suggest that effort to improve teacher professionalism positively impact students' academic achievement and course satisfaction, although there is a difference according to the year grade. This study provides implications for education policy makers and teacher educators.

• IE interfaces
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• v.10 no.3
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• pp.11-21
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• 1997

The communication between members who participate in the product development project has an effect on the project time, cost, and quality. This reason requires the engineering database which is the kernel of product information. This study focuses on data and process modeling for engineering database related to electronic consumer product. First, Through the definition of engineering database, the characteristics of engineering data, mainly product data are analyzed. Second, The object and class for engineering database are defined. This results of the study can be applied with engineering database design and workflow design of PDM. It also can be used as a reference model when the company develops product with suppliers.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5568-5587
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• 2018

This research uses artificial intelligence methods for computer network intrusion detection system modeling. Primary classification is done using self-organized maps (SOM) in two levels, while the secondary classification of ambiguous data is done using Sugeno type Fuzzy Inference System (FIS). FIS is created by using Adaptive Neuro-Fuzzy Inference System (ANFIS). The main challenge for this system was to successfully detect attacks that are either unknown or that are represented by very small percentage of samples in training dataset. Improved algorithm for SOMs in second layer and for the FIS creation is developed for this purpose. Number of clusters in the second SOM layer is optimized by using our improved algorithm to minimize amount of ambiguous data forwarded to FIS. FIS is created using ANFIS that was built on ambiguous training dataset clustered by another SOM (which size is determined dynamically). Proposed hybrid model is created and tested using NSL KDD dataset. For our research, NSL KDD is especially interesting in terms of class distribution (overlapping). Objectives of this research were: to successfully detect intrusions represented in data with small percentage of the total traffic during early detection stages, to successfully deal with overlapping data (separate ambiguous data), to maximize detection rate (DR) and minimize false alarm rate (FAR). Proposed hybrid model with test data achieved acceptable DR value 0.8883 and FAR value 0.2415. The objectives were successfully achieved as it is presented (compared with the similar researches on NSL KDD dataset). Proposed model can be used not only in further research related to this domain, but also in other research areas.

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.203-216
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• 2020

The purpose of this study is to explore the effects of a VR(virtual reality)-based biology class on both the cognitive and affective domains by developing and applying a VR-based biology program for 6th-grade elementary school students. For this research, we developed a VR teaching material about 'digestion' reflecting virtual reality characteristics and one hundred five students in an elementary school in an urban area participated in this study and took three VR-based lessons. To examine the cognitive effects of a VR-based biology class, the study subjects were divided into two groups. The experimental group was composed of 50 individuals who participated in VR-based biology lessons, while 55 students of a control group learned through general lessons. We collected data using drawing tasks for measuring students' modeling performance level from these groups and analyzed the cognitive effect of VR-based instruction. We also recorded 21 interviews of students after the intervention, which were transcribed to verify the students' perception of cognitive and affective effects. The key results are as follows: First, we demonstrated the possibility of applying a VR program reflecting VR characteristics (manipulation, multi-sensory, and interaction). Second, we found out that a VR-based biology class significantly enhances higher levels of thinking (spatial, abstract, and reflective thinking). Third, we examined students' perceptions on this program and came to the conclusion that VR characteristics positively affected cognitive and affective domains. This study may be able to contribute to offering guidelines on how to apply VR-programs to future science education effectively.

• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.23-32
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• 2007

Nowadays, XML has been favored by many companies internally and externally as a means of sharing and distributing data, due to its open-architectural structure. XML-GL, a graphical query language for document has the advantage of containing both structuring and defining of itself. By incorporating UML an XML document can become object-oriented and can be represented by graphical means. This paper proposes a XML-GL query modeling solution by using UML class diagrams. In order for the modeled objects to be properly restricted, the Object Constraint Language has been defined. This process converts XML documents into Object-Oriented data and combined with UML class diagrams, searches for XML documents can be increased.

• Journal of The Korean Digital Architecture Interior Association
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• v.6 no.2
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• pp.25-30
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• 2006

The purpose of this study was to investigate how student felt the strengths and shortness of presentation methods for formation of interior spaces. For this study, the process of the interior architecture design class was divided into three stages: the programming. the design development, and the design completion. In the design development stage, students used presentation methods: hand sketch, scale model, computer modeling, and virtual realty. The strengths of hand sketch was that quick expression. Models provided three-dimensional feelings. Computer modelling provide realistic color and texture. Virtual reality provided three-dimensional immersion and real scale. It is effective that students collect brain storm images using quick hand sketch in the beginning of design development stage. After that, they compose interior spaces in study models with small scale. Watching the models, they design details of spaces by using hand sketch and computer modelling. Using virtual reality, they can check the scale and circulation. Finally, they complete computer modelling by texture mapping and check the final design in virtual reality.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.04a
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• pp.274-283
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• 2002

This paper presents an efficient models for reinforeced concrete structures using CART-ANFIS(classification and regression tree-adaptive neuro fuzzy inference system). a fuzzy decision tree parttitions the input space of a data set into mutually exclusive regions, each of which is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the Predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it everywhere continuous and smooth. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.115-125
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• 2018

The one of goals of the 2015 revised national curriculum is the successful application of achievement standards-based assessment, which assesses both the results and process of learning, ensuring that all students have achieved the educational objectives, to schools. Therefore, an achievement standards and evaluation support system is required to manage a whole process of teaching and learning based on achievement standards and provide the personalized assessment feedback to students to improve their achievement levels. In this paper, we perform a design of integrated data model and system of teaching plan, subject content, assessment plan, assessment result, and feedback data is required based on an achievement standards repository. In addition, we create a student's dashboard webpage, which representing different types of achievement of the student, and perform the comparative analysis of data models to evaluate the quality of the proposed model.